Key determinants of purchase intentions for geographical indication agricultural products: A hybrid PLS-SEM and ANN approach

Abstract

In recent years, the sales of Geographical Indication agricultural products (GI agri-products) have increased annually, yet various aspects of their perceived value remain inadequately defined. This study reconstructs the perceived value model for GI agri-products based on their unique regional attributes, while also integrating the Theory of Planned Behavior (TPB). Aims to delve into these factors to clarify how GI products attract consumers and influence their purchase decisions. A mixed-method approach was employed, combining PLS-SEM and Artificial Neural Networks (ANN) to analyze data collected from 358 consumers in the Chinese market. Notably, ANN complements SEM by addressing its limitations in capturing nonlinear relationships. Results indicate that perceived value is the primary driver of purchase intentions, followed by attitude and perceived behavioral control, with subjective norms having a lesser yet still significant impact. These insights provide valuable implications for marketing strategies, assisting stakeholders in effectively promoting GI agri-products. By enhancing consumers' experiences of the non-functional value of GI agri-products, marketing efforts for these products can be more effectively realized.