The impact of artificial intelligence on the performance of green supply chain management: an empirical study using spss

Environmental sustainability has become a strategic imperative for organizations due to increasing regulatory pressures, resource scarcity, and stakeholder expectations. Green Supply Chain Management (GSCM) has emerged as a comprehensive approach to integrate environmental considerations into procurement, production, logistics, and reverse logistics processes. At the same time, Artificial Intelligence (AI) is reshaping modern supply chains through advanced analytics, machine learning, predictive modeling, and automation. This study examines the impact of AI adoption on GSCM performance using a quantitative, survey-based approach. Data were collected from ۲۲۰ supply chain professionals across manufacturing, logistics, and service industries. The research model was tested using SPSS software through reliability analysis (Cronbach’s Alpha), Pearson correlation, and simple linear regression. The findings indicate that AI adoption has a significant positive effect on GSCM performance (β = ۰.۵۸, p < ۰.۰۰۱). Furthermore, AI contributes to improved environmental performance through waste reduction, optimized energy consumption, enhanced demand forecasting accuracy, and improved decision-making efficiency. The study highlights the strategic importance of AI in achieving sustainable supply chain transformation and provides practical implications for managers and policymakers seeking to enhance environmental sustainability through digital technologies.

کلیدواژه ها:

Artificial Intelligence ، Green Supply Chain Management ، Sustainability ، SPSS ، Regression Analysis ، Digital Transformation