Identifying the main components and indicators of green human resource management and green supply chain in the automotive industry (qualitative data-based approach)

Due to the increasing regulation of governmental and non-governmental organizations and the request of customers regarding environmental issues and the intensification of competitive environment, industrial enterprises have also found that improving environmental performance can differentiate them from other competitors and thus follow a suitable model is very important for them. For this purpose, in this study, whit using the qualitative method of Grand Theory, a green human resource management model and a green supply chain in the Iranian automotive industry were designed. The method of data collection is form of documents and face-to-face interviews with 14 knowledgeable experts in the field of green human resource management and green supply chain, which have been identified using targeted sampling method. To analyze the qualitative data, three methods of open, axial and selective coding were used. The results showed that at first 216 effective sub-codes were identified during the study of the main concepts and finally the proposed final model with a line of communication between the research categories in the form of six main codes including; Causal conditions are the central category, context, intervening conditions, strategy and consequences. Therefore, the proposed model can be used as a tool for forecasting and policy in the field of human resources and supply chain in the automotive industry.