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Model of the Consumer Switching Behavior Related to Healthy Food Products

Author

Listed:
  • Anas Hidayat

    (Management Department, Faculty of Business and Economics, Universitas Islam Indonesia, Yogyakarta 55283, Indonesia)

  • Tony Wijaya

    (Management Department, Faculty of Economy, Universitas Negeri, Yogyakarta 55284, Indonesia)

  • Asmai Ishak

    (Management Department, Faculty of Business and Economics, Universitas Islam Indonesia, Yogyakarta 55283, Indonesia)

  • Sri Rejeki Ekasasi

    (Management Department, Sekolah Tinggi Ilmu Manajemen, Yayasan Keluarga Pahlawan Negara, Yogyakarta 55284, Indonesia)

  • Guruh Ghifar Zalzalah

    (Management Department, Faculty of Business, Universitas Persatuan Guru Republik Indonesia, Yogyakarta 55581, Indonesia)

Abstract

This study aimed to examine the effect of customers’ attitudes, subjective norms, and perceived behavior control on their intention to switch to healthy food products. This research also tested brand awareness as a moderator of customers’ behavioral choices to switch to healthy food products by switching behavior. The study was conducted by distributing a questionnaire. It involved 318 participants and employed partial least square regression as the data analysis method. This study shows the significant influence of customers’ attitudes on their switching intentions toward healthy food products, and perceived behavior control significantly influences customers’ switching intentions toward healthy food products. Customers’ perceived behavior control, as well as their intentions to switch toward healthy food products, significantly influences their switching behavior. Brand awareness has a moderate influence on customers’ intentions to switching behavior on healthy food products. This study contributes to developing the model of customer behavior in switching from fast food products to healthy food products. This study reveals that subjective norms do not significantly influence the switching behavior of customers.

Suggested Citation

  • Anas Hidayat & Tony Wijaya & Asmai Ishak & Sri Rejeki Ekasasi & Guruh Ghifar Zalzalah, 2021. "Model of the Consumer Switching Behavior Related to Healthy Food Products," Sustainability, MDPI, vol. 13(6), pages 1-12, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3555-:d:522433
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    References listed on IDEAS

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    1. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    2. Chakravarty, Sugato & Feinberg, Richard & Rhee, Eun-Young, 2004. "Relationships and individuals' bank switching behavior," Journal of Economic Psychology, Elsevier, vol. 25(4), pages 507-527, August.
    3. Yi-Fei Chuang & Yang-Fei Tai, 2016. "Research on customer switching behavior in the service industry," Management Research Review, Emerald Group Publishing Limited, vol. 39(8), pages 925-939, August.
    4. Rana, Jyoti & Paul, Justin, 2017. "Consumer behavior and purchase intention for organic food: A review and research agenda," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 157-165.
    5. Sanjib Bhuyan, 2011. "Do consumers' attitudes and preferences determine their FAFH behavior? An application of the theory of planned behavior," Agribusiness, John Wiley & Sons, Ltd., vol. 27(2), pages 205-220, Spring.
    6. Shirley Taylor & Peter A. Todd, 1995. "Understanding Information Technology Usage: A Test of Competing Models," Information Systems Research, INFORMS, vol. 6(2), pages 144-176, June.
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