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How Does Human Resource Management Influence Organizational Outcomes? A Meta-Analytic Investigation of Mediating Mechanisms

December 2012
Academy of Management Journal 55(6):1264-1294

DOI:10.5465/amj.2011.0088

Authors:

Kaifeng Jiang

The Ohio State University

David P. Lepak

University of Massachusetts Amherst

Jia Hu

University of Notre Dame

Judith C Baer

Rutgers, The State University of New Jersey

Drawing on the ability-motivation-opportunity model, this meta-analysis examined the effects of three dimensions of HR systems-skills-enhancing, motivation-enhancing, and opportunity-enhancing-on proximal organizational outcomes (human capital and motivation) and distal organizational outcomes (voluntary turnover, operational outcomes, and financial outcomes). The results indicate that skill-enhancing practices were more positively related to human capital and less positively related to employee motivation than motivation-enhancing practices and opportunity-enhancing practices. Moreover, the three dimensions of HR systems were related to financial outcomes both directly and indirectly by influencing human capital and employee motivation as well as voluntary turnover and operational outcomes in sequence.

Meta-analytic Correlations between HR Dimensions and Organizational Outcomes a

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Effects of HPWS on Organizational Outcomes a

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HOW DOES HUMAN RESOURCE MANAGEMENT INFLUENCE

ORGANIZATIONAL OUTCOMES?

A META-ANALYTIC INVESTIGATION OF

MEDIATING MECHANISMS

KAIFENG JIANG

DAVID P. LEPAK

Rutgers, the State University of New Jersey

JIA HU

University of Notre Dame

JUDITH C. BAER

Rutgers, the State University of New Jersey

Drawing on the ability-motivation-opportunity model, this meta-analysis examined the

effects of three dimensions of HR systems—skills-enhancing, motivation-enhancing,

and opportunity-enhancing—on proximal organizational outcomes (human capital

and motivation) and distal organizational outcomes (voluntary turnover, operational

outcomes, and financial outcomes). The results indicate that skill-enhancing practices

were more positively related to human capital and less positively related to employee

motivation than motivation-enhancing practices and opportunity-enhancing practices.

Moreover, the three dimensions of HR systems were related to financial outcomes both

directly and indirectly by influencing human capital and employee motivation as well

as voluntary turnover and operational outcomes in sequence.

In the past two decades, researchers in strategic

human resource management (HRM) have exam-

ined why and how organizations achieve their

goals through the use of human resource (HR) prac-

tices. Although traditional HRM research has fo-

cused on the impact of individual HR practices, the

strategic perspective on HRM research emphasizes

bundles of HR practices, often referred to as high-

performance work systems (HPWS), high-involve-

ment work systems, and high-commitment work

systems, in examinations of the effects of HRM on

employee and organizational outcomes (Wright &

McMahan, 1992). A burgeoning body of strategic

HRM research has shown that the use of systems

of HR practices intended to enhance employees’

knowledge, skills, and abilities, motivation, and

opportunity to contribute is associated with posi-

tive outcomes such as greater commitment (Gong,

Law, Chang, & Xin, 2009), lower turnover (Batt,

2002), higher productivity and quality (MacDuffie,

1995), better service performance (Chuang & Liao,

2010), enhanced safety performance (Zacharatos,

Barling, & Iverson, 2005), and better financial per-

formance (Huselid, 1995).

Despite the robust evidence for the positive rela-

tionships between HRM and various organizational

outcomes (Combs, Liu, Hall, & Ketchen, 2006), im-

portant issues remain regarding the mechanisms

through which HRM is associated with different

organizational outcomes. First, the theoretical logic

underlying the mechanisms linking HRM and

organizational outcomes remains fragmented

(Huselid & Becker, 2011; Wright & Gardner, 2003).

Specifically, some researchers have adopted a be-

havioral perspective to suggest that HR practices

affect organizational outcomes by influencing em-

ployee role behaviors; if employees act in ways that

are consistent with company goals, performance

should improve. Other researchers have adopted

more of a human capital and resource-based per-

spective, focusing on the potential contributions of

employees’ competencies—that is, their knowl-

edge, skills, and abilities. Interestingly, although

employees contribute through both their competen-

cies and their actions, researchers have typically

focused on one perspective to understand how HR

We thank the action editor for this article, Jason Shaw,

and three anonymous reviewers, Patrick McKay, Rebecca

Kehoe, and Mark Huselid for helpful comments and sug-

gestions. We acknowledge financial support from the

SHRM Foundation (Project No. 143). The interpretations,

conclusions, and recommendations are those of the au-

thors and do not necessarily represent those of the SHRM

Foundation.

娀Academy of Management Journal

2012, Vol. 55, No. 6, 1264–1294.

http://dx.doi.org/10.5465/amj.2011.0088

1264

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systems impact organizational outcomes (excep-

tions include Takeuchi, Lepak, Wang, and Takeu-

chi [2007]). Considering multiple perspectives

simultaneously provides a broader and more com-

plete picture of the relationship between HRM and

organizational outcomes.

Second, although prior research has demonstrated

the mechanism through which HRM relates to some

organizational outcomes, it remains unclear as to how

HRM relates to different organizational outcomes that

range from very proximal (i.e., HR outcomes) to more

distal (i.e., financial outcomes). This lack of integra-

tion is problematic given the different perspectives

adopted in the literature, perspectives that might

highlight the importance of different but potentially

related outcomes. Exploring the possible paths be-

tween HRM and financial outcomes will likely pro-

vide a more integrative model of how HR systems

operate to impact a multitude of related and impor-

tant outcomes (e.g., Becker & Huselid, 1998; Delery &

Shaw, 2001; Guest, 1997).

Third, it is assumed in existing research that the

components of HR systems have identical impacts

on outcomes. For example, when scholars adopt an

additive approach to measure HR systems, each

component of the system is treated as if it exerts an

equal influence on the outcomes under investiga-

tion. Although this is a possible reflection of how

HR systems operate, scholars have recently chal-

lenged this assumption and argued that different

sets of HR practices may impact the same outcomes

in a heterogeneous way (e.g., Batt & Colvin, 2011;

Gardner, Wright, & Moynihan, 2011; Gong et al.,

2009; Shaw, Dineen, Fang, & Vellella, 2009; Subra-

mony, 2009). As these studies have suggested, it is

important to explore the differential effects of the

different components of HR systems.

Given these issues, the primary objective of this

study is to develop an integrative model of the mech-

anisms mediating between HRM and organizational

outcomes through a meta-analytic approach. Drawing

on the behavioral perspective on HRM, human capi-

tal theory, and the resource-based view of the firm,

we aim to extend and refine existing HRM-organiza-

tional outcomes models by exploring multiple medi-

ating paths and differentiating among the effects of

subdimensions of HR systems.

THEORETICAL BACKGROUND AND

HYPOTHESES

Existing Theories and Research on Relationships

between HRM and Organizational Outcomes

Understanding the relationship between HRM

and organizational outcomes is one of the long-

standing goals of macro HRM research. Indeed,

Becker and Huselid (1998) considered this relation-

ship as one of the essential pursuits of strategic

HRM research. This stream of research has several

key components. First, organizational outcomes are

viewed as multidimensional. Drawing on Dyer and

Reeves’s (1995) work, researchers in strategic HRM

have categorized organizational outcomes into

three primary groups related to HRM: HR out-

comes, operational outcomes, and financial out-

comes. HR outcomes refer to those most directly

related to HRM in an organization, such as em-

ployee skills and abilities, employee attitudes and

behaviors, and turnover. Operational outcomes are

those related to the goals of an organizational op-

eration, including productivity, product quality,

quality of service, and innovation. Financial out-

comes reflect the fulfillment of the economic goals

of organizations. Typical financial outcomes in-

clude sales growth, return on invested capital, and

return on assets. In this study, we use “organiza-

tional outcomes” to refer to all three categories of

outcomes at the organizational level.

Second, strategic HRM research suggests that dif-

ferent types of outcomes may not necessarily have

equivalent relationships with HR practices (Becker

& Huselid, 1998; Delery & Shaw, 2001; Guest, 1997;

Lepak, Liao, Chung, & Harden, 2006; Ostroff & Bo-

wen, 2000). Moreover, it is commonly asserted that

HRM may influence the three types of organiza-

tional outcomes in sequence. For example, HR

practices are expected to first influence HR out-

comes (e.g., employee skills and motivation),

which are proximal and the least likely to be con-

taminated by factors beyond HR practices. HR out-

comes, in turn, may mediate the influence of HR

practices on productivity, quality, service, safety,

innovation, and other operational outcomes, which

further affect financial outcomes.

Although existing HR research often implies that

HR outcomes serve as a key mediator between HR

systems and key outcomes, the specific natures of

models of this meditation depend on the theoreti-

cal perspective researchers have adopted when ex-

amining this relationship. On the one hand, several

researchers have adopted the behavioral perspec-

tive of HRM (Jackson, Schuler, & Rivero, 1989).

According to this perspective, organizations do not

perform themselves, but instead use HR practices

to encourage productive behaviors from employees

and thus to achieve desirable operational and fi-

nancial objectives (Becker & Huselid, 1998). If an

organization requires efficient employees, for ex-

ample, its chosen HR practices and their effective-

ness would likely differ from those of an organiza-

tion that requires employees to be cooperative, to

2012 1265Jiang, Lepak, Hu, and Baer

focus on service, or to engage in some other critical

role behavior. The effectiveness of HR practices is

realized when employees act in ways that are

needed for implementing strategies and achieving

various business objectives.

On the other hand, some macro HRM researchers

have focused less on the behaviors of employees

and more on their competencies within organiza-

tions. Researchers taking on this perspective often

invoke human capital theory and the resource-

based view of the firm. Human capital theory em-

phasizes that human capital—the composition of

employee skills, knowledge, and abilities—is a cen-

tral driver of organizational performance when the

return on investment in human capital exceeds la-

bor costs (Becker, 1964; Lepak & Snell, 1999; Ploy-

hart & Moliterno, 2011). The resource-based view

provides additional insights as to why human cap-

ital can help firms to outpace competitors and pro-

poses that organizations obtain a competitive ad-

vantage from resources that are rare, valuable,

inimitable, and nonsubstitutable (Barney, 1991;

Mahoney & Pandian, 1992). Researchers have ar-

gued that human capital, especially high-quality

and/or organization-specific human capital, has the

potential to serve as a source of competitive advan-

tage (Wright, McMahan, & McWilliams, 1994). Or-

ganizations may use HR practices to create and

maintain valuable human capital, including both

generic and organization-specific human capital,

which in turns drives high operational and finan-

cial performance (Becker & Huselid, 1998; Delery &

Shaw, 2001; Ployhart & Moliterno, 2011; Snell &

Dean, 1992).

Although the behavioral perspective of HRM, hu-

man capital theory, and the resource-based view of

the firm let researchers adopt different angles to

look at the relationships between HR practices and

more distal outcomes, under all three perspectives

HR outcomes are viewed as a critical path from

HRM to operational and financial outcomes. Even

with this agreement, however, researchers have not

successfully combined multiple approaches to de-

lineate an overarching picture of how this path

unfolds. For example, most of the extant empirical

research has examined the influence of HR systems

on operational or financial performance either

through motivation-related variables (e.g., Chuang

& Liao, 2010; Collins & Smith, 2006; Gelade & Ivery,

2003; Gong et al., 2009; McClean & Collins, 2011;

Sun, Aryee, & Law, 2007) or through human capital

variables (e.g., Cabello-Medina, Lopez-Cabrales, &

Valle-Cabrera, 2011; Yang & Lin, 2009; Youndt &

Snell, 2004). Insights into each type of variable are

important yet insufficient to fully capture the pro-

cess linking HRM to outcomes. Thus, research is

needed to explore how HRM can help organiza-

tions achieve financial goals through multiple

paths (Takeuchi et al., 2007).

Decomposing HR Systems into

Three HR Dimensions

Scholars have recently argued that although em-

ployees are exposed to HR systems rather than in-

dividual practices, the parts of these systems are

not necessarily equivalent in their impact. Most

research has portrayed an HR system as an additive

index of a set of individual HR practices (Combs et

al., 2006); there are reasons to believe, however,

that the highly varied set of HR practices can be

categorized into several subdimensions. Indeed,

dividing HR systems into subdimensions is not

new in strategic HRM research. For example, draw-

ing on an employee-organization relationship

framework (Tsui, Pearce, Porter, & Tripoli, 1997),

researchers have argued that HR practices may be

categorized as falling into HRM inducement and

investment practices, and HRM expectation-

enhancing practices (e.g., Batt & Colvin, 2011; Gong

et al., 2009; Shaw et al., 2009; Shaw, Delery, Jen-

kins, & Gupta, 1998; Shaw, Gupta, & Delery, 2005).

The first two types are designed to improve em-

ployees’ expected outcomes, whereas the third type

reflects organizations’ expectations about employ-

ees’ contributions.

Taking a different approach, some researchers

have drawn upon the ability-motivation-opportu-

nity (AMO) model of HRM and suggested that em-

ployee performance is a function of three essential

components: ability, motivation, and opportunity

to perform. Extending this logic, HR systems de-

signed to maximize employee performance can be

viewed as a composition of three dimensions in-

tended to enhance employee skills, motivation, and

opportunity to contribute, respectively (Appel-

baum, Bailey, Berg, & Kalleberg, 2000; Bailey, 1993;

Boxall & Purcell, 2008; Delery & Shaw, 2001; Ger-

hart, 2007; Katz, Kochan, & Weber, 1985; Lepak et

al., 2006). Recently, several empirical studies have

adopted and validated this conceptual framework

(e.g., Bailey, Berg, & Sandy, 2001; Batt, 2002; Gard-

ner et al., 2011; Huselid, 1995; Kehoe & Wright, in

press; Liao, Toya, Lepak, & Hong, 2009; MacDuffie,

1995; Subramony, 2009).

In keeping with these studies, Lepak and col-

leagues (2006) suggested that it might be fruitful to

conceptualize HR practices as falling into one of

three primary dimensions: skill-enhancing HR

practices, motivation-enhancing HR practices,

and opportunity-enhancing HR practices. Skill-

enhancing HR practices are designed to ensure ap-

1266 DecemberAcademy of Management Journal

propriately skilled employees; they include com-

prehensive recruitment, rigorous selection, and

extensive training. Motivation-enhancing HR prac-

tices are implemented to enhance employee moti-

vation. Typical ones include developmental perfor-

mance management, competitive compensation,

incentives and rewards, extensive benefits, promo-

tion and career development, and job security. Op-

portunity-enhancing HR practices are designed to

empower employees to use their skills and motiva-

tion to achieve organizational objectives. Practices

such as flexible job design, work teams, employee

involvement, and information sharing are generally

used to offer these opportunities. The use of the

three dimensions of HR systems instead of a unidi-

mensional or two-dimensional framework is based

on an examination of differential effects of the three

dimensions of HR systems on different types of HR

outcomes.

Linking HR Dimensions to Multiple Outcomes

According to the ability-motivation-opportunity

model of HRM, HR outcomes can conceptually be

divided into human capital, motivation, and oppor-

tunity to contribute (Becker & Huselid, 1998; Del-

ery & Shaw, 2001; Guest, 1997), and human capital

and employee motivation are two of the most crit-

ical mediating factors that have been examined in

the literature (e.g., Gardner et al., 2011; Gong et al.,

2009; Liao et al., 2009; Sun et al., 2007; Takeuchi et

al., 2007; Youndt & Snell, 2004). In line with the

literature, we focus on the mediating roles of hu-

man capital and employee motivation. As previous

research suggests, human capital can be viewed as

a composition of employees’ knowledge, skills, and

abilities (Coff, 2002), and employee motivation re-

fers to the direction, intensity, and duration of em-

ployees’ effort (Campbell, McCloy, Oppler, & Sager,

1993), as manifested by positive work attitudes

(e.g., collective job satisfaction, commitment, per-

ceived organizational support) and work behaviors

(e.g., organizational citizenship behavior).

Although we anticipate that all three HR dimen-

sions are positively related to both human capital

and employee motivation, we also anticipate that

the three HR dimensions may play different roles in

building human capital and enhancing employee

motivation. We expect that, compared with moti-

vation-enhancing and opportunity-enhancing HR

practices, skill-enhancing HR practices will likely

have a stronger impact on human capital and a

weaker impact on employee motivation.

According to the ability-motivation-opportunity

framework, skill-enhancing HR practices can di-

rectly help to optimize the levels or types of em-

ployees’ skills and abilities. For example, recruit-

ment and selection practices are intended to insure

that employees have the skills needed for task per-

formance, and training and development may fur-

ther provide employees with organization-specific

skills with which to perform their work. Indeed,

Delaney and Huselid (1996) indicated that organi-

zations can enhance the skills of their workforces

both by hiring high-quality individuals and by im-

proving the level of skills in their current work-

forces. Relatedly, prior research shows that the use

of comprehensive selection and training practices

fostered employees’ collective human capital (e.g.,

Cabello-Medina et al., 2011; Takeuchi et al., 2007;

Yang & Lin, 2009; Youndt & Snell, 2004). Further-

more, research suggests that practices such as com-

petitive compensation, extensive benefits, and job

security may help attract capable employees and

retain them in organizations, and practices such as

work teams, employee involvement, and flexible

job design may provide employees with opportuni-

ties to share knowledge and to learn new skills.

However, the relationships between the other two

HR dimensions and human capital are seen as less

direct. Research has shown that practices from

these two dimensions were less positively related

to human capital than skill-enhancing HR practices

(Cabello-Medina et al., 2011; Yang & Lin, 2009).

Therefore, we propose the following:

Hypothesis 1a. Skill-enhancing HR practices

are positively related to human capital.

Hypothesis 1b. Motivation-enhancing HR prac-

tices are positively related to human capital.

Hypothesis 1c. Opportunity-enhancing HR

practices are positively related to human

capital.

Hypothesis 2a. Skill-enhancing HR practices

are more positively related to human capital

than motivation-enhancing HR practices.

Hypothesis 2b. Skill-enhancing HR practices

are more positively related to human capital

than opportunity-enhancing HR practices.

We also posit that the three dimensions of HR

systems are positively related to employee motiva-

tion to different degrees. First, investment in all

three HR dimensions generally indicates that organ-

izations value and support employees’ contribu-

tions. According to social exchange theory (Blau,

1964) and the norm of reciprocity (Gouldner, 1960),

employees who perceive an organization’s actions

toward them as beneficial may feel obligated to

reciprocate and be motivated to exert more effort at

work. More specifically, motivation-enhancing HR

2012 1267Jiang, Lepak, Hu, and Baer

practices (e.g., performance-based compensation,

incentives and benefit, promotion opportunities,

and job security) are more likely to provide em-

ployees with extrinsic motivation that links their

work efforts to external rewards. Practices such as

work teams, employee involvement, and flexible

job design help to generate employees’ intrinsic

motivation, which encourages them to seek out

challenges at work (Ryan & Deci, 2000). In addition,

skill-enhancing HR practices can enhance employ-

ees’ skills and abilities, which may help career

development and induce promotion opportunities

in their organizations (Tharenou, Saks, & Moore,

2007). However, the effect of skill-enhancing HR

practices on employee motivation is relatively in-

direct and likely to be contingent on the practices

in the other two HR dimensions. For example, even

though training can improve employees’ skills at

work, the increased skills may not necessarily lead

to promotion in their organization. Therefore, we

expect all three HR dimensions to be positively

associated with employee motivation and, com-

pared with the other two dimensions, skill-enhanc-

ing HR practices are less positively related to em-

ployee motivation. Recent empirical research that

examined the influence of three HR dimensions on

employee affective commitment (Gardner et al.,

2011) has also supported this reasoning. Therefore,

we hypothesize:

Hypothesis 3a. Skill-enhancing HR practices

are positively related to employee motivation.

Hypothesis 3b. Motivation-enhancing HR prac-

tices are positively related to employee

motivation.

Hypothesis 3c. Opportunity-enhancing HR

practices are positively related to employee

motivation.

Hypothesis 4a. Skill-enhancing HR practices

are less positively related to employee motiva-

tion than motivation-enhancing HR practices.

Hypothesis 4b. Skill-enhancing HR practices

are less positively related to employee motiva-

tion than opportunity-enhancing HR practices.

In addition to the direct effects of the three HR

dimensions on human capital and employee moti-

vation, we propose that human capital and em-

ployee motivation mediate the relationships be-

tween the three HR dimensions and more distal

outcomes related to voluntary turnover (voluntary

organizational exit), operational outcomes, and

subsequent financial outcomes.

Several researchers have viewed voluntary turn-

over as a critical intermediate outcome that is dis-

tinct from human capital and employee motivation

(e.g., Batt, 2002; Batt & Colvin, 2011; Gardner et al.,

2011; Guthrie, 2001; Shaw et al., 1998, 2005, 2009;

Sun et al., 2007). Research has consistently demon-

strated that HR practices designed to enhance em-

ployee skills and motivation are significantly and

negatively associated with voluntary turnover (e.g.,

Arthur, 1994; Batt, 2002; Guthrie, 2001; Huselid,

1995). Some researchers attribute the negative rela-

tionships to the emotional bond between employ-

ees and organizations formed by HR practices. In

other words, because HR practices enhance em-

ployees’ motivation at work, these employees are

reluctant to leave their organizations (e.g., Gardner

et al., 2011; Sun et al., 2007). Investment in the

three aspects of HR systems implies that organiza-

tions value employees’ contribution and expect to

establish long-term employment relationships with

their employees. As a result, employees are encour-

aged to work harder to reciprocate and thus are less

prone to quit their jobs.

Human capital theory and the resource-based

view of the firm indicate that employees with ap-

propriate human capital resulting from HR invest-

ments may be less likely to leave their organiza-

tions. First, researchers have suggested that

employees with high levels of human capital are

more capable of meeting job demands, receiving

positive performance appraisals, obtaining promo-

tions, and participating in decision making (Batt &

Colvin, 2011; Shaw et al., 2009). Therefore, com-

pared with those with less human capital, employ-

ees with higher levels of human capital will be less

likely to leave their organizations. In addition, em-

ployees with high levels of human capital are better

able to learn at work, which facilitates the devel-

opment of specific human capital (Ployhart & Mo-

literno, 2011). The accumulated specific human

capital may in turn reduce the likelihood employ-

ees leave, because the specific human capital that is

unique and valuable for their current organization

may not provide value to other organizations (Bar-

ney, 1991; Lepak & Snell, 1999). Employees are

unable to obtain return on their input in developing

the specific human capital if they quit (Shaw et al.,

2005). Therefore, we hypothesize:

Hypothesis 5a. Human capital mediates the

negative relationships between the three di-

mensions of HR systems and voluntary

turnover.

Hypothesis 5b. Employee motivation mediates

the negative relationships between the three

dimensions of HR systems and voluntary

turnover.

1268 DecemberAcademy of Management Journal

Human capital and employee motivation are also

expected to mediate the influence of the three HR

dimensions on operational outcomes. Researchers

have widely recognized the potential impact of hu-

man capital on organizational effectiveness (Bar-

ney, 1991; Coff, 1997; Snell, Youndt, & Wright,

1996; Wright et al., 1994; Wright, Dunford, & Snell,

2001). According to human capital theory and the

resource-based view, human capital is the primary

determinant of productivity (Dess & Shaw, 2001)

and can be a source of competitive advantage when

it is valuable and unique for an organization, hard

to replace without significant costs, and not easily

imitated by rivals (Coff, 1997; Wright et al., 1994).

Therefore, with high-quality human capital pools,

organizations are more likely to achieve opera-

tional goals such as high productivity and quality,

great service, and innovation. Research has pro-

vided support for the positive effect of human cap-

ital on operational performance (Crook, Todd,

Combs, Woehr, & Ketchen, 2011).

Moreover, researchers taking a behavioral per-

spective suggest that the value of employees’ hu-

man capital cannot be realized unless they are will-

ing to use their capabilities (Jackson & Schuler,

1995). To encourage employees to do so, organiza-

tions need to utilize HR practices to enhance their

intrinsic and extrinsic motivation at work, which

can further lead to desired work behaviors and

discretionary efforts contributing to operational

outcomes (Deci, Connell, & Ryan, 1989). A number

of empirical studies have shown that positive work

attitudes (e.g., collective commitment) and positive

perceptions of a work environment (e.g., perceived

organizational support) mediate the relationships

between high-performance work systems and oper-

ational outcomes (e.g., Chuang & Liao, 2010; Gelade

& Ivery, 2003; Rogg, Schmidt, Shull, & Schmitt,

2001; Sun et al., 2007). Therefore, we hypothesize:

Hypothesis 6a. Human capital mediates the

positive relationships between the three di-

mensions of HR systems and operational

outcomes.

Hypothesis 6b. Employee motivation mediates

the positive relationships between the three di-

mensions of HR systems and operational

outcomes.

Finally, we propose mediating effects of volun-

tary turnover and operational outcomes on the re-

lationships between the three HR dimensions and

financial outcomes. The relationship between vol-

untary turnover and financial performance is com-

plex, depending on what kinds of employees leave

and whether they have been replaced appropri-

ately. According to human capital theory, when

capable employees leave, an organization loses the

human capital embodied in those departing and

also loses the chance to realize a return on its

investment in developing the human capital (Dess

& Shaw, 2001). Especially when employees possess

organization-specific human capital, the loss will

be detrimental for organizations’ financial perfor-

mance, and organizations need to take a long time

to regain their competitive advantage (Osterman,

1987; Strober, 1990). On the other hand, research

has also suggested that organizations need some

level of voluntary turnover. This is because em-

ployees who do not fit their jobs will self-select out

of organizations, which also need new employees

to provide fresh stimulus (Dalton & Todor, 1979;

Jovanovic, 1979; Schneider, 1978). However, no

matter which kinds of employees leave, organiza-

tions also incur additional costs related to turnover

(Dess & Shaw, 2001). For example, administrative

resources used in recruitment, selection, and train-

ing would have been in vain, and the organizations

need to invest additional resources to search for

and train new employees to replace the leavers. At

the same time, operational outcomes will suffer

during the vacant and training period. Further, a

high turnover rate can corrupt the morale of organ-

izations and trigger more employees to leave their

jobs, thereby negatively affecting financial out-

comes (Hausknecht & Trevor, 2011). In keeping

these arguments, empirical studies have consis-

tently demonstrated the existence of a negative re-

lationship between voluntary turnover and finan-

cial performance (e.g., Batt, 2002; Glebbeek & Bax,

2004; Huselid, 1995; Kacmar, Andrews, Van Rooy,

Steilberg, & Cerrone, 2006; Morrow & McElroy,

2007; Shaw et al., 2005). Therefore, we propose a

negative relationship between voluntary turnover

and financial performance.

The rationale for the positive relationship be-

tween operational outcomes and financial out-

comes is clear in the literature. The financial out-

comes of an organization are a function of a variety

of factors, including industry environment, organ-

izational strategy, and organizational characteris-

tics (White & Hamermesh, 1981). Among these ex-

planatory factors, business operations within an

organization may be a salient determinant of finan-

cial outcomes because outcomes such as productiv-

ity, quality, and service are directly related to prof-

itability (Curtis, Hefley, & Miller, 1995). In a meta-

analytic review, Capon, Farley, and Hoenig (1990)

found that quality of product and service were pos-

itively associated with financial outcomes. Like-

wise, Crook and colleagues (2011) also reported a

positive relationship between operational out-

2012 1269Jiang, Lepak, Hu, and Baer

comes and financial outcomes. In view of these

findings, we propose a positive relationship be-

tween operational and financial outcomes.

In sum, drawing upon the behavioral perspective

of HRM, human capital theory, and the resource-

based view of the firm, we propose a mediating

model in which the three dimensions of HR sys-

tems are indirectly related to financial outcomes

through human capital, employee motivation, vol-

untary turnover, and operational outcomes in se-

quence. In building this framework, we focus on

the mediating role of employees in the link of HRM

with financial performance. However, our model

does not exclude other paths through which HRM

can help increase financial outcomes. In fact, both

theoretical and empirical research has suggested

that HRM can provide firms with organizational

capital reflected by internal fit and flexibility

(Evans & Davis, 2005; Wright & Snell, 1998) and

social capital (Collins & Clark, 2003; Delery &

Shaw, 2001; Gittell, Seidner, & Wimbush, 2010),

both of which can be sources of competitive advan-

tage for organizations. Given these alternative pos-

sibilities, we hypothesize that the intermediate out-

comes proposed in our model partially mediate the

positive relationships between the three HR dimen-

sions and financial outcomes.

Hypothesis 7. Human capital, employee moti-

vation, voluntary turnover, and operational

outcomes partially mediate the positive rela-

tionships between the three dimensions of HR

systems and financial outcomes.

METHODS

Data Collection

We tested the mediating hypotheses with the

help of meta-analytic structural equation modeling

(SEM) techniques (Cheung & Chan, 2005, 2009;

Viswesvaran & Ones, 1995). To identify studies that

could be used in the meta-analysis, we first

searched the PsycINFO, Web of Science, and Pro-

Quest Digital Dissertations databases for studies

published before May 2011. We used multiple key-

words. For HRM, we used the keywords “human

resource work practice/system,” “high-perfor-

mance work practice/system,” “high-involvement

work practice/system,” or “high-commitment work

practice/system,” whereas for organizational out-

comes, we searched for studies that also included

the keywords “performance,” “outcome,” “atti-

tudes,” “satisfaction,” “commitment,” “motiva-

tion,” “human capital,” “turnover,” “productivity,”

“quality,” “service,” “safety,” “growth,” or “profit-

ability.” Moreover, we used the same search terms

to search conference programs from the Academy

of Management (AOM) and the Society of Indus-

trial and Organizational Psychology from 2000 to

2010. Second, we referred to the reference lists of

the prior reviews on this topic, including theoreti-

cal reviews (e.g., Becker & Gerhart, 1996; Becker &

Huselid, 1998; Lengnick-Hall, Lengnick-Hall, An-

drade, & Drake, 2009; Lepak et al., 2006; Wright &

Boswell, 2002) and meta-analytic reviews (Combs

et al., 2006; Subramony, 2009). Third, we made an

effort to identify unpublished studies through the

listservs of the AOM’s Human Resources and Organ-

izational Behavior Divisions.

Four inclusion criteria were used to select stud-

ies. First, we focused only on studies that examined

the relationships between HR practices and organ-

izational outcomes at the organizational level (e.g.,

establishment, business unit, or firm). We did not

include studies that investigated individual-level

relationships between employee-perceived HR

practices/systems and individual outcomes (e.g.,

Agarwala, 2003; Barling, Kelloway, & Iverson,

2003) or cross-level relationships between organi-

zation-level HR practices and individual-level out-

comes (e.g., Liao et al., 2009; Takeuchi, Chen, &

Lepak, 2009). Second, we only included studies

that emphasized the use of HR practices/systems in

organizations but not the effectiveness or the value

of these practices or systems (e.g., Huselid, Jackson,

& Schuler, 1997; Richard & Johnson, 2004). Third,

we included studies in the meta-analysis if they

reported at least one correlation among individual

HR practices and various organizational outcomes.

We excluded the studies that only presented the

correlations of HR systems rather than those of

individual HR practices with organizational out-

comes (e.g., Bae & Lawler, 2000). Studies without

the statistical information (e.g., sample sizes, cor-

relation coefficients) necessary to calculate effect

sizes were also excluded (e.g., Cappelli & Neumark,

2001; Ichniowski, Shaw, & Prennushi, 1997). Fi-

nally, when the same sample was used in two or

more articles, we considered only the one that pro-

vided more information. In contrast, when a study

used two or more independent samples, we coded

these independent samples separately. The inclu-

sion criteria yielded a final set of 116 articles rep-

resenting 120 independent samples that included a

total of 31,463 organizations.

We first developed the coding sheet and instruc-

tions as recommended by Lipsey and Wilson

(2001). The first author and the third author then

independently coded a random selection of 15 ar-

ticles to assess the level of agreement regarding

sample sizes, effect sizes, and reliability. After both

coders checked data entry and resolved errors, they

1270 DecemberAcademy of Management Journal

independently coded the rest of studies. The con-

sensus rate was 96 percent, and disagreements

were solved through discussion between the two

coders.

Operationalization of Variables

Three dimensions of HR systems. We identified

14 HR practices frequently examined in the litera-

ture. By following previous research using the abil-

ity-motivation-opportunity framework (e.g., Appel-

baum et al., 2000; Batt, 2002; Gardner et al., 2011;

Guest, 1997; Lepak et al., 2006; Subramony, 2009),

we categorized these practices into three dimen-

sions. Skill-enhancing HR practices included re-

cruitment, selection, and training. Motivation-en-

hancing HR practices consisted of performance

appraisal, compensation, incentive, benefit, pro-

motion and career development, and job security.

In addition, opportunity-enhancing HR practices

covered job design, work teams, employee involve-

ment, formal grievance and complaint processes,

and information sharing.

Organizational outcomes. We summarized var-

ious organizational outcomes into five categories.

Human capital included overall organizational hu-

man capital measured via established scales (e.g.,

Subramaniam & Youndt, 2005; Youndt, Subrama-

niam, & Snell, 2004) and the education level of a

workforce. Employee motivation was reflected by

collective job satisfaction, organizational commit-

ment, organizational climate, perceived organiza-

tional support, and organizational citizenship be-

havior. Voluntary turnover only represented the

percentage of employees who quit or voluntarily

left the organizations. Dismissal rate and overall

turnover rate were not included. In addition, we

viewed productivity, quality, service, innovation,

and overall operational performance as operational

outcomes, and we viewed return on assets, return

on equity, market return, sale growth, and overall

financial performance as financial outcomes.

As suggested by Aguinis, Pierce, Bosco, Dalton,

and Dalton (2011), we provide a table, in Appendix

A, that lists all the included studies and our cate-

gorizations of the three HR dimensions and differ-

ent types of outcomes. This information is impor-

tant to allow future research to replicate and extend

this study.

Meta-analytic and Model-Testing Procedures

To test the mediating model through meta-ana-

lytic SEM, we needed to calculate meta-analytic

correlations among three dimensions of HR sys-

tems and different types of organizational out-

comes by correcting for measurement error and

sampling error (Hunter & Schmidt, 2004). We first

performed reliability corrections for informant-re-

ported measures of HR practices and organizational

outcomes to correct for measurement error. For

those studies that did not report the reliabilities of

the informant-reported measures, we imputed the

reliabilities using the weighted mean of the avail-

able reliabilities estimated from the other studies

(Lipsey & Wilson, 2001). Regarding the variables

that were measured with archival data (e.g., return

on assets), we adopted a more conservative .80

reliability estimate, which has been used in previ-

ous meta-analyses in management (e.g., Dalton,

Daily, Certo, & Roengpitya, 2003; Dalton, Daily,

Ellstrand, & Johnson, 1998; Dalton, Daily, Johnson,

& Ellstrand, 1999). For example, if training prac-

tices were measured by reflective items (e.g., “This

firm invests considerable time and money in train-

ing”) in a study that reported the reliability of these

items, we would correct for the reliability for train-

ing. In contrast, if training practices were measured

by archival data (e.g., “On average how many hours

of formal training do employees in this firm receive

each year?”), we would correct for a reliability of

.80 for this measure. For comparison purposes, we

also calculated the reliability-corrected correlation

by using a reliability of 1.00 for archival measures

and did not find changes in the main findings of

this study.

Second, to calculate the composites of HR prac-

tices (i.e., HR dimensions) and the composites of

outcome variables (i.e., organizational outcomes

categories), we combined the correlations among

individual HR practices and outcomes using the

formula provided by Hunter and Schmidt (2004:

435–439):

rXY ⫽

冘

rxiyj

冑

n⫹n

共

n⫺1

兲

r៮xixj

冑

m⫹m

共

m⫺1

兲

r៮yiyj.

If it is assumed that xrepresents a dimension of HR

systems (e.g., skill-enhancing HR practices) and y

represents a category of organizational outcomes

(e.g., employee motivation), ⌺r៮xiyj is the sum of the

correlations between HR practices (e.g., recruit-

ment, selection, and training) and outcome vari-

ables (e.g., collective satisfaction and commit-

ment); nand mare the numbers of HR practices

and outcome variables respectively; r៮xixj is the av-

erage correlation among HR practices; and r៮yiyj is

the average correlation among outcome variables.

By using this formula, we created a single effect

size for each relationship within each study.

Third, we used a random-effects model to correct

for the sampling error by weighting each study’s

effect size by its sample size (Hunter & Schmidt,

2012 1271Jiang, Lepak, Hu, and Baer

2004). We also computed the 95% confidence in-

terval (CI) around the sample-weighted mean cor-

relation and Qhomogeneity statistic. Confidence

intervals provide an estimate of the variability

around the estimated average correlation; a 95% CI

excluding zero indicates that one can be 95 percent

confident that the confidence interval includes the

average mean true score. The Qstatistic indicates

the variance in the sample-weighted mean correla-

tion; a significant Qsuggests the heterogeneity of a

given relationship. Research has suggested that a

random-effects model provides a more accurate es-

timate than a fixed-effects model when relation-

ships are heterogeneous (Cheung & Chan, 2005;

Erez, Bloom, & Wells, 1996; Overton, 1998).

Finally, we used the created correlation matrices

in SEM computed in LISREL 8.72 (Jöreskog & Sör-

bom, 2005). Because the sample sizes for different

correlations were not identical, we imputed the

sample size for the SEM analyses by calculating the

harmonic mean of the correlation sample sizes

(Viswesaran & Ones, 1995). Compared with the

arithmetic mean, the harmonic mean gives much

less weight to large sample sizes and thus results in

a more conservative parameter estimate. Four es-

tablished model fit statistics—chi-square (

␹

), the

root-mean-square error of approximation (RMSEA),

the comparative fit index (CFI), and the standard-

ized root-mean-square residual (SRMR)—were

used to examine the viability of the structural mod-

els (Kline, 2005). Acceptable model fit is associated

with nonsignificant chi-square values and with a

CFI greater than .90, an RMSEA less than or equal

to .08, and an SRMR less than .10 (Kline, 2005). We

used two statistics to test the hypotheses predicting

relative effects of three HR dimensions on human

capital and employee motivation. One was the Z-

test, which shows the significance of the difference

between regression coefficients (Clogg, Petkova, &

Haritou, 1995), and the other was the epsilon sta-

tistic, which has been commonly used to determine

the relative weight of each predictor in explaining

the variance of dependent variables (Johnson, 2000;

Johnson & LeBreton, 2004). The results of relative

weights represent the proportion of total variance

) explained by each HR dimension. To analyze

mediation, we used Sobel’s (1982) test to examine

the statistical significance of indirect effects.

RESULTS

Differential Effects of HR Dimensions

Table 1 summarizes the correlation results of the

relationships among HR dimensions and organiza-

tional outcomes categories. To test Hypotheses 1, 2,

3, and 4, we included all three dimensions of HR

systems in regressions examining their effects on

human capital and employee motivation. As shown

in Table 2, all three HR dimensions had significant

and positive effects on human capital. The results

of Z-tests show that the regression coefficient of

skill-enhancing HR practices (

␤

⫽.29, p⬍.01) was

significantly larger than the coefficients of motiva-

tion-enhancing HR practices (

␤

⫽.22, p⬍.01, Z⫽

2.74, p⬍.01) and opportunity-enhancing HR prac-

tices (

␤

⫽.07, p⬍.01, Z⫽8.68, p⬍.01). Moreover,

the analyses of relative weights indicate that skill-

enhancing HR practices explained the largest per-

centage of variance in human capital (48%), fol-

lowed by motivation-enhancing HR practices

(36%) and opportunity-enhancing HR prac-

tices (16%).

Similarly, we found significantly positive effects

of three HR dimensions on employee motivation.

Consistently with our prediction, the influences of

motivation-enhancing HR practices (

␤

⫽.29, p⬍

.01, Z⫽⫺8.64, p⬍.01) and opportunity-enhanc-

ing HR practices (

␤

⫽.25, p⬍.01, Z⫽⫺7.07, p⬍

.01) were significantly stronger than that of skill-

enhancing HR practices (

␤

⫽.07, p⬍.01). Motiva-

tion-enhancing HR practices and opportunity-en-

hancing HR practices respectively explained 45

and 38 percent of the variance of employee moti-

vation, whereas skill-enhancing HR practices ex-

plained 17 percent. In sum, Hypotheses 1 through 4

were supported.

Mediation Results

Hypotheses 5 through 7 predict that the three HR

dimensions have both direct effects and indirect

effects through human capital, employee motiva-

tion, voluntary turnover, and operational outcomes

on financial outcomes. We tested the proposed

model (Figure 1) by inputting correlation matrices

(Table 1) into LISREL 8.72 (Jöreskog & Sörbom,

2005). As shown in Table 3, the model fit of the

proposed model was acceptable (

␹

[9] ⫽264.82,

RMSEA ⫽.09, CFI ⫽.98, SRMR ⫽.04). All the

proposed relationships among HR dimensions and

organizational outcomes categories were signifi-

cant and consistent with our prediction except

for the direct relationship between opportunity-

enhancing HR practices and financial outcomes

(

␤

⫽⫺.03, n.s.). Thus, we dropped this direct path

from the model, which only marginally impacted

fit (model 1: ⌬

␹

[1] ⫽4.65, p⬍.05). We also tested

the direct relationships between three HR dimen-

sions and voluntary turnover and operational out-

comes. As presented in Table 3, adding paths from

skill-enhancing HR practices to both outcomes sig-

1272 DecemberAcademy of Management Journal

nificantly improved fit over that of model 1 (model

2: ⌬

␹

[2] ⫽80.71, p⬍.01). However, the path from

skill-enhancing HR practices to voluntary turnover

was not significant (

␤

⫽⫺.02, p⬎.05). Dropping

this path did not impact fit (model 3: ⌬

␹

[1] ⫽1.56,

n.s.). Furthermore, we added the direct paths from

motivation-enhancing HR practices to voluntary

turnover and operational outcomes and found a

significant improvement in the fit over that of

model 3 (model 4: ⌬

␹

[2] ⫽10.54, p⬍.01). The

TABLE 1

Meta-analytic Correlations between HR Dimensions and Organizational Outcomes

Variables 1 2 34567

1. Skill-enhancing practices

2. Motivation-enhancing practices (r,r

).38, 46

k(N) 55 (14,670)

95% CI .40: .53

Q822.75**

3. Opportunity-enhancing practices (r,r

).38, 47 .37, 44

k(N) 49 (13,079) 50 (13,740)

95% CI .40: .53 .37: .52

Q557.95** 855.49**

4. Human capital (r,r

).35, 42 .36, 38 .25, 30

k(N) 13 (2,013) 19 (3,249) 13 (2,068)

95% CI .27: .57 .26: .49 .24: .37

Q133.88** 175.97** 23.58*

5. Employee motivation (r,r

).25, 32 .33, 43 .32, 41 .37, 42

k(N) 20 (4,915) 22 (4,591) 19 (4,647) 12 (1,165)

95% CI .26: .37 .34: .51 .31: .51 .23: .61

Q63.23** 148.79** 183.61** 111.91**

6. Voluntary turnover (r,r

)⫺.19, ⫺.21 ⫺.15, ⫺.17 ⫺.17, ⫺.22 ⫺.22, ⫺.26 ⫺.31, ⫺.37

k(N) 19 (6,181) 24 (6,674) 19 (8,092) 7 (1,363) 11 (2,879)

95% CI ⫺.14: ⫺.29 ⫺.09: ⫺.25 ⫺.10: ⫺.33 ⫺.01: ⫺.53 ⫺.18: ⫺.56

Q142.39** 213.38** 384.16** 130.46** 208.62**

7. Operational outcomes (r,r

).25, 32 .19, 25 .25, 32 .25, 29 .32, 38 ⫺.15, ⫺.19

k(N) 36 (10,224) 37 (11,041) 35 (9,576) 8 (1,198) 23 (4,618) 22 (6,002)

95% CI .25: .39 .17: .33 .25: .39 .06: .53 .30: .47 ⫺.10: ⫺.27

Q436.07** 626.61** 354.35** 108.92** 142.24** 189.14**

8. Financial outcomes (r,r

).22, 26 .22, 27 .15, 20 .19, 24 .32, 38 ⫺.15, ⫺.19 .38, 48

k(N) 41 (9,966) 41 (12,219) 27 (5,610) 12 (2,028) 17 (3,354) 17 (4,055) 33 (8,863)

95% CI .21: .32 .21: .33 .13: .26 .16: .32 .25: .51 ⫺.08: ⫺.30 .39: .57

Q247.07** 384.70** 130.73** 32.04** 206.61** 181.60** 547.24**

The mean sample-size-weighted correlation (r) and mean sample-sized-weighted correlation corrected for attenuation due to unreli-

ability (r

) are presented. A “k” indicates the number of independent samples, and “N” is the total sample size. The 95% CI is the

95% confidence interval around the mean sample-size-weighted corrected correlation (r

). Qis the chi-square-test for the homogeneity of

corrected correlations (r

) across studies.

*p⬍.05

** p⬍.01

TABLE 2

Results of Differential Effects of HR Dimensions on Human Capital and Motivation-Related Attitudes

Predictors

Human Capital Employee Motivation

␤

t%R

␤

t%R

Skill-enhancing HR practices (A) .29 15.76** 48% .07 3.90** 17%

Motivation-enhancing HR practices (M) .22 12.12** 36% .29 16.30** 45%

Opportunity-enhancing HR practices (O) .07 3.84** 16% .25 14.12** 38%

Total R

.22 .25

Z,A⫺M 2.74** ⫺8.64**

Z,A⫺O 8.68** ⫺7.07**

Standardized coefficients are presented. Zis the test for the significance of the difference between the regression coefficients.

*p⬍.05

** p⬍.01

2012 1273Jiang, Lepak, Hu, and Baer

FIGURE 1

Theoretical Model of Effects of HR Dimensions on Organizational Outcomes

Skill-Enhancing

HR Practices

Motivation-

Enhancing HR

Practices

Opportunity-

Enhancing HR

Practices

Human

Capital

Employee

Motivation

Voluntary

Turnover

Operational

Outcomes

Financial

Outcomes

TABLE 3

Fit Statistics for Alternative Models

Models

␹

df ⌬

␹

CFI RMSEA SRMR AIC

Three HR dimensions

Theoretical model (Figure 1) 264.82 9 .98 .09 .04 318.32

Alternative model 1

269.47 10 4.65*

.98 .08 .05 321.47

Alternative model 2

188.76 8 80.71**

.98 .08 .03 244.76

Alternative model 3

190.32 9 1.56

.98 .07 .03 244.32

Alternative model 4

179.78 7 10.54**

.99 .08 .03 237.78

Alternative model 5

180.54 8 0.76

.99 .08 .03 236.54

Alternative model 6

(Figure 2) 130.32 6 50.22**

.99 .08 .02 190.32

Latent high performance work systems (HPWS)

Theoretical model (Figure 3) 570.74 16 .95 .10 .05 610.74

Alternative model 7

(Figure 4) 406.51 14 147.72**

.96 .09 .03 450.51

n⫽3,724.

Deletes the direct paths from opportunity-enhancing HR practices to financial outcomes.

Model fit compared with the theoretical model of the effects of three HR dimensions on organizational outcomes (Figure 1).

Adds the direct paths from skill-enhancing HR practices to voluntary turnover and operational outcomes.

Model fit compared with the previous model.

Deletes the direct paths from skill-enhancing HR practices to voluntary turnover.

Adds the direct paths from motivation-enhancing HR practices to both voluntary turnover and operational outcomes.

Deletes the direct path from motivation-enhancing HR practices to operational outcomes.

Adds the direct path from opportunity-enhancing HR practices to voluntary turnover and operational outcomes.

Adds the direct path from HPWS to both voluntary turnover and operational outcomes.

Model fit compared with the theoretical model of the effects of HPWS on organizational outcomes (Figure 3).

*p⬍.05

** p⬍.01

1274 DecemberAcademy of Management Journal

path from motivation-enhancing HR practices and

operational outcomes was not significant (

␤

⫽

⫺.02, n.s.), and we dropped it without impacting fit

(model 5: ⌬

␹

[1] ⫽0.76, n.s.). Finally, we added the

direct paths from opportunity-enhancing HR prac-

tices to voluntary turnover and operational out-

comes, and both paths were significant (model 6:

⌬

␹

[2] ⫽50.22, p⬍.01). Therefore, we kept model

6 as the final model for the mediation analyses.

Figure 2 presents the standardized path estimates

for the final mediating model. Both human capital

and employee motivation were negatively related

to voluntary turnover (

␤

⫽⫺.20, p⬍.01 for human

capital;

␤

⫽⫺.34, p⬍.01 for employee motivation)

and were positively related to operational out-

comes (

␤

⫽.15, p⬍.01 for human capital;

␤

⫽.26,

p⬍.01 for employee motivation). In turn, volun-

tary turnover was negatively related to financial

outcomes (

␤

⫽⫺.08, p⬍.01), whereas operational

outcomes were positively associated with financial

outcomes (

␤

⫽.42, p⬍.01). Sobel (1982) tests

showed that the indirect relationships between all

three HR dimensions and voluntary turnover, op-

erational outcomes, and financial outcomes were

significant (Zvaried from 8.05 to 13.89, all p-values

were less than .01). In sum, these results suggest

that human capital, employee motivation, volun-

tary turnover, and operational outcomes partially

mediated the relationships between skill-enhanc-

ing and motivation-enhancing HR dimensions and

financial outcomes and fully mediated the relation-

ship between opportunity-enhancing HR practices

and financial outcomes. Hypotheses 5 through 7

were generally supported.

We obtained the indirect effects and total effects

of the three HR dimensions on financial outcomes

from the estimates in SEM. The total effects of

skill-enhancing, motivation-enhancing, and oppor-

tunity-enhancing HR dimensions on financial out-

comes were .13, 18, and .09 respectively (all p’s ⬍

.01). The indirect effects mediated by human capi-

tal, employee motivation, voluntary turnover, and

operational outcomes were .08, 05, and .09 for the

three HR dimensions respectively. We also calcu-

lated the squared multiple correlations (i.e., R

s) for

structural equations predicting human capital (.22),

employee motivation (.25), voluntary turnover

(.18), operational outcomes (.22), and financial out-

comes (.26). The results indicate that the final

model explained a moderate amount of variance in

these variables.

FIGURE 2

Final Model of Effects of HR Dimensions on Organizational Outcomes

Human

Capital

= .22

Employee

Motivation

= .25

Voluntary

Turnover

= .18

Operational

Outcomes

= .22

Skill-Enhancing

HR Practices

Motivation-

Enhancing HR

Practices

Opportunity-

Enhancing HR

Practices

Financial

Outcomes

= .26

.05**

.29**

.07**

.21**

.29**

.13**

.07**

.25**

–.20**

.16**

–.34**

.26**

–.08**

.43**

.12**

.07**

.11**

–.05**

.46**

.44**

.47**

Standardized coefficients are presented; n⫽3,714.

** p⬍.01

2012 1275Jiang, Lepak, Hu, and Baer

In addition, we conducted a post hoc analysis to

examine whether the three-dimensional model

(model 6) fit the data better than a unidimensional

model that treats the three HR dimensions as indi-

cators of high-performance work systems (HPWS;

Figure 3). As shown in Table 3, the partial mediat-

ing model (model 7), in which HPWS has direct

impact on voluntary turnover, operational out-

comes, and financial outcomes, fit the data well

(

␹

[14] ⫽406.51, RMSEA ⫽.09, CFI ⫽.96, SRMR ⫽

.03). Because the two models (6 and 7) were not

nested, we relied on indexes other than chi-square

change to compare them. In general, the three-di-

mensional model (model 6: RMSEA ⫽.08, CFI ⫽

.99, SRMR ⫽.02) fit better than unidimensional

model 7, but the differences in fit indexes were not

great. Then we used an additional fit index, Akai-

ke’s information criterion (AIC; Akaike, 1974),

which is generally used in SEM to compare non-

nested models estimated with the same data (Hen-

son, Reise, & Kim, 2007; Kline, 2005). The value of

AIC itself does not indicate the quality of a model;

only the AIC relative to that of another model is

meaningful. Lower values indicate a better fit, and

so the model with the lowest AIC is the best fitting

one. As shown in Table 3, the AIC for model 6

(190.32) was lower than that for model 7 (450.51),

which indicates the three-dimensional model fit

the data better than the unidimensional model.

DISCUSSION

Our aim in this meta-analytic review is to con-

tribute to strategic HRM research by exploring the

mediating mechanisms through which HR prac-

tices influence organizational outcomes. Drawing

upon the ability-motivation-opportunity model of

HRM, the behavioral perspective of HRM, human

capital theory, and the resource-based view of the

firm, we proposed and found that the three dimen-

sions of HR systems had differential relationships

with human capital and employee motivation,

which were in turn related to voluntary turnover

and operational outcomes, and were further asso-

ciated with financial outcomes. In addition, our

findings demonstrated the direct relationships be-

tween skill-enhancing HR practices and motiva-

tion-enhancing HR practices and financial out-

comes. Below we discuss the research and practical

implications of our findings.

Research Implications

This research offers a number of important theo-

retical contributions. First, we adopt multiple the-

oretical perspectives on HRM to extend previous

mediating models of HRM’s influence on organiza-

tional outcomes (e.g., Becker & Huselid, 1998; Del-

ery & Shaw, 2001; Guest, 1997). Drawing upon the

behavioral perspective on HRM, human capital the-

ory, and the resource-based view, the current study

demonstrates that HRM positively relates to finan-

cial performance both by encouraging desired em-

ployee behaviors and by building a valuable human

capital pool. It also suggests that future research

should simultaneously address the mediating roles

of human capital and employee motivation so that

it can provide a clearer understanding of the link-

FIGURE 3

Theoretical Model of Effects of HPWS on Organizational Outcomes

Skill-Enhancing

HR Practices

Motivation-

Enhancing HR

Practices

Opportunity-

Enhancing HR

Practices

Human

Capital

Employee

Motivation

Voluntary

Turnover

Operational

Outcomes

Financial

Outcomes

High

Performance

Work Systems

1276 DecemberAcademy of Management Journal

age between HRM and operational and financial

outcomes.

Moreover, this study embraced the multidimen-

sionality of performance as well as the potential for

different relationships with proximal and distal

outcomes. Researchers have recently called for

studies to simultaneously examine multiple out-

come variables that have only been studied inde-

pendently before (Lengnick-Hall et al., 2009). With

the help of meta-analytic techniques, we tested a

comprehensive mediating model and provided em-

pirical support for the theoretical proposition that

HRM first relates to proximal outcomes, which fur-

ther relate to distal outcomes (Becker & Huselid,

1998; Delery & Shaw, 2001; Dyer & Reeves, 1995;

Guest, 1997) and revealed that the relationships

between HRM and distal outcomes (e.g., opera-

tional and financial outcomes) could be mediated

through multiple pathways (e.g., through human

capital and employee motivation). Moreover, as we

expected, there were direct relationships between

skill-enhancing HR practices and motivation-en-

hancing HR practices and financial outcomes that

could not be explained by the mediating process.

This is consistent with prior research suggesting

that HRM can improve organizational effectives

through alternative approaches such as affecting

internal interaction within organizations (Evans &

Davis, 2005; Gittell et al., 2010) and enhancing the

social capital of organizations (Collins & Clark,

2003). The findings of the current study and others

suggest that it is meaningful for future research to

further explore other mediators of the relationship

between HRM and organizational outcomes.

One major contribution of this study to the stra-

tegic HRM literature is that the results suggest dif-

ferential effects of the three dimensions of HR sys-

tems. This finding is important both in theory and

in the methodology of measuring HR systems. The-

oretically, this finding challenges previous re-

search, in which the assumption has been that all

HR practices in an HR system function in the same

pattern. Our findings remind researchers that dif-

ferent dimensions of HR systems may have unique

relationships with specific organizational out-

comes. For example, skill-enhancing HR practices

were more effective in enhancing human capital,

whereas motivation-enhancing HR practices and

opportunity-enhancing HR practices were more

likely to improve employee motivation. This result

is also consistent with recent research suggesting

the heterogeneous effects of the components of HR

systems on organizational outcomes (e.g., Batt &

Colvin, 2011; Gardner et al., 2011; Gong et al., 2009;

Liao et al., 2009; Shaw et al., 2009; Subramony,

2009). HR practices are not only distinct, but also

FIGURE 4

Effects of HPWS on Organizational Outcomes

.67**

Skill-Enhancing

HR Practices

Motivation-

Enhancing HR

Practices

Opportunity-

Enhancing HR

Practices

Human

Capital

= .34

Employee

Motivation

= .38

Voluntary

Turnover

= .15

Operational

Outcomes

= .22

Financial

Outcomes

= .27

High

Performance

Work Systems

.67**

.64**

.58**

.62**

.21**

–.10**

.03

–.28*

.16**

–.05**

.37**

–.08*

.34**

Standardized coefficients are presented; n⫽3,714.

*p⬍.05

** p⬍.01

2012 1277Jiang, Lepak, Hu, and Baer

operate via different pathways. Therefore, we en-

courage additional research to explore the influ-

ence of these components of HR systems to advance

knowledge of the relationship between HRM and

organizational outcomes.

The findings of the differential relationships be-

tween the dimensions of HR systems and organiza-

tional outcomes also offer methodological implica-

tions for strategic HRM research. First, if all three

dimensions of HR systems have unique effects on

organizational outcomes, failure to include any di-

mension may compromise the overall impact of HR

systems on organizational outcomes or at least lead

to inaccurate results. Moving forward, we encour-

age researchers to include all three HR dimensions

in their measures of HR systems. Moreover, the

results show that the three HR dimensions have

differential relationships with human capital and

employee motivation. Relatedly, the results indi-

cate that the three-dimensional model fit the data

slightly better than the model combining the three

HR dimensions into a unidimensional HPWS ele-

ment. Combined, these findings offer preliminary

evidence that the three HR dimensions are better

viewed as three distinct but related components of

HR systems rather than interchangeable indicators

of HR systems. This suggestion is consistent with

previous research that argued that the measure of

HR systems should be formative rather than reflec-

tive (e.g., Jiang, et al., 2012; Shaw et al., 2005,

2009), and it encourages researchers to reconsider

whether it is appropriate to utilize addition of HR

practices to represent HR systems. As an alternative

approach, researchers might categorize HR prac-

tices into the three HR dimensions and explore

their main effects and interactions on organiza-

tional outcomes (e.g., Gardner et al., 2011). In ad-

dition, we encourage future research to compare

the use of multidimensional and unidimensional

models of HR systems and their effects on organi-

zational outcomes. This stream of research can fur-

ther verify the findings of this study and offer im-

plications for the measurement of HR systems.

Practical Implications

Our study also offers implications for managerial

practices. First of all, our finding indicates that the

investment in three HR dimensions was associated

with the increase in financial outcomes. Specifi-

cally, we found that given no change in other con-

ditions, a one standard deviation increase in skill-

enhancing, motivation-enhancing, or opportunity-

enhancing HR practices was related to a .13, .18, or

.09 standard deviation increase in financial out-

comes. For example, Huselid (1995) examined the

relationship between motivation-enhancing HR

practices and financial performance and reported a

mean and standard deviation of 0.46 and 1.64 for

Tobin’s Q. If we apply our finding to this study, one

standard deviation increase in motivation-enhanc-

ing HR practices is associated with 64 percent im-

provement in Tobin’s Q. This result suggests that

organizations can obtain substantial financial ben-

efits from investing in the three HR dimensions

considered here.

In addition, the results of this study shed light on

the ways through which managers can increase the

benefits of investing in HRM. The results indicate

that to retain talented employees and realize oper-

ational and financial objectives, organizations need

to use HR practices to enhance both employee

skills and motivation at work. More specifically,

we suggest that organizations focus more on prac-

tices, such as recruitment, selection, and training

when enhancing employee skills. In contrast, when

organizations aim to improve employee motiva-

tion, they should consider how to appraise employ-

ees’ performance, how to compensate for their

work, how to make jobs meaningful and interest-

ing, and how to involve employees in work teams

and decision making. With these suggestions, how-

ever, we do not deny the potential effects of recruit-

ment, selection, and training in enhancing em-

ployee motivation or the positive impact of

performance appraisal, compensation, job design,

or employee involvement in developing employ-

ees’ human capital. Instead, we encourage organi-

zations to maximize the return on their investment

in HRM by using appropriate HR practices. For

example, in order to improve employee motivation,

it may be wise to check whether performance ap-

praisal and compensation systems appropriately

reflect employees’ contribution at work rather than

training employees how to complete their work.

Our study also indicates that organizations’ in-

vestment in HRM leads to financial outcomes

through a mediating process. Any other factors that

can impact the intermediate variables may affect

the effects of HRM on the distal financial outcomes.

This reminds managers of attending to whether

their HR practices improve employee skills and

motivation effectively and whether other manage-

rial initiatives can boost or undermine the effects of

HR practices. For example, researchers have re-

ported that leadership and organizational culture

have an important impact on employee motivation

(Hartnell, Ou, & Kinicki, 2011; Ilies, Nahrgang, &

Morgeson, 2007). Therefore, managers may con-

sider how these factors can complement the effects

of HR practices in enhancing employee motivation.

1278 DecemberAcademy of Management Journal

Limitations and Future Research

Several limitations should be noted in the cur-

rent study. First, some studies included in this

meta-analysis used informant-reported measures to

evaluate HR practices and organizational outcomes

from the same source. This may lead to common

method bias, which might inflate the correlations

between HR practices and organizational out-

comes. Relatedly, most of the studies included in

the analysis had cross-sectional designs, which

may limit conclusions regarding the direction of

the mediating mechanism. The results from the

current investigation should be interpreted with

these limitations in mind. We encourage more lon-

gitudinal studies that collect information on HR

practices and organizational outcomes from differ-

ent sources. Future meta-analysis can explore if a

longitudinal research design may influence the es-

timates of effect sizes and the mediating mecha-

nisms examined in this study.

Second, potential moderators may exist in the

relationships among HR dimensions and organiza-

tional outcome categories. For example, recent

meta-analytic reviews have reported that industry

type (manufacturing industry vs. service industry)

and country moderated the relationship between

HPWS and organizational outcomes (Combs et al.,

2006; Rabl, Jayasinghe, Gerhart, & Kuehlmann,

2011; Subramony, 2009). Researchers have also

suggested that HR practices applied to a specific

group of employees, or used for employees in gen-

eral, may influence their effects on organizational

outcomes (Gerhart, Wright, McMahan, & Snell,

2000). However, owing to the relatively few studies

in the subgroups divided by the potential modera-

tors, we were not able to test the mediating model

separately in each subgroup. Future research can

examine this mediating model by using samples

from different industries, different countries, and

different job groups.

A third limitation of this study is that we were

unable to explore synergy among the three HR di-

mensions by examining their interactions, even

though the synergies within HR systems have been

suggested in the literature (e.g., Delery, 1998; Ger-

hart, 2007; Jiang et al., 2012). Operationally, this

was impossible owing to how existing studies were

measured. However, moving forward, if a good

amount of research includes all three HR dimen-

sions while reporting the correlations of HR dimen-

sions and organizational outcomes with interaction

terms comprised of the three HR dimensions, fu-

ture meta-analytic review will be able to exam-

ine this.

Fourth, in the current study we examined volun-

tary turnover as an intermediate outcome mediat-

ing the relationships between the three HR dimen-

sions as well as employee human capital and

motivation and financial outcomes. However, a

growing literature indicates that voluntary turnover

may moderate the relationship between HRM and

financial outcomes (e.g., Guthrie, 2001; Haus-

knecht & Trevor, 2011; Shaw, 2011; Shaw et al.,

2005). However, we were not able to test the inter-

actions between the three HR dimensions and vol-

untary turnover because very few studies reported

the correlations between the interaction terms and

the variables examined. We encourage scholars to

explore this issue in future research. In addition,

recent turnover research suggests that involuntary

turnover or dismissal is also influenced by HR

practices and negatively related to operational and

financial outcomes (Batt & Colvin, 2011; Haus-

knecht & Trevor, 2011). It is worth considering the

roles of both types of turnover in the mediating

process rather than just focusing on voluntary

turnover.

Fifth, like other meta-analyses testing mediating

process (e.g., Chang, Rosen, & Levy, 2009; Colquitt,

Scott, & LePine, 2007; Robbins, Oh, Le, & Button,

2009), the current meta-analysis did not include

control variables in the regression models (e.g., in-

dustry, size, unionization, strategy) because many

studies did not provide correlations with these

variables.

Finally, our study only focused on the relation-

ships between HRM and organizational outcomes

at the organizational level, even though there is a

growing research focus on cross-level influences of

organization-level HRM on individual-level out-

comes (e.g., Liao et al., 2009; Snape & Redman,

2010; Takeuchi et al., 2009) and on the influence of

employee-perceived HR systems on individual out-

comes (e.g., Butts, Vandenberg, DeJoy, Schaffer, &

Wilson, 2009; Kehoe & Wright, in press). We en-

courage more empirical studies on the effects of

organization-level HR systems and employee-per-

ceived HR systems on individual outcomes. Over

time, there may be enough studies for a future

meta-analysis summarizing these effects on indi-

vidual outcomes.

Conclusions

This meta-analysis examined and extended the

theoretical model linking human resource manage-

ment with organizational outcomes (e.g., Becker &

Huselid, 1998; Delery & Shaw, 2001; Guest, 1997).

We found that three dimensions of HR systems (i.e.,

skill-enhancing, motivation-enhancing, and oppor-

2012 1279Jiang, Lepak, Hu, and Baer

tunity-enhancing HR practices) were positively re-

lated to human capital and employee motivation in

different patterns in such a way that, compared

with the other two HR dimensions, skill-enhancing

HR practices were more positively related to hu-

man capital and less positively related to employee

motivation. In addition, human capital and em-

ployee motivation mediated the relationships be-

tween three HR dimensions and voluntary turnover

and operational outcomes, which in turn related to

financial outcomes. We also found direct relation-

ships between the three dimensions of HR systems

and voluntary turnover, operational outcomes, and

financial outcomes and thus encourage future re-

search exploration of additional mediators in the

relationships between HRM and organizational

outcomes.

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Kaifeng Jiang (kfjiang@eden.rutgers.edu) is a doctoral

candidate in the School of Management and Labor Rela-

tions at Rutgers, the State University of New Jersey. His

primary research interests include strategic human re-

source management, workplace climate, turnover, and

employee engagement.

David P. Lepak (lepak@smlr.rutgers.edu) is a professor in

the School of Management and Labor Relations at Rut-

gers, the State University of New Jersey. He received his

Ph.D. from the Pennsylvania State University. His cur-

rent research interests focus on the strategic management

of human capital as well as managing contingent labor

for competitive advantage.

Jia (Jasmine)Hu (jhu@nd.edu) is an assistant professor of

management at the Mendoza College of Business, Uni-

versity of Notre Dame. She received her Ph.D. with con-

centrations in organizational behavior and human re-

sources from the University of Illinois at Chicago. Her

primary research interests focus on understanding the

effects of leadership, work teams, and human resource

management practices on employee and team outcomes.

Judith C. Baer (jcbaer@ssw.rutgers.edu) is an associate

professor of social work at Rutgers, the State University

of New Jersey, and an associate professor of psychiatry at

New York University’s Langone Medical School, where

she is a member of the Institute of Social and Psychiatric

Initiatives. She received her Ph.D. from the University of

Houston. Her scholarly interests include research on the

nosology of mental disorders, risk and resiliency factors

important to adolescent development, as well as person-

ality factors that affect faculty-student relationships.

This article continues with an appendix.

1288 DecemberAcademy of Management Journal

APPENDIX

Coding of Studies Included in the Meta-analysis

Study

Skill-

Enhancing

HR Practices

Motivation-

Enhancing

HR Practices

Opportunity-

Enhancing

HR Practices

Human

Capital

Employee

Motivation Turnover

Operational

Outcomes

Financial

Outcomes

Ahmad and

Schroeder

(2003)

Selective

hiring,

extensive

training

Compensation

contingent

performance,

employment

security

Team and

decentralization,

sharing

information

Organizational

commitment

Overall

operational

performance

Akhtar, Ding

and Ge (2008)

Training Employment

security,

results-

oriented

appraisal,

internal

career

opportunities,

profit

sharing

Participation,

job

description

Product/service

performance

Overall

financial

performance

Appleyard

and Brown

(2001)

Training Team

participation

Labor

productivity

Armstrong,

Flood,

Guthrie, Liu,

MacCurtain,

and Mkamwa

(2010)

Voluntary

turnover

Productivity,

innovation

Arthur (1994) Voluntary

turnover

Productivity

Audea, Teo,

and Crawford

(2005)

Staffing,

training

Appraisal,

compensation,

industrial

relations

Job function Technological

skills,

managerial

and

operational

skills

Barksdale

(1994)

Career-

enhancement

practices

Work-family

assistance

practices

Organizational

climate

Voluntary

turnover

Return on

invested

assets, return

on equity

Bartram,

Stanton,

Leggat,

Casimir, and

Fraser (2007)

Recruitment,

training

Performance

management

HR planning,

participation

Voluntary

turnover

Batt (2002) HR incentive

index

Work design

index

Job skill level Quit rate Percent change

in sales

Batt, Colvin,

and Keefe

(2002)

Training Variable pay,

pay to cost

of living

Problem-

solving

groups,

self-

directed

teams

Quit rate

Batt and

Colvin (2011)

Initial

training,

selection

ratio,

systemic

selection

procedures

Internal

mobility

opportunities,

relative

pay,

pensions

Problem-

solving

groups,

self-

directed

teams

Average

education

Quit rate Customer

satisfaction

Beltran-

Martin, Roca-

Puig, Escrig-

Tena, and

Bou-Llusar

(2008)

Selective

staffing,

comprehensive

training

Developmental

performance

appraisal,

equitable

rewards

system

Skills Customer

service

Brown,

Sturman, and

Simmering

(2003)

Compensation Return on assets

Cabello-

Medina,

Lopez-

Cabrales, &

Valle-Cabrera

(2011)

Selection Incentives on

compensation,

career

development

Empowerment Human

capital

Innovative

performance

Chan, Shaffer,

and Snape

(2004)

HR skill index HR

motivation

index

Overall

operational

performance

Market

performance

Chandler and

McEvoy

(2000)

Training

hours

Outcome

based pay

Total quality

management

Firm earnings

Chen and

Huang (2009)

Staffing,

training

Performance

appraisal,

compensation

Participation Innovation

Chuang and

Liao (2010)

Staffing,

training

performance,

compensation,

caring

Involvement Customer

knowledge

Helping behavior Service

performance

Market

performance

Collins and

Smith (2006)

Climate for trust,

cooperation

Sale growth,

revenue

Collins,

Smith, and

Stevens

(2001)

Acquisition

practices,

development

practices

Commitment-

building

practices

Networking

practices

Years of

education

and

experience

Employee

motivation

Sales growth

Continued

2012 1289Jiang, Lepak, Hu, and Baer

APPENDIX

(Continued)

Study

Skill-

Enhancing

HR Practices

Motivation-

Enhancing

HR Practices

Opportunity-

Enhancing

HR Practices

Human

Capital

Employee

Motivation Turnover

Operational

Outcomes

Financial

Outcomes

Colvin, Batt,

and Keefe

(2005)

Variable pay,

internal

promotion,

average pay

Problem-

solving

groups,

self-

directed

teams

Average

education

Quit rate Discipline

rate

Datta,

Guthrie, and

Wright (2005)

Productivity Sales growth

De Winne and

Sels (2010)

Selection,

training

Group-based

appraisal

and

performance

Participation Percentage of

highly

educated

employees

Innovation

Delaney and

Huselid

(1996)

Staffing

selectivity,

training

Incentive

compensation,

internal

labor

market

Grievance

procedure,

decentralized

decision

making

Perceived

market

performance

Delery and

Doty (1996)

Training Appraisals,

job

security,

career

opportunities,

profit

sharing

Participation Innovation Return on

assets, return

on equity

Delery, Gupta,

Shaw,

Jenkins, and

Ganster (2000)

Pay and

benefits

Voice

mechanisms

Quit rate

Den Hartog

and Verburg

(2004)

Employee

skills and

direction

Pay-for-

performance,

profit

sharing,

profit

sharing,

performance

evaluation

Autonomy,

information

sharing

meetings

Voluntary

turnover

Overall

operational

performance

Economic

outcome

Ericksen

(2006)

Workforce

alignment

Voluntary

turnover

Sales growth

Faems, Sels,

De Winne,

and Maes

(2005)

Selection,

training

Career

management,

compensation,

performance

management

Participation Voluntary

turnover

Productivity Value added

Fey and

Björkman

(2001)

Training and

development

Pay and

performance

appraisal

Information

sharing and

complaint

resolution

Overall

financial

performance

Fey,

Björkman,

and

Pavlovskaya

(2000)

Training Performance

based

compensation,

job

security,

career

planning,

salary level

Decentralization,

complaint

resolution

Overall

financial

performance

Gardner,

Wright, and

Moynihan,

(2011)

Skill HR

practices

Motivation

practices

Empowerment

practices

Education

level

Affective

commitment

Voluntary

turnover

Gelade and

Ivery (2003)

Staffing,

professional

development

Job design General climate Staff retention Customer

satisfaction,

clerical

accuracy

Overall

financial

performance

Gerhart and

Milkovich

(1990)

Pay and

incentive

Education,

experience

Return on

assets, sale

Ghebregiorgis

and Karsten

(2007)

Recruitment,

selection,

training,

development

Compensation Voluntary

turnover

Productivity

Gibson,

Porath,

Benson, and

Lawler (2007)

Team,

information

sharing,

boundary

setting

Customer

service,

quality

Overall

financial

performance

Gong, Chang,

and Chueng

(2010)

Selective

hiring,

extensive

training

Pay

contingent

performance,

career

planning,

performance

appraisal

Participation

in decision

making

Collective affective

commitment,

collective organ-

izational

citizenship

behavior

Gong, Law,

Chang, and

Xin (2009)

Selective

hiring,

extensive

training

Employment

security,

pay

contingent

performance,

career

development,

performance

appraisal

Participation

in decision

making

Affective

commitment

Overall

financial

performance

Continued

1290 DecemberAcademy of Management Journal

APPENDIX

(Continued)

Study

Skill-

Enhancing

HR Practices

Motivation-

Enhancing

HR Practices

Opportunity-

Enhancing

HR Practices

Human

Capital

Employee

Motivation Turnover

Operational

Outcomes

Financial

Outcomes

Guerrero and

Barraud-

Didier (2004)

Training Performance-

based

compensation,

stock,

benefit

Teamwork,

information

sharing

Work climate Productivity

and service

quality

Profitability

Guest, Michie,

Conway, and

Sheehan

(2003)

Voluntary

turnover

Labor

productivity,

quality of

goods and

service

Profitability,

Tobin’s Q,

return on

investment

Guest,

Conway, and

Dewe (2004)

Selection

tests,

recruitment,

training

and

development

Performance

appraisal,

performance-related

pay,

employee

security

Employee

involvement,

information,

equal

opportunities,

job design,

teamwork

Employment

relations

Voluntary

turnover

Innovation

Guthrie (2000) Selection Pay,

incentive,

profit

sharing

Voluntary

turnover

Guthrie (2001) Retention rate Productivity

Harel and

Tzafrir (1999)

Recruitment,

selection,

training

Incentive

compensation,

internal

labor

market

Participation,

grievance

procedure

Overall

operational

performance

Market

performance

Harrell-Cook

(1999)

Voluntary

turnover

Productivity Return on

assets, return

on equity,

return on

sales

Hatch and

Dyer (2004)

Screening

test,

training

Team

involvement

Voluntary

turnover

Heffernan,

Harney,

Cafferkey, and

Dundon

(2009)

Organizational

climate,

Volunteer

turnover

Innovation Overall

financial

performance

Hong (2009) Human

capital

Room

occupancy

Revenue, gross

operating

profit

Huselid

(1995)

Employee

skills

practices

Employee

motivation

practices

Voluntary

turnover

Productivity Tobin’s Q,

return on

assets, sales

growth

Iverson and

Zatzick (2011)

Employee morale Labor

productivity

Kalleberg and

Moody (1994)

Training Compensation Decentralization Employee relations Employee

retention

Product,

service

Market

Katou and

Budhwar

(2006)

Recruitment,

selection,

training

and

development

Reward and

relations

Skills Attitudes Voluntary

turnover

Overall

financial

performance

Katz, Kochan,

and Weber

(1985)

Participation

suggestion

programs

Employee attitudes Labor

efficiency,

quality of

product

Kepes, Delery,

and Gupta

(2009)

Performance-

based pay,

pay level

Accident

frequency

ratio, out-

of-service-

percentage,

operating

ratio

Return on

equity

Khatri (2000) Structured

interviews,

employment

tests,

training

Benefits,

performance-based

compensation,

performance

appraisal

Employee

participation,

planning

Non-financial

performance

Profitability,

sales growth

Kim and Gong

(2009)

Group-based

pay

Tacit

knowledge

Organizational

citizenship

behavior

Tobin’s Q,

return on

assets

Kintana,

Alonso, and

Olaverri

(2006)

Staffing,

training

Pay level,

security,

incentive

Job rotation,

team,

communication

Overall

operational

performance

Kirkman and

Rosen (1999)

Job satisfaction,

organizational

commitment

Productivity,

customer

service

Lee and Chee

(1996)

Selection,

training

Incentive pay,

pay

contingent

upon

performance

Information

flow,

information

change,

involvement

Return on

equity, return

on assets,

value added,

sales growth

rate

Lee and

Miller (1999)

Training and

education

Compensation,

profit

sharing

Return on assets

Continued

2012 1291Jiang, Lepak, Hu, and Baer

APPENDIX

(Continued)

Study

Skill-

Enhancing

HR Practices

Motivation-

Enhancing

HR Practices

Opportunity-

Enhancing

HR Practices

Human

Capital

Employee

Motivation Turnover

Operational

Outcomes

Financial

Outcomes

J. Li (2003) Staffing,

training

Group

incentive,

internal

labor

market

Job

enrichment,

grievance

procedure

Overall

operational

performance

Market

performance

Y. Li (2003) Average

salary

Proportion of

university

graduates

Voluntary

turnover

Return on

assets, sale

per employee

Liao (2005) Staffing,

training

and

development

Performance

appraisal,

rewards

contingent

upon

performance

Overall

financial

performance

Liao and

Chuang (2004)

Training Performance

incentives

Employee

involvement

Service climate Service

performance,

service

quality,

customer

satisfaction

and loyalty

Liao, Toya,

Lepak, and

Hong (2009)

Human

capital

Empowerment,

extrinsic

motivation, POS

Customer

satisfaction

Liouville and

Bayad (1998)

Social

performance

Overall

operational

performance

Economic

performance

Litz and

Stewart (2000)

Training Productivity

Lopez-

Cabrales,

Perez-Luno,

and Cabrera

(2009)

Knowledge-

based

practices

Collaborative

practices

Innovation

Lui, Lau, and

Ngo (2004)

Selective

hiring,

development

Career

development,

performance-based

compensation

MacDuffie

(1995)

Work systems

index

Labor

productivity,

quality

Mavondo,

Chimhanzi,

and Stewart

(2005)

Innovation,

operating

efficiency

Marketing

effectiveness,

financial

performance

McClean and

Collins (2011)

Employee effort Overall

operational

performance

Miah and

Bird (2007)

Hiring,

training

and

development

Organizational

climate

Voluntary

turnover

Growth rate

Minbaeva,

Pedersen,

Björkman,

Fey, and Park

(2003)

Training Performance

appraisal,

promotion,

performance-based

compensation

Communication Employees’

ability

Employees’

motivation

Neal, West,

and Patterson

(2005)

Organizational

climate

Productivity

Ngo, Lau, and

Foley (2008)

Employee relations

climate

Overall

operational

performance

Overall

financial

performance

Ngo, Turban,

Lau, and Lui

(1998)

Structural

training

and

development

Compensation Employee

satisfaction

Employee

retention

Sales, net profit

Noble (2000) Performance-

based pay,

job security

Teams,

consultation

Commitment Productivity

Nowicki

(2001)

Pay and

benefit,

performance

evaluation

Communication,

suggestions

for

improvement

Job satisfaction Voluntary

turnover

Revenue

Park,

Mitsuhashi,

Fey, and

Björkman

(2003)

Employee

skill

Attitudes,

motivation

Patterson,

West, and

Wall (2004)

Skill

enhancement

Job

enrichment

Productivity Profit

Paul and

Anantharaman

(2003)

Selection,

training

Performance

appraisal,

compensation,

career

development,

employee

ownership

Job design,

teamwork

Competence Organizational

commitment

Employee

retention

Productivity,

quality,

speed of

delivery

Financial

performance

Continued

1292 DecemberAcademy of Management Journal

APPENDIX

(Continued)

Study

Skill-

Enhancing

HR Practices

Motivation-

Enhancing

HR Practices

Opportunity-

Enhancing

HR Practices

Human

Capital

Employee

Motivation Turnover

Operational

Outcomes

Financial

Outcomes

Perry-Smith

and Blum

(2000)

Staffing

selectivity,

training

effectiveness

Incentive

compensation,

benefits

Grievance

procedures,

decentralized

decision

making

Market

performance,

profit-sales

growth

Rodwell and

Teo (2008)

Selective

staffing,

comprehensive

training

Performance

appraisal

Organization’s

commitment to

employees

Market

performance

Rogg,

Schmidt,

Shull, and

Schmitt

(2001)

Training,

hiring,

testing

Performance

review

Job

description

Employee

commitment

Customer

service

Russell,

Terborg, and

Powers (1985)

Training Productivity

Shaw, Delery,

Jenkins, and

Gupta (1998)

Training,

selection

ratio,

selection

procedures

Average pay,

benefits,

performance

appraisal,

procedural

justice, job

stability

Electric

monitoring

Quit rates

Shaw, Dineen,

Fang, and

Velella (2009)

Selective

staffing

Quit rates

Shaw, Gupta,

and Delery

(2005)

Voluntary

turnover

Productivity,

accident

rate,

operating

ratio

Revenue, return

on equity

Shih, Chiang,

and Hsu

(2006)

Job security Overall

financial

performance

Singh (2004) Selection,

training

Performance

appraisal,

compensation

system,

career

planning

Employee

participation,

job

definition

Market

performance

Skaggs and

Youndt (2004)

Human

capital

Return on

equity, return

investment

Snell and

Youndt (1995)

Staffing,

training

and

development

Performance

appraisal,

performance-based

reward

Return on

assets, sales

growth

Stavrou

(2005)

Job design Voluntary

turnover

Steingruber

(1996)

Training Return on assets

Stup (2006) Training,

selection

Performance

review,

incentives,

benefits

Written job

descriptions,

communication,

participation

Organizational

commitment

Subramony,

Krause,

Norton, and

Burns (2008)

Compensation Employee morale Productivity,

customer

satisfaction

Sun. Aryee,

and Law

(2007)

Organizational

citizenship

behavior

Voluntary

turnover

Productivity

Takeuchi,

Lepak, Wang,

and Takeuchi

(2007)

Human

capital

Social exchange

relationship

Tzafrir

(2005a)

Selection,

training

Incentive

compensation,

internal

labor

market

Employee

participation

Overall

operational

performance

Market

performance

Tzafrir

(2005b)

Training Evaluation,

compensation,

internal

labor

market

Participation Trust Overall

operational

performance

Market

performance

Veld, Paauwe,

and Boselie

(2010)

Performance

management

Communication,

autonomy,

information

sharing

Education

level

Commitment

Vlachos

(2008)

Selective

hiring,

training

and

development

Compensation,

job security

Decentralization,

information

sharing

Product

quality

Market share,

sales

Way (2002) Extensiveness

of staffing,

formal

training

Group-based

performance

pay, pay

level

Job rotation,

self-

directed

teams,

involvement

Voluntary

turnover

Labor

productivity

Continued

2012 1293Jiang, Lepak, Hu, and Baer

APPENDIX

(Continued)

Study

Skill-

Enhancing

HR Practices

Motivation-

Enhancing

HR Practices

Opportunity-

Enhancing

HR Practices

Human

Capital

Employee

Motivation Turnover

Operational

Outcomes

Financial

Outcomes

Welbourne

and Andrews

(1996)

Training Organization-

based

rewards

Tobin’s Q

White (1998) Incentives,

compensation,

job security

Participation Productivity

Whitener

(2001)

Staffing,

training

Appraisal,

rewards

Perceived organiza-

tional support,

trust, organiza-

tional

commitment

Wood,

Holman, and

Stride (2006)

Selection

tests,

training

Performance

appraisal,

internal

career

opportunity

Work design,

teams,

flexible

work

Employee

quitting,

unauthorized

absence

Productivity,

customer

satisfaction

Wright,

Gardner,

Moynihan,

and Allen

(2005)

Commitment Productivity,

quality

Profitability

Wright,

McCormack,

Sherman, and

McMahan

(1999)

Selection,

training

Compensation,

appraisal

Participation Employee

skills

Employee

motivation

Overall

financial

performance

Yang and Lin

(2009)

Recruiting

and

selection,

training

and

development

Performance

appraisal,

compensation

Human

capital

Overall

operational

performance

Youndt (1997) Human

capital

Returns, sales

growth

Youndt and

Snell (2004)

Acquisition

practices,

developmental

practices

Egalitarian HR

practices,

documentation

practices

Human

capital

Overall

financial

performance

Zacharatos,

Barling, and

Iverson (2005)

Selective

hiring,

training

Employment

security,

contingent

compensation

Teams,

information

sharing, job

quality

Zhu, Chew,

and Spangler

(2005)

Selection,

training

Compensation Planning Sales

1294 DecemberAcademy of Management Journal

Influence High-Performance Work Systems and Knowledge Management Process on Open Innovation, The Mediator Effect Knowledge Worker Productivity

Article

Sep 2023

Psychological need satisfaction across work and personal life: an empirical test of a comprehensive typology

Article

Full-text available

Sep 2023

Introduction A comprehensive typology of the satisfaction of psychological needs at work and in personal life was developed and tested. The typology proposes five scenarios ( Enriched, Middling, Impoverished, Work-Fulfilled, and Personal Life-Fulfilled ) accounting for various profiles of employees showing distinct configurations of global and specific levels of need satisfaction at work and in personal life. Methods The scenarios were tested in a sample of 1,024 employees. Results Using latent profile analysis, five profiles were identified that were consistent with four or the five scenarios, either aligned ( Globally Satisfied, Globally Unsatisfied ) or misaligned ( Globally Satisfied at Work with High Relatedness, Globally Satisfied in Personal Life with High Autonomy, and Globally Satisfied in Personal Life with Low Autonomy ) across domains. No profile corresponding to the Middling scenario was observed. Discussion The results indicate that perceived job and individual characteristics predicted membership in distinct profiles. More importantly, unlike the profile Globally Unsatisfied , the profile Globally Satisfied contributed substantially to higher well-being (vitality and lower psychological distress), and to more favorable job attitudes (job satisfaction and lower turnover intentions) and behaviors (self-rated job performance and lower absenteeism, presenteeism, and work injuries). Furthermore, two of the misaligned profiles were also substantially associated with highly desirable outcome levels.

The Value of Employee Engagement to Enhance Work Performance and Customer Service in Public Libraries

Chapter

Nov 2019

The organizational culture of a public library plays an important role in the successful achievement of its purpose and mission. Effectively serving patrons and the larger community is an overarching strategic goal of public library systems, and public library leaders who are supportive of workers and committed to promoting a culture of employee engagement hold the potential for enjoying numerous positive individual and organizational outcomes such as effective service work performance and increased customer service and satisfaction. This chapter highlights the benefits of fostering an environment of employee engagement and its enhancement on service work performance and customer service in public libraries.

The path analysis of entrepreneurship impacts on circular economy in emerging markets: a mediating role of digital technology

Article

Sep 2023
MANAGE DECIS

Purpose The purpose of this article is to explore the impact of the firm's entrepreneurship for the transformation of circular economy (CE). The role of entrepreneurship is thought to be important for the process of four Rs in the CE, and the authors have tried to study the role and impact path of entrepreneurship in CE. Design/methodology/approach Empirical data from Chinese listed firms are collected, and a measure of digital technology is constructed by text mining method. Mediation analysis method is used to test the proposed hypothesis. Findings The results show that the innovation entrepreneurship has a significant positive impact upon the CE and digital technology is playing a mediating role in the impact path. However, the business entrepreneurship is negatively affecting the CE adoption. Also, the proportion of shares hold by the institution has a heterogenous influence for the innovation entrepreneurship. Practical implications This study guides policy makers about the role of entrepreneurship and the mediating effect of digital technology and to encourage the adoption of CE for firms. Originality/value This study reveals the mediation effect of digital technology in the impact of entrepreneurship on CE in the emerging market. The heterogeneity of the proportion of shares hold by the institutions is also analyzed in the empirical study.

Idiosyncratic Deals and Organizational Performance: A Study of the Indian Travel Intermediaries Industry

Chapter

Jan 2019

The purpose of this study is to examine the mediating mechanism of idiosyncratic deals (i-deals) content (e.g., task, career, flexibility) in the relationship between core self-evaluations - CSE (e.g., efficacy, esteem, stability, locus of control), employee outcomes (e.g., motivation, commitment, work engagement and organizational citizenship behavior), and the mediating mechanism of employee outcomes in the relationship between i-deals and organizational performance (e.g., productivity, growth, creativity). The hypotheses of the study were tested with the application of structural equation modelling on data collected from 141 employees working in 17 companies operating in the Indian travel intermediaries industry. The findings show that i-deals content positively and partially mediate the relationship between CSE and employee outcomes, and employee outcomes positively and fully mediate the relationship between i-deals content and organizational performance. Implications of the findings for both research and practice are discussed.

FLEXIBLE WORK ARRANGEMENT AND EMPLOYEE PERFORMANCE; A CASE OF LAKE VICTORIA NORTH WATER WORKS DEVELOPMENT AGENCY

Article

Oct 2021

STRATEJİK BEŞERİ SERMAYE ALANININ ORTAYA ÇIKIŞI: ORTAK-ATIF ANALİZİThe Emergence of the Strategic Human Capital Field: A Co-Citation Analysis

Article

Sep 2023

İsmail Çağrı DOĞAN

Bu çalışmada strateji ve insan kaynakları yönetimi alanlarının ortasında doğmuş Stratejik Beşeri Sermaye’nin bir alt çalışma alanı olarak varlığının tespit edilmesi amaçlanmıştır. Sonrasında ise işletme biliminin en önde gelen dergilerinde Stratejik Beşeri Sermaye başlığı ile yayınlanmış makaleler temel alınarak bu alanın entelektüel yapısının analiz edilmesi hedeflenmiştir. Dile getirilen çalışmaların yapılabilmesi için dünyada en çok değer görmüş işletme bilimi dergilerinde yani İşletme Okulları Birliği Akademik Dergi Kılavuzuna (ABS/4*-4-3) toplam 472 makale tespit edilmiş ve bu makaleler atıf ve ortak-atıf analizi bibliyometrik analiz yöntemleri kullanılarak analiz edilmiştir. Atıf ve ortak atıf analizlerinin sonucu olarak beşeri sermaye alanının 2018 yılı sonrasında strateji ve stratejik insan kaynakları yönetimi alanlarından bağımsız bir bilimsel araştırma alanı olarak ortaya çıktığı tespit edilmiştir. Araştırmanın bulguları dâhilinde Stratejik Beşeri Sermaye çalışmalarının bireylerin bilgi, beceri tecrübeleri gibi özelliklerinin hangi işletme seviyesinde (birey, takım veya firma) tartışılması gerektiği ve bu özelliklerin nasıl sürdürülebilir rekabet avantajına dönüştürülebileceği konularında yoğunlaştığı tespit edilmiştir. Son olarak alanla ilgili yapılabilecek diğer çalışmalarla ilgili yönlendirmeler yapılmıştır.

The differential effects of human resource management on organizational innovation: a meta-analytic examination

Article

Sep 2023
INT J MANPOWER

Purpose This meta-analytical review aims to clarify the relationships between three bundles of human resource management (HRM) practices—competency-enhancing, motivation-enhancing and opportunity-enhancing—and organizational innovation by addressing two questions: (a) Which types of HRM bundles are most strongly related to different forms of innovation (i.e. process and product innovation)? And (b) Which mechanism provides a stronger explanation for the positive effects of HRM bundles on innovation? Design/methodology/approach Based on data from 103 studies, a meta-analysis was conducted to quantitatively summarize existing HRM–innovation studies at the organizational level. Findings The results showed that the competency-enhancing bundle was more positively related to product innovation than the motivation-enhancing and opportunity-enhancing bundles. The opportunity-enhancing bundle was most strongly associated with process innovation. The authors further found that knowledge management capability (KMC) and employee motivation mediated the positive relationship between the three HRM bundles and innovation outcomes. In comparing the two mechanisms, this review suggests that KMC better explains both the impact of the competency-enhancing HRM bundle on product innovation and the effect of the opportunity-enhancing bundle on process innovation. Originality/value Based on behavioral and knowledge management perspectives, this study takes a sub-bundle approach to providing an integrative review by comparing the direct effects and mediating paths of HRM bundles on product and process innovation.

Self-control and emotional exhaustion: mediating role of effort-reward imbalance and emotional demands

Article

Sep 2023
Int J Organ Anal

Purpose The purpose of this paper is to study the relationship between trait self-control (TSC) and emotional exhaustion, and to examine the mediating role of effort–reward imbalance (ERI) and emotional demands. Design/methodology/approach A quantitative study was conducted using data from 441 employees working in different organizations in the information technology sector in India. PROCESS macro with a bootstrap sample size of 5,000 was used for mediation analysis. Findings TSC demonstrated a significant negative relationship with emotional exhaustion. Results indicated the crucial role played by ERI and emotional demands in influencing the emotional exhaustion of employees with higher TSC. Originality/value This study adds substantially to our knowledge of the role of TSC in employee experiences of emotional exhaustion. Results suggest how employees’ ERI perceptions and experiences of emotional demands determine whether higher TSC would reduce experiences of exhaustion. This adds to the knowledge of positive outcomes of self-control while throwing some light on why the use of self-control does not always incur a psychological cost, as suggested by some studies. The findings suggest that self-control is an individual resource that has the ability to alleviate emotional exhaustion through its influence on employees‘ effort–reward perceptions and experiences of emotional demands.

Review and Prospect of Human Capital Research Based on Knowledge Mapping

Chapter

Sep 2023

Shuyu Guo

Technical and Strategic Human Resources Management Effectiveness as Determinants of Firm Performance

Article

Full-text available

Feb 1997

The Impact of Human Resource Management Practices on Perceptions of Organizational Performance

Article

Full-text available

Aug 1996

Methods of Meta-Analysis

Book

Jan 2004

Human resource management and performances: proposition and test of a causal model

Article

Aug 1998

This research aims at clarifying the links which may exist between human resource management practices and economic performance of firms. To this end, a theoretical model of an exploratory nature is proposed, based on the hypothesis of the existence of cascading relationships between three categories of performance: social, organizational and economic. The model is applied to a sample of almost 300 French small and mid-sized firms. The principal hypotheses put forth within the context of this study are to a large degree validated. This allows the formulation of interesting recommendations for managers and opens new ways for scholars pursuing this line of research.

An Organization-Level Analysis of Voluntary and Involuntary Turnover

Article