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Marketing motivations influencing food choice in 16 countries: segmentation and cluster analysis

Author

Listed:
  • Carla Henriques

    (Polytechnic Institute of Viseu, Portugal)

  • Ana Matos

    (Polytechnic Institute of Viseu, Portugal)

  • Madalena Malva

    (Polytechnic Institute of Viseu, Portugal)

  • Elena BartkienÄ—

    (Lithuanian University of Health Sciences, Lithuania)

  • Ilija Djekić

    (University of Belgrade, Serbia)

  • Monica Tarcea

    (University of Medicine, Pharmacy, Sciences and Technology of Târgu Mureș, Romania)

  • Marijana Matek Sarić

    (University of Zadar, Croatia)

  • MaÅ¡a ÄŒerneliÄ -Bizjak

    (University of Primorska, Slovenia)

  • Veronika Dolar

    (State University of New York, United States)

  • Ayman EL-Kenawy

    (University of Sadat City, Egypt)

  • Vanessa Ferreira

    (Federal University of Minas Gerais, Brazil)

  • Dace Klava

    (Latvia University of Life Sciences and Technologies, Latvia)

  • MaÅ‚gorzata Korzeniowska

    (Wrocław University of Environmental and Life Sciences, Poland)

  • Elena Vittadini

    (University of Camerino, Italy)

  • Marcela Leal

    (Red IESVIDAS and CONINUT, Argentina)

  • Lucia Frez-Muñoz

    (Wageningen University & Research, Netherlands)

  • Maria Papageorgiou

    (International Hellenic University, Greece)

  • Viktória Szűcs

    (Hungarian Chamber of Agriculture, Hungary)

  • Paula M. R. Correia

    (Polytechnic Institute of Viseu, Portugal)

  • Raquel P. F. Guiné

    (Polytechnic Institute of Viseu, Portugal)

Abstract

Food behaviour is governed by different kinds of motivations, some of individual nature and others related with the external food environment. This study investigated the eating motivations in sixteen countries with respect to commercial and marketing influences on food choices. The questionnaire survey was developed between September 2017 and June 2018, via online tools, targeting a convenience sample of residents in sixteen countries (Argentina, Brazil, Croatia, Egypt, Greece, Hungary, Italy, Latvia, Lithuania, Netherlands, Poland, Portugal, Romania, Serbia, Slovenia and the United States of America). The number of valid responses received was 11,919 participants. The data were treated using SPSS software, and the main statistical techniques used included exploratory factor analysis, evaluation of internal reliability through Cronbach's alpha, cluster analysis (hierarchical and k-means) and logistic regression. The results obtained showed two groups of people: low motivated and notably motivated consumers. The results showed high asymmetries between countries, with highest percentage of highly motivated consumers in Egypt and the lowest percentage of highly motivated in Portugal. It was further observed that consumers more influenced by commercial and marketing aspects (the notably motivated) tend to be women, young, single, less educated, less likely to be professionally active, and those who live mostly in rural or suburban areas. Less exercise and overweight are also factors associated with greater propensity for commercial and marketing motivations. Furthermore, health problems such as shellfish or gluten intolerance, hypertension and high cholesterol confer less propensity to be in the segment of the notably motivated consumers. In conclusion, this work highlighted the role of geographic, sociodemographic and lifestyle factors as food choice determinants.

Suggested Citation

  • Carla Henriques & Ana Matos & Madalena Malva & Elena BartkienÄ— & Ilija Djekić & Monica Tarcea & Marijana Matek Sarić & MaÅ¡a ÄŒerneliÄ -Bizjak & Veronika Dolar & Ayman EL-Kenawy & Vanessa Ferreira , 2022. "Marketing motivations influencing food choice in 16 countries: segmentation and cluster analysis," Insights into Regional Development, VsI Entrepreneurship and Sustainability Center, vol. 4(1), pages 10-25, March.
    • Handle: RePEc:ssi:jouird:v:4:y:2022:i:1:p:10-25
    DOI: 10.9770/ird.2022.4.1(1)
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    More about this item

    Keywords

    marketing segmentation; food consumption; eating motivation; cluster analysis;
    All these keywords.

    JEL classification:

    • G40 - Financial Economics - - Behavioral Finance - - - General

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