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The role of product-related information and factors impacting consumer attitudes during health-conscious food purchase in Hungary

Author

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  • Soós, Gabriella
  • Biacs, Péter Ákos

Abstract

The aim of this study is to identify factors impacting consumer attitudes towards the purchase of functional foods, also known as foods with a positive physiological impact on health, in Hungary. Our work also focuses on the volume of information currently available to consumers when making such a choice, and on identifying consumer clusters. Particular attention is paid to the extent to which the available information can impact the respective purchase decision, which channels are used in obtaining such information, and which information is considered reliable or unreliable by shoppers. Based on the results of focus group research, we conducted a questionnaire-based survey (n=502). To reduce the high number and hard-to-interpret attitude variables, a factor analysis was performed, followed by the formation of consumer segments via cluster analysis according to the consumer attitude indicators. These segments were termed Health-conscious consumers, Consumers with limited information, The sceptics and The price conscious, and were characterised according to socio-demographic, behavioural and attitude variables. Then, we sought to identify the sources of information that would best address a given segment, and explored the efficiency of information transfer in the functional food market.

Suggested Citation

  • Soós, Gabriella & Biacs, Péter Ákos, 2018. "The role of product-related information and factors impacting consumer attitudes during health-conscious food purchase in Hungary," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 120(1), April.
  • Handle: RePEc:ags:stagec:273115
    DOI: 10.22004/ag.econ.273115
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    References listed on IDEAS

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    1. Jureckova, Jana & Picek, Jan, 2007. "Shapiro-Wilk-type test of normality under nuisance regression and scale," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 5184-5191, June.
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