| Summary: | Fresh agricultural products are characterised by strong seasonality and perishability. Ensuring their freshness and quality during transportation within cold chain logistics systems presents a critical challenge for enterprises managing these goods. Hence, the adoption of Artificial Intelligence (AI) in cold chain logistics systems has become essential for advancing agricultural logistics. Leveraging the growing integration of AI within the agricultural sector, this study investigates the determinants of AI adoption in cold chain logistics systems among Chinese fresh agricultural product enterprises, using the Technology-Organization-Environment (TOE) framework. Complementing this focus, the study also investigates the moderating factors related to AI ethics, ensuring that its adoption does not result in adverse effects on the domain or its stakeholders. This study used a questionnaire survey to collect data from 368 managers in large and medium-sized fresh agricultural product companies in China. A purposive sampling method was used to select participants who had experience with AI in cold chain logistics. The data were analysed using PLS-SEM to explore the factors influencing AI adoption. The findings reveal that factors including technical relative advantage, complexity, compatibility, adoption cost, top management support, organizational readiness, government support, and vendor support play a significant role in influencing the adoption of AI technology by these enterprises. AI ethics functions as a significant moderating variable, particularly influencing the relationships between technical relative advantage, compatibility, top management support, organizational readiness, government support, and vendor support. The ethical adoption model established by this study provides a foundation for future research and offers valuable insights for the ethical adoption of AI in Chinese enterprises. By prioritizing ethical considerations, this approach fosters the sustainable development of the cold chain logistics industry, ensuring that AI adoption benefits all stakeholders while minimizing potential risks.
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