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

Abstract 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.