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How Does Human Resource Management Influence Organizational Outcomes?

A Meta-Analytic Investigation of Mediating Mechanisms

Article  in  The Academy of Management Journal · December 2012

DOI: 10.5465/amj.2011.0088

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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.

� Academy of Management Journal 2012, Vol. 55, No. 6, 1264–1294. http://dx.doi.org/10.5465/amj.2011.0088

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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

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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-

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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

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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.

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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-

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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

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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 � � rxiyj

�n � n�n �1� r�xixj�m � m�m �1� r�yiyj .

If it is assumed that x represents 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); n and m are 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 Q homogeneity 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 Q statistic indicates the variance in the sample-weighted mean correla- tion; a significant Q suggests 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 (�2), 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 (R2) 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 (�2[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: ��2[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[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: ��2[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[2] � 10.54, p � .01). The

TABLE 1 Meta-analytic Correlations between HR Dimensions and Organizational Outcomesa

Variables 1 2 3 4 5 6 7

1. Skill-enhancing practices 2. Motivation-enhancing practices (r, rc) .38, 46

k (N) 55 (14,670) 95% CI .40: .53 Q 822.75**

3. Opportunity-enhancing practices (r, rc) .38, 47 .37, 44 k (N) 49 (13,079) 50 (13,740) 95% CI .40: .53 .37: .52 Q 557.95** 855.49**

4. Human capital (r, rc) .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 Q 133.88** 175.97** 23.58*

5. Employee motivation (r, rc) .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 Q 63.23** 148.79** 183.61** 111.91**

6. Voluntary turnover (r, rc) �.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 Q 142.39** 213.38** 384.16** 130.46** 208.62**

7. Operational outcomes (r, rc) .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 Q 436.07** 626.61** 354.35** 108.92** 142.24** 189.14**

8. Financial outcomes (r, rc) .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 Q 247.07** 384.70** 130.73** 32.04** 206.61** 181.60** 547.24**

a The mean sample-size-weighted correlation (r) and mean sample-sized-weighted correlation corrected for attenuation due to unreli- ability (rc) 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 (rc). Q is the chi-square-test for the homogeneity of corrected correlations (rc) across studies.

* p � .05 ** p � .01

TABLE 2 Results of Differential Effects of HR Dimensions on Human Capital and Motivation-Related Attitudesa

Predictors

Human Capital Employee Motivation

� t %R2 � t %R2

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 R2 .22 .25 Z, A�M 2.74** �8.64** Z, A�O 8.68** �7.07**

a Standardized coefficients are presented. Z is 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 Modelsa

Models �2 df ��2 CFI RMSEA SRMR AIC

Three HR dimensions Theoretical model (Figure 1) 264.82 9 .98 .09 .04 318.32 Alternative model 1b 269.47 10 4.65*c .98 .08 .05 321.47 Alternative model 2d 188.76 8 80.71**e .98 .08 .03 244.76 Alternative model 3f 190.32 9 1.56e .98 .07 .03 244.32 Alternative model 4g 179.78 7 10.54**e .99 .08 .03 237.78 Alternative model 5h 180.54 8 0.76e .99 .08 .03 236.54 Alternative model 6i (Figure 2) 130.32 6 50.22**e .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 7j (Figure 4) 406.51 14 147.72**k .96 .09 .03 450.51

a n � 3,724. b Deletes the direct paths from opportunity-enhancing HR practices to financial outcomes. c Model fit compared with the theoretical model of the effects of three HR dimensions on organizational outcomes (Figure 1). d Adds the direct paths from skill-enhancing HR practices to voluntary turnover and operational outcomes. e Model fit compared with the previous model. f Deletes the direct paths from skill-enhancing HR practices to voluntary turnover. g Adds the direct paths from motivation-enhancing HR practices to both voluntary turnover and operational outcomes. h Deletes the direct path from motivation-enhancing HR practices to operational outcomes. i Adds the direct path from opportunity-enhancing HR practices to voluntary turnover and operational outcomes. j Adds the direct path from HPWS to both voluntary turnover and operational outcomes. k 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: ��2[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[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 (Z varied 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., R2s) 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 Outcomesa

Human Capital R2 = .22

Employee Motivation

R2 = .25

Voluntary Turnover R2 = .18

Operational Outcomes R2 = .22

Skill-Enhancing HR Practices

Motivation- Enhancing HR

Practices

Opportunity- Enhancing HR

Practices

Financial Outcomes R2 = .26

.05**

.29**

.07**

.21**

.29**

.13**

.07**

.25**

–.20**

.16**

–.34**

.26**

–.08**

.43**

.12**

.07**

.11**

–.05**

.46**

.44**

.47**

a 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 (�2[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 Outcomesa

.67**

Skill-Enhancing HR Practices

Motivation- Enhancing HR

Practices

Opportunity- Enhancing HR

Practices

Human Capital R2 = .34

Employee Motivation

R2 = .38

Voluntary Turnover R2 = .15

Operational Outcomes R2 = .22

Financial Outcomes R2 = .27

High Performance

Work Systems

.67**

.64**

.58**

.62**

.21**

–.10**

.03

–.28*

.16**

–.05**

.37**

–.08*

.34** a 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.

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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 ([email protected]) 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 ([email protected]) 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 ([email protected]) 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 ([email protected]) 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 on 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 HR practices

Empowerment HR 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 on 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 on 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 in 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, HR 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 on 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 HR practices, developmental HR practices

Egalitarian HR practices, documentation HR 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

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