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Understanding the Robotic Restaurant Experience: A Multiple Case Study

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  • Seyitoğlu, Faruk
  • Ivanov, Stanislav Hristov

    (Varna University of Management)

Abstract

The purpose of this study is to investigate the robotic restaurant experience of travellers around the world and understand the components of robotic restaurant experience. Following this aim, travellers who had experienced a robotic restaurant were purposefully selected as a sample group for the study. Since the robotic restaurants are limited around the world, multiple case study method has been chosen to gather richer data. A user-generated content technique which is a form of qualitative case study method has been benefited. The data of this study were gathered between 18-29 November 2019 from travellers’ reviews (n=587) describing experiences they had between February 2013-November 2019. The results reveal a model of components of robotic restaurant experience that include seven main themes: attraction for kids, robotic system, service quality, memorable experience, ambience related attributes, food related attributes (economic value and gastronomic aspects), and deficiencies (in robotic system, in service quality, in ambience related attributes and in food related attributes). This paper is first to investigate the robotic restaurant experience of travellers around the world. Moreover, it contributes to the research on restaurant experience and offers a model of components of the robotic restaurant experience.

Suggested Citation

  • Seyitoğlu, Faruk & Ivanov, Stanislav Hristov, 2020. "Understanding the Robotic Restaurant Experience: A Multiple Case Study," SocArXiv e6rfa, Center for Open Science.
    • Handle: RePEc:osf:socarx:e6rfa
    DOI: 10.31219/osf.io/e6rfa
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    References listed on IDEAS

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    1. Gentile, Chiara & Spiller, Nicola & Noci, Giuliano, 2007. "How to Sustain the Customer Experience:: An Overview of Experience Components that Co-create Value With the Customer," European Management Journal, Elsevier, vol. 25(5), pages 395-410, October.
    2. Labrecque, JoAnne & Ricard, Line, 2001. "Children's influence on family decision-making: a restaurant study," Journal of Business Research, Elsevier, vol. 54(2), pages 173-176, November.
    3. DongHee Kim & SooCheong Shawn Jang, 2019. "The psychological and motivational aspects of restaurant experience sharing behavior on social networking sites," Service Business, Springer;Pan-Pacific Business Association, vol. 13(1), pages 25-49, March.
    4. Tussyadiah, Iis, 2020. "A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism," Annals of Tourism Research, Elsevier, vol. 81(C).
    5. Jeacle, Ingrid & Carter, Chris, 2011. "In TripAdvisor we trust: Rankings, calculative regimes and abstract systems," Accounting, Organizations and Society, Elsevier, vol. 36(4), pages 293-309.
    6. Yrjölä, Mika & Rintamäki, Timo & Saarijärvi, Hannu & Joensuu, Johanna & Kulkarni, Gauri, 2019. "A customer value perspective to service experiences in restaurants," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 91-101.
    7. Jang, SooCheong (Shawn) & Namkung, Young, 2009. "Perceived quality, emotions, and behavioral intentions: Application of an extended Mehrabian-Russell model to restaurants," Journal of Business Research, Elsevier, vol. 62(4), pages 451-460, April.
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    Cited by:

    1. Stanislav Ivanov & Craig Webster & Faruk Seyitoğlu, 2023. "Humans and/or robots? Tourists’ preferences towards the humans–robots mix in the service delivery system," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 195-231, March.
    2. Seyitoğlu, Faruk & Ivanov, Stanislav & Atsız, Ozan & Çifçi, İbrahim, 2021. "Robots as restaurant employees - A double-barrelled detective story," Technology in Society, Elsevier, vol. 67(C).

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