Green human resource management (GHRM) as a part of the social responsibility of companies emphasizes on preserving the environment and optimal use of resources. Companies producing electrical and electronic household appliances need to design and implement an effective model of human resource management with an emphasis on human resources due to the nature of using special tools in production and the nature of their products being dependent on electric energy. The purpose of this research is to design a green human resource management model in line with the social responsibility of electrical household appliance manufacturing companies with an interpretive structural modeling (ISM) approach. The statistical population included university faculty members with relevant academic and research fields, managers and experts familiar with green human resources in factories producing electrical and electronic household appliances, 6 companies, the Industry, Mining and Trade Organization, and the General Environment Department of Guilan Province. This research was conducted in two stages. In the first stage, interview tools and purposeful selection methods were used to identify the effective factors. Based on the rule of theoretical saturation, interviews were conducted with 12 people. In the second stage, to determine how the identified factors affect each other, an interpretive structural modeling matrix questionnaire was used, in which 24 experts participated using targeted sampling. The analysis of interviews in the first stage and matrix questionnaires using MATLAB software showed that there are 11 effective factors on green human resource management in seven levels of structural interpretation. The key factors with high influence and low dependence are green human resources planning, green job analysis and design, green organizational culture, green human resources selection and green human resources training and development. Green human resources planning has the most power of influence and green control and supervision has the most dependence.