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Frontline robots in tourism and hospitality: service enhancement or cost reduction?

Author

Listed:
  • Daniel Belanche

    (University of Zaragoza)

  • Luis V. Casaló

    (University of Zaragoza)

  • Carlos Flavián

    (University of Zaragoza)

Abstract

Robots are being implemented in many frontline services, from waiter robots in restaurants to robotic concierges in hotels. A growing number of firms in hospitality and tourism industries introduce service robots to reduce their operational costs and to provide customers with enhanced services (e.g. greater convenience). In turn, customers may consider that such a disruptive innovation is altering the established conditions of the service-provider relationship. Based on attribution theory, this research explores how customers’ attributions about the firm motivations to implement service robots (i.e. cost reduction and service enhancement) are affecting customers’ intentions to use and recommend this innovation. Following previous research on robot’s acceptance, our research framework analyzes how these attributions may be shaped by customers’ perceptions of robot’s human-likeness and their affinity with the robot. Structural equation modelling is used to analyze data collected from 517 customers evaluating service robots in the hospitality industry; results show that attributions mediate the relationships between affinity toward the robot and customer behavioral intentions to use and recommend service robots. Specifically, customer’s affinity toward the service robot positively affects service improvement attribution, which in turn has a positive influence on customer behavioral intentions. In contrast, affinity negatively affects cost reduction attribution, which in turn has a negative effect on behavioral intentions. Finally, human-likeness has a positive influence on affinity. This research provides practitioners with empirical evidence and guidance about the introduction of service robots and its relational implications in hospitality and tourism industries. Theoretical advances and future research avenues are also discussed.

Suggested Citation

  • Daniel Belanche & Luis V. Casaló & Carlos Flavián, 2021. "Frontline robots in tourism and hospitality: service enhancement or cost reduction?," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 477-492, September.
  • Handle: RePEc:spr:elmark:v:31:y:2021:i:3:d:10.1007_s12525-020-00432-5
    DOI: 10.1007/s12525-020-00432-5
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    2. Song, Jinzhu & Gao, Yanhuan & Huang, Youlin & Chen, Lihan, 2023. "Being friendly and competent: Service robots' proactive behavior facilitates customer value co-creation," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    3. Mathieu Lajante & David Remisch & Nikita Dorofeev, 2023. "Can robots recover a service using interactional justice as employees do? A literature review-based assessment," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 315-357, March.
    4. Jialei Ye & Luyi Yang & Ruwei Yun, 2022. "An Impact Evaluation of the Application of Sharing Products in Tourism Services," Sustainability, MDPI, vol. 14(13), pages 1-23, June.
    5. Kuen-Cheng Lee & I-Hsiung Chang & Tsung-Jen Wu & Ru-Si Chen, 2022. "The Moderating Role of Perceived Interactivity in the Relationship Between Online Customer Experience and Behavioral Intentions to Use Parenting Apps for Taiwanese Preschool Parents," SAGE Open, , vol. 12(1), pages 21582440221, March.
    6. Xing, Xinyu & Song, Mengmeng & Duan, Yucong & Mou, Jian, 2022. "Effects of different service failure types and recovery strategies on the consumer response mechanism of chatbots," Technology in Society, Elsevier, vol. 70(C).
    7. Ji-Hyoung Chin & Chanwook Do & Minjung Kim, 2022. "How to Increase Sport Facility Users’ Intention to Use AI Fitness Services: Based on the Technology Adoption Model," IJERPH, MDPI, vol. 19(21), pages 1-12, November.
    8. Nora Nahr & Marikka Heikkilä, 2022. "Uncovering the identity of Electronic Markets research through text mining techniques," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1257-1277, September.
    9. Lee, Kuo-Wei & Li, Chia-Ying, 2023. "It is not merely a chat: Transforming chatbot affordances into dual identification and loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    10. Tianyang Huang, 2022. "What Affects the Acceptance and Use of Hotel Service Robots by Elderly Customers?," Sustainability, MDPI, vol. 14(23), pages 1-17, December.
    11. Li, Chia-Ying & Zhang, Jin-Ting, 2023. "Chatbots or me? Consumers’ switching between human agents and conversational agents," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    12. Mariani, Marcello M. & Machado, Isa & Nambisan, Satish, 2023. "Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda," Journal of Business Research, Elsevier, vol. 155(PB).
    13. Liu, Xiaohui & He, Xiaoyu & Wang, Mengmeng & Shen, Huizhang, 2022. "What influences patients' continuance intention to use AI-powered service robots at hospitals? The role of individual characteristics," Technology in Society, Elsevier, vol. 70(C).

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    More about this item

    Keywords

    Service robots; Human-likeness; Affinity; Customer attributions; Customer behavioral intentions; Hospitality industry;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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