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A comparison of hypothetical survey rankings with consumer shopping behavior and product knowledge

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  • Grebitus, Carola
  • Colson, Gregory
  • Menapace, Luisa

Abstract

Hypothetical surveys are commonly used to elicit consumer behavior to guide product development, marketing, and labeling strategies. However, despite the prevalence of surveys in consumer food studies, previous work has not assessed the relationship between hypothetical responses and actual consumer behavior in real-world purchase situations.We explore whether attributes cited by consumers in surveys as being important to them when making decisions indeed factor into their product decision process in real-world markets. Evidence from a point of sale study of 702 pork purchasers indicates that there is a strong correspondence between hypothetical survey ratings and actual shopping behavior.

Suggested Citation

  • Grebitus, Carola & Colson, Gregory & Menapace, Luisa, . "A comparison of hypothetical survey rankings with consumer shopping behavior and product knowledge," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 44(1), pages 1-13.
    • Handle: RePEc:ags:joaaec:120448
    DOI: 10.22004/ag.econ.120448
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    Cited by:

    1. Banterle, Alessandro & Cavaliere, Alessia & Ricci, Elena Claire, 2012. "Food labelled Information: An Empirical Analysis of Consumer Preferences," 2012 International European Forum, February 13-17, 2012, Innsbruck-Igls, Austria 144960, International European Forum on System Dynamics and Innovation in Food Networks.
    2. Otieno, D., 2018. "Consumer Willingness to Pay for Fair Trade Attributes of Goat Meat in Kenya," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277156, International Association of Agricultural Economists.
    3. Otieno, David & Ogutu, Sylvester, 2015. "Consumer willingness to pay for animal welfare attributes in a developing country context: The case of chicken in Nairobi, Kenya," 2015 Conference, August 9-14, 2015, Milan, Italy 212602, International Association of Agricultural Economists.
    4. repec:vul:omefvu:v:9:y:2017:i:2:id:232 is not listed on IDEAS
    5. Balcombe, Kelvin & Bradley, Dylan & Fraser, Iain & Hussein, Mohamud, 2016. "Consumer preferences regarding country of origin for multiple meat products," Food Policy, Elsevier, vol. 64(C), pages 49-62.
    6. Iancu Ramona Maria, 2014. "Consumers’ Perception and Behavior Towards Ecosanogene Products Made by Goat Milk," Management of Sustainable Development, Sciendo, vol. 6(2), pages 87-92, December.
    7. Giovanna Sacchi & Vincenzina Caputo & Rodolfo M. Nayga, 2015. "Alternative Labeling Programs and Purchasing Behavior toward Organic Foods: The Case of the Participatory Guarantee Systems in Brazil," Sustainability, MDPI, vol. 7(6), pages 1-20, June.
    8. Banterle, Alessandro & Cavaliere, Alessia & Ricci, Elena Claire, 2013. "Food Labelled Information: An Empirical Analysis," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 3(2), pages 1-15, January.
    9. Paulius Neciunskas & Laura Tomaseviciute & Dovile Kazlauske & Justina Gineikiene & Ruta Kazlauskaite, 2017. "Uniqueness Perception And Willingness To Buy Protected Geographical Origin Versus Doppelgaenger Brands," Organizations and Markets in Emerging Economies, Faculty of Economics, Vilnius University, vol. 8(2).
    10. Cuffaro, Nadia & Di Giacinto, Marina, 2015. "Credence goods, consumers’ trust in regulation and high quality exports," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 4(2), pages 1-19, August.
    11. Shepherd, Jonathan D. & Saghaian, Sayed H., 2015. "Risk Perception and Trust Interaction in Response to Food Safety Events across Products and the Implications for Agribusiness Firms," Journal of Food Distribution Research, Food Distribution Research Society, vol. 46(3), pages 1-21, November.

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    More about this item

    Keywords

    Food Consumption/Nutrition/Food Safety; Marketing;

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture

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