Skip to content


  • Research
  • Open Access

The neglected state of organizational-level turnover studies in the Chinese context: a call for research

Frontiers of Business Research in ChinaSelected Publications from Chinese Universities201711:6

  • Received: 27 February 2017
  • Accepted: 28 February 2017
  • Published:


In this essay, the authors discuss the neglected state of organizational-level turnover research in the Chinese context. They provide a brief overview of the importance of turnover research in the organizational sciences, highlight the role of performance-related turnover rates research, and outline general theories and findings that appear in the Western and English-language literature. This evidence is compared with a dearth of studies using samples of Chinese organizations and in Chinese-language journals. They conclude by calling for additional theory and empirical studies on turnover rates.


  • Turnover
  • Retention
  • Strategic human resource management
  • Organizational performance
  • Productivity
  • Strategic management

The study of turnover—voluntary and involuntary departures from the organization—spans 100 years and the area is considered a foundation area within industrial and organizational psychology, human resource management, and organizational behavior (Hom et al., 2017). Aside from the practical value of turnover research, this domain has produced some of the most iconic individual-level theories in our field, such as March and Simon’s (1958) pioneering desirability and ease of movement theory, Mobley’s (1979) job content model, Lee and Mitchell’s (1994) unfolding model, and Mitchell et al.’s (2001) job embeddedness theory. Spanning nearly 70 years, these theories provide detailed, multifaceted explanations for why people quit their jobs and why they stay.

In terms of implications for management and organizations, organizational-level turnover research may be even more critical. This stream details not only the antecedents of turnover patterns in organizations, but also how workforce churn impacts the organizational performance. At this level of analysis, the research tradition is nearly as rich. Researchers in many disciplines (e.g., management, finance, economics, sociology, medicine, marketing, and public administration) have detailed conceptual models and accompanied them with empirical testing for why and how the organizational context and practices influence quit and discharge rates (e.g., Batt and Colvin, 2011; Shaw et al., 1998) and for how turnover patterns relate to important outcomes such as accident rates, productivity, profitability, and stock market returns (e.g., Arthur, 1994; Huselid, 1995; Shaw, Gupta, et al., 2005; Shaw, Duffy, et al., 2005). These findings are showcased in two major meta-analyses (Heavey et al., 2013; Park and Shaw, 2013). Theory tradition at the organizational level is also abundant; major, differential theories have been developed or brought to bear in economics, sociology, human resource management, and organizational behavior, to name a few (Park and Shaw, 2013; Shaw, Gupta, et al., 2005).

In this editorial, we outline the importance of such organizational-level turnover rate research and note the striking dearth and major omission of this type of research in the Chinese context, and outline a call for contextual and industry studies in China to fill the gap.

The importance of turnover rate and organizational performance research

The organizational-level turnover literature is poly-theoretic; four main themes predominate (Park and Shaw, 2013). The first is a view of depletion via human capital or social capital losses. Per this perspective, higher turnover rates damage organizational performance by reducing the organization’s ability to function effectively. The mechanisms between voluntary turnover and the ultimate financial performance of the organization are presumed to be workforce-related, viz., lower productivity and customer satisfaction as well as higher disruption, accidents and errors. A related view originated in Price’s (1977) sociological perspective on turnover. Price’s (1977) theorization takes a similar direction of thought, but instead presumes that turnover effects are not monotonic. Instead, he argues that the first instances of voluntary quits are the most damaging to performance (Shaw, Gupta, et al., 2005). In this view, a rise from zero turnover to moderate levels creates the most impactful loss of knowledge, skills, and abilities (Alexander et al., 1994; Shaw et al., 2013) and the most significant disruption-creating gaps in organizational communication networks (Shaw, Duffy, et al., 2005).

A third view originates in the organizational behavior literature and, perhaps, enjoys the most popularity, but the least empirical support, in terms of describing turnover’s effects. Dalton and Todor (1979) and others lauded a functional view of turnover, arguing that moderate turnover rates bring new ideas and infuse the organization with stagnation-fighting energy from outside. In direct opposition to Price’s (1977) arguments, the functional view presupposes that low-to-moderate turnover improves organizational functioning; Price (1977) suggests that these levels are the most damaging. In the inverted-U view, at higher turnover levels the negative depletion effects on performance will ultimately prevail. It is difficult to search the literature and find examples that support the inverted-U approach unequivocally; Glebbeek and Bax (2004) and Siebert and Zubanov (2009) offer some limited support (see, Shaw (2011), for a review). A fourth view is a classic contingency model that originated in the strategic HRM literature. Arthur (1994) argued and found that the relationship between turnover rates and performance was moderated by how much the organization had invested in its people (see also Guthrie (2001) and Shaw et al. (2013)). High investment organizations tend to perform better, but suffer greater productivity loss via turnover than organizations that invest little in their people.

In more recent years, researchers have attempted to synthesize and extend these founding theories by considering the role of replacements or hiring in assuaging the negative effects of turnover (e.g., Nyberg and Ployhart, 2013) and by factoring in the timing or clustering of turnover (Hausknecht and Holwerda, 2013). These new advancements have spurred a spate of additional empirical testing and hastened accumulation the evidence (Call et al., 2015; Reilly et al., 2014). As noted by Shaw (2017), the morass of organizational-level theory may have created some initial confusion, but the upside to the situation was a vast amount of empirical testing of alternative formulations. Thus, in addition to the presumed practical value of examining these relationships, the empirical literature provided the fuel for two comprehensive meta-analytic studies (Heavey et al., 2013; Park & Shaw, 2013), which confirm practically significant negative relationships between turnover rates and performance outcomes. These meta-analyses also show (1) little evidence to support other formulations other than practically important declines in performance as turnover rates rise, (2) few differences in turnover rate relationships across voluntary and total turnover operationalizations, and (3) some evidence that turnover rate effects differ across employment relationships and job types.

Organizational turnover research in the Chinese context—a missing link

A call for research

The preceding review makes the purpose of this essay—a call for additional organizational-level turnover and performance research—clear. Our search efforts were meticulous, if not exhaustive. These endeavors uncovered only a handful of Chinese studies, while hundreds of such studies conducted in Western samples appear in the Western literature. The reasons for the dearth are unknown, but we can offer some speculation. First, it is possible that researchers believe that turnover consequences are not as severe in this context. The meta-analytic evidence does show that the turnover—organizational performance correlation is somewhat weaker in Asian samples (Park and Shaw, 2013) but it is difficult to place confidence in this comparison given the small number of Asian-sample studies. Second, it is possible that it is more difficult to collect or obtain such data in China compared to North America, where most of the studies originate. In the North American context, key-informant research designs are plentiful (Gupta and Shaw, 2000). In these studies, turnover data are typically obtained from key informants (e.g., plant managers or HRM managers) in large samples of organizations within or across industries. These turnover reports are then placed into empirical models with archival data obtained from industry associations, government databases, or purchased from third-party suppliers (e.g., Huselid, 1995; Shaw et al., 2009). Although individual-level survey data sets seem to be relatively easy to collect within Chinese organizations, organizational-level research conducted with a key informant design appears to be lacking. Third, strong industrial associations often characterize or bring together organizations in Western industries. Researchers are often able to access organizations and data via industry associations and trade conferences. These connections lead researchers to rich data sources underpinning years’ worth of within-industry studies, for example, in automobile manufacturing (MacDuffie et al., 1996; Jacobides et al., 2016) and trucking (Shaw et al., 1998; Shaw, Gupta, et al., 2005; Shaw and Gupta, 2007), to name only two. It is possible that these associations function differently in China, making it more difficult for researchers to obtain the data and access needed for large organizational samples.

Whatever the root causes, our contention is that such research is potentially fruitful and may offer insights that are not apparent in the existing broader literature. First, there is certainly a need to continue to test alternative theories of the turnover—performance relationships that already appear in the literature. Indeed, as Shaw, Gupta, et al., (2005) and others have pointed out, tests of differential or competing theories are needed in the literature, as are attempts to integrate these alternative theories (see Nyberg and Ployhart, 2013; Shaw et al., 2013). Second, it is certainly possible that turnover—performance dynamics operate differently in Chinese organizations, leaving open the possibility for new theoretical development and empirical comparisons against existing conceptual foundations. Third, there are many clear differences in employment relationships, workforce management, and the labor market in China. These contextual factors could be brought to bear as antecedents of turnover rates, or as moderating factors between workforce outflow and performance. Fourth, Chinese organizations face some temporal and seasonal challenges that are unique. For example, there are severe, yet somewhat predictable, mass turnover events after the Lunar Year Holiday and/or after bonus payments. In addition, many organizations near metropolitan centers deal with frequent influx and outflow of migrant workers, which creates administrative, hiring, exit, and productivity-related challenges that are not seen in Western countries where the residential population and labor market are more stable.

To conclude, we hope this call challenges and energizes Chinese researchers to consider the value in turnover rate studies at the unit and organization level. Such endeavors will surely balance the scales of empirical evidence. Additional studies in the fascinating Chinese context will also likely lead to facets of insights that, despite its 100-year history, have yet to be observed in the turnover literature.




Authors’ contribution

JDS drafted the initial version of the paper. JDS and SS then iterated work on subsequent drafts of the paper until a final version was agreed upon. Both authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

Faculty of Business, The Hong Kong Polytechnic University, Li Ka Shing Tower 829, Hung Hom, Kowloon, Hong Kong


  1. Alexander, J. A., Bloom, J. R., & Nuchols, B. A. (1994). Nursing turnover and hospital efficiency: An organization level analysis. Industrial Relations, 33(4), 505–520.Google Scholar
  2. Arthur, J. (1994). Effects of human resource systems on manufacturing performance and turnover. Academy of Management Journal, 37(3), 670–687.View ArticleGoogle Scholar
  3. Batt, R., & Colvin, A. (2011). An employment systems approach to turnover: HR practices, quits, dismissals, and performance. Academy of Management Journal, 54(4), 695–717.View ArticleGoogle Scholar
  4. Cai, L., & Li, B. 蔡立新, 李彪. 2016. 高管离职与高管薪酬、公司绩效的关系——基于2010 ~ 2013年创业板公司面板数据 (Top management turnover, monetary incentive, and firm performance: Evidence from a panel data of listed companies from 2010 to 2013). 财会月刊 (Finance and Accounting Monthly), (5): 25–29.Google Scholar
  5. Call, M., Nyberg, A. J., Polyhart, R. E., & Weekley, J. (2015). The dynamic nature of collective turnover and unit performance: The impact of time, quality, and replacement. Academy of Management Journal, 58(4), 1208–1232.View ArticleGoogle Scholar
  6. Chen, L, Yuan, Q, Zhou, C, Wang, C. 陈琳, 袁庆宏, 周常宝, 王春艳. 2016. 基于社会网络的集体离职过程中人际互动动态机制构建 (Constructing interpersonal interaction dynamic mechanism of collective turnover process: Qualitative research of social network perspective). 管理学报 (Chinese Journal of Management), (11): 1597–1605.Google Scholar
  7. Dalton, D. R., & Todor, W. D. (1979). Turnover turned over: An expanded and positive perspective. Academy of Management Review, 4(2), 225–235.Google Scholar
  8. Deng, Y, Du, L, & Yang, X. 邓玉林, 杜伦伦, 杨晓丽. 2016. 高管团队薪酬差距对高管离职的影响——高管团队薪酬水平的调节作用 (Influence of Executive Team Pay Gap on Executive Turnover—regulating role of executive team pay level). 世界科技研究与发展 (World Sci-tech R&D), (3): 656–662.Google Scholar
  9. Glebbeek, A. C., & Bax, E. H. (2004). Is high employee turnover really harmful? An empirical testing using company records. Academy of Management Journal, 47(2), 277–286.View ArticleGoogle Scholar
  10. Gupta, N., Shaw, J. D., & Delery, J. E. (2000). Correlates of response outcomes among organizational key informants. Organizational Research Methods, 3, 323–347.View ArticleGoogle Scholar
  11. Guthrie, J. P. (2001). High involvement work practices, turnover and productivity: Evidence from New Zealand. Academy of Management Journal, 44(1), 180–190.View ArticleGoogle Scholar
  12. Hausknecht, J. P., & Holwerda, J. A. (2013). When does employee turnover matter? Dynamic member configurations, productive capacity, and collective performance. Organizational Science, 24(1), 210–225.View ArticleGoogle Scholar
  13. He, J, Liu, C. 何江俊, 刘畅. 2011. 制造业员工离职率对生产力影响的实证研究——基于A集团的面板数据 (An empirical study on the effect of manufacturing workers’ turnover rates on productivity: Evidence from A company). 生产力研究 (Productivity Research), (4): 107–109.Google Scholar
  14. Heavey, A. L., Holwerda, J. A., & Hausknecht, J. P. (2013). Causes and consequences of collective turnover: A meta-analytic review. Journal of Applied Psychology, 98(3), 412–453.View ArticleGoogle Scholar
  15. Hom, P. W., Lee, T. W., Shaw, J. D., & Hausknecht, J. P. (2017) One hundred years of employee turnover theory and research. Journal of Applied Psychology, 102(2): 530–545.Google Scholar
  16. Huselid, M. A. (1995). The impact of human resource management practices on turnover, productivity, and corporate financial performance. Academy of Management Journal, 38(3), 635–672.View ArticleGoogle Scholar
  17. Jacobides, M. G., MacDuffie, J. P., & Tae, C. J. (2016). Agency, structure, and the dominance of OEMs: Change and stability in the automotive sector. Strategic Management Journal, 37(9), 1942–1967.View ArticleGoogle Scholar
  18. Lee, T. W., & Mitchell, T. R. (1994). An alternative approach: The unfolding model of voluntary employee turnover. Academy of Management Review, 19(1), 51–89.Google Scholar
  19. Li, J, Liu, S. 李济含, 刘淑莲. 2016. 国企高管薪酬改革与离职潮关系研究 (The relationship between compensation reform in state-owned companies and turnover rates). 证券市场导报 (Securities Market Herald), (10): 11–19.Google Scholar
  20. Liu, Q, Tang, X. 刘琼, 汤新华. 2015. 我国创业板上市公司高管离职影响因素研究 (Antecedents of top management turnover rates in companies listed in growth enterprise board). 商业会计 (Commercial Accounting), (5): 60–62.Google Scholar
  21. MacDuffie, J. P., Sethuraman, K., & Fisher, M. L. (1996). Product variety and manufacturing performance: evidence from the international automotive assembly plant study. Management Science, 42(3), 350–369.View ArticleGoogle Scholar
  22. March, J. G., & Simon, H. A. (1958). Organizations. New York: Wiley.Google Scholar
  23. Mei, C, Zhao, X. 梅春, 赵晓菊. 2016. 薪酬差异、高管主动离职率与公司绩效 (Pay dispersion, voluntary managerial turnover rate and corporate performance). 外国经济与管理 (Foreign Economic & Management), (4): 19–35.Google Scholar
  24. Mitchell, T. R., Holtom, B. C., Lee, T. W., Sablynski, C. J., & Erez, M. (2001). Why people stay: using job embeddedness to predict voluntary turnover. Academy of Management Journal, 44(6), 1102–1121.View ArticleGoogle Scholar
  25. Mobley, W. H. (1979). Intermediate linkages in the relationship between job satisfaction and employee turnover. Journal of Applied Psychology, 62(2), 237–240.View ArticleGoogle Scholar
  26. Nyberg, A. J., & Ployhart, R. E. (2013). Context-emergent turnover (CET) theory: A theory of collective turnover. Academy of Management Review, 38(1), 109–131.View ArticleGoogle Scholar
  27. Park, T. Y., & Shaw, J. D. (2013). Turnover rates and organizational performance: A meta-analysis. Journal of Applied Psychology, 98(2), 268–309.View ArticleGoogle Scholar
  28. Price, J. L. (1977). The study of turnover. Ames: Iowa State Press.Google Scholar
  29. Reilly, G. P., Nyberg, A. J., Maltarich, M., & Weller, I. (2014). Human capital flows: Using CET theory to explore the process by which turnover, hiring, and job demands affect unit performance. Academy of Management Journal, 57(3), 766–790.View ArticleGoogle Scholar
  30. Shaw, J. D. (2011). Voluntary turnover and organizational performance: Review, critique, and research agenda. Organizational Psychology Review, 1(3), 187–213.View ArticleGoogle Scholar
  31. Shaw, J. D. (2017). Moving forward at AMJ. Academy of Management Journal, 60, 1–5.View ArticleGoogle Scholar
  32. Shaw, J. D., & Gupta, N. (2007). Pay system characteristics and quit patterns of good, average, and poor performers. Personnel Psychology, 60(4), 903–928.View ArticleGoogle Scholar
  33. Shaw, J. D., Delery, J. E., Jenkins, G. D., & Gupta, N. (1998). An organization-level analysis of voluntary and involuntary turnover. Academy of Management Journal, 41(5), 511–525.View ArticleGoogle Scholar
  34. Shaw, J. D., Duffy, M. K., Johnson, J. L., & Lockhart, D. E. (2005). Turnover, social capital losses, and performance. Academy of Management Journal, 48(4), 594–606.View ArticleGoogle Scholar
  35. Shaw, J. D., Gupta, N., & Delery, J. E. (2005). Alternative conceptualizations of the relationship between voluntary turnover and organizational performance. Academy of Management Journal, 48(1), 50–68.View ArticleGoogle Scholar
  36. Shaw, J. D., Dineen, B. R., Fang, R., & Vellella, R. F. (2009). Employee-organization exchange relationships, HRM practices, and quit rates of good and poor performers. Academy of Management Journal, 52(5), 1016–1033.View ArticleGoogle Scholar
  37. Shaw, J. D., Park, T. Y., & Kim, Y. (2013). A resource-based perspective on human capital losses, HRM investments, and organizational performance. Strategic Management Journal, 34(5), 572–589.View ArticleGoogle Scholar
  38. Shen, Y, Xu, C, Jiao, L. 沈友娣, 许成, 焦丽华. 2011a. 高管成群离职、大股东控制力与公司业绩实证研究——基于中国2008—2009年制造业新增ST公司的证据 (An empirical study on senior managers’ clustering dimission, power of principal shareholders and company performance—evidence from manufacturing ST companies during 2008-2009). 华东经济管理 (East China Economic Management), (6): 67–70.Google Scholar
  39. Shen, Y, Xu, C, Jiao, L. 沈友娣, 许成, 焦丽华. 2011b. 高管成群离职行为在财务困境预警中的信息含量实证研究——基于中国2008-2009年制造业新增ST公司的证据 (The signaling effect of financial distress on clustering of turnover of top management teams: Evidence from new ST manufacturing companies in the years 2008 and 2009). 经济问题探索 (Inquiry Into Economic Issues), (2): 75–80.Google Scholar
  40. Shen, Y, Quan, Y, Yang, Y, Huang, H, Zhang, H. 沈余, 权渝, 杨远志, 黄红利, 张惠林. 2016. 改革护士绩效考核模式降低护士离职率 (Performance appraisal reform reduces turnover rates of nurses). 西南国防医药 (Medical Journal of National Defending Forces in Southwest China), (11): 1331–1332.Google Scholar
  41. Siebert, W. S., & Zubanov, N. (2009). Searching for the optimal level of employee turnover: A study of a large U.K. retail organization. Academy of Management Journal, 52(2), 294–313.View ArticleGoogle Scholar
  42. Xie, Q. 谢青青. 2012. 我国基金经理离职率与基金绩效的实证研究 (Empirical study on the relationship between fund managers’ turnover rates and fund performance). 会计之友 (Friends of Accounting), (19): 35–37.Google Scholar
  43. Yang, X, Huang, L. 杨栩, 黄亮华. 2008. 企业管理团队中集体离职危机及治理研究 (How to manage clustered turnover in management teams). 求索 (Seeker), (9): 32–34.Google Scholar
  44. Yang, X. 杨晓丽. 2013. 高管团队薪酬差距与离职率关系研究——基于电子产业上市公司的数据 (Study on the relationship between TMT pay gap and turnover rate—Based on the data from the electronic industry listed company). 电子测试 (Electronic Test), (12): 33–35.Google Scholar
  45. Zhang, Y, Hao, Y, Wang, M, Liu, J, Zhang, L. 张亚琴, 郝义彬, 王美英, 刘婧童, 张刘敏. 2014. 医护一体工作模式对护士执业认可度和护士离职率的影响 (Influence of integrated medical care working mode on recognition of nurse practitioners and nurses’ turnover rate). 护理研究 (Chinese Nursing Research), (16): 2011–2012.Google Scholar
  46. Zhao, Y. 赵玉洁. 2016. 与虎谋皮抑或珠联璧合——股权激励计划影响高管离职吗? (Does stock incentive affect top management turnover rates?)证券市场导报 (Securities Market Herald), (8): 22–32.Google Scholar
  47. Zhou, J. 周俊. 2008. 人口特征异质性对高管离职率的作用研究 (A study of the impact of demographic heterogeneity on top management team’s turnover). 中大管理研究 (China Management Studies), (4): 69–83.Google Scholar


© The Author(s). 2017