Work-Life Benefits and Positive Organizational Behavior

Journal of Organizational Behavior

J. Organiz. Behav. 29, 171–192 (2008)

Published online in Wiley InterScience

(www.interscience.wiley.com) DOI: 10.1002/job.506

*Correspondence to:MI 49008-5429, U.S.

Copyright # 2008

Work-life benefits and positiveorganizational behavior: is therea connection?

LORI MUSE1*, STANLEY G. HARRIS2,

WILLIAM F. GILES2 AND HUBERT S. FEILD2

1Department of Management, Western Michigan University, Kalamazoo, Michigan, U.S.A.2Department of Management, Auburn University, Auburn, Alabama, U.S.A.

Summary Focusing on the employee well-being component of positive organizational behavior (POB),this study explores the relationship between organization provided benefit programs and POB.Specifically, we ask the question: are employees’ use and perceived value of a work-life benefitpackage associated with their positive attitudes and behaviors in the workplace? Grounded insocial exchange theory and the norm of reciprocity, we develop and estimate a modelidentifying differential relationships of benefit use and perceived benefit value with employeeattitudinal and performance outcomes. Employing the multigroup method, the hypothesizedmodel was fit to the data of two dissimilar organizations. Results support our hypothesis thatproviding work-life benefits employees use and/or value is part of a positive exchange betweenthe employee and employer. This exchange is positively related to employees’ feelings ofperceived organizational support and affective commitment to the organization and reciproca-tion in the form of higher levels of task and contextual performance behaviors. Results alsorevealed that employees’ perceptions of benefit program value play a critical role regardless ofactual program use in influencing attitudes and behavior. Our findings emphasize theimportance of valuing employees and investing in their well-being inside as well as outsidethe workplace. Copyright # 2008 John Wiley & Sons, Ltd.

Introduction

Luthans (2002) and Wright (2003) recently charged the field of organizational behavior with

approaching research from a more positive perspective, pointing to the vast number of articles with a

negative slant (375 000) compared to a positive vein (1000) as evidence of the need for change in

approach. They suggest that it is time to start framing research with a positive lens, offering positive

organizational behavior (POB) as one avenue. POB is defined as ‘the study and application of

positively oriented human resource strengths and psychological capacities that can be measured,

Lori Muse, Department of Management, Western Michigan University, 3369 Schneider Hall, Kalamazoo,A. E-mail: [email protected]

John Wiley & Sons, Ltd. Accepted 10 September 2007

172 L. MUSE ET AL.

developed, and effectively managed for performance improvement in today’s workplace’ (Luthans,

2003, p. 167).

Much of the research thus far has worked to define measurable components of POB, identifying

confidence, hope, optimism, well-being, emotional intelligence, and resiliency as meeting the

definitional criteria (Luthans, 2002). However, research has not yet explored if and how an organization

might create an environment conducive to POB. Focusing on the employee well-being component of

POB, this study investigates the implications of use and perceived value of work-life employee benefit

packages for positive employee attitudes and behaviors in the workplace.

Nearly three decades ago, Kanter (1977) proposed the view of work and family in the business world

as that of two separate domains. More recently businesses have begun to realize that work and family

are indeed intertwined and need to be treated as such. Each year in their 100 best companies to work for

list, Fortune magazine identifies organizations that are increasingly expanding and diversifying their

work-life benefit programs in an attempt to help employees better manage the work and non-work

demands facing them. Evolving from ‘family-friendly’ initiatives, ‘work-life’ benefits are designed to

help employees with the many facets of their lives including their personal well-being, professional

development, and family responsibilities (Galinsky, Bond, & Friedman, 1996; McShane & Von

Glinow, 2000). Following an investment-in-employees approach as opposed to the traditional

utilitarian lens, a work-life benefits package can include benefits from six categories: child-related

(e.g., childcare facilities, financial assistance, and referral, childhood health programs, and maternity/

paternity leave), time/schedule (e.g., flex-time, compressed workweek, and job sharing), physical

health (e.g., health insurance, medical and fitness centers, and wellness programs), psychological

well-being (e.g., counseling and employee assistance programs), professional development (e.g.,

tuition reimbursement and training), and eldercare (e.g., assistance and referrals).

It is the emphasis of work-life life benefits on employee well-being that connects them with POB.

Wright (2003) identified one of the challenges facing POB is offering ‘a more balanced view of human

nature than that offered by the traditional utilitarian approach’ (p. 440). Wright also highlighted the

application of Fredrickson’s (1998, 2001) ‘broaden and build’ theory of positive emotions as a way to

strengthen POB research. Fredrickson’s theory identifies positive emotions as central to an individual’s

growth and development, enabling people to become more pro-active. Applying Frederickson’s theory

to work-life benefits would suggest sending a message that the organization cares about its employees

enough to provide a benefit package that they use and/or value and that contributes to their well-being

as a person, not just an employee, is a more balanced approach that could facilitate proactive attitudes

and behaviors in the workplace. Prior research has identified affective commitment and performance as

means for employees to reciprocate favorable treatment from their employer (Rhoades & Eisenberger,

2002).

Positive employee attitudes and behaviors have been theoretically and empirically tied to diverse

aspects of employee benefits including benefit choice (Duleborn, Murray, & Sun, 2000), benefit

availability (Allen, 2001; Behson, 2005; Grover & Crooker, 1995), benefit satisfaction (Williams,

Malos, & Palmer, 2002), perceived benefit fairness (Parker & Allen, 2001), knowledge of how to take

advantage of benefits (Haar & Spell, 2004), benefit use (Allen, 2001; Butler, Gasser, & Smart, 2004;

Lambert, 2000), benefit usefulness (Lambert, 2000), and perceived benefit value (Haar & Spell, 2004;

Wilson, Northcraft, & Neale, 1985). Despite this literature, several authors have noted that the nature of

the relationships between work-life benefit programs and employee attitudes and behaviors remains

unclear and have called for more research on the impact of work-life benefits in the workplace (Casper

& Buffardi, 2004; Eby, Casper, Lockwood, Bordeaux, & Brinley, 2005; Kossek & Ozeki, 1998; 1999).

Responding to this call, we develop a model, grounded in social exchange theory and the norm of

reciprocity, relating employees’ use and perceived value of work-life benefits to four important

attitudinal and behavioral outcomes: employees’ level of perceived organizational support (POS),

Copyright # 2008 John Wiley & Sons, Ltd. J. Organiz. Behav. 29, 171–192 (2008)

DOI: 10.1002/job

WORK-LIFE BENEFITS 173

affective commitment and task and contextual performance. To better assess the model’s

generalizability, we test the model in two dissimilar organizations. This study contributes to the

research on POB and employee benefits and their integration in several ways. First, we respond to

Lambert (2000) and Haar and Spell’s (2004) call for more research on the relative roles of benefit use

and perceived value. Second, the model developed and tested is the first that has simultaneously

examined benefits’ influence across our four diverse outcome variables. Previous research has

examined only subsets of these outcomes and none have theoretically integrated the four in a single

model. Third, this research challenges previous beliefs that employee benefits cannot be related to POS

(Shore & Shore, 1995; Wayne, Shore, & Liden, 1997).

Literature Review, Theoretical Model, and Hypotheses

Social exchange theory and the norm of reciprocity generally provide the theoretical justification for

expecting work-life benefits to be positively reciprocated by employees in the form of positive attitudes

and behaviors (e.g., Lambert, 2000). Social exchange theory characterizes the employee–employer

relationship as an exchange of valued resources (Blau, 1964). Researchers have revealed recognition

and rewards (Shore & Shore, 1995), fair treatment of employees (Kacmar & Carlson, 1997), strong

levels of supervisory support (Eisenberger, Huntington, Hutchison, & Sowa, 1986), and training

(Wayne et al., 1997) are perceived by employees as valued resources offered by organizations to their

employees. Employees can chose to reciprocate in the workplace by developing an emotional

attachment to the organization in the form of affective commitment (Eisenberger, Fasolo, &

Davis-LaMastro, 1990; Settoon, Bennett, & Liden, 1996), exerting extra effort in performing

job-related tasks (Meyer, Sampo, Paunonen, Gellatly, Goffin, & Jackson, 1989; Meyer, Stanley,

Herscovitch, & Topolnytsky, 2001), and exhibiting more pro-social behaviors (Meyer et al., 2001).

Connecting social exchange theory (Blau, 1964) and the norm of reciprocity (Gouldner, 1960) with

work-life benefits suggests such programs have the potential to create a positive exchange relationship

between the employer and employee. Consistent with this argument, Lambert (2000) found benefit use,

aggregated across the diverse benefits in a work-life benefits package, was positively related to

interpersonal helping behaviors and POS.

Benefit use and perceived value

Lambert (2000) emphasized the centrality of perceived value of work-life benefits in the exchange

relationship. Lambert employed Gouldner’s (1960) argument that individuals react differently to the

same action based on their value system to justify the importance focusing on benefit value in

determining an employee’s resulting feelings of obligation. In other words, since individuals can value

benefits differently, it is the value ascribed the benefits offered rather than just the offering of benefits

that engenders reciprocation. For example, a benefit such as childcare is unlikely to engender

reciprocation from someone with no children and no plans to have any because the benefit has no

perceived value to them. Consistent with this hypothesis, Lambert (2000) found that the perceived

‘usefulness’ of a work-life benefits package (i.e., the extent to which it helped balance work and family

demands, provided benefits they could not afford, helped their children have opportunities to do things

they would not have otherwise been afforded, and helped in difficult times) was positively related

to three specific manifestations of organizational citizenship behavior (OCB): suggestions submitted to

the organization, quality meeting attendance, and interpersonal helping among a sample of employees

in one organization.


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174 L. MUSE ET AL.

Lambert distinguished benefit use from perceived benefit value and intended to control for benefit

use. Unfortunately, problems with model identification did not allow benefit use to be used as a control.

However, Lambert did examine the relationship between use and the other variables in the study and

found it to positively relate to perceived benefit usefulness, and interpersonal helping. She concluded

that more research on the relative roles of benefit use and perceived value in the exchange relationship

was needed.

Complicating interpretation of Lambert’s (2000) results for understanding the role of work-life

benefits for POB is a recent study by Haar and Spell (2004). Haar and Spell failed to find any positive

relationships between the perceived value of six specific work-family practices and normative,

affective, or continuance commitment in a sample of six subunits of a New Zealand Government

department. They also reported finding no relationships between use of the benefits and commitment.

Haar and Spell’s results may have been influenced by focusing on a department that was embedded in

the larger government system. To the extent that some benefits were common across government

departments, one would not expect such common benefits to engender reciprocation to a specific

department.

How are the differences between Lambert’s (2000) and Haar and Spell’s (2004) findings to be

resolved? A commonality between both studies was a grounding in social exchange theory and the

theoretical expectation that both use and value would encourage positive employee reciprocation.

Perhaps Lambert’s emphasis on the aggregated benefit package made it easier to demonstrate a

reciprocal relationship. Haar and Spell did not aggregate to the benefit package level; by focusing on

discrete benefits, the relationships Haar and Spell expected with the commitment variables may have

been diluted. Lambert also focused on very specific behavioral manifestations of OCB while Haar and

Spell looked at forms of departmental commitment. It is clear that a more integrative and expanded

theoretical framework of key variables is needed to help clarify the role of benefits in employees’

reciprocating attitudes and behaviors.

Benefits and perceived organizational support

Work-life benefit programs can be interpreted as a signal that the organization cares about the well-

being of its employees, thereby strengthening the employer-employee bond and creating a desirewithin

employees to reciprocate. While the use of work-life benefits themselves may directly engender a

desire to reciprocate, using such benefits might also signal a generalized feeling of organizational

support that encourages reciprocation. POS has been defined as the global beliefs employees develop

concerning the extent to which the organization values their contributions and cares about their

well-being (Eisenberger et al., 1986). Antecedents of POS include signals sent by top management that

are interpreted by employees as the organization caring for them (Shore & Shore, 1995).

Whereas some researchers have speculated that work-life benefits can contribute to workers’

feelings of POS (Grover & Crooker, 1995; Kossek, 1989), others have contended that benefits offered

to all employees cannot be related to POS because such benefits are not discretionary and therefore do

not signal to employees that they are valued (Shore & Shore, 1995; Wayne et al., 1997). We agree with

Shore and Shore (1995) and Wayne et al. (1997) that benefit availability should not be related to POS

because the sheer provision of benefits does not vary across employees. However, employees can use

and/or value the same benefit differently (Casper & Buffardi, 2004) therefore making benefit use and

perceived benefit value variable rather than constant. Providing work-life benefits that are used and/or

valued can be viewed as a message from the organization that it is concerned enough for its employees’

well-being to offer a benefit package that addresses employee needs not covered by traditional

benefit plans.


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Support represents yet another resource offered by organizations, leading us to expect assessments of that

support, in the form of POS, to encourage reciprocation. Therefore, work-life benefits can encourage

reciprocation in two ways: direct reciprocation for the benefits used themselves and reciprocation for the

resulting POS generated by the symbolic value of offering such benefits. Similarly, Lambert (2000)

hypothesized that POS would mediate the relationship between perceived benefit usefulness and OCB

behaviors. While she found both use and perceived usefulness positively related to POS, POS was not

related to two of the OCB behaviors and negatively related to one. Lambert’s results suggest that POS may

not play a role in reciprocation in the form of specific OCB behaviors or that the role played is not direct.

Clearly, the nature of the role played by POS in the exchange process requires clarification.

Theoretical model

In the present study, we focus on re-examiningwork-life benefit use and perceived value through a POB lens

with an aim at improved understanding of their connections with employee attitudes and behaviors.

Specifically, we believe the influence of work-life benefits on the organization-employee social exchange is

most likely to be evidenced in their aggregate use and value and therefore we focus on use and perceived

value aggregated across the benefits included in a total package. In addition, we believe a more expansive

theoretical ordering of employee POS, commitment, and behaviors will strengthen the theory, research, and

subsequent understanding. Finally, we contend that a broader focus on task and contextual behaviors will be

more fruitful than Lambert’s (2000) focus on three very specific behaviors reflective of OCB. Based on

theory and extant research, we developed a model of proposed relationships shown in Figure 1. The

rationale for this model and the relationships it depicts are discussed below.

Use of benefits, POS, and affective commitment

The emotional attachment associated with affective commitment characterizes the employer/employee

relationship such that employees remain with the organization because they want to. Employees whose

Figure 1. Hypothesized model for examining differential relationships of employee benefit use and perceivedbenefit value


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176 L. MUSE ET AL.

basic needs and expectations are met tend to develop stronger affective attachment to the organization

than do those whose needs and expectations are not met (Meyer, Allen, & Smith, 1993). Use of

work-life benefits satisfies certain employee needs, contributing to their well-being and therefore can

positively influence the employee–employer relationship and contribute to employees positively

evaluating their commitment and attachment to the organization. Employees can reciprocate the

benefits they have utilized with greater psychological attachment to the organization. In addition to

directly reciprocating the use of benefits with affective commitment, benefit use should also be

associated with greater assessments in POS, which can also be reciprocated with affective

commitment.

Hypothesis 1a. Use of work-life benefits will have a positive direct relationship with affective

commitment.

Hypothesis 1b. The relationship between use of work-life benefits and affective commitment will

also be partially mediated through POS.

Perceived benefit value, POS, and affective commitment

Haar and Spell (2004) hypothesized a direct relationship between perceived benefit value and

organizational commitment. They assessed perceived value by simply asking respondents to rate how

valuable each practice was to them. Consequently, perceived valuewas subject to interpretation relative

to each individual’s past, present, and future needs and circumstances. They only found a correlation

between perceived value (across six work-life benefits) and affective commitment, and it was in the

direction opposite what they hypothesized. In addition to the potential that some of the benefits were

not features of the department, but rather of the government as a whole as described earlier, Haar and

Spell’s focus on the value of individual benefits may have diluted the reciprocity they expected.

Aggregating across benefits, as Lambert (2000) did might have been more appropriate since

commitment is more likely to result from an aggregated sense of support.

Haar and Spell also expected and tested for a direct relationship between perceived value

and commitment; they even controlled for a potentially intervening attitude, POS. In contrast,

Weathington and Tetrick (2000) suggest that benefit importance will have an indirect rather than a

direct relationship with affective commitment. Benefits that are valued may not have yet been utilized

and consequently may also not engender any current repayment obligation. It is logical however, to

expect benefit value to symbolically reinforce general assessments of POS. In turn, we expect

these POS sentiments to translate into reciprocal employee affective commitment. Employees

experience psychological attachment to the organization because the organization has demonstrated its

continuing support for their well-being (Rhoades & Eisenberger, 2002; Rhoades, Eisenberger, &

Armeli, 2001).

Hypothesis 2. Perceived benefit value will have a positive relationship with affective commitment

that is fully mediated through POS.

Affective commitment and task and contextual performance

Researchers have identified task and contextual performance as distinct constructs within the broader

domain of job performance (Borman & Motowidlo, 1993; Van Scotter, Motowidlo, & Cross, 2000).


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Task performance has been described as those tasks that differentiate one occupation from another and

are required as part of the individual’s job. In contrast, contextual performance addresses behaviors that

‘support the broader organizational, social, and psychological environment in which the technical core

must function’ (Borman &Motowidlo, 1993, p. 73). Moreover, contextual behaviors are not tied to any

one specific job but are common to many jobs within the organization. Examples of contextual

performance behaviors include taking the initiative to solve a problem, working harder than necessary

(job dedication), praising a co-worker, and helping a co-worker without being asked (interpersonal

facilitation) (Van Scotter et al., 2000).

Contextual performance differs from OCBs which have been defined as ‘individual behavior that is

discretionary, not directly or explicitly recognized by the formal reward system, and that in the aggregate

promotes the effective functioning of the organization’ (Organ, 1988, p. 4). Some researchers have

suggested that many of the behaviors in OCB scales are really more in-role behaviors rather than extra-role

(e.g.,Morrison, 1994). Additionally, researchers have suggested that some forms ofOCB are just as likely to

lead to rewards as in-role behaviors (Organ, 1997; Orr, Sackett, & Mercer, 1989). According to Organ

(1997), contextual performance is a broader construct than OCB because is recognizes non-task related

behaviors that can be both in-role and extra-role and rewarded and non-rewarded. While the constructs of

contextual performance and OCB are similar (Findley, Mossholder, & Giles, 2000; Organ, 1997),

contextual performance is free of some criticisms that have been leveled at the conceptual requirement of

OCB. Therefore, this study focuses on contextual performance.

Following social exchange (Blau, 1964) and the norm of reciprocity (Gouldner, 1960), we would

expect that work-life benefits would ultimately be reciprocated by employee task and contextual

performance. Consistent with this expectation, Lambert (2000) demonstrated positive relationships

between work-life benefit use and perceived usefulness and OCB. However, we feel that the influence

of benefit use and perceived value on performance is not direct and instead will be fully mediated

through affective commitment. Task and contextual performance are not direct reimbursements for

work-life benefits. Instead, they are more likely ‘repayments’ for a generalized sense of psychological

and affective attachment to the organization. Balance theory (Heidner, 1958) suggests individuals must

have a balance between their attitudes and behaviors. Violations of balance create cognitive dissonance

(Festinger, 1957) which has been shown to generate stress and motivate attempts to reduce the

dissonance. Being affectively committed to an organization is an attitude that is cognitively dissonant

with positive task and contextual performance. Research on the employee–employer relationship has

demonstrated that employees can chose to reciprocate positive treatment by their employer by exerting

extra effort in performing job-related tasks (Meyer et al., 1989, 2001), and exhibiting more pro-social

behaviors (Meyer et al., 2001; Settoon et al., 1996). Based on theoretical rationale and empirical

support for a relationship with OCB, we anticipate affective commitment will mediate the positive

relationships between benefit use and POS with both task and contextual performance.

Hypothesis 3a. Affective commitment will fully mediate the positive relationship of benefit use with

task performance.

Hypothesis 3b. Affective commitment will fully mediate the positive relationships of benefit usewith

the contextual performance dimensions of interpersonal facilitation and job dedication.

Hypothesis 4a. Affective commitment will fully mediate the positive relationship of POS with task

performance.

Hypothesis 4b. Affective commitment will fully mediate the positive relationships of POS with the

contextual performance dimensions of interpersonal facilitation and job dedication.


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178 L. MUSE ET AL.

Organizational Context

In the summer and fall of 2001, we collected data for this study from two research sites. The sites

chosen were a healthcare organization (Organization A) and a manufacturing company

(Organization B), both listed in 2000 and 2001 among Fortune magazine’s 100 best companies

in America to work for (Levering, Moskowitz, Sung, Daniels, & Spencer, 2001). Since our study

focused on POB and work-life benefits, we chose these companies because both had extensive, yet

diverse work-life benefit programs that had been in place for quite a long time. Our choice of these

organizations is consistent with Haar and Spell’s (2004) observation, based on Whitener, Brodt,

Korsgaard, & Werner’s (1998) discussion of the norm of reciprocity, that ‘when testing for

reciprocation between employers and employees, the organization researched should ideally

already offer multiple work-family practices and have been doing so for some time, thus allowing

for a moral obligation to develop’ (p. 1042). Whereas our choice of organizations might reduce the

generalizability of our results to organizations with lesser developed work-life benefits, we

attempted to enhance generalizability by choosing organizations from two very different industries

(i.e., healthcare and manufacturing) with divergent jobs.

Organization A (Healthcare Organization)

Organization A is located in a small city in the southeastern United States, and at the time of our

study employed approximately 1700 employees. As a healthcare organization, the majority of

employees in Organization A were professionals including managers, physicians, nurses,

pharmacists, laboratory specialists, dieticians, and radiology technicians. Females made up

83 per cent of employees and 68 per cent of the population were white.

Organization A is one of its city’s largest employers and is governed by a ten person Board of

Directors. The president had led the organization for 12 years and believed strongly that the

treatment of employees influences the level of care they provide to patients. The organization

routinely strove to continually better meet the needs of its employees, emphasized an open door

policy and asked for employee feedback via surveys and team meetings throughout the year.

Organization A offered a diverse range of work-life benefits. Child-related benefits included paternity/

maternity leave and on-site childcare. Health benefits included a fitness center, long-term disability insu-

rance, and medical insurance including prescription, dental, vision, and cancer plans. Scholarships to

encourage professional development were also available. To support psychological well-being, Organi-

zation A offered employee assistance and employee in crisis programs. Finally, to help employees manage

their time and schedule demands, a leave bank and on-site credit union and cafeteria were offered.

Organization B (Manufacturing Organization)

Organization B, also located in the southeast, is a steel pipe manufacturer that at the time of our

study employed 2200 employees. Most employees worked in manufacturing, with some

professional positions in sales, research, finance and accounting. The employee population was

84 per cent male and 87 per cent white. The companywas founded over 100 years ago and continued

to be based upon Christian principles, emphasizing in its value statement the golden rule ‘do unto

others as you would have done unto you.’ The CEO had managed the company for 12 years and

reported to a 12 person board that included several employee members. The organization had an

extremely low turn-over rate of 3 per cent annually.

Organization B also offered a diverse range of work-life benefits to its employees. Child-related

benefits included a well-baby program. Health benefits included wellness and diabetes education

programs, medical and long-term disability insurance, and on-site medical and physical therapy


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treatment. Employee professional development was encouraged through an on-site company

college and a tuition reimbursement program. To support psychological well-being, Organization B

provided an employee assistance program. Finally, to help employees manage their time and

schedule demands, vacation, sick, and bereavement leaves were offered as were general leaves of

absence. In addition, the organization provided an on-site cafeteria.

Method

Sample

We collected multiple-source data using a voluntary employee questionnaire and a supervisor

evaluation of employee task and contextual performance. A random sample of 1000 employees was

selected from each organization. Code numbers were used to match returned employee questionnaires

with corresponding supervisor evaluations. Employees from Organization A received the survey via

internal mail and were allowed to complete the questionnaire during work hours. Organization A also

reminded employees of the survey deadline with posters throughout the organization, an article in the

organization newsletter, and announcements at departmental meetings. There were 54 surveys returned

as undeliverable in organization A due to employees’ being on vacation or having terminated their

employment with the organization. Employee questionnaires were sent directly to employees’ homes

in Organization B where employees completed them on their personal time. All employee surveys were

deliverable in Organization B. Response rates were 57 per cent (539 completed surveys) for

Organization A and 31 per cent (313 completed surveys) for Organization B.

Respondents from Organization A, were 83 per cent female, 68 per cent White, 27 per cent Black,

51 per cent under the age of 40, and 54 per cent had been with the organization 5 years or less.

Participants from Organization B were 84 per cent male, 87 per cent White, 12 per cent Black, 74 per

cent 40 or older and 60 per cent had been with the organization for 20 years or more. We compared

respondents from each organization with data available for all employees on race and gender, to test for

non-response bias. Females were more likely to respond in Organization A (85 per cent of respondents

versus 78 per cent of the employee population) [x2 (1, N¼ 535)¼ 8.97, p< .01]. Whites were more

likely to respond in Organization B (87 per cent of respondents versus 73 per cent of the employee

population) [x2 (3, N¼ 311)¼ 32.42, p< .01], and females were also more likely to respond (16 per

cent of respondents versus 11 per cent of the employee population) [x2 (1, N¼ 311)¼ 8.19, p< .01]. In

sum, men were underrepresented in both organization samples, and Blacks were underrepresented in

the Organization B sample.

Supervisor evaluation surveys were distributed via internal mail in both organizations to supervisors

of those employees who returned their surveys. A total of 457 supervisor surveys were returned from

Organization A and 263 from Organization B for response rates of 85 per cent and 84 per cent,

respectively. Following Goodman and Blum’s (1996) procedure for assessing non-random sampling, to

test for response bias from the supervisors, multinomial logistic regression analysis was performed on

the data from each organization regressing employee provided measures of benefit use, benefit value,

POS, and affective commitment on a dichotomous variable representing a completed supervisor

evaluation (1¼ yes). The results revealed only benefit use for Organization B had a significant

regression coefficient, indicating supervisors from Organization B were more likely to complete a

performance evaluation for employees who used their benefits more. However, given that the


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180 L. MUSE ET AL.

supervisors were not aware of how frequently employees used most of their benefits, it is unlikely that

this issue led to non-response bias.

Measures

Use of work-life benefits

Use of work-life benefits was measured by asking employees ‘How often have you or your family used

each benefit listed below during your employment with the company?’ The benefits listed were specific

to those offered by the organization (15 benefits were included for Organization A and 14 for

Organization B; refer to the previous description of the organizations in the ‘Organization Context’

sidebar for a listing). A 5-point response scale was used ranging from 1¼ ‘never,’ to’ 5¼ ‘many times.’

We expanded the more commonly used dichotomous ‘have used’ or ‘have-not-used’ measure (e.g.,

Lambert, 2000) to account for the degree of use of the benefits offered in the package, using an average

as an index measure of benefit use in the analyses.

Perceived value of work-life benefitsPerceived value of work-life benefits was assessed by employees with a measure similar to the one used

by Haar and Spell’s (2004). Haar and Spell asked respondents to indicate ‘How valuable is [this

work-family practice] to you’ on a 5-point scale (1¼ no value; 5¼ invaluable). To make sure that

respondents were considering the potential future value of the benefit as well as its present value, we

asked: ‘How valuable do you think each of the benefits below is or could be in the future to you and your

family?’ followed by a list of all benefits offered. Concerned that respondents may inaccurately

interpret ‘invaluable’ as the prefix ‘in’ can often be interpreted as ‘not’ (as in ‘incorrect’), we employed

a response scale that ranged from 1¼ ‘not valuable at all’ to 5¼ ‘very valuable.’ An index was created

by averaging across all benefit value items.

Perceived organizational support (POS)

Consistent with prior POS research (Lynch, Eisenberger, & Armeli, 1999; Settoon et al., 1996), an

eight-item shortened version of the POS scale developed by Eisenberger et al. (1986) was completed by

employees. Example items include, ‘Help is available from my company when I have a problem’ and

‘My company really cares about my well-being,’ anchored at 1¼ ‘strongly disagree’ and 5¼ ‘strongly

agree’ (a¼ .93 for both organizations).

Affective commitment

Employee affective commitment was measured using a six-item scale developed by Meyer and Allen

(1991). Example items anchored at 1¼ ‘strongly disagree’ and 5¼ ‘strongly agree’ include, ‘I feel

emotionally attached to this company’ and ‘I feel a strong sense of belonging to this company’ (a¼ .89

for both organizations).

Task performanceSupervisors assessed the task performance of employee respondents using a seven-item scale

(Williams &Anderson, 1991) anchored at ‘1¼ strongly disagree’ to ‘5¼ strongly agree.’ Sample items

include ‘Fulfills responsibilities specified in job description’ and ‘Performs tasks that are expected of

him/her’ (a¼ .96 for Organization A and a¼ .94 for Organization B).

Contextual performance

Supervisors assessed employee contextual performance using a 15-item scale developed by Van Scotter

et al. (2000). Supervisors were asked, ‘How likely is this person to do the following’: with responses


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anchored at ‘1¼ unlikely’ to ‘5¼ extremely likely.’ Examples from the interpersonal facilitation

subscale include ‘Praise co-workers when they are successful.’ and ‘Treat others fairly.’ Examples from

the job dedication subscale are ‘Work harder than necessary.’ and ‘Take the initiative to solve a work

problem.’ (a¼ .93 and .94 for interpersonal facilitation and job dedication respectively for both

organizations).

Control variables

In their review of antecedents of pay satisfaction, Miceli and Lane (1991) suggested both age and

gender were related to perceptions of benefits. Since that time, researchers have found age to be related

to benefit satisfaction (Judge, 1993) and perceptions of benefits (Williams, 1995). Research has also

reported a relationship between gender and benefit use (Lambert, 2000; Thompson, Beauvais, &

Lyness, 1999) and perceptions of benefits (Lambert, 2000). In their meta-analysis, Judge, Thoreson,

Bono, and Patton (2001) found both organizational and job tenure to have a significant relationship with

job performance. Based on these findings, organizational tenure, job tenure, age and gender as reported

by employees were used as control variables. To allay respondents’ potential concerns about the

anonymity of their responses, the tenure and age variables were categorical in nature. Organizational

and job tenure was assessed using six ordinal categories (less than 1 year, 1–5 years, 6–10 years, 11–

15 years, 16–20 years, and greater than 20 years). Agewas assessed with seven ordinal categories (<21,

21–29, 30–39, 40–49, 50–59, 60–69, and 70 and older). Gender was assessed dichotomously

(female¼ 1; male¼ 0).

Analyses

A two-step modeling approach recommended by Anderson and Gerbing (1988) was used along with

the multigroup method as described by Vandenberg (2002). Two-step modeling entails assessing the

factor structure prior to estimating the structural paths to avoid the interaction of the measurement

and structural models (Hair, Anderson, Tatham, & Black, 1995). Each organization’s data were kept

separate and the models, first the measurement followed by the structural, were fit to the data

simultaneously to apply the multigroup method. First, separate confirmatory factor analyses were

performed on each organization’s data. Second, to identify if the factor structure was consistent across

both organizations, the measurement model was fit to the data. Next to test the hypotheses and

determine if the paths were invariant in both organizations, the structural model was fit to the data.

Mediation testing procedures by Kenny, Kashy, and Bolger (1998) were used to test all hypothesized

mediated relationships contained in the structural model. Finally, a fully latent model was examined to

identify any potential detriment of using latent indicators in the structural model.

Measurement model

The confirmatory factor analyses for all measures except benefit use and benefit value (index measures)

identified five distinct and unidimensional constructs for both datasets with strong factor loadings (all

items were significant on their intended construct at p< .001). The model fit the data of both

organizations well; root mean square error adjusted (RMSEA)¼ .06 and comparative fit index

(CFI)¼ .98. Researchers have suggested RMSEAvalues less than .08, and CFI values greater than .90

indicate a good fit (Hoyle, 1995). Descriptive statistics for control and model variables are presented in

Table 1 for Organization A and in Table 2 for Organization B.


DOI: 10.1002/job

Table

1.Means,standarddeviations,coefficientalphas,andintercorrelationsfororganizationA

Variables

MSD

12

34

56

78

910

11

1.Organizational

tenure

a1.85

1.41

2.Jobtenure

a1.46

1.17

.77

3.Gender

b0.85

0.35

.07

�.01

4.Agec

3.41

1.15

.45

.36

.04

—5.Benefituse

2.16

0.70

.47

.35

.06

.12

—6.Benefitvalue

3.95

0.75

�.06

�.09

.05

�.15

.22

—7.Perceived

organizational

support

3.44

0.77

�.06

�.07

.02

.07

.04

.22

(.93)

8.Affectivecommitment

3.54

0.81

.13

.07

.05

.20

.19

.22

.71

(.89)

9.Taskperform

ance

4.30

0.55

.14

.04

.06

.15

.12

.07

.13

.11

(.96)

10.Jobdedication

3.96

0.75

.06

�.03

.02

.05

.08

.05

.14

.12

.75

(.94)

11.Interpersonal

facilitation

4.00

0.73

.05

�.03

.05

.09

.04

.06

.18

.16

.62

.79

(.93)

Note:Coefficientalphas

arelisted

inparenthesisonthediagonal.WithN¼457andnon-directional

testscorrelationsof.09–.11aresignificantat

p<.05;correlations�.12are

significantat

p<.01.

aTenure

variablesweremeasuredusingsixcategories

(0¼less

than1year,1¼1–5years,2¼6–10years,3¼11–15years,4¼16–20years,5¼greaterthan20years).

bGender

was

coded

as0¼male;1¼female.

cAgewas

measuredusingseven

categories

(1�21,2¼21–29,3¼30–39,4¼40–49,5¼50–59,6¼60–69,7¼70andolder).


DOI: 10.1002/job

182 L. MUSE ET AL.

Table

2.Means,standarddeviations,coefficientalphas,andintercorrelationsforOrganizationB

Variables

MSD

12

34

56

78

910

11

1.Organizational

tenure

a4.18

1.85

2.Jobtenure

a2.50

1.72

.58

3.Gender

b0.15

0.36

�.34

�.17

4.Agec

4.11

1.00

.77

.52

�.12

5.Benefituse

2.17

0.48

.25

.13

.09

.23

—6.Benefitvalue

3.96

0.73

�.15

�.17

.20

�.08

.22

—7.Perceived

organizational

support

3.28

0.83

�.08

�.11

.12

.03

.04

.31

(.93)

8.Affectivecommitment

3.69

0.78

.04

�.02

.07

.13

.11

.24

.72

(.89)

9.Taskperform

ance

4.18

0.67

.02

�.02

.01

.02

.00

�.06

.14

.17

(.94)

10.Jobdedication

3.97

0.83

�.11

�.06

.13

�.11

.04

�.04

.21

.24

.69

(.94)

11.Interpersonal

facilitation

3.92

0.83

�.16

�.10

.18

�.12

.03

.05

.24

.25

.50

.81

(.93)

Note:Coefficientalphas

arelisted

inparenthesis

onthediagonal.WithN¼263andnon-directional

testscorrelationsof.13–.15aresignificantat

p<.05;correlations�.16are

significantat

p<.01.

aTenure

variablesweremeasuredusingsixcategories

(0¼less

than1year,1¼1–5years,2¼6–10years,3¼11–15years,4¼16–20years,5¼greaterthan20years).

bGender

was

coded

as0¼male;1¼female.

cAgewas

measuredusingseven

categories

(1�

21,2¼21–29,3¼30–39,4¼40–49,5¼50–59,6¼60–69,7¼70andolder).


DOI: 10.1002/job


Table 3. Multigroup method analysis goodness-of-fit tests for measurement and structural models

Model x2 df p x2/df CFI TLI RMSEA

Measurement models Null model 23 857.41 1332.00 0.00 17.91 0.00 0.00 0.15No constraints 2763.36 1168.00 0.00 2.37 0.93 0.92 0.04Factor loadings constrained 2821.34 1199.00 0.00 2.35 0.93 0.92 0.04Covariances constraineda 2834.57 1209.00 0.00 2.34 0.93 0.92 0.04Structural models Null model 3166.43 132.00 0.00 23.99 0.00 0.00 0.18No constraints 23.51 20.00 0.26 1.18 0.99 0.99 0.02Structural paths constrained 31.73 27.00 0.24 1.18 0.99 0.99 0.02

aFactor loadings also constrained.

184 L. MUSE ET AL.

Multigroup analysis

Following Byrne’s advice (2004) on testing for multigroup invariance, three models were run to determine

if the factor structure was invariant across both organizations: (a) a model without constraints fitting the

data to both organizations, (b) a model constraining the factor loadings to be equal across both

organizations, and (c) a model constraining the factor loadings and the covariances between factors to be

equal across both organizations. Model results are presented in Table 3. The unconstrained model fit the

data well (CFI¼ .93, TLI¼ .92, RMSEA¼ .04), therefore this model was the baseline model to which

subsequentmodels were compared. Experts suggest invariance has been achievedwhen themodel fit of the

successive models does not significantly deteriorate (Taris, Bok, & Meijer, 1998). Given Chi-square

differences are sample size dependent (Brannick, 1995), researchers have suggested using alternative fit

indices (Hu & Bentler, 1998). Specifically, Cheung and Rensvold (2002) found DCFI��0.01 to be a

robust indicator of equivalence across groups. Accordingly, we employed the DCFI critical value in our

multigroupmethod testing.When compared to the baselinemodel, both the factor loadings and covariance

constrainedmodels held constant at a CFI value of .93. In addition, other fit indices indicate bothmodels fit

the data equally well (TLI¼ .92, RMSEA¼ .04). Based on these findings we concluded invariance was

achieved and the factors were consistent across both organizations.

Structural model

Manifest indicators were created in both datasets for each latent variable by averaging the items for

each scale (Kenny, 1979). Error variances for all scales were constrained to the product of one minus

the reliability of the scale and its variance (Joreskog & Sorbom, 1982). Each of the four control

variables (organizational tenure, job tenure, age, and gender) were allowed to co-vary with each other

and had a path to benefit use, benefit value, POS, affective commitment, task performance,

interpersonal facilitation and job dedication. Similar to the logic of testing the measurement model, two

models were compared:(a) a model without constraints, fitting the data to both organizations and (b) a

model constraining the structural paths to be equal across both organizations (Byrne, 2004).

Results

Estimation of the hypothesized model

Results examining the hypothesized model are presented in Table 3; the fit of the unconstrained and

constrained models was identical (a2/df¼ 1.18, CFI¼ .99, TLI¼ .99, and RMSEA¼ .02), indicating


DOI: 10.1002/job


the structural model was invariant between the two organization samples. All hypothesized paths,

except two (H:1b no support; H:3b partial support) were fully supported. Benefit use as hypothesized

(H:1a), had a direct effect on affective commitment (b¼ .15 p< .001) but contrary to H1b did not also

have an indirect relationship mediated through POS.

Mediation testing procedures by Kenny et al. (1998) were employed to test Hypothesis 2 (Perceived

benefit value will have a positive relationship with affective commitment that is fully mediated through

POS.). Two alternative models were examined, one testing a direct relationship between perceived

benefit value and affective commitment constraining the path from benefit value to POS to zero, and a

second with the direct relationship plus an indirect relationship as mediated by POS. A significant

relationship between benefit value and affective commitment existing in the model without the

mediator, that becomes non-significant in the model with the mediator, indicates full mediation. The

model examining the direct relationship between benefit value and affective commitment indicated a

significant relationship (b¼ .08, p< .05), with a moderate fit with the data (CFI¼ .98, TLI¼ .89,

RMSEA¼ .06). The model allowing POS to mediate the relationship revealed that the relationship

between benefit value and affective commitment became non-significant (b¼ .06, p¼ .14) and

provided a good fit with the data (CFI¼ .99, TLI¼ .99, RMSEA¼ .02). Additionally, when compared

to the hypothesized model, a Chi-square difference test indicated a non-significant difference [x2 (1,

N¼ 720)¼ 2.73, ns], providing support for Hypothesis 2. Following Anderson and Gerbing (1988)

when a path is added to a hypothesized model, a non-significant difference in Chi-squares indicates the

additional paths do not significantly improve the model, thereby supporting the hypothesized model as

a better fit as it is more parsimonious.

Similarly, to test the mediated relationships of benefit use and performance in Hypotheses 3a

(affective commitment will fully mediate the positive relationship of benefit usewith task performance)

and 3b (affective commitment will fully mediate the positive relationships of benefit use with the

contextual performance dimensions of interpersonal facilitation and job dedication), two alternative

models were compared, one with direct relationships between benefit use and each of the performance

variables (task performance, interpersonal facilitation, and job dedication) constraining the path from

benefit use and affective commitment to zero, and a second with the mediated relationships added. The

first model showed direct relationships from benefit use to two of the three performance variables were

significant (btask performance¼ .08, p< .05; binterpersonal facilitation¼ .03, ns; bjob dedication¼ .06, p< .05)

and fit the data well (CFI¼ .99, TLI¼ .94, RMSEA¼ .04). The model allowing affective commitment

to mediate the relationships revealed that those that were significant without the mediator became

non-significant with the mediator (btask performance¼ .06, p¼ .33; binterpersonal facilitation¼ .01, p¼ .83;

bjob dedication¼ .04, p¼ .48). Additionally, when compared to the hypothesized model, a Chi-square

difference test indicated a non-significant difference [x2 (3,N¼ 720)¼ 2.53, ns], providing full support

for hypothesis 3a and partial support for 3b.

The same procedure described above was used to test the mediated relationships of POS and

performance in Hypotheses 4a (affective commitment will fully mediate the positive relationship of

POS with task performance) and 4b (affective commitment will fully mediate the positive relationships

of POS with the contextual performance dimensions of interpersonal facilitation and job dedication).

The first model without the mediation included showed that direct relationships from POS to each of

the performance variables were significant (btask performance¼ .13, p< .01; binterpersonal facilitation¼ .19,

p< .001; bjob dedication¼ .15, p< .01) and fit the data well (CFI¼ .99, TLI¼ .99, RMSEA¼ .01). The

model allowing affective commitment to mediate the relationships revealed that the relationship

between POS and all three performance variables became non-significant (btask performance¼ .13,

p¼ .08; binterpersonal facilitation¼ .15, p¼ .06; bjob dedication¼ .11, p¼ .15). Additionally, when compared

to the hypothesized model, a Chi-square difference test indicated a non-significant difference [x2 (3,

N¼ 720)¼ 5.06, ns], fully supporting the hypothesized meditated relationships in H4a and b.


DOI: 10.1002/job

186 L. MUSE ET AL.

Taken together, the analyses supported our hypothesized model, with the exceptions of the indirect

path linking benefit use to affective commitment through POS and the mediated relationship of benefit

use and job dedication by affective commitment. A fully latent model was also run for Organization A

to identify any potential problems from our use of manifest indicators rather than a fully latent model

(where all items for all variables are employed in the analyses). Due to its larger sample size,

Organization A (N¼ 457 versusN¼ 263) was better able to support a fully latent model. Results of this

model mirrored those of the final constrained structural model, with very little changes in path

coefficients and no change in their significance level, suggesting that using manifest indicators did not

influence our results. The hypothesized model with resulting path coefficients and associated

significance levels from the multigroup constrained model are shown in Figure 2.

Discussion

This study contributes to the POB and employee benefits research in four primary ways. First and

foremost, we contribute to integrating POB’s emphasis on employee well-being and employee benefits

literature by providing empirical evidence that work-life benefits are directly associated with affective

commitment and indirectly to important work behaviors. Second, our findings clarify the differential

paths that benefit use and perceived benefit value take in their relationships with affective commitment.

Third, the significant relationship between benefit value and POS provides additional empirical support

to that provided by Lambert (2000) countering previous beliefs that employee benefits cannot be

related to POS (Shore & Shore, 1995;Wayne et al., 1997). Lastly, this research works toward answering

the calls to investigate the impact of work-life benefits in the workplace (Casper & Buffardi, 2004; Eby

et al., 2005; Kossek & Ozeki, 1998; 1999).

Figure 2. Multigroup method analysis results. Structural paths constrained to be equal across organizations. Allnumbers reflect standardized path coefficients. Organization A N¼ 457, Organization B N¼ 263. NS¼ not

significant,�p< .05,

��p< .01,��p< .001. All tests are one-tailed


DOI: 10.1002/job


Work-life benefits and positive organizational behavior

This study contributes to bridging the gap between POB research and the employee benefits literature.

Contrary to the results reported by Haar and Spell (2004), our results strongly suggest that providing

work-life benefits that employees use and value engenders positive affective commitment to the

organization. Consistent with Lambert (2000), we found that benefit use and perceived value were

positively associated with important work behaviors. However, we extend Lambert’s work by

providing evidence that these relationships are best considered indirect and mediated through affective

commitment. Through this enhanced emotional attachment to the organization, use and perceived

value of benefits indirectly are associated with higher levels of task and contextual performance

behaviors. The performance outcomes can be partially explained by balance theory (Heidner, 1958)

which indicates that a need for a balance between employee attitudes and behaviors would lead

employees to exert more effort in their performance and pro-social behaviors once they felt more

emotionally attached to the organization. Our findings are also consistent with the strategic human

resource management literature (Arthur, 2003; Mello, 2006) that suggests that caring for employees’

well-being and corporate profitability may not be as mutually exclusive as was once thought.

Distinction between benefit use and perceived value

Another compelling finding of this study is the importance of drawing a clear distinction between

benefit use and perceived benefit value. Consistent with Lambert (2000) and Haar and Spell (2004), our

measures of benefit use and perceived benefit value were only moderately correlated (r¼ .22 in both

organizations). Benefit use and perceived value were also found to have differential paths to affective

commitment. The results support a direct relationship between benefit use and affective commitment

accounting for 2 per cent of the variance in affective commitment. In contrast, perceived benefit value’s

relationship with affective commitment accounted for 6.5 per cent of the variance in affective

commitment but was entirely mediated through POS. Benefit use’s relationship to affective

commitment was not mediated through POS. It seems that because employees are receiving something

tangible resulting from their use of benefits, they are likely to directly reciprocate with affective

commitment to the granting organization. However, perceived value is less tangible than benefit use; it

informs broader judgments of POS that in turn encourage affective commitment.

Our findings extend the results of Grover and Crooker (1995) who found the availability of flex-time,

maternity/paternity leave and childcare (regardless of use) was associated with strong emotional

attachment to the organization. Our study focused on the perceived value of a broader group of benefits

and identifies the importance of how these benefits are perceived by employees. The differential

relationships of benefit use and perceived benefit value found in this study can be explained by POB,

social exchange theory, and the norm of reciprocity. The results suggest that benefits do not need to be

used to be valued. For example, a cancer plan and employee-in-crisis program are two benefits

employees are likely to value but hope to not actually use. Benefits that are used satisfy employee needs

and thus influence the employee–employer relationship by motivating these employees to reciprocate.

Benefit value and POS

The link between perceived benefit value and POS is consistent with Lambert (2000) and contradicts

arguments that employee benefits do not signal to employees they are valued and are therefore not

related to POS (Shore & Shore, 1995; Wayne et al., 1997). Our findings are consistent, however, with


DOI: 10.1002/job

188 L. MUSE ET AL.

suggestions that organizations can communicate employee value by offering benefits that assist

employees with meeting multiple demands, such as childcare, counseling, and time off for emergencies

(Lynch et al., 1999). The results found in this study across two distinctly different organizations,

indicate employee perceptions of work-life benefits can indeed signal to employees that the

organization values and supports them and cares about their well-being. Whereas benefits viewed as

valuable may not have been used, and may have not yet satisfied a need, they serve as a signal of caring

by the organization (i.e., POS). It is this feeling that the organization cares for the employees that

initiates the reciprocation process.

Impact of work-life benefits in the workplace

Finally, this research begins to identify and explain the impact of work-life benefits in the workplace.

To date, this is the only study examining relationships among work-life benefit use, work-life benefit

value, POS, affective commitment, and task and contextual performance collectively in the same

model. Luthans (2002) charged that ‘POB must go beyond mere employee selection’ (p. 699). This

study provides evidence that work-life benefits are one way of meeting that goal. Our findings extend

those of Casper and Buffardi (2004) who linked perceptions of work-life benefits to company

attractiveness and job pursuit intentions. Results of this study suggest that the positive influence of

work-life benefits does not end with recruiting but continues during employment. Our results are also

consistent with Allen (2001) who argued that simply offering family-friendly benefits is not enough;

the culture must be supportive of the programs so that employees perceive the benefits positively and

feel comfortable using them. Further examining employee perceptions of benefit programs is important

because the results of this study suggest that valued work-life benefits, regardless of their current or past

use, are positively associated with important employee attitudes and behaviors in the workplace.

Practical applications

The results of this study have important implications to organizations and practicing human resource

managers. When deciding which benefits to offer, organizations frequently follow a strict utilitarian

approach giving costs and benefits offered by competitors’ careful consideration (Lawler, 1990). Our

findings suggest a more balanced approach including an assessment of employees’ perceptions of

benefit value as a critical part of the decision making process. Suggestions for conducting such an

analysis include personal interviews, focus groups, and survey questionnaires. Questions might include

‘What benefits are most important to you?’, ‘If you were given X dollars for benefits, how would you

spend them?’ (Noe, Hollenbeck, Gerhart, &Wright, 2003), and ‘How valuable do you think each of the

following benefits are?’ By providing work-life benefits that are valued, employers can send a message

to employees that the company cares about their well-being and supports them. The resulting employee

perceptions of organizational support should motivate employees to reciprocate. Employees can fulfill

their desire to reciprocate by becoming more emotionally attached to the organization and enhancing

their performance of both job-related duties and behaviors that support the organization as a whole (i.e.,

job dedication and interpersonal facilitation).

Limitations

The cross-sectional nature of the data collected is one limitation of this study which prevents the

examination of causal relationships. Although other variable orders cannot be eliminated, applying


DOI: 10.1002/job


Fishbein and Ajzen’s (1975) theory of reasoned action suggests the order of the variables in our model

is theoretically reasonable. Studies collecting longitudinal data, both before and after work-life benefits

are implemented, are needed to further examine the direction of these benefits’ relationships with

employee attitudes and behaviors.

Another limitation is the possibility that the relationships reported might be affected by other,

non-assessed variables that are potential ‘third variable contaminants,’ because of their relationships

with the measured variables. For example, in their meta-analysis Rhoades and Eisenberger (2002)

identified supervisor support as the second strongest antecedent of POS. Research has also revealed a

correlation between supervisor support and benefit use (Thompson et al., 1999), and perceptions of

benefits (Allen, 2001). Additionally, positive and negative affect has been linked to several variables

contained in this study: perceptions of benefits (Williams, 1995), POS (Rhoades & Eisenberger, 2002),

affective commitment (Cropanzano, James, & Konovsky, 1993), and performance (Baumann & Kuhl,

2002; Cropanzano et al., 1993). Studies including these variables as well as others that could be third

variable contaminants would be helpful in solidifying the exact nature of the relationships in this study.

Generalizability of the results is another limitation of this study. Men were underrepresented in both

organizations, and Blacks were underrepresented in Organization B. Therefore, more research is

needed to determine if the results could be generalized to more diverse workforces. Additionally,

studies exploring other avenues for building POB in the workplace would be fruitful in understanding

this new area of research. Future research comparing the relationship of benefit use with other types of

commitment (continuance and normative commitment) similar to Haar and Spell (2004) would also

provide a valuable contribution. Moreover, future research examining different conceptualizations of

benefit use and perceived benefit value, as well as exploring additional antecedents and consequences,

would shed light on their surrounding nomological net.

Conclusion

In sum, the results of this study suggest that providing work-life benefits that employees use and/or

value is part of a positive exchange between the employee and employer, whereby both parties can

benefit. Our findings emphasize the importance to organizations in assessing employees’ perceived

value of benefits when making decisions concerning these programs. Work-life benefits can send a

message of caring for employees’ well-being that can have positive consequences in the workplace for

both the employee and the employer. Our findings suggest work-life benefits and POB are connected

and contribute to the research on both POB and employee benefits and also provide practical insight to

organizations interested in creating a positive climate for employees.

Author biographies

Lori Muse is an Associate Professor of Management at California State University, Fullerton. Her

primary research interest focuses on the employee–employer relationship, including work-family

conflict and work-life benefits.

Stanley G. Harris is the Torchmark Professor of Management at Auburn University and Faculty

Director of the Physician’s Executive MBA Program and the Management Ph.D. program concen-

tration in Organizational Studies, Strategy, and Change.


DOI: 10.1002/job

190 L. MUSE ET AL.

William F. Giles received his Ph.D. in Industrial/Organizational Psychology from the University of

Tennessee and teaches various courses in human resource management at Auburn University. His

primary research interest is performance appraisal, with secondary interests in training and selection.

His research has been published in journals such as Journal of Applied Psychology, Academy of

Management Journal, and Personnel Psychology.

Hubert S. Feild is Torchmark Professor of Management in the College of Business at Auburn

University. His professional interests include human resource selection and research methods in human

resource management.

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Work-Life Benefits and Positive Organizational Behavior