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HOW MUCH DO HIGH‐PERFORMANCE WORK PRACTICES MATTER? A META‐ANALYSIS OF THEIR EFFECTS ON ORGANIZATIONAL PERFORMANCE
Abstract
Although there is growing evidence that high performance work practices (HPWPs) affect organizational performance, varying sample characteristics, research designs, practices examined, and organizational performance measures used has led extant findings to vary dramatically, making the size of the overall effect difficult to estimate. We use meta‐analysis to estimate the effect size and test whether effects are larger for (a) HPWP systems versus individual practices, (b) operational versus financial performance measures, and (c) manufacturing versus service organizations. Statistical aggregation of 92 studies reveals an overall correlation that we estimate at .20. Also, the relationship is stronger when researchers examine systems of HPWPs and among manufacturers, but it appears invariant across performance measures. We use our findings as a basis to offer 4 suggestions intended to shape research practices such that future meta‐analyses might answer today's emerging questions.
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HUSELID, M. A. (1995) · Academy of Management Journal · doi:10.2307/256741 · Cited by 9,342
Hunter, J., & Schmidt, F. (2004) · doi:10.4135/9781412985031 · Cited by 3,023
Job Resources Buffer the Impact of Job Demands on Burnout.
Bakker, A. B., Demerouti, E., & Euwema, M. C. (2005) · Journal of Occupational Health Psychology · doi:10.1037/1076-8998.10.2.170 · Cited by 2,483
THEORY TESTING: COMBINING PSYCHOMETRIC META‐ANALYSIS AND STRUCTURAL EQUATIONS MODELING
VISWESVARAN, C., & ONES, D. S. (1995) · Personnel Psychology · doi:10.1111/j.1744-6570.1995.tb01784.x · Cited by 926
Baltes, B. B., Briggs, T. E., Huff, J. W., Wright, J. A., & Neuman, G. A. (1999) · Journal of Applied Psychology · doi:10.1037/0021-9010.84.4.496 · Cited by 837 · cited 1×
“Perhaps HPWPs that increase empowerment, such as broad job designs (Delery & Shaw, 2001), or reduce stress, such as flexible work schedules ( Baltes, Briggs, Huff, Wright, & Neuman, 1999 ), matter more in service settings than among manufacturers.”
BackgroundA disagreement about within-group agreement: disentangling issues of consistency versus consensus
Kozlowski, S. W., & Hattrup, K. (1992) · Journal of Applied Psychology · doi:10.1037/0021-9010.77.2.161 · Cited by 514
Cited by
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Renwick, D. W. S., Redman, T., & Maguire, S. (2013) · International Journal of Management Reviews · doi:10.1111/j.1468-2370.2011.00328.x · Cited by 2,586
Transfer of Training: A Meta-Analytic Review
Blume, B. D., Ford, J. K., Baldwin, T. T., & Huang, J. L. (2010) · Journal of Management · doi:10.1177/0149206309352880 · Cited by 1,477
The Role Of Context In Work Team Diversity Research: A Meta-Analytic Review
Joshi, A., & Roh, H. (2009) · Academy of Management Journal · doi:10.5465/amj.2009.41331491 · Cited by 1,362
Wang, G., Oh, I.-S., Courtright, S. H., & Colbert, A. E. (2011) · Group & Organization Management · doi:10.1177/1059601111401017 · Cited by 1,315
Kramar, R. (2014) · The International Journal of Human Resource Management · doi:10.1080/09585192.2013.816863 · Cited by 960
Building Sustainable Organizations: The Human Factor.
Pfeffer, J. (2010) · Academy of Management Perspectives · doi:10.5465/amp.2010.50304415 · Cited by 862
Barrick, M. R., Thurgood, G. R., Smith, T. A., & Courtright, S. H. (2015) · Academy of Management Journal · doi:10.5465/amj.2013.0227 · Cited by 544
Longoni, A., Luzzini, D., & Guerci, M. (2018) · Journal of Business Ethics · doi:10.1007/s10551-016-3228-1 · Cited by 444
HRM and innovative work behaviour: A systematic literature review
Bos-Nehles, A., Renkema, M., & Janssen, M. (2017) · Personnel Review · doi:10.1108/pr-09-2016-0257 · Cited by 430
Hong, Y., Liao, H., Hu, J., & Jiang, K. (2013) · Journal of Applied Psychology · doi:10.1037/a0031666 · Cited by 386
Is Disability Disabling in All Workplaces? Workplace Disparities and Corporate Culture
SCHUR, L., KRUSE, D., BLASI, J., & BLANCK, P. (2009) · Industrial Relations: A Journal of Economy and Society · doi:10.1111/j.1468-232x.2009.00565.x · Cited by 354
Busch, T., & Friede, G. (2018) · Corporate Social Responsibility and Environmental Management · doi:10.1002/csr.1480 · Cited by 345
Attribution theory in the organizational sciences: The road traveled and the path ahead
Harvey, P., Madison, K., Martinko, M., Crook, T. R., & Crook, T. A. (2014) · Academy of Management Perspectives · doi:10.5465/amp.2012.0175 · Cited by 293
Kalshoven, K., & Boon, C. T. (2012) · Journal of Personnel Psychology · doi:10.1027/1866-5888/a000056 · Cited by 251
A Multi-Level Process Model for Understanding Diversity Practice Effectiveness
Nishii, L. H., Khattab, J., Shemla, M., & Paluch, R. M. (2018) · Academy of Management Annals · doi:10.5465/annals.2016.0044 · Cited by 233
The science and practice of workforce analytics: Introduction to the HRM special issue
Huselid, M. A. (2018) · Human Resource Management · doi:10.1002/hrm.21916 · Cited by 179
Toward a more comprehensive model of firms’ human capital rents
Chadwick, C. (2017) · Academy of Management Review · doi:10.5465/amr.2013.0385 · Cited by 159
A meta‐analysis of the effects of electronic performance monitoring on work outcomes
Ravid, D. M., White, J. C., Tomczak, D. L., Miles, A. F., & Behrend, T. S. (2023) · Personnel Psychology · doi:10.1111/peps.12514 · Cited by 159
Methods for second order meta-analysis and illustrative applications
Schmidt, F. L., & Oh, I.-S. (2013) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2013.03.002 · Cited by 151
The (potential) demise of HRM?
Dundon, T., & Rafferty, A. (2018) · Human Resource Management Journal · doi:10.1111/1748-8583.12195 · Cited by 144
Kaufman, B. E. (2010) · ILR Review · doi:10.1177/001979391006400104 · Cited by 122
Market competition, HRM, and firm performance: the conventional paradigm critiqued and reformulated
Kaufman, B. E. (2015) · Human Resource Management Review · doi:10.1016/j.hrmr.2014.08.001 · Cited by 118
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Win-Win-Lose? Sustainable HRM and the promotion of unsustainable employee outcomes
Bush, J. T. (2020) · Human Resource Management Review · doi:10.1016/j.hrmr.2018.11.004 · Cited by 110
Taylor, S., Osland, J., & Egri, C. P. (2012) · Human Resource Management · doi:10.1002/hrm.21509 · Cited by 110
The unexpected side of relational e-HRM: Developing trust in the HR department
Bissola, R., & Imperatori, B. (2014) · Employee Relations · doi:10.1108/er-07-2013-0078 · Cited by 73
Ideology in HRM Scholarship: Interrogating the Ideological Performativity of ‘New Unitarism’
Greenwood, M., & Van Buren, H. J. (2017) · Journal of Business Ethics · doi:10.1007/s10551-016-3084-z · Cited by 66
The "HR–line-connecting HRM system" and its effects on employee turnover
Kim, S., Su, Z., & Wright, P. M. (2018) · Human Resource Management · doi:10.1002/hrm.21905 · Cited by 47
Human resource management: the promise, the performance, the consequences
Brewster, C., Gooderham, P. N., & Mayrhofer, W. (2016) · Journal of Organizational Effectiveness: People and Performance · doi:10.1108/joepp-03-2016-0024 · Cited by 42
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Bos-Nehles, A. C. (2024) · doi:10.3990/1.9789085705130 · Cited by 40
Metadata
- Authors
- COMBS, J., LIU, Y., HALL, A., & KETCHEN, D.
- Venue
- Personnel Psychology
- Publisher
- Wiley
- Published
- 2006-08-17
- Volume
- 59
- Issue
- 3
- Pages
- 501-528
- ISSN
- 0031-5826 (ISSN-L)
- 1744-6570
- OpenAlex
- W2161443229
- Cited by
- 2,092
- References
- 6
- FWCI
- 54.45
- Type
- journal article
- Language
- en
- Open access
- closed
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