ARTIFICIAL INTELLIGENCE IN CHINA'S RETAIL INDUSTRY: A SYSTEMATIC LITERATURE REVIEW
DOI:
https://doi.org/10.35631/JISTM.1142013Keywords:
Artificial Intelligence, China, Machine Learning, Retailing, Systematic ReviewAbstract
Artificial Intelligence (AI) has emerged as a transformative force in China's retail industry, enabling intelligent decision-making across demand prediction, dynamic pricing, supply chain optimization, and consumer behavior analysis. Despite the growing body of research, existing studies remain fragmented across diverse literature sources, lacking a structured and unbiased review framework. This fragmentation limits the ability to systematically assess AI applications for operational efficiency, resilience, and sustainability in China's retail sector, making it difficult for researchers and practitioners to identify best practices and prioritize high-impact AI solutions. To address this critical gap, this study makes two primary contributions. First, we develop a comprehensive systematic review methodology tailored to the field of AI in retailing, drawing on 450 peer-reviewed articles published between 2015 and 2025, sourced from the Web of Science Core Collection. Second, leveraging this methodology, we categorize prevalent AI techniques including machine learning, deep learning, reinforcement learning, and natural language processing. We then map these techniques to their practical applications within retail operations across the dimensions of efficiency, resilience, and sustainability. Furthermore, we identify critical research gaps and propose promising directions for future investigation. The proposed review framework and novel classification scheme provide a structured foundation for future empirical research and guide industry adoption of AI strategies in China's rapidly evolving retail landscape.
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