Abstract
Investigating the determinant of consumer preference for game meat safety is crucial in promoting game meat consumption. In this study, we examined the impact on consumer preferences for a safety attribute, taking the individual risk attitude and the risk perception into account. We used data from a survey and a labeled discrete choice experiment involving 476 Italian consumers and analyzed it with a latent class model. The results show that all consumers gain utility from game meat with this safety claim. Furthermore, consistent groups of consumers who dislike game meat are likely to be risk-averse and perceive game meat as hazardous. Therefore, a marketing or public policy strategy aimed at promoting game meat consumption should focus on reinforcing consumers’ trust in more stringent safety standards. For instance, highlighting the safety measures and inspections involved in the production of game meat can help increase consumer confidence in its safety.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
Data available on request from the authors.
Notes
1 In Italy the regions are local authorities corresponding to NUTS 2 classification by Eurostat.
2 The study was approved by the Ethics Committee of the University of Pisa (Committee on Bioethics of the University of Pisa - Review No. 30/2022) and was conducted in accordance with the ethical principles expressed in the Declaration of Helsinki. Informed consent was obtained from respondents prior to the collection of survey data.
3 “We ask you to indicate your preferences exactly as you would if you were in a real grocery store and were going to face the consequences of your choice, namely that you would have to pay for the selected product. Therefore, answer as if you had actually bought the product because recent studies have shown that there are noticeable differences between the choice of a product in a hypothetical situation (surveys similar to this one) and in the real market” (Translated from Italian).
4 in appendix reports the estimates from the Mixed Logit Model.