Green innovation and environmental performance: The role of green transformational leadership and green human resource management
Sanjay Kumar Singh,
Manlio Del Giudice,
Roberto Chierici and
Domenico Graziano
Technological Forecasting and Social Change, 2020, vol. 150, issue C
Abstract:
Drawing upon the resource-based view and the ability-motivation-opportunity theory, we examined how green human resource management interplays on to the linkages amongst green transformational leadership, green innovation and environmental performance. Using a survey questionnaire, we collected triadic data from 309 manufacturing sector small and medium-sized enterprises (SMEs). We used covariance-based structural equation modeling (SEM) to examine hypotheses in this study. Results of the study suggest that green HRM practices mediates the influence of green transformational leadership on green innovation. We also found that green HRM indirectly through green innovation influences firm's environmental performance. Overall, the findings of our study support all hypotheses of direct and indirect effects and have several theoretical and practical implications. Finally, our study significantly advances theory and suggests that HRM-performance relationship neither depends upon the additive effect of green transformational leadership and green innovation as antecedent and mediator, respectively, nor on their interactive effect but a mix of both combinational forms (ie., additive and interactive) to affect firm environmental performance. Overall, our study contributes and advances the previous studies wherein in leadership plays critical role to influence the HRM practices and that in turn to predict green innovation in the organization.
Keywords: Green transformational leadership; Green human resource management; Green innovation; Environmental performance; SEM approach; SMEs (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (194)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:150:y:2020:i:c:s0040162519309588
DOI: 10.1016/j.techfore.2019.119762
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