How consumers’ perception and information processing affect their acceptance of genetically modified foods in China: a risk communication perspective

Guo, Qiaozhe; Yao, Nengzhi; Zhu, Weiwei

Abstract

This study aims to explore the roles of consumers’ risk and benefit perception and food information processes in predicting their acceptance of genetically modified food. We integrate the protective action decision and heuristic systematic models to develop a conceptual model to predict customers’ purchase intention. We conducted a survey questionnaire with measures adapted from existing Likert scales. We used a sample of 573 respondents from Shandong Province, China, comprising people who had ever purchased genetically modified products. We tested our hypotheses using a structural equation model. Results suggest that perceived risk is a negative determinant of purchase intention, while perceived benefit is a positive factor of purchase intention. Moreover, perceived benefit is an important predictor of purchase intention. Perceived risk significantly affects information need, information seeking, and systematic processing. Perceived benefit has a positive relationship with information need and systematic processing. Information seeking is stimulated by information need and further predicts systematic processing. Our results suggest the effectiveness of the protective action decision and heuristic systematic models in predicting people’s intention to purchase genetically modified food and highlight the importance of risk communications in this context.

Citation

Guo, Q., Yao, N., & Zhu, W. (2020). How consumers’ perception and information processing affect their acceptance of genetically modified foods in China: a risk communication perspective. Food Research International, 137, Article 109518. https://doi.org/10.1016/j.foodres.2020.109518

• Journal Article Type: Article
• Acceptance Date: Jul 2, 2020
• Online Publication Date: Jul 9, 2020
• Publication Date: 2020-11
• Deposit Date: Jul 9, 2020
• Publicly Available Date: Jul 9, 2021
• Journal: Food Research International
• Print ISSN: 0963-9969
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 137
• Article Number: 109518
• DOI: https://doi.org/10.1016/j.foodres.2020.109518
• Public URL: https://durham-repository.worktribe.com/output/1261082