The perils of hotel technology: The robot usage resistance model

Fu, Shixuan; Zheng, Xiaohui; Wong, IpKin Anthony

doi:10.1016/j.ijhm.2022.103174

Cited by 77 publications

(52 citation statements)

References 53 publications

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“…Further, Ali et al (2022) studied the motivational factors and barriers affecting Generation Z employees’ acceptance to work with service robots in hotels, highlighting the unique characteristics of Generation Z in affecting their technology usage as the future workforce. Some scholars have also started to look at the negative aspects of service robot adoption in hotel industry (Fu et al , 2022) and suggest ways to mitigate such negative impact. For instance, Yu et al (2022) suggested that employee skills such as tech-savviness and social skills could effectively lower their turnover intention.…”

Section: Introductionmentioning

confidence: 99%

Hotel robots: an exploratory study of Generation Z customers in China

Chen

Xue

Tuomi

et al. 2022

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Purpose Given little light has been shed on the preference of Generation Z tourists or tourists from different cultural backgrounds toward service robot preference in hospitality contexts, this study aims to explore robot service preferences in the accommodation sector in the Chinese market, with a specific focus of Generation Z customers. Design/methodology/approach This study followed an exploratory sequential research design including two qualitative methods (i.e. projective techniques and semistructured interviews) to reach its objectives. Findings This study suggests that service robots are more preferred for routine tasks and gender differences exist in the preference of service robot’s anthropomorphism level. The preferences are driven by four factors based on different levels of hedonic and utilitarian values: experienced-hedonic value, utilitarian-hedonic value, task-relevant value and utilitarian value. Research limitations/implications First, because of the exploratory nature of this study, the data interpretation is unavoidably subjective; therefore, the results can be confirmed by using a more rigorous research method. Second, this study only focuses on the preference of Generation Z customers in China in the hotel sector; as the cultural differences exist in different countries, this study’s findings cannot be readily generalized across populations and service contexts. Finally, this study fails to dig into the effect of gender differences on varying levels of anthropomorphic attributes. Practical implications As hotels adopt service robots more widely, managers need to identify customers’ service preferences and prioritize tasks between robots and human resources for more efficient service. Particularly important is understanding the benefits and challenges of specific robot implementations rather than looking for a one-size-fits-all mode of operation. Originality/value To the best of the authors’ knowledge, this is the first study to understand robot service preference with regard to specific tourist groups in illustrating their preference for service delivery. Drawing on self-determination theory, this study potentially provides a theoretical basis for hotel service process optimization.

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Section: Introductionmentioning

confidence: 99%

Hotel robots: an exploratory study of Generation Z customers in China

Chen

Xue

Tuomi

et al. 2022

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“…The advent of smart restaurant and dining renders as a new phenomenon of interest in foodservice (Peek, 2021). Given the objective stated above, the present research builds the necessary foundation based on three hospitality research areas: service quality (Lin et al , 2020; Wong and Yang, 2020), AI and robots (Doborjeh et al , 2022; Jiang and Wen, 2020; Pillai and Sivathanu, 2020; Fu et al , 2022) and information technology applications in restaurants and other related contexts (Stylos et al , 2021; Law et al , 2022; Mariani and Baggio, 2022). In particular, we seek to synthesize these streams of work to better assess how technologies, especially AI and robots, are infused within the smart restaurants through the lens of service quality.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…In recent years, AI has been applied to various fields, including management for event lodging, travel agencies, supply chains, restaurants and sales and marketing (Davari et al , 2022; Doborjeh et al , 2022; Fu et al , 2022). AI applications in front-line services may focus on assisting or complementing employees doing more routine tasks.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Smart dining, smart restaurant, and smart service quality (SSQ)

Wong

Huang

Lin

et al. 2022

IJCHM

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Purpose Have you been to a smart restaurant, and how were its services? A common limitation of hospitality studies stems from the lack of research on how service quality is shaped within smart technology. This study aims to fill this literature void not merely to reiterate the importance of technology but also to recast service quality through the lens of information technology. It synthesizes the 5-S model of smart service quality (AKA SSQ) as a new conceptualization of service quality application in smart hospitality contexts such as smart restaurants. Design/methodology/approach This study undertook a qualitative research design based on theoretical synthesis from service quality, information technology and attention restoration. Drawing from online review comments and semistructured interviews from smart restaurants, the authors improvised the SSQ model to identify the essence of smart service in smart dining establishments. Findings “5-S” reflects an extension of the literature to denote a new SSQ abstraction pertinent to s-servicescape, s-assurance, s-responsiveness, s-reliability and s-empathy. A nomological network was posited to better understand the importance of smart design and consequence of SSQ. Research limitations/implications The emergence of smart dining gives rise to smart restaurants, which puts technology at center stage. As consumers are becoming increasingly comfortable with self-service technology, auto-payment and ordering systems and robotic services, technology in foodservice will continue to play an essential role to better serve diners. Geared with advanced innovations and intelligent devices, smart restaurants are now more than mere eateries. It is a trend and a lifestyle. Originality/value This novel SSQ concept adds new nuances to the literature by acknowledging the technological essence in today’s hospitality industry. By integrating smart technology into the service quality paradigm, the authors are able to observe several interesting behaviors exhibited during smart dining, including tech-induced restoration, which opens a new avenue to understand how attention restoration could be attained through immersion in a technologically advanced setting. By synthesizing theoretical essence from service quality, attention restoration and information technology, the authors are able to create a new dialog that should warrant a forum of discussion in future studies.

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“…Hospitality 5.0 refers “to the extension of the modularity, real-time capabilities, virtualization, decentralization and interoperability design principles of Industry 5.0 to the hospitality industry” ( Pillai et al, 2021 ) is swiftly becoming a mainstream concept in the industry. Specifically, contactless automation technology, mobile technology, robotics, artificially intelligent machines, and virtual and augmented reality are gradually but steadily diffusing into the critical guest touchpoints in the guest consumption journey ( Luo et al, 2021 , Fu et al, 2022 ). This gradual proliferation of service robots is projected to continue.…”

Section: Introductionmentioning

confidence: 99%