Proposing a Green Human Resource Management Framework for Steel Industry

Document Type : Research Paper

Authors

1 اصفهان

2 دانشگاه اصفهان

3 Management, administrative and economic, university of Isfahan, Iran

Abstract

The purpose of this study is to propose a framework for green human resource management in steel industry.  The statistical population of the research includes the employees of Mobarakeh Steel Company of Isfahan. This applied research employs a compound method (quantitative and qualitative methods) for data collection. Interviews are conducted for designing the research model. Having conducted 25 interviews, the researchers designed the basic research model. To test the validity, triangular method, paired method, and subject review method were used. Test-retest method was used to verify the reliability of the test. In the quantitative section, a questionnaire tailored to the model was designed to validate the designed model based on the interviews. This model was examined through structural equation method. Research population consisted of 380 people in the quantitative section from whom 181 were selected as the sample group according to the krejcie and Morgan table. Content validity method was used to test the validity of the questionnaire, and the reliability of the questionnaire was determined using Cronbach's alpha. The results of the structural equation modeling confirmed the designed model by AMOS software. The results indicated that green human resources management has an impact on individual, organizational and group outcomes. In terms of the internalization and changing attitudes of Mobarakeh employees and managers regarding environmental issues, the most important way to change attitudes in this company is to educate and increase knowledge of the employees on environmental issues.

Keywords

References

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Journal of Research in Human Resources Management
Volume 9, Issue 4 - Serial Number 30
SERIAL NO.30
February 2018
Pages 153-179

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History

  • Receive Date: 14 October 2017
  • Revise Date: 24 November 2017
  • Accept Date: 23 January 2018

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