The physical and mental health of an organization’s members is critical to its success because organizational productivity is maximized when members interact with each other in a healthy way (Schaef & Fassel, 1988). According to the definition put forth by the World Health Organization (1948), health is a “state of complete positive physical, mental, and social well-being and not merely the absence of disease or infirmity” (p. 1). When a worker experiences declining health because of excessive stress, the impact is felt by not only the employee and his or her family but also by the employing organization, and the detrimental effect can extend to the entire society (De Jonge, Bosma, Peter, & Siegrist, 2000). If employees of an organization fail to maintain reasonably good health because of chronic, cumulative, and unrelenting job stress, they will eventually become physically and mentally worn out, inevitably hampering their job satisfaction and adversely affecting organizational performance (Zhong et al., 2009).

The core functions of modern organizational management include increasing employee capabilities and motivation to maximize both job satisfaction and organizational performance (Pfeffer, 1998). In this regard, it is desirable that academics and field managers pay close attention to the well-being of employees by investigating occupational stress reduction through developing and implementing innovative management measures. One such measure is high- commitment human resource management (HRM), a component of strategic HRM that is included in the universalistic approach proffered by Pfeffer, who drafted a series of best practices drawn from successful corporations. Some of Pfeffer’s practices, such as job security, empowerment, appropriate and adequate rewards, and information sharing, were subsequently proved effective by Bond and Bunce (2001) and Kim and Kang (2014). Such factors as job autonomy and empowerment, participation in decisions, obtaining extensive qualifications, and information sharing enhance employees’ job control capacity (Topcic, Baum, & Kabst, 2016); thus, we assumed that job control is embedded, to some extent, in the high-commitment HRM system.

Literature Review

A review of recent empirical studies on high-commitment HRM reveals two diametrically opposed mainstream arguments. In the first perspective, the positive effect of high-commitment HRM on motivation, job satisfaction, employee commitment to the organization (Gould-Williams, 2004; Jiang, Lepak, Hu, & Baer, 2012; Schopman, Kalshoven, & Boon, 2015), and reduced job stress (Davis & Wilson, 2000; Kim & Kang, 2014; Lewicka & Krot, 2015) is emphasized. In the other perspective, it is concluded that high-commitment HRM intensifies job stress by increasing job demands and work intensity (Godard, 2004; Jensen, Patel, & Messersmith, 2013; Ramsay, Scholarios, & Harley, 2000). The contradiction may originate from discrepancies in the research participants or sampling employed in each study, but it may also have arisen from the multi- dimensional character of the HRM system itself, and how it is perceived by individual workers. In other words, the same high-commitment HRM system may have very different impacts on the organization’s performance and the health of its members, depending on how the members experience and perceive the system (Lewicka & Krot, 2015; Zhang, Fan, & Zhu, 2014).

In fact, traditional studies on high-commitment HRM, which were typically conducted at the organizational level, have often been criticized for insufficient investigation into the experiences and perceptions of organizations’ members (Kehoe & Wright, 2013; Zhang et al., 2014).

The Current Study

In the current study, we considered the perception of high-commitment HRM by an organization’s members as a major variable of interest to achieve our primary purpose of verifying its relationship with job stress.

We adopted the job demands–resources (JDR) model to investigate job stress (Bakker & Demerouti, 2007; Topcic et al., 2016) for two reasons: First, the concept of job control (Jensen et al., 2013) is more widely interpreted in this model than it is in the job demands–control model that was developed by Karasek and Theorell (1990). In the JDR model, it is maintained that sufficient mobilization of resources, such as supplies, tools, support, and cooperation, reduces job stress for a given job demand situation. Second, the JDR model has a more dynamic character than the person–organization fit model, as it accounts for the changeable relationships among job demands, job control, and job resources. A high-commitment HRM system and support from supervisors are considered to be meaningful resources in this regard (Monnot & Beehr, 2014; Rahimi, 2008). Moreover, employees’ actual experiences with the high-commitment HRM system or with supervisor support can dynamically affect the relationships among job demands, job control, and job resources. Accordingly, the JDR model can be properly applied to examine the stress-buffering effects of perceived supervisory support as well as high-commitment HRM practices.

In today’s corporate world, where performance-related pressure is very high, supervisors, as agents of the organization, have enormous influence on the organization’s members (Monnot & Beehr, 2014). Prior researchers (Brough & Frame, 2004; Monnot & Beehr, 2014) have revealed that higher, compared to lower, social support from supervisors and colleagues leads to lower turnover intention because employees experience reduced levels of job stress. This leads to our second purpose in this study: verification of the relationship between perceived supervisor support and job stress.

Regardless of how good an institution or innovation is in any system, it is the people who are the operators and who can be influenced by it in any meaningful way (Pfeffer, 1994, 1998). In several of the aforementioned studies, scholars have suggested that perceived supervisor support and organizational support could have an impact on the relationship between HRM practices and job stress (Brough & Frame, 2004; Monnot & Beehr, 2014; Topcic et al., 2016). Etzion (1984) and Viswesvaran, Sanchez, and Fisher (1999) have also suggested that social support from supervisors not only reduces job stress itself but also positively regulates its cause and effect. Therefore, we asserted that, compared to other employees, employees who believe that they have support from their supervisor would have a more positive perception of high-commitment HRM and would be less likely to suffer job stress. This leads to the third purpose of this research: empirical examination of the moderating effect of supervisor support on the relationship between perception of high-commitment HRM and job stress. An organization’s high-commitment HRM was analyzed as an organizational- level variable, whereas an employee’s perception of it was analyzed as an individual-level variable. Thus, we established the following three hypotheses in our empirical study:
Hypothesis 1: The perception of high-commitment HRM will be negatively associated with job stress.
Hypothesis 2: Perceived supervisor support will be negatively associated with job stress.
Hypothesis 3: Perceived supervisor support will moderate the negative association between perception of high-commitment HRM and job stress.

Method

Participants and Procedure

We targeted the entire population of production employees at a multinational manufacturing corporation operating in South Korea. This 150-year-old company, headquartered in the United States, operates factories in approximately 40 countries globally, and entered South Korea in the early 1970s, introducing its labor management partnership program in the mid-1980s. The company is known for its favorable labor relations and high-commitment HRM system.

Valid survey responses were received from 2,036 employees (85% response rate), through the company’s internal online system. To elicit candid responses, respondents were informed that they would not be personally identified in the survey results. The participants were predominantly male (88%), 33% were aged between 20 and 29 years, 53% were between 30 and 39 years old, 11% were aged 40 to 49, and 3% were in their 50s and older. A little over half (57%) had a high school education or less as their highest educational qualification, and the rest (43%) had a bachelor’s degree. Rank-and-file employees accounted for 79% of the respondents, followed by assistant managers (18%), and the remaining 3% held the position of manager or a more senior position.

Measures

Responses to the survey were rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). As the survey was originally developed in English, two fluent bilingual (English–Korean) speakers translated all items into Korean and then back-translated them into English to ensure semantic equivalence (Brislin, 1980).

Job stress. We used Keller’s (1984) four-item job stress scale to assess employees’ stress: “I experience tension from my job,” “Aspects of my job are a source of frustration to me,” “There is a lot of strain from working in my job,” and “I usually feel pressured in my job.” Cronbach’s alpha was .87 in this study.

Perception of high-commitment HRM. To measure employees’ perception of high-commitment HRM, we used seven items that Pfeffer (1994, 1998) developed to describe the practices of successful organizations: “The company strives for employment security” (employment security), “The company hires employees based on their aptitude and specialty” (selective hiring), “The company grants employees the authority necessary to perform their work” (self-managed teams and decentralization of authority), “The company compensates employees fairly based on their performance” (comparatively high compensation contingent on organizational performance), “The company provides employees with fair opportunities for training” (extensive training), “The company treats employees without any discrimination” (minimal status distinctions), and “The company shares extensive information with employees” (extensive sharing of financial and performance information). Cronbach’s alpha was .89 in this study.

Perceived supervisor support. We used Jokisaari and Nurmi’s (2009) three-item measure of perceived supervisor support: “My supervisor provides helpful advice on how to perform my job tasks,” “My supervisor gives sufficient feedback on my job performance,” and “My supervisor provides task assignments that improve skills and knowledge.” Cronbach’s alpha was .88 in this study.

Control variables. To prevent possible compounding effects, we controlled for five typical demographic variables. For gender, we coded female and male as 0 and 1, respectively. Level of education was coded across three levels: 1 = high school diploma or lower, 2 = 2–4-year college degree, and 3 = graduate school degree. We coded age across five levels and, even though there were no participants in this age group, we included a coding for those younger than 20 years: 1 = under 20 years, 2 = 20–29 years, 3 = 30–39 years, 4 = 40–49 years, and 5 = 50 years or older. Job grade was coded in accordance with the five levels used in the company, from 1 = lowest level to 5 = highest level. Finally, organizational tenure was coded across five levels: 1 = less than 3 years, 2 = 3 to under 5 years, 3 = 5 to under 7 years, 4 = 7 to under 10 years, and 5 = over 10 years.

Data Analysis

To examine whether or not the key variables in this study have discriminant power, we conducted a confirmatory factor analysis. The model’s chi-square (χ²) value was 702.00 (df = 124, p < .001), with the comparative fit index (CFI) and Tucker–Lewis index (TLI) being .97 and .96, respectively; both of the latter statistics are above the accepted standard of .95 (Hair, Black, Babin, & Anderson, 2010). The root mean square error of approximation (RMSEA) value of .048 also met the accepted standard of being below .050 (Hair et al., 2010). In addition, the items’ factor loadings, which served as the study constructs, all exceeded the minimum standard of .50 and showed significant loading values. Thus, we determined that the model’s validity was acceptable.

We conducted χ² difference tests to verify whether or not the hypothesized research model in this study was superior to alternative models, and the results suggested that the hypothesized model had a better overall fit compared to the other models. The CFI, TLI, and RMSEA of the research model were also superior to those of the alternative models. As such, the research model was concluded to be a better fit to the data than the alternative options were.

The correlations among variables may appear exaggerated because we analyzed data derived from the same respondents. To detect possible common method bias, we conducted Harman’s single-factor test in accordance with the suggestion by Podsakoff, MacKenzie, Lee, and Podsakoff (2003). The result indicated that the factor with the highest eigenvalue of 5.84 explained only 31% of all variance, thus suggesting that common method bias was unlikely to be salient.

To test the hypotheses, we performed a hierarchical multiple regression analysis using the ordinary least squares method. The independent and moderating variables were multiplied to form the interaction term so as to test the moderating effect proposed in Hypothesis 3. To avoid multicollinearity and render data interpretation easier, we centered the variables, then created an interaction term by multiplying the two grand-mean-centered variables, as suggested by Aiken and West (1991). In addition, the simple slopes figure was added to enhance understanding of the suggested moderating effect. We used STATA version 12.1 (StataCorp., TX, USA) to perform the data analyses.

Results

Descriptive Statistics, Correlations, and Reliabilities

The means and standard deviations of, correlations among, and reliability coefficients of, each variable are presented in Table 1. Perception of high- commitment HRM, as the independent variable, was negatively correlated with the dependent variable of job stress. Perceived supervisor support, as the independent and moderating variable, was also negatively correlated with job stress; that is, it was aligned in the same direction as proposed in Hypothesis 3.

Gender (male), age, job grade, and organizational tenure all exhibited significant negative correlations with job stress as well.

Results of Hierarchical Multiple Regression Analyses

Table 2 depicts the results of hierarchical multiple regression analyses with job stress as the dependent variable. In all models, the highest variation inflation factor of the variables, which is related to the coefficient of regression, was 2.90—that is, much lower than the cut-off value of 10.00. Thus, we determined that multicollinearity was unlikely to exist in our dataset (Aiken & West, 1991).

We included the control variables in Model 1 in Table 2, then in Model 2 we added the perception of high-commitment HRM, as the independent variable. In Model 3, we added perceived supervisor support, which was the independent and moderating variable, and in Model 4 we added the interaction term of independent and moderating variables.

As can be seen in Table 2, Model 2 had significantly more explanatory power (ΔR²) than Model 1 did. Further, the coefficient of regression for the perception of high-commitment HRM was significant in a negative direction, as was the case for Models 3 and 4. These findings support Hypothesis 1.

As can be seen in Table 2, Model 3 had significantly more explanatory power than Model 2 did, and the coefficient of regression for perceived supervisor support was significant in a negative direction. In addition, perceived supervisor support was also negatively significant in Model 4. These findings support Hypothesis 2.

As can be seen in Table 2, Model 4 had significantly more explanatory power than Model 3 did, and the coefficient of regression for the interaction term was negatively significant. These findings support Hypothesis 3.

In addition, in order to examine the interaction effect more precisely, we drew simple slopes, as suggested by Aiken and West (1991). One standard deviation below the mean (M − 1 SD) of perceived supervisor support, as the moderating variable, was assumed to be conceptually low, and one standard deviation above (M + 1 SD) was assumed to be conceptually high. At each low and high position of the moderating variable (i.e., perceived supervisor support), we drew simple slope lines, as depicted in Figure 1, to show the relationship between perception of high-commitment HRM and job stress. Furthermore, we conducted simple slopes tests to establish whether or not the slopes of the regression lines differed significantly from zero. The results indicated that the slopes of the two regression lines were significant, which we interpret to indicate that higher perceived supervisor support reinforced the perception of high-commitment HRM’s effect of lowering job stress. This also supports Hypothesis 3.

Discussion

Our aim in this study was to examine the universal applicability of high- commitment HRM (Pfeffer, 1994, 1998) to a Korean sample, specifically in regard to reducing job stress. We also aimed to clarify the relationship between supervisor support and job stress, and to determine whether or not supervisor support plays a role in the relationship between high-commitment HRM and job stress. Drawing upon the JDR model, we found that both perceived high- commitment HRM and perceived supervisor support reduced job stress. The moderating role of supervisor support on this relationship was also confirmed through our empirical results.

Theoretical and Practical Implications

Addressing the two conflicting views on the organizational effect of high- commitment HRM, in this study we have reconfirmed its positive effect in regard to reducing stress (Davis & Wilson, 2000; Kim & Kang, 2014; Lewicka & Krot, 2015). These results are quite different from those obtained in some other studies (Godard, 2004; Jensen et al., 2013; Ramsay et al., 2000). For example, Topcic et al. (2016) reported that job resources like flexible working hours or participation in decision making had no significant stress-reducing effect. In our study, however, the more the participants experienced and recognized high- commitment HRM, the less job stress they reported. Thus, high-commitment HRM, which is characterized by employment security, self-managed teams, comparatively high compensation contingent on organizational performance, minimal status distinctions, and extensive sharing of information, could have a universal effect for successful companies in both Korean and U.S. contexts. Notably, both the system and practice of high-commitment HRM itself and also employees’ perceptions of it produce the positive outcomes of lower job stress and concomitant promotion of employee health. As such, we assume that when a high-commitment HRM system is consistently practiced by management and is substantially experienced and clearly perceived by employees, these conditions could, in themselves, have a stress-buffering effect for the employees.

In addition, we have shown that perceived supervisory support, as an important job resource, can considerably reduce job stress (Lewicka & Krot, 2015; Monnot & Beehr, 2014). Furthermore, we found that perceived supervisory support had a moderating effect of strengthening the inverse relationship between positive perceptions of high-commitment HRM and job stress. We find it unsurprising that almost all prior researchers of the role of supervisor support have reported that this variable has positive effects on employee well-being (Jokisaari & Nurmi, 2009; Lewicka & Krot, 2015; Monnot & Beehr, 2014; Schopman et al., 2015). In sum, we have made a novel contribution to the existing literature by verifying that a positive perception of supervisory support is a preceding variable of job stress reduction as well as strengthening the inverse relationship between perception of high-commitment HRM and job stress.

This study also has several practical implications. First, our findings indicate that providing company-wide training and communication are both important factors in the process of implementing high-commitment HRM, so that all members of the organization become fully aware of its purpose and usage. No matter how excellent a system may be, it may not achieve its goal without all parties concerned having a clear understanding about how it operates.

Second, from the perspective of the universalistic approach, the innovative practice of high-commitment HRM is highly likely to spread across international borders with the acceleration of economic globalization (Pfeffer, 1998). Our study results indicate that a high-commitment HRM system, which was initially developed by multinational corporations, may be effective and valid for use in factories and organizations globally. Therefore, the management of not only multinational corporations but also local enterprises should be alert to the importance of employee perceptions of the high-commitment HRM system.

Third, when employees perceive stronger supervisory support this increases the breadth and depth of resources that members of an organization believe to be mobilized, leading to enhanced job performance capabilities and reduced job stress (Topcic et al., 2016; Viswesvaran et al., 1999). Therefore, it is necessary to promote both labor productivity and employee satisfaction by amicably and supportively strengthening supervisor–subordinate relationships.

Study Limitations and Future Research Directions

The first limitation to this study is that we surveyed the employees of a single manufacturing company, which calls into question the general applicability of the research results to other contexts. Although we did survey all employees of this particular company, not merely a representative sample, it will nonetheless be necessary in the future to expand the research scope to other economic sectors, such as health or public services, in order to improve the generalizability of the findings.

Second, there might be exaggerated relationships among the variables because the same respondents provided all data. Although we confirmed with Harman’s one-factor test that common method bias was unlikely to exist, the possibility of this type of bias having occurred cannot be entirely ruled out. Therefore, designing a research approach to separate response sources for independent versus dependent variables is a necessary step to take in future studies.

Third, we did not employ multilevel analysis to simultaneously examine group- and individual-level variables. Our use of individual-level variables as the unit of analysis was appropriate considering that our aim was to analyze the relationship between individual perceptions of fairness within the personnel management system and the resultant job stress. However, as the impact of a firm’s personnel management system on job stress as an enterprise- or individual-level variable has multilevel characteristics, a multilevel analysis is still recommended. In the future, it will be necessary to design a study incorporating multilevel analysis to investigate in depth the impact of multilevel organizational variables on employees’ job stress.

References

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Bakker, A. B., & Demerouti, E. (2007). The job demands–resources model: State of the art. Journal of Management Psychology, 22, 309–328. http://doi.org/cd5

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Rahimi, E. (2008). Survey of organizational job stress among physical education managers. Psychological Reports, 102, 79–82. http://doi.org/b69wcc

Ramsay, H., Scholarios, D., & Harley, B. (2000). Employees and high performance work systems: Testing inside the black box. British Journal of Industrial Relations, 38, 501–531. http://doi.org/cxjk4w

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Schopman, L. M., Kalshoven, K., & Boon, C. (2015). When health care workers perceive high- commitment HRM will they be motivated to continue working in health care? It may depend on their supervisor and intrinsic motivation. The International Journal of Human Resource Management. Advance online publication. http://doi.org/bdgh

Topcic, M., Baum, M., & Kabst, R. (2016). Are high-performance work practices related to individually perceived stress? A job demands–resources perspective. The International Journal of Human Resource Management, 27, 45–66. http://doi.org/bddp

Viswesvaran, C., Sanchez, J. I., & Fisher, J. (1999). The role of social support in the process of work stress: A meta-analysis. Journal of Vocational Behavior, 54, 314–334. http://doi.org/d2nxxz

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Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage.

Bakker, A. B., & Demerouti, E. (2007). The job demands–resources model: State of the art. Journal of Management Psychology, 22, 309–328. http://doi.org/cd5

Bond, F. W., & Bunce, D. (2001). Job control mediates change in a work reorganization intervention for stress reduction. Journal of Occupational Health Psychology, 6, 290–302. http://doi.org/fc53xd

Brislin, R. W. (1980). Translation and content analysis of oral and written material. In H. Triandis & J. Berry (Eds.), Handbook of cross-cultural psychology (Vol. 2, pp. 389–444). Boston, MA: Allyn & Bacon.

Brough, P., & Frame, R. (2004). Predicting police job satisfaction and turnover intentions: The role of social support and police organisational variables. New Zealand Journal of Psychology, 33, 8–16.

Davis, J., & Wilson, S. M. (2000). Principals’ efforts to empower teachers: Effects on teacher motivation and job satisfaction and stress. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 73, 349–353. http://doi.org/b7g9j2

de Jonge, J., Bosma, H., Peter, R., & Siegrist, J. (2000). Job strain, effort–reward imbalance and employee well-being: A large-scale cross-sectional study. Social Science & Medicine, 50, 1317–1327. http://doi.org/fq6vp8

Etzion, D. (1984). Moderating effect of social support on the stress–burnout relationship. Journal of Applied Psychology, 69, 615–622. http://doi.org/d2q8s2

Godard, J. (2004). A critical assessment of the high-performance paradigm. British Journal of Industrial Relations, 42, 349–378. http://doi.org/bjsfpj

Gould-Williams, J. (2004). The effects of ‘high commitment’ HRM practices on employee attitude: The views of public sector workers. Public Administration, 82, 63–81. http://doi.org/bqj6gh

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River, NJ: Pearson.

Jensen, J. M., Patel, P. C., & Messersmith, J. G. (2013). High-performance work systems and job control: Consequences for anxiety, role overload, and turnover intentions. Journal of Management, 39, 1699–1724. http://doi.org/dcm7tg

Jiang, K., Lepak, D. P., Hu, J., & Baer, J. C. (2012). How does human resource management influence organizational outcomes? A meta-analytic investigation of mediating mechanisms. Academy of Management Journal, 55, 1264–1294. http://doi.org/bdgd

Jokisaari, M., & Nurmi, J.-E. (2009). Change in newcomers’ supervisor support and socialization outcomes after organizational entry. Academy of Management Journal, 52, 527–544. http://doi.org/ddb5h2

Karasek, R., & Theorell, T. (1990). Healthy work: Stress, productivity, and the reconstruction of working life. New York, NY: Basic Books.

Kehoe, R. R., & Wright, P. M. (2013). The impact of high-performance human resource practices on employees’ attitudes and behaviors. Journal of Management, 36, 366–391. http://doi.org/cr2k3h

Keller, R. T. (1984). The role of performance and absenteeism in the prediction of turnover. Academy of Management Journal, 27, 176–183. http://doi.org/ctc4w3

Kim, J. H., & Kang, Y. H. (2014). Does the perception of high-commitment human resource management decrease job stress? The moderating role of employees’ perceptions of the industrial relations climate [In Korean]. Korean Academy of Management Journal, 22, 143–168.

Lewicka, D., & Krot, K. (2015). The model of HRM-trust-commitment relationships. Industrial Management & Data Systems, 115, 1457–1480. http://doi.org/bdgf

Monnot, M. J., & Beehr, T. A. (2014). Subjective well-being at work: Disentangling source effects of stress and support on enthusiasm, contentment, and meaningfulness. Journal of Vocational Behavior, 85, 204–218. http://doi.org/bdgg

Pfeffer, J. (1994). Competitive advantage through people: Unleashing the power of the work force. Boston, MA: Harvard Business Press.

Pfeffer, J. (1998). The human equation: Building profits by putting people first. Boston, MA: Harvard Business Press.

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879–903. http://doi.org/czw

Rahimi, E. (2008). Survey of organizational job stress among physical education managers. Psychological Reports, 102, 79–82. http://doi.org/b69wcc

Ramsay, H., Scholarios, D., & Harley, B. (2000). Employees and high performance work systems: Testing inside the black box. British Journal of Industrial Relations, 38, 501–531. http://doi.org/cxjk4w

Schaef, A. W., & Fassel, D. (1988). The addictive organization. San Francisco, CA: Harper & Row.

Schopman, L. M., Kalshoven, K., & Boon, C. (2015). When health care workers perceive high- commitment HRM will they be motivated to continue working in health care? It may depend on their supervisor and intrinsic motivation. The International Journal of Human Resource Management. Advance online publication. http://doi.org/bdgh

Topcic, M., Baum, M., & Kabst, R. (2016). Are high-performance work practices related to individually perceived stress? A job demands–resources perspective. The International Journal of Human Resource Management, 27, 45–66. http://doi.org/bddp

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World Health Organization. (1948). World Health Organization constitution. Geneva, Switzerland: Author.

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The authors thank Professor Sun-Hyuk Kim

Korea University

for her support with data collection and comments.

Su-Dol Kang, College of Business and Economics, Korea University, 2511 Sejong-ro, Sejong City 30019, Republic of Korea. Email: [email protected]