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1 Department of Commerce, University School of Business, Chandigarh University, Mohali, Punjab, India
2 Department of Commerce, Mahatama Gandhi Kashi Vidyapith, Varanasi, Uttar Pradesh, India
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Companies now have been more aware of the increasing necessity of integrating environmental and human resources management practices. Green human resource management (GHRM) uses human resource management (HRM) strategies to foster sustainable resource usage in corporate organisations and advances the issues of environmental sustainability through disruptive technologies. To foster the implementation of GHRM uniformly throughout industries across the world could only reflect the marginal impact on environmental sustainability. The purpose of the research article is to identify whether the adoption of GHRM in the organisation brought behavioural change among employees towards organisational commitment that could lead environmental sustainability. The study is conducted amongst different public and private sector banks in the Varanasi district of Uttar Pradesh, India, through primary data collection of 330 respondents. For analysing the adoptability of green behaviour amongst employees in the organisation, we have adopted structural equation modelling to examine the employee’s commitment. The test result of the above tool of studying the four different latent variables leads us to conclude that path analysis and load factor exhibited stronger relationship through post-moderating effect, that is, latent variables lead towards green commitment. This leads us to conclude that organisations are trying to get environmental sustainability through GHRM practices, which in turn gives them a status of an environmentally sensitive organisation as well as some edge in this competitive environment. As a policy government is also expecting from organisations to develop themselves as environmentally sensitive by providing impetus of employee’s commitment.
GHRM, disruptive technology, environmental sustainability, human resource management, PLS-SEM
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