Identification and Optimization of Social Responsibility Accounting Components Aimed at Minimizing Adverse Environmental Impacts Using Grey Wolf Algorithm

Ahmadi, Fatemeh; Parandin, Kaveh

doi:10.22077/jgdms.2025.8895.1259

Identification and Optimization of Social Responsibility Accounting Components Aimed at Minimizing Adverse Environmental Impacts Using Grey Wolf Algorithm

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نوع مقاله : مقاله پژوهشی

نویسندگان

Fatemeh Ahmadi ¹
Kaveh Parandin ²

¹ Department of Accounting, Ilam Branch, Islamic Azad University, Ilam, Iran

² Department of Accounting, Faculty of Management, Economics and Accounting, Payame Noor University, Tehran, Iran.

10.22077/jgdms.2025.8895.1259

چکیده

Social Responsibility Accounting serves as a vital tool, enabling stakeholders to evaluate organizations' performance in addressing social responsibility issues based on the information disclosed by these organizations. This research aims to identify and optimize the components of Social Responsibility Accounting to minimize adverse environmental impacts, utilizing the Grey Wolf Algorithm (GWA) at Ilam International Cement Company. In the qualitative phase of the study, a systematic review was conducted to extract components of Social Responsibility Accounting with a focus on reducing negative environmental impacts. Initially, 178 relevant articles were selected, and after screening, 16 articles were identified as pertinent to the research topic. From these, 12 key components were extracted. In the quantitative phase, the Grey Wolf Algorithm was applied to data collected through questionnaires. The findings revealed that if the values of six components level of social responsibility, unusual activities, transparency in social responsibility accounting objectives, interaction and communication with stakeholders, integration of social responsibility accounting into planning and budgeting, and the level of expenditure and investment in social activities exceed one, then Social Responsibility Accounting aimed at minimizing adverse environmental impacts at Ilam International Cement Company is maximized. This research demonstrates that the application of the identified components and their optimization using advanced algorithms such as the Grey Wolf Algorithm can significantly assist organizations in achieving their environmental and social goals. The results of this study can serve as a guide for other industrial organizations to improve their environmental and social performance.

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