Chinese consumers' willingness-to-pay for safety label on tomato: evidence from choice experiments. Issue 1 (6th February 2017)

• Record Type: Journal Article
• Authors: Yin, Shijiu; Chen, Mo; Xu, Yingjun; Chen, Yusheng
• Is Part Of: China agricultural economic review. Volume 9:Issue 1(2017)
• Page Start: 141
• Page End: 155
• Publication Date: 2017-02-06
• Subjects: China -- Willingness-to-pay -- Choice experiment -- Random parameter logit model -- Safety label -- Tomato; Agriculture -- Economic aspects -- China -- Periodicals; Rural development -- China -- Periodicals; Agriculture and state -- China -- Periodicals; 338.10951
• DOI: 10.1108/CAER-11-2015-0147
• Languages: English
• ISSNs: 1756-137X

Abstract

Abstract : Purpose: Unlike some developed countries, Chinese food safety certification system is multi-level including organic/green/hazard-free certifications. The purpose of this paper is to assess consumers' preferences for tomatoes carrying these different labels. Design/methodology/approach: Data used in this study came from choice experiments (CEs) conducted in Shandong province, China. Based on experiment data, a random parameter logit model was established to analyze consumers' willingness-to-pay (WTP). Findings: Consumers' WTP for organic tomatoes was higher than that for hazard-free and green-certified tomatoes. Furthermore, consumers' WTP for the European Union (EU) organic label was higher than that for the Chinese organic label, whereas a non-significant difference existed between the levels of consumers' WTP for hazard-free and green-certified tomatoes. Consumers with different food safety risk perception (FSRP) had large differences in WTP, whereas those with varying environmental awareness (ENAW) had similar levels of WTP. Originality/value: This contribution is the first research which focuses on consumers' WTP for EU organic label, Chinese organic label, green label, or hazard-free label on tomato through CEs in China. Furthermore, the influence of consumers' FSRP and ENAW on their preference was analyzed through a random parameter logit model.