A Cross-Level Holistic Model Of Public Service Motivation

ABSTRACT

Using a sample of 63 supervisors and their direct reports (189 immediate subordinates), this study investigated a cross-level model of public service motivation’s (PSM) antecedents in the Chinese public sector. Correlation analyses and hierarchical linear modeling (HLM) results simultaneously revealed that both subordinates’ proactive personality and supervisors’ servant leadership were related positively to subordinates’ PSM. Additionally, HLM analyses demonstrated that supervisors’ servant leadership and their immediate subordinates’ proactive personality interacted to correlate positively with subordinates’ PSM. Implications of the findings, limitations, and directions for future research are discussed.

ACKNOWLEDGMENTS

We appreciate the invaluable and insightful comments and suggestions from Prof. Bradley E. Wright (University of Georgia) and Prof. Donald P. Moynihan (University of Wisconsin-Madison) on a draft. We are indebted to Prof. David A. Hofmann (University of North Carolina-Chapel Hill) for his advice on hierarchical linear modeling (HLM) analysis. We are indebted to an anonymous reviewer of the International Public Management Journal for their insightful suggestions.

Notes

For the match between subordinates and the supervisor’s evaluations in work groups, snowball sampling technique was used.

Although previous studies demonstrate that educational background would be an effective predictor of individual PSM, in this study we cannot control for it because most respondents (95%) hold a bachelor’s degree.

Results of moderated regression demonstrated that the interaction term accounted for an additional 2.6% of the variance (i.e., R²change .026). According to McClelland and Judd (1993), an R²change of this magnitude should be considered rather large because moderator effects are so difficult to detect and even those explaining as little as 1% of the variance should be considered important.

According to Aguinis et al. (2010), the following models are estimated and compared.

(1)

(2)

(3)

To assess whether the slopes are different across groups (low servant leadership group vs. high servant leadership group), we compare whether the R²resulting from Equation (3) is statistically different from the R²resulting from Equation (2).

We acknowledge that common method variance (CMV) may have influenced the relationships between variables. However, our research plan considered CMV and ways to mitigate its possible effects. Three factors helped mitigate concerns about CMV (Podsakoff et al. 2003). First, there is a relatively strong theoretical argument underlying the relationships among the four key variables (Kelman 2015). Second, subsequent research based on rigorous designs (e.g., longitudinal designs and experimental designs) has confirmed the relationships among the key variables, increasing confidence that the results can be replicated under different conditions (e.g., Esteve et al. 2016; Schwarz et al. 2016; Yang et al. 2011). Third, current research has suggested that, even if significant CMV exists between the dependent and independent variables, this problem does not produce a corresponding significant interactive effect. CMV attenuates rather than amplifies significant interactions in such data (Evans 1985; Siemsen et al. 2010). In addition to the various practices we adopted (i.e., multiple sources) in the current design (Podsakoff et al. 2003), we believe that the three points noted earlier moderate CMV-related threats associated with the current study’s findings.

Supplemental evidence shows that proactive personality could be an antecedent to all dimensions of PSM, but servant leadership only affects some dimensions of PSM. Moreover, there is little significant moderating effect of servant leadership on the relationships between proactive personality and specific dimensions of PSM. Additional correlation analysis demonstrated that there were strong correlations among the dimensions of PSM (the supplemental evidence is available from the first author). Thus, we decided to take the aggregate approach in the current study and combine the dimensions of PSM together into “whole” constructs to increase both conceptual parsimony and predictive validity and to enable comparison and consistency (especially with recent research).

Additional information

Funding

This research was supported by the National Natural Sciences Foundation of China (Project 71002035 and 71673185) and SMC-Chenxing Young Scholar Program (Shanghai Jiao Tong University).

Notes on contributors

Bangcheng Liu

Bangcheng Liu ([email protected]) is professor of organizational behavior and human resource management at the School of International and Public Affairs, Shanghai Jiao Tong University. He received his Ph.D. in management at the Antai School of Management, Shanghai Jiao Tong University. His current research focuses on cross-cultural organizational behavior and strategic human resource management, especially for public organizations. He also is interested in talent policy and innovational and entrepreneurial management.

James L. Perry

James L. Perry ([email protected]) joined Indiana University’s School of Public and Environmental Affairs in 1985, where he is now Distinguished Professor Emeritus and Chancellor’s Professor of Public and Environmental Affairs Emeritus. He is also affiliate professor of philanthropic studies. Perry’s 40 years of scholarship include expertise in public management, public organizational behavior, government and civil service reform, national and community service, public service motivation, and performance-related pay.

Xinyu Tan

Xinyu Tan ([email protected]) is a doctoral student at the School of International and Public Affairs, Shanghai Jiao Tong University. He is currently working on his Ph.D. thesis on innovational behavior and management in Chinese public organizations.

Xiaohua Zhou

Xiaohua Zhou ([email protected]) is assistant professor at the School of Business, University of Hong Kong. She received her Ph.D. in management at the School of Business Administration, University of Miami. Her research focuses on leadership, interpersonal influence, innovation, and organizational change management.