Document Type : Research Paper
Authors
Abstract
The purpose of this study was to design a model for prioritizing the factors influencing the acceptance of social responsibility using artificial neural networks. The method of this research is descriptive-survey. The statistical population of the research is all employees of the Department of Sports of Kurdistan Province, which was 240 at the time of the research. The target population is, in the first place, experts in the academic field. In the first phase, four main dimensions of social responsibility were collected by studying literature of authoritative literature (library studies) (Table 1).These factors were at the disposal of the panel of experts, including 11 university professors. The experts verified the content validity of the factors with an average above 79/0. The statistical population in the second section was the staff and managers of the Department of Sports and Youth of Kurdistan province. Based on the Klein index, 100 individuals were selected as the sample. After ensuring the initial validity, the components were based on a Likert scale-based questionnaire. Structural Validity (Confirmatory Factor Analysis) and Reliability (Cronbach's Alpha) were evaluated. Finally, validity (0.79) and structural reliability (0.891) were confirmed. Then, using artificial neural network method, the factors influencing the acceptance of social responsibility among employees were estimated and measured. The results of the research showed that, in the process of accepting social responsibility among employees, the component of ethics of business in the first priority and the component of economic needs were placed in the top priority.
Keywords
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