Proceedings / Actes Volume 29, Division 9, 2008 - Index of

Annual Conference of the Administrative Sciences Association of Canada 

Congrès annuel de l’Association des sciences administratives du Canada 

ASAC 2008 

Proceedings / Actes Volume 29, Division 9, 2008 

Human Resources/ Ressources Humaines 

Edited by/ Édités par 

Zhenzhong Ma, Ph.D. 

Odette School of Business 

University of Windsor 

Selected Papers / Textes choisis 

Halifax, Nova Scotia May 24-27, 2008 / 24 au 27 mai, 2008

ACKNOWLEDGEMENTS 

I would like to thank every author who 

submitted papers and symposium proposals to 

the HR Division. 

I would also like to thank the reviewers for their 

great work. Their efforts were remarkable and 

their valuable comments will no doubt help the 

authors in their research. 

Thanks to Francine Schlosser, Division Chair, 

and Sean Lyons, Division Program Chair, for 

their suggestions and guidance during the 

preparations for ASAC 2008. 

Finally, I would like to thank all the colleagues 

who volunteered to serve as Discussant and 

Chair during the various conference sessions. 

Zhenzhong Ma 



REMERCIEMENTS 

Je tiens à remercier tous les auteurs qui ont 

présenté des documents et des propositions au 

colloque de la Division des ressources humaines. 

Je tiens également à remercier les 

commentateurs pour leur excellent travail. Leurs 

efforts ont été remarquables et de leurs 

précieuses observations vont sans doute aider les 

auteurs dans leur recherche. 

Grâce à Francine Schlosser, président de la 

division, et Sean Lyons, Division Programme 

président, pour leurs suggestions et conseils au 

cours de la préparation de l'ASAC 2008. 

Enfin, je tiens à remercier tous les collègues qui 

se sont portés volontaires pour servir en tant que 

commentateur et président pendant les 

différentes sessions de la conférence. 

Zhenzhong Ma 


University of Windsor

REVIEWERS / ÉVALUATEURS 

Marjorie Armstrong-Stassen University of Windsor 

Christa L. Austin McMaster University 

Nicole Bérubé Concordia University 

Akanksha Bedi McMaster University 

Travor C. Brown Memorial University 

Nita Chhinzer University of Guelph 

Inta Cinite Carleton University 

Julie Cloutier Université du Québec à Montréal 

Michel Cossette Université du Québec à Montréal 

Rocky Dwyer Department of National Defence 

Janice Foley University of Regina 

Ivona Hideg University of Toronto 

Jack Ito University of Regina 

Scott Jeffrey University of Waterloo 

Mark Julien Brock University 

Linda Keup Concordia College 

Theresa J. Kline University of Calgary 

Ivy Kyei-Poku University of Western Ontario 

Richard Lacoursière Université du Québec à Trois-Rivières 

Marian Luncasu HEC Montréal 

Sean Lyons University of Guelph 

Pamela Mathews Charles Sturt University 

Morris B. Mendelson University of New Brunswick 

Marc S. Mentzer University of Saskatchewan 

Denis Morin Université du Québec à Montréal 

Peter Mudrack Kansas State University 

Floyd Ormsbee Clarkson University 

Mark Podolsky McMaster University 

Chet Robie Wilfrid Laurier University 

Joel Rudin Rowan University 

Hermann Schwind Saint Mary’s University 

Geoffrey Smith University of Guelph 

Thomas S. Stone Oklahoma State University 

Rick Tallman University of Northern British Columbia 

Andrew Templer University of Windsor 

Michel Tremblay HEC Montréal 

Jean M. Trudel Université de Sherbrooke 

Yoshio Yanadori University of British Columbia 

2

TABLE OF CONTENTS / TABLE DES MATIÈRES 

The Relationship of Work Status (In)Congruency with Perceived Employer Commitment 

and Commitment of Community Health Nurses ………………………………………….... 6 

Seung Hwan (Mark) Lee (University of Western Ontario) 

Marjorie Armstrong-Stassen (University of Windsor) 

Sheila J. Cameron (University of Windsor) 

Do firm compensation strategies matter to all employees? The scope of firm compensation 

strategies in high technology firms ………………………………………………………….. 25 

Yoshio Yanadori (University of British Columbia) 

Can the diversity literature help business schools address their relevance crisis? …….… 40 

Janice Foley (University of Regina) 

The Influence of Training Transfer Climate and Individual Trainee Characteristics on 

Customer Orientation ………………………………………………………………………... 54 

Christopher Perryer (University of West Australia) 

Steven McShane (University of West Australia) 

Disaggregating Unemployment: Job Leavers, Losers and Layoffs …………………….… 74 

Nita Chhinzer (University of Guelph) 

Khaldoun Ababneh (McMaster University) 

Do Employees Profit from Profit Sharing? A Longitudinal Analysis of Canadian 

Establishments ………………………………………………………………………………. 91 

Richard Long (University of Saskatchewan) 

Tony Fang (York University) 

HONOURABLE MENTION – MENTION HONORABLE 

Explaining Chronological and Subjective Age Differences in Job Satisfaction …………. 111 

Nicole Berube (Concordia University) 

BEST PAPER – MEILLEURE COMMUNICATION 

Are Reactions to Feedback the Mediating Link Between Feedback and Performance?... 125 

I. M. Jawahar (Illinois State University) 

3

ABSTRACTS / RÉSUMÉS 

Leadership and Creativity: The Mediating Effects of Intrinsic Motivation, Domain- 

Relevant Skills, and Creativity-Relevant Processes …………………………………… 150 

Mardi Witzel (Wilfrid Laurier University) 

Who receives a performance appraisal and does it matter? An empirical investigation of 

the determinants of the receipt of a performance appraisal and its effect on job satisfaction 

…………………………………………………………………………………………….. 150 

Sara L. Mann (University of Guelph) 

Gary Latham (University of Toronto) 

Strategic Responsiveness within an IMSA Framework- Institutional and Resource Based 

Perspectives ………………………………………………………………………………. 151 

Saba Sharih (Wilfrid Laurier University) 

Simon Taggar (Wilfrid Laurier University) 

Recruiters’ perceptions of applicants’ volunteer experience: Are all volunteer assignments 

equally relevant? ………………………………………………………………………… 151 

Christa L. Austin (McMaster University) 

Catherine E. Connelly (McMaster University) 

Barriers to Transfer: Participant’s Perspective: Preliminary Results ………………. 152 

Travor C. Brown (Memorial University) 

Martin McCracken (University of Ulster) 

Sergio De Leon (Memorial University) 

Serious Threats to Canadian University Faculty Members –Survey Outcomes ……. 152 

Sunny Marche (Dalhousie University) 

John F. Duffy (Dalhousie University) 

Geneviève Perron (Dalhousie University) 

A Statistical Investigation of Antecedents and Outcomes of Job-Related Stress for Teachers 

…………………………………………………………………………………………….. 153 

James Doyle (University of Carlton) 

Alia El Banna (University of Carlton) 

Linda Duxbury (University of Carlton) 

Chris Higgins (University of Carlton) 

Exploring Faking in the Context Of Multi-Stage Selection Systems ………………… 153 

Shawn Komar (University of Waterloo) 

Douglas J. Brown (University of Waterloo) 

Chet Robie (Wilfrid Laurier University) 

4

Political Skill: A Meta–Analysis of Its Predictors and Outcomes ……………….…… 154 

Akanksha Bedi (McMaster University) 

Mark S. Skowronski (McMaster University) 

Aaron C. H. Schat (McMaster University) 

Exploring the relationship between organizational culture and Quit behaviour: Evidence 

from Canadian call centers ……………………………………………………………... 154 

Wendy R. Carroll (Saint Mary’s University) 

Terry H. Wagar (Saint Mary’s University) 

Kent V. Rondeau (University of Alberta) 

Developments in Canadian Employment Law and the Supreme Court of Canada: Evidence 

from an Examination of Reasonable Notice in the Wrongful Dismissal Common Law 

………………………………………………………………………………………….… 155 

Jim D. Grant (Nipissing University) 

Terry H. Wagar (Saint Mary’s University) 

5

ASAC 2008 Seung Hwan (Mark) Lee (Student) 

Halifax, Nova Scotia Ivey School of Business 

University of Western Ontario 

Marjorie Armstrong-Stassen 



Sheila J. Cameron 

Faculty of Nursing 


THE RELATIONSHIP OF WORK STATUS (IN)CONGRUENCY WITH PERCEIVED EMPLOYER 

COMMITMENT AND COMMITMENT OF COMMUNITY HEALTH NURSES 

Using a social exchange framework, we examined the relationship of work status 

(in)congruency with organization-specific and job-specific aspects of perceived 

employer commitment and with nurses’ commitment to their organization, to 

their job, and to their profession. The participants were 1,230 female nurses 

employed in community health agencies in Canada. Part-time nurses preferring 

full-time work perceived greater job insecurity and lack of access to development 

opportunities, but reported the highest level of commitment to their organization 

and profession. Full-time nurses preferring part-time work perceived less 

organizational support, reported lowest level of meaning empowerment, affective, 

normative, and professional commitment, but reported greatest continuance 

commitment. 

Work status congruency occurs when a person’s current work status (full-time or part-time) 

matches their preference for work status (prefers to work full-time or prefers to work part-time). Work 

status incongruency occurs when a person’s work status is inconsistent with the person’s preferred work 

status, i.e., the person is working full-time but prefers to work part-time or the person is working parttime 

but prefers to work full-time. Work status (in)congruency has been shown to be significantly related 

to employee attitudes and well-being including job satisfaction (Armstrong-Stassen, Al-Ma’aitah, 

Cameron & Horsburg, 1998; Armstrong-Stassen, Horsburgh & Cameron, 1994; Barker, 1993; Burke & 

Greenglass, 2000; Holtom, Lee & Tidd, 2002; Keil, Armstrong-Stassen, Cameron & Horsburgh, 2000; 

Krauz, Sagie & Biderman, 2000), organizational commitment (Holtom et al., 2002; Krauz et al., 2000), 

turnover intent and voluntary turnover (Armstrong-Stassen et al., 1994, 1998; Burke & Greenglass, 2000; 

Holtom et al., 2002), in-role and extra-role performance (Holtom et al., 2002), burnout (Armstrong- 

Stassen et al., 1994, 1998; Burke & Greenglass, 2000; Krauz et al., 2000), absenteeism (Burke & 

Greenglass, 2000), and psychosomatic and physical health symptoms (Burke & Greenglass, 2000). These 

studies have generally supported the prediction that employees with an incongruent work status would 

exhibit more negative attitudes toward their organization and their job and report poorer well-being than 

employees with a congruent work status. 

Much of the research to date has investigated the relationship of work status (in)congruency 

across a wide variety of employee attitudes within an individual study. The present study differs from 

previous studies by focusing specifically on the relationship between work status (in)congruency and 

commitment. The purpose of our study was to examine the influence of work status (in)congruency on 

two aspects of commitment: perceived commitment from the organization to its employees and 

employees’ commitment to their organization, to their job, and to their profession. We examined two 

sources of perceived commitment from the organization to the employee: organizational practices at the 

organizational-level (perceived organizational support, perceived fair treatment, perceived job security, 

6

and perceived development opportunities) and organizational practices associated with the employee’s 

job (job challenge, job autonomy, and empowerment). 

Consistent with many of the previous studies investigating work status or work status congruency, 

our study was also conducted with nurses. However, unlike previous studies, the nurses in our study were 

employed in community health agencies and not in hospitals. Nurses are an appropriate population for 

the study of part-time workers because of the large number of nurses who work part time (Armstrong- 

Stassen et al., 1998). The part-time employment rate of registered nurses (RNs) in Canada is 

approximately 30% of all RNs employed in the healthcare sector (Pyper, 2004). About one in five of 

those nurses working part time are not doing so by choice, i.e., they would prefer to work full time. 

The conceptual framework (see Figure 1) employed in this study is based on the social exchange 

theory and the norm of reciprocity (Blau, 1964; Gouldner, 1960). Employees will be willing to show 

greater commitment to their organization only when they perceive their organization has demonstrated its 

commitment to them. We propose that various organizational practices, such as allowing employees to 

work their preferred work status, will be perceived by employees as evidence of organizations 

demonstrating commitment. In turn, employees will reciprocate by showing greater commitment to their 

organization, job, and profession. Conversely, if organizational practices do not address employees’ 

needs and preferences, employees will perceive that their organization is not committed to them. In this 

case, employees will feel less obligated to commit to their organization, job, and profession. 

FIGURE 1 

CONCEPTUAL FRAMEWORK 

Work Status (In)Congruency and Perceived Commitment from the Organization 

An organization can demonstrate its commitment to its employees in a variety of ways. Our 

study focused on organizational actions at the organizational-level (caring and support for employees, 

treating employees fairly, providing job security, and ensuring opportunities for career development) and 

also at the job-level (providing job challenge, autonomy, and sense of empowerment). We propose that 

nurses whose work status is congruent (working full-time and prefer to work full-time or working parttime 

and prefer to work part-time) will perceive that their organization has demonstrated significantly 

more commitment to them than those nurses whose work status is incongruent (working full-time but 

prefer to work part-time or working part-time but prefer to work full-time). 

7

Perceived organizational support underlies the social exchange between employees and their 

organization (Eisenberger, Huntington, Hutchison & Sowa, 1986; Gakovic & Tetrick, 2003). Perceived 

organizational support is the general belief that the organization cares about its employees, values their 

contribution, and is committed to them (Eisenberger et al., 1986). In a recent study investigating the 

mismatch in working hours, van Emmerik and Sanders (2005) recommended that future research consider 

perceived organizational support and other components of organizational commitment. In their 

recommendations for future research, Stamper and Van Dyne (2001) noted that perceived organizational 

support may be a key link between work status and employee attitudes and behavior. However, we found 

only one published study that has examined the relationship between work status congruency and 

perceived organizational support. Armstrong-Stassen et al. (1998) found that Canadian nurses working 

full-time but preferring to work part-time in four hospitals that had undergone a recent amalgamation 

tended to report lower perceived organizational support than the other three groups but the difference was 

not significant. All four groups of nurses, including those with a congruent work status, reported 

relatively low levels of perceived organizational support suggesting that any significant differences across 

the work status groups may have been overridden by the downsizing of the nursing staff that accompanied 

the amalgamation. 

We suggest nurses will perceive organizations as not caring and not committed to them if they 

experience a mismatch in their preferred working hours. We therefore predicted that full-time nurses who 

preferred to work full-time and part-time nurses who preferred to work part-time would report 

significantly higher levels of perceived organizational support than full-time nurses who preferred to 

work part-time and part-time nurses who preferred to work full-time. 

Hypothesis 1a: Nurses with a congruent (FT/FT, PT/PT) work status will perceive significantly 

higher levels of organizational support than nurses with an incongruent (FT/PT and PT/FT) work 

status. 

There has also been little research on how work status congruency influences employees’ 

perceptions of fair treatment. Some researchers (Feldman, Leanna & Turnley, 1997; Tansky, Gallagher & 

Wetzel, 1997) speculated part-time workers to perceive that they are treated less fairly than full-time 

workers. Feldman and Doerpinghaus (1992) found that nurses working part-time did express some 

concerns about being treated less fairly. This may especially be true for part-time nurses who desire fulltime 

status. These nurses may perceive that they receive fewer rewards and less recognition than fulltime 

nurses. We therefore predicted that part-time nurses who preferred to work full-time would perceive 

that they are treated less fairly than full-time nurses who preferred full-time work and full-time nurses 

who preferred part-time work. 

Hypothesis 1b: Part-time nurses who prefer to work full-time (PT/FT) will perceive they are 

treated significantly less fairly than full-time nurses who prefer to work full-time (FT/FT) and 

full-time nurses who prefer to work part-time (FT/PT). 

Part-time jobs in general are associated with greater job insecurity than full-time jobs 

(Schellenberg, 1997). When compared with full-time workers, part-time workers have been shown to be 

less satisfied with their job security (Levanoni & Sales, 1990) and at greater risk of being laid off (Barker, 

1993; McDonald & Wanner, 1992). There is some empirical evidence that part-time nurses who prefer 

full-time employment have the greater perceived job insecurity than nurses with a congruent work status 

(FT/FT or PT/PT) and full-time nurses who prefer to work part-time (Armstrong-Stassen et al., 1994; 

Burke & Greenglass, 2000; Keil et al., 2000). We therefore expected that community health nurses who 

were working part-time but preferred to work full-time would perceive significantly less job security than 

nurses with a congruent work status and full-time nurses who preferred part-time employment. 

8

Hypothesis 1c: Nurses working part-time but preferring full-time work (PT/FT) will perceive 

significantly lower job security than full-time nurses preferring full-time work (FT/FT), part-time 

nurses preferring part-time work (PT/PT) and full-time nurses preferring part-time work (FT/PT). 

Ng, Butts, Vandenberg, De Joy, and Wilson (2006) noted that providing opportunities for 

learning, such as acquiring new knowledge and skills that benefits one’s career development, 

demonstrates care and support for employees which in turn would result in the reciprocation of 

commitment by the employees to the organization. Part-time workers in general have less access to 

development opportunities (Gallie, White, Cheng & Tomlinson, 1998; MacDermid, Dean Lee, Buck & 

Williams, 2001; Skinner, 1999). They have been found to be significantly less satisfied than full-time 

employees with development opportunities (Bergmann, Grahn & Wyatt, 1986; Comfort, Johnson & 

Wallace, 2003; Edwards & Robinson, 2004) and to feel excluded from development opportunities (Barker, 

1993; Edwards & Robinson, 2004). We found no published studies that have investigated the effects of 

work status congruency on how employees perceive their organization’s provision of development 

opportunities. However, we expected that within the part-time group, nurses who preferred to work fulltime 

would be less satisfied with their access to development opportunities than those part-time nurses 

who preferred part-time employment. Stratton (1996) found that part-time workers who preferred to 

work full-time more closely resembled full-time workers than other part-time workers who preferred to 

work part-time. This suggests that part-time nurses who want to work full-time may have a strong 

interest in pursuing development opportunities and that they will be more sensitive to the lack of career 

development opportunities than part-time nurses who prefer to work part-time. 

Hypothesis 1d: Nurses working part-time but preferring full-time work (PT/FT) will perceive 

significantly fewer development opportunities than full-time nurses preferring full-time work 

(FT/FT), part-time nurses preferring part-time work (PT/PT) and full-time nurses preferring parttime 

work (FT/PT). 

An organization can also demonstrate its commitment to its employees by providing them with an 

interesting and challenging role, allowing employees to make decisions about their job, and creating a 

sense of empowerment to make those decisions. Ng et al. (2006) suggested that such variables as 

autonomy and psychological empowerment that allow employees to fulfill their desire to have more 

control at work may be especially relevant for enhancing employees’ commitment to the organization. 

Part-time workers have been found to perceive less control over their work (Ross & Wright, 1998), to 

have more routine and less challenging jobs (Ross & Wright, 1998), to have less decision-making 

autonomy (Feldman & Doerpinghaus, 1992; Gallie et al., 1998; Ross & Wright, 1998), and to manifest a 

lower sense of empowerment (Markey, Hodgkinson & Kowalczyk, 2002). We expected that this may 

especially be the case for those nurses who are working part-time but prefer full-time work. Part-time 

nurses who prefer to work part-time may have resigned themselves to performing jobs that are routine, 

that offer little autonomy, and that provide few opportunities to exercise control. On the other hand, parttime 

nurses who prefer to work full-time are likely to view full-time jobs as an opportunity to engage in 

more challenging and meaningful work, to have more control over their job, and to have greater 

empowerment. This may result in these nurses having a negative perception of their current part-time job. 

Hypothesis 1e: Part-time nurses who prefer to work full-time (PT/FT) will report significantly 

lower levels of job challenge, job autonomy, and empowerment than full-time nurses who prefer 

full-time work (FT/FT), full-time nurses who prefer part-time work (FT/PT), and part-time nurses 

who prefer part-time work (PT/PT). 

Perceived Work Status (In)Congruency and Nurses’ Commitment 

9

Meyer and Allen (1997) view organizational commitment as a multidimensional construct which 

includes affective commitment (emotional attachment), continuance commitment (attachment due to 

perceived loss associated with leaving), and normative commitment (attachment through moral 

obligation). Most of the research comparing work status and work status congruency and organizational 

commitment has focused on affective commitment and neglected possible differences for other types of 

commitment (Thorsteinson, 2003). Holtom et al. (2002) found that work status congruency was 

significantly positively related to affective commitment suggesting that full-time and part-time workers 

with a congruent work status will exhibit greater commitment to their organization than full-time and 

part-time workers with an incongruent work status. Krauz, Sagie and Bidermann (2000) found that 

organizational commitment was higher for nurses who preferred to work more hours (PT/FT) and lower 

for nurses who preferred to work fewer hours (FT/PT). Similar findings were reported for Dutch 

Ministry employees by van Emmerick and Sanders (2005). These researchers concluded that 

mismatches of preferring to work fewer hours are more detrimental to affective commitment than 

mismatches of preferring to work more hours. We therefore predicted that nurses who were working fulltime 

but who preferred to work part-time would express significantly less affective commitment toward 

their organization than nurses in the other three groups. 

Hypothesis 2a: Nurses working full-time but preferring to work part-time (FT/PT) will report 

significantly less affective commitment to their organization than full-time nurses preferring fulltime 

work (FT/FT), part-time nurses preferring part-time work (PT/PT), and part-time nurses 

preferring full-time work (PT/FT). 

The relationship of work status with continuance and normative commitment has received sparse 

attention and we found no published studies that have examined the relationship of work status 

congruency with these two dimensions of commitment. Conway and Briner (2002) and Hackett and 

Bycio (1993) found that full-time nurses expressed significantly higher levels of continuance commitment 

than part-time nurses. However, it can be argued that nurses with an incongruent work status may exhibit 

higher levels of continuance commitment than nurses with a congruent work status. It may be that nurses 

with an incongruent work status continue to stay with their organization either because of the sacrifices 

involved in leaving or because there are no other available alternatives. We therefore predicted that 

nurses with an incongruent work status would report significantly higher levels of continuance 

commitment than nurses with a congruent work status. 

Hypothesis 2b: Nurses with an incongruent (FT/PT, PT/FT) work status will report significantly 

greater continuance commitment than nurses with a congruent (FT/FT, PT/PT) work status. 

We found only one study that has examined the effect of work status on normative commitment. 

Hackett and Bycio (1993) found no significant differences between full-time and part-time nurses for 

normative commitment. Affective commitment and normative commitment are highly similar dimensions 

of commitment (Cooper-Hakim & Viswesvaran, 2005) and should exhibit similar relationships with other 

variables. Given that full-time nurses who prefer to work part-time have been shown to express less 

affective commitment toward their organization than the other three groups, we extrapolated from this to 

propose that nurses working full-time but preferring part-time work would express significantly lower 

levels of normative commitment than nurses in the other three groups. 

Hypothesis 2c: Nurses working full-time but preferring to work part-time (FT/PT) will report 

significantly less normative commitment than full-time nurses preferring full-time work (FT/FT), 

part-time nurses preferring part-time work (PT/PT), and part-time nurses preferring full-time 

work (PT/FT). 

10

Another form of commitment, job involvement, reflects the extent to which individuals identify 

psychologically with their job (Blau & Boal, 1987). There is empirical research comparing the job 

involvement of full-time and part-time workers but we could find no published studies that have 

investigated the relationship between work status congruency and job involvement. Part-time workers in 

general report significantly less job involvement than full-time workers (Bergmann, Grahn & Wyatt, 1986; 

Hackett & Bycio, 1993; Morrow, McElroy & Elliot, 1994; Sverke, Gallagher & Hellgren, 2000; Wetzel et 

al., 1990). Part-time nurses are more likely to feel they are underemployed than full-time nurses. 

However, part-time nurses who prefer to work full-time are more likely to perceive that they are 

underemployed than part-time nurses who prefer to work part-time. Feldman et al. (1997) noted that 

underemployment has been consistently linked with poorer job involvement. We therefore expected that 

nurses working part-time who preferred to work full-time would report significantly lower levels of job 

involvement than nurses in the other three groups. 

Hypothesis 2d: Nurses working part-time but preferring full-time work (PT/FT) will report 

significantly lower job involvement than full-time nurses preferring full-time work (FT/FT), parttime 

nurses preferring part-time work (PT/PT), and full-time nurses preferring part-time work 

(FT/PT). 

Professional commitment is another form of commitment that has received little attention in the 

work status literature. We found only three published studies that have examined the relationship 

between work status and professional commitment. Two of these studies (Hackett & Bycio, 1993; Wetzel 

et al., 1990) found no significant differences between full-time and part-time nurses for professional 

commitment. Morrow et al. (1994) found that full-time nurses reported higher professional commitment 

than part-time nurses but there were no significant differences for preferred work status. Unfortunately, 

Morrow et al. collapsed across full-time and part-time and this may have masked significant differences 

within the full-time and part-time congruent and incongruent groups. We propose that full-time nurses 

who prefer to work part-time and part-time nurses who prefer to work full-time will be less committed to 

their profession because their needs or preferences are not being fulfilled. We therefore expected nurses 

with incongruent work status to exhibit lower levels of commitment to the nursing profession than nurses 

with congruent work status. 

Hypothesis 2e: Nurses with an incongruent (FT/PT, PT/FT) work status will report significantly 

less professional commitment than nurses with a congruent (FT/FT, PT/PT) work status. 

A second objective of our study was to identify the relevant predictors of each of the forms of 

nurses’ commitment. Based on previous research, we expected the perceived employer commitment 

variables to be differentially associated with the five commitment variables. In particular, we expected 

the organizational practices that were organization specific (perceived organizational support, fair 

treatment, job security and development opportunities) to be important predictors of organizational 

commitment and the organizational practices that were job-specific (job challenge, job autonomy, 

empowerment) to be important predictors of job involvement. We anticipated that both types of 

organizational practices would be associated with professional commitment. 

Participants and Procedure 

Method 

In 2005, we mailed questionnaire packets to 2,576 registered nurses employed in community 

health agencies. The nurses were randomly selected from the College of Nurses of Ontario registry list. 

Seventeen questionnaire packets were returned because the person had moved, 61 nurses indicated they 

11

were not eligible to participate for various reasons (e.g., retired, on disability, left the profession). A total 

of 1275 questionnaires was received with two of these discarded because they were incomplete giving a 

response rate of 51%. Ninety-eight percent of the respondents were women. The current paper only 

deals with the female nurses. 

The 1,230 female participants had worked for their respective community health agency an 

average of 9.91 years (SD = 7.52) and in their current job an average of 8.55 years (SD = 6.75). Their 

average age was 46.77 years (SD = 9.36) ranging from 26 to 73 years. About 34% worked in public 

health, 28% worked in home care, 24% worked in community care access centres, and the remaining 14% 

worked in a variety of community health settings including clinics, doctors’ offices, and community 

mental health. The majority (85%) of the respondents was married. 

Measures 

Work status congruency. Respondents were asked to indicate their current work status (full-time 

or part-time) and then to indicate their preferred work status (full-time or part-time). We created a work 

status variable of four categories: full-time nurses preferring full-time work (FT/FT), full-time nurses 

preferring part-time work (FT/PT), part-time nurses preferring full-time work (PT/FT), and part-time 

nurses preferring part-time work (PT/PT). Of these four groups, two have a congruent work status 

(FT/FT, n = 456 and PT/PT, n = 478) and two have an incongruent work status (FT/PT, n = 212 and 

PT/FT, n = 49). There were 35 missing values. 

Perceived employer commitment. We assessed perceived organizational support with nine items 

from the Survey of Perceived Organizational Support scale developed by Eisenberger et al. (1986). We 

modified the items to read “my agency” instead of “my organization.” Sample items are “My agency 

values my contribution to its well-being” and “My agency really cares about my well-being.” The 

response categories ranged from 1 (strongly disagree) to 5 (strongly agree). The reliability coefficient 

(Cronbach alpha) was .94. Perceptions of being treated fairly were adapted from Price and Mueller’s 

(1986) 6-item perceived distributive justice scale. Sample items are “To what extent do you feel you are 

fairly rewarded for the amount of effort that you put forth?” and “To what extent do you feel you are 

fairly rewarded considering the responsibilities that you have?” The response categories ranged from 1 

(to no extent) to 5 (very great extent). The coefficient alpha was .95. We measured perceived job 

security with three items from Hellgren and Sverke (2003). A sample item is “I feel uneasy about losing 

my job in the near future” (reverse scored). The response categories ranged from 1 (strongly disagree) to 

5 (strongly agree). The coefficient alpha was .83. The10-item measure of professional development 

opportunities was developed for this study. Respondents were asked to rate how well their agency was 

doing in providing them with such opportunities as training to update their current job skills or to learn 

new skills and expertise, release time with pay for attending professional development activities, 

opportunities for promotion or advancement, and opportunities to utilize their knowledge and skills in 

their current position. The response categories ranged from 1 (very poorly) to 5 (very well). The 

coefficient alpha was .92. 

We assessed job challenge with five items adapted from Zeitz, Johannesson and Ritchie (1997). 

A sample item is “My job requires me to do many different things at work, using a variety of skills.” The 

coefficient alpha was .83. Job autonomy was measured with four items adapted from Price’s (1997) 

measure of work autonomy. A sample item is “I have a great deal of freedom as to how to do my job.” 

The coefficient alpha was .83. We assessed two dimensions of empowerment—meaning and outcome 

empowerment. The meaning dimension of empowerment was assessed using the 3-item Meaning 

subscale developed by Spreitzer (1995). A sample item is “My job activities are personally meaningful to 

me.” The coefficient alpha was .79. The 3-item measure of the outcome dimension of empowerment was 

adapted from the Outcome Empowerment scale developed by Irvine, Leatt, Evans and Baker (1999). 

12

This is similar to Spreitzer’s impact subscale but was specifically developed for nurses. A sample item is 

“I feel that I am able to bring about improvements in the way work is done in community health nursing.” 

The coefficient alpha was .79. For the four job features measures, the response categories ranged from 1 

(strongly disagree) to 5 (strongly agree). 

Nurses’ commitment. Organizational commitment consisted of affective, continuance and 

normative commitment. Affective commitment was assessed with three items from the Affective 

Commitment scale developed by Meyer, Allen and Smith (1993). A sample item is “This agency has a 

great deal of personal meaning for me.” The coefficient alpha was .86. Continuance commitment was 

assessed with three items from the Continuance Commitment scale developed by Meyer et al. (1993). A 

sample item is “It would be hard for me to leave my agency right now, even if I wanted to.” The 

coefficient alpha was .61. Normative commitment was measured with three items from the Normative 

Commitment scale developed by Meyer et al. (1993). A sample item is “This agency deserves my 

loyalty.” The coefficient alpha was .75. For each of the organizational commitment scales, the word 

“organization” was replaced with “agency. The response categories for the three organizational 

commitment measures ranged from 1 (strongly disagree) to 5 (strongly agree). We measured job 

involvement with six items from the Job Involvement-Role (JIR) scale developed by Paullay, Alliger and 

Stone-Romero (1994). The JIR items reflect the degree to which people are engaged in the specific tasks 

that make up their job. Sample items are “I’ll stay overtime to finish something that I’m working on” and 

“I am very much involved personally in the type of work that I do in my present job.” The response 

categories ranged from 1 (strongly disagree) to 5 (strongly agree). The coefficient alpha was .70. The 5item 

measure of professional commitment was adapted from Reilly and Orsak (1991). Sample items are 

“If I could go into a different profession other than nursing which paid the same, I would probably do it” 

(reverse scored) and “I definitely want a career for myself in the nursing profession.” The response 

categories ranged from 1 (strongly disagree) to 5 (strongly agree). The coefficient alpha was .87. 

Demographic variables. The demographic variables included the workplace setting (public 

health, community care access centre, home care, other), length of time employed in current workplace, 

length of time employed in current position, age, gender, and marital status. 

Data Analysis 

To test our hypotheses, we conducted multivariate analysis of covariance (MANCOVA) with 

work status (in)congruency as the independent variable and organizational tenure, job tenure and age as 

the covariates. Thorsteinson (2003) noted that demographic differences such as age and tenure may 

obscure potential differences between full-time and part-time workers’ attitudes. We used Tukey post 

hoc comparisons to identify significant differences among the four work status groups. To identify the 

relative contribution of work status (in)congruency and the perceived employer commitment variables on 

the five forms of nurses’ commitment, we conducted a series of hierarchical regressions. We effects 

coded the work status (in)congruency variable and used FT/FT as the comparison group. The control 

variables (organizational tenure, job tenure, and age) were entered in the first step, in step 2 we entered 

the three dummy coded work status (in)congruency groups (FT/PT, PT/FT and PT/PT), and in step 3 we 

entered the perceived employer commitment variables. 

Results 

There was a significant overall work status (in)congruency effect for both the organizationspecific 

aspects (F(12,3030) = 4.02, p < .001) and the job-specific aspects (F(12,3330) = 3.99, p < .001) of 

perceived employer commitment. The means, standard deviations, and ANCOVA F-values are presented 

in Table 1. Hypothesis 1a predicted that nurses with a congruent work status would perceive significantly 

13

higher levels of perceived organizational support than nurses with an incongruent work status. This 

hypothesis was supported for nurses working full-time but not for nurses working part-time. Full-time 

nurses who preferred to work full-time perceived significantly higher levels of organizational support 

than did full-time nurses who preferred to work part-time. 

Hypothesis 1b predicted that part-time nurses who preferred to work full-time would perceive 

being treated significantly less fairly than both groups of full-time nurses. This hypothesis was partially 

supported. Part-time nurses who preferred full-time work perceived that they were treated less fairly than 

full-time nurses who preferred full-time work but there was no significant difference between part-time 

nurses who preferred full-time work and full-time nurses who preferred part-time work. 

Table 1 

Means, SD, and ANCOVA F-values for Perceived Commitment from the Organization Variables 

FT/FT FT/PT PT/FT PT/PT F-value 

Mean 

(SD) 

Organizational Features: 

Organizational Support 3.29 a 

(.84) 

Fair Treatment 2.77 a 

(.87) 

Job security 3.69 a 

(1.02) 

Development Opportunities 3.05 a 

(.85) 

Mean 

(SD) 

3.06 a 

(.79) 

2.54 

(.81) 

3.70 b 

(.90) 

2.91 b 

(.78) 

Mean 

(SD) 

3.21 

(.90) 

2.47 a 

(.86) 

2.96 abc 

(1.16) 

2.57 abc 

(.98) 

Mean 

(SD) 

3.17 

(.77) 

2.69 

(.76) 

3.60 c 

(.94) 

2.92 c 

(.72) 

Job Features: 

Job Challenge 4.21 a 

4.13 4.12 

(.59) (.63) (.53) (.68) 

Job Autonomy 3.60 a 

3.45 3.62 

(.78) (.79) (.76) (.82) 

Meaning Empowerment 4.25 4.09 

(.55) 

a 

4.30 

(.55) 

a 

4.14 

(.47) (.54) 

Outcome Empowerment 3.79 a 

3.64 3.65 

(.77) (.83) (.87) (.73) 

Note. Superscripts denote means that differ significantly across the work status groups. 

* p < .05 ** p < .01 *** p < .001 

4.02 a 

3.45 a 

3.58 a 

3.73* 

4.21* 

6.83*** 

4.81** 

8.30*** 

3.17* 

6.24*** 

5.99*** 

There was support for hypotheses 1c and 1d. Part-time nurses who preferred full-time work 

perceived significantly lower job security and fewer development opportunities than did nurses in the 

other three groups. 

Hypothesis 1e, which predicted that part-time nurses who preferred full-time work would report 

significantly lower levels of job challenge, job autonomy, and empowerment received no support. The 

significant differences were primarily between the two work status congruent groups (FT/FT and PT/PT). 

Full-time nurses who preferred full-time work reported significantly higher levels of job challenge, job 

autonomy, and outcome empowerment than did part-time nurses who preferred part-time work. Contrary 

to our prediction, part-time nurses who preferred full-time work reported a significantly higher sense of 

meaning empowerment than did full-time nurses who preferred part-time work. 

14

There was an overall significant work status (in)congruency effect for the nurses’ commitment 

variables (F(15,3259) = 9.48, p < .001). The means, standard deviations and ANCOVA F-values are in 

Table 2. Hypothesis 2a predicted that full-time nurses who preferred part-time work would report 

significantly less affective commitment to their agency than nurses in the other three groups. This 

hypothesis was partially supported. Full-time nurses who preferred part-time work reported significantly 

less affective commitment to their agency than did part-time nurses who preferred full-time work. Parttime 

nurses who preferred part-time work also reported significantly less affective commitment to their 

agency than part-time nurses who preferred full-time work. 

Hypothesis 2b predicted that nurses with an incongruent work status would report higher 

continuance commitment than nurses with a congruent work status. Part-time nurses who preferred fulltime 

work reported significantly higher continuance commitment than full-time nurses who preferred fulltime 

work and part-time nurses who preferred part-time work. Full-time nurses who preferred part-time 

work reported significantly higher levels of continuance commitment than part-time nurses who preferred 

part-time work. 

Table 2 

Means, SD, and ANCOVA F-values for Nurses’ Commitment 

FT/FT FT/PT PT/FT PT/PT F-value 

Mean 

(SD) 

Mean 

(SD) 

Mean 

(SD) 

Mean 

(SD) 

Affective Commitment 3.41 

(.96) (.92) (.99) (.92) 

Continuance Commitment 3.11 a 

3.32 

(.83) 

c 

3.55 

(.79) 

ab 

(.81) (.78) 

Normative Commitment 3.07 2.82 

(.88) 

a 

3.11 

(.83) 

a 

2.94 

(.96) (.77) 

Job Involvement 

a b 

4.01 3.84 

(.60) 

a 

4.00 

(.66) (.56) (.58) 

Professional Commitment 3.51 a 

a b c 

3.07 3.58 

(.92) (.91) 

b 

(.83) (.87) 

Note. Superscripts denote means that differ significantly across the work status groups. 

* p < .05 ** p < .01 *** p < .001 

3.17 a 

3.51 ab 

3.17 b 

2.88 bc 

3.83 b 

3.45 c 

7.06*** 

21.62*** 

5.19** 

9.68*** 

11.46*** 

Hypothesis 2c was only partially supported. Full-time nurses who preferred part-time work 

reported significantly lower normative commitment than part-time nurses who preferred part-time work. 

There were no significant differences between the FT/PT nurses and nurses with a congruent work status 

(FT/FT, PT/PT). 

Hypothesis 2d predicted that part-time nurses who preferred full-time work would report 

significantly lower job involvement than nurses in the other three groups. This hypothesis received no 

support. Full-time nurses who preferred full-time work reported significantly higher job involvement 

than full-time nurses who preferred part-time work and part-time nurses who preferred part-time work. 

There were no significant differences found for part-time nurses who preferred full-time work. 

Hypothesis 2e predicted that nurses with an incongruent work status would report significantly 

lower commitment to the nursing profession than nurses with a congruent work status. This was 

supported for the FT/PT group but not for the PT/FT group. Full-time nurses who preferred part-time 

15

work reported significantly lower levels of professional commitment than full-time nurses who preferred 

full-time work, part-time nurses who preferred full-time work and part-time nurses who preferred parttime 

work. 

The hierarchical regression results are presented in Table 3 (affective and continuance 

commitment), Table 4 (normative commitment and job involvement), and Table 5 (professional 

commitment). The predictor variables accounted for 52% of the variance in affective commitment, 15% 

of the variance in continuance commitment, 48% of the variance in normative commitment, 43% of the 

variance in job involvement, and 30% of the variance in professional commitment. 

The significant predictors of affective commitment were perceived organizational support, 

meaning empowerment, outcome empowerment, and development opportunities. The significant 

predictors of continuance commitment were the three work status groups, perceived job security, and 

meaning empowerment. The significant predictors of normative commitment were perceived 

organizational support, outcome empowerment, perceived fair treatment, development opportunities, 

meaning empowerment, and FT/PT work status. The significant predictors of job involvement were 

meaning empowerment, job challenge, outcome empowerment, job autonomy, and PT/PT work status. 

The significant predictors of professional commitment were meaning empowerment, outcome 

empowerment, FT/PT work status, and perceived organizational support. 

Table 3 

Hierarchical Regression Results of Affective and Continuance Commitment 

Step 1 

β 

Affective Commitment Continuance Commitment 

Step 2 

β 

Step 3 

β 

Step 1 

β 

Step 2 

β 

Step 3 

β 

Organizational tenure .23*** .22*** .23*** .00 -.01 .02 

Job tenure -.12** -.11** -.06 .12** .15*** .14*** 

Age .08* .08* -.03 -.03 -.01 .01 

R 2 = .05 

F = 15.37*** 

R 2 = .01 

F = 4.62** 

FT/PT -.10** -.02 .12** .09** 

PT/FT .01 .02 .09** .07* 

PT/PT -.12** -.05 -.15*** -.19*** 

R 2 = .06 

∆ R 2 = .01 

F = 5.15** 

R 2 = .07 

∆ R 2 = .06 

F = 21.32*** 

Organizational support .50*** -.07 

Fair treatment .04 .00 

Job security -.01 -.17*** 

Develop opportunities .08** -.02 

Job challenge -.03 -.05 

Job autonomy .01 -.04 

Meaning empowerment .15*** -.08* 

Outcome empowerment .12*** -.02 

R 2 = .52 

∆ R 2 = .46 

F = 116.18*** 

* p < .05 ** p < .01 *** p < .001 

R 2 = .15 

∆ R 2 = .08 

F = 10.74*** 

16

Table 4 

Hierarchical Regression Results of Normative Commitment and Job Involvement 

Step 1 

β 

Normative Commitment Job Involvement 

Step 2 

β 

Step 3 

β 

Step 1 

β 

Step 2 

β 

Organizational tenure .16*** .16*** .17*** .05 .05 .03 

Job tenure -.08 -.08 -.02 -.07 -.06 -.04 

Step 3 

β 

Age .11** .11** .00 .25*** .25*** .16*** 

R 2 = .04 

F = 12.05*** 

R 2 = .06 

F = 22.24*** 

FT/PT -.14*** -.06* -.07* -.03 

PT/FT -.03 -.01 .02 .00 

PT/PT -.10** -.04 -.16*** -.07* 

R 2 = .05 

∆ R 2 = .01 

F = 6.29*** 

R 2 = .09 

∆ R 2 = .03 

F = 8.30*** 

Organizational support .45*** .03 

Fair treatment .11*** .01 

Job security -.04 -.05 

Develop opportunities .08* -.05 

Job challenge -.03 .26*** 

Job autonomy .01 .09** 

Meaning empowerment .08** .31*** 

Outcome empowerment .13*** .10** 

R 2 = .48 

∆ R 2 = .43 

F = 101.24*** 

* p < .05 ** p < .01 *** p < .001 

R 2 = .43 

∆ R 2 = .34 

F = 72.01*** 

Table 5 

Hierarchical Regression Results of Professional Commitment 

Professional Commitment 

Step 1 

β 

Step 2 

β 

Step 3 

β 

Organizational tenure .01 .00 .00 

Job tenure -.04 -.05 -.02 

Age .14*** .14*** .07* 

R 2 = .02 

F = 6.07*** 

FT/PT -.18*** -.13*** 

PT/FT .01 .01 

PT/PT -.03 .03 

R 2 = .05 

∆ R 2 = .03 

17

F = 9.99*** 

Organizational support .10* 

Fair treatment .04 

Job security .03 

Develop opportunities .04 

Job challenge -.07 

Job autonomy -.02 

Meaning empowerment .30*** 

Outcome empowerment .23*** 

R 2 = .30 

∆ R 2 = .25 

F = 43.44*** 

* p < .05 ** p < .01 *** p < .001 

Discussion 

Work status research has been criticized in the past for being largely atheoretical (Barling & 

Gallagher, 1996). In the present study, we applied social exchange theory to investigate the relationships 

between work status (in)congruency with perceived employer commitment and with nurses’ commitment. 

For the organization-specific aspects of perceived employer commitment, the findings partially supported 

our prediction that nurses with an incongruent work status would perceive significantly less 

organizational support and feel they are treated less fairly than nurses with a congruent work status. The 

findings fully supported our prediction that part-time nurses who preferred full-time employment would 

perceive significantly less job security and fewer development opportunities than nurses in the other three 

groups. However, there was no support for the predictions regarding work status (in)congruency and the 

job-specific aspects of perceived employer commitment. In this case, the significant differences were 

primarily between the two groups of nurses with a congruent work status (FT/FT, PT/PT). Full-time 

nurses who preferred to work full-time reported significantly more job challenge, greater job autonomy, 

and a greater sense of outcome empowerment than part-time nurses who preferred to work part-time. 

These findings indicate that work status incongruency (FT/PT, PT/FT) has a greater influence on the 

organization-specific aspects of perceived employer commitment (perceived organizational support, fair 

treatment, job security, and development opportunities) whereas work status congruency (FT/FT, PT/PT) 

has a greater influence on the job-specific aspects of perceived employer commitment (job challenge, job 

autonomy, and outcome empowerment). 

Reynolds (2003) noted that researchers tend to focus on employees who are part-time but prefer 

full-time work and give little attention to employees who are full-time but prefer part-time employment. 

The findings of our study show that full-time nurses who preferred to work part-time perceived 

significantly less organizational support than the other three groups, reported the lowest sense of meaning 

empowerment, and expressed the lowest levels of affective commitment (along with the PT/PT group), 

normative commitment, and professional commitment. Compared with the FT/PT group, part-time 

nurses who preferred to work full-time (PT/FT) reported less job security and less access to development 

opportunities. At the same time, they expressed a greater sense of meaning empowerment and higher 

levels of affective, normative, and professional commitment. These findings suggest that employers need 

to provide part-time nurses who prefer to work full-time with full-time positions if at all possible. 

Otherwise, they may jeopardize the commitment of these nurses to both the organization and the nursing 

profession. But what may be even more critical is to provide full-time nurses who want part-time work 

with part-time employment. By not doing so, these nurses may already have decided that their 

18

organization has failed to fulfill its obligations to them and, in turn, may reduce their commitment toward 

their organization and profession. 

What is noteworthy about the regression findings is the association of the meaning and outcome 

dimensions of empowerment with nurses’ commitment. The meaning dimension of empowerment was 

the only perceived employer commitment variable that was a significant predictor of all five forms of 

nurses’ commitment and the outcome dimension of empowerment significantly predicted four of the 

nurses’ commitment variables. Nurses who felt their work was personally meaningful and important to 

them and who felt that they were instrumental in making improvements to community health nursing 

reported significantly greater affective, normative, job, and professional commitment than nurses who 

lacked a sense of empowerment. Nurses who felt their work was personally meaningful and important to 

them also were significantly less likely to be staying with their agency because they felt they had to, i.e., 

they expressed lower levels of continuance commitment. Consistent with social exchange theory, Liden, 

Wayne & Sparrowe (2000) proposed that empowerment may be linked with employee’s sense of 

commitment (affective) to the organization through the process of reciprocation. Individuals are 

appreciative when an organization provides them with work context that results in a sense of 

empowerment and, in turn, will reciprocate by being more committed to the organization. The findings of 

our study suggest that empowerment not only is associated with greater affective commitment but that it 

is strongly related to other forms of commitment as well. 

As expected, the job-specific aspects of perceived employer commitment were significant 

predictors of job involvement. Nurses with greater job challenge, autonomy, and empowerment reported 

significantly higher levels of involvement in their job than nurses whose job lacked these aspects of 

perceived employer commitment. For the organization-specific aspects of perceived employer 

commitment, perceived organizational support was a significant predictor of affective commitment, 

normative commitment and professional commitment. Nurses who perceived their agency cared about 

them, valued their contribution, and was committed to them reported significantly greater affective, 

normative and professional commitment than nurses who lacked this type of employer commitment. 

Access to development opportunities was a significant predictor of affective and normative commitment. 

Nurses who felt they had access to such opportunities as training to update current skills and to acquire 

new skills, promotion or transfer to a different job, and funding to attend professional development 

activities reported significantly higher levels of affective and normative commitment to their agency than 

nurses who lacked access to these development opportunities. Perceived fair treatment was a significant 

predictor of normative commitment. Nurses who perceived that they were receiving adequate rewards 

and recognition reported significantly higher levels of normative commitment than nurses who perceived 

they were being treated unfairly. 

The predictor variables accounted for the least amount of variance in continuance commitment. 

All three work status (in)congruency variables remained significant predictors of continuance 

commitment even after the perceived employer commitment variables had been entered. Apart from the 

work status (in)congruency variables, only perceived job security and the meaning dimension of 

empowerment were significant predictors of continuance commitment. Nurses who perceived less job 

security and who did not feel that their job was personally meaningful or important to them reported 

significantly higher levels of continuance commitment. Allen and Meyer (1996) noted that continuance 

commitment has few significant relationships with work-related attitude measures and suggested that 

continuance commitment may be an affectively neutral construct. The findings of the present study lend 

some support to this conjecture. On the other hand, both the ANCOVA and hierarchical regression 

findings suggest that work status (in)congruency has important implications for continuance commitment. 

Nurses with an incongruent work status reported significantly greater continuance commitment than 

nurses with a congruent work status. This means that community health nurses who are being denied 

19

their preferred work hours are remaining with their agency because they feel they have to, not because 

they feel an emotional attachment or a moral obligation to remain. 

Along with the limitations associated with the cross-sectional research design and the selfreported 

data, the findings of this study may not be generalizable beyond the nursing population. 

Although the overall sample size was relatively large with over 1,200 respondents, the number of nurses 

in the PT/FT group was small compared to the number of nurses in the FT/FT, FT/PT, and PT/PT groups. 

This reduces the likelihood of finding significant differences between the PT/FT group and the other three 

groups. All of the measures except for continuance commitment had reliability coefficients of .7 or above. 

We have used this same measure of continuance commitment in previous studies and the coefficient 

alphas have been in the acceptable range (above .7). However, other researchers have also reported low 

reliability coefficients for the continuance commitment scale. For example, Ko, Price and Mueller (1997) 

reported a coefficient alpha of .58 for the 6-item version of Meyer et al.’s (1993) continuance 

commitment subscale. The continuance commitment subscale has not been without controversy, 

especially in regard to whether it is unidimensional or consists of multiple dimensions. The items may be 

less applicable to certain work contexts or interpreted differently by different populations. In our case, it 

was community health nurses, and in the case of Ko et al., it was employees in South Korea. 

The present findings have management implications for community health nursing. Our study 

suggests that when agencies fail to meet the needs of their nurses (i.e., failing to provide nurses with their 

preferred work status), nurses may reciprocate by exhibiting reduced organizational commitment, job 

involvement, and professional commitment. It is important for employers to accommodate the needs and 

provide nurses with the flexibility to match their preferred work status to avoid the expenses associated 

with work dissatisfaction (Havlovic, Lau & Pinfield, 2002). Campbell, Fowles, and Weber (2004) have 

stressed the importance of increasing the attractiveness of nurses’ jobs to retain a highly motivated 

workforce. Thus, the need for agencies to accommodate the needs and preferences of its nurses is 

becoming more crucial to develop and maintain commitment in the workplace. 

Maynard, Thorsteinson and Parfyonova (2006) noted that work status congruency models are 

valuable in extending research past simple full-time/part-time differences. However, Maynard et al. also 

claimed that even work status congruency models may, by themselves, still be too simplistic. These 

researchers argued for the need to incorporate reasons why people engage in full-time or part-time work. 

We suggest that future research not only look at the reasons for working full-time or part-time but also the 

reasons why employees prefer their current work status or why they prefer a different work status. 

Researchers also need to identify the reasons why employees are not able to work their preferred work 

status. 

The present study examined the relationship of work status in(congruency) with organizationspecific 

and job-specific aspects of perceived employer commitment and with nurses’ commitment to 

their organization, to their job, and to their profession. In general, the pattern of findings reported here 

show that nurses with an incongruent work status perceived less commitment from the organization than 

nurses with a congruent work status. Thus, it is vital for employers to try and accommodate the needs of 

their employees with regards to work status preferences. Furthermore, our findings suggest that 

employers should try to develop methods of increasing employees’ empowerment (meaning and outcome) 

as having a sense of empowerment was found to be the strongest predictor of nurses’ commitment. 

20

References 

Allen, N.J., & Meyer, J.P, “Affective, continuance, and normative commitment to the organization: an 

examination of construct validity,” Journal of Vocational Behavior, 49, (1996), 252-276. 

Armstrong-Stassen, M., Al-Ma’aitah, R., Cameron, S.J., & Horsburgh, M.E, “The relationship between 

work status congruency and the job attitudes of full-time and part-time Canadian and Jordanian 

nurses,” The International Journal of Human Resource Management, 9, (1998), 41-57. 

Armstrong-Stassen, M., Horsburgh, M.E., & Cameron, S.J, “The reactions of full-time and part-time 

nurses to restructuring in the Canadian health care system,” Paper presented at the annual 

convention of the Academy of Management, Dallas, TX, (1994, August). 

Barker, K, “Changing assumptions and contingent solutions: The costs and benefits of women working 

full- and part-time,” Sex Roles, 28, (1993), 47-71. 

Barling, J., & Gallagher, D.G, “Part-time employment,” In C.L. Cooper & I.T. Robertson (Eds.), 

International review of industrial and organizational psychology Vol. 11 (pp. 243-277). 

Chichester, England: John Wiley & Sons, 1996 

Bergmann, T.J., Grahn, J.L., & Wyatt, R, “Relationship of employment status to employee job 

satisfaction,” Akron Business and Economic Review, 17(2), (1986), 45-50. 

Blau, G.J., & Boal, K.R, “Conceptualizing how job involvement and organizational commitment affect 

turnover and absenteeism,” Academy of Management Review, 12, (1987), 288-300. 

Blau, P.M., Exchange and power in social life. New York, NY: Wiley, 1964. 

Burke, R.J., & Greenglass, E.R, “Work status congruence, work outcomes and psychological well-being,” 

Stress Medicine, 16, (2000), 91-99. 

Campbell, S. L., Fowles, E. R., & Weber, B. J., “Organizational structure and job satisfaction in public 

health nursing,” Public Health Nursing, 21(6), (2004), 564-571. 

Comfort, D., Johnson, K., & Wallace, D, “Part-time work and family-friendly practices in Canadian 

workplaces,” http://www.statcan.ca, [Accessed 9 July 2003]. 

Conway, N., & Briner, R.B., “Full-time versus part-time employees: Understanding the links between 

work status, the psychological contract, and attitudes,” Journal of Vocational Behavior, 61, 

(2002), 279-301. 

Cooper-Hakim, A., & Viswesvaran, C., “The construct of work commitment: Testing an integrative 

framework,” Psychological Bulletin, 131, (2005), 241-259. 

Edwards, C., & Robinson, O., “Evaluating the business case for part-time working amongst qualified 

nurses,” British Journal of Industrial Relations, 42, (2004), 167-183. 

Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D., “Perceived organizational support,” Journal 

of Applied Psychology, 71, (1986), 500-507. 

21

Feldman, D.C., & Doerpinghaus, H.I., “Missing persons no longer: Managing part-time workers in the 

‘90s,” Organizational Dynamics, Summer, (1992), 59-72. 

Feldman, D.C., Leana, C.R., & Turnley, W.H., “A relative deprivation approach to understanding 

underemployment,” Trends in Organizational Behavior, 4, (1997), 43-60. 

Gakovic, A., & Tetrick, L.E., “Perceived organizational support and work status: a comparison of the 

employment relationships of part-time and full-time employees attending university classes,” 

Journal of Organizational Behavior, 24, (2003), 649-666. 

Gallie, D., White, M., Cheng, Y., & Tomlinson, M., Restructuring the employment relationship. Oxford: 

Clarendon Press, 1998. 

Gouldner, A.W., “The norm of reciprocity: A preliminary statement,” American Sociological Review, 25, 

(1960), 161-178. 

Hackett, R.D., & Bycio, P., “An examination of the job related attitudes of part-time versus full-time 

employed nurses,” Paper presented at the annual conference of the Administrative Sciences 

Association of Canada, Lake Louise, (1993, June). 

Havlovic, S. J., Lau, D. C., & Pinfield, L. T., “Repercussions of work schedule congruence among fulltime, 

part-time, and contingent nurses,” Health Care Management Review, 27(4), (2002), 30-41. 

Hellgren, J., & Sverke, M., “Does job insecurity lead to impaired well-being or vice versa? Estimation of 

cross-lagged effects using latent variable modeling,” Journal of Organizational Behavior, 24, 

(2003), 215-236. 

Holtom, B.C., Lee, T.W., & Tidd, S.T., “The relationship between work status congruence and workrelated 

attitudes and behaviors,” Journal of Applied Psychology, 87, (2002), 903-915. 

Irvine, D., Leatt, P., Evans, M.G., & Baker, R.G., “Measurement of staff empowerment within health 

service organizations,” Journal of Nursing Measurement, 7, (1999), 79-95. 

Keil, J.M., Armstrong-Stassen, M., Cameron, S.J., & Horsburgh, M.E., “Part-time nurses: The effect of 

work status congruency on job attitudes,” Applied Psychology: An International Review, 49, 

(2000), 227-236. 

Ko, J., Price, J.L., & Mueller, C.W. (1997). Assessment of Meyer and Allen’s three-component model of 

organizational commitment in South Korea. Journal of Applied Psychology, 84, 961-973. 

Krausz, M., Sagie, A., & Bidermann, Y., “Actual and preferred work schedules and scheduling control as 

determinants of job-related attitudes,” Journal of Vocational Behavior, 56, (2000), 1-11. 

Liden, R.C., Wayne, S.J., & Sparrowe, R.T. “An examination of the mediating role of psychological 

empowerment on the relations between the job, interpersonal relationships, and work outcomes,” 

Journal of Applied Psychology, 85, (2000), 407-416. 

Levanoni, E., & Sales, C.A., “Differences in job attitudes between full-time and part-time Canadian 

employees,” Journal of Social Psychology, 130, (1990), 231-237. 

22

MacDermid, S.M., Dean Lee, M., Buck, M., & Williams, M.L., “Alternative work arrangements among 

professionals and managers: Rethinking career development and success,” The Journal of 

Management Development, 20, (2001), 305-317. 

Markey, R., Hodgkinson, A., & Kowalczyk, J., “Gender, part-time employment and employee 

participation in Australian workplaces,” Employee Relations, 24, (2002), 129-150. 

Maynard, D.C., Thorsteinson, T.J., & Parfyonova, N.M., “Reasons for working part-time: Subgroup 

differences in job attitudes and turnover intentions,” Career Development International, 11, 

(2006), 145-162. 

McDonald, P.L., & Wanner, R.A., “Part-time work and the older worker in Canada,” In B.O. Warme, 

K.L.P. Lundy & L.A. Lundy (Eds.), Working part-time: Risks and opportunities (pp. 187-203). 

New York: Praeger, 1992. 

Meyer, J.P., & Allen, N.J., Commitment in the workplace: Theory, research, and application. Thousand 

Oaks, CA: Sage Publications, 1997. 

Meyer, J.P., Allen, N.J., & Smith, C.A., “Commitment to organizations and occupations: Extension and 

test of a three-component conceptualization,” Journal of Applied Psychology, 78, (1993), 538- 

551. 

Morrow, P.C., McElroy, J.C., & Elliot, S.M., “The effect of preference for work status, schedule, and 

shift on work-related attitudes,” Journal of Vocational Behavior, 45, (1994), 202-222. 

Ng, T.W.H., Butts, M.M., Vandenberg, R.J., DeJoy, D.M., & Wilson, M.G., “Effects of management 

communication, opportunity for learning, and work schedule flexibility on organizational 

commitment,” Journal of Vocational Behavior, 68, (2006), 474-489. 

Paullay, I.M., Alliger, G.M., & Stone-Romero, E.F., “Construct validation of two instruments designed to 

measure job involvement and work centrality,” Journal of Applied Psychology, 79, (1994), 224- 

228. 

Price, J.L., “Handbook of organizational measurement,” International Journal of Manpower, 18, (1997), 

305-558. 

Price, J.L., & Mueller, C.W., Handbook of organizational measurement. Marshfield, Mass: Pitman 

Publishing Inc., 1986. 

Pyper, W., “Employment trends in nursing,” Perspectives on Labour and Income, 5(11), (2004), 5-17. 

Reilly, N.P., & Orsak, C.L., “A career stage analysis of career and organizational commitment in 

nursing,” Journal of Vocational Behavior, 39, (1991), 311-330. 

Reynolds, J., “You can’t always get the hours you want: Mismatches between actual and preferred work 

hours in the U.S.,” Social Forces, 81, (2003), 1171-1199. 

Ross, C.E., & Wright, M.P., Women’s work, men’s work, and the sense of control,” Work & 

Occupations, 25, (1998), 333-355. 

23

Schellenberg, G., The changing nature of part-time work. Ottawa: The Centre for International Statistics, 

Canadian Council on Social Development, 1997. 

Skinner, D., “The reality of equal opportunities: The expectations and experiences of part-time staff and 

their managers,” Personnel Review, 28, (1999), 425-438. 

Spreitzer, G.M., “Psychological empowerment in the workplace: Dimensions, measurement, and 

validation,” Academy of Management Journal, 38, (1995), 1442-1465. 

Stamper, C.L., & Van Dyne, L., “Work status and organizational citizenship behavior: a field study of 

restaurant employees,” Journal of Organizational Behavior, 22, (2001), 517-536. 

Stratton, L.S., “Are “involuntary” part-time workers indeed involuntary?” Industrial and Labor Relations 

Review, 49, (1996), 522-536. 

Sverke, M., Gallagher, D.G., & Hellgren, J., “Alternative work arrangements: Job stress, well-being and 

pro-organizational attitudes among employees with different employment contracts,” In K. 

Isaksson, C. Hogstedt, C. Eriksson, & T. Theorell (Eds.), Health effects on the new labour market 

(pp. 145-168). New York: Plenum, 2000. 

Tanksy, J.W., Gallagher, D.G., & Wetzel, K., “The effects of demographics, work status and relative 

equity on attitudes of full and part-time workers,” Canadian Journal of Administrative Sciences, 

14, (1997), 315-326. 

Thorsteinson, T.J., “Job attitudes of part-time vs. full-time workers: A meta-analytic review,” Journal of 

Occupational and Organizational Psychology, 76, (2003), 151-177. 

Van Emmerik, I.J.H., & Sanders, K., “Mismatch in working hours and affective commitment,” Journal of 

Managerial Psychology, 20, (2005), 712-726. 

Wetzel, K., Soloshy, E.D., & Gallagher, D.G., “The work attitudes of full-time and part-time registered 

nurses,” Health Care Management Review, 3(15), (1990), 79-85. 

Zeitz, G., Johannesson, R., & Ritchie, J.E. Jr., “An employee survey measuring total quality management 

practices and culture. Group & organization Management, 22, (1997), 414-444. 

24

ASAC 2008 Yoshio Yanadori 

Halifax, Nova Scotia Sauder School of Business 

University of British Columbia 

DO FIRM COMPENSATION STRATEGIES MATTER TO ALL EMPLOYEES? THE SCOPE 

OF FIRM COMPENSATION STRATEGIES IN HIGH TECHNOLOGY FIRMS 

This study evaluated the extent and nature of firm compensation 

strategies using employee compensation data from U.S. high-technology 

firms. I found that firm pay level strategies influenced the pay level for 

strategic employee groups (i.e., managers, R&D employees) to a greater 

extent than the pay level for other employee groups. My analyses also 

revealed that firms applied consistent pay level and pay mix strategies 

across different employee groups. 

“(Strategy is defined as) the determination of the basic long-term goals and objectives of an enterprise, 

and the adoption of courses of action and the allocation of resources necessary for carrying out these 

goals” (Chandler, 1962: 13). 

As suggested by Chandler, resource allocation presents a key element of corporate strategy. Granted, the 

way firms manage employee compensation will form one important dimension of corporate strategy as it 

is directly associated with the allocation of compensation budget, which accounts for more than 50 

percent of operating expenses in most firms (Milkovich & Newman, 2008). Reported relationships 

between compensation management and subsequent firm performance endorse the strategic nature of 

compensation management (Gerhart, 2000). 

If compensation management is really strategic, firms will exhibit differences in this respect. 

Indeed, compensation researchers have long recognized that aspects of compensation differ systematically 

across firms (Gerhart & Rynes, 2003). Senior managers make strategic decisions when determining their 

employee compensation taking various contextual factors into consideration to achieve organizational 

goals. Differences in strategic decisions yield inter-firm differences in aspects of compensation such as 

pay level (e.g., Groshen, 1991) and pay mix (e.g., Gerhart & Milkovich, 1990). Empirical studies have 

shown that inter-firm differences in these aspects lead to inter-firm differences in performance (Gerhart, 

2000). Building on this notion, compensation textbooks elaborate how senior managers determine these 

aspects and their implications to employee behavior and organizational outcomes (Martocchio, 2006; 

Milkovich & Newman, 2008). 

Despite the recognition of the role firm compensation strategies play in shaping firm 

compensation systems, current theory and research offer ambiguous predictions regarding the scope of 

compensation strategies. On the one hand, some studies focused on the compensation for specific 

employee groups, typically managerial employees (e.g., Kerr, 1985), and found that firm compensation 

strategies shape the compensation for these employees. Implicit in this argument is that the scope of firm 

compensation strategies is limited; they may not influence compensation for other employee groups. On 

the other hand, there are studies that examined employee compensation in firms and reported that firm 

compensation strategies influence compensation systems in organizations as a whole (e.g., Boyd & 

Salamin, 2001). These studies suggest that the influence of firm compensation strategies pierces 

throughout the firms. Thus, although compensation researchers agree on the importance of firm 

compensation strategies, some ambiguity remains about how they influence compensation for different 

employee groups within firms in different ways. 

25

In this study, I seek to address this issue using employee compensation data from US hightechnology 

firms. The data include compensation information for employees below the executive level 

holding different jobs (i.e., research and development (R&D), technical, administrative) with different 

responsibilities (i.e., middle-level managers, non-managerial employees). I examine how firm 

compensation strategies shape compensation systems for these employees by focusing on two dimensions: 

pay level and pay mix, which have been rigorously studied by prior researchers. 

Effects of Firm Compensation Strategies 

Theory Development 

Organizational variation in compensation management forms one key research area for labor 

economists and management researchers. Among various aspects of compensation management, much of 

research effort has been devoted to understand inter-firm differences in pay level and pay mix (Gerhart, 

2000). 

While pay rates are determined to a large extent by the supply and demand in the labor market, 

inter-firm differences in pay rates have consistently been reported (Gerhart & Rynes, 2003). It is in part 

attributable to the differences in employees’ human capital retained, but inter-firm differences still persist 

after controlling for such worker effects (Groshen, 1991). Empirical investigations revealed that some 

firm-level characteristics such as firm size, profitability, and industry membership are systematically 

associated with firm pay level (Gerhart & Milkovich, 1990). Beyond these firm characteristics, Gerhart 

and Milkovich (1990) explicitly claimed that firm compensation strategies play a role in the determination 

of firm pay level. Examining managerial pay, they reported that firm pay rates are systematically different 

after controlling for employee human capital, job characteristics, and firm characteristics. The authors 

contended that firm-specific effects reflected firm compensation strategies. 

Employee compensation consists of various pay programs (e.g., base pay, short-term incentives, 

long-term incentives, and benefits) and anecdotal evidence indicates that firms have discretion in mixing 

different programs (e.g., Lincoln Electric, Starbucks, SAS Institute). Similar to pay level, Gerhart and 

Milkovich (1990) reported that inter-firm differences in pay mix for managerial employees, measured as 

the ratio of bonus to base pay, are still apparent after controlling for observable firm characteristics (i.e., 

firm size and performance), as well as worker characteristics and job characteristics. Their empirical 

analyses revealed that firm specific effects accounted for a greater proportion of the variance in pay mix 

than they accounted for the proportion of the variance in pay level. Based on this result, the authors 

claimed that firms have more discretion in pay mix than in pay level. 

This study’s first set of hypotheses intends to confirm the effects of firm compensation strategies 

on employee compensation in high-technology firms. It is claimed that high-technology workers are less 

hesitant to change their employers in pursuit of better working conditions (Cappelli, 1999). Due to a 

higher degree of worker mobility, firms may have difficulty in deviating from market pay rates. For pay 

mix, most firms in the high-technology industry had adopted stock-based compensation, and it is regarded 

as the norm in this industry (National Center for Employee Ownership, 2001). Taken together, firms may 

have limited discretion in shaping employee compensation in high-technology industry. Given these 

industry characteristics, it is important to test the effects of firm compensation strategies on employee 

compensation. If firm compensation strategies really play a role in shaping employee compensation, firms 

will exhibit systematic differences in pay level and pay mix after controlling for observable job 

characteristics and firm characteristics, reflecting the differences in firm compensation strategies. 

26

Hypothesis 1a: Employee pay level is systematically different across high-technology firms. 

Hypothesis 1b: Employee pay mix is systematically different across high-technology firms. 

While this study’s primary interest is to test whether or not high-technology firms exhibit 

systematic differences in pay level and pay mix, it is also interested in evaluating the degree to which 

firm-specific effects account for the variance in employee pay level and mix. I will also compare firmspecific 

effects on pay level and those on pay mix to see if firm has more discretion in determining pay 

mix than in determining pay level, as reported by Gerhart and Milkovich (1990). 

Scope of Firm Compensation Strategies 

Within-firm differences. Much of prior research on firm compensation strategies examined 

their effects on compensation for a particular employee group, rather than compensation for the entire 

employees in the firm. The majority of studies examined the effects of firm compensation strategies on 

managerial compensation (Kerr, 1985; Gerhart & Milkovich, 1990).Yet, some studies analyzed other 

employee groups such as research and development employees (R&D) in high-technology firms 

(Yanadori & Marler, 2006), faculty members in research oriented universities (Gomez-Mejia & Balkin, 

1992a), and customer service representatives in call centers (Batt, 2001). 

This line of research claims that firm decision makers pay closer attention to the compensation 

for “strategic employee groups,” employee groups that make critical contributions to firm competitive 

advantage (Gomez-Mejia & Balkin, 1992b: 101; Milkovich, 1988: 266). Given the fact that firm success 

hinges on the performance of strategic employee groups, senior managers elaborate firm compensation 

strategies in such a way that they encourage their strategic employee groups to exhibit desirable behaviors. 

As a result, firm compensation strategies primarily influence the compensation for strategic employee 

groups. To the author’s knowledge, Yanadori and Marler (2006) is the only empirical study that explicitly 

drew upon the notion of strategic employee groups (i.e., R&D employees in high-technology firms); 

nevertheless, aforementioned studies focused on specific employee groups (i.e., R&D employees, faculty 

members, customer service representatives) as they played a critical role in firm effectiveness and thus 

firm compensation strategies were more apparent in their compensation. 

Traditionally strategic employee groups referred to managers as their behavior directly influences 

firm performance irrespective of industry or firm business strategy (Milkovich, 1988). Accordingly 

researchers have typically examined the effects of firm compensation strategies on executive 

compensation (Berkema & Gomez-Mejia, 1998). Recently, researchers have extended this model to 

middle-level managers (e.g., Kerr, 1986) as their contributions to firm effectiveness have been well 

established. Several empirical studies reported that not only senior executives but also middle-level 

managers’ compensation is associated with firm performance (e.g., Gerhart & Milkovich, 1990). If 

managers make up a part of strategic employee groups, firm compensation strategies will influence their 

pay level and pay mix to a greater extent than other employees’ pay level and pay mix. Consequently, I 

hypothesize that firm compensation strategies influence managerial employees’ compensation to a greater 

extent than they influence non-managerial employees’ compensation. 

Hypothesis 2a: Firm-specific effects on pay level are greater for managerial employees’ 

compensation than for non-managerial employee compensation in high-technology firms. 

Hypothesis 2b: Firm-specific effects on pay mix are greater for managerial employees’ compensation 

than for non-managerial employee compensation in high-technology firms. 

As I will subsequently discuss in the method section, this study’s empirical approach does not 

directly measure firm compensation strategies. Rather, consistent with prior studies (Gerhart & Milkovich, 

1990; Gerlach & Stephan, 2006), I estimate firm-specific effects, which I regard reflect firm 

compensation strategies. 

27

On top of middle-level managers, research and development (R&D) employees will make up the 

strategic employee groups in high technology firms as firm success often hinges on innovation (Gomez- 

Mejia & Balkin, 1992b). Admittedly the contributions R&D employees make to their firms could vary 

depending on firm business strategy (e.g., concentrate on innovation, or emphasize marketing); 

nevertheless, research shows that how firms manage their employees that engage in developing 

innovation influences high-technology firms’ performance (Collins & Smith, 2006). Granted, firms will 

carefully develop firm compensation strategies for R&D employees’ compensation and thus firm effects 

will be more apparent for their pay level and mix. It follows that firm effects on pay level and mix for 

R&D employees will be greater than firm effects on pay level and mix for non-R&D employees. 

Hypothesis 3a: Firm-specific effects on pay level are greater for R&D employees’ compensation 

than for other employee groups’ compensation in high-technology firms. 

Hypothesis 3b: Firm-specific effects on pay mix are greater for R&D employees’ compensation than 

for other employee groups’ compensation in high-technology firms. 

Nature of within-firm differences. The research that focused on the compensation for specific 

employee groups appears to assume that firm compensation strategies have a limited influence on the 

compensation for other employee groups. Yet there are also studies that analyzed compensation for all 

employees and identified the influence of firm compensation strategies throughout the firms (Balkin & 

Gomez-Mejia, 1990; Boyd & Salamin, 2001). Hence, extant empirical evidence offers an ambiguous 

picture regarding how firm compensation strategies influence compensation for different employee 

groups in different manners. 

More broadly, the field of human resource management faces a similar theoretical challenge as to 

whether firms apply similar practices to different employee groups or not. A line of strategic human 

resource management research has recognized distinct intra-firm differences in human resource practices, 

which are grounded in the differences in employee contributions to firm competitiveness (Lepak & Snell 

1999, Osterman, 1987). It essentially argues that, given the differences in the type and level of 

contributions different employee groups make to firm competitive advantage, employers form different 

types of employment relationship, adopting different human resource practices. In spite of this argument, 

the majority of strategic human resource management studies captured the entire employees in firms for 

their unit of analysis (e.g., Arthur, 1994; Datta, Guthrie, & Wright, 2005). These studies implicitly 

assumed that similar practices were applied to employees throughout the firms. In short, similar to firm 

compensation strategies, current theory and research are ambiguous as to how firm human resource 

strategies shape human resource practices for different employee groups in different managers. 

In the context of compensation management, assuming that firm compensation strategies 

influence the compensation for strategic employee groups, I contend that firms apply consistent strategies 

to compensation for other employee groups. Equity theory (Adams, 1965) offers a primary underpinning 

for this expectation. This theory claims that individuals compare their pay with their comparators’ and 

they choose various persons for their comparators including their colleagues holding different jobs in the 

same firms. If some groups of employees are paid above the market, while other groups are paid below 

the market, underpaid employee groups may find the situation inequitable and exhibit negative reactions. 

Concerning pay mix, different pay mix arrangements are associated with different level of employee 

income risk (Eisenhardt, 1988). If employees in one group find their compensation is more variable (so 

risky), they may find their firms’ decisions unfair. However, if income risk level is shared in a consistent 

manner across employee groups, such the sense of inequity may be minimized. 

Hence, I propose that firms are likely to apply consistent pay level and mix strategies across 

employee groups. High-technology firms determine compensation strategies for managerial employees 

28

and R&D employees, who are strategic employee groups, and in order to maintain equity across 

employee groups, consistent pay level and mix strategies will be applied to other employees (i.e., nonmanagerial 

employees, non-R&D employees). 

Hypothesis 4a: Firm-specific effects on managerial employees’ pay level are positively associated 

with firm-specific effects on non-managerial employees’ pay level in high-technology firms. 

Hypothesis 4a: Firm-specific effects on managerial employees’ pay mix are positively associated with 

firm-specific effects on non-managerial employees’ pay mix in high-technology firms. 

Hypothesis 5a: Firm-specific effects on R&D employees’ pay level are positively associated with 

firm-specific effects on other employee groups’ pay level in high-technology firms. 

Hypothesis 5a: Firm-specific effects on R&D employees’ pay mix are positively associated with firmspecific 

effects on other employee groups’ pay mix in high-technology firms. 

Overall, I claim that firms differentiate pay level and pay mix strategies among employee groups 

in the sense that these strategies influence different employee groups’ compensation to a different extent. 

Yet, as firms apply consistent pay level and pay mix strategies to their employees within organizations, 

inter-firm differences in pay level and mix are still apparent. 

Data and Variables 

Methods 

Data. This study’s analysis drew upon an employee-level compensation data set collected as a 

part of an annual compensation survey administered to US high technology firms by Clark Consulting, a 

Boston-based consulting company. Clark Consulting aggregates individual employee compensation 

information from participating firms, and provides them with market pay information. 

I analyzed the compensation data in 1997 and 1998. The data in both years include information 

on individual employee compensation from approximately 100 firms, both public and private, operating 

in the high-technology industry. Because the survey is administered annually, firms and employees 

included vary between these two years. I restricted our sample to publicly-traded firms whose firm 

characteristics information is available. The 1997 data set includes compensation information for 82,365 

employees from 73 firms and the 1998 data set includes compensation information for 102,881 

employees from 94 firms. Firm characteristics information was collected from Standard & Poor’s 

COMPUSTAT. 

Table 1 summarizes information about the firms in my data sets. It presents the means of the 

following statistics: number of employees, firm sales (in million dollars), return on assets (ROA, in 

percent), and research and development (R&D) intensity (in percent). The R&D intensity for a firm was 

calculated by dividing R&D expenditure by sales. The high-technology category includes firms with an 

R&D intensity measure that meets the 5.0 percent threshold or exceeds it. As these figures suggest, the 

majority of firms in our dataset were established high-technology firms. 

29

TABLE 1 

Descriptive Statistics 

1997 1998 

data data 

Sales $7,277 million $7,859 million 

Number of employees* 32,279 33,823 

ROA 2.90% 3.63% 

R&D intensity* 12.65% 13.39% 

* N = 73 for the 1997 data set and 94 for the 1998 data set. This information is not available 

for some firms. Mean statstics are calculated among firms with information. 

Dependent variables. I evaluated the extent and nature of firm compensation strategies in two 

aspects of compensation management: pay level and pay mix. For the measure of pay level, I analyzed 

base pay and total pay. Total pay is the sum of base pay, payment from financial incentive plans (i.e., 

profit sharing, stock awards), and various employee benefits. Monetary values of stock awards were 

calculated using Black-Scholes model, and the monetary values of employee benefits represented 

hypothetical values that an employee would need to purchase equivalent plans in the marketplace. 

With respect to pay mix, I examined the ratio of financial incentives to base pay and the ratio of 

long-term pay to short-term pay. The relative emphasis on financial incentives in employee compensation 

has been studied rigorously and their inter-firm differences are well acknowledged (Gerhart & Milkovich, 

1990). Researchers also recognize that firms mix pay components with different time horizons (i.e., shortterm 

pay vs. long-term pay, Gomez-Mejia & Balkin, 1992b; Yanadori & Marler, 2006) in different 

manners. Short-term pay includes base pay, profit sharing, and other short-term incentives, and long-term 

pay includes stock awards. I hereafter refer to these pay mix variables as incentive intensity and long-term 

to short-term ratio, respectively. I applied logarithmic transformation to all pay variables as their 

distributions were skewed. 

Independent variables. I estimated my four pay variables (i.e., base pay, total pay, incentive 

intensity, and long-term to short-term ratio) using six variables. The first variable is region. Many firms in 

the high-technology industry are clustered in specific geographical locations. In this study, I focused on 

the compensation information of employees that worked in one of the following three locations: Silicon 

Valley in California, Austin Texas, and the Route 128 area in Massachusetts. The second variable is job 

level. Our data sets include 8 job levels. Levels 1-5 are professional contributors (= non-managerial 

employees), and level 6-8 are middle-level managers. A higher number represents a higher job level. The 

third variable is job. My data sets consist of employees holding different jobs. The 1997 data set consists 

of employees holding 49 jobs, and the 1998 data set consists of employees holding 55 jobs. The fourth 

variable is firm. The 1997 data set includes pay information from 73 firms, and the 1998 data set includes 

pay information from 94 firms. All these four variables were treated as categorical variables. 

The remaining two variables were related to observable firm characteristics. Past research has 

consistently reported that firm size and performance are key influences on firm pay level and pay mix. I 

used firm sales 1 and return on assets (ROA) as the proxies of firm size and firm performance, respectively. 

Logarithmic transformation was applied to firm sales as its distribution was skewed. 

1 This study did not use the number of employees for the proxy of firm size as Compustat data base does not include 

this information for some firms. We believe that using the number of employee in our analysis would not change our 

results because firm sales and the number of employees was highly correlated in our sample (r = 0.96 for both the 

1997 data set the 1998 data set). 

30

Analysis 

Firm-specific effects on pay level and pay mix. I empirically evaluated the extent to which 

firm explained the variance in pay level and pay mix after controlling for other relevant factors (i.e., 

region, job level, job, firm, firm size, and firm performance). Following previous studies (e.g., Gerhart & 

Milkovich, 1990), I regarded firm-specific effects as the influences of firm compensation strategies. 

In order to understand the firm-specific effects on compensation management, I ran two models. 

The first model estimated fixed firm effects, which are firm-specific effects after controlling for region, 

job level, and job. They essentially represented the degree to which a firm’s pay level or mix deviated 

from a standard firm’s pay level and pay mix. The second model estimated idiosyncratic effects, the 

portion of the fixed firm effects that was not explained by observable firm-level characteristics (i.e., firm 

size and performance; Gerlach & Stephan, 2006). For estimating fixed firm effects, I used the following 

model: 

PDijkm = µ + αi + βj + χk + δm + εijkm (1) 

PDijkm denotes the pay variable (i.e., base pay, total pay, incentive intensity, or long-term to shortterm 

pay) in region i (i = Silicon Valley, Austin, or the Route 128 area), of job level j (j = 1, 2, 3,..8), job 

k (k = 1, 2, 3,…49 for the 1997 data set and 1, 2, 3, …55 for the 1998 data set), in firm m (m = 1, 2, 

3, ..73 for the 1997 data set and 1, 2, 3, ..94 for the 1998 data set). µ is the sample mean, and α, β, χ, and 

δ represent the effects of region, job family, job level, and firm, respectively. I calculated the increases in 

R-squared by adding variables in the following hierarchical order: region, job level, job, and firm. The 

change in R-squared when firm was added to the model was captured as the proportion of the variance 

explained by fixed firm effects. 

For estimating idiosyncratic effects, I used the same model but substituted firm size and firm 

performance variable for the firm categorical variable. Similar to the analysis on fixed firm effects, I 

added independent variables in the order of region, job level, job, and firm size and performance. The 

change in R-squared was calculated when I added firm size and performance, which I regarded the part of 

fixed firm effects that was accounted for by firm size and performance. I then subtracted the change in Rsquared 

attributed to firm size and firm performance from the change in R-squared attributed to fixed firm 

effects. The difference represents the proportion of the variance explained by idiosyncratic effects (i.e., 

fixed firm effects unexplained by firm size or performance). 

I first estimated fixed firm effects and idiosyncratic effects using all observations that included 

employees holding different jobs in different job levels. Next, as I hypothesized the effects of firm 

compensation strategies will be different across employee groups, I estimated firm-specific effects 

according to different employee groups separately. Employees were sorted into either middle-level 

managers (Levels 6 to 8) or non-managerial employees (Levels 1 to 5). Employee jobs (49 jobs in the 

1997 data set and 55 jobs in the 1998 data set) were categorized into three large job families: R&D, 

technical, and administrative. As a result, I estimated firm effects according to six employee groups: R&D 

managers, R&D non-managerial employees, technical managers, technical non-managerial employees, 

administrative managers, and administrative non-managerial employees. 

I expected that the effects of firm compensation strategies to be bigger on managerial 

compensation than on non-managerial employees’ compensation. Likewise, I hypothesized that the 

effects to be bigger on R&D employees’ compensation than on other employees’ compensation. In order 

to test these hypotheses, I estimated the correlation coefficients between compensation variables and firm 

effects by taking the square root of the R-squared calculated in the previous step. I then applied Fisher’s 

z-test (Cohen, Cohen, West, & Aiken, 2003) to examine if the correlation coefficients were significantly 

31

different between managers and non-managerial employees or between R&D employees and other 

employees. 

Consistency across jobs. In order to evaluate the consistency of firm compensation strategies 

across employee groups, I first estimated each firm’s fixed firm effects and idiosyncratic effects on this 

study’s pay variables according to six employee groups. Specifically, fixed firm effects were estimated 

using the model specified in (1). Then I regressed firm size and firm performance on the estimated fixed 

firm effects. The residuals of this regression, interpreted as the portion of fixed firm effects unexplained 

by firm size or performance, were used as the proxy for each firm’s idiosyncratic firm effects. In this 

regression, I took a one-year lag for these two firm characteristics. 

I then calculated the correlation coefficients between the firm effects for managers and nonmanagers 

within job families (i.e., R&D managers vs. R&D non-managerial employees, technical 

managers vs. technical non-managerial employees, and administrative managers vs. administrative nonmanagers) 

to see if firm compensation strategies for managers are associated with those for nonmanagerial 

employees. With respect to consistency across job families, I calculated correlation 

coefficients among R&D employees, technical employees, and administrative employees to see if firm 

compensation strategies for R&D employees are associated with those for technical employees or 

administrative employees. 

Results 

Tables 2a and 2b present the amount of the variance (in percent) in this study’s pay variables 

explained by six independent variables. For each pay variable, I first present the result of the analysis that 

examined all employees, and then I display the results of the analyses on different employee groups. The 

numbers in the column of “Firm” represent the proportion of the variance explained by fixed firm effects. 

The numbers in the column of “Firm effects not explained by firm size or performance” represent the 

proportion of the variance attributable to idiosyncratic firm effects. The interpretation of the results does 

not change according to firm effects used (i.e., fixed-firm effects or idiosyncratic effects). Thus, for the 

ease of discussion, I present my interpretation of the results by focusing on the results of idiosyncratic 

firm effects (i.e., column “Firm effects not explained by firm size or performance”). 

The analyses using all employees show that firms were distinctly different in their pay level and 

pay mix. While the degree varied across variables and between years, idiosyncratic firm effects were all 

significant at the p < 0.001 level. These results supported Hypotheses 1a and 1b. Both pay level and pay 

mix were systematically different across firms, indicating that firms developed distinct compensation 

strategies for their pay level and pay mix. The comparison across pay variables revealed that idiosyncratic 

firm effects explained the variance in pay mix variables (i.e., incentive intensity and long-term to shortterm 

ratio) to a greater extent that they explained the variance in pay level variables (i.e., base pay and 

total pay). This result was consistent with Gerhart and Milkovich (1990). I also found that the proportion 

of the variance in total pay explained by idiosyncratic firm effects were greater than the proportion of the 

variance in base pay explained by idiosyncratic firm effects. This result may suggest that firms in my 

sample took market pay rates into account more seriously when they determined employee base pay level 

than when they determined total pay level. 

Next, I examined the degree to which idiosyncratic firm effects on compensation management 

varies across employee groups. Overall, my hypotheses were supported for the determination of employee 

pay level, but they were not supported for the determination of employee pay mix. Idiosyncratic firm 

effects influenced managerial employees’ pay level to a greater extent than they influenced nonmanagerial 

employees’ pay level. For instance, idiosyncratic effects accounted for 19.54% of the variance 

in R&D managers’ base pay in 1997, whereas they accounted for 7.24% of the variance in R&D non- 

32

managerial employees’ base pay in the same year (z = 13.69, p < 0.001). Likewise, idiosyncratic effects 

accounted for 25.35% of the variance in R&D managers’ total pay in 1997, whereas they accounted for 

12.91% of the variance in administrative non-managerial employees’ total pay in the same year (z = 12.24, 

p < 0.001). This pattern was consistent for the comparisons between technical managers and technical 

non-managerial employees, and comparisons between administrative managers and administrative nonmanagerial 

employees. Idiosyncratic firm effects accounted for significantly greater variance in 

managerial employees’ pay level than they did non-managerial employees’ pay level. The results were 

essentially the same in the analyses of the 1998 data set. Thus, Hypotheses 2a was supported. 

As we hypothesized, idiosyncratic firm effects influenced R&D employees’ pay level to a greater 

extent than other employees’ pay level. For instance, idiosyncratic firm effects accounted for a greater 

proportion of R&D manager’s base pay than technical managers’ base pay (19.54% vs. 13.27%, z = 4.34, 

p < 0.001) and administrative managers’ base pay (19.54% vs. 8.86%, z = 8.11, p < 0.001) in 1997. 

Idiosyncratic firm effects explained a greater proportion of R&D non-managerial employees’ base pay 

than technical non-managerial employees’ base pay (7.24% vs. 3.18%, z = 11.07 , p < 0.001) and 

administrative non-managerial employees’ base pay (7.24% vs. 3.26%, z = 8.75, p < 0.001) in 1997. This 

pattern was consistent for total pay in 1997. The results were essentially consistent for the analyses of the 

1998 data set except that the comparison of idiosyncratic effects on total pay between R&D managers and 

those technical managers (29.51% vs. 28.23%, z = 0.63, p = 0.53). Hence, Hypothesis 3a was supported. 

In contrast, I failed to obtain the strong evidence that shows idiosyncratic firm effects accounted 

for managers’ pay mix than non-managerial employees’ pay mix. In my analyses on the 1997 data set, 

idiosyncratic firm effects generally accounted for the variance in non-managerial employees’ incentive 

intensity to a greater extent than they accounted for the variance in managers’ incentive intensity (22.96% 

for managers vs. 25.87% for non-managerial employees in R&D job family, 22.83% vs. 26.28% within 

technical job family, and 18.77% vs. 31.29% within administrative job family). Although idiosyncratic 

firm effects influenced managers’ pay mix more than non-managers’ pay mix in some occasions (e.g., 

42.73% of R&D managers’ long-term to short-term ratio vs. 32.51% of R&D non-managerial employees’ 

long-term to short-term ratio in 1998, z = 9.86, p < 0.000), my analyses revealed no consistent patterns. 

Thus, I concluded that Hypothesis 2b was not supported. 

Similarly, I did not find the strong evidence for the greater influence of idiosyncratic firm effects 

on R&D employees’ pay mix than on other employees’ pay mix. Hypothesis 3b was not supported. 

Finally, I examined the correlations among fixed firm effects and idiosyncratic firm effects for 

different employee groups. Tables 3A and 3B shows the relationships between firm effects on pay level 

among three job families. Most combinations yielded highly significant correlations. The only exception 

was the correlation between the firm effects on R&D non-managerial employees’ base pay and those on 

administrative non-managerial employees’ base pay in 1998. Tables 4A and 4B present the relationship 

between firm effects on pay mix. All combinations were statistically significant at the p < 0.001 level. 

Table 5 summarizes the correlations between firm effects on managerial employees’ pay level and mix 

and firm effects on non-managerial employees pay level and mix. Correlation coefficients were all highly 

significant, too. From these results, I concluded that firm strategies on pay mix and pay level were 

consistently applied across employee groups. These results offered the support for Hypotheses 4a, 4b, 4c, 

and 4d. Note that my analyses did not establish causal relationship (i.e., compensation strategies for 

managers influence compensation strategies for non-managerial employees, compensation strategies for 

R&D employees influence compensation strategies). My analyses simply revealed that firm compensation 

strategies were applied consistently across employee groups. 

33

Pay variable 

TABLE 2A 

Firm Effects on Compnesation Management in 1997 

Percent of variance attributable to: 

Region Job level Job family Firm 

Firm size and 

performance 

Firm effects not 

explained by 

firm size or 

performance 

Error Total 

Base pay All employees 7.47% 65.25% 7.20% 3.22% 0.07% 3.15% 16.86% 100.00% 

R&D Managers 16.37% 34.51% 1.20% 19.73% 0.19% 19.54% 28.19% 100.00% 

R&D Non-managers 11.61% 61.94% 0.70% 7.98% 0.74% 7.24% 17.78% 100.00% 

Technical Managers 8.02% 36.93% 6.29% 14.68% 1.41% 13.27% 34.08% 100.00% 

Technical Non-managers 10.00% 61.85% 3.36% 3.26% 0.08% 3.18% 21.53% 100.00% 

Administrative Managers 7.84% 47.27% 5.05% 9.87% 1.00% 8.86% 29.98% 100.00% 

Administrative Non-managers 4.34% 52.06% 15.70% 3.61% 0.35% 3.26% 24.30% 100.00% 

Total pay All employees 7.70% 55.86% 5.25% 11.88% 4.22% 7.66% 19.32% 100.00% 

R&D Managers 9.70% 23.30% 2.22% 36.44% 11.09% 25.35% 28.34% 100.00% 


Technical Managers 5.32% 26.61% 7.30% 27.77% 6.32% 21.45% 33.00% 100.00% 


Administrative Managers 8.62% 36.80% 6.54% 23.67% 8.70% 14.97% 24.37% 100.00% 


Incentive All employees 10.92% 6.79% 4.65% 39.11% 16.01% 23.09% 38.53% 100.00% 

intensity R&D Managers 6.66% 4.38% 5.40% 38.89% 15.92% 22.96% 44.67% 100.00% 





Administrative Non-managers 18.96% 2.14% 4.52% 48.40% 17.10% 31.29% 25.99% 100.00% 

Long-term All employees 2.84% 6.58% 5.77% 40.20% 17.93% 22.27% 44.61% 100.00% 

to short-term R&D Managers 2.03% 2.92% 4.73% 50.08% 21.25% 28.83% 40.24% 100.00% 

ratio R&D Non-managers 3.72% 1.65% 5.20% 45.54% 22.52% 23.02% 43.89% 100.00% 





N = 82,365 for overall, 5,452 for R&D managers, 36,322 for R&D non-managers, 3,634 for technical managers, 21,252 for technical non-managers, 4,094 for administrative 

managers, and 11,601 for administrative non-managers 

34

Pay variable 

TABLE 2B 

Firm Effects on Compnesation Management in 1998 

Percent of variance attributable to: 

Region Job level Job family Firm 

Firm size and 

performance 

Firm effects not 

explained by 

firm size or 

performance 

Error Total 

Base pay All employees 6.95% 67.45% 6.42% 2.45% 0.02% 2.43% 16.73% 100.00% 

R&D Managers 18.65% 28.08% 1.43% 21.92% 0.21% 21.72% 29.91% 100.00% 






Total pay All employees 7.32% 57.19% 4.88% 9.88% 0.98% 8.90% 20.73% 100.00% 

R&D Managers 9.46% 19.41% 1.50% 34.97% 5.81% 29.15% 34.67% 100.00% 






Incentive All employees 9.43% 7.53% 4.12% 39.94% 4.53% 35.41% 38.98% 100.00% 

intensity R&D Managers 2.03% 6.38% 8.60% 45.58% 7.34% 38.24% 37.41% 100.00% 



Technical Non-managers 8.54% 1.65% 6.21% 43.30% 4.10% 39.20% 40.29% 100.00% 



Long-term All employees 5.68% 7.65% 4.88% 33.87% 4.79% 29.08% 47.91% 100.00% 

to short-term R&D Managers 5.19% 3.10% 2.91% 47.52% 4.79% 42.73% 41.29% 100.00% 

ratio R&D Non-managers 8.06% 2.15% 5.08% 40.58% 8.07% 32.51% 44.13% 100.00% 

Technical Managers 5.29% 2.53% 3.93% 40.94% 1.42% 39.52% 47.31% 100.00% 




N = 82,365 for overall, 5,452 for R&D managers, 36,322 for R&D non-managers, 3,634 for technical managers, 21,252 for technical non-managers, 4,094 for administrative 

managers, and 11,601 for administrative non-managers 

35

TABLE 3A TABLE 3B 

Conherence across Job Families Conherence of Pay Level Strategy 

Managerial Pay Level Non-managerial Pay Level 

Job family A R&D Technical Admin. Job family A R&D Technical Admin. 

Job family B Job family B 

R&D Fixed firm effects Base pay - 0.59*** 0.67*** R&D Fixed firm effects Base pay - 0.50*** 0.00 

Total pay - 0.81*** 0.79*** Total pay - 0.74*** 0.59*** 

Idiosyncratic firm Base pay - 0.59*** 0.68*** Idiosyncratic firm Base pay - 0.50*** 0.10 

effects Total pay - 0.78*** 0.77*** effects Total pay - 0.74*** 0.64*** 

Technical Fixed firm effects Base pay 0.70*** - 0.65*** Technical Fixed firm effects Base pay 0.66*** - 0.47*** 

Total pay 0.68*** - 0.78*** Total pay 0.90*** - 0.80*** 

0.50*** 

Idiosyncratic firm Base pay 0.73*** - 0.64*** Idiosyncratic firm Base pay 0.68*** - 0.81*** 

effects Total pay 0.71*** - 0.76*** effects Total pay 0.90*** - - 

Admin. Fixed firm effects Base pay 0.41** 0.34** - Admin. Fixed firm effects Base pay 0.33** 0.59*** - 

Total pay 0.85*** 0.59*** - Total pay 0.79*** 0.91*** - 

Idiosyncratic firm Base pay 0.42** 0.31* - Idiosyncratic firm Base pay 0.44*** 0.63*** - 

effects Total pay 0.84*** 0.54*** - effects Total pay 0.83*** 0.92*** - 

Values below the diagonal are based on the analysis on the 1997 data set and above are based on the analysis on the 1998 data set. 

N ranges from 54 to 64 in the 1997 data set and from 67 to 88 in the 1998 data set, depending on combinations. 

*** p < 0.001, ** p < 0.01, * < 0.05. 

TABLE 4A TABLE 4B 

Conherence across Job Families Conherence of Pay Level Strategy 

Managerial Pay Mix Non-managerial Pay Mix 

Job family A R&D Technical Admin. Job family A R&D Technical Admin. 

Job family B Job family B 

R&D Fixed firm effects Incentive intensity - 0.82*** 0.86*** R&D Fixed firm effects Incentive intensity - 0.87*** 0.82*** 

Long-term to - 0.84*** 0.86*** Long-term to - 0.88*** 0.83*** 

short-term ratio short-term ratio 

Idiosyncratic firm Incentive intensity - 0.81*** 0.86*** Idiosyncratic firm Incentive intensity - 0.86*** 0.82*** 

effects Long-term to - 0.82*** 0.85*** effects Long-term to - 0.87*** 0.81*** 


Technical Fixed firm effects Incentive intensity 0.69*** - 0.84*** Technical Fixed firm effects Incentive intensity 0.91*** - 0.94*** 

Long-term to 0.80*** - 0.83*** Long-term to 0.93*** - 0.93*** 


Idiosyncratic firm Incentive intensity 0.67*** - 0.84*** Idiosyncratic firm Incentive intensity 0.90*** - 0.94*** 

effects Long-term to 0.79*** - 0.83*** effects Long-term to 0.92*** - 0.92*** 


Admin. Fixed firm effects Incentive intensity 0.86*** 0.78*** - Admin. Fixed firm effects Incentive intensity 0.90*** 0.97*** - 

Long-term to 0.87*** 0.83*** - Long-term to 0.89*** 0.96*** - 


Idiosyncratic firm Incentive intensity 0.84*** 0.74*** - Idiosyncratic firm Incentive intensity 0.89*** 0.97*** - 

effects Long-term to 0.85*** 0.82*** - effects Long-term to 0.87*** 0.95*** - 


Values below the diagonal are based on the analysis on the 1997 data set and above are based on the analysis on the 1998 data set. 

N ranges from 54 to 64 in the 1997 data set and from 67 to 88 in the 1998 data set, depending on combinations. 

*** p < 0.001 

36

TABLE 5 

Conherence between Managers and Non-managers 

Pay level Pay mix 

Job family Base pay Total pay Incentive intensity Long-term to 

short-term ratio 

1997 1998 1997 1998 1997 1998 1997 1998 

R&D Fixed firm effects 0.55*** 0.66*** 0.73*** 0.80*** 0.80*** 0.87*** 0.83*** 0.89*** 

Idiosyncratic firm 0.55*** 0.66*** 0.73*** 0.78*** 0.78*** 0.86*** 0.81*** 0.88*** 

effects 

Technical Gross firm effects 0.38** 0.36** 0.65*** 0.67*** 0.77*** 0.79*** 0.75*** 0.75*** 

Idiosyncratic firm 0.40** 0.37*** 0.63*** 0.64*** 0.73*** 0.78*** 0.71*** 0.75*** 

effects 

Admin. Gross firm effects 0.41*** 0.48*** 0.66** 0.73*** 0.79*** 0.83*** 0.75*** 0.75*** 

Idiosyncratic firm 0.40** 0.45*** 0.62*** 0.73*** 0.77*** 0.83*** 0.71*** 0.74*** 

effects 

N ranges from 54 to 64 for the 1997 data set and 74-80 for the 1998 data set, depending on combinations. 

*** p < 0.001, ** p < 0.01. 

Discussion and Conclusion 

Consistent with prior compensation studies, this study confirmed firm specific effects on 

employee pay level and pay mix. After controlling for job characteristics (i.e., job level, job) and firm 

characteristics (i.e., size and performance), firm exhibited distinct differences in their employee pay level 

and mix. This study argues that the observed firm-specific effects reflected firm compensation strategies. 

This study further found that firm specific effects had a greater influence on the pay level for 

strategic employee groups, managers and R&D employees in our sample, than other employee groups. 

This supported this study’s one of key arguments that firm compensation strategies will influence 

compensation for strategic employee groups to a greater extent than they will influence compensation for 

other employee groups. In contrast, I failed to obtain the strong evidence to support the argument that 

firm compensation strategies influence strategic employees’ pay mix to a greater extent that they do other 

employees’ pay mix. 

Compensation research, as well as strategic human resource management research, has been 

ambiguous as to how firm compensation strategies influence different employee groups in different 

manners. My empirical analyses revealed that firms developed consistent pay level and pay mix strategies 

across employee groups. If a firm pays above the market pay rates for one employee group (e.g., R&D 

employees), the firm also pays above the market above pay rates for other employee groups (e.g., 

technical employees, administrative employees). Likewise, if a firm emphasizes financial incentives for 

one employee group, the firm also emphasizes financial incentives for other employee groups. While my 

analyses were not sufficient to establish the causal direction, this study’s findings are consistent with my 

contention that firms determine the pay level strategies for strategic employee groups first, and then they 

mirror them to develop the pay level strategies for other employees. Although my analyses showed the 

strong correlations among pay mix strategies for different employee groups within firms, I obtained weak 

evidence to support my contention that firm pay mix strategies will influence strategic employee groups 

the most, and thus I am unable to interpret that firm pay mix strategies will influence strategic employee 

groups first and then they will apply similar pay mix strategies to other employee groups. 

37

In this manner, this study’s model was well supported for pay level, whereas it received mixed 

support for pay mix. This may suggest that the way firms develop and apply compensation strategies may 

be different between pay level and pay mix. Given the fact that firm effects are greater for pay mix (e.g., 

23.09% for idiosyncratic firm effects on incentive intensity in 1997) than pay level (e.g., 7.66% for 

idiosyncratic firm effects on total pay in the same year), pay mix may be more strategic and thus warrant 

more firm discretion. As a result, firms may develop their firms’ overall pay mix strategies first, and 

apply the strategies to all employee groups consistently. In contrasts, pay level is traditionally determined 

by comparing internal structure with relevant market pay rates, and this comparison is typically conducted 

according to employee groups (Milkovich & Newman, 2008). As a result, firm pay level strategies tend to 

be segmented according to job families. In fact, the correlation coefficients among firm pay mix strategies 

for different employee groups were generally higher than those among firm pay level strategies for 

different employee groups (Tables 4a, 4b, and 5). Admittedly, this is nothing but one possibility, and thus 

more careful empirical analyses will be necessarily to better understand the extent and nature of firm pay 

level strategies and pay mix strategies. 

In conclusion, this study makes the first step to understand how firm compensation strategies 

influence employee pay level and mix for different employee groups in different manners. While its 

analyses revealed some important phenomena, they also posed a new question, which is concerned with 

the possible differences in the nature and extent between pay level strategies and pay mix strategies. More 

empirical studies are needed to answer this question. 

References 

Arthur, J .B. (1998). Effects of human resource systems on manufacturing performance and turnover. 

Academy of Management Journal, 37: 670-687. 

Adams, J. S. (1965). Inequity in social exchange. In L. Berkowitz (ed.) Advances in experimental social 

psychology. New York: Academic Press. 

Balkin D. B., & Gomez-Mejia, L. R. (1987). Toward a contingency theory of compensation strategy. 

Strategic Management Journal, 8: 169-182. 

Balkin D. B., & Gomez-Mejia, L. R. (1990). Matching compensation and organizational strategies. 


Batt, R. (2001). Explaining wage inequality in telecommunications services: customer segmentation, 

human resource practices, and union decline. Industrial and Labor Relations Review, 54: 425-449. 

Berkema, H. G., & Gomez-Mejia, L .R. (1998). Managerial compensation and firm performance: a 

general research framework. Academy of Management Journal, 41: 135-145. 

Boyd, B. K., & Salamin, A. (2001). Strategic reward systems: A contingency model of pay system design. 


Cappelli, Peter. (1999). Career jobs are dead. California Management Review, 42: 146-167. 

Chandler, A. D., Jr. (1962). Strategy and structure. Cambridge, MA: MIT Press. 

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis 

for the behavioral sciences (3 rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates. 

38

Collins, C. J., & Smith, K. G. (2006). Knowledge exchange and combinations: the role of human resource 

practices in the performance of high-technology firms. Academy of Management Journal, 49: 544- 

560. 

Datta, D. K., Guthrie, J. P., & Wright, P. M. (2005). Human resource management and labor productivity: 

does industry matter? Academy of Management Journal, 48: 135-145. 

Eisenhardt, K. M. (1989). Agency- and institutional-theory explanations: The case of retail sales 

compensation. Academy of Management Journal, 31: 488-511. 

Gerhart, B. (2000). Compensation strategy and organizational performance. In S. Rynes and B. Gerhart 

(Eds.), Compensation in organizations. San Francisco, CA: Jossey-Bass. 

Gehart, B., & Milkovich, G. T. (1990). Organizational differences in managerial compensation and 

financial performance. Academy of Management Journal, 33: 663-691. 

Gerhart, B., & Rynes, S. L. (2003). Compensation: Theory, evidence, and strategic implications. 

Thousand Oak, CA: Sage. 

Gomez-Mejia, L.R., & Balkin, D. B. (1992a). Determinants of faculty pay: An agency theory perspective. 

Academy of Management Journal, 35: 921-955. 

Gomez-Mejia, L.R., & Balkin, D. B. (1992b). Compensation, organizational strategy, and firm 

performance. South-Western: Cincinnati. 

Groshen, E. (1991). Sources of intra-industry wage dispersion: how much do employers matter? 

Quarterly Journal of Economics, 106: 869-885. 

Gerlach, K, & Stephan, S. (2006). Pay Policies of Firms and Collective Wage Contracts – An Uneasy 

Partnership? Industrial Relations, 45: 47-67. 

Kerr, J. (1985). Diversification strategies and managerial rewards: an empirical study. Academy of 

Management Journal, 16: 155-179. 

Lepak, D. P., & Snell, S. A. (1999). The human resource architecture: Toward a theory of human capital 

allocation and development. Academy of Management Review, 24: 31-48. 

Milkovich, G. T. (1988). A strategic perspective on compensation management. In G. R. Ferris, & K. M. 

Rowland (Eds.).Research in Personnel and Human Resources Management, Vol. 6: 263-288. 

Greenwich CT: JAI Press. 

Milkovich, G. T., & Newman, J. (2008). Compensation (9 th ed.). New York: McGraw-Hill. 

National Center for Employee Ownership (2001). Current practices in stock option plan design. Oakland, 

CA. 

Osterman, P. (1987). Choice of employment systems in internal labor markets. Industrial Relations, 26: 

46-67. 

Yanadori, Y., & Marler, J. H. (2006). Compensation strategy: does business strategy influence 

compensation in high-technology firms? Strategic Management Journal, 27: 559-570. 

39

ASAC 2008 Janice Foley 

Halifax, Nova Scotia 

Faculty of Business Administration 

University of Regina 

CAN THE DIVERSITY LITERATURE HELP BUSINESS SCHOOLS 

ADDRESS THEIR RELEVANCE CRISIS? 

According to Volume 50, Issues 4 - 6 of the Academy of 

Management Journal, some influential members of the Academy 

perceive that business schools are currently facing a severe crisis of 

legitimacy in the eyes of their stakeholders. In this paper I propose 

that the diversity literature may be of some assistance in 

determining how to move forward. 

Introduction 

Some of the most prestigious of the Academy’s members weighed in on the Editors’ 

Forums “Research With Relevance to Practice” (Issue 4), “The Research-Practice Gap in Human 

Resource Management” (Issue 5) and “AMJ Turns 50! Looking Back and Looking Ahead,” all 

suggesting that all is not well in business schools today. Legitimacy has long been a problem for 

business schools (Pfeffer and Wong, 2002) but what appears to have provoked the current rash of 

commentary is the perception that business schools have failed in their mission to improve 

management practice through their research and education activities. As a consequence they 

have become increasingly vulnerable to encroachments into their “turf” by competitors from 

outside the Academy. Osborne and Cowen (1995: 28) commented over a decade ago that 

business schools were heading for a “train-wreck” and might eventually become “expensive 

engines pulling passengerless trains.” While this has not yet come to pass, some concern about 

the future of business schools may be warranted. 

The concerns expressed in the Editors’ Forums can be summarized as: business schools’ 

failure to meet the expectations of their stakeholders, comprised of students, employers, and the 

broader society, with respect to delivering relevant management education and producing 

research insights that improve management practice; and a deficient academic system that is 

institutionalized and therefore resistant to change, that promotes a rigid view of what constitutes 

acceptable scholarship, thus contributing to teaching and research outputs that may not serve the 

public good. 

These problems are not likely to bring about the imminent demise of business schools. 

But commentators warn that it is likely that business schools are going to have to start proving 

their worth to an increasingly skeptical public if they are to continue to enjoy their current status 

(McGrath, 2007). That means they will have to hone their capacity to change as required to meet 

expectations (Osborne and Cowen, 1995; Trank and Rynes, 2003). The pressure for business 

schools to become learning organizations that welcome and encourage diversity is growing. 

40

Canadian business schools will not be exempt from these pressures, and a proactive approach to 

head off emergent problems seems appropriate. 

Hence, this paper will summarize what has given rise to the concerns expressed, and the 

proposed solutions. Then insights from the diversity literature will be drawn upon to assess 

business schools’ current ability to change, and the obstacles that are likely to present themselves 

if they make the attempt. 

A Brief Description of the Perceived Problems facing today’s Business Schools 

As indicated, there are two categories of problems that are perceived to be contributing to 

the legitimacy crisis currently facing business schools. The first is the failure to meet stakeholder 

expectations. 

Failure to Meet Stakeholder Expectations 

According to the current and past contributors to the discussion on this topic, blame has 

been laid on business schools for first, failing to deliver a management curriculum to students 

that makes them ethical and effective managers, and further, for selling MBA degrees as a way 

to enhance personal career success rather than to acquire or enhance management skills (Pfeffer 

and Fong, 2002; 2004). Although the evidence does not support the myth of career-enhancement, 

the marketing ploy has been so successful that “learning” does not appear to motivate the typical 

MBA student (Pfeffer and Fong, 2002). Business schools have given in to student demands, 

making curricular changes that are indefensible on pedagogical grounds, such as dumbing down 

course content and raising average grades in the interests of improving school or individual 

professor rankings (Zell, 2001). As a consequence they can be criticized for failing to protect the 

public welfare by churning out incompetent managers, and not acting in the long-term best 

interests of students. 

Other criticisms have also been levied on business school curricula (Mintzberg, 2004; 

Porter and McKibbin, 1988), for instance excess emphasis on analysis rather than “problemfinding, 

lack of integration across disciplinary lines, and inadequate attention to implementation 

or the development of “soft” skills. The claim has also been made that “bad” theory is taught 

(Ghoshal, 2005) that reinforces a highly negative view of human behavior, encourages 

pathological management practice and discourages ethical management practice. Thus he and 

others (Mitroff, 2004) contend that business schools have contributed to the corporate scandals 

that have recently come to light. Hence what is, or is not, being taught in business schools is 

having serious repercussions for students, for their employers, and ultimately for society. 

From the perspective of practicing managers, business school research is generally 

irrelevant with few, if any, really interesting management advances initiated by business school 

faculty (Cohen 2007). Rarely are research topics of great interest to practitioners (Pfeffer, 2007), 

but even where they are, the academic penchant for conducting “rigorous” scientific studies does 

not produce timely findings, or findings that resonate with practitioners’ experience. Nor do the 

academic journals effectively communicate findings to practitioners, who are reported to be 

more influenced by simpler, less rigourous studies conducted by non-academics (Cohen, 2007; 

41

Vermeulen, 2007) than they are by studies produced by more credible, academic researchers. 

They are also influenced by emotional appeals (Bartunek, 2007), which are absent from most 

academic work. Theories published that do bridge the academic-practitioner divide are 

essentially untested (Hambrick, 2007). While they do inform practice, the existence of 

competing theories carrying contradictory prescriptions for action lessen their utility (Ghoshal, 

2005). 

Perhaps because of these difficulties, as well as business schools’ failure to articulate and 

defend the notion that a particular body of knowledge underpins the practice of management 

(Pfeffer and Fong, 2004; Trank and Rynes, 2003), practitioners have grown more inclined to see 

business education as a commodity that can be easily packaged for purchase or sale (Trank and 

Rynes, 2003). As schools have grown increasingly dependent on corporate funding for their 

operational needs, this idea may have contributed to the growing sense that business schools are 

not essential to the delivery of business training or to the improvement of management practice 

through research. 

The Failures of the Academic System 

The general accusation lodged against the academic system is that it discourages the 

search for relevance, which results in the failure to meet stakeholder expectations (Cornuel, 

2005). One contributing factor is the increasing funding shortfalls facing universities as a result 

of government cutbacks, which have brought about many changes which have had severe 

repercussions for business programs and faculty members. A second is the way doctoral students 

are selected, socialized and rewarded. 

The immediate result of the funding shortfalls has been that business schools have been 

forced to seek out external funding sources to cover operating expenses, and the most lucrative 

source has been business corporations. As a result of the infusion of funds from corporations, 

business schools have been exposed to increasing pressure to meet corporate demands for 

relevance, for commodification of educational programming, and for the development of 

vocational rather than professional skills in the classroom (Trank and Rynes, 2003). Schools 

have also expanded graduate programs to generate additional tuition revenues, which has 

diverted resources away from undergraduate and doctoral training (Trank and Rynes, 2003) and 

introduced students into graduate programs who arguably lack the academic preparation to be 

there. This has exerted downward pressure on academic standards, deprofessionalized course 

content and inflated grades (Zell, 2001), all in the interests of meeting student demands and 

influencing media , so as not to jeopardize enrollment numbers and tuition revenues. Student 

evaluations which are being taken seriously by Deans when evaluating academics’ performance, 

are reinforcing these trends. 

What is important to notice in all this is that business schools’ responses to these funding 

shortfalls have not been guided by any concern over the outcomes of the initiatives introduced 

(Pfeffer and Fong, 2002), for instance the caliber of the students that have been credentialed, or 

the social consequences of having poorly trained or unethical managers running business 

enterprises. Even AACSB accreditation does not ensure that a business school delivers quality 

education (McGrath, 2007; Trank and Rynes, 2003) because there is no consensus within the 

42

management academy about what “quality” means, or what constitutes the body of professional 

management knowledge that students need to master prior to graduation. It is felt that this has 

put business schools even more at the mercy of market pressures (Trank and Rynes, 2003). 

A second failure of the academic system, as mentioned, relates to the way doctoral 

students are selected, socialized to the job, and rewarded. For example, doctoral students are 

rarely recruited from practitioner ranks, and may have little if any work experience. As a 

consequence, they may not have much understanding of, or interest in, the practical issues that 

managers face (Pfeffer and Fong, 2002). Their primary mandate, throughout their training, is to 

learn how to do research that will meet the rigorous standards set by the top management 

journals (Agarwal and Roetker, 2007; Ghoshal, 2005; Rynes, 2007a). Developing teaching skills 

is deemed of secondary importance. 

The research they produce is expected to conform to the North American model (Ghoshal, 

2005; Markides, 2007; Pfeffer, 2007) in order to be publishable in the top management journals. 

This model emphasizes the scientific method and a logical positivist research epistemology, and 

is grounded in the literature of a single discipline. Students are taught to avoid research that is 

not geared to theory building, that is multi-disciplinary, that covers topics that might be 

controversial, or that might have managerial relevance (Mitroff, 2004; Vermeulen, 2007). The 

fact that qualitative methods produce more “interesting” findings (Rynes, 2007b), that this model 

may be unsuited to the development of social theory (Ghoshal, 2005), and that it may inhibit 

theory-building that is context-sensitive, which is deemed to be increasingly necessary in a 

global world (Tsui, 2007), has not lessened the model’s influence within the Academy. 

Vermeulen (2007) suggests that research irrelevance may be attributable to the belief held by the 

“silent majority” that relevance compromises scientific objectivity. 

Pursuing the other forms of scholarship identified by Boyer (1990), such as the 

integration or application of research findings, and their dissemination through teaching, bars 

academics from the “high table” (Ghoshal, 2005) as they have value only on the fringes of the 

Academy. So desires for status and publishing opportunities create tremendous pressures for 

students seeking jobs and faculty members seeking tenure, to adopt and conform to the North 

American model, which is the dominant model internationally, throughout the early stages of 

their careers. If socialization is successful, by the time tenure is achieved this model has been 

deeply entrenched. 

The result is that academics currently place the ability to use mathematical models to 

produce testable propositions above the need to generate “truth” (Ghoshal, 2005: 81). Their 

“irrelevant” but scientifically rigorous research produces theories that are rarely, if ever, tested 

(Hambrick, 2007; Pfeffer, 2007). The same phenomena carry different labels and offer different 

prescriptions for practice (Ghoshal, 2005). The importance of teaching is deemphasized – at least 

until instructors run afoul of their student “customers.” And a narrow view of scholarship is 

absorbed that makes it unacceptable to spend time in ways that would benefit practitioners. 

It is little wonder then that students are able to question the return on their investment in a 

business degree, and that practicing managers turn to non-academic sources to gain insight into 

how to address their problems. 

43

The Proposed Solutions to the Crisis 

Many of the solutions proposed to correct these problems were fairly straightforward. As 

lack of relevance in both teaching and research was largely attributed to the academic system and 

the behaviours it encourages, suggestions were made to change the way doctoral students were 

recruited, for instance by selecting them from the ranks of practicing manages (Ghoshal, 2005; 

Pfeffer and Fong, 2002). In terms of doctoral training, there were recommendations that the 

Academy should broaden its views of what contributes to knowledge (Ghoshal, 2005; March, 

2005), and what are acceptable forms of scholarship (Bartunek, 2007; Markides, 2007; 

Vermeulen, 2007) to include the development of practical understanding based on “disciplined 

imagination” rather than “formalized falsification” (Ghoshal, 2005). Reward systems should be 

revised to encourage “conceptual diversity” (March, 2005; Pfeffer and Fong, 2002). To increase 

relevance, impact on managerial practice could be included in the evaluation criteria for tenure 

decisions (McGrath, 2007). 

The research enterprise was singled out for major overhaul. It was seen as necessary for 

management researchers to recommit to the disinterested search for knowledge and an improved 

understanding of management phenomena (Pfeffer and Fong, 2004; Starkey et al., 2004). 

Research should focus on important problems (Pfeffer and Fong, 2002) and practitioners should 

be included in the research process, from the definition of research questions, through to the 

discussion of implications for practice (Bartunek, 2007; Ghoshal, 2005; Vermeulen, 2007). 

Theory-testing as well as theory-building needed to be embraced (Hambrick, 2007; March, 2004). 

Journals had to become more open to publishing “interesting facts” for which no explanatory 

theory was available but that might have potential consequence (Hambrick, 2007), and to 

publishing controversial finding and studies that found no significant effects (Pfeffer, 2007). 

Journal articles could feature expanded “Implications for Practice” sections. 

The value of studies conducted outside the traditions of the North American model 

needed to be recognized. That model had to become less restrictive, to allow deep 

contextualizing of findings (Tsui, 2007) and to increase the legitimacy of field research 

(McGrath, 2007) as well as encourage cross-disciplinary work (Mitroff, 2004; Osborne and 

Cowen, 1995). Pluralism with respect to theory, methods, and research questions needed to be 

relegitimized (Ghoshal, 2005; Tsui, 2007). Novel ways of disseminating research findings, such 

as publishing in practitioner journals and books, writing textbooks and case studies, and 

participating in talk shows or making videos were proposed as ways to broaden researchers’ 

impact on practitioners (Bartunek, 2007; McGrath, 2007). 

One of the suggestions advanced for changing the research enterprise also addressed the 

problems associated with management education. Klimoski (2007) suggested that the Academy 

should encourage research regarding the desired outcomes of management education, and what 

kinds and amounts of learning students needed to perform well in class and on the job. Many of 

the contributors felt it was necessary to articulate the field of knowledge that defined 

professional management (McGrath, 2007; Pfeffer and Fong, 2004; Trank and Rynes, 2003) in 

order to fulfill what some felt was the primary mission of business schools, the passing on of 

such knowledge (McGrath, 2007; Pfeffer and Fong, 2004). Curricular reform could then be 

guided by an understanding of what is necessary to improve professional practice (Pfeffer and 

44

Fong, 2002) rather than by the dictates of the market (Trank and Rynes, 2003). There was some 

agreement on the need for training in ethics and corporate social responsibility (Ghoshal, 2005; 

McGrath, 2007; Osborne and Cowen, 1995; Trank and Rynes, 2003; Zell, 2001), and Cornuel 

(2005) suggested that business education should also prepare students to become innovative 

leaders. The need to specify metrics to permit assessment of learning outcomes was noted 

(Klimoski, 2007; Pfeffer and Fong, 2002; Trank and Rynes, 2003). 

Some general suggestions were made for business schools. One was that they should 

clarify their core purpose (Pfeffer amd Fong, 2004) and stop participating in the oversimplification 

of business knowledge in the interests of profit (Trank and Rynes, 2003). They 

could start serving niche markets, to reduce competition between school (Zell, 2001). They were 

advised to model themselves on other professional schools and return to their roots as university 

departments with educational and research responsibilities, as well as responsibilities to the 

public to exercise “due diligence” (Trank and Rynes, 2003) concerning the social consequences 

of management practice (Pfeffer and Fong, 2002; 2004) in order to differentiate themselves from 

their competitors. One blunt recommendation was that business schools had to “become learning 

organizations - or else” (Osborne and Cowen, 1995: 28). 

Several contributors directly advanced the notion that greater diversity within business 

schools was needed in order to serve all stakeholders better. Greenberg et al. (2007: 454) 

proposed that students would benefits from “diverse professors who are guided by diverse 

interpretive frames of their roles,” while Bennis and O’Toole (2005) emphasized the need for 

skill variety and different perspectives. In regard to the improvement of research, March (2005: 

16) argued against the requirement to conform to a particular research paradigm, noting that 

“…it is what [scholars] do not share that makes [discourse] valuable.” Emphasizing that point, 

Agarwal and Hoetker (2007: 1318) observed that “…diversity of thought… of design… theories 

and methodologies introduced by scholars from related disciplines” were all valuable to the 

evolution of particular disciplines and the field of management. But they went on to 

acknowledge one of the major problems with implementing any of the recommendations 

proposed above, that “the extent to which the value is captured depends on the ability of our 

discipline to assimilate relevant perspectives, which itself relates to whether consensus exists on 

the value of a disciplined integration of multiple perspectives.” 

According to Lawler (2007) and others (Bartunek, 2007; Hambrick, 2007; Pfeffer, 2007), 

this consensus does not currently exist within the Academy and business schools have shown 

little sign of wanting to change their approach to research. Members of the “academic high table” 

(Ghoshal, 2005) have internalized the existing rules (Pfeffer, 2007) and are likely to be heavily 

represented on journal review boards and tenure committees, and within the senior faculty, 

where they help to reproduce the academic system by socializing new entrants into conformity 

with the North American research model. Any change in the status quo is likely to impose costs 

on the senior faculty (Markides, 2007), and the schools that are currently winning the ratings 

game have no incentive to change (Pfeffer and Fong, 2002). 

Other problems have been identified as well. The demand for relevance in research and 

teaching is a new burden for a professoriate that is already over-extended (Pfeffer and Fong, 

2002). The resources needed to support a change in emphasis (Ghoshal, 2005) are unlikely to 

45

materialize when the funding shortfalls that gave voice to demands for relevance still exist, and 

external competition for business education dollars is increasing. There is a deep-seated bias 

against pursuing relevance as it is perceived to be antithetical to the advancement of scientific 

knowledge (Vermeulen, 2007). Opposing viewpoints exist regarding whether there is an 

excessive focus on theory-building (Hambrick, 2007), whether it would be desirable to 

incorporate multiple perspectives when building theory (Agarwal and Hoetker, 2007), whether 

adopting a pluralistic approach to scholarship would be acceptable, what constitutes 

“professional” management education, and what responsibility the professoriate has to prevent 

unscrupulous management practice (Trank and Rynes, 2003: 199). 

Osborne and Cowen (1995: 29) articulate the need for businesses to change their 

emphases from bottom-line thinking and concern for shareholders to “the entire ecology of 

human enterprise – energy, conservation, environment, and justice efficacies.” Business schools 

have a role to play in ensuring these outcomes materialize. The competencies embodied in the 

Academy, such as how to encourage organizational innovation (Pfeffer, 2007), how to establish 

educational standards, and how to create and evaluate “truth” (McGrath, 2007), constitute potent 

resources to draw upon in ensuring better outcomes materialize. But creativity is needed to find 

ways to reconcile the wide variety of opinions regarding what is desirable, in order to establish a 

shared vision for the future. 

Currently, according to Ghoshal (2005: 82), non-paradigm-following scholars have been 

“[eliminated] from our milieu or, at best, [accommodated] at the periphery.” March (2005: 20) 

believes that the future of the field lies with those “ambivalent scholars” at the periphery, 

possibly because they have less invested in the dominant research paradigm. Therefore, 

capitalizing on the diverse views that already exist within the professoriate, recognizing and 

legitimizing the work of scholars who currently operate outside the existing research paradigm, 

and validating the generation of common sense-based knowledge and critical theories (March, 

2005) would appear to be helpful steps. Long-range thinking is being encouraged to ensure that 

the best interests of students, business and society are met (Ghoshal, 2005; McGrath, 2007; 

Pfeffer and Fong, 2002; 2004; Trank and Rynes, 2003), and that business schools enhance their 

perceived usefulness. 

Since the general diversity literature explores how the benefits of diversity can be 

captured and the potential costs avoided, and also identifies the contextual factors that influence 

outcomes, it may provide some insights regarding the likely outcomes of attempting to introduce 

any changes into the Academy and the types of roadblocks that might be encountered. 

Overview of Relevant Diversity Literature 

Many different aspects of diversity have been examined within the diversity literature. 

The type of diversity that is of concern in this section is diversity as it relates to the ideas, 

approaches and activities related to teaching and research that are found within business schools. 

This is fairly close to Thomas and Ely’s (1996: 80) definition of organizational diversity as “the 

varied perspectives and approaches to work that members of different identity groups bring.” 

46

Historically, the interest in diversity arose from the changes in the demographic make-up 

of the North American workforce, and the introduction of team-based work methods (Page, 

2007), the belief in the moral incorrectness of discriminating against minority group members 

(Von Bergen et al., 2005), the obligation to comply with affirmative action and employment 

equity laws, and the instrumental notion that, if an organization’s workforce reflected the 

demographic makeup of its current or future customer base, organizational pay-offs would result. 

In none of these cases was diversity valued for its ability to capture the full range of employee 

capabilities, in order to benefit them, the organization, and society. Instead, individuals were 

expected to assimilate into the mainstream organization, adopting its values, culture, priorities, 

and the like (Dass and Parker, 1999), making their differences disappear. 

Then a qualitative study done by Thomas and Ely (2001: 265) produced the proposition 

that organizations could only tap into the true benefits of diversity if they viewed differences as 

learning opportunities and fully integrated diverse employee perspectives into how the 

organization’s “markets, products, strategies, missions, business practices, and even cultures” 

were defined. Although their study examined diversity with respect to race, they theorized that it 

was the differences in “life experiences, knowledge and insights” associated with racial 

differences that were of value. Klein and Harrison (2007) subsequently proposed that variety 

with respect to knowledge, ideas, values, attitudes and beliefs would confer positive benefits on 

organizations. 

The positive benefits of diversity have been identified as: greater innovation, better 

problem-solving and better predictions (Page, 2007); greater profitability, learning, creativity, 

flexibility, and individual and organizational growth (Thomas and Ely, 1996); internal resiliency 

in the face of change, greater meaningfulness of work and the advancement of social change 

(Svyantek and Bott, 2004); capitalizing on the full potential of employees to encourage 

organizational and national success (Oliver, 2005); greater efficiency, customer satisfaction, 

employee development and social responsibility (Dass and Parker, 1999); better decision making 

(Hartel, 2004); and greater recruitment success (Jayne and Dipboye, 2004). These benefits, 

however, have not always materialized during empirical tests and much of the literature raises 

doubts about the value of differences as they seem to be frequently accompanied by interpersonal 

and communication difficulties that impede organizational functioning. Some researchers have 

suggested that the process-oriented difficulties that arise within a diverse workforce might 

outweigh any associated gains (Jayne and Dipboye, 2004; Pitts and Jarry, 2007). 

Several studies have tried to reconcile the inconsistent findings, focusing on contextual 

factors that seem to affect outcomes. There is greater evidence supporting the performance 

effects of job-related rather than demographic differences (Svyantek and Bott, 2004). Task 

complexity and organizational strategy have been singled out, with the rationale that creativity 

and other benefits of diversity are more likely to materialize if the task is difficult and the 

company has adopted a growth strategy that makes creativity and innovation necessary (Bell and 

Berry, 2007; Dass and Parker, 1999). The number of diverse individuals and/or perspectives 

matters, as does whether or not power relations between the dominant and minority groups are 

sufficiently equalized to allow diverse perspectives to emerge (Klein and Harrison, 2007; 

Thomas and Ely, 2001). Thomas and Ely (1996; 2001) also found that the presence of common 

values across groups, including the valuing of diversity, is highly significant. The degree to 

47

which diversity is, in fact, integrated into the core activities of the organization (Dass and Parker, 

1999) and whether organizational socialization tactics encourage homogeneity or diversity 

(McMillan-Capehart, 2006), are also relevant to outcomes. 

The issues around shared values and ways of doing things, for example how new entrants 

are socialized, suggest that whether or not the organizational culture values diversity (Thomas 

and Ely, 1996; 2001) and encourages diversity openness (Hartel, 2004) is critical. Such a culture 

must specify effective means of reconciling differences in order to address the conflicts and 

misunderstandings to which differences can give rise (Jackson et al., 2003). Hartel (2004) 

noted that group processes tend to be more problematic in organizations that are less open to 

diversity. As Dass and Parker (1999) observed, conflict and debate, if badly handled, can be 

destructive to organizational functioning. Hence how diversity initiatives are implemented is 

important. 

This implicates the leadership in the success of any diversity initiative. Klein and 

Harrison (2007) observed that diversity that resulted in polarized opinions would not be helpful. 

Therefore, if leaders do not provide time for dialogue that allows hidden assumptions, values and 

beliefs to be revealed, and do not manage the revealed differences in such a way that different 

viewpoints can be reconciled to forge a sense of similarity that crosses cultural, functional and 

hierarchical lines, positive outcomes are unlikely to materialize (Dass and Parker, 1999; Thomas 

and Ely, 2001). In addition, lack of diversity within the top management team (Dass and Parker, 

1999) and lack of demonstrated commitment to diversity at that level, reflects and influences the 

prevailing organizational climate. Thomas and Ely (2001) noted that the leaders’ vision of the 

purpose of a diversified workforce is of fundamental importance. So, the optimum benefits of 

diversity will never be realized if leaders feel diversity is only important because of employment 

laws, or because it allows niche markets to be better exploited, and refuse to allow diversity to 

influence core organizational functioning or to look favourably on differences. 

Can the Academy Become More Relevant? 

It might be argued that the Academy’s current insistence on homogenization is morally 

wrong, given that an increasing proportion of its members are internationally-trained, or 

internationally-based, that the North American model privileges “Anglophone experiences, 

researchers, and worldviews… [and] undermines the effectiveness of scholarly development and 

the fairness of scholarly competition (March, 2005: 7). That it provides little insight “into the 

nature of management in novel or emerging-economy contexts” (Tsui, 2007: 1356) might be 

considered morally objectionable, as well as detrimental to the advancement of management 

knowledge. However, the diversity literature suggests that justifying diversity on the basis of 

moral arguments is not sufficient to reap its optimal benefits. Encouraging assimilation, which is 

what the current system accomplishes, at least at its core, is similarly ineffective. Valuing 

diversity for its capacity to release the full capabilities of employees or, in the case of the 

Academy, its members, with the inevitable positive impact this would have on management 

knowledge, would yield the best outcomes. But the Academy’s current interest in diversity arises 

from a perception of crisis, not from an acceptance of the value of diversity as such, which 

predicts sub-optimal outcomes. 

48

There are other indicators that diversity initiatives are unlikely to succeed. Relegitimizing 

pluralism into the Academy, as recommended by Ghoshal (2005) and Tsui (2007), will only be 

effective if, in the process, the core activities such as how the publication process works, how 

new entrants are socialized, and how the professoriate is rewarded, are fundamentally altered. 

This, in turn, can only materialize with the support of the Academy’s leadership, which might be 

loosely construed to consist of administrators, senior faculty, tenure committee members, top 

journal reviewers, and “high table” members. For instance, practitioner-academic partnerships 

will not materialize unless the reward system is changed. Expanding the “Implications for 

Practice” sections in journal articles must be authorized by journal editors. Reassuming 

responsibility for studying the negative as well as positive impacts of business practice for 

groups other than shareholders might produce outputs that would be eyed with suspicion by 

tenure committees, and might also be discouraged by Deans if it threatened the flow of corporate 

funds. Deans might also have a great deal to say about the nature and extent of curricular and 

program reform that would be tolerated, for the same reason. 

Introducing more fundamental changes, like converting business schools into learning 

organizations as Osborne and Cowen (1995) proposed, would require huge amounts of time and 

effort, and would have to be implemented and facilitated by the formal leadership. Hence the 

Deans of the business schools would have to be sold on the idea and willing to provide the 

resources and support necessary. They would probably face resistance from faculty members 

who are rewarded for their individual research outputs rather than for their citizenship 

behaviours, particularly when they have benefited from the current situation and might not see 

any immediate need for change. 

Even if such an initiative did get off the ground, the skewed power relations within the 

Academy, with students at the bottom, internationally-respected scholars at the top, and 

peripheral scholars somewhere in the middle, would make it difficult to elicit and then integrate 

the full range of opinions and suggestions present, which Senge (2006) identifies as critical to the 

creation of learning organizations. In addition, it seems reasonable to depict the homogenizing 

culture of the Academy as diversity-closed, and in such cultures, group process difficulties are 

more likely to arise (Hartel, 2004). Because there is no tradition, and no individual or institution 

held responsible for reconciling differing views and expectations within the Academy, the skills 

necessary to resolve conflict may be lacking. Given all these circumstances, establishing a 

common belief in the value of diversity would not come easily. 

However, the literature also suggests that encouraging greater diversity might be a fitting 

solution to the problems perceived to be bedeviling the Academy. First, the type of diversity 

being encouraged, of ideas, approaches and activities related to teaching and research, is the jobrelated 

diversity that the diversity literature has found to be most strongly associated with 

improved performance outcomes. Second, modifying how core activities are performed within 

the Academy can be considered a complex task requiring innovative solutions, which is the kind 

of task most likely to benefit from diverse inputs. Third, creativity is going to be necessary if 

some kind of consensus on how to move forward is to be forged across quite significant status, 

disciplinary and values divides, which again is most likely to be forthcoming when the combined 

talents of a highly intelligent, diverse community are brought to bear on the problem. 

49

It is difficult to imagine what might act as a catalyst to change the current situation. 

Lawler (2007) suggested that the AACSP’s draft report on the Academy’s research impact might 

stimulate change. A decline in MBA enrollments as prospective students come to realize the 

degree no longer is associated with career success, or general enrollment declines and loss of 

tuition dollars as competitors make further inroads into the field of management education might 

serve as wake-up calls. Finally, the emergence of leaders within the Academy who see the need 

and have both the inclination and the ability to forge a consensus on issues and potential 

solutions, would be a hopeful development. 

Conclusion 

If it is true that the future of business schools will be jeopardized by continued inaction 

on the relevance front, and if the diversity literature is correct, we can conclude that a culture that 

values diversity and finds ways to make it work will produce the best alternatives, predictions, 

problem solutions and outcomes for the Academy. Although it has been argued that the 

Academy’s current diversity-closed culture is not particularly helpful, it should be noted that 

some substantial diversity already exists at the periphery of the North American research model, 

and within the international management research community where different research traditions 

prevail. This may be adaptive for the research community overall. Those scholars currently 

working outside the dominant paradigm have adapted to their marginalized status within the 

Academy, finding alternative research communities and funding sources, and different places to 

publish and otherwise disseminate their work. Some of them may even have chosen to be on the 

periphery so that they could do relevant research and teaching. 

So, to end this paper on a positive note, it is possible that the looming crisis the Academy 

fears at worst may be overstated, and at best, may never materialize. 

50

References 

Agarwal, R. & Hoetker, G. (2007). A Faustian bargain? The growth of management and its 

relationship with related disciplines. Academy of Management Journal, 50(6), 1304-1322. 

Bartunek, J. (2007). Academic-practitioner collaboration need not require joint or relevant 

research: Toward a relational scholarship of integration. Academy of Management Journal, 

50(6), 1323-1333. 

Bell, M. & Berry, D. (2007). Viewing diversity through different lenses: Avoiding a few blind 

spots. Academy of Management Perspectives, 21(4), 21-25. 

Bennis, W. & O’Toole, J. (2005). How business schools lost their way. Harvard Business 

Review, 98-104. 

Boyer, E. (1990). Scholarship reconsidered: Priorities of the professoriate. Princeton, NJ: 

Carnegie Foundation for the Advancement of Teaching. 

Cohen, D. (2007). The very separate worlds of academic and practitioner periodicals in Human 

Resource Management. Academy of Management Journal, 50(5), 1013-1019. 

Cornuel, E. (2005). The role of business schools in society. Journal of Management 

Development, 24(9), 819-829. 

Dass, P. & Parker, B. (1999). Strategies for managing human resource diversity: From 

resistance to learning. Academy of Management Executive, 13(2), 68-80. 

Ghoshal, S. (2005). Bad management theories are destroying good management practices. 

Academy of Management Learning and Education, 4(1), 75-91. 

Greenberg, D., Clair, J., & MacLean, T. (2007). Enacting the role of management professor: 

Lessons from Athena, Prometheus, and Asclepius. Academy of Management Learning and 

Education, 6(4), 439-457. 

Hambrick, D. (2007). The field of management’s devotion to theory: Too much of a good thing? 

Academy of Management Journal. 50(6), 1346-1352. 

Hartel, C. (2004). Towards a multicultural world: Identifying work systems, practices and 

employee attitudes that embrace diversity. Australian Journal of Management, 29(2), 189- 

200. 

Jackson, S., Joshi, A. & Erhardt, N. (2003). Recent research on team and organizational 

diversity: SWOT analysis and implications. Journal of Management, 29(6), 801-830. 

Jayne, M. & Dipboye, R. (2004). Leveraging diversity to improve business performance: 

Research findings and recommendations for organizations. Human Resource Management, 

43(4), 409-424. 

51

Klein, K. & Harrison, D. (2007). On the diversity of diversity: Tidy logic, messier realities. 

Academy of Management Perspectives, 21(4), 26-33. 

Klimoski, R. (2007). From the editor: Becoming a prophet in our own land. Academy of 

Management Learning and Education, 6(4), 433-438. 

Lawler, E. (2007). Why HR practices are not evidence-based. Academy of Management 

Journal, 50(5) 1033-1036. 

March, J. (2005). Parochialism in the evolution of a research community: The case of 

organization studies. Management and Organization Review, 1(1), 5-22. 

Markides, C. (2007). In search of ambidextrous professors. Academy of Management Journal, 

50(4), 762-768. 

McGrath, R. (2007). No longer a stepchild: How the management field can come into its own. 

Academy of Management Journal, 50(6), 1365-1378. 

McMillan-Capehart, A. (2006). Heterogeneity of homogeneity. Socialization makes the 

difference in firm performance. Performance Improvement Quarterly, 19(1), 83-98. 

Mintzberg, H. (2004). Managers not MBAs: A hard look at the soft practice of managing. San 

Francisco: Berrett-Koehler. 

Mitroff, I. (2004). An open letter to the Deans and the faculties of American business schools. 

Journal of Business Ethics, 54, 185-189. 

Oliver, D. (2005). Achieving results through diversity: A strategy for success. Ivey Business 

Journal, March/April, 1-6. 

Osborne, R. & Cowen, S. (1995). Business schools must become learning organizations – or 

else. Learning Organization, 2(2), 28-31. 

Page, S. (2007). Making the difference: Applying a logic of diversity. Academy of 

Management Perspectives, 21(4), 6-20. 

Pfeffer, J. (2007). A modest proposal: How we might change the process and product of 

managerial research. Academy of Management Journal, 50(6), 1334-1345. 

Pfeffer. J. & Fong, C. (2002). The end of business schools? Less success than meets the eye. 

Academy of Management Learning and Education, 1(1), 78-95. 

Pfeffer, J. & Fong, C. (2004). The business school ‘business’: Some lessons from the US 

experience. Journal of Management Studies, 41(8), 1501-1520. 

52

Pitts, D. & Jarry, E. (2007). Ethnic diversity and organizational performance: Assessing 

diversity effects at the managerial and street levels. International Public Management 

Journal, 10(2), 233-254. 

Porter, L. &.McKibbin, L. (1988). Management education and development: Drift or thrust 

into the 21st century. New York: McGraw-Hill. 

Rynes, S. (2007a). AMJ turns 50! Looking back and looking forward. Academy of 

Management Journal, 50(6), 1277-1279. 

Rynes, S. (2007b). Time flies when you’re having fun: AMJ, 2005-2007. Academy of 


Senge, P. (2006). The fifth discipline. The art & practice of the learning organization. New 

York: Doubleday. 

Starkey, K., Hatchuel, A. & Tempest, S. (2004). Rethinking the business school. Journal of 

Management Studies, 41(8), 1521-1531. 

Svyantek, D. & Bott, J. (2004). Received wisdom and the relationship between diversity and 

organizational performance. Organizational Analysis, 12(3), 295-317. 

Thomas, D.& Ely, R. (1996). Making differences matter: A new paradigm for managing 

diversity. Harvard Business Review, September/October, 79-90. 

Thomas, D. & Ely, R. (2001). Cultural diversity at work: The effects of diversity perspectives 

on work group processes and outcomes. Administrative Science Quarterly, 46(2), 229-273. 

Trank, C. & Rynes, S. (2003). Who moved our cheese: Reclaiming professionalism in business 

education. Academy of Management Learning and Education, 2(2), 189-205. 

Tsui, A. (2007). From homogenization to pluralism: International management research in the 

Academy and beyond. Academy of Management Journal, 50(6), 1353-1364. 

Vermeulen, F. (2007). “I will not remain insignificant”: Adding a second loop to matter more. 

Academy of Management Journal, 50(4), 754-761. 

Von Bergen, C., Soper, B., Parnell, J. (2005). Workforce diversity and organizational 

performance. Equal Opportunities International. 24(3/4), 1-16. 

Zell, D. (2001), The market-driven business school. Has the pendulum swung too far? Journal 

of Management Inquiry, 10(4), 324-338. 

53

ASAC 2008 Christopher R Perryer 

Halifax, Nova Scotia Steven L McShane 

UWA Business School 

The University of Western Australia 

THE INFLUENCE OF TRAINING TRANSFER CLIMATE AND 

INDIVIDUAL TRAINEE CHARACTERISTICS ON CUSTOMER 

ORIENTATION 

This study tests hypotheses regarding the factor structure of a 

prominent training transfer climate instrument, the issue of 

moderating rather than just direct effects of training transfer climate, 

and the effects of two trainee characteristics -- organizational 

commitment and cynicism about organizational change -- on the 

transfer of training. 

Increasingly, scholars and practitioners alike recognize that human capital is a critical 

source of organizational competitive advantage (Appelbaum, Bailey, Berg, & Kalleberg, 

2000; Benson, Young, & Lawler III, 2006; Pfeffer, 1998). Furthermore, developing 

employee competencies is considered one of the core components of high performance work 

practices that, when combined with other such practices, can leverage the value of human 

capital (Becker & Huselid, 2006; Combs, Liu, Hall, & Ketchen, 2006; Lawler III, Mohrman, 

& Ledford Jr., 1998). Training is one of the primary tools for developing employee 

competencies, yet much of the value of this training isn’t transferred to the job or deteriorates 

within a short time after being transferred. For example, 150 Canadian human resource 

executives recently estimated that less than two-thirds of employees use their training back 

on the job, and this diminishes to 44% and 34% after six months and one year, respectively 

(Saks & Belcourt, 2006). Others provide more dismal figures, estimating that as little as 10- 

15% of what is learned in formal training programs is transferred or remains in use one year 

later (Cromwell & Kolb, 2004; Newstrom, 1986). 

Given the substantial investment in workplace training -- approximately $850 per 

employee in Canada and much higher in the United States (Grant & Hughes, 2007) -- it is 

little wonder that scholars have been eager to identify factors that facilitate or hinder transfer 

of training (Burke & Hutchins, 2007). Indeed, some scholars identify transfer of training as 

the critical point through which training influences organizational effectiveness (Kozlowski, 

Brown, Weissbein, Cannon-Bowers, & Salas, 2000). Baldwin and Ford (1988) laid the 

foundation for current thinking about training transfer predictors, and many others have 

either built models or empirically tested some of these factors. However, much of that 

research has concentrated on trainee characteristics, such as trainee ability and motivation, or 

training design issues, such as the relevance of program content to trainees or instructional 

techniques. Only recently have scholars taken a more integrated approach to the subject by 

examining the unique and combined effects of trainee characteristics and workplace factors 

on training transfer (Lim & Morris, 2006; Tziner, Fisher, Senior, & Weisberg, 2007). 

54

This paper hopes to shed further light on the transfer of training in three ways. First, we 

examine the construct validity (specifically the factor structure) of a training transfer climate 

instrument that has gained prominence over the past decade. Second, we test the moderator 

effects, not just the direct effects, of training transfer climate on the training outcome variable, 

which in this study is employee customer orientation. Third, together with the training 

transfer climate dimensions, this study examines the predictive effects of two trainee 

characteristics, organizational commitment and cynicism of organizational change. The 

significance and rationale for these research objectives are explained over the next few pages. 

Training Transfer Climate 

Several training transfer studies employ the term “training transfer climate” to describe 

work environment conditions that influence the generalization and maintenance of 

knowledge and skills learned during training (E. F. III Holton, Bates, Seyler, & Carvalho, 

1997; Machin & Fogarty, 2004; Tracey, Tannenbaum, & Kavanagh, 1995; Washington, 

2002). Significant relationships have been reported between training transfer climate and the 

degree of learning transferred from the training program to the workplace, but these findings 

are sometimes inconsistent. One concern recently identified by Burke and Hutchins (2007) is 

that “measures of transfer climate are in a state of transition.” We take a more critical 

position: the problem of conceptualizing and measuring training transfer climate has existed 

from its earliest days. Holton et al (1997) similarly state that, notwithstanding general 

agreement regarding the importance of training transfer climate, there is no clear, shared 

understanding of the transfer climate construct. 

The confusion in defining and measuring training transfer climate is apparent while 

sifting through the more than 60 published studies on the subject. A dozen of these studies 

operationalized training transfer climate as a single composite measure without conducting 

any construct validation to support a single-factor approach. Almost four-dozen studies took 

a multi-dimensional approach to training transfer climate by examining several variables or 

dimensions that the researchers claim are within the construct definition. However, most of 

these studies did not attempt to identify and measure the construct’s full conceptual domain 

and, even where so attempted, did not rely on a theoretical framework to justify inclusion of 

these dimensions of training transfer climate (Detailed tabulations of these studies are 

available from the authors on request.). 

A small number of publications have studied training transfer climate with a theoretical 

foundation, typically adopting the behaviourist and/or social learning model. The most 

widely cited of these is Rouiller & Goldstein (1993), who suggest that transfer climate 

consists of situational and consequence cues. Their work was further developed by Thayer 

and Teachout (1995), who adopted and refined Rouiller and Goldstein’s measure of these 

cues. Most recently, Machin and Fogarty (2004) further refined the training transfer climate 

measure developed and revised in the earlier two studies. One of our objectives is to test the 

reliability and factor structure of this emerging instrument, thereby hopefully moving closer 

to establishing a conceptual and operational foundation for training transfer climate. 

Hypothesis 1: Training transfer climate consists of six factors, goal cues, social 

cues, task cues, positive reinforcement, negative reinforcement and punishment, 

and extinction. 

55

Hypothesis 2: Employee perceptions of the training transfer climate are positively 

related to employee customer orientation. 

Moderator Effects of Training Transfer Variables 

Another issue investigated by this study is the direct versus moderator effects of training 

transfer climate variables on training outcomes. Although Baldwin and Ford (1988) 

encouraged further research on the interaction effects of training transfer variables, only a 

handful of studies have done so (Burke & Baldwin, 1999; Mathieu, Tannenbaum, & Salas, 

1992; Richman-Hirsch, 2001; Smith-Jentsch, Salas, & Brannick, 2001). This is surprising 

because variables that facilitate or hinder training transfer are, by definition, moderating the 

relationship between the employee’s attendance and learning in the training program and 

training outcomes such as on-the-job attitudes and behaviour. Moderator variables affect the 

strength or direction of the relationship between predictor and criterion variables (Baron & 

Kenny, 1986; Mason, Tu, & Cauce, 1996; Sharma, Durand, & Gur-Arie, 1981). Training 

transfer variables are moderators because they purportedly affect the strength of the 

relationship between training program attendance or learning and on-the-job attitudes or 

behaviour. 

Consider the following example: Suppose that a training program taught employees the 

procedures for driving forklifts more safely, such as looking, signaling, and visually checking 

the equipment before driving. Compared to typical forklift driving, these safe-driving 

behaviours slightly increase the time required to complete tasks. Let’s further suppose that 

employees with light or moderate workloads apply the learned forklift safety behaviours 

more often than do employees with heavy workloads. In this example, workload moderates 

the relationship between forklift safety training attendance or learning and on the job 

behaviour. The reason for this moderator is that the predictive effect of the training program 

varies with (i.e. depends or is contingent upon) the level of workload. A high correlation 

would be observed between training program attendance or learning and on-the-job 

behaviour when workload is low or medium – employees who attended the training program 

or learned more in that program engage in more forklift safety behaviours than those who did 

not attend or learned very little in the program. The correlation decreases as workload 

increases – the incidence of forklift safety behaviour varies minimally by attendance or 

learning in the training program when employees experience high workloads. Moderator 

variables often have a direct association with the dependent variable, but they also have 

additional explained variance as an interaction term with the predictor variable (training 

attendance or learning in our example). 

As mentioned, a few studies have examined the moderator effects of some training 

transfer variables. At least two studies found no moderator effect (Rouiller & Goldstein, 

1993; Tracey et al., 1995). Others have reported a moderator effect, but many of these have 

limitations. At least one study claimed to investigate the moderator effect, but did not 

conduct any moderated analysis (Kontoghiorghes, 2001). Burke and Baldwin (1999) reported 

a significant moderator effect size, but relied on a small sample and their dependent variable 

was the trainees’ use of transfer strategies, rather than transfer of the training content itself. 

Richman-Hirsch’s (2001) study of goal-setting training found a significant interaction 

between a supportive work environment and post-training behaviour. However, goal setting 

56

is also a training transfer variable, which may have confounded the results. Finally, none of 

these or other training transfer studies conducted a preliminary test to see whether the 

significant moderator effect is spurious due to curvilinear relationships between predictor and 

dependent variables (Lubinski & Humphreys, 1990). Consequently, the present study 

hypothesizes that the effect of training program attendance on the dependent variable will be 

moderated by training transfer climate variables. This hypothesis will include a test for 

quadratic (curvilinear) effects: 

Hypothesis 3: Training transfer climate variables will moderate the relationship 

between participation in the training intervention and employee customer 

orientation. 

Trainee Characteristics and Transfer of Learning 

Notwithstanding the importance of training transfer climate, trainee characteristics also 

have an influence on the degree to which training concepts and practices are transferred to 

the workplace (Burke & Hutchins, 2007; Lim & Morris, 2006; Tziner et al., 2007). 

Personality, motivation, ability, and self-efficacy have been widely studied as predictors of 

training transfer. There are, however, other individual trainee characteristics that have 

received far less attention from researchers. One of these, organizational commitment, is the 

relative strength of an individual’s identification with, and involvement in an organization 

(Mowday, Steers, & Porter, 1979). Meyer and Allen (1997) maintain that organizational 

commitment has a positive influence on the training process. Some research supports this 

assertion (Naquin & Holton III, 2002; Tracey, Hinkin, Tannenbaum, & Mathieu, 2001), 

whereas other studies report that organizational commitment has a nonsignificant influence 

on training transfer (Facteau, Dobbins, Russell, Ladd, & Kudisch, 1995). The lack of clarity 

surrounding the effect of this variable warrants further investigation. 

This study also introduces cynicism about organizational change as an individual 

characteristic that we hypothesize will have an inverse effect on training transfer. Cynicism 

about organizational change is defined as “a pessimistic outlook for successful change, and 

blame placed on ‘those responsible’ for lacking the motivation and/or the ability to effect 

successful change” (Reichers, Wanous, & Austin, 1997). We believe that this construct has 

particular relevance to training transfer, because training is an important strategy to support 

the change process. To date no studies have attempted to examine the relationship between 

training transfer climate and cynicism about organizational change. It is, however, a variable 

that shows great explanatory promise, and consequently warrants further study, leading to the 

fourth research question. 

Hypothesis 4: Organizational commitment is positively related to employee 

customer orientation. 

Hypothesis 5: Cynicism about organizational change is negatively related to 

employee customer orientation. 

57

Research Setting 

Methods 

The research setting for this study is Centrelink, which was formed by the Australian 

government in the late 1990s to centralize a range of social services and payments previously 

distributed by dozens of government departments and agencies. This innovative “one-stop 

shop” currently provides services to approximately 6.5 million customers each year, which 

includes more than 6 billion customer record transactions and distribution of AUD $66 

billion on behalf of the 31 government policy departments (Centrelink, 2007; Halligan, 2007). 

Centrelink’s leaders have focused on customer service as a key driver of organizational 

change. One intervention introduced to support this cultural transformation is the Value 

Creation Workshop (VCW) (Vardon, 1998). VCWs are one-day workshops conducted by 

trained facilitators held away from Centrelink offices with up to 20 customer and 20 

employee participants. During the morning session, employees listen (without speaking) to 

customers describing their experiences and expectations from Centrelink. The morning 

session also involves technology that allows employee participants to predict how customers 

will respond to issues, and to assess the accuracy of their predictions. Customers and 

employees mingle during lunch, after which customers leave. In the afternoon session, 

employees build on the customer feedback to develop strategies for customer service 

improvement (Australian National Audit Office, 2005; Bennington & Cummane, 1998). 

To date there have been no empirical studies of the Value Creation Workshop, even 

though it has been applied to a few organizations. One published paper (Bennington & 

Cummane, 1998) details the methodology of the intervention, and suggests that it is a useful 

market research tool that has the added benefit of improving service quality. However, in the 

absence of any rigorous research, the usefulness of the intervention is largely based on the 

claims of the promoters of the program (Bennington, 1999). While this study relies on selfreports 

of the degree to which employees apply the training, it will add to the limited existing 

knowledge about the intervention. 

Sample and Data Collection 

Data were collected from Centrelink customer service employees in two Australian states. 

The population consists of a mixture of people who have been exposed to the training 

intervention and those who have not. Data were initially collected through an intranet survey, 

with invitations and web site link delivered by email to employees with primarily customer 

service duties. Due to a low response rate through the online survey, hard copies of the 

questionnaire were also distributed in person by the first author to customer services 

employees located at Centrelink’s main metropolitan centres in Perth. Those who completed 

the hard copy version indicated that they had not completed the online survey. In total, online 

and hard copy questionnaires were returned by 260 employees, although missing data 

reduced the final data set to 234 cases. The response rate is slightly below the average of 21 

percent reported in a study of response rates in the 1990s (Paxson, Dillman, & Tarnai, 1995), 

and should be considered a limitation of this study. However, the sample size is adequate for 

inferential data analysis (Guadagnoli & Velicer, 1988; Hair, Anderson, Tatham, & Black, 

58

1998). Also, statistical power for these data is well above the .80 level necessary to detect 

medium to large effects in regression-based research (Cohen, 1988) 

Measures 

Customer Orientation. The dependent variable – a training outcome – in this study is 

the employee’s customer orientation, which is defined as “an employee’s tendency or 

predisposition to meet customer needs in an on-the-job context” (Brown, Mowen, Donavan, 

& Licata, 2002, p. 111). This variable was measured using the 22-item (α = .97) scale 

developed by Kelly (1992). A typical item is “It is important to have operating hours that are 

convenient for customers”. Other customer orientation scales were not used because they 

emphasized selling (rather than service) or after sales service, or were less parsimonious with 

no apparent advantage. 

Training Transfer Climate. This study adopted the 56-item scale refined and tested by 

Machin and Fogarty (2004). This instrument was originally developed by Rouiller and 

Goldstein (1993) based on their behaviourist and social learning conceptual foundation of 

training transfer variables. The instrument was later refined and adapted for military use by 

Thayer & Teachout (1995). The current version by Machin and Fogarty is a further 

development of the previous two versions. The instrument consists of six subscales, three 

relating to workplace cues (goal cues, social cues and task cues), and three relating to 

workplace consequences (positive reinforcement, negative reinforcement and punishment, 

and extinction). Machin and Fogarty (2004) reported good reliabilities for five subscales and 

marginally acceptable (α = .66) for the negative reinforcement and punishment subscale. The 

present study reports similar results; reliability exceeded .80 on each the first five subscales, 

but was exceptionally low (α = .27) on the sixth dimension. As with most training transfer 

instruments (for an exception see: Holton et al (1997)), this scale has received limited 

construct validation of its assumed underlying factor structure. 

Organizational Commitment. This variable was measured using the 15-item (α = .91) 

scale developed by (Mowday et al., 1979). A typical item is “I could just as well be working 

for a different organization as long as the type of work was similar”. This scale is widely 

used when the research focuses only on affective attachment (Mowday, 1998). 

Cynicism about Organizational Change. This variable was measured using the 8-item 

(α = .93) scale developed by Wanous, Reichers, & Austin (2000). This scale consists of four 

items measuring the level of pessimism regarding the likely success of change, and four 

items measuring dispositional attribution about those people responsible for effecting 

successful change. A typical item is “The people responsible for making things better around 

here do not care enough about their jobs.” 

Training Attendance. Data were also obtained relating to the number of times 

respondents had been exposed to the training intervention, and the most recent attendance at 

a workshop. In this study, whether or not the respondent had attended the Value Creation 

Workshop was coded as a dichotomous variable (1=Yes, 0=No). 

59

Results 

To test the hypotheses, two separate statistical analyses were conducted. The first 

hypothesis was tested through factor analysis of the training transfer climate instrument. The 

remaining hypotheses were tested through hierarchical multiple regression. 

Factor Analysis of Training Transfer Climate Scale 

Maximum likelihood factor analysis with promax rotation was conducted on the 56-item 

training transfer climate scale, which produced twelve factors with eigenvalues greater than 1 

and explained 66% of the variance. These results were not readily interpretable due to few 

items on each factor and several items with cross loading above .40. Next, items were forced 

to load on six factors, as specified in the original studies. These results (available from the 

authors) did not support the hypothesized subscales due to high cross-loading of some items 

and low eigenvalues for some items. Given problems with the original six-factor model, a 

scree plot was conducted on the training transfer climate items. This plot indicated that a 

four-factor structure would be the most appropriate fit for this data. The original 56 items 

were forced to load on four factors, and items loading below .50 were deleted. The 

procedure was repeated two more times. This analytic process resulted in a 35-item 

instrument with all items loading cleanly on no more than one factor. The four factors – 

which we labeled support, extinction, control and outcomes (reinforcement) -- have 

reliabilities ranging from .73 to .94 and the factor structure accounts for 48% of variance. 

The support factor, which has 20 items, includes all statements relating to physical and 

informational resources (e.g., “Necessary tools/equipment are available”, “Supervisors 

answer VCW questions”) as well as items pertaining to training transfer goals (e.g., 

“Supervisors help staff to set goals”). The extinction factor includes seven items, including 

all items found in the original extinction subscale. These items represent the supervisor’s 

indifference to the training program and its application (e.g. “Supervisors don’t notice use of 

VCW ideas”, “Supervisors don’t care about VCW”). The outcomes factor consists of four 

items that combine positive reinforcement and punishment. Two items refer to prospects of 

promotion for those who apply their training (e.g., “No promotion without using VCW 

ideas”). The other two items refer to how staff are treated when the training is applied on the 

job. The control factor consists of four items, three of which refer to time limitations of 

applying the training (e.g., “No time to do the job using VCW ideas”). 

Based on the revised training transfer climate instrument, Table 1 presented the means, 

standard deviations, internal consistency reliabilities and zero-order correlations for all 

variables in this study. These data indicate that all variables have good reliability and, except 

for customer orientation, are only slightly skewed from normality. The high mean score for 

customer orientation is expected, because the organization specifically attracts and selects 

people with a strong customer orientation. Although not ideal for multivariate research, the 

distribution for this variable was not normalized because of warnings about such a procedure 

(Cohen & Cohen, 1983) and because attitude data are typically negatively skewed 

(McDougall & Beattie, 1998). The skewed distribution likely suppresses the true effect sizes 

of variables associated with customer orientation. 

60

Most variables also have low or moderate intercorrelations. The highest intercorrelation 

is between organizational commitment and cynicism about organizational change (r=-.67), 

which is consistent with the relationship between these two variables in previous studies. 

Support and extinction also have a high zero-order correlation (r=.65). However, both of 

these correlations are below the .70 limit suggested by Tabachnick and Fidell (1996). 

Examination of the correlation diagnostics established that no condition indexes were greater 

than 30, indicating that multicollinearity was not a significant problem. However, inspection 

of the variance inflation factors (VIFs) suggests that multicollinearity may in fact be present, 

posing a potential, but not serious, problem for the interpretation of these results. All 

independent variables were centered prior to regression analyses to minimize 

multicollinearity issues between first order and higher order (interaction) terms (Aiken & 

West, 1991; Cohen & Cohen, 1983; MacCallum & Mar, 1995). 

Table 1 

Means, standard deviations, reliabilities and bivariate correlations 

Variable α Mean SD 1 2 3 4 5 6 7 

1. Customer 

orientation 

.96 6.24 .80 

2. Training 

attendance y/n 

- - - .14* 

3. Commitment .90 4.12 1.16 .18** -.04 

4. Cynicism about 

change 

.92 3.41 1.31 -.20** .02 -.67** 

5. Support .94 3.96 1.09 .22** .03 .51** -.63** 

6. Extinction .86 4.29 1.31 .05 -.00 .52** -.60** .65** 

7. Outcomes .75 3.00 1.11 -.30 -.06 .15* -.07 .26** .06 

8. Control .73 2.96 1.28 -.18** -.04 .42** -.40** .27** .45** .15* 

**Correlation is significant at the 0.01 level. 

*Correlation is significant at the 0.05 level. 

Hierarchical Regression Analysis 

The remaining hypotheses postulated that there would be a significant relationship 

between each of the independent variables, including the interaction terms, and the dependent 

variable customer orientation. These hypotheses were tested using hierarchical regression 

analysis, shown in Table 2. Independent variables were entered in a logical sequence that 

paralleled the transfer experience. As per moderated regression procedures, the higher order 

(interaction) terms were entered in later steps. The results showed a good fit of the data to the 

model. The overall model produced an R² of .30, and an adjusted R² of .26. 

61

Table 2 

Hierarchical Regression Analysis of Customer Orientation 

Variable B SE B β R² Adj. R² ∆ R² ∆ F 

Step 1 .02 .01 .02 4.32* 

Training .11 .05 .14* 

Step 2 .05 .04 .03** 8.32** 

Training .11 .05 .14* 

Commitment .15 .05 .19** 

Step 3 .06 .05 .01 2.70 

Training .11 .05 .14* 

Commitment .07 .07 .09 

Cynicism -.11 .07 -.14 

Step 4 .17 .15 .11** 7.49** 

Training .10 .05 .12 

Commitment .14 .07 .18* 

Cynicism -.12 .08 -.15 

Support .17 .07 .21* 

Extinction -.11 .07 -.13 

Outcomes -.05 .05 -.06 

Control -.24 .06 -.30** 

Step 5 .19 .16 .02 2.70 

Training -.20 .17 -.25** 

Commitment .16 .07 .20* 

Cynicism -.08 .08 -.10 

Support .21 .08 .26** 


Outcomes -.05 .05 -.07 

Control -.24 .06 -.30** 

Train X Commit. .01 .06 .01 

Train X Cynicism .09 .05 .40 

Step 6 .30 .26 .11** 8.46** 

Training -.54 .18 -.67** 

Commitment .18 .07 .23** 

Cynicism -.07 .07 -.09 

Support -.17 .07 .21* 


Outcomes -.04 .05 -.05 

Control -.24 .05 -.30** 

Train X Commit. -.11 .06 -.13 

Train X Cynicism .19 .05 .86** 

Train X Support .21 .07 .23** 

Train X Extinction .01 .08 .01 

Train X Outcomes -.04 .05 -.05 

Train X Control .26 .06 .34** 

* p ≤ .05 ** p ≤ .01 B values are unstandardized coefficients; β values are standardized coefficients 

62

Participation in the Value Creation Workshop was entered in step 1 of the hierarchical 

regression analysis. Alone, this variable had a significant but minimal practical association 

with customer orientation (adjusted R² = .01). The individual trainee characteristic of 

organizational commitment was added to the model in step 2. The change in R² was 

significant (p ≤ .01), and R² increased to .05 (adjusted R² = .04), indicating that 

organizational commitment was a significant predictor of customer orientation. Cynicism 

about organizational change was added in step 3, but did not add significantly to the model. 

The four transfer climate variables -- support, extinction, control and outcomes -- were 

entered together in step 4. Entering these variables resulted in a significant increase in R², 

raising the explained variance by 10 percent (adjusted R² = .15). Only the transfer climate 

dimensions of support (β=0.23, p ≤ .01), and control (β=-0.30, p ≤ .01) were statistically 

significant. The β weight for control is negative, since high scores on this variable indicate 

low levels of control were statistically significant. Control has a negative regression weight 

because high scores on this subscale indicate low levels of control. Step 5 of the hierarchical 

regression analysis consisted of entering the interaction terms of training with the two trainee 

characteristics (organizational commitment and cynicism about organizational change). The 

change in R² was not significant, indicating that the interaction terms do not predict customer 

orientation at this step. 

To determine the appropriate variables to enter in the next step an effect size comparison 

procedure was conducted (Lubinski & Humphreys, 1990). This procedure identifies whether 

the underlying structural model is best approximated by a curvilinear relationship or by a 

moderator relationship. The effect size comparison procedure involves testing whether a 

quadratic (squared) term for transfer climate produces a greater increase in R² than does the 

interaction term for transfer climate and training attendance. The results of this procedure 

suggest that, while a significant curvilinear effect is present, a stronger more meaningful 

moderator effect is also present, and the moderator effect better describes the underlying 

structure of the relationship between transfer climate and customer orientation. 

Based on the effect size comparison procedure, step 6 consisted of entering the four 

interaction terms of training attendance with the four training transfer climate variables. The 

change in R² was significant and R² increased substantially to .30 (adjusted R² = .26), 

indicating that the interaction between attendance and transfer climate was a significant 

predictor of customer orientation. In this final step of the multiple regression analysis, four 

first order variables were significantly associated with customer orientation: training, control, 

organizational commitment, and support. In addition, three interaction variables were 

statistically significant: training with control, support, and cynicism about organizational 

change. 

Discussion and Conclusions 

This study set out to improve our knowledge of transfer of training in three ways. First, 

we hoped to contribute to the construct validation of the training transfer climate scale that 

has received recent attention. Second, our goal was to further illuminate the effect of training 

transfer climate, particularly to examine the moderator rather than just the direct effects of 

this variable’s dimensions. Finally, this study investigated the effects on training transfer of 

63

two trainee characteristics that previously received limited attention. The results of each of 

these research objectives are discussed below. 

Training Transfer Climate Direct Effects 

This study reported that two of the four training transfer climate variables – control and 

support– had strong direct associations in the predicted direction with customer orientation. 

The strong effect size for control reflects the idea that employees have less of a customer 

orientation when faced with heavy workloads. Customer service may require additional time, 

which is not available when workloads are high. With less time to provide good customer 

service, employees eventually feel less customer orientation. 

Support is a broadly-defined construct in the training transfer literature, but consistently 

includes actions by the supervisor as well as workplace conditions that support application of 

the learned skills or knowledge back on the job. Several measures of support, including the 

one in this study, also include setting objectives that encourage use of trained material on the 

job (McSherry & Taylor, 1994). The significance of support as a direct predictor of customer 

orientation is consistent with many previous studies on transfer of training (Brinkerhoff & 

Montesino, 1995; Facteau et al., 1995; Lim & Johnson, 2002; Nijman, Nijhof, Wognum, & 

Veldkamp, 2006). Supervisor support, for example, might directly motivate employees to 

provide better customer service, whether or not the company offered a training program to 

also strengthen this orientation. 

Training Transfer Climate Moderator Effects 

One of the most important findings in this study is that training transfer climate (or 

specific dimensions of this variable) moderates the relationship between the customer service 

training intervention and the employee’s customer orientation. These moderator variables 

alone added 11 percent explained variance to the equation, a substantially higher result than 

is found in most studies involving moderator effects (Champoux & Peters, 1987; Chaplin, 

1991). Equally important, the variance in the dependent variable attributable to the 

moderator effect of transfer climate was as great as the variance attributable its main effect. 

The moderator effect for control indicates that employees with heavy workloads are 

much less likely to apply what they learned from training back on the job. Employees might 

cope with work overload by applying familiar work procedures rather than new practices 

learned through the training program. The moderator effect for support indicates that 

employees who receive supervisor support, work resources, and work goals coaching are 

more likely to apply what they learned from training back on the job compared to those who 

receive less support. This finding makes sense for two reasons. First, employees have an 

easier time applying their training back on the job where the work environment has resources 

needed to improve customer service. Second, training transfer requires the employee to 

generalize what they have learned in the training program to the job (Baldwin & Ford, 1988). 

Even the best training programs require on-the-job support from supervisors and co-workers 

to guide trainees through this generalization process; in other words, to show them how and 

where to apply their newfound skills, knowledge, and attitudes in the workplace. 

The strong moderator effect of training transfer climate has important implications for 

future research on this topic. Most training transfer literature suggests that the effect of 

64

training on workplace behaviour depends on (i.e. is contingent upon) the level of training 

transfer climate (or its specific dimensions) as well as trainee characteristics and related 

variables. In other words, they typically propose that these variables moderate the 

relationship between training and workplace behaviour. Yet, the majority of training transfer 

studies test only for the direct effect of each variable, not for the moderator effect. The few 

studies that do conduct moderator analysis typically overlook the procedure of initially 

testing for quadratic rather than moderator relationships. This study’s findings suggest that 

training transfer climate not only moderates the effect of training on employee behaviour and 

attitudes; it is one of the most important predictors of training outcomes. Future research 

doesn’t need to change the underlying model; rather, it needs to conduct a moderator effect 

as current models specify. 

Individual Trainee Characteristics 

This study hypothesized that organizational commitment would be positively related to 

employee customer orientation, and that cynicism about organizational change would be 

negatively related to employee customer orientation. The significant direct effect of 

organizational commitment on customer orientation reported in this study is consistent with 

findings in some earlier studies, but not others (Bartlett, 2001; Facteau et al., 1995; Orpen, 

1999; Tesluk, Farr, Mathieu, & Vance, 1995; Tracey et al., 2001). The findings of the present 

study suggest that employees with a stronger affective commitment to the organization are 

more dedicated to the employer’s goals and initiatives, which would include serving 

customers where (as in this organization) customer service is one of the organization’s core 

values. Committed employees simply accept that customer oriented behaviour is appropriate 

because they share the values and ideals of the organization. In addition, employees with 

higher affective commitment may have higher customer orientation because their 

commitment motivates them to be more mindful during the learning process and to apply that 

knowledge or skill on the job. This is consistent with the observation by Tesluk et al (1995) 

that organizational commitment is likely to have a greater effect when a training intervention 

is strongly endorsed by the organization. 

Cynicism about organizational change is a relatively new construct that has received 

limited attention from researchers. Tesluk et al (1995) examined the impact of the broad 

construct of cynicism on generalization of training, but we could find no other research that 

has investigated the more specific construct of cynicism about organizational change in the 

context of training transfer. Training is an important strategy for managing the change 

process, so it seems logical that cynicism about organizational change would have a 

significant direct effect on training outcomes. This variable was nonsignificant in the present 

study, however. One possible explanation is that, due to the high negative correlation 

between organizational commitment and cynicism about organizational change, the latter 

offered little additional explanatory value beyond the variance explained by organizational 

commitment. Another explanation may be that this variable is a broadly-based attitude that 

would not interfere with an ongoing specific training initiative. Perhaps other factors in the 

workplace combined to encourage customer oriented behaviour, and this outweighed the 

impact of individual cynicism about customer orientation. 

65

Although not specifically hypothesized, this study also examined whether the trainee 

characteristics moderated the relationship between participation in the customer service 

training program and employee customer orientation. The interaction term of training 

participation with organizational commitment was not significant. This suggests that the 

strength of the relationship between participation in the workshop and customer orientation 

was unaffected by the level of employee organizational commitment or cynicism about 

organizational change. 

The interaction term regarding training participation and cynicism about organizational 

change was statistically significant in the final step of the regression analysis, suggesting that 

the strength of the relationship between participation in the workshop and customer 

orientation varied with the level of employee cynicism about organizational change. This 

finding is intuitively appealing, since employees with low levels of cynicism about change 

would logically be expected to apply new learning to a greater extent than employees who 

were cynical about the value of trying to implement change in their jobs. The finding that an 

interaction between attendance at a training intervention and cynicism about organizational 

change is a significant predictor of transfer is a new finding that has not been previously 

reported in the literature. However, this finding seems to run contrary to the earlier finding 

that there is no statistically significant main effect on customer orientation for this variable. 

While the absence of a main effect does not conceptually preclude the existence of a 

moderator effect (Baron & Kenny, 1986), it makes the moderator effect more difficult to 

explain. The most likely explanation is that while employees who are cynical about change 

can still have high levels of customer orientation, employees who are cynical about change 

are less likely to transfer training content, in this case customer orientation, to their jobs. 

Influence of Participation in the Training Program 

In order to identify the influence of participation in the training intervention, it was also 

hypothesized that attendance at the workshop would be positively related to employee 

customer orientation. The direct effect of participation in the training intervention was 

significant when first entered, became non-significant when the transfer climate variables 

were entered, and did not become a significant predictor of customer orientation until all 

other variables, including the interaction terms, had been entered into the regression model. 

This suggests that when individual trainee characteristics and transfer climate variables are 

accounted for, participation in the training program does have a positive impact on transfer. 

Factor Structure of Training Transfer Climate Instrument 

We were surprised to discover that the data in this study did not support the six-factor 

structure of training transfer climate that had been developed (with minor variations) and 

applied in two previous widely-cited studies as well as in a more recent study. Instead, the 

study found that training transfer climate consists of four factors, relating to supervisory and 

co-worker support, including both social and material support (support), behaviour from 

supervisors that directly discourages transfer (extinction), personal control over workload 

and workflows (control), and the degree to which transfer leads to desired personal outcomes 

(outcomes). 

66

While the hypothesized six-factor structure was not supported, the four-factor structure 

found in this study (support, extinction, control, and outcomes) identifies aspects of the work 

environment that intuitively would be likely to affect employee attitudes to the transfer of 

new skills and knowledge to the job. Furthermore, this analysis provides further insight 

regarding the current debate about whether training transfer climate is a multidimensional or 

unidimensional construct (Burke & Hutchins, 2007; Tracey, 2005; Tracey et al., 2001). The 

workplace cues and consequences dimensions introduced by Rouiller and Goldstein (1993) 

loaded on one factor in this study. However, the resulting four-factor structure had minimal 

cross-loadings and, equally important, seems to have differential association with other 

variables in this study. 

These findings complement and extend the results of earlier studies on training transfer 

climate in one important way. Most previous studies have not attempted to understand the 

makeup of the training transfer climate construct itself, but have instead sought to examine 

the influence of particular variables upon transfer. In many cases, they have simply 

combined a number of items, and claimed that the amalgam constituted transfer climate. In 

other cases, researchers adopted scales used in earlier studies, but even these more frequently 

used scales were rarely tested for factor structure and other elements of construct validity. 

While the results of this study do not point to the existence of transfer climate variables that 

have not been previously identified, they do suggest that a different combination of 

dimensions might comprise the transfer climate construct. 

Each of these four factors has been identified as a transfer climate variable in previous 

studies (Bates, Holton, Seyler, & Carvalho, 2000; Elwood F. III Holton, Bates, & Ruona, 

2000; E. F. III Holton et al., 1997). In those studies alone, however, a total of from nine to 

sixteen factors were found to constitute the transfer climate construct. The more 

parsimonious structure identified in this study has the practical utility that Noe (2000) has 

urged, as well as theoretical rigour, and is consequently a useful contribution to 

understanding transfer climate. 

One recent study (Clarke, 2002) identified a transfer climate structure almost identical to 

the structure found in this study. Clarke found that heavy workloads, time pressures (control), 

lack of reinforcement (support), an absence of feedback (extinction), and the degree to which 

employees saw in-service training as personal development rather than job related training 

(outcomes) were work environment factors that impede transfer of training. The factor 

structure identified by Kirby and colleagues (2003) also has similarities to the structure 

identified in this study. They identified three factors, which they labeled good supervision, 

workload, and choice independence. Their first factor related to a supportive and receptive 

work environment, with good supervision and clear expectations, broadly equivalent to the 

support factor in the present study. Their second factor related to workload levels, and their 

third factor was related to independence about the way employees could approach their work. 

These two factors equate to the control factor that emerged in the present study. 

A particularly interesting finding of this study is the emergence of the factor that relates 

to control over work and pressure of time. Oddly enough, this seems to support one piece of 

Rouiller and Goldstein’s (1993) original model, namely “self-control” cues. That dimension 

was removed from subsequent studies by other researchers on the basis that the dimension 

67

elated to personality rather than to training transfer climate. However, a careful reading of 

Rouiller and Goldstein’s (1993) paper reveals that they were clearly referring to the extent to 

which a trainee has control over his or her own work, and not to some aspect of individual 

personality. 

Implications and Limitations 

The findings of this study suggest a number of ways in which managers can improve the 

degree of training transfer. The importance of supervisor and co-worker support behaviour 

made apparent by this study confirms the findings of many earlier studies. Managers need to 

show that they are prepared to set goals, reinforce learning and provide appropriate tools and 

equipment. Failure to do so will substantially inhibit transfer. Supportive co-worker 

behaviour is likely to encourage the transfer of training to the job through peer pressure. In 

addition, managers need to convince employees that they really care about the training being 

transferred to the job. They need to ensure that employees have the time and freedom to 

apply their newly acquired skills, without the pressure of high workload levels or constant 

interruptions. This study has shown that employees are more likely to transfer learning to the 

job if they can reasonably expect to receive some valued personal outcomes by doing so. 

Managers also need to address employee concerns about the sincerity of their statements 

to employees. The interaction of attendance and cynicism about organisational change was 

found to a significant predictor of customer orientation. Cynicism about organisational 

change is a two-dimensional construct consisting of pessimism (programs that are supposed 

to solve problems around here won’t do much good) and dispositional attribution (the people 

responsible for solving problems around here don’t care enough about their jobs). High 

levels of cynicism about organisational change, and high levels of employee cynicism in 

general, are likely to be the outcome of a series of negative organisational events or 

experiences in which employees feel that they have in some way been let down or misled by 

the organisation or its management. 

This raises a number of important issues for managers. Firstly, employees are not likely 

to transfer learning if they perceive that managers are not serious about the value of the 

training or the need to transfer. This is particularly so where the training intervention is not a 

traditional skill based one, and might be considered by some employees as simply the latest 

management fad. Managers who direct employees to attend such a program, even though the 

manager may see little value in the program, are likely to be perceived as lacking integrity, 

and are unlikely to gain employee commitment to transferring any new skills. Managers who 

do not demonstrate that their decisions are based on soundly developed strategic thinking are 

also unlikely to inspire confidence and trust in their fitness for management. 

Finally, this study has several limitations that need to be acknowledged. One design 

limitation is the fact that the study relied on employee self-reports at one point in time. It is 

possible that a longitudinal study would have provided better insight regarding the influence 

of the transfer climate on transfer relapse. Also, data on third-party observations of employee 

customer service would have greatly added to the quality of this research. Unfortunately, 

constraints imposed upon the study necessitated complete respondent anonymity. The lower 

than desired response rate is another limitation, which raises the possibility that the 

68

espondent group was not representative of the population and that relationships among the 

variables could vary from the population parameters. Finally, this study measured attendance 

at the training program, which is a relatively simplistic dichotomous indicator representing 

whether the individual learned from the training program (i.e. those who didn’t attend would 

not have learned, except possibly indirectly through association with attendees). A more 

precise indicator of training would be to measure how much learning actually occurred by 

each person within the program. 

69

References 

Aiken, L. S., & West, S. G. (1991). Multiple Regression: Testing and interpreting 

interactions. Thousand Oaks: Sage Publications Inc. 

Appelbaum, E., Bailey, T., Berg, P., & Kalleberg, A. L. (2000). Manufacturing advantage: 

Why high-performance work systems pay off. Ithaca, N. Y.: Cornell University Press. 

Australian National Audit Office. (2005). Centrelink's Value Creation Program. Canberra: 

Government of Australia. 

Baldwin, T. T., & Ford, J. K. (1988). Transfer of training: A review and directions for future 

research. Personnel Psychology, 41(1), 63-105. 

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social 

psychological research: Conceptual, strategic, and statistical considerations. Journal 

of Personality and Social Psychology, 51(6), 1173-1182. 

Bartlett, K. R. (2001). The relationship between training and organizational commitment: A 

study in the health care field. Human Resource Development Quarterly, 12(4), 335- 

352. 

Bates, R. A., Holton, E. F. I., Seyler, D. L., & Carvalho, M. A. (2000). The role of 

interpersonal factors in the application of computer-based training in an industrial 

setting. Human Resource Development International, 3(1), 19-42. 

Becker, B. E., & Huselid, M. A. (2006). Strategic human resources management: Where do 

we go from here? Journal of Management, 32(6), 898-925. 

Bennington, L. (1999). Tools for transforming organisations. In F. Sofo (Ed.), Human 

resource development: Perspectives, roles, and practice choices (pp. 301-320). 

Warriewood, NSW: Business and Professional Publishing Pty Ltd. 

Bennington, L., & Cummane, J. (1998). Measuring service quality: A hybrid methodology. 

Total Quality Management, 9(6), 395-405. 

Benson, G. S., Young, S. M., & Lawler III, E. E. (2006). High-involvement work practices 

and analysts' forecasts of corporate earnings. Human Resource Management, 45(4), 

519-537. 

Brinkerhoff, R. O., & Montesino, M. U. (1995). Partnership for training transfer: Lessons 

from a corporate study. Human Resource Development Quarterly, 6(3), 263-274. 

Brown, T. J., Mowen, J. C., Donavan, D. T., & Licata, J. W. (2002). The customer 

orientation of service workers: Personality trait effects on self and supervisor 

performance ratings. Journal of Marketing Research, 39(1), 110-119. 

Burke, L., & Baldwin, T. T. (1999). Workforce training transfer: A study of the effect of 

relapse prevention training and transfer climate. Human Resource Management, 38(3), 

227-241. 

Burke, L., & Hutchins, H. M. (2007). Training transfer: An integrative literature review. 

Human Resource Development Review, 6(3), 263-296. 

Centrelink. (2007). Annual report, 2006-07. Canberra: Commonwealth of Australia. 

Champoux, J. E., & Peters, W. S. (1987). Form, effect size, and power in moderated 

regression analysis. Journal of Occupational Psychology, 60, 243-255. 

Chaplin, W. F. (1991). The next generation of moderator research in personality psychology. 

Journal of Personality, 59, 143-178. 

70

Clarke, N. (2002). Job/work environment factors influencing training transfer within a human 

service agency: Some indicative support for Baldwin and Ford's transfer climate 

construct. International Journal of Training and Development, 6(3), 146-162. 

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, 

NJ.: Lawrence Erlbaum,. 

Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the 

behavioral sciences (2nd ed.). Hillsdale, New Jersey: Lawrence Erlbaum Associates, 

Inc. 

Combs, J., Liu, Y., Hall, A., & Ketchen, D. (2006). How Much Do High-Performance Work 

Practices Matter? A Meta-Analysis Of Their Effects On Organizational Performance. 

Personnel Psychology, 59(3), 501-528. 

Cromwell, S. E., & Kolb, J. A. (2004). An examination of work-environment support factors 

affecting transfer of supervisory skills training to the workplace. Human Resource 

Development Quarterly, 15(4), 449-471. 

Facteau, J. D., Dobbins, G. H., Russell, J. E. A., Ladd, R. T., & Kudisch, J. D. (1995). The 

influence of general perceptions of the training environment on pretraining 

motivation and perceived training transfer. Journal of Management, 21(1), 1-25. 

Grant, M., & Hughes, P. D. (2007). Learning and development outlook 2007: Are we 

learning enough? Ottawa: Conference Board of Canada. 

Guadagnoli, E., & Velicer, W. F. (1988). Relation of sample size to the stability of 

component patterns. Psychological Bulletin, 103(2), 265-275. 

Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate Data 

Analysis (5th ed.). Upper Saddle River, NJ: Prentice-Hall Inc. 

Halligan, J. (2007). Advocacy and Innovation in Interagency Management: The Case of 

Centrelink. Governance, 20(3), 445-467. 

Holton, E. F. I., Bates, R. A., & Ruona, W. E. A. (2000). Development of a generalized 

learning transfer system inventory. Human Resource Development Quarterly, 11(4), 

333-360. 

Holton, E. F. I., Bates, R. A., Seyler, D. L., & Carvalho, M. B. (1997). Towards construct 

validation of a transfer climate instrument. Human Resource Development Quarterly, 

8(2), 95-113. 

Kelley, S. (1992). Developing customer orientation among service employees. Journal of the 

Academy of marketing Science, 20(1), 27-36. 

Kirby, J. R., Knapper, C. K., Evans, C. J., Carty, A. E., & Gadula, C. (2003). Approaches to 

learning at work and workplace climate. International Journal of Training and 

Development, 7(1), 31-52. 

Kontoghiorghes, C. (2001). Factors affecting training effectiveness in the context of the 

introduction of new technology - a US case study. International Journal of Training 

and Development, 5(5), 248-260. 

Kozlowski, S. W. J., Brown, K., Weissbein, D. A., Cannon-Bowers, J. A., & Salas, E. (2000). 

A multilevel approach to training effectiveness. In K. Klein & S. W. J. Kozlowski 

(Eds.), Multi-level theory, research, and methods in organizations (pp. 157-210). San 

Francisco, CA: Jossey-Bass. 

Lawler III, E. E., Mohrman, S. A., & Ledford Jr., G. E. (1998). Strategies for high 

performance organizations. San Francisco: Jossey-Bass. 

Lim, D. H., & Johnson, S. D. (2002). Trainee perceptions of factors that influence learning 

transfer. International Journal of Training and Development, 6(1), 36-48. 

71

Lim, D. H., & Morris, M. L. (2006). Influence of trainee characteristics, instructional 

satisfaction, and organizational climate on perceived learning and training transfer. 

Human Resource Development Quarterly, 17(1), 85-115. 

Lubinski, D., & Humphreys, L. G. (1990). Assessing spurious moderator effects: Illustrated 

substantively with the hypothesised ("synergistic") relation between spatial and 

mathematical ability. Psychological Bulletin, 107(3), 385-393. 

MacCallum, G. H., & Mar, C. M. (1995). Distinguishing between moderator and quadratic 

effects in multiple regression. Psychological Bulletin, 118(3), 405-421. 

Machin, M. A., & Fogarty, G. J. (2004). Assessing the antecedents of transfer intentions in a 

training context. International Journal of Training and Development, 8(3), 222-236. 

Mason, C. A., Tu, S., & Cauce, A. M. (1996). Assessing moderator variables: Two computer 

simulation studies. Educational and Psychological Measurement, 56(1), 45-62. 

Mathieu, J. E., Tannenbaum, S. I., & Salas, E. (1992). Influences of individual and 

situational characteristics on measures of training effectiveness. Academy of 


McDougall, M., & Beattie, R. S. (1998). The missing link? Understanding the relationship 

between individual and organisational learning. International Journal of Training and 

Development, 2(4), 288-299. 

McSherry, M., & Taylor, P. (1994). Supervisory support for the transfer of team-building 

training. The International Journal of Human Resource Management, 5(1), 107-119. 

Meyer, J. P., & Allen, N. J. (1997). Commitment in the workplace: Theory, research, and 

application. Thousand Oaks, CA: Sage. 

Mowday, R. T. (1998). Reflections on the study and relevance of organizational commitment. 

Human Resource Management Review, 8(4), 387-401. 

Mowday, R. T., Steers, R. M., & Porter, L. W. (1979). The measurement of organizational 

commitment. Journal of Vocational Behavior, 14, 224-247. 

Naquin, S. S., & Holton III, E. F. (2002). The effects of personality, affectivity, and work 

commitment on motivation to improve work through learning. Human Resource 

Development Quarterly, 13(4), 357-376. 

Newstrom, J. W. (1986). Leveraging management development through the management of 

transfer. Journal of Management Development, 5(5), 33-45. 

Nijman, D.-J. J. M., Nijhof, W. J., Wognum, A. A. M., & Veldkamp, B. P. (2006). Exploring 

differential effects of supervisor support on transfer of training. Journal of European 

Industrial Training, 30(7), 529-549. 

Noe, R. A. (2000). Invited reaction: Development of a generalized learning transfer system 

inventory. Human Resource Development Quarterly, 11(4), 361-365. 

Orpen, C. (1999). The influence of the training environment on trainee motivation and 

perceived training quality. International Journal of Training and Development, 3(1), 

34-43. 

Paxson, M. C., Dillman, D. A., & Tarnai, J. (Eds.). (1995). Improving response to business 

mail surveys. New York: John Wiley & Sons. 

Pfeffer, J. (1998). The human equation: Building profits by putting people first. Boston: 

Harvard University Press. 

Reichers, A. E., Wanous, J. P., & Austin, J. T. (1997). Understanding and managing 

cynicism about organizational change. Academy of Management Executive, 11(1), 48- 

59. 

72

Richman-Hirsch, W. L. (2001). Posttraining interventions to enhance transfer: The 

moderating effects of work environments. Human Resource Development Quarterly, 

12(2), 105-120. 

Rouiller, J. Z., & Goldstein, I. L. (1993). The relationship between organizational transfer 

climate and positive transfer of training. Human resource Development Quarterly, 

4(4), 377-390. 

Saks, A. M. A., & Belcourt, M. M. (2006). An investigation of training activities and transfer 

of training in organizations. Human resource management, 45(4), 629. 

Sharma, S., Durand, R. M., & Gur-Arie, O. (1981). Identification and analysis of moderator 

variables. Journal of Marketing Research, 18(3), 291-300. 

Smith-Jentsch, K. A., Salas, E., & Brannick, M. T. (2001). To transfer or not to transfer? 

Investigating the combined effects of trainee characteristics, team leader support, and 

team climate. Journal of Applied Psychology, 86(2), 279-292. 

Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics (3rd ed.). New York: 

HarperCollins College Publishers. 

Tesluk, P. E., Farr, J. L., Mathieu, J. E., & Vance, R. J. (1995). Generalization of employee 

involvement training to the job setting: Individual and situational effects. Personnel 

Psychology, 48(3), 607-632. 

Thayer, P. W., & Teachout, M. S. (1995). A climate for transfer model (AL/HR-TP-1995- 

0035): Brooks Air Force Base TX: Technical Training Research Division, Armstrong 

Laboratory. 

Tracey, J. B. (2005). Construct validity of a general training climate scale. Organizational 

research methods, 8(4), 353-374. 

Tracey, J. B., Hinkin, T. R., Tannenbaum, S., & Mathieu, J. E. (2001). The influence of 

individual characteristics and the work environment on varying levels of training 

outcomes. Human Resource Development Quarterly, 12(1), 5-23. 

Tracey, J. B., Tannenbaum, S. I., & Kavanagh, M. J. (1995). Applying trained skills on the 

job: The importance of the work environment. Journal of Applied Psychology, 80(2), 

239-252. 

Tziner, A., Fisher, M., Senior, T., & Weisberg, J. (2007). Effects of trainee characteristics on 

training effectiveness. International Journal of Selection and Assessment, 15(2), 167- 

174. 

Vardon, S. (1998). Restructuring in the Australian government: Creating a responsive service 

delivery agency. Speech to senior Canadian government officers. 

Wanous, J. P., Reichers, A. E., & Austin, J. T. (2000). Cynicism about organizational change. 

Group and Organization Management, 25(2), 132-153. 

Washington, C. L. (2002). The relationships among learning transfer climate, transfer selfefficacy, 

goal commitment, and sales performance in an organization undergoing 

planned change. Unpublished PhD, The Ohio State University, Ohio. 

73


Halifax, Ontario 

Nita Chhinzer 

College of Management and Economics 

University of Guelph 

Chhinzer@uoguelph.ca 

416.857.3570 

DISAGGREGATING UNEMPLOYMENT: JOB LEAVERS, LOSERS AND LAYOFFS 

This research suggests the need to disaggregate unemployed persons 

into job leaver, job loser and job layoff categorizations. 

Multinominal logit regression on Labour Force Survey data 

(n=38,546) suggests that demographic, human capital and work 

related variables account for almost a third of the variance in 

likelihood to fall into the disaggregated unemployment categories. 

Khaldoun Ababneh 

Faculty of Business 

McMaster University 

ababneki@mcmaster.ca 

905-525-9140 x. 26356 

There has been much written about profiling the labour force in North America (i.e. Aaronson et 

al., 2006; Cappelli, 2005; Juhn & Potter, 2006; i.e. Panagiotidis & Pelloni, 2007; Van Horn, 2006). 

Significantly less has been written about the characteristics of the employed. Of this, the majority of 

research treats unemployed persons as a homogenous group (most recently: Aaronson et al., 2006; 

Autor et al., 2006; most recently: Riley & Young, 2007). Traditionally, researchers have modelled job 

movers into one undifferentiated category when modelling the job mobility decision (Borjas, 1981; 

Kidd, 1991; Simpson, 1990). The research that attempts to understand micro level differences in 

unemployed persons focuses almost exclusively on economic data and is significantly dated (Borjas, 

1981; Henry S Farber, 1997; Henry S. Farber & Hall, 1993; Hamermesh, 1989; Hanisch, 1999; Kidd, 

1994; Picot et al., 1998). Additionally, these studies assess antecedents and outcomes of 

unemployment using job leaver (quits) or job layoff categories, with no consideration for the job loser 

(dismissals) category. This paper updates and modifies existing research on individual level 

differences based on categorizations of unemployment in three significant ways. 

First, this research treats the unemployed group as non-homogenous. Rather than comparing 

employed with unemployed persons, we identify individual level factors correlated with the 

likelihood to belong to the job leaver (quit), job loser (dismissal or permanent layoff) or job layoff 

category (temporary layoff) by assessing Labour Force Survey (LFS) data collected over a five year 

period. We use multinomial logit regression analysis on a sample size of 38,546 individuals to begin 

to analyse unemployed persons based on causes of unemployment. 

Second, we examine the Canadian labour force. To date, empirical evidence from Canada on the 

distinction of types of unemployment has been significantly hindered by the lack of data. Thus, only 

a limited number of studies are available exploring distinct categories of unemployment in Canada 

(Kidd, 1994; McLaughlin, 1991; Picot et al., 1998). The Canadian labour force is significantly 

different than the United States labour force. Levels of unemployment, employment legislation and 

social services to support the unemployed are also significantly different. We extend beyond existing 

research to focus on disaggregating unemployment within the Canadian realm. 

74

Third, we use demographic, human capital and work related variables to support the notion that 

unemployment via job leaver, job layoff and job losers categories results in different profiles of 

unemployed persons, when compared with a control group of job stayers (individuals who did not 

change jobs in the survey period). This extends existing research which is focused almost exclusively 

on the economic perspectives of unemployment. 

The primary contribution of this paper is to suggest that we must disaggregate the unemployed 

group to help us understand the pattern of unemployment in a more comprehensive and pragmatic 

way. Through profiling unemployment based on the job leavers, job losers and job layoff categories, 

we can understand patterns of unemployment, as well as the differences in the composition and 

correlations associated with each form of job loss. 

Next, we present core definitions and provide a brief review of existing literature. Following that, 

we present a discussion of variables used in this study. Due to the exploratory nature of this research, 

a limited number of variables were used in our analysis. Although additional variables may be 

influential in characterisizing job leavers, losers and layoffs, these specific variables were 

theoretically applicable and available in the LFS. The results section includes evaluation of labour 

market transition rates and multinomial logit estimates of the likelihood to belong to one of the three 

categories of unemployment on two levels; comparisons against the control group of job stayers and 

intergroup pair-wise comparisons. We end with discussions and limitation of the study. 

Disaggregating the Unemployed Group: Definitions 

Some individuals chose to voluntarily enter unemployment, through turnover in the form of a quit 

or a resignation. For the purpose of this study, the job leavers group is defined as individuals who 

were employed within the last twelve months, but were not employed at the time of the survey due to 

voluntary reasons (e.g. quit) (Statistics Canada, 2007). Comparatively, the job losers group is defined 

as individuals who were employed within the last twelve months, but employment was permanently 

terminated at the time of the survey due to involuntary reasons (e.g. dismissal or permanent layoff) 

(Statistics Canada, 2007). The last group is the job layoff group representing individuals who were 

temporarily laid off and have a potential for recall (Statistics Canada, 2007). It is important to note 

that the job layoff group experience temporary unemployment and may be recalled by the firm, 

whereas job loser’s employment is permanently terminated. 

As an independent group of unemployed persons, the job leavers group has been studied 

comprehensively in the past. A number of models propose theoretical antecedents of an employee’s 

intention to leave, including factors such as work and non work related variables, perceived 

alternatives and shock (Carnicer et al., 2004; P. W. Hom & Griffeth, 1995; Lee et al., 1996; Mobley, 

1982; Porter & Steers, 1973; Steers & Mowday, 1981). Hundreds of studies attempt to identify 

antecedents of voluntary turnover, resulting in many meta analyses on this topic (Cohen & Cohen, 

1983; Cotton & Tuttle, 1986; R. W. Griffeth et al., 2000; P. Hom et al., 1992; P. W. Hom & Griffeth, 

1995; Steel & Ovaille, 1984; Tett & Meyer, 1993). 

The most recent meta-analysis identified a significant number of variables as direct and indirect 

predictors of voluntary turnover in the form of quits (R. W. Griffeth et al., 2000). Eliminating 

variables about cognitions and behaviours about the withdrawal process (e.g. intention to quit, job 

search efforts) individual level variables found to have the highest correlation with voluntary job loss 

were organizational commitment (r = -0.27), role clarity (r = -0.24), tenure (r = -0.23), role conflict (r 

= 0.22), overall job sat (r = 0.22) and absenteeism (r = -0.21). Additionally, age and marital status are 

negatively correlated with voluntary turnover (r = -0.23 and -0.05 respectively) while education is 

75

positively correlated with voluntary turnover (r = 0.06) (for all correlations p-value < 0.05). The 

research ascertains that gender is not significantly correlated with voluntary turnover (r = 0.03). 

Existing research in turnover generally limits the analysis of the employed versus unemployed 

groups using the job leavers (quit) group to homogeneous represent unemployed person for three 

main reasons. First, in the past most turnover was voluntary (Byrt, 1957; Marsh & Mannari, 1977), 

therefore the study of involuntary turnover may have been perceived as non-imperative. Second, 

theory was easier to form when turnover could be treated as homogenous. It would be hard to explain 

quits, dismissals and layoffs in the same theory because they may have different determinants. 

Focusing on the voluntary turnover category provided a more homogeneous group to research. Third, 

involuntary turnover is organizationally initiated, so it was assumed that the selection procedure was 

solely performance based. This lead to the belief that “involuntary exits are desirable because 

employers would not want to keep poor performers/excess manpower” (R. Griffeth & Hom, 2001: pg 

4). 

Flows into unemployment, specifically job leavers, job losers and job layoffs receive limited 

attention in U.S. literature, and remain focused on economic indicators of each category (Borjas, 1981; 

Henry S Farber, 1997; Henry S. Farber, 1999; Henry S. Farber & Hall, 1993; Hamermesh, 1989). 

With a common sample of a series from the Displaced Workers Survey in the 1980’s and 1990’s, the 

focus of these studies is the antecedents and outcomes of unemployment via the job loser and job 

layoff categories, without consideration of the job leaver category. 

Due to a lack of data sources on unemployment in Canada, only Kidd (1994) and Picot et al. 

(1998) explore the issue of categorizing unemployed persons. Kidd (1994) examines whether a 

meaningful difference exists between quits and layoffs. The results provide support that job leavers 

and job layoffs are a non-homogenous group. The study collected Canadian labour market data, 

including reasons for unemployment in 1986 and 1987. Kidd’s econometric model assumed 

membership into one of four mutually exclusive categories: quit (n=617), layoff (n=261), job stayers 

(n=397), and a residual (other mover category). The distinction between a quit and a layoff was 

dependent on whether unemployment was voluntary; assuming that a quit was voluntary and a layoff 

was involuntary. Based on Kidd’s economic perspective, wage equation estimates were developed 

(controlling for marital status, age, education, industry, occupation and province of residence) and 

dependent on if the job separation was voluntary versus involuntary (quit vs. layoff). 

The findings of Kidd’s empirical research support the fact that when the voluntary versus 

involuntary distinction is made, the party who wishes to initiate the job separation gains monetary 

benefits. After job separation, those who quit (voluntarily separated) earned an average salary 18% 

higher than job stayers. Likewise, those who were laid off (involuntarily separated) earned an average 

salary 30% less than job stayers. This suggests that the economic benefit during an involuntary 

separation is positive for the employer, since the employee’s pay level was not representative of 

productivity in a fixed market. However, an employee whose market value was higher than the actual 

wage set by the employer gains the economic benefit of voluntary separation. Therefore, there are 

opposing antecedents to quits versus layoffs. 

There are a number of limitations of this study. Kidd’s study utilized data from the Labour 

Market Activity Survey (LMAS) of 1986-1987, therefore the data and findings are significantly dated. 

The sample accessed was full time, paid male workers between the ages of 16-64. Therefore, the 

study provides only a partial view of unemployment due to limitations in the data collected. Also, this 

research compared only quits versus layoffs. There is no awareness of those who entered 

unemployment through dismissals and no differentiation of permanent versus temporary layoffs. 

76

In a second Canadian study, Picot, Lin and Pyper (1998) used a random sample of all Canadian 

workers to study layoff trends. The information was extracted from the Longitudinal Worker File, 

which is one component of the Labour Force Survey. The purpose of Picot and her colleagues study 

was three fold; 1) to examine the underlying causes of layoffs, 2) to empirically prove an increase in 

layoffs in the 1990’s and 3) to examine if layoffs are continuous events. Picot et al. (1998) provide 

evidence of a number of correlations between various factors (such as age, gender, and skill level) 

and likelihood to experience. Layoff victims are older (over 55 years of age at time of layoff) when 

the layoff was a single event. In continuous layoff situations (where the individual is laid off from 5 

or more companies within a 10 year span), younger individuals are most likely to be the subjects 

(between 25 and 34 years of age). Annual earnings, education and skill level are found to be the most 

influential determinants of the likelihood of experiencing a lay off. However, this study does not 

include comparisons of layoffs, quits and dismissals. 

A crucial finding in the Picot et al. study was that from 1978-1993 a 1% change in unemployment 

was associated with a 0.89% decrease in quit rates, a 0.61% increase in use of temporary layoffs and 

a 0.38% decrease in hiring rates. There was also a small effect on use of permanent layoffs with a 

0.34% increase in permanent layoffs for every 1% increase in unemployment. One finding that was 

evident in the data, but not explicitly stated by the authors is that quit rates and layoff rates 

consistently reacted in opposite directions. This, further support for creating a distinction between job 

leavers, job losers and job layoffs categories is secured. 

Given the exploratory perspective adopted in the research, only a limited number of variables can 

be used to demonstrate that disaggregating unemployment will enhance our understand of the 

unemployment phenomena. To do so, we select and rationalize our choice of seven variables in the 

next section. Through analysis of these variables, we hope to secure support for examining 

unemployment within the three categories above. 

Theoretical Perspectives in Variable Selection 

The variables selected for the data analysis met two minimal standards. One, the variables must 

have a theoretical link to studies of unemployment. Two, the variables must be measured in the LFS 

for unemployed individuals. 

Human Capital Theory 

The first two variables are embedded in human capital theory; education and tenure. Human 

capital refers to the employee’s tacit knowledge of firm specific information, such as the knowledge, 

skills, abilities and other attributes of individual employees (Becker, 1963). Firm specific skills such 

as familiarity with products, procedures and technical characteristics of a firm cannot be transferred 

among firms (Hitt & Ireland, 2002; Schultze, 1999). 

Education. Education provides a general training program to help introduce individuals to broad 

concepts, industries and ideologies. Generally, the higher an individual’s education, the less firm 

specific their skill set, therefore their knowledge and skills are more transferable. This also translates 

into a lower level of firm specific human capital, which can affect organizational decisions regarding 

employee exits. In Griffeth, Hom and Gaertner’s (2000) meta-analysis on antecedents of turnover, a 

statistically significant positive relationship between education and voluntary turnover (quits) was 

noted. Although a correlation between education and turnover is established in existing research, no 

study explicitly examines the relationship between education and different flows into unemployment, 

as per this study. 

77

Individuals with lower levels of education may be less mobile in the workforce due to their 

lack of generalizable skills. These individuals may perceive their chances for re-employment to be 

low, due to high requirements for firm specific training upon reemployment. Likewise, individuals 

with low education may have experienced high levels of firm specific knowledge and training, 

therefore from a company perspective may not be candidates for layoffs during a downsizing event. 

Education is traditionally segmented in terms of four classifications: ‘high school or less’, ‘some 

post secondary education’, ‘completed post secondary certificate or diploma’, and ‘university and 

above’ (e.g. Industry Canada, Canada’s Office of Consumer Affairs). According to the Labour Force 

Survey in 2004, 41% of the labour force had completed high school or less as their highest level of 

educational attainment. A small percent had some post secondary education as their highest level of 

educational attainment (7.4%). An additional 36.9% of the labour force completed a post secondary 

certificate or diploma, while 14.7% of the labour force possessed a university degree or higher 

education. 

Tenure. Tenure is defined as the total time an individual is employed by the company. Generally, 

the higher an individual’s experience with the organization, the more firm specific their skill set. 

Traditionally, job tenure provided some protection from displacements, but the benefits of high tenure 

are shrinking (Fallick, 1996; Henry S Farber, 1997; Seitchik, 1991). Kidd (1995) and Farber (1993) 

provide evidence that tenure is influential in predicting individual unemployment. Individuals who 

remain employed have twice as much tenure than those who quit, and individual who quit generally 

have slightly longer tenure than layoffs. Tenure groups used in this research align with Kidd’s 

analysis (1994). 

In addition to Human Capital factors affecting this variable, longer tenure with a company also 

suggests that the individual employee may have more invested with the company such as investing in 

a house near work, work friendships extending to personal life and an attachment to the job. These 

investments are jeopardized when an employee with more experience loses employment, thus it is 

possible that high tenure is desirable for employment. Therefore, we would expect the unemployed 

groups to have lower tenure regardless of means of unemployment. 

Work Related Variables 

The next two variables selected are work related variables; industry and occupation. Individual 

work related variables include individual job or organizational factors that may be directly related to 

turnover behaviour, such as industry and occupation (Mobley, 1982). 

Industry. There has been an ongoing debate regarding the influence of industry on turnover. In 

the United States, chances of displacement increases significantly if the industry an individual is 

employed in is doing poorly overall (Fallick, 1996). Aligned with this perspective, industry 

differences are proven to have a significant and negative correlation with the likelihood for job loss in 

Canada (Kidd, 1994). In contrast, Picot et al (1998) provide evidence that the predictive layoffs are 

more of an individual company decision than an industry specific decision in Canada. They suggest 

that companies in the same industry, facing the same economic concerns can choose to layoff, freeze 

hiring, use technology to decrease costs, launch new products, or cut back services as possible 

competing responses to industry downturn. Therefore, turnover cannot be explained by cyclical 

variations in demand or industry level factors such as growth or decline. This debate remains 

unresolved; therefore the inclusion of industry as a variable in this study is justifiable. 

Industry trends can be explored using the goods versus services industry difference, as per 

previous unemployment research. Farber (1993) found that from 1982-1985, job loss was 

78

concentrated in the goods (manufacturing) industry, but in 1986-1991, the job loss was concentrated 

in the services industry. As manufacturing jobs become increasingly scarce in the Canadian 

employment outlook, employees may be less likely to quit due to a perceived lack of alternative 

employment opportunities in the manufacturing industry. Additionally, layoffs may be more likely to 

occur in industries on the decline, such as the manufacturing industry. In contrast, service sector jobs 

are increasing in the Canadian economy, therefore, employers may be less likely to dismiss 

employees, due to a perceived labour shortage in the service industries. 

Occupation. The occupation variable may be directly related to flows into unemployment. Over 

time, the number and types of occupational available to the labour force change due to technological 

advancements, globalization, economic growth, demographics and consumer behaviour. While there 

are thousands of possible occupations, we categorized jobs according to the North American Industry 

Classification System (NAICS). Most users of this type of information create clusters of similar 

occupations for the use and interpretation of the results (Fallick, 1996; Henry S Farber, 1997; Henry S. 

Farber & Hall, 1993; Kidd, 1994). 

Similarly, we use five main categories. First, ‘management, business, finance and administrative’ 

occupations create a bundle of jobs that are directly involved in providing services and guidance to 

employees at multiple levels in the organization. This group of occupations does not directly 

contribute to revenue generation or production, but is part of the core organizational structure. 

Second, occupations ‘unique to primary industries, processing and manufacturing’ create a cluster of 

jobs that directly impact an organizations production and are traditionally considered blue collar jobs. 

Next, ‘trades, transportation, equipment operators and related’ occupations focus on supply chain 

and logistical jobs in Canada. These account for almost a quarter of all occupations in the sample. 

Fourth, ‘sales and service’ occupations include jobs which require brokering of products/services or 

actual delivery of services (e.g. call centres). Lastly, a catch all group of ‘others’ includes jobs that 

the labour force survey could not clearly define under one occupational title. 

Projections for 2009 suggest that the services industry will continue to grow, while growth will 

stagnate, then decline in primary industries in Canada (Government of Canada and the Ontario 

Ministry of Training, 2007). In Ontario, 24% of job growth between 2004 and 2009 is projected to 

come from professional jobs while manufacturing will be responsible for an additional 10% of job 

growth (Government of Canada and the Ontario Ministry of Training, 2007). Given that the labour 

market and perceived alternative employment opportunities differ by occupation, it is perceivable that 

individuals in occupations with expected growth in Canada may be more likely to be in the job leaver 

category. These individuals may perceive that their occupations are in high demand, therefore may 

choose to exit the firm to gain more desireable employment terms or compensation. Individuals in 

occupations with minimal growth forecasts may be more likely to fall into the job loser and job layoff 

category, since some of these jobs may become obsolete. As well, these individuals would be less 

likely to turnover via quits (job leaver) since the labour market may be flooded with qualified 

candidates, therefore reducing perceived chances for reemployment. Unemployment trends may vary 

by occupation, therefore this was included in the analysis. 

Demographics 

The remaining three variables selected are demographic variables: age, marital status and gender. 

Demographic variables refer to individual attributes that employees bring to work. These traits 

remain stable across jobs, employers and contexts and are associated with the individual employee in 

all settings. Personal characteristic may influence the decision to quit since they help the employee 

predict their internal versus external advantages and disadvantages. These demographic conditions 

79

can dictate the employee’s perception of opportunities they have outside of the company, as well as 

likelihood to voluntarily leave, since most of these attributes are non-changeable by the employee. 

In contrast, a combination of federal, state and provincial laws has limited management’s ability 

to decide whom to separate from their jobs. Although management should be aware that using 

demographics as a determinant in practice (dismissals or layoffs) is legal only under exceptional 

circumstances (e.g. Bona Fida Occupational Requirement), cases of layoffs and dismissals are being 

met with increased legal resistant (Balkin, 1992). As a result, it is possible that the group of job 

leavers may be demographically different than the job stayers group, but there should be no 

demographic differences between the job stayers, job losers and job layoffs groups. 

Methods 

Data used in this analysis was collected from the Labour Force Survey (LFS) . Started in 1945 

and maintained by a body of the Canadian Federal Government (Statistics Canada), the LFS provides 

the only source of monthly labour force data in Canada. Responses are self-reported, therefore the 

analysis is one of self reported measures of flows into unemployment. 

Sampling 2% of the Canadian population a month, the LFS clusters individuals into three main 

categories: employed, unemployed and not in the labour force. This study uses the group of employed 

persons (or job stayers) as the base or control group. When the complete sample is assessed, the 

control group of employed persons overwhelms the unemployed persons group by a ratio of more 

than 30:1. A correction for this is required, since when the proportion of employed to unemployed 

(or vice versa) diverges from 50%, variance and correlations are attenuated (Pedhazur, 1982). A 

randomly selected group of employed persons equal in count to the group of unemployed persons 

allows for true unbiased assessment of correlates and variance of the flows into unemployment. 

Additionally, individuals who are not in the labour force (people unwilling and unable to work) 

represent a group that is neither employed or unemployed. Therefore, individuals not in the labour 

force were not included in the analysis. A mix of questions about the unemployment decision and 

activity prior to unemployment aid Statistics Canada in their classifying individuals into one of three 

unemployed groups: job leavers (quits/resignations), job losers (dismissals/permanent layoff) and job 

layoffs (temporary layoffs). 

Participants in the survey are sampled monthly and form a six month panel. The response rate 

averages 95% a month. In the rare case that a participant drops out of the panel, a weight adjustment 

is applied to the account and the individual is not replaced. The LFS also utilizes a seasonal 

adjustment for institutional events like vacation, holidays and climate events. Seasonal variations 

from almost 1,300 participants are adjusted to prevent seasonal factors from effecting 

employment/unemployment analysis. 

Since significant revisions were made to LFS questionnaire in 1976 and 1997, the period of study 

is limited to 2000-2004. This ensures reliability of the results, by guaranteeing survey questions were 

consistent. We pooled monthly data to develop an annual measure of flows into unemployment. More 

specifically, given that survey participants were part of a 6 month panel, we merged information from 

the March and September data files to create our database. The risk of sampling the same individual 

in the labour force twice is completely eliminated, through forcing six months of difference in the 

sample, increasing the validity of the results. 

A total of 19,273 unique individuals experienced unemployment during the survey period. An 

equal randomly selected number of employed persons from as the control group. Of the unemployed 

80

persons group, 3,542 participants experienced temporary laid offs, falling into the job layoff category. 

An additional 12,397 persons experienced some form of permanent involuntary flow into 

unemployment (e.g. dismissal or permanent layoff) falling into the job loser category. The remaining 

3,334 individuals initiated the flow into unemployment by resigning or quitting, thereby fall into the 

job leaver category. 

Multinomial Logit Regression Analysis 

Results 

Multinomial logit regression (MNL) analysis is conducted here to estimate the probability (or odd 

ratios) of an individual flowing into the job leaver, job loser, or job layoff category relative to remain 

in the job stayer category by using seven predictors (i.e. education, tenure, industry, occupation, age, 

gender, and martial status). To conduct the MNL analysis, we set the coefficients of the job stayer 

category to zero so that the other estimated parameters could be interpreted relative to this reference 

group (i.e. job stayer category). 

Using a chi-squared test to evaluate fit (χ² ( 54 , N = 38,546 ) = 12119.754 ), the model including 

seven predictors against the null model (constant-only model) is statistically significant. This means 

that the model with the seven predictors as a set is outperforming the null model in predicting 

individual unemployment status. Thus, we reject the null hypothesis that all coefficients in our model 

are jointly zero. The likelihood ratio-test for each of the seven predictors shows that each predictor of 

our model is statistically significant (p-value < .001) in influencing the likelihood that an individual 

will flow into a specific employment status. 

Table 1 provides an assessment of the over or under representation of each variable based on the 

corresponding flow into unemployment, compared to the control group (job stayers). For example, 

there are 18.7% more individuals with education levels of `high school or less` in the job layoff group 

than in the job stayer group. In contrast, there are 15.1% less individuals with `high school or less` 

education in the job leaver group than in the job stayer group. 

Table 1. 

Labour Market Transition Rates (percentage difference in population as compared to job 

stayers) 

Job 

Layoff 

Job 

Loser Job Leaver 

Education 

High school or less 18.7% -1.3% -15.1% 

Some post secondary -12.3% -4.1% 30.1% 

Post secondary certificate or diploma -5.3% 1.7% -1.7% 

university and above -60.0% 2.0% 54.0% 

Tenure 

1 year -27.8% 11.2% -12.2% 

2 years -14.8% -2.6% 26.1% 

3-4 years 8.9% -8.9% 25.0% 

5-9 years 38.7% -13.5% 12.6% 

10 years + 75.7% -19.3% -8.6% 

Occupation 

Management, Business, Finance, and Administrative 

Occupations -50.0% 3.1% 43.8% 

Sales and Service Occupations -33.2% -4.5% 51.5% 

Trades, Transportation and Equipment Operators and 

Related Occupations 36.3% 0.3% -39.7% 

Occupations Unique to Primary Industries, Processing and 44.7% 0.5% -22.8% 

81

Manufacturing 

Other -46.7% 2.5% 38.5% 

Industry 

Goods 38.5% 0.7% -48.4% 

Services -32.1% -0.6% 40.4% 

Sex 

Male 7.8% 2.3% -17.1% 

Female -12.6% -3.7% 27.8% 

Age 

25-34 -15.0% -1.8% 22.9% 

35-44 2.1% 0.0% -2.1% 

45-54 6.4% 0.8% -10.5% 

55-64 15.3% 2.5% -24.6% 

Marital status 

Married 44.8% 28.9% 24.8% 

Single -56.7% -39.5% -37.6% 

Divorced/Widowed/Separated -14.3% 6.7% 14.3% 

The results in Table 1 suggest that job losers (dismissals) and job stayers are similar in proportion 

of educational experience, suggesting that education level is not a main variable in the decision 

function to dismiss an employee. In fact, we consistently find that the job stayer and job leavers 

groups are similar in representation by the majority of the variables analysed in this study, with the 

exception of tenure and marital status. 

There is a negative relationship between education level and likelihood to experience a temporary 

layoff. Specifically, employees with high school or less education represent 18.7% more of the job 

layoff group than the job stayer group. Comparatively, employees with university and above 

education represent almost 60% less of those experiencing a job layoff that their proportion in the 

remaining labour force. This provides empirical support that education levels provide protection 

from layoff, as theorized in human capital theory. 

Flow into unemployment is more likely to be employee initiated when an employee possessed 

higher levels of education. Specifically, employees with high level of education represent 54% more 

of the job leaver category than they represent in the labour force. Aligned with this, individuals with 

lower levels of education were 15% less likely to initiate job loss. Following human capital theory, 

those with transferable skill sets (gained from general training and education) are more prone to 

initiate job loss through participation in the job leaver category than the job stayers and those with 

lower levels of education. 

At first glance, the results of tenure do not clearly identify a relationship between experience with 

the firm and flows into unemployment. However, if year 1 is eliminated, the relationships become 

more evident. Employees with high tenure make up more than their fair share of the employees laid 

off; almost doubling their representation in the 10 years plus group, as compared to the control group 

of job stayers. As tenure increases, so does the representation in the group of laid off persons. The 

opposite situation hold true for the job leavers group. As tenure increases, representation in the job 

leavers group decreases. In contrast to patterns between job losers and job stayers outlined in the 

education variable, tenure appears to negatively influence likelihood to be dismissed. Surprisingly, 

employees in their first year of employment are less likely to quit or be laid off, but slightly more 

likely to be dismissed, which is the opposite of the results for the remaining years. 

Tenure can also be viewed as a unique variable in that the group of job losers is somewhat 

affected by tenure when compared to job stayers. With the exception of tenure and marital status, the 

group of job losers was not proportionately different than the control group. The results suggest that 

dismissals and permanent layoff likelihood decreases with tenure. In the first year, employees are 

most likely to fall into the job losers category (represented 11.2% more in the job losers group than 

82

the job stayers group), and tenure does provide protection from dismissals and permanent layoffs in 

later years, when compared to the job stayers group (represented 19.3% less in the job losers group 

than the job stayers group). 

Management and business related occupations showed the largest range of change based on 

unemployment category. Individuals with these occupations has 50% less representation in the job 

layoff group, but 43.8% more representation in the job leaver group than their portion of the job 

stayers group. A similar pattern is revealed with sales and service jobs. The opposite situation holds 

true for trades, primary industries and manufacturing in Canada. Therefore, individuals in more white 

collar jobs are significantly more likely to initiate job loss via quitting or resigning from their job, 

while those in traditional blue collar jobs are much more likely to experience a layoff in Canada. 

A similar pattern is formed when we contrast the goods industry with the services industry. 

Individuals in the goods industry are significantly more likely to experience a job layoff, while 48.4% 

less likely to voluntarily leave their job. The opposite relationship is found in the services industries. 

As hypothesized, perhaps the growth of the services industries and the perceived tightness in the 

services labour market is responsible for these differences. The results suggest that when the services 

versus manufacturing differentiation is made, trends of flows into unemployment significant change. 

Thus, this variable is valuable in differentiating unemployment in Canada. 

Females are disproportionately overrepresented in the job leaver category by almost 28% and 

underrepresented in the job layoff category. There may be a number of factors associated with this 

such as age, non work related responsibilities, occupation and industry differences that can be 

attributed to gender. Future studies may be valuable in explaining the differences highlighted in the 

results for unemployment trends based on gender in Canada, as per Table 1. 

The age variable identifies an interesting trend. While the job losers group is almost identical in 

terms of representation to the job stayers group, as age increases, the chances of unemployment 

through job layoffs increases and unemployment through voluntary job loss (job leavers) decreases. 

This suggests a positive relationship between age and likelihood to be laid off, and a negative 

relationship between age and likelihood to quit or resign. This variable is important in that if the 

results were aggregated (comparing employed versus unemployed persons) no effect of age would be 

evident. However, when the age category is disaggregated, it is highly influential in determining 

types of unemployment in Canada. 

Married individuals are overrepresented (24.8% - 44.8%), while singles are underrepresented 

significantly (37.6% - 56.7%) in all categories of unemployment. This is one of two variables in 

which the job loser category is significantly different than the job stayers category. As well, 

individuals who were in a partnership that no longer exists due to death, divorce or separation are 

14.3% overrepresented in the job leaver category, and 14.3% underrepresented in the job layoff 

category. This is another ideal example supporting the need to disaggregate unemployment data in 

Canada. The relationship between marital status and unemployment remains largely unexplored in 

research, but the results suggest a direct or indirect influence of marital status on quits, dismissals, 

permanent layoffs and temporary layoffs in the Canadian labour force. 

Table 2. 

Multinomial Logit Estimates of the Likelihood of Flows into Unemployment 

Job Layoff 

Vs. 

Job Loser 

Vs. Stayers 

Job 

Leaver 

All movers 

Vs. 

83

Stayers Vs. Stayers leavers 

Education 

high school or less 1.145*** 0.494*** 0.246*** 0.512** 

(3.142) (1.639) (1.280) (1.668) 

some post secondary 0.782*** 0.259*** 0.285** 0.309** 

(2.186) (1.296) (1.329) (1.362) 

post secondary certificate or diploma 0.802*** 0..298*** 0.057 .284** 

Tenure 

(2.230) (1.347) (1.059) (1.328) 

1 year 1.376*** 2.626*** 2.078*** 2.279** 

(3.956) (13.820) (7.992) (9.768) 

2 years 0.834** 1.664*** 1.508*** 1.454** 

(2.303) (5.280) (4.516) (4.280) 

3-4 years 0.771*** 1.294*** 1.235*** 1.153** 

(2.162) (3.647) (3.438) (3.167) 

5-9 years 0.391*** 0.664*** 0.624*** 0.577** 

Occupation 

(1.478) (1.942) (1.865) (1.781) 

Occupations Unique to Primary Industry, 

1.440*** 0.449*** 0.083 0.581** 

Processing, Manufacturing (4.222) (1.568) (1.086) (1.789) 

Sales and Service Occupations 

0.680*** 0.128** 0.261*** 0.243** 

(1.975) (1.136) (1.299) (1.275) 

Trades, Transportation and Equipment Operators 1.696*** 0.526*** 0.148* 0.682** 

and Related Occupations (5.454) (1.691) (1.160) (1.977) 

Others .244** -0.069 -0.193** -.052 

Industry 

(1.276) (.933) (.824) (.949) 

Goods 0.804*** 0.478*** -0.215** 0.436** 

Sex 

(2.234) (1.613) (0.807) (1.547) 

Male -0.270*** 0.098** -0.013 0.007 

Age 

(0.764) (1.103) (0.987) (1.007) 

25-34 -0.403*** -0.549*** 0.017 -0.407** 

(0.668) (0.577) (1.017) (.666) 

35-44 -0.213** -0.306*** 0.010 -0.232** 

(0.809) (0.736) (1.010) (.793) 

45-54 -0.137* -0.165*** 0.024 -0.127* 


(0.872) (0.848) (1.024) (.881) 

Single 0.109* 0.420*** 0.478** 0.375** 

(1.115) 1.522 (1.613) (1.455) 

Others 0.203*** 0.369*** 0.448 0.349 

(1.225) (1.447) (1.565) (1.418) 

The reference variables are: job stayer (employment status), university and above (education), 10+ years (tenure), Management, Business, 

Finance, and Administrative (occupation), services (industry), female (sex), 55-64 (age), and married (marital status). The coefficients for 

the reference groups are all zero. 

Table 2 presents more related information concerning the multinomial logit analysis (MNL). The 

first, second, and third columns of Table 2 report the coefficient estimates and the odds ratios 

(reported in parentheses) of our multinomial logit analysis. The first column presents the coefficient 

estimates and the odd ratios comparing job layoffs with job stayers. The second column presents the 

coefficient estimates and the odd ratios comparing job losers with job stayers. The third column 

presents the coefficient estimates and the odd ratios comparing job leavers with job stayers. A 

positive coefficient indicates that a specific category of an independent variable increases the 

likelihood of being in a certain work status in comparison to the job stayers group (the reference 

group), while a negative coefficient indicates that a specific category (corresponding category or 

variable) of an independent variable decreases the likelihood of being in a certain work status in 

comparison to the job stayers group (the reference group). Asterisks identify the categories of the 

independent variables that have significant effects on the flows into unemployment based on our three 

categories. The probability (odds) ratios indicate the magnitude of the likelihood of belonging to a 

certain flow into unemployment relative to the job stayers group. A variable that increases the 

likelihood of being in a specific unemployed group relative to the job stayers group has probability 

ratio greater than one, while a variable that decreases the likelihood of being in a specific work status 

84

has probability ratio lower than one. Following is a presentation for the effects of each of the seven 

variables on the flows into unemployment. 

Education. Comparing job layoff with job stayer groups, column 1 of Table 2 shows that the 

coefficient for the categories ‘high school or less’, ‘some post secondary’, and ‘post secondary 

certificate or diploma’ are positive and significant. This means that individuals who hold ‘high school 

or less’, ‘some post secondary’, and ‘post secondary certificate or diploma’ level of education are 

more likely than individuals who hold a level of education of ‘university and above’ (reference group) 

to experience temporary layoffs. Specifically, Table 2 shows that the probability of being in a job 

layoff status relative to the probability of being in a job stayer status is higher for individuals who 

hold ‘high school or less’ (3.142 times higher), ‘some post secondary’ (2.186 times higher), and ‘post 

secondary certificate or diploma’ (2.230 times higher) than for individuals who hold ‘university and 

above’ degree. Comparing the job loser group with job stayers, column 2 of Table 2 reports similar 

effects for the education categories as those reported above when comparing job layoff with job 

stayers, but with different odds ratio. Comparing job leavers with job stayer, column 3 of Table 2 also 

reports similar result as those discussed above except that individuals who hold ‘post secondary 

certificate or diploma’ were not significant. 

Tenure. With regard to tenure, the results demonstrate that the coefficient for individuals who 

have been with the organization for ‘1 year’, ‘2 years’, ‘3 years’ and ‘5-9 years’ are more likely to be 

in job layoff, job loser, or job leaver category than to be in the job stayer category, as compared to 

those who have been with the organization for ten years and above (i.e., the reference group for 

tenure). For example, individuals who have been with the organization for two years are 13.820 times 

more likely to flow into job losers’ status than individuals who have been with the organization for 

ten years or more. The results also indicate that the likelihood of flowing into job loser, layoff, or 

leaver status diminish as individuals gain more tenure with an organization. For example, the odds 

ratios of flow into job layoff status are highest, in descending order, for: (a) individuals who have one 

year tenure (3.956); (b) individuals who have two years (2.303), (c) individuals who have 3-4 years 

(2.162) and individuals how have 5-9 years (1.478). 

Occupation. The result from Table 2 show that the probabilities of a job layoff relative to the 

probability of a job stayer status is higher for individuals who worked for ‘trades, transportation and 

related occupations’, ‘primary industry and manufacturing’, ‘sales and service occupations’, and the 

other occupations category (in that order) than for individuals in the reference group (i.e. the category 

‘management and administrative related’). This means that individuals who hold occupations in 

management and administrative related were less likely to be laid off than individuals who are 

holding all the other type of occupations. Similar results are observed when comparing the probability 

for those of job losers to those of job stayers, however with different odd ratios. 

Industry. Individuals who worked in goods industry were significantly more likely to flow into 

job layoff or job loser category than to remain in job stayer category, as compared to those in the 

service industry. However, individuals who worked in good industry are significantly less likely to 

flow into job leaver category than to remain in job stayer category, as compared to those in the 

service industry. 

Gender. Comparing flows into job layoffs with flows into job stayers, the coefficient for “Male” 

is negative and significantly different from zero. This indicates that males are less likely than females 

to flow into the job layoff category. Comparing flows into job losers with flows into job stayers, the 

85

esult also shows that males are less likely than females to flow into job layoffs category. However, 

although the above findings concerning gender are significant, their magnitudes are relatively small. 

Age. According to the results in Table 2, age is also an important factor in determining the flows 

into unemployment. All the coefficients that comparing job layoffs and job losers with job stayers for 

the different levels of the age categories (i.e. 25-34,35-44, and 45-54) are negative and significantly 

different from the reference group (i.e. 55-64 age group). The interpretation of this is that younger 

workers are less likely to flow into the job layoff or job loser categories relative to job stayers. When 

compared the flows into job leavers relative to job stayers, we observed no significant effect for age. 

Marital status. Although the results in Table 2 show significant relationships between the subcategories 

of the marital status variable and the flows into unemployment, the magnitudes of flowing 

into a specific work status are very minimal. 

Univariate Logit Analysis 

Previous researchers (Borjas, 1981; Kidd, 1994) examining job separation did not differentiate 

among the different types unemployment. Specifically, past research grouped all the job movers into 

one category, which they labelled as job movers. However in our research, we argue that there are 

different categories of unemployment and these categories are differently influenced by the seven 

predictors suggested in this study. To support our argument, we conducted a univariate logit analysis 

and compare its results with the multinomial analysis results discussed above. 

Column 4 of Table 2 provides the binary logit analysis results. Although the result of the binary 

analysis demonstrates that the seven factors significantly influenced the probability (odd ratios) of an 

individual being classified into job stayer or job mover work status, a multinomial logit analysis that 

disaggregate job movers into three categories (job layoffs, job losers, and job leavers) demonstrates 

that there are significant differences in the effect of the factors associated with these categories. For 

example, the results clearly demonstrate that the odds ratios of flowing into job layoff, job loser, or 

job leaver category, compared with the flows into a job stayer category, are respectively, 3.14, 1.63, 

and 1.28 times higher for individuals who have high school or less level of education. In addition, 

table 2 also shows that the odds of flowing into job layoff, job loser, or job leaver category, compared 

with the flows into a job stayer category, are respectively, 3.95, 13.82, and 7.99 times higher for 

individuals who worked with an organization for a year or less. 

Table 3. 

Multinomial Logit Estimates of the Likelihood of Flows into Unemployment 

Job losers 

Vs. 

leavers 

Job layoffs 

Vs. 

leavers 

Job layoffs 

Vs. 

losers 

Education 

high school or less 0.248** 0.898** 0.651** 

(1.281) (2.456) (1.917) 

some post secondary -0.025 0.498** 0.523** 

(.975) (1.645) (1.687) 

post secondary certificate or diploma 0.241** 0.744** 0.504** 

(1.272) (2.105) (1.655) 

Tenure 

1 year .548** -.702** -1.250** 

(1.729) (.495) (.286) 

2 years .156* -0.673** -0.830** 

(1.169) (.510) (.436) 

3-4 years .059 -.464** -.523** 

86

(1.061) (.629) (.593) 

5-9 years 0.040 -0.233@ -0.273** 

Occupation 

(1.041) (.792) (.761) 

-.124 -0.437** -0.313* 

Management, Business, Finance, and Administrative Occupations (.884) (.646) (.731) 

Sales and Service Occupations -0.257** -0.018 0.240* 

(.773) (.983) (1.271) 

Trades, Transportation and Equipment Operators and Related 0.254* 1.111** 0.858** 

Occupations (1.289) (3.038) (2.358) 

Occupations Unique to Primary Industries, Processing and 

0.243* 0.921** 0.678** 

Manufacturing (1.275) (2.512) (1.969) 

Industry 

Goods 0.693** 1.019** 0.326** 

(1.999) (2.769) (1.385) 

Sex 

Male 0.111* -0.257** -0.368** 

(1.117) (.744) (.692) 

Age 

25-34 -0.566** -0.420** 0.146* 

(.568) (.657) (1.157) 

35-44 -0.316** -0.222@ 0.094 

(.729) (.801) (1.098) 

45-54 -0.188* -0.160 0.028 

(.828) (.852) (1.028) 


Married -0.058** 0.369** 0.311** 

(1.059) (1.446) (1365) 

Single -0.021 0.124 0.145@ 

(0.979) (1.446) (.1156) 

Reference variables are: university and above (education), 10+ years (tenure), other (occupation), services (industry), female (sex), 55-64 

(age), divorced, widowed or separated (marital status) 

To examine if these ratios are significantly different from each other, we conducted two more 

new separate multinomial logit analyses by using the job leavers as reference group for the first 

analysis and using job losers as the reference group for the second analysis. Table 3 shows the result 

of these multinomial logit analyses. For example, table 3 shows that individuals who have high 

school or less are more likely to experience dismissal or permanent layoff (odd ratio = 1.281) and 

temporary layoff (odd ratio = 2.456) than voluntarily enter unemployment through resigning. Table 3 

also provides several significant results that demonstrate that there are different types of movers (or 

flows into unemployment) and these types are differently influenced by the seven predictors 

suggested in this study. In sum, the above discussed analysis provide strong support for our 

arguments regarding the need of disaggregating job movers into three categories (job layoffs, job 

losers, and job leavers) instead of pooling them into one group. 

Discussion 

There are a number of noteworthy contributions of this paper. Overall, this research is just the 

beginning of our understanding patterns of flows into unemployment at both practical and theoretical 

levels. The unemployed group can no longer be assumed to be homogeneous. There are significant 

differences in the composition and correlations associated with the job layoff, job leaver and job loser 

groups. Table 2 clearly identifies that disaggregating the unemployed group helps us understand the 

patterns of flows into unemployment in a more comprehensive and pragmatic way. 

As outlined in Table 1, the job loser group is not significantly different than the job stayer group. 

These two groups are different only in the marital status and tenure of their members. This suggests 

that when dismissing an employee, age, gender, education, occupation and industry do not change the 

87

composition of the active labour force. Instead, the composition of the active labour force is 

significantly affected by job layoffs and job leavers. It is critical to note that on average, if the job 

layoff group was over represented in a specific category, then the opposite relationship is found for 

the job leaver group (e.g. there were 48.4% less people in the job leaver group and 38.5% more 

people in the job layoff group than in the job stayer group for the goods industry) and vice versa. 

Future research can evaluate if there are consistently opposite antecedents to job layoff and job leaver 

groups. 

Patterns of unemployment have been outlined in this paper. For example, the higher the education, 

the lower the likelihood to be laid off. Additionally, individuals employed in the services industry are 

predominantly more likely to quit (job leaver), whereas individuals employed in the manufacturing 

industry are more likely to be laid off (job layoff). These patterns can be further solidified in future 

research to address why these norms are occurring and what the practical implications of these 

differences are. 

The multinomial data analysis can be arranged into an algorithm to help predict patterns of labour 

force movement as the mix of the labour force changes. This data can be used for multiple purposes 

such as policy development for unemployment insurance, human resources planning within the firm, 

and even career selection. The sample provides statistical strength and the data spans across a five 

year period, securing our confidence in the generalizability of the results. 

Limitations of this study include the limited number of variables used in this research. Doe to the 

exploratory nature of the research, only seven variables were analysed to suggest differences in 

categories of unemployed persons. Future studies can include behaviour or cognitive variables 

(organizational commitment, job satisfaction, work relates stress), economic variables (wages, 

inflation) and additional demographic variables (race, visible minority status, number of dependants). 

As well, the data is limited to the Canadian labour force and cross sectional in nature. The diversity of 

the labour force and the complexity of understanding employment patterns can be evaluated using 

similar studies across countries, or in a longitudinal analysis. 

References 

Aaronson, S., Fallick, B., Figura, A., & Pingle, J. (2006). The recent decline in the labor 

force participation rate and its implications for potential labor supply/comments and 

discussion. Brookings Papers on Economic Activity, 69-145. 

Autor, D. H., Katz, L. F., & Kearney, M. S. (2006). The polarization of the u.S. Labor market. 

The American Economic Review, 96(2), 189. 

Balkin, D. B. (1992). Managing employee separations with the reward system. The Executive, 

6(4), 64. 

Becker, G. (1963). Human capital. New York: Columbia Press. 

Borjas, G. J. (1981). Job mobility and earnings over the life cycle. Industrial & Labor 

Relations Review, 34(3), 365. 

Byrt, W. (1957). Methods of measuring labour turnover. Personnel Practices Bulletin, 13, 

413-417. 

Canada, S. (2007). Guide to the labour force survey. In L. S. Division (Ed.): Minister of 

Industry. 

Cappelli, P. (2005). Will there really be a labor shortage? Human Resource Management, 

44(2), 143-150. 

88

Carnicer, M., Sanchez, A., Perez, M., & Jimenez, M. (2004). Analysis of internal and 

external labour mobility: A model of job-related and non-related factors. Personnel 

Review, 33(2), 222. 

Cohen, J., & Cohen, P. (1983). Applied multiple regression correlation analysis for the 

behaviour sciences (2nd ed). Hillsdale, NJ: Erlbaum. 

Cotton, J., & Tuttle, J. (1986). Employee turnover: A meta- analysis and review with 

implications for research. Academy of Management Review, 11, 55-70. 

Fallick, B. C. (1996). A review of the recent empirical literature on displaced workers. 

Industrial & Labor Relations Review, 50(1), 5. 

Farber, H. S. (1997). The changing face of job loss in the united states, 1981-1995. 

Brookings Papers on Economic Activity. 

Farber, H. S. (1999). Mobility and stability: The dynamics of job change in labor markets. 

The Handbook of Labor Economics, 3. 

Farber, H. S., & Hall, R. (1993). The incidence and costs of job loss: 1982-91; comments and 

discussion. Brookings Papers on Economic Activity(1), 73. 

Government of Canada and the Ontario Ministry of Training, C. a. U. (2007). Ontario job 

futures. In C. a. U. a. t. E. A. a. I. D. Labour Market Information and Research group 

of the Ministry of Training, Ontario Regional Office (Ed.) (Vol.): Ontario Ministry of 

Training, Colleges and Universities and the Government of Canada. 

Griffeth, R., & Hom, P. (2001). Retaining valued employees. Thousand Oaks: Sage 

Publications. 

Griffeth, R. W., Hom, P. W., & Gaertner, S. (2000). A meta-analysis of antecedents and 

correlates of employee turnover: Update, moderator tests, and research implications 

for the next millennium. Journal of Management, 26(3), 463. 

Hamermesh, D. S. (1989). What do we know about worker displacement in the u.S.? 

Industrial Relations, 28(1), 51. 

Hanisch, K. (1999). Job loss and unemployment research from 1994-1998: A review and 

recommendations for research and intervention. Journal of Vocational Behaviour, 55, 

188-220. 

Hitt, M., & Ireland, D. (2002). The essence of strategic leadership: Managing human and 

social capital. Journal of Leadership & Organizational Studies, 9(1), 3. 

Hom, P., Caranikas-Walker, F., Prussia, G. E., & Griffeth, R. (1992). A meta-analytical 

structural equation model of employee turnover. Journal of Applied Psychology, 77, 

890-909. 

Hom, P. W., & Griffeth, R. (1995). Employee turnover. Cincinnati, OH: South-Western. 

Juhn, C., & Potter, S. (2006). Changes in labor force participation in the united states. The 

Journal of Economic Perspectives, 20(3), 1. 

Kidd, M. P. (1991). An econometrc model of interfirm labour mobility. Econometrica, 24, 

517-535. 

Kidd, M. P. (1994). Some canadian evidence on the quit/lay-off distinction. The Canadian 

Journal of Economics, 27(3), 709. 

Lee, T. L., Mitchell, T. R., Wise, L., & Fireman, S. (1996). An unfolding model of voluntary 

employee turnover. Academy of Management Journal, 39(1), 5. 

Marsh, R. M., & Mannari, H. (1977). Organizational commitment and turnover - a prediction 

study. Administrative Science Quarterly, 22(1), 57. 

McLaughlin, K. (1991). A theory on quits and layoffs with efficient turnover. Journal of 

Political Economy, 99(1-29). 

89

Mobley, W. (1982). Employee turnover: Causes, consequences and control. Reading: 

Addison-Wesley. 

Panagiotidis, T., & Pelloni, G. (2007). Nonlinearity in the canadian and u.S. Labor markets: 

Univariate and multivariate evidence from a battery of tests. Macroeconomic 

Dynamics, 11(5), 613. 

Pedhazur, E. J. (1982). Multiple regression in behavioral research: Explanation and 

prediction (2nd ed.). New York: Holt, Rinehart and Winston. 

Picot, G., Lin, Z., & Pyper, W. (1998). Permanent layoffs in canada: Overview and 

longitudinal analysis. The Canadian Journal of Economics, 31(5), 1154. 

Porter, L. W., & Steers, R. M. (1973). Organizational, work and personal factors in employee 

turnover and absenteeism. Psychological Bulletin, 80(2), 151. 

Riley, R., & Young, G. (2007). Skill heterogeneity and equilibrium unemployment. Oxford 

Economic Papers, 59(4), 702-726. 

Schultze, C. (1999). Downsized and out? The Brookings Review, 17, 9-14. 

Seitchik, A. (1991). Who are displaced workers? In John T Addison ed. “Job Displacement: 

Consequences and Implications for Policy” Detroit: Wayne University Press. 

Simpson, W. (1990). Starting even? Job mobility and the wage gap between young single 

males and females. Applied Economics, 22, 723-737. 

Steel, R. P., & Ovaille, N. K. (1984). A review and meta-analysis of research on the 

relationship between behavioral intentions and employee turnover. Journal of Applied 

Psychology, 69, 673-686. 

Steers, R., & Mowday, R. (1981). Employee turnover and post-decision accommodation 

process: in L. Cummings and B. Staw Research in Organizational Behaviour, JAI 

Press, Connecticut. 

Tett, R. P., & Meyer, J. P. (1993). Job satisfaction, organizational commitment, turnover 

intention, and turnover: Path analyses based on meta-analytical findings. Personnel 

Psychology, 46(2), 259. 

Van Horn, C. E. (2006). Mega-trends in the american workforce. Human Resource 

Development Quarterly, 17(4), 475. 

90

ASAC 2008 Richard J. Long 

Halifax, Nova Scotia University of Saskatchewan 

Tony Fang 

York University 

DO EMPLOYEES PROFIT FROM PROFIT SHARING? 

A LONGITUDINAL ANALYSIS OF CANADIAN ESTABLISHMENTS 

Using panel data from a large sample of Canadian establishments, this 

paper examines whether there is any link between adoption of an 

employee profit sharing plan and subsequent employee earnings. Overall, 

growth in employee earnings during the three-year period subsequent to 

adoption of profit sharing did not differ significantly between 

establishments that had or had not adopted profit sharing. However, 

growth in employee earnings was significantly higher among profit 

sharing adopters that paid above-market wages prior to adoption of profit 

sharing. This suggests that profit sharing may be financially beneficial to 

employees in establishments making high investments in human capital. 

Although employee profit sharing is a pay practice that has a long history (Coates, 1991), and one 

that many firms continue to adopt (Lawler, Mohrman, & Ledford, 1998; Long & Shields, 2005; 

Parent, 2002), there is little evidence on whether and under what conditions employees benefit 

financially from profit sharing. While proponents argue that profit sharing increases total employee 

earnings (Bell & Hanson, 1987; Tyson, 1996), others contend that the effect of profit sharing on 

employee earnings will be neutral (Weitzman, 1984), and still others argue that profit sharing can 

actually serve to reduce employee earnings (Katz & Meltz, 1991). 

This is an important issue, from both a conceptual and practical perspective. Understanding the 

effects of profit sharing on employee earnings can help improve our theoretical understanding of this 

concept, and will also provide guidance to those (such as employees, their unions, and public policy 

makers) who have had a long-standing interest in knowing whether profit sharing is financially 

beneficial for employees (Florkowski, 1991). Using panel data from a sample of 1,717 Canadian 

establishments, this paper examines whether the adoption of employee profit sharing increases, 

decreases, or does not change employee earnings subsequent to adoption, and whether several factors 

(employee participation, union density, company size, and compensation level) condition its effects 

on employee earnings. Our research contributes to knowledge by applying a longitudinal design to a 

carefully constructed sample of Canadian establishments (the first profit sharing study to do so), by 

assessing both cash earnings and total earnings, and by testing for interactions with important 

establishment-level characteristics. 

Theoretical and Empirical Background 

Why should employee profit sharing affect employee earnings? The answer seems obvious—if 

employees start receiving profit sharing payments in addition to their regular compensation, then their 

total earnings should increase. But note that this outcome is contingent on two key circumstances. 

Total employee earnings will increase only when (a) the employer is profitable and actually pays a 

profit sharing bonus to its employees, and (b) this bonus exceeds any downward adjustments that may 

91

e made to other pay components subsequent to adoption of profit sharing. 

Regarding the first circumstance, if employee profit sharing is itself a practice that serves to 

increase company profits, as proponents would argue (Bell & Wallace, 1987; Tyson, 1996), this 

would provide an additional avenue for increased employee earnings. 2 Increased profits would 

produce a larger profit sharing bonus, and would also provide the employer with a greater financial 

capacity on which to base increases to components of pay other than profit sharing. But note that a 

causal connection between employee profit sharing and employer profitability is not a necessary 

condition for profit sharing to result in an increase in employee earnings, providing the employer is 

profitable subsequent to adoption of profit sharing. Absent a profitability-enhancing effect of profit 

sharing, profit sharing could increase employee earnings through a redistribution of profit from 

capital to labor. Of course, this would occur only if employers refrain from making downward 

adjustments (in excess of the profit sharing bonus) to other pay components. 

Whether employers would make such downward adjustments depends on their motives for 

adopting employee profit sharing. Theory suggests three main sets of motives for adopting profit 

sharing, all aimed at enhancing firm performance, but operating through different processes. The first 

set of motives is based on the substitution argument (Weitzman, 1984; Kruse, 1993). Under this 

argument, firms use profit sharing to substitute for fixed pay components (i.e. wages and benefits) to 

better align the firm’s labor costs with fluctuations in its ability to pay. When the firm’s financial 

capacity is high (i.e. in times of high profitability), employees receive a higher level of earnings, but 

when the firm’s financial capacity declines, so do employee earnings, thus reducing labor costs. 

Absent a variable pay component (as provided by employee profit sharing), the main alternative for 

reducing labor costs is employee layoffs, which risks loss of valuable human capital. In his 

longitudinal study of US firms, Kruse (1996) found that firms with higher financial variability were 

indeed somewhat more likely to adopt profit sharing, although the magnitude of this effect was small. 

Firms pursuing the substitution motive may effect this substitution gradually (through 

constraining future increases in fixed pay components) or more immediately. For example, a common 

use of employee profit sharing in both the United States and Canada is as a vehicle to accumulate 

retirement savings for employees (Kruse, 1993; Long, 2006). One possibility, then, is to discontinue 

an existing retirement savings plan that requires fixed commitments from the employer in favor of a 

retirement plan based on profit sharing. Another possibility is simply to cut wages in conjunction with 

the introduction of profit sharing, as was done by financially-troubled North American automakers 

during the 1980s (Katz & Meltz, 1991). In this latter circumstance, however, the motive was not so 

much to introduce profit sharing as to make employers and their unions more amenable to the 

substantial pay cuts that the automakers argued were necessary for firm survival. 

In contrast, the second set of motives centers around using profit sharing as a vehicle explicitly 

intended to increase total employee earnings, with the object of enhancing employee attraction and 

retention. In this case, profit sharing may be regarded by employers as a less risky way to move to 

above-market “efficiency wages” than by increasing fixed wages and benefits. Alternatively, lowwage 

employers may use profit sharing to move closer to market pay rates. Either way, the employer 

has no intention of reducing other pay components, which would defeat the purpose of the profit 

sharing plan. To effect this increase in total employee earnings, some employers may simply add 

profit sharing to their current compensation practices, while others may use profit sharing as a vehicle 

2 Although the empirical evidence that employee profit sharing increases company productivity is quite clear, the 

empirical evidence on whether or not employee profit sharing actually increases firm profits is inconclusive 

(Magnan & St-Onge, 2005). For example, in his US study, Kim (1998) found that while profit sharing appeared to 

lead to increased company productivity, it did not lead to increased company profitability. He speculated that the 

productivity gain was fully captured by employees, in the form of profit sharing bonuses. 

92

to deliver a new benefit to employees. For example, employers that do not currently have employee 

pension plans may introduce employee profit sharing as a vehicle for generating retirement savings 

(Kruse, 1993; Tyson, 1996). 

The third set of motives centers around the explicit use of profit sharing as a productivityenhancing 

vehicle, by serving to increase employee motivation and cooperation on the job (Long, 

2000). In contrast to the efficiency-wages motive described above, the motive is not to increase firm 

performance by increasing employee earnings (which does so by attracting and retaining more highly 

qualified and productive employees), but to create a work context in which employees are motivated 

to work more diligently and effectively towards organizational goals. Employee profit sharing 

provides both the incentive and the reward for so doing. The implicit assumption is that an effective 

employee profit sharing plan should increase employee earnings, but that is not the direct motive for 

adoption of profit sharing. 

Given this, to understand the impact of employee profit sharing on employee earnings, it would 

be useful to understand the motives of top management for introducing employee profit sharing. One 

study that attempted to directly tap the motives of top management for adopting employee profit 

sharing could be found (Long, 1997). In his study, Long (1997) conducted telephone interviews with 

Chief Executive Officers of Canadian firms that had recently implemented employee profit sharing. 

Using an open-ended question, he found that the most frequently cited motives for adopting profit 

sharing could be clustered into two main groups. The first group of motives centered around 

improving company performance, through “improving employee motivation,” “promoting 

teamwork,” or “helping employees better understand the business.” The second set of motives 

centered around providing better rewards to employees, with profit sharing seen as “improving the 

compensation package,” “rewarding loyal employees,” “retaining employees,” and “building 

employee commitment.” 

Overall, no Canadian CEO mentioned any motive that might imply making pay more variable by 

reducing the fixed portion of the compensation package. However, in a survey of managers employed 

at US firms that had employee profit sharing, Mitchell and Broderick (1990) queried managers (not 

necessarily chief executive officers) on whether profit sharing was best at “raising productivity,” 

“increasing loyalty”, or “linking labor costs to firm’s economic conditions.” The answer most 

frequently selected was “linking labor costs,” followed by “increasing loyalty.” However, these 

responses are likely less indicative of the motives for introducing profit sharing than the perceived 

results of profit sharing. 

What is the overall evidence on the impact of employee profit sharing on employee earnings? 

Unfortunately, most evidence on this question is not recent, tends to be cross-sectional in nature, and 

shows mixed results. Mitchell, Lewin and Lawler (1990) used 1974 survey data from the United 

States Bureau of Labor Statistics, and found that both employee hourly wages and total compensation 

were higher in firms with profit sharing. However, in further research, they examined union contracts 

during the 1981-1988 period, and found that 36% of union contracts containing profit sharing 

provisions contained first year wage reductions, compared to only 14% of contracts that did not 

contain profit sharing. Consistent with this, data from the 1979-1988 period, Bell and Neumark (1993) 

examined US data from the 1979-1988 period and found that, among unionized manufacturing firms 

in the United States, those with profit sharing showed a lower growth in labor costs than firms 

without profit sharing (implying that profit sharing served to constrain employee earnings). 

A survey by the US Chamber of Commerce (1989) conducted in 1989 found that, in the 

manufacturing sector, fixed compensation was lower in profit sharing firms than those without profit 

sharing, but the opposite was true among nonmanufacturing firms.) Kim (1998) used a US data base 

93

collected in 1986 to conclude that profit sharing had increased labor costs in US firms, and, by 

implication, employee earnings. Finally, a study by Handel and Gittleman (2004), based on 1995 data 

from US business establishments, found profit sharing to be significantly positively related to 

employee earnings. 

In European research, Estrin and Wilson (1989) found that, among British engineering and 

metalworking firms during 1978-1982, fixed pay was higher in firms with profit sharing than those 

firms without profit sharing. Wadhwani and Wall (1990) also found in their sample British 

manufacturing firms that profit sharing tended to increase total employee compensation. Hart and 

Hubler (1991) examined a survey of German workers conducted in 1984-1985, and found that profit 

sharing was associated with higher individual wages, and found no support for the substitution 

argument. However, a more recent British study (Forth & Millward, 2004) based on 1998 data found 

no relationship between “financial participation” (which co-mingled profit sharing and employee 

stock plans) and employee hourly earnings, and a recently-published paper (McNabb & Whitfield, 

2007) based on the same data set found no relationship between presence of employee profit sharing 

and employee earnings. 

However, to adequately address the question of whether profit sharing affects employee earnings, 

longitudinal research is needed, and just two such studies could be found. Parent (2002) used data 

from the US National Longitudinal Survey of Youth collected during the 1990s to examine individual 

employee earnings before and after employees started receiving profit sharing payments and found 

interesting results—profit sharing apparently increased the earnings of male employees, but had no 

impact on the earnings of female employees. Kruse (1993:117) examined data from US public 

corporations during the 1975-1990 period and concluded that there was “very little difference in 

average compensation growth” between those firms that had or had not adopted profit sharing. He 

also concluded that there was some evidence for a substitution effect, as a slight increase in total 

compensation among profit sharing firms (relative to non-profit sharing firms) was less than the 

amount of the profit sharing bonuses. But as he notes, the sample on which he bases this conclusion is 

small, numbering just 30 companies. 

Conditions Affecting Profit Sharing and Earnings 

While the question of whether profit sharing affects employee earnings is our central focus, we 

also examine several conditions that may influence this relationship. Specifically, does employee 

participation in decision-making, union density, firm size, or the pre-existing compensation level of 

employees affect the relationship between the introduction of employee profit sharing and subsequent 

employee earnings? 

If profit sharing is to increase total employee earnings, it is more likely to do so when profit 

sharing serves to increase the total financial resources available to the firm. Although the precise 

conditions under which profit sharing is most likely to enhance the financial performance of the firm 

are not well understood, one of these possible conditions is scope for employee participation in 

decision making. Numerous commentators (Bell and Hanson, 1987; Strauss, 1990; Kandel and Lazear, 

1992) argue that profit sharing will be more effective in improving organizational performance when 

accompanied by participatory practices. Proponents argue that the participatory mechanism serves as 

a key channel through which employees can operationalize the interest in workplace performance that 

has been generated by the financial incentive (Levine & Tyson, 1990). This argument is also 

consistent with the “high-involvement,” “high-commitment,” or “high-performance” models of 

strategic human resources management, which posit that it is the interaction between a variety of 

complementary human resources practices which produces significant increases in company 

94

performance (Allen & Wright, 2007; Delery & Doty, 1996; Lawler, 1986, 1992; Pil & MacDuffie, 

1996). If so, this higher company performance should translate into higher employee earnings, by 

increasing the size of the profit sharing bonuses, by increasing the firm’s capacity for higher fixed pay, 

or both. 

There is in fact some empirical evidence that supports this argument. Kim (1998) found in his US 

sample that profit sharing increased firm profitability when combined with employee involvement 

programs, but not otherwise. McNabb & Whitfield (2007) found a significant positive interaction 

between profit sharing and employee participation (in the form of joint consultative schemes) on 

employee earnings in Britain. 

Another condition under which profit sharing may be more likely to lead to increased employee 

earnings is when employees are members of a trade union. The argument here is that, if they accept 

profit sharing, employees represented by a union will be better able to protect and maintain their other 

(fixed) pay components than employees who are not so represented. Moreover, through their 

bargaining power, unionized workers may also be in a better position to negotiate profit sharing plans 

that are beneficial to employees, by ensuring, for example, that “threshold” levels for the payment of 

profit sharing bonuses are not unrealistically high. 

However, rather than working to create more lucrative employee profit sharing plans, unions have 

generally focused their attention on simply opposing profit sharing plans, because of a preference for 

negotiated fixed wages, because of a concern that profits are subject to management manipulation, 

and because of concerns that profit sharing will be used as a tool to weaken loyalty to the union (Katz 

& Meltz, 1991). Indeed, a large body of evidence can be found that points to a negative association 

between union presence and presence of profit sharing, including studies in Canada (Long, 1989; Ng 

& Maki, 1994; Wagar & Long, 1995; Jones & Pliskin, 1997; Long & Shields, 2005), the United 

States (Cheadle, 1989; Kim, 1993; Cooke, 1994; Kruse, 1993, 1996), Britain (Poole, 1989), Germany 

(Heywood et al, 1998), and Australia (Long & Shields, 2005). But other studies for Canada (Long, 

1992), Britain (Estrin & Wilson, 1989), Germany (Carstensen et al, 1992), and Australia (Drago & 

Heywood, 1995) show no association, while two studies show positive relationships, one in Britain 

(Gregg & Machin, 1988) and the other in Brazil (Zylberstajn, 2002). 

However, all of the above results are from cross-sectional studies. In the two longitudinal studies 

that have addressed this issue, Kruse (1993; 1996) found some very interesting results. When he 

examined cross-sectional data, he found that union presence was negatively related to presence of 

profit sharing in his two U.S. samples. However, when he examined adoptions of profit sharing, he 

found no relation between union presence and subsequent adoption of profit sharing in either sample. 

And when he examined cash-based profit sharing plans only, he found a significant positive 

relationship between union presence and adoption of profit sharing. This may indicate that, in the 

United States at least, unions are attempting to shape the nature of profit sharing plans, preferring 

cash-based plans over deferred profit sharing plans. 

A third factor that may influence the relationship between employee profit sharing and employee 

earnings is company size. If company size affects the success of profit sharing, then this may also 

affect the employee earnings produced by profit sharing. However, arguments can be made that firm 

size will be either negatively or positively related to profit sharing effectiveness. The negative 

argument is based on what economists refer to as the “1/N” or “free-rider” problem (Olson, 1971; 

Jensen & Meckling, 1976). If an individual employee increases effort and productivity, that 

individual receives only a small portion of the productivity gain, having to share it with all others 

included in the profit sharing system (“N”). Even if an individual does not change his or her effort, he 

or she can still gain from the increased effort of others, and thus become a “free rider.” The 

95

magnitude of this problem is thought to increase as “N” increases, suggesting that larger firms will 

benefit less from profit sharing than smaller firms. 

However, there are several counterarguments to this line of thinking. Proponents of profit sharing 

contend that profit-sharing systems can put into motion a set of dynamics that will discourage “free 

riding” and “loafing.” For example, Fitzroy and Kraft (1986) argue that if employees as a group 

understand that their economic well-being is maximized under conditions where free riding and 

loafing are minimized, then group norms may develop that value high productivity, and workers 

themselves will monitor adherence to these norms—“mutual monitoring” in agency terms. Similarly, 

Cooper, Dyck, and Frohlich (1992) argue that collective pay systems can overcome these problems if 

they include worker participation and a fair distribution rule. To the extent that these processes negate 

the “1/N” problem, then smaller firms may not benefit more from profit sharing than larger firms, and 

would therefore be no more likely to adopt profit sharing. 

Indeed, there may be reasons why profit sharing might be more beneficial to larger firms than to 

smaller firms. Larger firms will inherently have higher monitoring costs, because of their greater 

number of employees, and if profit sharing can play a role in reducing these monitoring costs, as 

suggested by Long’s (1994) study, profit sharing may be more beneficial to larger firms. Finally, if 

profit sharing helps to make employees more knowledgeable about and interested in the performance 

of the company as Long (1997) found, employees may be more motivated to share information that 

will contribute to higher quality organizational decision making (Kruse, 1993). Since it might be 

easier for employees to withhold this information in larger firms, where top management is more 

remote from the shop floor, profit sharing may benefit larger firms more than smaller firms. 

Overall, the weight of empirical evidence is against a negative relationship between firm size and 

presence of employee profit sharing, as most studies show either no relationship between firm size 

and profit sharing, or a positive relationship. No relationship between firm size and presence of 

employee profit sharing was found by studies conducted in Canada (Long, 1989; Wagar & Long, 

1995; Long, 2002), the United States (Cheadle, 1989; Kruse, 1993, 1996) and Germany (Heywood et 

al, 1998), while longitudinal studies of profit sharing adoptions in the U.S. (Kruse, 1993, 1996) also 

showed no relationship with firm size. Positive relationships between firm size and presence of profit 

sharing were found in studies in Canada (Jones & Pliskin, 1997; Long, 1997; Long & Shields, 2005), 

in Britain (Poole, 1989; Poole & Jenkins, 1998), in Germany (Carstensen et al, 1992), and in 

Australia (Long and Shields, 2005). Just two studies show a negative relationship, one in Britain 

(Estrin & Wilson, 1989) and one in Japan (Kato & Moroshima, 2003). 

Finally, one other factor that may condition the relationship between profit sharing and employee 

earnings is the relative value of the human capital employed within the firm, as proxied by whether 

the firm compensates its employees above the market average for its industry. Presumably, firms pay 

above-market wages in order to attract and retain a higher quality of human capital within the firm. 

These firms may see profit sharing as a mechanism for leveraging their high investment in human 

capital, as employees at these firms may have more capacity to contribute to firm success than 

employees at firms with a lower quality of human capital. Hart and Hubler (1991) also point out that 

under rent-sharing theory, workers with relatively high levels of wage compensation are more likely 

to participate in profit sharing, as Long and Fang (2007) have found. Because of the value added by 

these employees, and their relative scarcity, it seems unlikely that firms with a high investment in 

human capital would use profit sharing for any purpose other than sharing rents with these employees, 

thus raising the total earnings of these employees. 

Methodology 

96

Sample and Analytical Procedure 

In conducting this research, we utilize a longitudinal panel of data, based on the Workplace and 

Employee Surveys (WES) conducted by Statistics Canada in 1999, 2001, and 2004. These surveys are 

designed to be representative of the total population of “workplaces” in Canada, but exclude business 

locations in the sparsely populated Yukon, Nunavut and Northwest Territories, as well as those in 

agriculture, fishing, road, bridge and highway maintenance, government services and religious 

organizations. The WES then follows the same workplaces over time, although replacement is made 

in every third year for workplaces that drop out of the survey. As utilized by Statistics Canada, a 

“workplace” is a business unit located at a single geographic location, and is analogous to the term 

“establishment” as frequently used in survey research. In this paper, we will generally use the more 

commonly understood term “establishment” to denote the unit of analysis. Our sample is limited to 

for-profit organizations only. 

The sample frame for the WES was generated from the Statistics Canada Business Register, 

which is a list of all businesses in Canada, updated monthly. Prior to sample selection, the business 

locations on the frame were stratified by industry, region, and size (based on estimated employment), 

and the sample was then selected using a Neyman allocation (Statistics Canada, 2004). The response 

rates for the 1999, 2001, and 2004 workplace surveys are stated by Statistics Canada as 95.2%, 85.9%, 

and 81.7% respectively, with most of the “non-responders” comprising owner-operators with no paid 

employees (Statistics Canada, 2006). Given the breadth and sensitivity of the information collected, 

these are rather remarkable response rates, no doubt facilitated by the facts that cooperation with 

Statistics Canada is obligatory and that extensive legal protections ensure confidentiality of responses. 

Data were collected through computer-aided telephone interviews with senior management 

officials at each workplace, conducted by trained interviewers based in Statistics Canada’s regional 

offices. Each workplace was first sent a copy of the survey, with instructions to regard the survey as 

“as a working tool to inform you ahead of time of the questions being asked and to help you in 

preparing your answers.” As the survey is lengthy, and includes many questions requiring reference 

to company records, the intent was to allow respondents time to locate this information before being 

interviewed. The instructions emphasized that the survey forms are not to be returned by mail, but 

that the information is to be provided directly to the interviewer. The intent here is to provide the 

opportunity for the interviewer to clarify questions and answers, and then to follow up if necessary. 

After each survey, before any data were made available for research purposes, Statistics Canada 

spent more than two years conducting various procedures to ensure a clean data set. During data 

collection, the computer aided interview format provided various checks to reduce the possibility of 

input errors or incorrectly recorded values. Following data collection, extended input editing was 

applied, followed by extensive data analysis and ratio editing to determine outlying observations 

based on robust outlier detection programs (Statistics Canada, 2004). 

The longitudinal panel of data for our study was constructed by first taking the 1999 WES and 

eliminating all workplaces with less than ten employees, those that are not for-profit enterprises, those 

that reported having profit sharing in 1999, and those that were not also included in the 2001 and 

2004 surveys. We also eliminated workplaces that adopted profit sharing during the 2001-2003 period. 

This resulted in 1,717 workplaces in our panel. A new variable was created in the 2001 data set based 

on whether the workplace reported having employee profit sharing in the 2001 survey, with “1” 

indicating that the workplace had adopted profit sharing, and “0” indicating the workplace continued 

not to have employee profit sharing. 

The rationale for this approach is that we wished to identify recent adopters of profit sharing (i.e. 

97

those that adopted between the 1999 and 2001 surveys, and then follow the growth of employee 

earnings during the three-year period 2001-2004. In this way, we have pre-existing data for both the 

workplaces that did and those that did not adopt profit sharing, and can compare earnings growth in 

the two groups, while incorporating a large array of control variables (as measured in 2001). 

The average workplace size (number of employees) is 51, and the average union density is 22.3 

percent. The distribution of workplaces by industry is: resources (1.4%), labor-intensive tertiary 

manufacturing (5.8%), primary product manufacturing (3.1%), secondary product manufacturing 

(5.8%), capital intensive tertiary manufacturing (6.3%), construction (6.1%), 

transportation/wholesaling (14.3%), communication/utilities (3.3%), retailing/consumer services 

(21.9%), finance/insurance (7.5%), real estate (1.6%), business services (15.2%), education and 

health services (5.3%), and information/cultural services (2.4%). 

Variable Measures 

An establishment was deemed to have adopted employee profit sharing if respondents to the 2001 

WES responded “yes” to the following question: 

“Does your compensation system include … [a] profit sharing plan? Profit-sharing plan 

is any plan in which employees receive a share of the profits from the workplace.” 

Any plans that applied only to managers were not deemed to be “employee profit sharing plans,” 

and these cases were eliminated from the panel. All remaining cases were designated “0” (no profit 

sharing adoption) or “1” (profit sharing adoption). Of the 1,717 establishments that did not have 

employee profit sharing in 1999, 247 (14.4%) had adopted it by 2001. 

Two measures of employee earnings growth are utilized. In so doing, we use an approach similar 

to that used by Kruse (1993) to control for industry differences. Growth in direct employee earnings 

was calculated by first taking the total gross payroll (including regular wages, commissions, overtime 

pay, piecework payments, and special payments) during the most recent fiscal year prior to data 

collection in 2001, and dividing this sum by the number of employees at the establishment. This 

quotient was then divided by the average employee earnings within the industrial sector in which the 

establishment operates, thus producing a ratio indicating whether the establishment paid above (a 

score of greater than 1) or below (a score of less than 1) the market in 2001. We label this variable 

“Cash Earnings 2001.” The cash earnings growth variable was derived based on the difference in real 

earnings (CPI-adjusted total payroll) between 2004 and 2001, divided by the 2001 cash earnings 

variable. 

However, merely using “cash real earnings growth” as the dependent variable may not portray the 

entire earnings picture. For example, some employers may consider profit sharing payments as 

“benefits” rather than direct earnings. This may be particularly true in cases where profit sharing 

payments are deferred, and are used as part of a retirement pension plan. Therefore, we also used a 

second measure of employee earnings growth—“Total Real Earnings Growth.” This measure was 

calculated in the same way as “cash real earnings growth,” except that it also included the cash value 

of non-wage benefits, such as the employer’s contribution to pension plans and other employee 

benefits. Another advantage of this second measure of earnings growth is that it will incorporate any 

decreases in the value of non-wage benefits subsequent to adoption of profit sharing. It is conceivable, 

for instance, that an employer may reduce non-wage benefits in concert with or subsequent to the 

adoption of profit sharing. 

To assess employee participation, we utilize a “participatory practices” index. 

98

Respondents were asked which (if any) of the following practices are currently in place, on a formal 

basis, for nonmanagerial employees: (a) suggestion systems, (b) problem solving teams, (c) joint 

labor-management committees, (d) information sharing programs, (e) flexible job design, and (f) selfdirected 

work groups. The participatory practices score for each establishment is the total number of 

these practices in place, and thus varies from “0” to “6”. This type of method has been commonly 

used in attempting to ascertain the extent to which firms practice employee participation (Pil & 

MacDuffie, 1996; Walsworth & Verma, 2007; Zatzick & Iverson, 2006). Because this variable 

measure is an index, and not a scale, reporting of a value for Cronbach’s alpha is not appropriate 

(Delery, 1998). Union density is the proportion of total employees at a given establishment covered 

by a collective bargaining agreement. Establishment size is taken as the total number of employees at 

a given establishment. 

To control for industry sector, thirteen dummy variables are created, representing all of the 

sectors discussed earlier in this section, with the exception of retailing, which serves as the omitted 

(comparison) variable for analytical purposes. A further set of controls is used to control for the 

possible effect of performance pay other than profit sharing. For example, individual incentives have 

long been positively associated with employee earnings (Mitchell, Lewin, & Lawler, 1990; Lazear, 

2000; Parent, 2002). Therefore, through the use of dummy variables, we control for the presence of 

individual incentives, merit pay, gain sharing, and employee stock plans. These controls are used in 

all multivariate analysis. 

Data analysis was carried out using OLS multiple regression, with each workplace weighted to 

represent its proportion in the general population. All continuous variables included in interaction 

terms were mean-centered before calculation of each interaction term. 

Results and Discussion 

Table 1 shows the means, standard deviations, and bivariate correlations for the sample. As can 

be seen, numerous variables are significantly related to profit sharing adoption. Profit sharing 

adopters are more likely to have all four types of performance pay plans—especially individual 

incentives and gain sharing—than establishments that did not adopt profit sharing. Establishments 

with more participatory practices are significantly more likely to adopt profit sharing, while 

establishments with more unionization are significantly less likely to adopt profit sharing. Profit 

sharing adopters also show significantly higher employee earnings in 2001—both in terms of cash 

earnings and total earnings—than establishments that did not adopt profit sharing. Indeed, the only 

variable not significantly related to profit sharing adoption is establishment size. This confirms the 

importance of controlling for these variables in our multiple regression analysis. 

Table 2 shows the multiple regression results, for both cash real employee earnings growth and 

total real employee earnings growth. As can be seen, profit sharing adoption is not significantly 

related to real employee earnings growth over the three-year period subsequent to adoption of profit 

sharing, regardless of whether the measure of real earnings growth is cash compensation or total 

compensation. The unstandardized regression coefficients are positive, but do not reach statistical 

significance. Thus, adoption of profit sharing appears to neither decrease employee earnings, as 

critics would fear, nor increase employee earnings, as advocates would expect. This result is virtually 

identical to that of Kruse’s (1993: 117) longitudinal study in the United States, where he found “very 

little difference in average compensation growth” between firms that had or had not adopted 

employee profit sharing. 

One possible interpretation of this result is support for the substitution argument, as Kruse (1993) 

99

has also noted. Assuming that the majority of establishments that adopted profit sharing were 

profitable in the period subsequent to adoption of profit sharing (our data in fact confirm this), it is 

not unreasonable to assume that profit sharing bonuses must have been paid by most establishments. 

Yet, payment of these bonuses has apparently not increased employee earnings. If so, then other 

earnings components must have been reduced in magnitude. What this implies is that in many 

establishments the adoption of profit sharing has served to maintain net employee earnings while 

reducing the fixed component of their compensation structures. 

100

Table 1 

Means, Standard Deviations, and Correlations a 

Variable Mean s.d. 1 2 3 4 5 6 7 8 9 10 11 

1. Profit Sharing Adoption .14 .35 - 

2. Participation Index 1.24 1.42 .19*** - 

3. Union Density .22 .35 -.10*** .09*** - 

4. Establishment Size 51.0 142.4 .04 .12*** .13*** - 

5. Cash Employee Earnings 2001 1.00 .61 .11*** -.08*** -.05* .01 - 

6. Total Employee Earnings 2001 1.00 .60 .10*** -.07*** -.04 .02 .99** - 

7. Individual Incentives .44 .50 .20*** .15*** -.06** .05* .09*** .09*** - 

8. Merit Pay .31 .46 .08*** .04* -.02 .07* .02 .02 .36*** - 

9. Gain Sharing .20 .40 .17*** .15*** .03 .03 -.05 -.04 .33*** .10** - 

10. Employee Stock Plan .11 .32 .09*** .18*** .11*** .09** -.01 .002 .29*** .31** .21*** - 

11. Cash Real Earnings Growth .08 .47 .01 -.07** .00 -.01 -.25*** -.25*** .06* .02 .00 .08*** - 

12. Total Real Earnings Growth .09 .48 .02 -.06** .01 -.01 -.25*** -.25*** .06* .01 .00 .07*** .99** 

a n = 1,717. *p

Table 2 

Multiple Regressions Predicting Employee Earnings Growth a 

Variable 

Growth in Cash Real Earnings Growth in Total Real Earnings 

Coefficient Standard Error Coefficient Standard Error 

Constant .271*** .094 .266*** .090 

1. Industry Controls 

Resources .004 .114 .037 .127 

Labor-Intensive Mfg. .082 .084 .086 .086 

Primary Product Mfg. .111 .093 .111 .095 

Secondary Product Mfg. .002 .068 .013 .068 

Capital-Intensive Mfg. .154* .083 .181** .088 

Construction .207* .119 .223* .120 

Transport/Wholesaling .103 .080 .110 .080 

Communications/Utilities .010 .065 .017 .066 

Finance/Insurance .143 .124 .137 .123 

Real Estate .203 .156 .213 .154 

Business Services .089 .134 .100 .141 

Education/ Health Services -.087 .096 -.109 .096 

Info/Cultural Services -.013 .088 -.011 .089 

2. Performance Pay Controls 

Individual Incentives .127*** .047 .127** .047 

Merit Pay -.031 .053 -.039 .054 

Gain Sharing -.082 .057 -.079 .056 

Employee Stock Plan .100 .079 .094 .085 

3. Establishment Characteristics 

Participation Index -.038* .022 -.035 .022 

Union Density .023 .077 .042 .080 

Establishment Size .00001 .00008 .00002 .00009 

Employee Earnings 2001 b -.273*** .048 -.268*** .046 

4. Profit Sharing Adoption .040 .059 .053 .061 

5. Interaction Terms 

PS X Participation .012 .023 .011 .023 

PS X Union Density -.055 .159 .015 .157 

PS X Size .00004 .00012 .00002 .00013 

PS X Earnings 2001 b .127** .060 .114 † .059 

Cases 1717 1717 

R 2 .116*** .118*** 

a OLS specification (unstandardized regression coefficients) with standard errors for both specifications. 

b Cash Earnings 2001 used for regressions predicting Growth in Cash Real Earnings, and Total Earnings 2001 used 

in regressions predicting Growth in Total Real Earnings. 

† p

Although profit sharing may therefore be seen, on average, as earnings neutral to employees, this 

implied substitution of variable pay for fixed pay increases the variability of employee earnings, and 

shifts some additional business risk to employees. However, unlike in the well-known case of individual 

incentives (Mitchell, Lewin, & Lawler, 1990), employees are apparently not receiving any compensation 

for undertaking this additional risk, since total employee earnings are unchanged subsequent to adoption 

of profit sharing. From an employee perspective, therefore, the implementation of employee profit sharing 

may actually result in a less attractive compensation outcome, once the (uncompensated) additional risk is 

factored in. 

However, are there any circumstances under which profit sharing adoption may positively affect 

employee earnings? Earlier, we speculated that profit sharing may show an interaction with any one of 

several variables—participatory practices, union density, company size, and compensation level policy. In 

fact, Table 2 does show one significant interaction effect—between profit sharing adoption and a highwage 

compensation policy. Employees in establishments that adopted profit sharing which had a highwage 

policy showed cash earnings growth about 12.7 percentage points higher than employees in other 

profit sharing establishments, and total earnings growth about 11.4 percentage points higher. This result 

suggests that employees in high-wage establishments will benefit from employee profit sharing, while 

employees in other establishments will not. This is consistent with the notion that establishments with a 

high investment in human capital will use profit sharing as a means to “share economic rent” and thus 

enhance the financial rewards to their employees. 

None of the other three variables show any interaction with profit sharing. That there is no evidence 

of an interaction between profit sharing and employee participation on employee earnings suggests that 

accompanying profit sharing with employee participation will not help employee earnings. That there is 

no significant interaction between profit sharing and union density suggests that unions do not play a 

significant role in developing more lucrative profit sharing plans, or in avoiding earnings substitution. 

That establishment size appears to play no significant role in the effects of profit sharing on employee 

earnings growth may indicate that size does not necessarily affect the results of profit sharing. 

That one prominent effect of employee profit sharing is apparently the substitution of variable for 

fixed pay is interesting, given that the Canadian CEOs in Long’s (1997) gave no indication of such a 

motive for their adoption of employee profit sharing. Of course, it is possible that other factors motivate 

adoption of profit sharing and that substitution of variable for fixed pay is an unintended side-effect. 

Another possibility is that motives for adoption of profit sharing have changed since Long’s study, which 

was conducted in 1989/90. Of course, it is also possible that many CEOs were not being entirely candid 

in identifying their motives for adoption of profit sharing. 

Finally, before concluding our discussion, we would like to briefly touch on several findings not 

central to our main question, but which are interesting nonetheless. One such finding is the relationship 

between employee participation and employee earnings. While there is some evidence that “highinvolvement” 

human resource practices can be beneficial to organizational performance (Ichniowski, 

Shaw, & Prennushi, 1997; Bailey, 1993; Huselid, 1995), there is little evidence to indicate that these 

practices are beneficial to employees, at least in terms of their earnings. Indeed, only one positive study 

could be found. Forth and Millward (2004) utilized a summative index of “high-involvement management 

practices” and found that this index was positively associated with employee earnings in their British 

sample. However, other studies in the United Kingdom (McNabb and Whitfield, 2007) and in the United 

States (Osterman, 2000; Handel & Gittleman, 2004) find no significant relationship between participatory 

practices and employee earnings. Indeed, McNabb and Whitfield (2007: 1014) find that “employees in 

establishments that have adopted quality circles actually face lower earnings, on average.” They conclude 

that even when tied to performance pay, employee participation offers little financial advantage to 

employees. 

103

Our results also provide no support for the argument that employee participation is beneficial to 

employee earnings. Indeed, we found our “participatory practices index” to be significantly negatively 

related to cash employee earnings (in 2001) and to cash real earnings growth, whether accompanied by 

employee profit sharing or not (as the insignificant interaction coefficients show). 

Turning to other performance pay plans, we found that individual incentives are significantly 

positively related to both cash and total employee earnings (in 2001) and to growth in both cash real 

compensation and total real compensation. This result is consistent with a long line of research suggesting 

that employees on individual incentives earn more than those who are not (Parent, 2002). Our research 

also extends this finding to growth in employee earnings. As for gain sharing plans, while our results 

show that although employees on gain sharing plans did not earn less than other employees in 2001, they 

did experience significantly slower growth in cash real earnings. Finally, merit pay showed no significant 

relationship to earnings in 2001 nor to earnings growth. Note, however, none of the results for the various 

types of performance pay (except of course for profit sharing) or for participation are based on adoptions 

of these practices, but simply presence of these practices. 

As with all empirical studies, our study has both strengths and limitations. Strengths include use of a 

data set which embodies a large-scale sample, a very high response rate, and is carefully designed to be 

representative of Canadian for-profit establishments. Use of the establishment level of analysis allows for 

more precise measurement of the study variables than the corporate-wide measures that are often used in 

this kind of research. Another strength is that the data base allows for longitudinal analysis, but a 

limitation is that we are able to follow employee earnings for only a three-year period subsequent to 

adoption of profit sharing. Whether the results would change if a longer time span were used is unknown. 

A potential problem for all types of survey research is the reliability of the information collected. 

Gerhart, Wright, McMahon, and Snell (2000) have found reliability to be a major concern for survey data 

when it is collected from a single respondent, as is the case for the WES. However, this single respondent 

issue may not pose as much of a concern for the WES as it does for some surveys. First, the format of the 

WES is designed to enhance reliability and validity of responses, by allowing for preparation by the 

respondent, while utilizing interviews for actual data collection, which enables clarification of both 

questions and answers. In so doing, trained Statistics Canada interviewers are used, who have no vested 

interest in the particular outcomes of studies based on the survey information. 

Second, Gerhart, Wright, McMahon and Snell (2000) note that establishment-level surveys are likely 

more reliable than corporate-level surveys, because the units of analysis are smaller, managers are more 

familiar with HR practices because they are responsible for implementing them, and HR practices are 

more homogenous, and Gerhart, Wright, and McMahon (2000) do indeed find higher generalizability 

coefficients at the plant than at the company level. Further research by Wright and his colleagues (Wright 

et al., 2001) concluded that single-respondent surveys should use a single business or single location as its 

unit of analysis, as is true for the WES. Compared to the mean size of the organizational unit used by 

other well-known HR studies, such as Huselid’s (1995) survey (4,413 employees), the WES use of a 

single location results in a much smaller mean size (about 40 employees). 

Conclusions and Implications 

The results of our research suggest that while, on average, profit sharing may be earnings-neutral for 

employees, profit sharing may not generally be financially desirable for employees, if it shifts business 

risk from the employer to the employee, with no additional compensation to the employee for undertaking 

this additional risk. Our results imply that, for most Canadian employers, employee profit sharing serves 

to substitute variable pay for fixed pay, with no significant change in either cash real earnings or total real 

104

earnings over time. But note that if this substitution of variable pay for fixed pay serves to enhance 

employment stability, as economic theory would predict (Weitzman and Kruse, 1990), a tradeoff of 

earnings stability for employment stability is one that many employees might find acceptable or even 

desirable. 

However, our results also show that the implications of profit sharing for employee earnings vary, 

depending on whether workers are employed in high-wage establishments. In high-wage establishments, 

employee profit sharing does apparently serve to increase earnings, perhaps suggesting that high-wage 

employers see profit sharing as a way of leveraging their high investments in human capital and 

enhancing employee earnings, while other employers see profit sharing as a way of substituting variable 

for fixed employee earnings and/or shifting business risk to employees. 

Employees should not count on their unions to prevent this latter outcome, as union density made no 

difference to the earnings outcomes flowing from adoption of employee profit sharing. Therefore, unless 

they represent employees at high-wage establishments, unions would probably best serve their members’ 

financial interests by avoiding profit sharing, something most North American unions already attempt to 

do. However, a second caveat to a policy of blanket opposition to profit sharing may be where unions can 

succeed in linking any loss in employee earnings stability to a gain in employment stability. Overall, what 

this suggests is that there may be circumstances under which unions find that profit sharing is beneficial 

to their members, and that a policy of blanket opposition to profit sharing may not always be in the best 

interests of their members. 

For employers, our results suggest that employee profit sharing is generally beneficial, if only 

because it serves to make employee compensation more responsive to the financial circumstances facing 

the firm, and because it serves to shift business risk to employees without adding to compensation costs. 

Of course, if employee profit sharing improves the productivity of the firm in some way, then the 

consequences are all the more beneficial to employers. Overall, our results imply either that profit sharing 

does not increase the overall financial performance of firms (and thus that there are no additional “rents” 

to share with workers) or that profit sharing does improve financial performance, but employees are not 

capturing any of this gain. This latter explanation is consistent with Kruse’s (1993) longitudinal results, 

which indicated that profit sharing had increased company productivity, but had not increased employee 

earnings. However, Kruse (1993) also observed wide variance across firms in the extent to which 

employee profit sharing brought productivity benefits, with about a third of profit sharing adopters 

showing no productivity gains at all. So it is possible that both explanations apply, but to different 

employers. 

The fact that we did find a set of employers (high-wage firms) whose employees do appear to benefit 

financially from adoption of profit sharing implies that profit sharing brings performance benefits to 

employers who invest relatively more than their competitors in human capital. Arguably, leveraging this 

investment through use of employee profit sharing serves to produce additional rents that can then be 

shared with employees. To the extent that this occurs, employee profit sharing will be beneficial to both 

employers and employees when adopted by high-wage firms. However, research specifically aimed at 

testing this proposition, which incorporates financial performance measures, is necessary before firm 

conclusions are drawn. 

105

References 

Allen, M.R., & Wright, P. (2007). Strategic management and HRM. In P. Boxall, J. Purcell & P Wright 

(Eds).The Oxford handbook of human resource management (pp. 88-107). Oxford: Oxford 

University Press. 

Bailey, T. (1993). Organizational innovation in the apparel industry. Industrial Relations, 32, 30-48. 

Bell, D.W., & Hanson, C.G. (1987). Profit Sharing and profitability: How profit sharing promotes 

business success. London: Kogan Page. 

Bell, L., & Neumark, D. (1993). Lump sum payments and profit sharing plans in the union sector of the 

United States economy. Economic Journal, 103, 602-619. 

Carstensen V., Gerlach, K. & Hubler, O. (1992). Determinants and microeconomic effects of profitsharing: 

Hypotheses and first results from German firms. Presented at the second meeting of the 

Impact of Profit Sharing in Europe (IPSE) Project, Paris. 

Cheadle, A. (1989). Explaining patterns of profit-sharing activity. Industrial Relations, 28(3), 387-400. 

Coates EM. (1991). Profit sharing today: Plans and provisions. Monthly Labor Review, 114(4), 19-25. 

Cooke, W.N. (1994). Employee participation programs, group-based incentives, and company 

performance: A union-nonunion comparison. Industrial and Labor Relations Review, 47(4), 594- 

609. 

Cooper, C., Dyck, B., & Frohlich, N. (1992). Improving the effectiveness of gainsharing: The role of 

fairness and participation. Administrative Science Quarterly, 37(3), 471-490. 

Delery, J.E. (1998). Issues of fit in strategic human resource management: Implications for research. 

Human Resource Management Review, 8(3), 289-309. 

Delery, J.E., & Doty, D.H. (1996). Modes of theorizing in strategic human resource management: Tests 

of universalistic, contingency, and configurational performance predictions. Academy of 


Drago R., & Heywood J.S. (1995). The choice of payment schemes: Australia establishment data. 

Industrial Relations, 34 (4), 507-531. 

Estrin S., & Wilson, N. (1989). Profit sharing, the marginal cost of labour and employment variability. 

University of Bradford, Management Centre. 

Fitzroy, F., & Kraft, K. (1986). Profitability and profit sharing. Journal of Industrial Economics, 35(2): 

113-130. 

Forth, John, and Neil Millward. (2004). High-involvement management and pay in Britain. Industrial 

Relations, 43(1), 98-119. 

Florkowski, G. (1991). Profit sharing and public policy: Insights for the United States. Industrial 

Relations, 30(1), 96-115. 

106

Gerhart, B., Wright, P.M., & McMahan, G.C. (2000). Measurement error in research on the human 

resources and firm performance relationship: Further evidence and analysis. Personnel 

Psychology, 53(4), 855-872. 

Gerhart, B., Wright, P.M., McMahan, G.C., & Snell, S.A. (2000). Measurement error in research on the 

human resources and firm performance relationship: How much error is there and how does it 

influence effect size estimates? Personnel Psychology, 53, 803-834. 

Gregg, P.A., & Machin, S.J. (1988). Unions and incidence of performance linked pay schemes in Britain. 

International Journal of Industrial Organization, 6(1), 91-107. 

Handel, Michael J., & Gittleman, Maury. (2004). Is There a Wage Payoff to Innovative Work Practices? 

Industrial Relations, 43(1), 67-97. 

Hart, R.A., & Hubler, O. (1991). Are profit shares and wages substitute or complementary forms of 

compensation? KYKLOS, 44(2), 221-231. 

Heywood, J.S., Hubler, O., & Jirjahn, U. (1998). Variable payment schemes and industrial relations: 

Evidence from Germany. KYKLOS, 51 (2), 237-257. 

Huselid, M.A. (1995). The impact of human resource management practices on turnover, productivity, 

and corporate financial performance. Academy of Management Journal, 38(3), 635-672. 

Ichniowski, C., Shaw, K., & Prennushi, G. (1997). The effects of human resource management on 

productivity. American Economic Review, 87, 291-310. 

Jensen, M., & Meckling, W. (1976). Theory of the firm: Managerial Behavior, agency costs, and 

ownership structure. Financial Economics, 3, 305-360. 

Jones, D.C., & Pliskin, J. (1997). Determinants of the incidence of group incentives: Evidence from 

Canada. Canadian Journal of Economics, 30(4B), 1027-1045. 

Kandel, E., & Lazear, E. (1992). Peer pressure and partnerships. Journal of Political Economy, 100, 801- 

817. 

Kato, T., & Morishima, M. (2003). The nature, scope and effects of profit sharing in Japan: Evidence 

from new survey data. International Journal of Human Resource Management, 14 (6), 942-955. 

Katz, H.C., & Meltz, N.M. (1991). Profit Sharing and auto workers earnings: The United States vs 

Canada. Relations industrielles/Industrial Relations, 46 (3), 515-530. 

Kim, S. (1998). Does profit sharing increase firm profits? Journal of Labor Research, 19(2), 351-370. 

Kruse, D.L. (1993). Profit sharing: Does it make a difference? Kalamazoo, MI: W.E. Upjohn Institute. 

Kruse, D.L. (1996). Why do firms adopt profit sharing and employee ownership plans? British Journal of 

Industrial Relations, 34, 515-538. 

Lawler, E.E. (1986). High-involvement management: Participative strategies for improving 

organizational effectiveness. San Francisco: Jossey-Bass. 

107

Lawler, E.E. (1992). The ultimate advantage: Creating the high-involvement organization. San Francisco: 

Jossey Bass. 

Lawler, E.E., Mohrman, S.A., & Ledford, G.E. (1998). Strategies for High Performance Organizations. 

San Francisco: Jossey Bass. 

Lazear, E.P. (2000). Performance pay and productivity. American Economic Review, 90, 1346-1361. 

Levine, D.I., & Tyson, L.D. (1990). Participation, productivity, and the firm’s environment. In A.S. 

Blinder (Ed.), Paying for productivity: A look at the evidence (pp. 15-94). Washington, DC: The 

Brookings Institution. 

Long, R.J. (1989). Patterns of workplace innovation in Canada. Relations industrielles/Industrial 

Relations, 44(4), 805-826. 

Long, R.J. (1992). The incidence and nature of employee profit sharing and stock ownership in Canada. 

Relations industrielles/Industrial Relations, 47(3), 463-488. 

Long, R.J. (1994). Gain sharing, hierarchy, and managers: Are they substitutes? Proceedings of the 1994 

Annual Conference, Administrative Sciences Association of Canada, 15(12):51-60. 

Long, R.J. (1997). Motives for profit sharing: A study of Canadian chief executive officers. Relations 

industrielles/Industrial Relations, 52(4), 712-733. 

Long, R.J. (2000). Employee profit sharing: Consequences and moderators. Relations 

industrielles/Industrial Relations, 55(3), 477-504. 

Long, R.J. (2002). Performance pay in Canada. In M. Brown & J.S. Heywood (Eds.), Paying for 

Performance: An International Comparison (pp. 52-89). Armonk, NY: M.E. Sharpe. 

Long, R.J. (2006). Strategic compensation in Canada. Toronto: Thomson Nelson. 

Long, R.J., & Shields, J.L. (2005). Performance pay in Canadian and Australian firms: A comparative 

study. International Journal of Human Resource Management, 16(10), 1783-1811. 

Long, R.J., & Fang, T. (2007). How strategic is strategic pay? The case of employee profit sharing. 

Proceedings of the Administrative Sciences Association of Canada Annual Conference, Ottawa. 

MacDuffie J.P. (1995). Human-resource bundles and manufacturing performance: Organizational logic 

and flexible production systems in the world auto industry. Industrial and Labor Relations 

Review, 48(2), 197-221. 

Magnan, Michel, & St-Onge, Sylvie. (2005). The impact of profit sharing on the performance of financial 

services firms. Journal of Management Studies, 42(4), 761-791. 

McNab, Robert, & Whitfield, Keith. (2007). The impact of varying types of performance-related pay and 

employee participation on earnings. International Journal of Human Resource Management, 

18(6), 1004-1025. 

Mitchell, D.J.B., Lewin, D., & Lawler, E.E. (1990). Alternative pay systems, firm performance, and 

productivity. In A.S. Blinder (Ed.), Paying for productivity: A look at the evidence (pp. 15-94). 

108

Washington, DC: The Brookings Institution. 

Mitchell, Daniel J.B., & Broderick, Renae F. (1991). Flexible systems in the American context: History, 

policy, research, and implications.” In D. Lewin, D. Lipski, & D. Sockell (Eds.) Advances in 

Industrial and Labor Relations, Greenwich, CT: JAI Press. 

Ng I., & Maki D. (1994). Trade-union influence on human resource management practices. Industrial 

Relations, 33(1), 121-135. 

Olson, M. (1971). The logic of collective action. Cambridge: Harvard University Press. 

Osterman, Paul. (2000). Work reorganization in an era of restructuring: Trends in diffusion and effects on 

employee welfare. Industrial and Labor Relations Review, 53, 179-196. 

Parent, M. (2002). Performance pay in the United States: Its determinants and effects. In M. Brown & J.S. 

Heywood (Eds.), Paying for Performance: An International Comparison (pp. 17-51). Armonk, 

NY: M.E. Sharpe. 

Pil, F.K., & MacDuffie, J.P. (1996). The adoption of high-involvement work practices. Industrial 

Relations, 35(3), 423-455. 

Poole, M. (1989). The origins of economic democracy: profit-sharing and employee-shareholding 

Schemes. London: Routledge. 

Poole, M. & Jenkins, G. (1990). The impact of economic democracy: profit sharing and employee 

shareholding schemes. London: Routledge. 

Poole, Michael, & Jenkins, G. (1998). Human resource management and the theory of rewards: Evidence 

from a national survey. British Journal of Industrial Relations, 36(2), 227-247. 

Statistics Canada. 2004. Workplace and Employee Survey compendium: 2001. Ottawa: Statistics Canada. 

Statistics Canada. 2006. Guide to the analysis of the Workplace and Employee Survey: 2003. Ottawa: 

Statistics Canada. 

Strauss, G. (1990). Participatory and gain sharing systems: History and hope. In M.J. Roomkin (Ed.) 

Profit sharing and gain sharing (pp. 1-45). Metuchen, NJ: Scarecrow Press. 

Tyson, D.E. (1996). Profit sharing in Canada. Toronto: John Wiley and Sons. 

US Chamber of Commerce. (1989). Employee Benefits. Washington, DC: Economic Policy Division, 

Chamber of Commerce of the United States. 

Wagar, T.H., & Long, R.J. (1995). Profit sharing in Canada: Incidence and predictors. Proceedings of the 

Administrative Sciences Association of Canada (Human Resources Division), 16:97-105. 

Walsworth, S., & Verma, A. (2007). Globalization, human resource practices and innovation: Recent 

evidence from the Canadian workplace and employee survey. Industrial Relations, 46(2), 222- 

240. 

Wahdwani, S., & Wall, M. (1990). The effects of profit sharing on employment, wages, stock returns, and 

109

productivity: Evidence from UK microdata. Economic Journal, 100, 1-17. 

Weitzman, M.L. (1984). The Share Economy. Cambridge, MA: Harvard University Press. 

Weitzman, M.L., & Kruse, D.L. 1990. Profit sharing and productivity. In A.S. Blinder (Ed.), Paying for 

productivity: A look at the evidence (pp. 95-142). Washington, D.C.: The Brookings Institution. 

Wright, P.M., Gardner, T.M., Moynihan, L.M., Park, H.J., Gerhart, B., & Delery, J.E. (2001). 

Measurement error in research on human resources and firm performance: Additional data and 

suggestions for future research. Personnel Psychology, 54(4), 875-901. 

Zatzick, C.D., & Iverson, R.D. ( 2006). High involvement management and workforce reduction: 

Competitive advantage or disadvantage? Academy of Management Journal, 49(5), 999-1015. 

Zylberstajn, H. (2002). The Brazilian case: Performance pay as workers’ right. In M. Brown and J.S. 

Heywood (Eds.), Paying for Performance: An International Comparison (pp. 236-260). Armonk, 

NY: M. E. Sharpe. 

110



EXPLAINING CHRONOLOGICAL AND SUBJECTIVE AGE 

DIFFERENCES IN JOB SATISFACTION 

Results of a survey of 282 middle managers provide a partial explanation 

for the age-job satisfaction relationship. Subjective age was a stronger 

predictor of job satisfaction. Recognizing, or having others recognize 

one’s work experience partially mediated the relationship between 

chronological age and subjective age, and job satisfaction (global and 

facet). 

Age and Job satisfaction 

Nicole Bérubé (Student) 

John Molson School of Business 

Concordia University 

Understanding the relationship between age and work attitudes is widely recognized as crucial for 

organizational success (Glass, 2007; Greller & Stroh, 1995; Kanfer & Ackerman, 2004). Our need for this 

information is emphasized by recent demographic trends. Workers over 40 years of age currently 

dominate the North American workforce (Bureau of Labor Statistics, 2002; Fullerton, 1999) and labor 

force participation among workers over 50 is reported to be up 32% from the previous decade (Conlin, 

2003). Although it is widely recognized that aging workers are valuable human capital (Fullerton, 1999), 

concerns about how to manage aging workers are widespread (Cloutier, Lefebvre, Ledoux, Chatigny, & 

St-Jacques, 2002; Crampton, Hodge, & Mishra, 1996; Critchley, 2004; DeLong, 2004). Starting from the 

premise that age provides temporal and social benchmarks for self-assessment (Lawrence, 1987, 1988), 

empirical studies have demonstrated that age measures account for significant variance in important work 

outcomes such as job satisfaction and organizational commitment (Cleveland & Shore, 1992). Generally, 

past studies of the relationship between age and job satisfaction report that older workers are more 

satisfied with their jobs than are younger workers (e.g., Kalleberg & Loscocco, 1983; Rhodes, 1983; 

Wright & Hamilton, 1978). However, work attitudes evolve over time and current workplace 

demographics call for more research to update and increase our knowledge about the relationship between 

age and important work attitudes. 

Job satisfaction is one of the most frequently researched concepts in management research because it 

predicts many important individual work outcomes such as absenteeism, turnover, and counterproductive 

behaviors (Dormann & Zapf, 2001). Within the substantial body of research on job satisfaction, studies 

have directly investigated explanations for the relationship between age and job satisfaction have found 

that salary, tenure, and organizational level (e.g., White & Spector, 1987) are mediators of the 

relationship with job satisfaction. However, these studies investigated only the effect of chronological age 

on global job satisfaction, and did not consider perceptual age (the age a person feels), or job satisfaction 

facets. More importantly, the bulk of studies on the relationship between age and job satisfaction dates 

back at least two decades and may no longer reflect the situation in more modern workplaces. For 

example, in today’s rapidly changing organizational context, one’s salary, tenure or organizational level 

cannot be assumed to be linearly related to age. Younger employees could be better educated than older 

ones, and thus have access to higher-level positions and higher salaries in the organization. Organizational 

111

changes leading to downsizing and attrition may have affected older employees. By finding new 

employment in other organizations, they may have less tenure than younger employees already 

established in the organization. It is therefore necessary to update our knowledge about job satisfaction as 

it relates to age in modern workplaces. This investigation must consider how age is defined in current 

work contexts. 

In management research, age is most often measured chronologically (Rhodes, 1983) and most 

organizational commitment studies have followed this norm. However, chronological age alone may not 

adequately reflect age-related attitudes. For example, individuals of identical chronological age may 

attach different subjective meanings to their age (Cleveland, Shore, & Murphy, 1997). Cleveland and 

Shore (1992) define two types of perceptual age – subjective age is a personal evaluation of how old or 

young individuals perceive themselves to be on the basis of shared characteristics with others, and 

perceived relative age is a self-evaluation that individuals have about their own age, based on general 

social comparisons with members of a referent group, such as co-workers. In this study, we will focus on 

subjective age. Cleveland and Shore (1992) found that perceptual age measures could account for 

additional variance in individual outcomes not accounted for by chronological age. For example, they 

found that among individuals who were relatively older than their coworkers, those who perceived 

themselves as subjectively older were more satisfied than individuals who perceived themselves as 

subjectively younger. Subsequently, Cleveland et al. (1997) developed perceptual age scales and reported 

that perceptual age accounted for variance in perceived organizational support that was not accounted for 

by chronological age. Bobko and Barispolets (2002) utilized a similar measure of subjective age and 

found that the relationship of this variable with job performance and job stress was significantly different 

from the relationships between chronological age, performance and stress. Although job satisfaction was 

not a focal outcome in either of these studies, the results of these studies suggest that studying subjective 

age might add to our understanding of the age-job satisfaction link. 

Why focus more on subjective age? As the Baby Boom cohort ages, new interpretations arise about 

age and aging. For example, the popular press abounds with advertisement slogans and headlines touting 

that “50 is the new 40” and “70 is the new 60” (i.e., Lindgren, 2007). These social signals may influence 

the way people subjectively perceive their age. Furthermore, the elimination of mandatory retirement age, 

the increase in the age for pension eligibility, the increase in shorter organizational tenure due to 

organizational reorganization and downsizing, as well as the increase in protean career patterns are all 

expected to contribute to continued increases in the proportion of older workers in the next few decades. 

The age norms relevant to work and career are likely to change with the increase in the proportion of 

older workers in the workforce, as it becomes increasingly acceptable to work, and even to establish new 

careers at an older age. In light of these trends, subjective age is becoming an increasingly important 

construct for studies that investigate relationships between age and work outcomes. However, it has more 

often been the object of studies in the field of gerontology and has received relatively little attention in the 

management literature to date. It is time to update and refine what we know about the age-job satisfaction 

relationship, and to investigate specifically and more thoroughly, the role of subjective age in work 

attitudes. 

Scholars have observed that older people tend to perceive themselves as subjectively younger than 

their chronological age (Rubin & Berntsen, 2006; Uotinen, Rantanen, Suutama, & Ruoppila, 2006), while 

younger people may tend to perceive themselves as subjectively older (Barnes-Farrell & Piotrowski, 

1989; Montepare & Lachman, 1989). This phenomenon could be the result of transitional phases in adult 

development that incite questioning and reformulation of aspirations (Peterson, 1996). The common 

saying that people are only as old as they feel can be informed by investigating subjective age. This 

construct offers individuals a way to adjust their age to suit the way they feel, or to subjectively accelerate 

or slow down the process of aging to suit their needs. For example, older employees may report being 

subjectively younger than their chronological age in order to preserve their self-perception of their 

112

development potential at work. Younger workers who are building their career may be focused on 

objectives that more experienced colleagues have achieved and seeing themselves as subjectively older 

may be a way to make these goals seem more readily accessible. 

Levy (2003) discussed that age self-stereotypes are readily internalized and reinforced through 

various cognitive processes. These self-stereotypes would most likely be strengthened by commonly held 

age stereotypes in the workplace, and together these would constitute an efficient way to evaluate one’s 

subjective age. The literature on age stereotypes at work has documented that older workers are generally 

perceived to be more knowledgeable and experienced. For example, Forte and Hansvick (1999) found 

evidence of job specific stereotyping against younger workers for jobs requiring supervisory abilities. 

These qualities are generally relevant for managerial positions and may be associated with appreciation 

and respect from others. Therefore, younger managers may subjectively rate themselves as older to 

attribute to themselves the positive biases of knowledge and experience that are generally attributed to 

older managers. 

Similarly, older individuals may attempt to capture the advantages of performance biases that favour 

younger managers, who are often perceived to be more adaptable and faster learners (Hassell & Perrewe, 

1995). By thinking in terms of both chronological and subjective age, individuals can enjoy both the 

advantages of positive biases relative to their chronological age while concurrently benefiting from the 

positive biases related to their subjective age. By reducing the negative work-related effects associated 

with advancing chronological age, subjective age may thus contribute to increasing job satisfaction, as 

employees get chronologically older. Given the advantage of greater work experience, older managers are 

more likely to be able to draw from knowledge that facilitates their work. Consequently, they are 

expected to be more satisfied with their jobs than younger managers who are more likely to be at a lower 

point on the job experience learning curve. 

An abundant body of literature confirms a positive relationship between chronological age and overall 

job satisfaction (e.g., Brush, Moch, & Pooyan, 1987; e.g., Dormann & Zapf, 2001; Rhodes, 1983). In 

addition, empirical evidence strongly supports the existence of a positive association between age and 

satisfaction with the work itself, or work on present job (Rhodes, 1983). Scholars have offered various 

explanations for the age-job satisfaction relationship. One common explanation for this relationship is 

based on the job change hypothesis, which maintains that compared to younger workers, older workers 

are more satisfied with their jobs because they have access to more desirable jobs, and because their needs 

and values have evolved over time to become more congruent with the jobs they occupy (Wright & 

Hamilton, 1978). Presumably, more desirable jobs have more satisfying job content and chronologically 

older persons should thus enjoy more satisfying jobs. 

We now turn to the relationship between subjective age and job satisfaction. Several studies report 

that people who felt subjectively older were more fatigued and felt less capable of working (Iskra-Golec, 

2002), had greater job and off-job stress (Barnes-Farrell, Rumery, & Swody, 2002), and had lower 

general work ability. Such factors are likely to reduce the amount of pleasure one derives from 

accomplishing one’s work. Based on the foregoing, we propose the following hypotheses. 

Hypothesis 1: Chronological age will be positively related to overall job satisfaction and to satisfaction 

with work on present job. 

Hypothesis 2: Subjective age will be negatively related to overall job satisfaction and to satisfaction with 

work on present job 

Cleveland and Shore (1997) and Bobko and Barispolets (2002) reported evidence that subjective age 

could account for additional variance in individual work outcomes beyond that of chronological age. 

113

Since subjective age is within the individual’s control, it is more likely to reflect one’s age identity at 

work and age-related work values than chronological age. Feeling subjectively older involves more than 

acknowledging a number that reflects the passage of time. It involves an assessment of the way one feels, 

looks, one’s interests and one’s ideal age. As such, it is a better reflection of a person’s age self-concept. 

Therefore, it should be a better predictor of job satisfaction than chronological age. Based on these 

arguments, we propose the following hypothesis. 

Hypothesis 3: Subjective age will be a stronger predictor than chronological age of overall job 

satisfaction and satisfaction with work on present job. 

In line with the job change hypothesis (Wright & Hamilton, 1978), workers should, over time, 

develop expertise that facilitates their work in some manner. Even if they occupy different jobs, they 

bring to their job previous experience and their knowledge of working provides them with tools to cope 

with the everyday challenges of work. Older workers also tend to be perceived by others as having a great 

deal of work experience, even if they may actually have less than younger workers (Forte & Hansvick, 

1999; Gibson & Klein, 1970). We propose that recognizing one’s work experience and realizing that 

others recognize it might explain the link between age and job satisfaction. 

Traditional management thinking about age at work is rooted in life and career development models 

(Levinson, Darrow, Klein, Levinson, & McKee, 1978; Super, 1957). These models argue fundamentally 

that different experiences define life and career stages. Aging increases the probability that one will 

encounter situations that provide opportunities to recognize one’s own work experience and have it be 

recognized by others. These might include encountering a work situation where past experience comes in 

handy, being told by someone at work that one’s experience is valued, or being perceived as having a 

certain level of expertise in one’s field of work. Since various work experience is likely to increase with 

age, older employees should be more likely than younger employees to be aware of circumstances where 

their work experience is appreciated or assessed in some way. Therefore, older employees should be 

more likely to entertain expectations about their work experience being valued by others and experiencing 

situations where they could appreciate their own work experience first hand. 

Evaluating experience might apply in the arena of perceptual age as well as chronological age. For 

example, individuals who are chronologically 50 years old, but who subjectively assess the way they 

look, feel and act as older, should be more likely to value already acquired experience and expect others 

to recognize and appreciate it. Therefore, they are likely to be more sensitive to signals in their 

environment that emphasize their acquired experience. In contrast, 50 year-olds who are subjectively 

younger in appearance, deportment and interests, are more likely to want to maintain their youthful selfimage 

and social connections. They would thus be expected to be less sensitive to recognition of their 

acquired experience, but may instead be more focused on learning new things. This discussion leads to 

the following hypothesis: 

Hypothesis 4: Chronological and subjective age will be positively related to occurrences of recognition of 

one’s work experience. 

Job satisfaction denotes a personal evaluation about the content and context of one’s job. Over the 

span of a person’s career, work and performance become important sources of relational and ego needs. 

As individuals acquire relevant work experience, having this experience recognized by others or 

recognizing it themselves, could engage the process of job satisfaction. Self-recognitions could be 

generated by successfully handling a challenging work situation, or by recognizing that one’s expertise 

has facilitated tasks. The level of enjoyment in the job should thus increase. Aside from the intrinsic 

satisfaction individuals get from accomplishing jobs they enjoy, people identify with their jobs for various 

reasons, including satisfying their sense of self-worth (Lemme, 1999), accessing socially satisfying 

114

elationships (Nuttman-Schwartz, 2004; Williams Walsh, 2001) and maintaining a recognized sense of 

place, usefulness and purpose in society (Shaw & Grubbs, 1981). Receiving validation from others of 

one’s experience is a strong social signal that validates one’s worthiness at work, a source of job 

satisfaction. Based on the foregoing, we hypothesize that: 

Hypothesis 5: Recognitions about work experience will be positively related to job satisfaction. 

The foregoing discussion leads us to the final goal of the research – to examine the various impacts of 

chronological and subjective age on global job satisfaction and satisfaction with work on present job, 

through the mediating influence of receiving recognition from others about one’s work experience, and 

recognizing one’s own work experience. Based on the discussion leading to the previous two hypotheses, 

we propose that: 

Hypothesis 6: Assessments about work experience will partially mediate the relationship between age and 

job satisfaction. 

Participants 

Method 

Data collection was conducted using an online questionnaire, administered to a sample of 588 

Canadian middle managers in a large multinational firm in the services industry. A total of 282 

respondents completed the questionnaire (response rate: 48%). Respondents ranged in age from 21 to 64 

years (mean = 41.97). Their average organization tenure was 9.46 years and their average position tenure 

was 4.70 years. Both genders were adequately represented in this sample (56.7% women). 

Measures 

Subjective age was measured using the Subjective Age Scale, a four-item measure developed by 

Cleveland and Shore (1997) and tested longitudinally, with good reliability (α = 0.88 and 0.93). Items 

asked respondents to describe the age group that corresponded to the following: 1) The way you generally 

feel; 2) The way you look or your appearance; 3) The age of people whose interests and activities are 

most like yours; 4) The age that you would most like to be if you could choose your age right now. In our 

study, respondents chose one of six options (16-25 years, 26-35 years, 36-45 years, 46- 55 years, 56-65 

years, and 66-75 years), coded 1 (16-25 years) to 6 (66-75 years). In the present study the Cronbach’s 

alpha internal consistency reliability was .884. 

Overall job satisfaction was measured using five items from the Brayfield and Rothe scale (Brayfield 

& Rothe, 1951). This shortened version has been used in other research projects exhibiting acceptable 

reliabilities between .82 and .86 (e.g., Bono & Judge, 2003; Judge, Bono, & Locke, 2000) . Sample items 

are: “Most days I am enthusiastic about my work,” and “I feel fairly satisfied with my present job.” 

Responses were made on seven-point disagree-agree scales, and composite scores were computed by 

averaging across items. The alpha reliability for this study was .835. 

Two facets of the Job Descriptive Index (Smith, Kendall, & Hulin, 1969) were measured: Satisfaction 

with work on present job and Satisfaction with promotion opportunities. Indices for each facet are based 

on three types of responses (“yes,” “no,” and “uncertain?”). This instrument is widely used, reliable 

(internal consistency coefficients between .80 and .88) and well validated (Spector, 1997). In the present 

study, Alpha reliabilities were .902 (Satisfaction with work on present job) and .835 (Satisfaction with 

promotion opportunities). The present paper utilises, only Satisfaction with work on present job. 

115

To explore individuals’ age-relevant experiences, we generated a list of 49 age-related events based 

on themes that emerged from a review of the literature on age and work attitudes. Several of these events 

were inspired or adapted from the Life Events Inventory (Holmes & Rahe, 1967) because of their 

relevance to age-related work attitudes (Hughes, Blazer, & George, 1988). The list of events was pretested, 

and subsequently, two raters independently coded the events according to themes, yielding several 

categories of events (inter-rater reliability = 97.9%). The questionnaire included six events that pertained 

to recognition of one’s work experience. Three of these signalled recognition of one’s experience by 

others: “A less experienced colleague came to me for advice,” “Someone appreciated my work 

experience,” and “Someone mentioned that I had substantial work experience in my field.” The other 

three represented self-recognition of one’s work experience: “My work required me to rely on knowledge 

that less experienced people do not have,” “I showed a less experienced colleague a “trick of the trade”,” 

and “I was able to work at my own pace or in my own way because of my experience.” Experience of 

age-relevant events was inventoried by asking respondents to report how often they experienced given 

events of occurrence during the past year (none = 0, once = 1, more than once = 2). Occurrences were 

summed to create an index for each type of recognition. Demographic data on chronological age, gender, 

years to retirement, and tenure were also measured on the questionnaire. 

Results 

Means, standard deviations and intercorrelations for the predictor and criterion variables are reported 

in Table 1. Chronological age and subjective age were positively correlated, which indicates that 

respondents identified subjectively with their chronological age group. 

Table 1 

Means, standard deviations and intercorrelations among variables 

1.Chronological age 282 41.97 8.99 1 

N M SD 1 2 3 4 5 6 

2. Subjective age 282 2.73 0.73 .761** 1 

3. Overall Job Satisfaction 282 5.46 1.17 .170** .230** 1 

4. Satisfaction with work 

on present job 

5. Experience recognized 

by self 

6. Experience recognized 

by others 

** p < .01 

* p < .05 

‡ 

p = .058 

282 42.02 12.44 .194** .212** .615** 1 

281 4.11 1.72 .135* .113 ‡ .180** .307** 1 

282 3.25 1.53 .191** .165** .228** .367** .313** 1 

116

We found significant, positive, zero-order correlations between chronological age and overall job 

satisfaction (β = .170; p< .001), as well as between chronological age and satisfaction with work on 

present job (β = .194; p < .001). Thus our first hypothesis was fully supported. Contrary to our second 

hypothesis, which predicted a negative relationship between subjective age and job satisfaction, we found 

significant, positive relationships between subjective age and overall job satisfaction (β = .230; p < .001), 

as well as between subjective age and satisfaction with work on present job (β = .212; p < .001). 

Hypothesis 3 predicted that subjective age would be a stronger predictor than chronological age of 

overall job satisfaction and satisfaction with work on present job. Table 1 shows that zero-order 

correlations for the relationship between subjective age and the two measures of job satisfaction were 

consistently stronger for subjective age, supporting H3. Additionally, Table 2 shows that when job 

satisfaction was regressed onto predictor variables in a multiple regression analysis, three variables 

contributed significantly to this regression: subjective age and the two types of work experience 

assessments. Job tenure and organizational tenure were used as control variables in these analyses. 

Table 2 

Multiple Regressions for Job Satisfaction and Satisfaction with Work on Present Job on Predictors 

Overall Job Satisfaction Satisfaction w/ Work on Present Job 

Beta 

t Beta 

t 

Chronological Age -.042 -.440 .043 .487 

Subjective age .205 2.324* .132 1.599† 

Org tenure -.026 -.340 .047 .647 

Job tenure .066 .928 -.135 -2.034* 

Experience recognized by self .119 1.963* .200 3.519** 

Experience recognized by others .189 3.031* .268 4.583** 

† p

Table 3 

Hierarchical Regressions for Overall Job Satisfaction on Predictors 

Variable entered 

R 2 

∆ R 2 

t to enter 

Experience recognized by self .032 .032 1.806† 

Experience recognized by others .065 .033 2.728* 

Chronological age .079 .014 -0.563 

Subjective age 

† p < .10 

* p < .05 

** p < .001 

.101 .022 2.596* 

The hierarchical regression procedure was repeated using satisfaction with work on present job as the 

criterion. When the explanatory variables were analyzed in hierarchical fashion with subjective age 

entered last, the model explained 20.7% of the variance in satisfaction with work on present job. 

Partialling other explanatory variables out of the chronological age-job satisfaction relationship reduced 

this correlation from .158 (p < .05) to .040 and it was no longer significant. Collinearity tolerance 

statistics were all over 0.87 except for the last variables entered in the equation. Collinearity tolerance 

statistics were lower for chronological age when it was entered last (Tolerance = .385) than for subjective 

age was it was entered last (Tolerance = .420). Overall, these results suggest that in this study, subjective 

age was a stronger predictor of job satisfaction than chronological age. 

Table 4 

Hierarchical Regressions for Satisfaction with Work on Present Job on Predictors 

Variable entered 

R 2 

∆ R 2 

t to enter 

Job tenure .001 .001 -1.971* 

Experience recognized by self .096 .095 3.563** 

Experience recognized by others .179 .082 4.820** 

Subjective age .205 .026 1.599† 

Chronological age 

† p < .10 

* p < .05 

** p < .001 

.207 .001 .662 

As hypothesized, chronological age was positively related to recognitions by self (β = .135, p < .05) 

and others (β = .191, p < .001) about one’s work experience. Furthermore, subjective age was positively 

related to recognitions by self (β = .113, p = .058) and others (β = .165, p < .05) about one’s work 

experience. Hypothesis 4 is thus fully supported. As hypothesized, self-recognition of work experience 

was positively related to overall job satisfaction (β = .180, p < .001) and to satisfaction with work on 

present job (β = .307, p < .001). Furthermore, recognition of one’s work experience by others was a 

118

significant, positive correlate of both overall job satisfaction (β = .228, p < .001) and satisfaction with 

work on present job (β = .367, p < .001). Hypothesis 5 is thus fully supported. 

In the next stage of the analysis, we examined whether the two types of assessments of one’s work 

experience mediated the link between age and job satisfaction. For these analyses, we followed the 

procedures described by Baron and Kenny (1986) and Sobel (1982). Because the mediation analysis was 

exploratory, we used the p < .10 levels for marginal significance to enable us to identify marginally 

significant relationships that we could follow up with a larger sample in future research. 

The analysis began by examining the relationship between chronological age and overall job 

satisfaction. In a regression analysis, chronological age was regressed on overall job satisfaction and 

found to be a significant predictor (β = .170, p < .001). At step 2, the “self-recognition of experience” 

index was introduced. The beta weight for chronological age associated with job satisfaction decreased 

but remained significant (β = .160, p = .007). These results suggest weak, partial mediation, which was 

confirmed by a Sobel test of mediation (Sobel’s z = 1.778, p = .075). We repeated this analysis using the 

“recognition of one’s experience by” index at step 2. The beta weight for age associated with job 

satisfaction decreased but remained significant (β = .132, p = .026). These results suggest weak, partial 

mediation, which was confirmed by a Sobel test of mediation (Sobel’s z = 2.375, p = .017). 

Next, subjective age was regressed on overall job satisfaction (β = .230; p< .001) and the “selfrecognition 

of experience” index was introduced at step 2. The beta weight for subjective age associated 

with overall job satisfaction decreased but remained significant (β = .211, p = .058). These results suggest 

weak, partial mediation, but the Sobel test of mediation was nonsignificant (Sobel’s z = 1.56, p = .12). We 

repeated this analysis using the “recognition of one’s experience by others” index at step 2. The beta 

weight for age associated with job satisfaction decreased but remained significant (β = .198, p = .001). 

These results suggest weak, partial mediation. This was confirmed by a Sobel test of mediation (Sobel’s z 

= 2.15, p = .031). 

Following this, chronological age was regressed on satisfaction with work on present job and found to 

be a significant predictor (β = .194, p < .001). At step 2, the “self-assessment of experience” index was 

introduced. The beta weight for chronological age associated with satisfaction with work on present job 

decreased but remained significant (β = .156, p = .007). These results suggest weak, partial mediation, 

which was confirmed by a Sobel test of mediation (Sobel’s z = 2.138, p = .03). We repeated this analysis 

using the “recognition of one’s experience by others” index at step 2. The beta weight for age associated 

with satisfaction with work on present job decreased but remained significant (β = .129, p = .023). These 

results suggest weak, partial mediation, which was confirmed by a Sobel test of mediation (Sobel’s z = 

2.904, p = .003). 

Finally, subjective age was regressed on satisfaction with work on present job and found to be a 

significant predictor (β = .212, p < .001). At step 2, the “self-recognition of experience” index was 

introduced. The beta weight for subjective age associated with satisfaction with work on present job 

decreased but remained significant (β = .211, p = .058). These results suggest weak, partial mediation, 

which was confirmed by a Sobel test of mediation (Sobel’s z = 1.790, p = 0.073). We repeated this 

analysis using the “recognition of one’s experience by others” index at step 2. The beta weight for age 

associated with satisfaction with work on present job decreased but remained significant (β = .156, p = 

.006). These results suggest weak, partial mediation. This was confirmed by a Sobel test of mediation 

(Sobel’s z = 2.15, p = .031). 

These results indicate that we obtained support for seven out of eight partial mediations. Therefore, 

our sixth hypothesis was partially supported. Generally, we concluded that there was weak but relatively 

consistent evidence that self-recognition about one’s work experience, as defined by the sum of the 

119

occurrences of three types of self-recognitions, and recognitions from others about one’s work 

experience, as defined by the sum of the occurrence of three types of recognitions by others, partially 

mediated the relationship between age and job satisfaction. 

Discussion 

Findings from this study show that the subjective evaluation individuals make about their age is an 

important factor in reporting occurrences of recognition of their work experience, by themselves or 

others. In this sample, respondents generally identified subjectively with their chronological age group. 

However, this general outcome may not hold across age groups or generational cohorts. Group 

differences were not included here due to length limitations. However, our finding of a general coherence 

between chronological and subjective age is nevertheless interesting since it suggests that by focusing on 

differences between groups, managers may lose sight of the notion that these differences may not 

generally matter as much as they are often assumed to matter. 

Findings also indicate that subjective age is more strongly related to both overall job satisfaction and 

satisfaction with work on present job. This indicates that much of the discourse about age in the 

workplace, which relies heavily on chronological age, may overlook issues that are important for 

managing key work outcomes. This perspective has important implications for human resource questions 

about staffing, recruitment, and retirement preparation – questions that become increasingly important as 

the Canadian workforce ages. 

The opposite direction we obtained for the relationship between subjective age and job satisfaction 

may be related to context. Our sample consisted of middle managers in the service industry. The samples 

used in previous studies (Barnes-Farrell et al., 2002; Iskra-Golec, 2002) consisted of people employed in 

a broader range of jobs in the health care sector. This suggests that differences in jobs and organizational 

sectors may influence assessments of subjective age. For example, health care workers occupy jobs that 

are generally more physically demanding than those occupied by managers. Furthermore, work in the 

health care sector may offer a more limited range of opportunities for doing tasks that people prefer more 

than others. To protect patients, health care must be delivered according to strict processes. By 

comparison, managers in the service industry have less physically demanding work and would be likely to 

be able to work more creatively, and on a much broader range of tasks. Overall, they are more likely to be 

able to work on tasks they prefer within the scope of their jobs. It is also possible that the more physical 

nature of the job of health care workers would also emphasize the negative consequences of feeling 

subjectively older (e.g., fatigue, reduced stamina). By comparison, managers in the service industry might 

not be as likely to feel the negative effects of feeling subjectively older. Furthermore, because of the great 

reliance on tacit knowledge in managerial jobs, they may be more likely to benefit from the stereotypes 

that favour older people with having more wisdom. Therefore, subjectively older managers would be 

more likely to be satisfied with their job and their job content than subjectively older health care workers. 

Our findings that older individuals are more likely than younger individuals to encounter occurrences 

of recognition by others emphasizes the importance of recognizing and valuing work experience, 

especially for older workers, who may be more sensitive to this form of appreciation. In a context where 

human resource practitioners are becoming concerned with issues of staffing and transfer of knowledge as 

Baby Boomers approach retirement, it will be important to find concrete ways to recognize and validate 

the knowledge and work experience acquired by older employees over the course of their lives. It is 

unlikely that unhappy workers will want to help their employers by training and mentoring their 

replacements. Valuing past work experience is not only likely to lead to more satisfied workers, but it 

could also help stimulate the sharing of tacit knowledge within organizations. 

120

More generally, the positive link we found between recognition of experience and job satisfaction 

suggests that organizations need to be more sensitive to the role that specific types of recognition play 

with regards to the association between age and job satisfaction. For example, it is reasonable that 

individuals begin to adjust their performance levels if they start to perceive that the association between 

organizational rewards and their performance is weakening. If recognition of experience suggests a 

stronger association, or signals that employees are more appreciated over time, it is not surprising that job 

satisfaction increases. These relationships can be further clarified with future research that focuses on the 

contextual and interpretive aspects of recognition of work experience. 

It has also been suggested that older employees may have cognitively rationalized lower expectations 

from their jobs, which may explain why they are more satisfied than younger workers (Kline, Sulsky, & 

Rever-Moriyama, 2000). Our findings suggest an alternative or complementary view – that employees 

seek out sources of satisfaction. This is an interesting perspective since recognizing experience is quite 

manageable. Often we think of communicating this type of recognition through praise or rewards. 

However, there are alternative recognition strategies that could work equally well or better, such as 

providing opportunities for older workers to show others what they know, and seeking out older workers 

for job challenges that require tacit knowledge. 

What might help us understand the age-satisfaction dynamics more clearly? We have shown that 

using subjective age constitutes a valuable key to this understanding. Accordingly, we recommend more 

thorough investigations of the age-commitment relationship, using perceptual age measures. For example, 

Cleveland and Shore (1992) found that individuals who perceived themselves as subjectively older and 

who reported perceiving themselves as subjectively older and relatively older than the members of their 

work group had the most positive work attitudes. This suggests that congruence between types of 

perceptual age is useful in explaining variance in the relationship between age and work attitudes. Due to 

space limitations, we focused only on subjective age as a perceptual age measure in this paper. However, 

future research should investigate the effects of both subjective age and perceived relative age (one’s age 

compared to the average age of members of one’s work group) on various forms of job satisfaction and 

other work attitudes. 

Although our findings are instructive, they must be considered in light of the limitations of this study. 

The sample consisted only of managers in a single industry, which raises concerns about the 

generalizability of the findings. Finally, this study is cross-sectional and therefore, no inferences can be 

made about causality. Furthermore, common method variance is always a concern with self-reports and 

with cross-sectional data analysis. Collecting longitudinal data on this sample in the future could help 

alleviate concerns with regards to common method variance. Although gender was measured in our 

survey, an analysis including gender extends beyond the scope of this paper. However, we plan to detail 

our findings regarding the effect of gender on the age-commitment relationship in future papers. In 

addition, our paper focuses on older workers, although the data collected is relevant to workers of various 

ages. A more thorough investigation of the results across ages is also planned in the future. 

This study extended research on the relationship between age and job satisfaction by investigating the 

influence of both chronological and subjective age on overall job satisfaction and satisfaction with work 

on present job. In light of the need for knowledge about managing an aging workforce, still relatively few 

studies have investigated the role of perceptual age measures on work attitudes and no studies on 

perceptual age have attempted to test possible explanations for the age-satisfaction relationship. Our study 

also contributes to managerial knowledge by providing information regarding the influence of key events 

on the job satisfaction of older employees. Our results contribute further to managerial knowledge by 

demonstrating significant links between subjective age and two types of job satisfaction, as well as 

between common indicators of recognition about one’s work experience, age, and job satisfaction. 

121

The importance of our findings lie in the widely-reported positive relationship between age and job 

satisfaction, and in the fact that organizational demographics will increasingly require managers to know 

more about managing aging workers. As the average age of employees in organizations increase with the 

advancing age of the Baby Boom cohort, the interplay between age and various forms of job satisfaction 

will become increasingly important for organizations. These relationships comport important implications 

for managing and retaining the most knowledgeable employees in an aging workforce. Since desirable 

consequences are advantageous to both organizations and employees, and since the proportion of older 

workers is increasing dramatically, we need to urgently devise practices that help maintain and increase 

job satisfaction for older workers. Investigating mediators of the age-satisfaction relationship will help 

identify relevant practices. In this study, we investigated the mediating role of recognition of work 

experience. Future studies should also examine the way these are transmitted to employees, and 

investigate other possibly relevant mediators, such as how organizational rewards and development 

activities are distributed and how opportunities to realize late-career ambitions are managed. 

REFERENCES 

Barnes-Farrell, J., & Piotrowski, M. J. (1989). Workers' perceptions of discrepancies between 

chronological age and personal age: You're only as old as you feel. Personality and Aging, 4(3), 

376 - 377. 

Barnes-Farrell, J., Rumery, S. M., & Swody, C. A. (2002). How do concepts of age relate to work and 

off-the-job stresses and strains? A field study of health care workers in five nations. Experimental 

Aging Research, 28, 87 - 98. 

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychology 

research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social 

Psychology, 51, 1173-1182. 

Bobko, N. A., & Barishpolets, A. T. (2002). Work ability, age and its perception, and other related 

concerns of Ukraine health care workers. Experimental Aging Research, 28, 59 - 71. 

Bono, J. E., & Judge, T. A. (2003). Self-concordance at work: understanding the motivational effects of 

transformational leaders. Academy of Management Journal, 46, 554-571. 

Brayfield, A. H., & Rothe, H. F. (1951). An Index of Job Satisfaction. Journal of Applied Psychology, 35, 

307-311. 

Brush, D. H., Moch, M. K., & Pooyan, A. (1987). Individual demographic differences and job 

satisfaction. Journal of Occupational Behavior, 8, 139 - 156. 

Cleveland, J. N., & Shore, L. M. (1992). Self and supervisory perspective on age and work attitudes and 

performance. Journal of Applied Psychology, 77, 469-484. 

Cleveland, J. N., Shore, L. M., & Murphy, K. R. (1997). Person-and context-oriented perceptual age 

measures: Additional evidence of distinctiveness and usefulness. Journal of Organizational 

Behavior, 18, 239-251. 

Cloutier, E., Lefebvre, S., Ledoux, É., Chatigny, C., & St-Jacques, Y. (2002). Enjeux de santé et de 

sécurité au travail dans la transmission des savoirs professionnels: Le cas des usineurs et des 

cuisiniers. Montreal, QC: IRSST (Institut de recherche Robert Sauvé en santé et en sécurité du 

travail). 

Conlin, M. (2003). Grandpa? He's busy at the office. Business Week Online, News Analysis (January 3, 

2003). Retrieved December 14 2005, from 

http://businessweek.com/bwdaily/dnflash/jan2003/nf2003013_1240.htm 

Crampton, S., Hodge, J., & Mishra, J. (1996). Transition - ready or not: The aging of America's work 

force. Public Personnel Management, 25(2), 243-256. 

Critchley, R. K. (2004). Doing nothing is not an option! Facing the imminent labor crisis. Mason, OH: 

South-Western. 

DeLong, D. W. (2004). Lost Knowledge. Oxford: Oxford University Press. 

122

Dormann, C., & Zapf, D. (2001). Job satisfaction: A meta-analysis of stabilities. Journal of 

Organizational Behavior, 22(5), 483 - 504. 

Forte, C. S., & Hansvick, C. L. (1999). Applicant age as a subjective employability factor: A study of 

workers over and under age fifty. Journal of Employment Counseling, 36, 24 - 35. 

Fullerton, H. N. J. (1999). Labor Force Projections to 2008: Steady Growth and Changing Composition. 

Monthly Labor Review, 122(11), 19-33. 

Gibson, J. L., & Klein, S. M. (1970). Employee attitudes as a function of age and length of service: A 

reconceptualization. Academy of Management Journal, 13, 411-425. 

Glass, A. (2007). Understanding generational differences for competitive success. Industrial and 

Commercial Training, 39, 98. 

Greller, M. M., & Stroh, L. K. (1995). Careers at midlife and beyond: A fallow field in need of 

sustenance. Journal of Vocational Behavior, 47, 232-247. 

Hassell, B. L., & Perrewe, P. L. (1995). An examination of beliefs about older workers: Do stereotypes 

still exist? Journal of Organizational Behavior, 16, 457- 468. 

Hughes, D., C., Blazer, D. C., & George, L. K. (1988). Age differences in life events: A multivariate 

controlled analysis. International Journal of Aging and Human Development, 27(3), 207-220. 

Iskra-Golec, I. (2002). Personal age and assessment of work stress in Polish nurses. Experimental Aging 

Research, 28, 51 - 58. 

Judge, T. A., Bono, J. E., & Locke, E. A. (2000). Personality and job satisfaction: The mediating role of 

job characteristics. Journal of Applied Psychology, 85(2), 237 - 249. 

Kalleberg, A. L., & Loscocco, K. A. (1983). Aging, values and rewards: Explaining age differences in job 

satisfaction. American Sociological Review, 48, 78-90. 

Kanfer, R., & Ackerman, P. L. (2004). Aging, adult development, and work motivation. Academy of 

Management Review, 29, 440-458. 

Kline, T. J. B., Sulsky, L. M., & Rever-Moriyama, S. D. (2000). Common method variance and 

specification errors: A practical approach to detection. The Journal of Psychology, 134, 401-421. 

Lawrence, B. S. (1987). An organizational theory of age effects. In N. DiTomaso (Ed.), Research in the 

sociology of organization (Vol. 5, pp. 37-71). Greenwich, CT: JAI Press. 

Lawrence, B. S. (1988). New Wrinkles in the Theory of Age: Demography, Norms, and Performance 

Ratings. Academy of Management Journal, 31, 309-337. 

Lemme, B. H. (1999). Development in Adulthood (2nd Ed.). Boston, MA: Allyn & Bacon. 

Levinson, D. J., Darrow, C. N., Klein, E. B., Levinson, M. H., & McKee, B. (1978). The seasons of a 

man's life. New York: Alfred A. Knopf. 

Levy, B. (2003). Mind matters: Cognitive and physical effects of aging self-stereotypes. Journal of 

Gerontology, 58B(4), 203 - 211. 

Lindgren, A. (2007). If 70 is the new 60, what’s your next career? Retrieved December 10, 2007, from 

http://www.retirement-retirement.com/story-436.php 

Montepare, J. M., & Lachman, M. E. (1989). "You're only as old as you feel": Self-perceptions of age, 

fears of aging, and life satisfaction from adolescence to old age. Psychology and Aging, 4(1), 73 - 

78. 

Nuttman-Schwartz, O. (2004). Like a High Wave: Adjustment to Retirement. The Gerontologist, 44(2), 

229-236. 

Peterson, C. (1996). The ticking of the social clock: Adults' beliefs about the timing of transitional events. 

International Journal of Aging and Human Development, 42(3), 189 - 203. 

Rhodes, S. R. (1983). Age-related differences in work attitudes and behavior: A review and conceptual 

analysis. Psychological Bulletin, 93, 323-367. 

Rubin, D. C., & Berntsen, D. (2006). People over 40 feel 20% younger than their age: Subjective age 

across the lifespan. Psychonomic Bulletin & Review, 13(5), 776 - 780. 

Shaw, J. B., & Grubbs, L. L. (1981). The process of retiring: Organizational entry in reverse. Academy of 

Management Review, 6, 41-47. 

123

Smith, P., Kendall, L., & Hulin, C. (1969). The measurement of satisfaction in work and retirement. 

Chicago, IL: Rand McNally. 

Sobel, M. E. (1982). Asymptotic intervals for indirect effects in structural equation models. In S. Leinhart 

(Ed.), Sociological Methodology. San Francisco, CA: Jossey-Bass. 

Spector, P. E. (1997). Job satisfaction: Application, assessment, causes and consequences. London: Sage. 

Super, D. E. (1957). The psychology of careers. New York: Harper. 

Uotinen, V., Rantanen, T., Suutama, T., & Ruoppila, I. (2006). Change in subjective age among older 

people over an eight-year follow-up: "Getting older and feeling younger?" Experimental Aging 

Research, 32(4), 381 - 393. 

White, A. T., & Spector, P. E. (1987). An investigation of age-related factors in the age-job-satisfaction 

relationship. Psychology and Aging, 2(3), 201 - 265. 

Williams Walsh, M. (2001, Feb 26, 2001). Reversing Decades-Long Trend, Americans Retiring Later in 

Life. New York Times, p. A1. 

Wright, H., & Hamilton, R. (1978). Work satisfaction and age: Some evidence for the job change 

hypothesis. Social Forces, 59(4), 1140-1158. 

124

ABSTRACTS / RÉSUMÉS 

ASAC 2008 Mardi Witzel (student) 

Halifax, Nova Scotia School of Business and Economics 

Wilfrid Laurier University 

LEADERSHIP AND CREATIVITY: THE MEDIATING EFFECTS OF INTRINSIC 

MOTIVATION, DOMAIN-RELEVANT SKILLS, AND CREATIVITY-RELEVANT 

PROCESSES 

The literature on organizational behavior seeks to identify the human and contextual dynamics 

that explain creativity. This research investigates the role of transactional and transformational 

leadership in predicting creative outcomes, with intrinsic task motivation, domain-relevant skills 

and creativity-relevant processes considered as mediators. A conceptual model and hypotheses 

are presented, with plans for empirical testing. 

ASAC 2008 Sara L. Mann 

Halifax, Nova Scotia Department of Business 

University of Guelph 

GaryP. Latham 

Rotman School of Management 

University of Toronto 

Who receives a performance appraisal and does it matter? An empirical investigation of 

the determinants of the receipt of a performance appraisal and its effect on job satisfaction 

An analysis of Statistic Canada’s Workplace and Employee Survey (WES), based on a five-year 

period, revealed that only 60% of the 20,834 respondents received a performance appraisal. 

Higher levels of job satisfaction were reported by individuals who perceived that their appraisal 

impacted their pay, benefits and most recent promotion. 

150

ASAC 2008 Saba Sharih (PhD Student) 

Halifax, Nova Scotia Simon Taggar 

School of Business & Economics 


STRATEGIC RESPONSIVENESS WITHIN AN IMSA FRAMEWORK- 

INSTITUTIONAL AND RESOURCE BASED PERSPECTIVES 

Organizational scholars have conceptualized organizational responsiveness to institutional 

pressures as a strategic choice. This thesis highlights a number of institutional and resourcebased 

determinants of this critical strategic choice from an intrafirm perspective. Cause, 

constituents and content are proposed as antecedents of strategic responses employed by the 

inner core employee segment to pressures exerted by other employee segments within an 

organization. Implications for theory building and practice are discussed. 

ASAC 2008 Christa L. Austin (student) 

Halifax, Nova Scotia Catherine E. Connelly 

Human Resources and Management 

DeGroote School of Business, McMaster University 

RECRUITERS’ PERCEPTIONS OF APPLICANTS’ VOLUNTEER EXPERIENCE: ARE ALL 

VOLUNTEER ASSIGNMENTS EQUALLY RELEVANT? 

An ongoing debate exists in the practitioner literature as to how recruiters interpret and use 

applicants’ volunteer experiences. This study found that recruiters perceived certain volunteer 

experiences to be more indicative of various desirable traits (i.e., motivation, interpersonal skills, 

leadership qualities). Practical implications and directions for future research are discussed. 

151

ASAC 2008 Travor C. Brown 

Halifax, NS Memorial University 

Martin McCracken 

University of Ulster 

Sergio De Leon (student) 

Memorial University 

BARRIERS TO TRANSFER: PARTICIPANT’S PERSPECTIVE: PRELIMINARY RESULTS 

Transfer of training is a critical issue for training programs. While considerable quantitative work has 

examined barriers to transfer, few studies have assessed transfer from the perspective of traineesthemselves. 

In this paper, we review open-ended qualitative data, from union and managerial participants 

enrolled in a leadership skills program, to examine barriers to transfer. 

ASAC 2008 Sunny Marche, PhD, CMC 

HALIFAX, NOVA SCOTIA John F. Duffy, PhD 

Geneviève Perron (Ph.D. Candidate) 

Faculty of Management / Faculty of Graduate Studies 

Dalhousie University 

SERIOUS THREATS TO CANADIAN UNIVERSITY FACULTY MEMBERS –SURVEY 

OUTCOMES 

Serious workplace threats have been reported for doctors, nurses, judges, lawyers 

and elementary school teachers. This is the first survey of workplace threats for 

university professors in Canada, and to the best of our knowledge, in the world. 

We report on a selection of existing related literature and the results from an 

online survey. 

152

ASAC 2008 James Doyle 

Halifax, Nova Scotia Alia El Banna 

Linda Duxbury 

Chris Higgins 

Carlton University 

A STATISTICAL INVESTIGATION OF ANTECEDENTS AND OUTCOMES OF JOB- 

RELATED STRESS FOR TEACHERS 

Developing a healthy workplace is an important concern for organizations, as the implications of 

job-related stress are extensive and have negative effects on both individuals and organizations. 

This research study explores job-related stress factors and the mental-health outcomes 

experienced by a sample of school teachers in Ontario. 



Shawn Komar (student) 

Douglas J. Brown 

Department of Psychology 

University of Waterloo 

Chet Robie 

School of Business and Economics 


EXPLORING FAKING IN THE CONTEXT OF MULTI-STAGE SELECTION SYSTEMS 

The current study examines the impact that faking on a conscientiousness measure has on 

performance in multi-stage selection contexts. The results suggest that combining personality 

measures with other measures will not mitigate the negative effect of faking. The results are 

discussed in terms of the implications for employee selection. 

153

ASAC 2008 Akanksha Bedi (student) 

Halifax, Nova Scotia Mark S. Skowronski (student) 

Dr. Aaron C. H. Schat 

DeGroote School of Business 

McMaster University 

POLITICAL SKILL: A META –ANALYSIS OF ITS 

PREDICTORS AND OUTCOMES 

This paper describes a meta-analysis of the antecedents, correlates, and outcomes of political skill. The 

results suggest negligible relationships between political skill and demographic variables and moderate 

relationships with job satisfaction and job performance. Practical and research implications of the findings 

are discussed. 

ASAC 2008 Wendy R. Carroll 

Halifax, Nova Scotia Ph.D. Student (ABD 

Saint Mary’s University 

Terry H. Wagar 


Kent V. Rondeau 

University of Alberta 

EXPLORING THE RELATIONSHIP BETWEEN ORGANIZATIONAL CULTURE AND 

QUIT BEHAVIOUR: EVIDENCE FROM CANADIAN CALL CENTRES 

Call centres are integral business operations for many organizations that have become 

characterized by high levels of voluntary turnover. In this paper, we examine the relationship 

between quit behaviour and organizational culture using data from a national survey of call centres 

and a case study of employees at one call centre. We found that call centres with a more social 

organizational culture type (clan) were associated with lower quit rates and longer periods of 

employee intention to stay with the organization. However, call centres with a more market 

oriented culture type were related to higher quit rates and shorter periods of intended stay with an 

organization. 

154

ASAC 2008 Jim D. Grant (PhD Candidate) 

Halifax, Nova Scotia School of Business and Economics 

Nipissing University 

Terry H. Wagar 

Sobey School of Business 


DEVELOPMENTS IN CANADIAN EMPLOYMENT LAW AND THE SUPREME COURT OF 

CANADA: EVIDENCE FROM AN EXAMINATION OF REASONABLE NOTICE IN THE 

WRONGFUL DISMISSAL COMMON LAW 

This study examined the determinants of reasonable notice in wrongful dismissal law in a way which 

incorporates the effect of Supreme Court of Canada (SCC) decisions such as in Wallace v. United Grain 

Growers (1997). We explored the relationship between reasonable notice awards and employees’ 

performance, vulnerability, and changing employment circumstances, as well as employers’ allegations of 

misconduct over and above poor performance and failure to employ progressive discipline. In addition, 

we wanted to determine if the Wallace decision, in which the SCC affirmed the bargaining inequality 

between employee and employer, has had an effect on notice periods in general. 

155

Proceedings / Actes Volume 29, Division 9, 2008 - Index of

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?