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Influence of Source Credibility on Consumer Acceptance of Genetically Modified Foods in China

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  • Mingyang Zhang

    (School of Economics and Management, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Chao Chen

    (College of Economics & Management, Nanjing Agricultural University, Nanjing 210095, China
    Center of Agriculture’s Genetically Modified Organisms’ Safety Management and Policy Research Organization of Nanjing Agricultural University (AGGMO), Nanjing 210095, China)

  • Wuyang Hu

    (Department of Agricultural Economics, University of Kentucky, Lexington, KY 40506, USA)

  • Lijun Chen

    (College of Economics & Management, Nanjing Agricultural University, Nanjing 210095, China)

  • Jintao Zhan

    (College of Economics & Management, Nanjing Agricultural University, Nanjing 210095, China)

Abstract

This paper examines the reasoning mechanism behind the consumer acceptance of genetically modified foods (GMFs) in China, and investigates influence of source credibility on consumer acceptance of GMFs. Based on the original Persuasion Model—which was developed by Carl Hovland, an American psychologist and pioneer in the study of communication and its effect on attitudes and beliefs—we conducted a survey using multistage sampling from 1167 urban residents, which were proportionally selected from six cities in three economic regions (south, central, and north) in the Jiangsu province through face to face interviews. Mixed-process regression that could correct endogeneity and ordered probit model were used to test the impact of source credibility on consumers’ acceptance of GMFs. Our major finding was that consumer acceptance of GMFs is affected by such factors as information source credibility, general attitudes, gender, and education levels. The reliability of biotechnology research institutes, government offices devoted to management of GM organisms (GMOs), and GMO technological experts have expedited urban consumer acceptance of GM soybean oil. However, public acceptance can also decrease as faith in the environmental organization. We also found that ignorance of the endogeneity of above mentioned source significantly undervalued its effect on consumers’ acceptance. Moreover, the remaining three sources (non-GMO experts, food companies, and anonymous information found on the Internet) had almost no effect on consumer acceptance. Surprisingly, the more educated people in our survey were more skeptical towards GMFs. Our results contribute to the behavioral literature on consumer attitudes toward GMFs by developing a reasoning mechanism determining consumer acceptance of GMFs. Particularly, this paper quantitatively studied the influence of different source credibility on consumer acceptance of GMFs by using mixed-process regression to correct endogeneity in information sources, while taking into consideration of information asymmetry and specific preference in the use of information sources.

Suggested Citation

  • Mingyang Zhang & Chao Chen & Wuyang Hu & Lijun Chen & Jintao Zhan, 2016. "Influence of Source Credibility on Consumer Acceptance of Genetically Modified Foods in China," Sustainability, MDPI, vol. 8(9), pages 1-16, September.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:9:p:899-:d:77460
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    References listed on IDEAS

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    1. Wallace E. Huffman & Matthew Rousu & Jason F. Shogren & Abebayehu Tegene, 2004. "Who Do Consumers Trust for Information: The Case of Genetically Modified Foods?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(5), pages 1222-1229.
    2. Zhang, Xiaoyong & Huang, Jikun & Qiu, Huanguang & Huang, Zhurong, 2010. "A consumer segmentation study with regards to genetically modified food in urban China," Food Policy, Elsevier, vol. 35(5), pages 456-462, October.
    3. David Roodman, 2011. "Fitting fully observed recursive mixed-process models with cmp," Stata Journal, StataCorp LP, vol. 11(2), pages 159-206, June.
    4. Annelies Verdurme & Jacques Viaene, 2003. "Consumer beliefs and attitude towards genetically modified food: Basis for segmentation and implications for communication," Agribusiness, John Wiley & Sons, Ltd., vol. 19(1), pages 91-113.
    5. Rodríguez-Entrena, Macario & Salazar-Ordóñez, Melania & Sayadi, Samir, 2013. "Applying partial least squares to model genetically modified food purchase intentions in southern Spain consumers," Food Policy, Elsevier, vol. 40(C), pages 44-53.
    6. Yingheng Zhou & Erpeng Wang, 2011. "Urban consumers' attitudes towards the safety of milk powder after the melamine scandal in 2008 and the factors influencing the attitudes," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 3(1), pages 101-111, February.
    7. Costa-Font, Montserrat & Gil, Jose Maria, 2007. "Structural Equation Modelling of Consumer Acceptance of Genetically Modified Food (GM) in the Mediterranean Europe: Spain, Greece and Italy," 103rd Seminar, April 23-25, 2007, Barcelona, Spain 9415, European Association of Agricultural Economists.
    8. Yingheng Zhou & Erpeng Wang, 2011. "an consumers' attitudes towards the safety of milk powder after the melamine scandal in 2008 and the factors influencing the attitudes," China Agricultural Economic Review, Emerald Group Publishing, vol. 3(1), pages 101-111, January.
    9. Costa-Font, Montserrat & Gil, José M. & Traill, W. Bruce, 2008. "Consumer acceptance, valuation of and attitudes towards genetically modified food: Review and implications for food policy," Food Policy, Elsevier, vol. 33(2), pages 99-111, April.
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    Cited by:

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    3. Changxin Yu & Haiyan Deng & Ruifa Hu, 2019. "Attitude Gaps with Respect to GM Non-Food Crops and GM Food Crops and Confidence in the Government’s Management of Biotechnology: Evidence from Beijing Consumers, Chinese Farmers, Journalists, and Gov," Sustainability, MDPI, vol. 12(1), pages 1-19, December.
    4. Haiyan Deng & Ruifa Hu & Carl Pray & Yanhong Jin, 2019. "Perception and Attitude toward GM Technology among Agribusiness Managers in China as Producers and as Consumers," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
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    7. Sheng, Jichuan & Qiu, Hong, 2018. "Governmentality within REDD+: Optimizing incentives and efforts to reduce emissions from deforestation and degradation," Land Use Policy, Elsevier, vol. 76(C), pages 611-622.

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