Why buy organic rice? genetic algorithm-based fuzzy association mining rules for means-end chain data

Autor: Nai-Hua Chen, Chi-Hsun Lee, Chi-Tsun Huang
Rok vydání: 2015
Předmět:
Zdroj: International Journal of Consumer Studies. 39:692-707
ISSN: 1470-6423
DOI: 10.1111/ijcs.12210
Popis: While empirical studies of organic food consumption have centred primarily on European and North American countries, the amount of research occurring in Asian countries is increasing. This article describes the attributes, consequences, and values influencing consumer perceptions and adoption of organic rice in Taiwan, where rice is the major food. Based on a means-end chain (MEC) rationale, regulatory focus theory and self-construal theory, this article describes the attributes, consequences and values influencing Taiwanese consumer perceptions and adoption of organic rice. Using a questionnaire and a sample of 300 organic food shoppers in Taiwan, we applied the MEC technique in a different fashion via the proposed genetic algorithm-based fuzzy association mining rules (GFAMR) algorithm to depict the attribute-consequence-value links to purchasing organic rice. This study has at least two merits: (a) it is among the first integrating regulatory focus theory, self-construal theory and MEC to explore the reason why Taiwanese consumers purchase organic rice and (b) it introduces a new method to quantitatively deal with MEC analysis. The results show that the most important ultimate values are fun and enjoyment in life and security, which are in line with the promotion focus and prevention focus, respectively, of regulatory focus theory. Furthermore, we found three consumer segments related to organic rice: prevention focused housekeepers, promotion-focused egoists, and promotion-focused (meta-personal self) altruists. The different paths found in the results can also provide green companies and policy makers with more information about organic rice consumers, allowing them to craft better marketing and communication strategies by which to promote organic food.
Databáze: OpenAIRE
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