Purpose
This paper aims to study the relationship between servant leadership (SL), employee turnover intention (TI) and organizational identification (OI) in hospitals.
Design/methodology/approach
The study uses a quantitative approach to investigate the relationships between SL, OI and TI, using data collected from a sample of 266 front-facing employees in a private Indian hospital setup. Structural equation modeling is used to analyze the data and test the hypotheses.
Findings
The findings reveal that servant leadership has a positive relationship with organizational identification and negatively impacts turnover intentions of the front-facing employee. Further, the study also reveals, contrary to expectations, organizational identification has no significant mediating effect between servant leadership and turnover intentions.
Research limitations/implications
This research is limited to front-facing employees in hospitals and the study may be extended to other industries in the service sector. Future studies may consider other mediating and moderating variables to fully understand the mechanism of impact of servant leadership on turnover intention. Multi-level studies can also be carried out.
Practical implications
With the ever-increasing expectations for better patient care, robust leadership models have required that address front-facing employee’s well-being, enabling their attention toward patients. This paper provides the impetus for the development and adoption of servant leadership specifically within hospitals and the service sector.
Originality/value
This study is one of the few studies that empirically examines servant leadership in the health-care domain. The study also contributes to the extant literature on servant leadership by empirically examining the mediation effect of organizational identification between SL and TI. To the authors’ best of knowledge, this study may be the first of its kind, providing evidence of servant leadership’s impact on turnover intention and organizational identification in hospitals using data from the Indian context.
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