Investigating the role of identified components on green human resource management and green supply chain with an approach to reducing environmental pollutants in Iran Khodro industry

Authors

1 PhD student, Department of Public Administration, Faculty of Humanities, Saveh Branch, Islamic Azad University, Saveh, Iran

2 Assistant Professor, Department of Public Administration, Faculty of Humanities, Saveh Branch, Islamic Azad University, Saveh, Iran

3 Assistant Professor, Department of Public Administration, Faculty of Humanities, Arak Branch, Islamic Azad University, Arak, Iran

Abstract

The present study aimed to provide a model for green human resource management and green supply chain in the automotive industry in Iran. This research is applied in terms of purpose, descriptive-survey in terms of nature and method, and cross-sectional in terms of time. The data collection tool is a researcher-made questionnaire with a Likert scale of 5 options whose validity and reliability have been confirmed. The statistical population of this study includes all elites as well as human resource managers and supply chain managers of companies affiliated to the automotive industry in Tehran province. Using Morgan table and random sampling method, 274 people were selected. The research hypotheses were tested using structural equation modeling and LISREL software. Findings showed that in the extracted model, there are categories of causal conditions, axial categories, context, intervening conditions, strategy and consequences in the final model that have a significant relationship with each other. The result of reviewing the five hypotheses of the research showed that all hypotheses were confirmed and the causal category on the central category, the central category on green human resources management strategies, the intervening conditions on green human resources management strategies, the contextual factors on human resources management strategies, respectively. Green and ultimately strategies have a positive and significant impact on outcomes.

Keywords