Data analysis of factors influencing consumers' payment price of traceable food

Abstract

Taking infant formula milk powder, an important food, as an example, this paper selects a total of 12 explanatory variables from three aspects: personal characteristics, family factors and psychological factors, takes consumers' willingness to pay for food traceability labels as dependent variable Y, and adopts binary logistic regression model to understand and analyze the influencing factors of consumers' willingness to pay for food traceability labels with big data collection and analysis. The results show that consumers' age, education background, monthly family income, consumers' trust in traceable labels and total family population will significantly affect consumers' willingness to pay for food traceability labels; specifically, younger consumers are more willing to pay for food traceability labels, consumers with higher education are more inclined to pay for food traceability labels, consumers with higher income are more inclined to pay for food traceability labels, consumers with higher education are more inclined to pay for food traceability labels, and consumers with high trust in traceability labels are more inclined to pay for food traceability labels.