The Role of Trust in Explaining Food Choice: Combining Choice Experiment and Attribute Best–Worst Scaling

• Main Authors: Ching-Hua Yeh, Monika Hartmann, Nina Langen
• Format: Article
• Language: English
• Published: MDPI AG 2020-01-01
• Series: Foods
• Subjects: preference; trust; choice experiment; best-worst scaling; latent class analysis; hierarchical bayesian mixed logit model
• Online Access: https://www.mdpi.com/2304-8158/9/1/45

This paper presents empirical findings from a combination of two elicitation techniques—discrete choice experiment (DCE) and best−worst scaling (BWS)—to provide information about the role of consumers’ trust in food choice decisions in the case of credence attributes. The analysis was based on a sample of 459 Taiwanese consumers and focuses on red sweet peppers. DCE data were examined using latent class analysis to investigate the importance and the utility different consumer segments attach to the production method, country of origin, and chemical residue testing. The relevance of attitudinal and trust-based items was identified by BWS using a hierarchical Bayesian mixed logit model and was aggregated to five latent components by means of principal component analysis. Applying a multinomial logit model, participants’ latent class membership (obtained from DCE data) was regressed on the identified attitudinal and trust components, as well as demographic information. Results of the DCE latent class analysis for the product attributes show that four segments may be distinguished. Linking the DCE with the attitudinal dimensions reveals that consumers’ attitude and trust significantly explain class membership and therefore, consumers’ preferences for different credence attributes. Based on our results, we derive recommendations for industry and policy.