فاطمه احمدی

Social Responsibility Accounting (SRA) represents a vital framework that empowers stakeholders to evaluate how effectively an organization fulfills its social and environmental responsibilities through transparent and evidence‑based disclosures. This study seeks to identify and optimize the key components of SRA that most effectively mitigate adverse environmental impacts, employing the Grey Wolf Optimization Algorithm (GWO) within the operational context of Ilam International Cement Company. The research adopts a mixed‑methods design to ensure both conceptual depth and empirical accuracy. In the qualitative phase, a systematic literature review was carried out to extract SRA components directly associated with environmental impact reduction. Out of an initial collection of 178 relevant publications, 16 studies were selected based on rigorous screening criteria, resulting in 12 core SRA components. In the quantitative phase, primary data were collected using a structured questionnaire and analyzed through the application of the Grey Wolf Optimizer to determine optimal combinations of these components. The findings reveal that when six critical components—(1) the degree of commitment to social responsibility, (2) involvement in distinctive or exceptional sustainability actions, (3) clarity and transparency of SRA objectives, (4) stakeholder interaction and communication, (5) integration of SRA into strategic planning and budgeting, and (6) the extent of expenditure and investment in social initiatives—each exceed a threshold value of one, the organization achieves maximum effectiveness in reducing environmental harm. This study demonstrates that integrating theoretically grounded SRA dimensions with advanced metaheuristic optimization methods such as the Grey Wolf Algorithm can substantially enhance an organization’s ability to meet both environmental and social sustainability objectives. The results provide a robust and operational framework for industrial enterprises aiming to strengthen their sustainability accounting, enhance stakeholder confidence, and align their organizational practices with internationally recognized environmental governance standards.

Financial resilience in businesses refers to their ability to withstand economic shocks and challenges while maintaining financial stability under difficult conditions. This study adopts an applied research approach with both descriptive and prescriptive future-oriented methods. It is qualitative research that uses Causal Layered Analysis (CLA) to identify financial resilience in entrepreneurial businesses. To achieve a deep understanding of causal layers, scenarios are developed based on the global business network perspective. Two rounds of interviews were conducted with 35 experts, both structured and unstructured, to extract financial resilience indicators in Iranian entrepreneurial businesses. From the literature review and expert interviews, 35 factors were identified. Two factors, enthusiasm and fear of failure, were eliminated, resulting in 33 final factors. The matrix of financial resilience scenarios for entrepreneurial businesses was presented in four scenarios: economic crisis, economic boom, old technology, and new technology. Subsequently, SWOT analysis was used to analyze and propose strategies aimed at directing towards the third scenario. The findings indicate that utilizing the CLA approach aims to offer a plan in the field of financial resilience for entrepreneurial businesses. This helps planners to set aside current thinking and consider possible and probable futures, which may not necessarily be a continuation of past trends, to achieve a long-term plan to enhance financial resilience in entrepreneurial businesses.