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Neuromarketing: some remarks by an economic experiment on food consumer perception and ethic sustainability
Journal Title: RIVISTA DI STUDI SULLA SOSTENIBILITA' 
Author/s: Daniela Covino, Immacolata Viola, Tetiana Paientko, Flavio Boccia 
Year:  2021 Issue: Language: English 
Pages:  13 Pg. 187-199 FullText PDF:  97 KB
DOI:  10.3280/RISS2021-001011
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It is well recognized that decisions are taken by consumers on a wider basis than the rational itself. Neuromarketing is a field of studies that merges brain science with marketing knowledge. Methods based on neuroscience and technology can be used to better understand the way consumers react and process information from marketing stimuli. Mostly, neuromarketing techniques are used by agri-food firms in order to encourage specific types of food consumption, not always on the purpose of enhancing consumers’ well being, healthy eating habits and public health. Among various kind of neuroscience techniques, neuroimaging has been used in order to reveal information about consumer preferences, since they pro-vide knowledge about the way consumers process marketing stimulus, and the consequent decision making. The number of studies dealing with neuromarketing is constantly growing althought it suffers for some limits that many researchers identify with sustainable ethical issues. For the purpose of the present study, we are interested mainly in the way specific marketing messages can generate an emo-tional response, and consequent consumer choice, respecting the parameters of ethical sustainability.

  1. Allum N., Surgis P., Tabourazi D., Brunton-Smith I. (2008). Science knowledge and attitudes across cultures: A meta-analysis. Public Understanding of Science, 17(1): 35-54.
  2. Alpízar F., Carlsson F., Martinson P. (2003). Using Choice Experiments for Non-market Valuation. Economic Issues, 8(1): 83-110.
  3. Antunez L., Vidal L., Sapolinski A., Gimenez A., Maiche A., Ares G. (2013). How do design features influence consumer attention when looking for nutritional information on food labels? Results from an eye-tracking study on pan bread labels. International Journal of Food Sciences and Nutrition, 64(5): 515-527.
  4. Ares G., Deliza R. (2010). Studying the influence of package shape and colour on consumer expectations of milk desserts using word association and conjoint analysis. Food Quality and Preference, 21(8): 930-937.
  5. Ares G., Giménez A., Deliza R. (2010). Influence of three non-sensory factors on consumer choice of functional yogurts over regular ones. Food Quality and Preference, 21(4): 361-367.
  6. Balogh P., Békési D., Gorton M., Popp J., Lengyel P. (2016). Consumer willingness to pay for traditional food products. Food Policy, 61: 176-184.
  7. Bhat C.R. (2003). Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences. Transportation Research Part B: Methodological, 37(9): 837-855.
  8. Bialkova S., van Trijp H. C. (2011). An efficient methodology for assessing attention to and effect of nutrition information displayed front-of-pack. Food Quality and Preference, 22(6): 592-601.
  9. Bialkova S., Grunert K. G., Juhl H. J., Wasowicz-Kirylo G., Stysko-Kunkowska M., van Trijp H. C. (2014). Attention mediates the effect of nutrition label information on consumers’ choice. Evidence from a choice experiment involving eye-tracking. Appetite, 76: 66-75.
  10. Boccia F., Covino D. (2016). Innovation and sustainability in agri-food companies: the role of quality. Rivista di Studi sulla Sostenibilità, 1: 131-141.
  11. Boccia F., Sarnacchiaro P. (2020). Chi-squared automatic interaction detector analysis on a choice experiment: An evaluation of responsible initiatives on consumers’ purchasing behavior. Corporate Social Responsibility and Environmental Management, 27(2): 1143-1151.
  12. Boccia F., Sarno V. (2013). Consumer perception and corporate social responsibility: An explorative survey on food Italian market. Quality - Access to Success, 14(132): 110-112.
  13. Boccia F., Covino D., Sarnacchiaro P. (2018). Genetically modified food versus knowledge and fear: A Noumenic approach for consumer behaviour. Food Research International, 111: 682-688.
  14. Boccia F., Di Donato P., Covino D., Poli A. (2019). Food waste and bio-economy: A scenario for the Italian tomato market. Journal of Cleaner Production, 227: 424-433.
  15. Butler M. J. (2008). Neuromarketing and the perception of knowledge. Journal of Consumer Behaviour, 7(4-5): 415-419.
  16. Chae S. W., Lee K. C. (2013). Exploring the effect of the human brand on consumers’ decision quality in online shopping: An eye-tracking approach. Online Information Review, 37: 83-100.
  17. Coast J., Al-Janabi H., Sutton E.J., Horrocks S.A., Vosper A.J., Swancutt D.R., Flynn T.N. (2012). Using qualitative methods for attribute development for discrete choice experiments: issues and recommendations. Health Economics, 21(6): 730-741.
  18. Covino D., Boccia F. (2014). Environmental management and global trade’s effects. Quality - Access to Success, 15(138): 79-83.
  19. Covino D., Boccia F. (2016). Potentialities of new agri-biotechnology for sustainable nutrition. Rivista di Studi sulla Sostenibilità, 2: 97-106.
  20. Danner L., Haindl S., Joechl M., Duerrschmid K. (2014). Facial expressions and autonomous nervous system responses elicited by tasting different juices. Food Research International, 64: 81-90.
  21. Di Vaio A., Boccia F., Landriani L, Palladino R. (2020). Artificial intelligence in the agri-food system: Rethinking sustainable business models in the COVID-19 scenario. Sustainability (Switzerland), 12(12): 4851.
  22. Fortunato V. C. R., Giraldi J. D. M. E., de Oliveira J. H. C. (2014). A review of studies on neuromarketing: Practical results, techniques, contributions and limitations. Journal of Management Research, 6(2): 201.
  23. Fugate D. L. (2007). Neuromarketing: A layman's look at neuroscience and its potential application to marketing practice. Journal of Consumer Marketing, 24(7): 385-394.
  24. Fugate D. L. (2008). Marketing services more effectively with neuromarketing research: A look into the future. Journal of Services Marketing, 22(2): 170-173.
  25. Garcia J. R., Saad G. (2008). Evolutionary neuromarketing: Darwinizing the neuroimaging paradigm for consumer behavior. Journal of Consumer Behaviour, 7(4-5).
  26. Gofman A., Moskowitz H. R., Fyrbjork J., Moskowitz D., Mets T. (2009). Extending rule developing experimentation to perception of food packages with eye tracking. The Open Food Science Journal, 3: 66-78.
  27. Goldberg J. H., Probart C. K., Zak R. E. (1999). Visual search of food nutrition labels. Human Factors, 41: 425-437.
  28. Gracia A., Loureiro M.L., Nayga Jr R. M. (2009). Consumers’ valuation of nutritional information: a choice experiment study. Food Quality and Preference, 20(7): 463-471.
  29. Graham D. J., Orquin J. L., Visschers V. H. M. (2012). Eye tracking and nutrition label use: A review of the literature and recommendations for label enhancement. Food Policy, 37: 378-382.
  30. Greene W. H., Hensher D. A. (2003). A latent class model for discrete choice analysis: contrasts with mixed logit. Transportation Research Part B: Methodological, 37(8): 681-698.
  31. Hanley N., Wright R.E., Adamowicz V. (1998). Using Choice Experiments to value the Environment. Environmental and Resource Economics, 11(3): 413-428.
  32. Hensher D.A., Rose J.M., Greene W.H. (2005). Applied choice analysis: a primer. Cambridge: Cambridge University Press.
  33. Hubert M., Kenning P. (2008). A current overview of consumer neuroscience. Journal of Consumer Behaviour, 7(4-5): 272-292.
  34. Lewinski P., Fransen M. L., Tan E. S. H. (2014). Predicting advertising effectiveness by facial expressions in response to amusing persuasive stimuli. Journal of Neuroscience, Psychology, & Economics, 7(1): 1-14.
  35. Louviere J.J., Flynn T.N., Carson R.T. (2010). Discrete choice experiments are not conjoint analysis. Journal of Choice Modelling, 3(3): 57-72.
  36. McClure S. M. (2004). Neural correlates of behavioral preference for culturally familiar drinks. Neuron, 44: 379-387.
  37. McFadden D. (1973). Conditional Logit Analysis of Qualitative Choice Behaviour. In Zarembka P., (ed.). Frontiers in Econometrics. New York: Academic press.
  38. Monaco D., Rossella E. (2004). The effect of expectations generated by brand name on the acceptability of dried semolina pasta. Food Quality and Preference, 15(5): 429-437.
  39. Morrison M., Bennett J., Blamey R., Louviere J. (2002). Choice modeling and tests of benefit transfer. American Journal of Agricultural Economics, 84(1): 161-170.
  40. Murray J. M., Delahunty, C. M. (2000). Mapping consumer preference for the sensory and packaging attributes of Cheddar cheese. Food Quality and Preference, 11(5): 419-435.
  41. Ohme R., Matukin M. (2012). A small frog that makes a big difference: Brain wave testing of TV advertisements. IEEE Pulse, 3(3): 28-33.
  42. Perrachione T. K., Perrachione J. R. (2008). Brains and brands: Developing mutually informative research in neuroscience and marketing. Journal of Consumer Behaviour, 7(4-5): 303-318.
  43. Piqueras-Fiszman B., Velasco C., Salgado-Montejo A., Spence, C. (2013). Using combined eye tracking and word association in order to assess novel packaging solutions: A case study involving jam jars. Food Quality and Preference, 28: 328-338.
  44. Ryan M., Gerard K. (2003). Using discrete choice experiments to value health care: current practice and future prospects. Applied Health Economics and Health Policy, 2(1): 55-64.
  45. Sarno V., Barmo M. (2014). Sustainability management in the agri-food companies: a practical guide. Quality - Access to Success, 15 (141): 96-99.
  46. Senior C., Lee N. (2008). Editorial: A manifesto for neuromarketing science. Journal of Consumer Behaviour, 7(4-5): 263-271.
  47. Stasi A., Songa G., Mauri M., Ciceri A., Diotallevi F., Nardone G., Russo V. (2018). Neuromarketing empirical approaches and food choice: A systematica Review. Food Research International, 108: 650-664.
  48. Vecchiato G., Kong W., Maglione A., Wei D. (2012). Understanding the impact of TV commercials: Electrical neuroimaging. IEEE Pulse, 3(3): 42-47.
  49. Verbeke W. (2005) Consumer acceptance of functional foods: socio-demographic, cognitive and attitudinal determinants. Food quality and preference, 16 (1): 45-57.
  50. Wunderlich S., Gatto K.A. (2015). Consumer perception of genetically modified organisms and sources of information. Advances in Nutrition, 6(6):842-851.
  51. Page G. (2012). Scientific realism: what ‘neuromarketing’ can and can’t tell us about consumers. International Journal of Market Research, 54(2): 287-290.

Daniela Covino, Immacolata Viola, Tetiana Paientko, Flavio Boccia, in "RIVISTA DI STUDI SULLA SOSTENIBILITA'" 1/2021, pp. 187-199, DOI:10.3280/RISS2021-001011

   

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