The Association Between Green HRM Practices and Employees' Eco‐Friendly Behavior
研究了酒店业中绿色人力资源管理实践如何通过组织认同和环境意识影响员工环保行为，并发现上级绿色支持会削弱这一正向关系。
ABSTRACT This study investigates the associations between green human resource management (GHRM) practices and employees' eco‐friendly behavior (EEFB) within hospitality organizations. Drawing on social exchange theory (SET) and self‐determination theory (SDT), the research empirically tests a framework that incorporates organizational identification and environmental consciousness as parallel mediators and supervisory green support (SGS) as a contextual moderator. Data were collected from 385 hotel employees using a two‐wave time‐lagged survey design, and the model was analyzed with partial least squares structural equation modeling (PLS‐SEM). The findings indicate that GHRM practices are positively associated with organizational identification and environmental consciousness. Among the mediating mechanisms, organizational identification significantly mediates the association between GHRM practices and eco‐friendly behavior, whereas environmental consciousness does not significantly mediate behavioral outcomes, consistent with the well‐documented gap between environmental attitudes and enacted behaviors in organizational settings. Furthermore, SGS exhibits a statistically significant moderation effect that attenuates the GHRM–EEFB association, indicating that higher levels of SGS are associated with a weaker positive link between formal GHRM practices and employees' discretionary eco‐friendly actions. Interpreted through SDT, this pattern is consistent with contexts in which supervisory “support” may be enacted or perceived as controlling rather than autonomy‐supportive, thereby dampening intrinsic motivation and weakening the behavioral impact of GHRM. Overall, the results highlight the greater behavioral salience of identity‐based mechanisms over awareness‐based mechanisms and underscore the importance of the perceived quality of supervisory enactment in shaping how organizational green signals translate into EEFB in service contexts.