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<p>This study investigates the country-of-origin (COO) effect in online red wine purchasing behavior through big data analytics, providing insights into the development of digital consumption. The analysis integrates structured data, such as user-generated content and product information, with unstructured data, including grape variety characteristics, to assess their influence on online purchasing decisions. K-means cluster analysis is applied to structured data, while hierarchical cluster analysis examines grape variety information. An AI-based Bayesian model is employed to predict the likelihood of COO preferences in online red wine purchases. This research enhances the understanding of COO-driven purchasing behavior and facilitates big data marketing strategies centered on consumer behavior in online reference communities based on user-generated content.</p>

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Country-of-origin effect in big data marketing of red wine: an AI-based Bayesian analysis of user-generated content

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月9日

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  • Huo Da,
  • Wenjia Gu,
  • Aidi Tang,
  • Sizheng Tang

摘要

This study investigates the country-of-origin (COO) effect in online red wine purchasing behavior through big data analytics, providing insights into the development of digital consumption. The analysis integrates structured data, such as user-generated content and product information, with unstructured data, including grape variety characteristics, to assess their influence on online purchasing decisions. K-means cluster analysis is applied to structured data, while hierarchical cluster analysis examines grape variety information. An AI-based Bayesian model is employed to predict the likelihood of COO preferences in online red wine purchases. This research enhances the understanding of COO-driven purchasing behavior and facilitates big data marketing strategies centered on consumer behavior in online reference communities based on user-generated content.