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Culture, religiosity, and economic configural models explaining tipping-behavior prevalence across nations

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  • Ferguson, Graham
  • Megehee, Carol M.
  • Woodside, Arch G.

Abstract

Unique from prior research that deconstructs culture into separate attributes and reports on the symmetric “net effect” of each, the current study identifies holistic configurations of culture that account for the prevalence of tipping behaviors across tourism industries. Consistent with the theory that distinct holistic cultures predict tipping and non-tipping behaviors, the findings identify configurations of cultural attributes (e.g. “masculine benevolence”, “feminine benevolence”, and “achieving individualist”) in combination with national religiosity and economic well-being that account for the majority of nations with high prevalence of tipping—as well as configurations (e.g. “collective individualist”) that account for nations with low prevalence of tipping. These configurations provide tourism operators, regulators, service providers and tourists with insight about the drivers of tipping expectations at the national level and therefore enable better management of the tourism experience. The paper also demonstrates the usefulness of a complexity theory approach to explore complex phenomena by revealing holistic configurations of antecedent conditions; identifying multiple configurations that explain the same outcome; demonstrating that configurations for high and low prevalence are asymmetric, and; demonstrating that antecedent conditions operate in opposite ways depending on other ingredients in a configuration.

Suggested Citation

  • Ferguson, Graham & Megehee, Carol M. & Woodside, Arch G., 2017. "Culture, religiosity, and economic configural models explaining tipping-behavior prevalence across nations," Tourism Management, Elsevier, vol. 62(C), pages 218-233.
  • Handle: RePEc:eee:touman:v:62:y:2017:i:c:p:218-233
    DOI: 10.1016/j.tourman.2017.05.001
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    Cited by:

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    3. Elif Aydin, Asli & Acun, Yüksel, 2019. "An investigation of tipping behavior as a major component in service economy: The case of taxi tipping," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 78(C), pages 114-120.
    4. Thrane, Christer & Haugom, Erik, 2020. "Peer effects on restaurant tipping in Norway: An experimental approach," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 244-252.
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    6. Mazanec, Josef A., 2020. "Hidden theorizing in big data analytics: With a reference to tourism design research," Annals of Tourism Research, Elsevier, vol. 83(C).
    7. Dyussembayeva, Shynar & Viglia, Giampaolo & Nieto-Garcia, Marta & Mattila, Anna S., 2022. "Would you like to add a gratuity? When explicit requests hamper tipping," Journal of Business Research, Elsevier, vol. 139(C), pages 908-917.
    8. Ferguson, Graham & Megehee, Carol M. & Woodside, Arch G., 2018. "Applying asymmetric, case-based, forecasting modeling in service research: Cultures’ consequences on customers’ service gratuities," Australasian marketing journal, Elsevier, vol. 26(4), pages 369-381.
    9. Krishen, Anjala S. & Berezan, Orie & Agarwal, Shaurya & Kachroo, Pushkin & Raschke, Robyn, 2021. "The digital self and virtual satisfaction: A cross-cultural perspective," Journal of Business Research, Elsevier, vol. 124(C), pages 254-263.
    10. Glückstad, Fumiko Kano & Schmidt, Mikkel N. & Mørup, Morten, 2020. "Testing a model of destination image formation: Application of Bayesian relational modelling and fsQCA," Journal of Business Research, Elsevier, vol. 120(C), pages 351-363.

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