Market dynamics and E-commerce satisfaction in China's aquatic food sector: Machine learning and data insights

Abstract

China's growing demand for aquatic foods, driven by the rapid expansion of e-commerce, is reshaping global seafood markets and influencing the broader sustainable food system. This transformation is altering domestic market dynamics and creating new challenges and opportunities in international trade, sustainable supply chains, and market competitiveness. This study investigates production trends, import reliance, and consumer e-commerce satisfaction in the aquatic food market, with a focus on implications for sustainable supply chain policy and management. By employing supervised machine learning technique, Support Vector Machines (SVM), along with Latent Dirichlet Allocation (LDA), Mann-Whitney U test, and logistic regression, the study uncovers critical insights into consumer preferences, including the factors driving e-commerce satisfaction, and supply chain dynamics, such as the impact of product freshness and delivery efficiency.

The study highlights the growing reliance on imports in China's aquatic food market, despite expanding domestic production. Fresh and frozen products, particularly crustaceans and finfish, consistently receive higher consumer satisfaction on e-commerce platforms, primarily due to their quality and freshness. Domestic producers face increasing pressure to meet these high standards, particularly in freshness, quality control, and delivery efficiency. The findings point to challenges in meeting consumer expectations and suggest opportunities for policy interventions to enhance the competitiveness of domestic aquatic food products. The research highlights the transformative role of e-commerce platforms in shaping China's aquatic food market, providing actionable insights for policymakers, producers, and e-commerce stakeholders to navigate emerging trends, improve supply chain efficiency, and meet evolving consumer demands.