Darko Milosevic, Dr.rer.nat./Dr.oec.

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The Roles of National Culture and Managerial Discretion



A Meta-Analysis of Country Differences in the High Performance Work System-
Business Performance Relationship:
The Roles of National Culture and Managerial Discretion
High performance work practices (HPWPs) are human resource (HR) practices designed to increase business performance by enhancing employee ability, motivation, and opportunity to contribute (AMO). HPWPs include, for example, selectivity in staffing, investments in training, pay for performance, and employee participation in decisions
(Becker & Huselid, 1998; Boxall & Purcell, 2003; Combs, Liu, Hall, & Ketchen, 2006; Delery & Shaw, 2001). A high performance work system (HPWS) includes combinations or bundles of multiple HPWPs that are hypothesized to create mutually reinforcing, synergistic effects (Appelbaum, Bailey, Berg, & Kalleberg, 2000; Barney & Wright, 1998; Chadwick, 2010; Huselid, 1995; Ichniowski, Shaw, & Prennushi, 1997; Lado & Wilson, 1994;
MacDuffie, 1995; Ramsay, Scholarios, & Harley, 2000; Wright, Dunford, & Snell, 2001; Wright & Snell, 1998). Research has documented a positive and meaningful relationship between the use of HPWSs and business (establishment, firm) performance (Arthur, 1994;
Becker & Huselid, 1998; Datta, Guthrie, & Wright, 2005; Huselid, 1995; Jiang, Lepak, Hu, & Baer, 2012; MacDuffie, 1995; Way, 2002; Youndt, Snell, Dean, & Lepak, 1996). For example, the Combs et al. (2006) meta-analysis reported a corrected correlation of .28 between HPWSs and business performance and showed that a one standard deviation increase in HPWSs was thus associated with a 126% increase in profitability. Further, Combs et al. (2006) also reported that most (roughly 70%) of the between-study variance in the effect size was not explained by statistical artifacts, suggesting there may be important substantive contextual moderators of the HPWS-business performance relationship.
The degree to which a body of theory and empirical evidence developed in one contextual setting can be generalized to others is a key question in management and applied


psychology broadly (e.g., Bamberger, 2008; Johns, 2006) and in strategic HR specifically
(e.g., Baird & Meshoulam, 1988; Dyer & Reeves, 1995; Lengnick-Hall & Lengnick-Hall, 1988; Miles & Snow, 1984; Schuler & Jackson, 1987; Wright & Sherman, 1999). In a global economy, an important question is whether HR practices that work in one country work the same in other countries. Our study provides the first systematic assessment of this question, based on 156 (including 108 non-United States) effect sizes from 35,767 firms/establishments.
Moderating Effects: National Culture and Managerial Discretion
Overview
That HR strategies, such as HPWSs, may not necessarily work the same everywhere, but instead depend on their fit with a country’s national culture and other country (e.g., institutional and/or legal) characteristics, is a core theoretical idea in the HR, strategy, and international management literatures (e.g., Adler, 2008; Aycan et al., 2000; Bae, Chen, Wan, Lawler, & Walumbwa, 2003; Brewster, 1995, 2007; Briscoe, Schuler, & Claus, 2009; Dowling, Festing,
& Engle, 2008; Evans, Pucik, & Barsoux, 2002; Ferner, 1999; Kostova, 1999; Kostova & Roth, 2002; Stahl & Björkman, 2006; Stavrou, Brewster, & Charalambous, 2010). Hofstede (1993) states that there are “cultural constraints in management theories” (p. 81), meaning that “not only practices but also the validity of theories may stop at national borders” (p. 82). In a similar vein, Brewster (1995) argues that what works in the United States may not work in Europe because of differences in institutional (especially greater legal/regulatory) pressures in Europe. As such, he called for a “European model of human resource management” (p. 1), and “exploring of the appropriateness of U.S. notions of HRM for adoption and institutionalization into European practice” (Lazarova, Morley, & Tyson, 2008, p. 1997) became a major research area. A similar debate about the transferability of HR strategies is taking place in the context of China, the world’s second largest economy, but not one of its most productive.[1] Tsui (2009) challenged scholars to consider which of two strategies would be more effective for management theory and practice in China: (1) applying existing North American based theory and evidence to the Chinese context or (2) developing new theories and corresponding streams of empirical research tailored specifically to the Chinese context.
To address the question of whether the HPWS-business performance relationship is moderated by country differences in national culture and other institutional factors, we rely primarily on national culture perspectives (e.g., Adler, 2008; Boyacigiller & Adler, 1991;
Hofstede, 1980, 1983, 1993, 2001; House, Hanges, Javidan, Dorfman, & Gupta, 2004; Johns, 2006; Newman & Nollen, 1996). National culture perspectives emphasize that national culture differences constrain or even dictate whether management practices such as HPWSs will be effective in different countries. Our conceptual framework additionally includes two aspects of managerial discretion (e.g., Crossland & Hambrick, 2011) as key country-level moderator variables: cultural tightness-looseness and institutional flexibility (defined primarily in terms of legal/regulatory constraints, with a focus on labor markets and labor unions).
National Culture
National culture has been defined as the “collective programming of the mind which distinguishes the members of one human group from another” (Hofstede, 1980, p. 25). National culture creates institutional/normative pressures for organizations to conform their management practices and cultures to a national model. Taras, Kirkman, and Steel (2010, p.
405) describe Hofstede’s (1980, 2001) work as “groundbreaking” and state that it has “inspired thousands of empirical studies” and that such studies are growing “exponentially”. Yet, they note that “conspicuously absent from … reviews is an attempt to provide a more quantitative examination of the empirical research” on national culture effects (p. 405). Taras et al.’s (2010) meta-analysis of 598 studies examined correlations between Hofstede’s culture scores and individual workplace attitudes and behaviors. However, they did not look at management practices or at unit or firm level outcomes such as performance. They also did not examine whether national culture moderates the effectiveness of HPWSs specifically or management practices in general, an important question that remains unanswered (Kirkman, Lowe, & Gibson, 2006).
As noted, Hofstede (1993) argues that national culture is an important moderator. He states that there are “cultural constraints in management theories” (p. 81), meaning that “not only practices but also the validity of theories may stop at national borders” (p. 82). In response to the classic standardization versus localization debate in the international management literature (Bartlett & Ghoshal, 1989; Hannon, Huang, & Jaw, 1995; Lillrank,
1995; Liu, 2004; Lu & Björkman, 1997; Perlmutter, 1969; Pudelko & Harzing, 2007; Rosenzweig & Nohria, 1994), Hofstede’s (2001) answer is clear: “For best results a multinational’s management practices should fit the local culture” (p. 441).
This fit logic is central to the national culture literature. Like Hofstede, Newman and Nollen (1996) emphasize that “national culture is a central organizing principle of employees’ understanding of work, their approach to it, and how they expect to be treated” (p. 755) and that fit occurs when management practices are “consistent” or “congruent” with employee expectations. In contrast, “when management practices are inconsistent with these deeply held [cultural] values, employees are likely to feel dissatisfied, distracted, uncomfortable, and uncommitted [and] as a result, they may be less able or willing to perform well” (Newman & Nollen, 1996, p. 755).
This use of the term fit is consistent with its use in the strategy literature, where it is also typically defined in terms of how “consistent” (using a priori theoretical logic) one or more components (e.g., strategy and environment) are (Nadler & Tushman, 1980, p. 45, cited in Ansari, Fiss, & Zajac, 2010, p. 73). By far the most typical way to assess an a priori hypothesized fit in the strategy literature (Boyd, Haynes, Hitt, Bergh, & Ketchen, 2012) is by estimating a statistical interaction between a strategy variable and a moderator variable such as the environment in predicting a criterion variable such as performance (Venkatraman, 1989). In our paper, the strategy is HPWS, the criterion is business performance, and the moderator is national culture.
To examine the influence of national culture as a moderator of the HPWS-business performance relationship, we followed advice to focus on a small number of “well-chosen dimensions” (Zaheer, Schomaker, & Nachum, 2012, p. 33) that, based on theory (e.g., Aycan,
2005; Early & Erez, 1997; Fischer & Smith, 2003; Gomez-Mejia & Welbourne, 1991;
Newman & Nollen, 1996; Peretz & Fried, 2012; Peretz & Rosenblatt, 2011; Schuler & Rogovsky, 1998), seem most relevant in understanding how HPWSs might be differentially effective in different countries.
As described below, national culture perspectives lead to the specific a priori prediction that the best fitting national culture for the success of an HPWS is one low on power distance, low on collectivism (i.e., high individualism), and high on performance orientation.[2] That is not to say that such a national culture is always a better fit with each and every aspect of an HPWS. However, based on accumulated theory and evidence, this specific national culture is expected a priori, on average, to better fit an HPWS and this stronger fit is, in turn, expected to result in higher HPWS effectiveness.
Power distance is “the degree to which members of a … society expect and agree that power should be shared unequally” (House et al., 2004, p. 537 and Table 17.2, p. 536). In high power distance cultures, not only are power, authority, and information unequally distributed, this hierarchy is also rigid and institutionalized (Hofstede, 2001; Peretz & Fried, 2012) and advancement to higher levels of the hierarchy is based on factors other than performance such as seniority, social class, family, or political connections (Early & Erez, 1997; Sturman, Shao, & Katz, 2012). Similarly, “reward allocation is based on criteria other than performance, such as seniority or being on good terms with management” (Aycan, 2005,
p. 1106) and “the performance-reward contingency is low” (Aycan, 2005, p. 1106). In addition, relatively few people have access to resources and information in high power distance cultures. As a result, hierarchy is reinforced and perpetuated (based on factors other than performance), making it difficult to involve a broad range of employees to participate in decisions, as well as hampering the use of performance in making promotion and pay decisions. The lack of emphasis on using and rewarding ability and skill in staffing decisions can translate into a workforce lacking in human capital (Ployhart & Moliterno, 2011) and performance. Thus, overall, a high power distance culture does not seem to be a setting that would enhance the effectiveness of HPWSs, which are designed to increase performance by enhancing workforce AMO.
In contrast, in low power distance cultures, ability, skills, and performance are expected to play a larger role in staffing, employee participation, and compensation. The de-
                                                 
is part of the GLOBE framework and, most important, its conceptual relevance seems clear given our focus on performance as a dependent variable.
emphasis on hierarchy and status in low power distance countries favors a high level of discretion and self-management that enables and encourages taking full advantage of employees’ input and participation to improve performance. Low power distance provides an environment that supports investment in the whole workforce’s training and development (Aycan, 2005; Coget, 2011; Peretz & Rosenblatt, 2011). Ability and performance, rather than seniority or social connections, play a more important role in selecting, developing, and motivating employees. Similarly, motivation-enhancing HPWS components such as pay for performance are likely to be more effective in low power distance countries (Aycan, 2005; Newman & Nollen, 1996). Consequently, the lower a country’s power distance, the stronger will be the HPWS-business performance relationship.
Collectivism reflects “the degree to which individuals express pride, loyalty, and interdependence in their families” (House et al., 2004, p. 463). The greater the in-group collectivism, the closer are the ties among group members and the stronger is people’s concern for others. Although that concern for and focus on the collective has the potential for some positive influences on HPWS effectiveness (e.g., for using teams and other participation in decision practices, especially when combined with lower power distance, Earley & Erez, 1997, Table 2.1, p. 27; Kirkman & Shapiro, 1997), there are also potential drawbacks. For example, in collectivist cultures, there is a norm of protecting reputations and avoiding social anxiety, which may cause unease with practices (performance appraisal/feedback, pay for performance) that recognize and differentiate employees on the basis of individual performance (Peretz & Fried, 2012). Selection and training/development decisions, like in high power distance societies, may give less weight to ability and performance and more weight to personal connections, in-group status, and social obligation
(House et al., 2004), which can lower performance.
In cultures low on collectivism (i.e., high on individualism), there is a stronger focus on “rationality” (House et al., 2004, p. 453), which translates into greater weight given in decisions to individual differences in ability, skills, and performance. Thus, HPWS components that aim to enhance employees’ ability such as training and development and selection are likely to be more effective in countries low on in-group collectivism (i.e., high on individualism) because there is greater acceptance of allocating opportunities based on individual ability and performance, rather than on the basis of group affiliation or status (Hofstede, 2001, Exhibit 5.3, pp. 226-227). Similarly, this emphasis on ability and performance as legitimate criteria also means a better fit with motivation-oriented HPWPs such as pay for performance (which use the equity/performance allocation rule rather than the equality or need rules that are more common in collectivist cultures) and thus greater effectiveness in low collectivism cultures (Early & Erez, 1997; Fischer & Smith, 2003;
Gomez-Mejia & Welbourne, 1991; Schuler & Rogovsky, 1998; Zhou & Martocchio, 2001). Low collectivism’s influence on the successful use of opportunity to contribute practices such as employee participation are less clear. On the positive side, low collectivism would be helpful because of the strong focus it places on individual responsibility (Newman & Nollen, 1996). On the other hand, high collectivism suggests that particular types of participation such as teams could work more effectively under high collectivism. An important caveat, however, is that teams, at least self-directed teams, must be able to carry out tasks formerly carried out by managers, including selection, work assignments/scheduling, and monitoring of individual performance. As noted above, making distinctions between individuals may be more difficult in collectivist cultures. On balance then, we expect that the lower the collectivism in a country, the stronger the HPWS-business performance link.
High performance orientation reflects “the extent to which a society is perceived to encourage and reward performance improvement” (House et al., 2004, p. 246) versus a focus on loyalty, harmony, and belongingness in low performance orientation cultures. Further, high performance orientation countries “emphasize results, set high performance targets, value taking initiative, and prefer explicit and direct communications” (House et al., 2004, p. 276). In contrast, in low performance orientation cultures, people “value social and family relations, loyalty, tradition, and seniority, and use subtle and indirect language” (House et al.. 2004, p. 276). Given the focus on results and performance in strongly performance-oriented cultures, HPWSs, with their focus on building performance through higher AMO, should be a strong fit and work especially well in such cultures (Aycan, 2005; Bae & Lawler, 2000; Coget, 2011; Peretz & Rosenblatt, 2011; Recht & Wilderom, 1998). Specifically, the use of pay for performance and making staffing decisions based on ability, skills, and performance should be a good fit. Also, the focus on direct communication in performance orientation cultures should facilitate the use and effectiveness of opportunity to contribute practices such as information sharing, teams, and other forms of employee participation in decisions. Based on the above discussion of national culture-based logic, when a country’s national culture is consistent with the cultural values of an HPWS, stronger business performance is expected: Hypothesis 1: The HPWS-business performance relationship will be more strongly positive in countries characterized by low power distance (H1a), low collectivism
(H1b), and high performance orientation (H1c).[3]
Managerial Discretion
Although the potential value of having management practices fit with/conform to national culture is the primary emphasis in mainstream national culture perspectives, at least some authors taking a national culture perspective (Gelfand, Nishii, & Raver, 2006) recognize that conformance is a choice, and that more conformance is not always better.
Indeed, Gelfand et al. (2006, Figure 1) identify “conformity vs. deviance” with respect to national culture as a key choice facing organizations. Likewise, Oliver (1991; see also Oliver, 1997) notes that institutional theory, which provides the broadest theoretical logic for the importance of institutional pressures and constraints such as national culture, has been called on to remedy “its lack of attention to the role of organizational self-interests and active agency” (p. 145) and further, to better recognize that the existence of institutional pressures toward conformity does not require the assumption that firms are “invariably passive and conforming to all institutional conditions” (p. 146). More recently, Heugens and Lander (2009) describe as a “central debate” in institutional theory literature the question: “Does conformity to institutional norms enhance or diminish organizational performance?” (p. 61). Thus, it is important to recognize that automatic conformance of HR practices to national culture norms is neither always inevitable nor necessarily always the most effective strategy.
The preceding discussion makes clear that managerial discretion must be incorporated into any conceptual treatment of whether a close fit between management practices and national culture is the best path to strong business performance. Managerial discretion plays a dominant role in strategic perspectives (Barney, 1991; Newbert, 2007; Wernerfelt, 1984) and related strategic HR perspectives (Barney & Wright, 1998; Dyer & Reeves, 1995; Lado & Wilson, 2004; Wright et al., 2001). In this vein, Cappelli and Crocker-Hefter (1996) observe that “there are examples in virtually every industry of highly successful firms that have very distinct management practices” (p. 7).
As we have seen, the role of managerial discretion is also recognized in at least some strands of institutional (e.g., Oliver, 1991, 1997) and national culture (Gelfand et al., 2006) perspectives. However, managerial discretion remains largely absent from mainstream national culture perspectives. As we have also seen, Hofstede (2001) takes a strong view that national culture constrains the effectiveness of management practices (and thus managerial discretion). Similarly, the GLOBE study (House et al., 2004) states that the “the major force shaping organizational practices is rooted in societal-level systems” (Brodbeck, Hanges, Dickson, Gupta, & Dorfman, 2004, p. 665) and that “organizations mirror societies from which they originate” (Javidan et al., 2004, p. 726).
Note that even if one accepts that organizations are compelled to conform, there is the complication that organizations have multiple constituents and their norms may conflict (Oliver, 1991). In the case of a multinational enterprise, for example, an organization would need to decide which national culture to conform to if cultural practice norms relating to HR differ in the host country and the home country (Kostova, Roth, & Dacin, 2008). Likewise, there may be one set of cultural/managerial practices within an industry in the home country, but a different set when looking at the full set of global competitors in that industry. This
“multiplicity of constituent demands” (Oliver, 1991) means that conforming to one norm (e.g., a global industry norm) may require it to be out of conformance with other norms (e.g., national culture norms). As such, managerial discretion must be exercised and “isomorphism
[with the norms of the local country] is not a necessary condition for legitimacy or survival”
(Kostova et al., 2008, p. 999).
Indeed, conforming to the (local) national culture norm could actually endanger survival if a new and different model is proving more successful for competing globally (e.g., in a particular industry). For example, Bae and Lawler (2000, p. 504) argued that, in Korea, “the pressures of globalization” made it necessary for firms to begin implementing HPWSs and that “cultural changes” necessarily followed that made workers and employers “more open” to such systems, despite the fact that Korea’s national culture was conventionally seen as having “important cultural traits that” would “undermine” the effectiveness of HPWSs. In other words, fit with the existing national culture in this case was not conducive to being competitive globally and, at some point, managerial discretion was required that looked past traditional fit with national culture (see related work by Gamble, 1993; Katz & Darbishire,
2000; Pudelko & Harzing, 2007; Quintanilla & Ferner, 2003.)
It seems likely that organizations, as a general rule, seek to achieve “strategic balance” (Deephouse, 1999) between conformance/fit and nonconformance/differentiation (Oliver, 1991, 1997). It also seems likely that organizations must balance achieving fit with the need to avoid a situation where inertia is so strong that it undermines the flexibility needed to achieve (dynamic) fit when the environment and/or competitive landscape changes (Teece, Pisano, & Shuen, 1997; Wright & Snell, 1998; Zajac, Kraatz, & Bresser, 2000). Such balance suggests the need to better incorporate the role of managerial discretion in our thinking. We focus on two specific aspects of managerial discretion as potential country-level moderators of the HPWS-business performance relationship: cultural tightness-looseness and institutional flexibility.
National culture tightness-looseness. Although most national culture perspectives and national culture research have focused on mean differences in institutional/cultural factors (see our hypothesis 1), work by Gelfand et al. (2006) demonstrates that variance in national culture, the tightness-looseness of national culture, may also be relevant. Cultural tightness-looseness reflects “the strength of social norms, or how clear and pervasive norms are within societies, and the strength of sanctioning, or how much tolerance there is for deviance from norms within societies” (Gelfand et al., 2006, p. 1226).
Our hypothesis 1, based on national culture perspectives, states that the HPWSbusiness performance relationship will be more positive in countries having a national culture consistent with an HPWS, and less positive in others. Here, we additionally make the case that hypothesis 1 is more likely to be supported in countries with tighter national cultures because in tight cultures, norms are stronger, tolerance for deviation from norms is less, and sanctioning for deviation from norms is stronger. In other words, managerial discretion is low. Our logic is similar to that of Taras et al. (2010), who found a significant moderating effect of cultural tightness-looseness such that national culture was more strongly predictive of individual workplace attitudes and behaviors in countries having tighter cultures, consistent with the idea that tighter cultures allow less room for individuals to deviate from societal norms. To the degree a similar process operates for firms, we would anticipate that tighter cultures not only provide less managerial discretion in choosing to use an HPWS if it does not fit the (mean) national culture, but also undermine the positive effects of an HPWS on business performance. Thus, the fit between an HPWS and national culture is more important in tight cultures.
Hypothesis 2: Cultural tightness-looseness will moderate the HPWS-business performance relationship, such that the relationship will be more positive in countries characterized by low power distance (H2a), low collectivism (H2b), and high performance orientation (H2c), when the national cultures are tighter.
Institutional flexibility. To complete the conceptual framework, it is necessary to incorporate stronger forms of institutional control than national culture. Oliver (1991) defines institutional control as “the means by which pressures are imposed on organizations” (p. 168). In contrast to national culture, the legal coercion form of institutional control is “legal or government mandates … imposed by means of authority rather than through pressures for voluntary compliance” (Oliver, 1991, p. 168). Oliver’s (1991) theory predicts that the typical organizational response to legal coercion is to acquiesce. According to Kostova (Kostova, 1999; Kostova et al., 2008), national culture captures the cognitive (shared schemas, frames, inferential sets, etc. that people use to process information) and normative aspects (values and norms) of how countries’ institutional environments differ, but it excludes the regulatory aspect (laws and rules) of country differences. Consistent with Oliver (1991), Kostova
(Kostova, 1999; Kostova et al., 2008) argues that, unlike in the case of national culture, firms have little discretion when it comes to complying with regulatory aspects of institutional pressure.
The importance of country differences in the regulatory environment is also emphasized in the comparative HR and industrial relations literatures (Björkman, Fey, & Park, 2007; Brewster, 1995, 1999, 2007; Freeman, Kruse, & Blasi, 2008; Paauwe & Boselie, 2003; Siegel & Larson, 2009; Sparrow & Brewster, 2006; Tregaskis & Brewster, 2006). Brewster (1999, p. 224), for example, highlights the following argument from Pieper (1990,
p. 8): “The major difference between HRM in the U.S. and Western Europe is the degree to which [HRM] is influenced and determined by [country differences in] regulations.”
We use the term institutional flexibility to capture country differences in regulatory and related constraints (e.g., centralized collective bargaining, inflexible labor markets) on employer discretion and flexibility. We define institutional flexibility as employer flexibility in hiring and firing practices (i.e., not impeded by laws/regulations), wage flexibility (i.e., not determined by regulation or centralized bargaining), and few legislative restrictions overall.
Unlike national culture norms, which may vary in how they constrain HPWS effectiveness based on how tightly these norms are adhered to, institutional (in)flexibility, with its strong regulatory/coercive control dimension, seems likely to constrain HPWS effectiveness much more systematically. If certain forms of pay for performance (e.g., stock options) are simply not legal or if rates of pay are set at the country or industry level, managerial discretion may not exist. Similarly, if a form of employee participation in decisions (e.g., codetermination in Germany or the Netherlands) is mandated by law, managerial discretion is limited. For employers wishing to implement certain HPWS practices even where managerial discretion is constrained, it may be necessary to invest substantial resources (time and money) to challenge legal restrictions and/or gain regulatory approval (and success is not assured). Thus, as Oliver (1991) notes, in the face of legal coercion or enforcement, the most likely strategic response is to acquiesce. Consequently, the heterogeneity among firms in HPWS use and effectiveness is less (more) likely where institutional flexibility is low (high).
Hypothesis 3: The higher the level of institutional flexibility in a country, the more positive the HPWS-business performance relationship.
Method
Sample
We searched for published and unpublished studies through March 2013 to include in our meta-analysis. We searched for articles with titles and abstracts in ABI/INFORM,
Business Source Premier/Complete, Google Scholar, JSTOR, ProQuest Dissertations and
Theses, ProQuest Dissertation Abstracts International, PsycINFO, PsycARTICLES, and
ScienceDirect databases using the terms “human resource management”, “human resource”,
“personnel”, “high performance work system”, “high performance”, “high involvement”, or
“high commitment” in combination with “performance”, “turnover”, or “productivity” in
English, as well as “Personalmanagement” or “HR-Praktiken” in combination with “Unternehmenserfolg” in German. The results from these searches were electronically screened for whether the terms “method” or “sample” and either “correlation” or “effect” appeared anywhere in the text of the article. We additionally searched for relevant in press articles across all journals from our literature search in which any research on the HPWSbusiness performance relationship had been published. We also searched for relevant articles in all available conference programs of the Academy of Management and the Society for Industrial and Organizational Psychology. In addition, we sent requests for unpublished manuscripts, working papers, conference papers, dissertations, and in press papers via the listservs of the following Academy of Management divisions: Business Policy and Strategy, Entrepreneurship, Health Care Management, Human Resources, International Management, Public and Nonprofit, and Technology and Innovation Management. We contacted all authors who had previously published on the HPWS-business performance relationship (based on the results of our literature search) to ask for any unpublished work that was relevant. We crosschecked these conference submissions, dissertations and working papers with papers already published and/or already included in our sample, and e-mailed the authors in cases where a full version of the article was not publicly available. Finally, we cross-checked our search results against previous meta-analyses and reviews related to our research topic (Boselie, Dietz, & Boon, 2005; Combs et al., 2006; Gmür & Schwerdt, 2005; Jiang et al., 2012;
Paauwe, 2004; Stock-Homburg, Herrmann, & Bieling, 2009; Subramony, 2009; Wright, Gardner, Moynihan, & Allen, 2005) and with Huselid’s (2003) summary of empirical studies from 1995 to 2003 that he provides on his homepage.
To be included in our meta-analysis, studies had to, first, measure and report the use of an HPWS or HR system. Studies focusing solely on individual HPWPs or HR practices were not included, unless the authors also examined the impact of an additive or multiplicative index of such practices. Also, studies examining the impact of broader strategic HR constructs (e.g., strategic HR effectiveness, HR-strategy fit) or other related constructs (e.g., role of HR department, downsizing practices) that did not represent the use of a system, bundle, or configuration of HR practices were excluded. Second, studies had to measure both HPWSs and operational or financial performance, and report effect size estimates at the firm- or establishment-level. Studies conducting analyses based on employee- or group-level measures of HPWSs and business performance were excluded, unless they were aggregated to the firm- or establishment-level prior to producing the effect size estimate. Studies not examining financial or operational business performance outcomes (e.g., job attitudes, occupational safety, and organizational citizenship behaviors) were also excluded even if the outcomes had been aggregated to the firm- or establishment-level prior


COUNTRY DIFFERENCES                                                                                                  19
to conducting analyses. Acceptable measures of business performance were either a) objective (e.g., market-to-book ratio, sales turnover), with data sourced from company archives or reported by executives and/or employees; or b) subjective ratings of performance (e.g., perceived organizational performance, perceived labor productivity). Measures of financial performance across studies in our sample included accounting returns, growth, and market returns, while measures of operational performance included productivity, quality, and retention. Certain studies included multidimensional measures of performance that were an aggregate of multiple financial and/or operational performance metrics. Third, studies had to report bivariate correlations for the HPWS-business performance relationship or an effect size statistic that could be converted to a bivariate correlation. Finally, studies based on samples of firms/establishments across multiple countries were excluded because this would require our coding of country characteristics (e.g., national culture) to vary within study rather than between studies. 
Applying these criteria resulted in a final sample of 156 studies representing 35,767 firms and establishments across 29 countries. Appendix A [not part of this pre-publication version] lists our sample of studies and information coded regarding each study. Online Supplement 1 provides detailed references for each study. Appendix B lists the countries in our sample along with country-level characteristics coded. Online Supplement 2 lists studies excluded from our meta-analytic sample and reasons for exclusion. In the description of our results, tables, appendices, and online supplements, N is the number of firms and establishments, K is the number of studies, and Ncountries is the number of countries.
Effect Sizes and Variables
Effect size. For each study in our sample, we coded the bivariate correlation coefficient estimate of the HPWS-business performance relationship, sample size (i.e., number of firms and/or establishments), as well as estimates of measurement error (e.g.,
inter-item reliability–alpha, inter-rater reliability–intraclass correlation) in both predictor and criterion variables. This information was coded by two of the authors for a sub-sample of 20 studies. Because the mean inter-rater agreement was 94%, and all disagreements were subsequently resolved through discussion, the task of coding the remaining studies was split between two of the authors. 
We contacted the authors of the original studies for any information that was not reported in the studies. When multiple correlation coefficient estimates were reported within a single study, for example between an HPWS and either measures of alternate business performance constructs or multiple measurements of the same business performance construct across time, a linear composite correlation (Hunter & Schmidt, 2004) was calculated using information reported in correlation matrices. If reliability estimates and sample sizes corresponding to each correlation coefficient within a study differed, we coded the arithmetic average of the multiple reliability estimates and the minimum of the multiple sample sizes. Multiple studies that had been published using the same dataset were treated as a single study by using an arithmetic average of the correlation coefficient estimates reported across these studies. In studies that used multiple types of HR systems composed of different bundles of practices, the bivariate correlations of each system with business performance were aggregated to create a single effect size estimate for the study, provided the items used in measuring the component practices in each system resembled the content of HPWSs. 
Moderators. For each study, we identified the country from which its sample of firms and/or establishments originated. Across countries represented in our sample, we coded information pertaining to the country-level characteristics of interest: (1) national culture, (2) cultural tightness-looseness, and (3) institutional flexibility.
National culture scores on power distance, collectivism (specifically, in-group collectivism), and performance orientation were obtained from the GLOBE study (House et al., 2004). We used the practices (“as is”) scales which range from 1 (low) to 7 (high). We chose to focus on practices (“as is”) rather than values (“should be”) because the national culture-related part of our theoretical framework focuses primarily on the normative/cognitive (national culture) and coercive (regulatory) institutional pressures organizations actually face when deciding whether to adopt management practices (in this case, HPWSs). Institutional and strategic perspectives also focus on the decision by organizations to conform or not conform to practices and strategies used by other organizations in their institutional fields and/or competitor groups. In addition, an examination of House et al.’s (2004) tables 16.9 (p. 475) and 17.6 (p. 543) reveals that the GLOBE practice scores are more strongly correlated with corresponding Hofstede (1980, 2001) national culture scores than the GLOBE value scores. For example, collectivism scores from Hofstede correlate .81 with the GLOBE in-group collectivism practices scale, but only .20 with the GLOBE in-group collectivism values scale.
Similarly, the GLOBE power distance practices and values scales have correlations of .57 and .03, respectively, with Hofstede’s power distance scale. Given that Hofstede’s work forms the primary theoretical basis for national culture perspectives, we feel it is important that our measures of national culture correspond not only conceptually, but also empirically with his work. We chose to use the national culture scores from GLOBE because they are based on more recent data than Hofstede’s scores (publication date of 2004 versus 1980), more closely corresponding to the time period during which most of the studies in our meta-analysis were conducted.
We obtained scores for cultural tightness-looseness from Gelfand et al. (2011, p. 1103). In our sample, scores range from 1.60 (Ukraine) to 11.80 (Malaysia), with higher scores corresponding to greater tightness of cultures (i.e., greater strength, clarity, and pervasiveness of cultural norms, and stricter sanctioning of deviation from norms).
Institutional flexibility was measured using three indicators from the Global Competitiveness Report 2010-2011 (World Economic Forum, 2010): 1) lack of burdensome government regulation (“How burdensome is it for businesses in your country to comply with government administrative requirements? [1 = extremely burdensome; 7 = not burdensome at all]”); 2) flexibility of wage determination (“How are wages generally set in your country? [1 = by a centralized bargaining process; 7 = up to each individual company]”); and 3) hiring and firing practices (“How would you characterize the hiring and firing of workers in your country? [1 = impeded by regulations; 7 = flexibly determined by employers]”). We constructed an overall institutional flexibility scale by summing the z scores of each dimension (α = .85). Scores on this index range between -3.82 (Italy) and 6.20 (Singapore), with higher scores indicating higher institutional flexibility.
Control variables. We included three industry categories (manufacturing, service, or mixed), level of analysis (firm versus establishment), and the composition of the HPWS as controls. For each HPWS, we measured the percentage of practices that fell into six areas: compensation, employee relations, performance management, training and development, promotion, and recruitment and selection. The mean inter-rater agreement for the information on the content of HPWSs coded by two of the authors across a subsample of 10 studies was 100%.
Analyses
We began our analyses by re-examining the HPWS-business performance relationship using the Hunter and Schmidt (2004) meta-analysis framework. Bivariate correlation coefficient estimates were aggregated across studies to generate the samplesize weighted overall average effect size (̅). Corrections were made for measurement error artifacts to obtain the weighted mean true score correlation (ρ) estimates. As internal consistency (coefficient alpha) for measures of the predictor (K = 108) and criterion (K = 64) variables were not reported by all studies, the artifact distribution method was used to correct for the attenuating effects of unreliability (due to items). The average internal consistency was .81 for HPWS measures and .82 for business performance measures. Estimates of inter-rater reliability in HPWS measures were even less commonly reported among studies (K= 13), and the average intraclass correlation was .36. Therefore, except in the case of the overall HPWS-business performance effect size estimate over all countries/regions (see Table 2), we did not have sufficient information to make corrections for rater measurement error.
To detect substantive moderators, we first employed the “75 percent rule” which suggests that moderators may be present whenever artifacts fail to explain 75% or more of the observed (uncorrected) variance in correlation coefficient estimates across studies (Hunter & Schmidt, 2004). Due to the tendency towards type-I error that is characteristic of this decision rule (Sagie & Koslowsky, 1993), 80% credibility intervals constructed around the true score correlation (ρ), and tests of homogeneity provided an alternative means of obtaining information regarding the true population variance of HPWS-business performance correlations. Additionally, we constructed 95% confidence intervals using the mean uncorrected correlation (̅) and its standard error to gain a sense of the precision of our metaanalytic estimates (Whitener, 1990).
We use hierarchical linear modeling (HLM) to examine moderating effects of the hypothesized country-level characteristics because the studies are nested within countries. Due to its implicit hierarchical structure and potential for random effects through heterogeneity in the mean corrected correlation, meta-analysis has been recognized as a special case of multilevel analysis (Hox, 2010; Hox & De Leeuw, 2003; Raudenbush & Bryk, 2002). We used HLM v.7.01 to construct three-level “variance-known” models (Raudenbush & Bryk, 2002, Chapter 7) with firms/establishments at level-1, studies at level2, and countries and between-country characteristics (e.g., national culture, institutional flexibility ) at level-3.[4] For each study in our sample, the level-1 sampling variance (σ²) of effect estimates is given by σ² = 1 / (Nj – 3), where Nj is the study sample size (i.e., number of firms and establishments) of the jth sample or study (Hox & De Leeuw, 2003, p. 93; Raudenbush & Bryk, 2002, p. 219). We entered the inverse of the sampling variance as nonnormalized weights at level-1, and constrained the level-1 variance (σ²) to be equal to 1 (see Hox, 2010; Hox & De Leeuw, 2003; Raudenbush, Bryk, Cheong, Congdon, & du Toit, 2004 for a discussion of v-known analysis using HLM). Also, as it may be incorrect to assume that our sampling distribution of correlation effect estimates (r) is normal (Hox & De Leeuw, 2003; Raudenbush & Bryk, 2002), effect sizes were transformed using Fisher’s z. Full maximum likelihood estimation was used and all main effect and interaction variables were grand-mean centered (Kreft & De Leeuw, 1998).
As an example, the equations corresponding to the model examining the moderating effect of power distance on the HPWS-business performance relationship are listed below, where i is firms and establishments (level-1 unit), j is studies (level-2 unit), k is countries (level-3 unit), zijk is the transformed Fisher’s correlation, σ²ijk is the level-1 sampling variance (which is externally specified and constrained to be equal to 1), U0jk is the level-2 variance, V00k is the level-3 variance, β0jk is the level-1 intercept, δ00k is the level-2 intercept, β1 to β9 are regression coefficients of level-2 control variables, γ000 is the level-3 intercept, and γ1 is the regression coefficient of the level-3 predictor variable (i.e., power distance). The statistical and practical significance of γ1 tests our hypotheses on the extent to which level-3 (i.e., country-level) variables (e.g., national culture, institutional flexibility) moderate the magnitude of HPWS-business performance correlations (zijk).
Level-1 model: zijk = β0jk + σ²ijk
Level-2 model: β0jk = δ00k + β1 Plant-level (dummy)0jk + β2 Percent
Compensation0jk + β3 Percent Employee Relations0jk + β4 Percent Performance
Management0jk + β5 Percent Training & Development0jk + β6 Percent
Promotion0jk + β7 Percent Recruitment & Selection0jk + β8 Manufacturing
(dummy)0jk + β9 Service (dummy)0jk + U0jk
Level-3 model: δ00k = γ000 + γ1 Power Distance00k + V00k
Results
Table 1 reports means, standard deviations, and correlations. The mean unweighted observed HPWS-business performance correlation was .28. Table 2 shows that the sample size weighted mean observed HPWS-business performance correlation (̅) was .22. The sample size weighted mean correlation corrected for random measurement error due to items (ρ) was .28.[5] In the full sample, artifacts (i.e., sampling error and measurement error due to items) accounted for 14.7% (i.e., less than 75%) of the observed variance in raw (uncorrected) correlations, suggesting the likely presence of substantive moderators. Further corroborative evidence of heterogeneity in effect estimates was found in the form of a statistically significant test of homogeneity (χ2 = 1189.93, p < .05) and what might be described as a relatively wide 80% credibility interval (.03 : .53). Table 2, which shows the 19 countries with K ≥ 2, indicates that
̅ and ρ are positive for all 19 countries. The smallest ̅ is .05 (Canada and the Netherlands), while the largest are .57 for Greece and .59 for Singapore. Only the confidence intervals for Canada, the Netherlands, and Ghana include zero. Table 2 also shows results by region (as defined in House et al., 2004). The highest ̅, .51, is for the Middle Eastern region, but that is based on only K = 3, N = 300. The next highest ̅, .33, is for the Confucian region (based on K = 40, N = 8,016). The lowest ̅, .06, is for the Germanic region (based on K = 5, N = 592).
In our dataset, studies are nested within countries and we are using country characteristics to explain between-study variance. The intraclass correlation for country (ICCcountry) is .322, indicating that 32.2% of the between-study variance in effect sizes occurs between countries and 67.8% occurs within countries. (Note: ICCregion = .188.) Consistent with standard HLM logic, we now examine the degree to which specific country characteristics are able to explain the variation in effect size magnitude. In doing so, we include controls[6] for industry, level of analysis, and HPWS content. The control variable model results are provided in Appendix C. 
According to hypothesis 1, which is based on national culture perspectives, countries with low power distance, low collectivism, and high performance orientation will have a more strongly positive HPWS-business performance relationship. As Table
3 shows, performance orientation is not statistically significantly related (B = -.149, p =
.24) to the HPWS-business performance effect size. In contrast, the coefficients for collectivism (B = .125, p < .05) and power distance (B = .229, p < .05) are statistically significant and (contrary to prediction) positive. As such, hypotheses 1a, 1b, and 1c, based on national culture perspectives, are rejected.[7]
Given the mean unweighted HPWS-business performance correlation of .28 (see Table 1), the effect size (r) is expected to be .35 in countries one standard deviation above the mean power distance and .21 in countries one standard deviation below the mean power distance.[8][9] Similarly, the effect size (r) is expected to be .36 in countries one standard deviation above the mean in-group collectivism and .19 in countries one standard deviation below the mean in-group collectivism.Table 3 also shows that country differences in power distance explain 34.7% of the between-country variation in effect sizes and 15.3% of the total between-study variation in effect sizes. Country differences in collectivism explain 49.2% of the between-country variation in effect sizes and 21.8% of the total between-study variation in effect sizes.
Hypothesis 2 stated that the HPWS-business performance effect size would be more strongly positive in low power distance (H2a), low collectivism (H2b), and high performance orientation (H2c) countries with tight national cultures. Table 4 shows that the cultural tightness-looseness * performance orientation coefficient is statistically significant and positive (B = .105, p < .05) and the cultural tightness-looseness * power distance coefficient is statistically significant and negative (B = -.084, p < .05). Although the cultural tightnesslooseness * in-group collectivism coefficient was not statistically significant, its sign was still negative. These findings are consistent with hypotheses 2a and 2c since countries that are culturally tight and either score lower on power distance or higher on performance orientation have more strongly positive HPWS-business performance effect sizes.
As illustrated in Figures 1 and 2, the national culture-based logic of hypothesis 1 appears to hold in high tightness national cultures, as indicated by the negative relationship between the HPWS-business performance effect size and power distance and the positive relationship between the HPWS-business performance effect size and performance
orientation. In contrast, the opposite appears to hold in low tightness (i.e., looser) national cultures as indicated by the positive relationship between the HPWS-business performance effect size and power distance and the negative relationship between the HPWS-business performance effect size and performance orientation. Thus, hypothesis 2 is supported. However, in all cases, the HPWS-business performance effect size remains positive.
Hypothesis 3 stated that the HPWS-business performance relationship would be more strongly positive when institutional flexibility was high. Table 5, however, shows that neither the separate dimensions (lack of burdensome government regulation, flexibility in hiring and firing, flexibility in wage determination) of institutional flexibility nor a scale combining these dimensions was statistically significantly related to the HPWS-business performance effect size. Thus, hypothesis 3 is not supported.
Discussion
Contextual differences must be considered in management theories (e.g., Bamberger, 2008; Johns, 2006). In a global economy, the potential importance of country-level contextual differences is especially relevant. Indeed, many scholars (e.g., Black & Porter,
1991; Boyacigiller & Adler, 1991; Brewster, 1995, 2007; Gerhart, 2009; Hofstede, 1983, 1993, 2001; Newman & Nollen, 1996; Tsui, 2006, 2009) have asked to what degree management (including HR) theory and practice generalizes across countries and to what degree new theories and research evidence must be developed for different countries. Here, we addressed one part of this broader question.
Specifically, we asked: Are HPWSs more effective when they fit the national culture and the institutional environment of a country? According to national culture perspectives, HPWSs should work better (i.e., the HPWS-business performance effect size should be more positive) in countries where they fit the national culture, which are hypothesized to be countries lower on power distance, lower on collectivism, and higher on performance orientation. Our findings, however, suggest that, contrary to national culture-based logic, HPWSs do not, on average, work better when they fit the national culture. Likewise, we found no evidence that the HPWS-business performance effect size was more positive in countries where HPWSs were hypothesized to better fit the institutional environment (i.e., countries having higher institutional flexibility). Thus, our main results suggest that national culture and institutional flexibility do not, on average, constrain the effectiveness of HPWSs.
In fact, although we found moderating effects of national culture, these effects were mostly the opposite of those hypothesized a priori using standard national culture-based logic. In other words, the HPWS-business performance effect size was, contrary to national culture-based expectations, more strongly positive in countries high on power distance and high on collectivism. The effect size was also more strongly positive in low performance orientation countries, again contrary to conventional national culture-based logic, but the difference was not statistically significant.[10]
Finally, our results suggest an important caveat: National culture-based logic (our hypothesis 1) receives empirical support in countries where managerial discretion is low, as indicated by the existence of a tight national culture. In tight cultures, the HPWS-business performance relationship was somewhat more positive in national cultures lower on power distance and/or higher on performance orientation. However, it is important to note that even in tight national cultures and in national cultures high on power distance and low on performance orientation, the HPWS-business performance effect size is positive. Indeed, even in tight national cultures, greater fit between national culture and HPWS resulted in effect sizes that were only slightly more positive than those observed when fit was expected a priori to be lower.
What explains the fact that some organizations choose to use HPWSs in countries even where the national culture of such countries is theorized to be a poor fit and further, that they succeed in using HPWSs under such conditions? First, as noted earlier, organizations may face a “multiplicity of constituent demands” (Oliver, 1991, Table 3, p. 160) or norms. It is increasingly rare that organizations compete only with other domestic organizations and only in their domestic market. Therefore, it is possible that the stronger positive HPWS-business performance relationship we have observed for firms that use HPWSs in countries where there is, according to national culture perspectives, a lack of fit with the national culture, is partly a result of such organizations conforming to a different, more global standard of management practice. For example, to be competitive in their industry on a global basis, they may decide to use a management strategy (e.g., an HPWS) that does not, according to national culture perspectives, fit the (mean) national culture.
They may decide they must make it work, despite challenges, to be able to compete globally. Similarly, Kostova et al. (2008) observe that “isomorphism [with the norms of the local country] is not a necessary condition for legitimacy or survival” (p. 999). One might take this logic one step further and suggest that isomorphism with the norms of the local country may, in some cases, undermine both legitimacy and survival in the global market.
Second, it is possible that organizations adapt HPWSs to some degree to reduce friction with (local) national culture norms. It seems likely that most management practices will be tailored by firms, whether in different countries or in the same country. Speaking of management practices broadly, Ansari et al. (2010) contend that “management practices often cannot be adopted by user organizations as ‘off the shelf’ solutions” but rather that “diffusing practices are likely to evolve during the implementation process, requiring custom adaptation, domestication, and reconfiguration to make them meaningful within specific organizational contexts” (pp. 67-68). Similarly, Pfeffer (1994), focusing on HR practices specifically, argued that although there was a set of best practices for managing people that apply to virtually all firms, “obviously, how one would implement these practices will vary significantly, based on a given organization’s strategy and its particular technology and environment” (Pfeffer, 1994, pp. 64-65). Pfeffer referred to this as “the contingent nature of the implementation of these practices” (p. 65), something he argued that “everyone would agree is necessary” (p. 65). Becker and Gerhart (1996) distinguished between (from most general to most specific) HR principles, HR policies, and HR practices. For example, a principle could be that employee performance is valued, but this principle could be operationalized with different policies and practices in different organizations.
Third, in a very similar vein, the international management literature, similar to Pfeffer’s (1994) concept of contingent implementation and Ansari et al.’s (2010) concept of customization, recognizes “hybridization” as “the insertion of a business system into a new society or context, and the processes of adaptation and learning involved” (Tolliday, Boyer, Charron, & Jürgens, 1998, pp. 3-4). For example, in the case of multinational enterprises, some may seek to achieve “convergence to a worldwide best practices model” (Pudelko & Harzing, 2007, p. 535) in the area of HPWSs, but at the same time, this “convergence” may accommodate unique local characteristics. For example, worker participation in decision making is mandated and institutionalized through co-determination in all but the smallest Dutch firms. Thus, to improve opportunity to contribute in a Dutch firm, the focus would need to be elsewhere (e.g., the use of self-directed work teams). Alternatively, it is possible that in this case the HPWS would focus more on the motivation and ability aspects. Thus, it is possible that the HPWSs examined in the studies that are part of our meta-analysis may have represented hybrids where “the ‘essence’ of [an HPWS is transferred], but in a reinterpreted and reinvented form that better fits the different institutional and cultural context” (Kühlmann, 2012, pp. 95-96). Kühlmann (2012) frequently observed such hybrids in his study of the transfer of HR practices within MNCs from Germany to China. In the international context, Evans et al. (2002) argue that in considering how much management practices need to conform to local norms, ‘‘the real question concerns what to respect, what to ignore, and what to reinvent when adapting work practices to another [country] environment” (p. 163).
Fourth, the above discussion, combined with some of our findings may point to the need to give greater attention to managerial discretion and the ability that organizations have to differentiate themselves from competitors even in the face of national culture and institutional constraints. The intraclass correlation for country indicated that 32% of between-study variance in effect sizes was between countries. That means that the majority of variance in effect sizes, 68%, was not explained by country. Thus, the effectiveness of an HPWS does not appear to be dictated by the country (or by specific country characteristics such as national culture or institutional flexibility). Further, the effect of country that we observe does not operate in the manner expected under conventional national culture perspectives. Specifically, the HPWS-business performance effect size was always positive, never negative and, except in tighter national cultures, the HPWS-business performance effect size was actually more strongly positive in national cultures where HPWSs were expected to fit less well (according to standard national culture-based logic and a priori hypotheses). Resource-based view (RBV) perspectives (Barney, 2001; Barney & Wright, 1998; Lado & Wilson, 1994; Wernerfelt, 1984; Wright et al., 2001) may help explain our findings, given that RBV perspectives recognize that sustained competitive advantage (i.e., outperforming industry competitors over time) can theoretically be achieved by following a strategy that creates value in a way that is rare and difficult to imitate. RBV perspectives may help explain why some firms choose to (successfully) implement an HPWS strategy in countries that have a national culture and/or institutional environment that is not seen as consistent with an HPWS or conducive to the use of an HPWS. Future research may wish to assess whether an HPWS has a higher payoff in countries where use of an HPWS is rare.
Fifth, our study suggests that an organization’s ability to successfully implement an HPWS in a country where fit with (mean) national culture is weak may depend, to some degree, on how tight or loose that national culture is. Specifically, as noted, we found that such a strategy was more successful in countries having looser national cultures, which provide more tolerance for deviation from cultural norms and likewise sanction such deviations less strongly. In contrast, in tight national cultures, we found that HPWSs were most effective when they fit the (mean) national culture. Importantly, under all combinations of (in)consistency with national culture and cultural tightness-looseness, the mean effect size for the HPWS-business performance relationship was positive.
Although we also expected institutional flexibility, especially with its strong regulatory/coercive component (as we defined and measured it), to influence the HPWSbusiness performance relationship, we did not find such evidence. One possibility is that coercive/legal institutional pressures are so strong and pervasive that HPWSs are either simply not feasible in some countries or are strictly required in other countries and thus, we do not observe their relationship with performance in those countries. As a consequence, it would be difficult to observe any moderating effect of institutional flexibility. Alternatively, it may be that institutional forces are either not as strong as sometimes argued or that our measures of institutional flexibility were not adequate for capturing the hypothesized effects. Perhaps there are particular aspects of the regulatory environment that vary by country and that influence the adoption and success of at least some components of HPWSs. Another possibility is that even in countries where regulatory constraints are high and some aspects of HPWSs may be difficult or even, in effect, not possible to use, organizations that are strongly committed to the use of HPWSs are able to use enough core HPWS practices to obtain positive effects.
Limitations and Future Directions
Our study has several limitations. First, our comparison of effect sizes across countries relies on non-representative samples, meaning that there may be file drawer/publication bias issues. We constructed a funnel plot (Hox, 2010; Hunter & Schmidt, 2004) of sample size (N) against effect size (̅). The funnel plot was symmetric (excluding one outlying large sample study reporting a negative effect estimate) and therefore not suggestive of a disproportionate exclusion of small-sample studies reporting small effect estimates. In addition, the fail-safe/file-drawer test of effect sizes (Hunter & Schmidt, 2004,
p. 501) indicated that the number of missing or excluded studies averaging null results (i.e., no statistically significant HPWS-business performance relationship) required to decrease our mean observed effect size (̅            = .22) to a small effect size of .10 (Cohen, 1988) would be 187. Given that this number is larger than our current meta-analytic sample size, it is unlikely that publication bias had a significant effect on our results.
We also checked the potential for publication bias by constructing funnel plots and conducting fail-safe/file-drawer tests on subsamples of studies from the United States, China, and Spain, the three countries from which the most number of studies originated. The funnel plots of effect estimates from each country failed to provide clear and convincing evidence of publication bias. Further, in each case the number of excluded studies reporting an effect size of zero required to reduce the mean observed r to a small effect size is 1 to 2.5 times as many studies (United States = 62, China = 40, Spain = 13) as currently included in each subsample. These results make it unlikely that the population of studies on the HPWSbusiness performance relationship in each country may have been disproportionately sampled across countries.
Second, it is possible that differences in effect sizes across countries reflect differences in the definition and measurement of the HPWS used. As noted above, HPWSs may be implemented differently in different studies. Whether within or across countries, this has been an issue at least since being highlighted in 1996 by Becker and Gerhart. In 2013,
17 years later, Posthuma, Campion, Masimova, and Campion stated that “High Performance Work Systems are designed to enhance organizational performance …Yet there is very little consensus about the structure of these systems and the practices therein” (p. 1184). Thus, what is in an HPWS and how that differs across studies is an ongoing issue and one that does not seem specific to multi-country studies such as ours. Nevertheless, we did address this issue empirically in three ways. First, we found that our results on moderation of the HPWS-business performance relationship were invariant to the inclusion of controls for six areas of HPWS content. This analysis is included in Appendix C. Second, a detailed comparison found that for 55 of 68 HPWS practices, China and the United States, which provided the most effect sizes for our study, showed significant similarity in use. This analysis is presented in Online Supplement 3.
Third, we then took the six countries providing the most effect sizes (United States,
China, Spain, United Kingdom, South Korea, Canada) and examined the percentage of HPWS practices that fell into the six HPWS content areas. These percentages were similar, again pointing to similarity in HPWS composition across countries in our sample (see Online Supplement 4). We next correlated the columns in the HPWS practice areas (6 rows) x countries (6 columns) matrix. The mean correlation between the countries was r = .82. The mean correlation of each non-U.S. country with the U.S. was r = .89.[11] We interpret these findings as indicating substantial similarity in the composition of HPWSs across countries.
These analyses do not rule out the possibility (noted earlier) that within the six HPWS areas, organizations in different countries use different practices and/or customize/adapt the same practices. However, we neither know of any evidence that documents such differences nor of any evidence that this is more likely in comparing organizations across countries versus within countries. We already know, for example, that the composition of HPWSs differs significantly across studies done even in a single country such as the United States. Future research on this question would be very helpful.
As a third potential limitation, our findings may be affected by selection bias. It is possible that we are more likely to observe successful/surviving cases of HPWSs. To the degree that occurs, the effect size estimates we have reported, at least for some countries, could be biased upward. Thus, future research that models the HPWS adoption/survival process in different countries would be useful. Our results indicate that some portion of organizations is able to successfully negotiate or overcome any country-level constraints and challenges to realize the positive payoff to HPWSs observed in our study. However, work on adoption might shed more light on the risk of following an HPWS strategy in different countries. 
Fourth, although we investigated the potential moderating effects of national culture and institutional flexibility, it is possible that other country differences may be relevant. Future studies may, for example, wish to examine other institutional factors such as a country’s educational system (Sparrow & Brewster, 2006), within-country differences in sector (e.g., state-owned versus privately-owned enterprises in China), economic factors such as varieties of capitalism (Hall & Soskice, 2001; Whitley, 1999), or how common HPWS use is in the country or industry (Bloom & Van Reenen, 2007). However, we know, based on the current study and previous studies, that country-level factors are often significantly correlated, thus placing a limit on how much additional country-level factors will contribute to our understanding. For example, Hall and Gingerich (2004)’s coordination index, which distinguishes liberal versus coordinated markets in the varieties of capitalism approach, correlates r = - .60 and r = .83, respectively, with the national culture variables of hierarchy and harmony (Schwartz, 2007).
Summary
Our study is the first to systematically examine, using the full body of available evidence, the degree to which the effectiveness of HPWSs is similar or different across countries and to what degree country-level moderators (national culture, cultural tightnesslooseness, institutional flexibility) may help explain any such differences. Our most important finding was that the mean effect size for the HPWS-business performance relationship was positive overall (corrected r = .28) and in every country (and statistically significant in all but three countries). Contrary to standard national culture-based logic, the HPWS-business performance effect size was actually more strongly positive in countries where the a priori hypothesized fit between an HPWS and the national culture was expected to be lowest, except in tight cultures. But, even here, the HPWS-business performance effect was always positive. As such, our findings challenge the conventional view of national culture perspectives that management practices must be fully tailored to the national culture and that managerial discretion is dominated by national culture (and/or home country institutional constraints).


[1] The most recent World Bank (2013) figures on productivity (gross domestic product per employed person, adjusted for purchasing power) are $14,196 for China, compared to an average of $51,965 for the other largest economies (United States, Japan, Germany, France).
[2] In addition to their central role in conceptual treatments of national culture’s role in organizations and in influencing the effectiveness of HR practices such as HPWSs, collectivism (individualism) and power distance are part of both Hofstede’s (1980, 2001) original framework and the more recent GLOBE framework (House et al., 2004). They have also received the most empirical attention of any national culture dimensions
(Taras et al., 2010). Performance orientation, per se, is not part of Hofstede’s original framework. However, it
[3]  Note that our fit hypothesis specifies, a priori, that a specific form of statistical interaction(s) must be supported to infer support for national culture-based logic.
[4] Hox (2010, p. 206) notes that “the random-effects model for meta-analysis assumes that study outcomes vary across studies, not only because of random sampling effects, but also because there are real differences across studies.” As such, under random-effects meta-analysis, “we have a hierarchical data set, with subjects within studies at the first level, and studies at the second level” (Hox, 2010, p. 206). When conducting a metaanalysis, ordinarily not the raw data are used but rather “the summary statistics that are the available data for the meta-analysis” (Hox, 2010, p. 207). Therefore, instead of representing a parameter to be estimated, the within-study variance is known.
[5] When additionally corrected for attenuation by random measurement error due to raters (Gerhart, Wright, McMahan, & Snell, 2000) in the predictor variable (i.e., HPWS) based on an average ICC(1) of .36 reported in a subsample of studies (K = 13), the mean true score correlation was .46.
[6] For comparison, results excluding control variables are presented in Online Supplement 5 and Online
Supplement 8.
[7] For interested readers, Online Supplement 7 additionally provides the results on the relationships between the six other national culture dimensions from the GLOBE study (House et al., 2004) and HPWS-business performance effect sizes. Descriptive statistics and correlations including these other national culture dimensions are presented in Online Supplement 6.
[8]  A change in .229 in Fisher’s z transformed r translates to a change of .23 in r. Given the standard deviation of power distance of .30 reported in Table 1, the change in r for a one standard deviation change in power distance can be calculated by multiplying .30 by .23, which is .069.
[9]  A change in .125 in Fisher’s z transformed r translates to a change of .12 in r. Given the standard deviation of in-group collectivism of .71 reported in Table 1, the change in r for a  one standard deviation change in ingroup collectivism can be calculated by multiplying .71 by .12, which is .0852.
[10] Given that the mean absolute correlation between the three national culture dimensions is .45, we also examined their combined moderating effect. We reverse-scored power distance and collectivism, converted each of the three national culture scores to z-scores, and then summed the z-scores to create a scale (α = .70) where higher scores indicate a national culture, based on national culture perspectives, that would better fit an HPWS. Consistent with hypothesis 1, countries with higher scores on this scale should have more strongly positive HPWS-business performance effect sizes. However, the results of this analysis confirmed our prior findings on the individual national culture dimensions with HPWS-business performance effect sizes found to be statistically significantly weaker (i.e., more negative or less positive) (B = -.044, p < .05) in countries having higher scores on the scale. A change of -.044 in Fisher z transformed r translates to a change of -.044 in r. The standard deviation for the national culture scale is 1.98. Thus, the change in r for a one standard deviation change in the national culture scale is .08712 (-.044*1.98). Given the mean unweighted HPWSbusiness performance correlation of .28 (see Table 1), this -.044 coefficient indicates that the expected HPWS-business performance effect size r would be .37 in countries one standard deviation below the mean on the national culture scale versus .19 in countries one standard deviation above the mean on the national culture scale. Again, these results do not support hypothesis 1.
[11] Given the small number of observations (countries), we computed correspondingly the shrunken r using the formula given by Cohen and Cohen (1983, p. 106). These were 77 and .86, respectively.

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