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Consumer Attitudes towards Genetically Modified Foods in Emerging Markets: The Impact of Labeling in Taiwan

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  • Ganiere, Pierre
  • Chern, Wen S.
  • Hahn, David E.
  • Chiang, Fu-Sung

Abstract

In 2001, Taiwan enacted a law for genetically modified food (GM foods) labeling. Beginning January 1st 2003, food containing more than 5% of GM ingredients must be labeled. Taiwan imports most of its soybeans from the United States. In order to assess the effects of the new policy, a telephone survey was conducted in 2002. A total of 257 interviews were completed. A typology of consumers' attitudes towards GM foods is constructed from the use of a multiple correspondence analysis and a classification method. Four profiles are identified: proponents, 52%, moderate opponents, 32.5%, extreme opponents, 12.5%, and those with no opinion, 5.5%.

Suggested Citation

  • Ganiere, Pierre & Chern, Wen S. & Hahn, David E. & Chiang, Fu-Sung, 2004. "Consumer Attitudes towards Genetically Modified Foods in Emerging Markets: The Impact of Labeling in Taiwan," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 7(3), pages 1-20.
    • Handle: RePEc:ags:ifaamr:8150
    DOI: 10.22004/ag.econ.8150
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    References listed on IDEAS

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    1. Rousu, Matthew & Huffman, Wallace & Shogren, Jason F. & Tegene, Abebayehu, 2002. "The Value of Verifiable Information in a Controversial Market: Evidence from Lab Auctions of Genetically Modified Food," Staff General Research Papers Archive 10009, Iowa State University, Department of Economics.
    2. W. J. Florkowski & A. H. Elnagheeb & C. L. Huang, 1998. "Risk perception and new food production technologies," Applied Economics Letters, Taylor & Francis Journals, vol. 5(2), pages 69-73.
    3. Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
    4. Michael Greenacre & Rafael Pardo, 2006. "Subset Correspondence Analysis," Sociological Methods & Research, , vol. 35(2), pages 193-218, November.
    5. Ganiere, Pierre & Chern, Wen S. & Hahn, David E., 2004. "Who Are Proponents And Opponents Of Genetically Modified Foods In The United States?," Working Papers 28315, Ohio State University, Department of Agricultural, Environmental and Development Economics.
    6. Hallman, William K. & Metcalfe, Jennifer, 1994. "Public Perceptions Of Agricultural Biotechnology: A Survey Of New Jersey Residents," Research Reports 18170, Rutgers University, Food Policy Institute.
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    Cited by:

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    3. Liao, Shuling & Chou, Cindy Yunhsin & Lin, Tzu-Han, 2015. "Adverse behavioral and relational consequences of service innovation failure," Journal of Business Research, Elsevier, vol. 68(4), pages 834-839.

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