Does green human resources management pay off? The mediating role of green innovation and employee attitude in sustainable supply chain management

This research demonstrates that the relationship between Green Human Resource Management (GHRM) practices and Sustainable Supply Chain Management (SSCM) performance is mediated by organizational capabilities rather than a direct process, and this effect is supported by the Resource-Based View (RBV). Research methodology – For the study, data were collected from a total of 476 participants from 71 companies operating in the textile sector and engaging in green management processes in the Southeastern Anatolia Region of Turkey. The significant role the region plays in machine-made carpet production was a key factor in this selection. Findings – It has been observed that GHRM enhances a company’s product and process in- novation capacity; it also reveals a critical distinction between the impacts of different innovation types. Process innovation plays a strong role in enhancing environmental performance through internal improvements. Additionally, it has been observed that concern is a stronger motivator than knowledge in achieving sustainability goals. Research limitations – The cross-sectional design of the study limits definitive proof of causal relationships between variables, it is recommended that future studies utilize longitudinal de- signs that can monitor the long-term effects of GHRM. Practical implications – The social aspect of sustainability in SSCM can be achieved by visible product innovations. Additionally, the perception gap between senior management and operational employees has been identified as the primary obstacle to implementing sustainability strategies. It has been emphasized that addressing this gap requires mobilizing emotional concern, a driving force stronger than purely cognitive knowledge. Originality/Value – This study brings together a detailed model by examining the effect of GHRM on SSCM relationship mediated by different innovation and attitude types simultaneously. This gives a more nuanced and applicable information.