Abstract
The paper exemplifies a practical application of combining MNL, RPL and LCM econometric models to study consumer preference heterogeneity in the multi-attributive setting, by analyzing a case study of information traceability preferences of Beijing consumers who buy fresh tomatoes in the post-COVID period. Methodologically, such application of different models (MNL, RPL, LCM) has initially allowed to identify general patterns in Chinese consumers’ preference in the tomato traceability information, then to identify and categorize distinct groups of customers and finally to provide details to their ‘marketing’ profiles towards their willingness to pay. As a result, consumer groups in this study were classified around three key attributes of tomato traceability information which reflect their priorities: consumers from “Price sensitivity” group demonstrated a higher willingness to pay for information on how products were produced (production condition) and products’ certification; “Testing Information Preference” group was willing to pay for the information about tomato’s product quality detection, and “Official Authority Approval Preference” group has developed priority for information on production condition. Such methodological approach provides rather precise characteristics about three different consumer groups, and thus fills in the existing lacunae in the literature and can serve a guiding tool for designing a regional food safety policy. The suggested methodology is transferrable for analyzing consumers’ choices for traceability information about other food products and beyond China.
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