Presenting the structural model of the green human resource management implementation process using the fuzzy interpretive structural modeling method
Subject Areas :
1 - Industrial Management Department, Faculty of Business and Economics, Persian Gulf University, Bushehr, Iran
Keywords: Green human resource management, interpretive structural modeling, Delphi technique, fuzzy,
Abstract :
Green human resources management, as a strong tool that takes the role of human factors, can help organizations to fulfill their social responsibilities in order to protect the environment. This research has been carried out with the aim of systematically reviewing previous researches in the field of green human resources management, as well as identifying key elements and providing a structural model to implement the green human resources management process in the chemical and petrochemical industries of Bushehr province. By studying thematic literature and using the textual content analysis approach, six basic indicators were counted, and in order to localize them in order to implement green human resources management in the chemical and petrochemical industries, the Delphi technique was used in three rounds. The statistical population of the research was formed by managers and experts familiar with the subject and working in the field of petrochemical industries. A researcher-made questionnaire was used to collect data, and its validity and reliability were also confirmed. In order to design the structural model of the effective indicators for the implementation of the green human resources management process, the interpretive structural modeling approach in the fuzzy environment was used to manage linguistic ambiguities in judgments. The results of the modeling and analysis of Mik Mak showed that individual, group and organizational indicators are among the basic and influential indicators in the field of Sabza's human resources management; Therefore, managers are suggested to emphasize and pay more attention to this group of indicators.
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