Revolutionizing cross-border e-commerce: A deep dive into AI and big data-driven innovations for the straw hat industry.

Journal: PloS one
PMID: 39705240

Abstract

This paper investigates the impact of artificial intelligence (AI) and big data analytics on optimizing cross-border e-commerce efficiency for straw hat manufacturers in Zhejiang Province, China. It identifies market and consumer demand trends through machine learning analysis of comprehensive e-commerce data and leverages generative AI to revolutionize production and marketing processes. The integration of AI-generated content (AIGC) technology facilitates streamlined design-to-production cycles and rapid adaptation to market changes and consumer feedback. Findings demonstrate that the application of AI and big data significantly enhances market responsiveness and sales performance for straw hat enterprises in cross-border e-commerce. This research contributes a novel framework for employing AI and big data to navigate the complexities of international commerce, providing strategic insights for small and micro enterprises seeking to expand their global market footprint.

Authors

  • Junjie Dai
    College of Science and Technology, Ningbo University, Ningbo, Zhejiang, China.
  • Xiaoyan Mao
    College of Science and Technology, Ningbo University, Ningbo, Zhejiang, China.
  • Pengyue Wu
    College of Science and Technology, Ningbo University, Ningbo, Zhejiang, China.
  • Huijie Zhou
    College of Science and Technology, Ningbo University, Ningbo, Zhejiang, China.
  • Lei Cao
    State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning, People's Republic of China. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning, People's Republic of China. University of Chinese Academy of Sciences, Beijing, People's Republic of China.

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