Investigating factors influencing consumer willingness to buy GM food and nano-food

  • Chengyan Yue
  • Shuoli Zhao
  • Christopher Cummings
  • Jennifer Kuzma
Research Paper


Emerging technologies applied to food products often evoke controversy about their safety and whether to label foods resulting from their use. As such, it is important to understand the factors that influence consumer desires for labeling and their willingness-to-buy (WTB) these food products. Using data from a national survey with US consumers, this study employs structural equation modeling to explore relationships between potential influences such as trust in government to manage technologies, views on restrictive government policies, perceptions about risks and benefits, and preferences for labeling on consumer’s WTB genetically modified (GM) and nano-food products. Some interesting similarities and differences between GM- and nano-food emerged. For both technologies, trust in governing agencies to manage technologies did not influence labeling preferences, but it did influence attitudes about the food technologies themselves. Attitudes toward the two technologies, as measured by risk–benefit comparisons and comfort with consumption, also greatly influenced views of government restrictive policies, labeling preferences, and WTB GM or nano-food products. For differences, labeling preferences were found to influence WTB nano-foods, but not WTB GM foods. Gender and religiosity also had varying effects on WTB and labeling preferences: while gender and religiosity influenced labeling preferences and WTB for GM foods, they did not have a significant influence for nano-foods. We propose some reasons for these differences, such as greater media attention and other heuristics such as value-based concerns about “modifying life” with GM foods. The results of this study can help to inform policies and communication about the application of these new technologies in food products.


GM Nanotechnology Willingness to buy Structural equation modeling Food Labelling 



This work was supported by the USDA Grant NIFA 2012-70002-19403 awarded to the Food Policy Research Center of the University of Minnesota, and in part, by the Genetic Engineering and Society Center at North Carolina State University. All opinions are of the authors and not the USDA-FPRC or GES center. The authors would like to thank Jonathan Brown, Ph.D. student at the University of Minnesota, for early assistance in helping to develop the survey instrument.

Supplementary material

11051_2015_3084_MOESM1_ESM.docx (23 kb)
Supplementary material 1 (DOCX 23 kb)


  1. Aaker DA, Bagozzi RP (1979) Unobservable variables in structural equation models with an application in industrial selling. J Mark Res 16:147–158CrossRefGoogle Scholar
  2. Allen W, Cummins R (2012). Monsanto threatens to sue Vermont if legislators pass a bill requiring GMO food to be labeled. AlterNet, April 4th. Accessed 3 March 2014Google Scholar
  3. AMOS (2013) AMOS for windows, 21st edn. SPSS Inc., ChicagoGoogle Scholar
  4. Arbuckle J (2005) Amos 6.0 user’s guide. Marketing Department, SPSS IncorporatedGoogle Scholar
  5. Bagozzi RP (1994) Structural equation models in marketing research: Basic principles. In: Bagozzi RP (ed) Principles of marketing research. Blackwell, Cambridge, pp 317–385Google Scholar
  6. Bentler PM (1990) Comparative fit indexes in structural models. Psychol Bull 107:238–246CrossRefGoogle Scholar
  7. Besley JC, Kramer VL, Priest SH (2008) Expert opinion on nanotechnology: risks, benefits, and regulation. J Nanopart Res 10:549–558CrossRefGoogle Scholar
  8. Bieberstein A, Roosen J, Marette S, Blanchemanche S, Vandermoere F (2013) Consumer choices for nano-food and nano-packaging in France and Germany. Eur Rev Agric Econ 40:73–94CrossRefGoogle Scholar
  9. Bollen KA (1998) Structural equation models. Wiley Online LibraryGoogle Scholar
  10. Bouwmeester H, Dekkers S, Noordam MY, Hagens WI, Bulder AS, De Heer C, Ten Voorde SE, Wijnhoven SW, Marvin HJ, Sips AJ (2009) Review of health safety aspects of nanotechnologies in food production. Regul Toxicol Pharmacol 53:52–62CrossRefGoogle Scholar
  11. Bredahl L (1999) Consumers cognitions with regard to genetically modified foods: results of a qualitative study in four countries. Appetite 33:343–360CrossRefGoogle Scholar
  12. Brown J, Kuzma J (2013) Hungry for information: public attitudes toward food nanotechnology and labeling. Rev Policy Res 30:512–548Google Scholar
  13. Cardello AV, Schutz HG, Lesher LL (2007) Consumer perceptions of foods processed by innovative and emerging technologies: a conjoint analytic study. Innov Food Sci Emerg Technol 8:73–83CrossRefGoogle Scholar
  14. Carmines EG, McIver JP (1981) Analyzing models with unobserved variables: Analysis of covariance structures. In: Bohrnstedt GW, Borgatta EF (eds) Social measurement: current issues. Sage, Newbury Park, pp 65–115Google Scholar
  15. Caswell JA (1998) Should use of genetically modified organisms be labeled? AgBioForum 1:22–24Google Scholar
  16. Center for Food Safety (2014) U.S. Polls on GE Food Labeling. Available at
  17. Chen M-F (2008) An integrated research framework to understand consumer attitudes and purchase intentions toward genetically modified foods. Br Food J 110:559–579CrossRefGoogle Scholar
  18. Chen M-F, Li H-L (2007) The consumer’s attitude toward genetically modified foods in Taiwan. Food Qual Prefer 18:662–674CrossRefGoogle Scholar
  19. Chern WS, Rickertsen K, Tsuboi N, Fu T-T (2002) Consumer acceptance and willingness to pay for genetically modified vegetable oil and salmon: a multiple-country assessment. AgBioForum 5:105–112Google Scholar
  20. Colson G, Rousu M (2013) What do consumer surveys and experiments reveal and conceal about consumer preferences for genetically modified foods? GM Crops Food 4(3):1–8CrossRefGoogle Scholar
  21. Cook AJ, Fairweather JR (2007) Intentions of New Zealanders to purchase lamb or beef made using nanotechnology. Br Food J 109:675–688CrossRefGoogle Scholar
  22. Dean M, Raats MM, Grunert KG, Lumbers M (2009) Factors influencing eating a varied diet in old age. Public Health Nutr 12:2421–2427CrossRefGoogle Scholar
  23. DeNavas-Walt C, Proctor BD, Smith JC (2010) US Census Bureau, Current Population Reports, P60-238. Income, poverty, and health insurance coverage in the United States, 2009Google Scholar
  24. Dudo A, Choi D-H, Scheufele DA (2011) Food nanotechnology in the news. Coverage patterns and thematic emphases during the last decade. Appetite 56:78–89CrossRefGoogle Scholar
  25. Eagly AH, Chaiken S (1993) The psychology of attitudes. Harcourt Brace Jovanovich College Publishers, OrlandoGoogle Scholar
  26. Finucane ML, Slovic P, Mertz CK, Flynn J, Satterfield TA (2000) Gender, race, and perceived risk: the ‘white male’ effect. Health Risk Soc 2:159–172CrossRefGoogle Scholar
  27. Fishbein M, Ajzen I (1975) Belief, attitude, intention and behavior: an introduction to theory and research. Addison-Wesley, Reading MAGoogle Scholar
  28. Ford D, Ferrigno L (2014) Vermont governor signs GM food labeling into law, CNN News, 8 MayGoogle Scholar
  29. Frewer LJ, Scholderer J, Bredahl L (2003) Communicating about the risks and benefits of genetically modified foods: the mediating role of trust. Risk Anal 23:1117–1133CrossRefGoogle Scholar
  30. Frewer L, Lassen J, Kettlitz B, Scholderer J, Beekman V, Berdal KG (2004) Societal aspects of genetically modified foods. Food Chem Toxicol 42:1181–1193CrossRefGoogle Scholar
  31. Frewer LJ, van der Lans IA, Fischer AR, Reinders MJ, Menozzi D, Zhang X, van den Berg I, Zimmermann KL (2013) Public perceptions of agri-food applications of genetic modification—a systematic review and meta-analysis. Trends Food Sci Technol 30:142–152CrossRefGoogle Scholar
  32. Ganiere P, Chern WS, Hahn D (2006) A continuum of consumer attitudes toward genetically modified foods in the United States. J Agric Resour Econ 31:129–149Google Scholar
  33. Grunert KG, Bredahl L, Scholderer J (2003) Four questions on European consumers’ attitudes toward the use of genetic modification in food production. Innov Food Sci Emerg Technol 4(4):435–445CrossRefGoogle Scholar
  34. Hallman WK (2012) Public perceptions of GM foods. The Food Policy Institute at Rutgers, The State University of New Jersey, White PaperGoogle Scholar
  35. Harris (2012) Nanotechnology Awareness may be low, but opinions are strong. The Harris Poll #52, September 6, 2012Google Scholar
  36. Hellier PK, Geursen GM, Carr RA, Rickard JA (2003) Customer repurchase intention: a general structural equation model. Eur J Mark 37:1762–1800CrossRefGoogle Scholar
  37. Hoban TJ (1998) Trends in consumer attitudes about agricultural biotechnology. AgBioForum 1:4Google Scholar
  38. Hossain F, Onyango B, Adelaja A, Schilling B, Hallman W (2004) Consumer acceptance of food biotechnology: willingness to buy genetically modified food products. J Int Food Agribus Market 15:53–76CrossRefGoogle Scholar
  39. Hu LT, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model 6:1–55CrossRefGoogle Scholar
  40. Huang M-Y, Huston SA, Perri M (2013) Consumer preferences for the predictive genetic test for alzheimer disease. J Genet Couns 23:172–178CrossRefGoogle Scholar
  41. Huffman WE (2003) Consumers’ acceptance of (and resistance to) genetically modified foods in high-income countries: effects of labels and information in an uncertain environment. Am J Agric Econ 85:1112–1118CrossRefGoogle Scholar
  42. Huffman WE, Shogren JF, Rousu M, Tegene A (2003) Consumer willingness to pay for genetically modified food labels in a market with diverse information: evidence from experimental auctions. J Agric Resour Econ 28:481–502Google Scholar
  43. International Food Information Council (2014) IFIC survey: consumer perceptions of food technology, 16th Ed., The International Food Information Council Foundation, Accessed March 2014
  44. Kalaitzandonakes N, Marks LA, Vickner SS (2007) Consumer response to mandated labeling of genetically modified foods, labeling genetically modified food: the philosophical and legal debate. Oxford University Press, New YorkGoogle Scholar
  45. Katare B, Yue C, Hurley T (2013) Consumer willingness to pay for nano-packaged food products: evidence from eye-tracking technology and experimental auctions, 2013 Annual Meeting, August 4–6, 2013, Washington, DC, Agricultural and Applied Economics AssociationGoogle Scholar
  46. Kim RB (2009) Factors influencing Chinese consumer behaviour when buying innovative food products. Agric Econ 55:436–445Google Scholar
  47. Kopicki A (2013) Strong support for labeling modified foods. New York Times, July 27, 2013Google Scholar
  48. Kuzma J, Priest S (2010) Nanotechnology, risk, and oversight: learning lessons from related emerging technologies. Risk Anal 30(11):1688–1698CrossRefGoogle Scholar
  49. Loureiro ML, Hine S (2004) Preferences and willingness to pay for GM labeling policies. Food Policy 29:467–483CrossRefGoogle Scholar
  50. Martinez-Poveda A, Molla-Bauza MB, del Campo Gomis FJ, Martinez LM-C (2009) Consumer-perceived risk model for the introduction of genetically modified food in Spain. Food Policy 34:519–528CrossRefGoogle Scholar
  51. McGuire WJ (1969) The nature of attitudes and attitude change. Handb Soc Psychol 3:136–314Google Scholar
  52. Michaelidou N, Hassan LM (2010) Modeling the factors affecting rural consumers’ purchase of organic and free-range produce: a case study of consumers’ from the Island of Arran in Scotland, UK. Food Policy 35:130–139CrossRefGoogle Scholar
  53. Millsap RE, Kwok O-M (2004) Evaluating the impact of partial factorial invariance on selection in two populations. Psychol Methods 9:93–99CrossRefGoogle Scholar
  54. Monica JC Jr (2008) FDA labeling of cosmetics containing nanoscale materials. Nanotechnol Law Bus 5:63–71Google Scholar
  55. Moon W, Balasubramanian SK (2001) Public perceptions and willingness-to-pay a premium for non-gm foods in the US and UK. AgBioForum 4:221–231Google Scholar
  56. Noussair C, Robin S, Ruffieux B (2002) Do consumers not care about biotech foods or do they just not read the labels? Econ Lett 75:47–53CrossRefGoogle Scholar
  57. NRC (2004) Safety of genetically engineered foods. National Academies Press, Washington, DCGoogle Scholar
  58. NRC (2009) Review of federal strategy for nanotechnology-related environmental, health, and safety research. National Academies Press, Washington, DCGoogle Scholar
  59. Nunnally JC, Bernstein I (1978) Psychometry theory. McGraw Hill, New YorkGoogle Scholar
  60. Palmer C (2003) Risk perception: another look at the ‘white male’ effect. Health Risk Soc 5(1):71–83CrossRefGoogle Scholar
  61. Phillips DM, Hallman WK (2013) Consumer risk perceptions and marketing strategy: the case of genetically modified food. Psychol Market 30(9):739–748CrossRefGoogle Scholar
  62. Poortinga W, Pidgeon NF (2005) Trust in risk regulation: cause or consequence of the acceptability of GM food? Risk Anal 25:199–209CrossRefGoogle Scholar
  63. Project on Emerging Nanotechnologies (2014) Consumer products inventory: an inventory of nanotechnology-based consumer products introduced on the market. Available at Last Accessed 16 Sept 2014
  64. Roco MC, Mirkin CA, Hesam MC (2010) Nanotechnology research directions for societal needs in 2020: retrospective and outlook. WTEC Study on Nanotechnology Research Directions, World Technology Evaluation Center, ArlingtonGoogle Scholar
  65. Rodríguez-Entrena M, Salazar-Ordóñez M, Sayadi S (2013) Applying partial least squares to model genetically modified food purchase intentions in southern Spain consumers. Food Policy 40:44–53CrossRefGoogle Scholar
  66. Roe B, Teisl MF (2007) Genetically modified food labeling: the impacts of message and messenger on consumer perceptions of labels and products. Food Policy 32:49–66CrossRefGoogle Scholar
  67. Rousu M, Monchuk D, Shogren J, Kosa K (2005) Consumer perceptions of labels and the willingness to pay for ‘second-generation’ genetically modified products. J Agric Appl Econ 37:647–657Google Scholar
  68. Saba A, Vasallo M (2002) Consumer attitudes toward the use of gene technology in tomato production. Food Qual Prefer 13(1):107–109CrossRefGoogle Scholar
  69. Saunders C, Guenther M, Tait P, Saunders J (2013) Assessing consumer preferences and willingness to pay for NZ food attributes in China, India and the UK, Proceedings of the 87th Annual Conference of the Agricultural Economics Society, University of Warwick, United Kingdom, pp 8–10Google Scholar
  70. Scheufele DA, Corley EA, Shih T, Kajsa Dalrymple E, Ho SS (2008) Religious beliefs and public attitudes toward nanotechnology in Europe and the United States. Nat Nanotechnol 4:91–94CrossRefGoogle Scholar
  71. Shaw D, Shiu E (2002) An assessment of ethical obligation and self-identity in ethical consumer decision-making: a structural equation modelling approach. Int J Consum Stud 26:286–293CrossRefGoogle Scholar
  72. Siegrist M (2000) The influence of trust and perceptions of risks and benefits on the acceptance of gene technology. Risk Anal 20:195–204CrossRefGoogle Scholar
  73. Siegrist M, Keller C (2011) Labeling of nanotechnology consumer products can influence risk and benefit perceptions. Risk Anal 31:1762–1769CrossRefGoogle Scholar
  74. Siegrist M, Cousin M-E, Kastenholz H, Wiek A (2007) Public acceptance of nanotechnology foods and food packaging: the influence of affect and trust. Appetite 49:459–466CrossRefGoogle Scholar
  75. Siegrist M, Stampfli N, Kastenholz H (2009) Acceptance of nanotechnology foods: a conjoint study examining consumers’ willingness to buy. Br Food J 111:660–668CrossRefGoogle Scholar
  76. SPSS (2013) SPSS for Windows, 21st edn. SPSS Inc, ChicagoGoogle Scholar
  77. Teisl MF, Garner L, Roe B, Vayda ME (2003) Labeling genetically modified foods: how do US consumers want to see it done? AgBioForum 6:6Google Scholar
  78. Toma L, McVittie A, Hubbard C, Stott AW (2011) A structural equation model of the factors influencing British consumers’ behaviour toward animal welfare. J Food Prod Market 17:261–278CrossRefGoogle Scholar
  79. United States Department of Agriculture, National Agricultural Statistics Service (NASS) (2012) Acreage Report, June 29Google Scholar
  80. Vandermoere F, Blanchemanche S, Bieberstein A, Marette S, Roosen J (2011) The public understanding of nanotechnology in the food domain: the hidden role of views on science, technology, and nature. Public Underst Sci 20(2):195–206.Google Scholar
  81. Verdurme A, Viaene J (2003a) Consumer attitudes towards GM food: literature review and recommendations for effective communication. J Int Food Agribus Market 13:77–98CrossRefGoogle Scholar
  82. Verdurme A, Viaene J (2003b) Consumer beliefs and attitude towards genetically modified food: basis for segmentation and implications for communication. Agribusiness 19:91–113CrossRefGoogle Scholar
  83. Worsley A, Wang WC, Hunter W (2013) Gender differences in the influence of food safety and health concerns on dietary and physical activity habits. Food Policy 41:184–192CrossRefGoogle Scholar
  84. Yawson RM, Kuzma J (2010) Systems mapping of consumer acceptance of agrifood nanotechnology. J Consum Policy 33:299–322CrossRefGoogle Scholar
  85. Yue C, Zhuo S, Kuzma J (2014) Heterogeneous consumer preferences for nanotechnology and genetic-modification technology in food products. J Agric Econ. doi: 10.1111/1477-9552.12090 Google Scholar
  86. Zhou G (2013) Nanotechnology in the food system: consumer acceptance and willingness to pay. Theses and Dissertations-Agricultural Economics, Paper 10Google Scholar
  87. Zhou G, Hu W, Schieffer J, Robbins, L (2013) Public acceptance of and willingness to pay for nanofood: case of canola oil. In 2013 Annual Meeting, August 4–6, 2013, Washington, DC (No. 149662)Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Chengyan Yue
    • 1
  • Shuoli Zhao
    • 2
  • Christopher Cummings
    • 3
  • Jennifer Kuzma
    • 4
  1. 1.Departments of Applied Economics and Horticultural Science, Bachman Endowed Chair in Horticultural MarketingUniversity of Minnesota-Twin CitiesSt. PaulUSA
  2. 2.Department of Applied EconomicsUniversity of Minnesota-Twin CitiesSt. PaulUSA
  3. 3.Division of Communication Research, Wee Kim Wee School of Communication and InformationNanyang Technological UniversitySingaporeSingapore
  4. 4.Genetic Engineering & Society CenterNorth Carolina State UniversityRaleighUSA

Personalised recommendations