Understanding Retailers’ Intentions to Use AI for Product Waste Reduction in Grocery Supply Chains: Extending the Technology Acceptance Model

Product waste in grocery supply chains remains a major concern for multiple stakeholders, particularly retailers, due to the direct financial losses it generates and the potential risks it poses to customer health and safety. In this context, digital technologies—especially artificial intelligence (AI)—offer promising opportunities to improve retail performance and reduce waste. Accordingly, this study aims to investigate the factors influencing retailers’ intentions to adopt AI-based solutions for product waste reduction. To achieve this objective, the Technology Acceptance Model (TAM) was extended by incorporating three additional constructs (i.e., perceived ethical responsibility, product waste reduction-related knowledge, and perceived economic utility of AI for product waste reduction). Data were collected from a purposive sample of 214 grocery retailers operating in major cities in northern Algeria. Structural Equation Modeling (SEM) was employed to test the proposed research model and hypotheses. The results indicate that retailers’ behavioral intentions to use AI for product waste reduction are significantly influenced by perceived economic utility of AI, AI for product waste reduction-related knowledge, perceived usefulness, and perceived ease of use. In contrast, perceived ethical responsibility for product waste reduction did not exhibit a statistically significant effect, although its relationship with behavioral intention was positive. This study contributes to the growing literature on AI adoption for waste reduction in the retail sector, particularly within developing country contexts, and offers practical insights for policymakers and industry stakeholders seeking to promote the adoption of digital technologies for sustainable supply chain management.