Journal of Hospitality and Tourism Technology

Zhang, Tingting; Lu, Lu

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-11-2024-438

Wang, Jiaxin (Sylvia); Fu, Xiaoxiao

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-01-2024-0006

This study aims to investigate guests’ experience and perceptions in smart hotels, with a primary focus on the human−robot experience.Design/methodology/approachUtilizing a thematic analysis using the inductive-deductive approach, 546 reviews from Chinese smart hospitality guests, sourced from Ctrip, were examined.FindingsThis study identified five highest-level categories reflecting guests’ perceptions of smart hotels service with themes and subthemes of utilitarian gratification (smart servicescape and smart service quality), sensual gratification (novelty and coolness), social gratification (social presence and social interaction), experiential gratification (functional and emotional experiential value) and satisfaction.Originality/valueThis research enriches the current understanding of guests’ experience within smart hotels, focusing on the human−robot interaction. The findings offer insightful implications for the enhancement of smart hotels, specifically in terms of smart facility offerings, service delivery and overall customer experience.

Jiao, Haoyue; Wong, IpKin Anthony; Lin, Zhiwei (CJ)

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-11-2023-0384

The study aims to propose a triadic interaction model to assess the effect of customer–customer (C2C), employee–customer and robot–customer interactions on customer voluntary performance in the context of smart dining.Design/methodology/approachAn explanatory sequential mixed methods design was used. First, a quantitative study surveyed Foodom patrons to assess the impact of triadic interactions on customer voluntary performance. The mediating role of trust and social support and the moderating effect of the need to belong were also explored. A post hoc study (Study 2) analyzed online comments to validate and complement the survey findings.FindingsWhile all interactions promote social support, the C2C interactions significantly correlate with customer trust. Moreover, customer voluntary performance is influenced by both customer trust and social support, while the need to belong remains as a moderator. Findings from Study 2 consolidate and enrich the relationships identified in Study 1.Research limitations/implicationsThis research reveals that patrons in smart dining still value interactions with employees and other diners. It enriches the stream of work on interaction quality by illuminating how different types of interactions could co-create value for customers, subsequently fostering voluntary behavior in smart dining contexts.Originality/valueThis research explores how patrons perceive interactions with robots in smart hospitality, highlighting their impact on trust and social support. It also sheds light on how interactions among robots, employees and customers influence customer voluntary performance, emphasizing the role of the need to belong in moderating relationships in this setting.

Li, Yuhao; Wang, Shurui; Li, Zehua

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-01-2024-0053

This study aims to apply the predictive processing theory to examine the influence of artificial intelligence (AI)-driven robotic performers on audience emotions and the audience’s resulting electronic word-of-mouth (eWOM) behaviors during tourism service encounters.Design/methodology/approachUsing a quantitative research methodology, survey responses from 339 regular customers of performing arts in tourism destinations were analyzed. The respondents were recruited through Prolific, a professional data collection platform. SPSS 23.0 was used for the preliminary analysis, from which a research model to achieve the aim was proposed. SmartPLS 3 was used for partial least squares structural equation modeling to test the model.FindingsInteractive and novel robotic performances significantly encouraged the consumers to share their experiences online, thereby enhancing eWOM. However, melodic resonance had no significant impact on eWOM intentions. The consumers’ emotional responses fully mediated the relationship of the novelty and interactivity of the performances to the consumers’ eWOM intentions but did not mediate the relationship of the musical elements to their eWOM intentions.Originality/valueThis study enriches the understanding of how AI-driven performances impact consumers’ emotional engagement and sharing behaviors. It extends the application of the predictive processing theory to the domain of consumer behavior, offering valuable insights for enhancing audience engagement in performances through technological innovation.

Lu, Yue (Darcy); Liang, Yifeng; Wang, Yao-Chin

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-12-2023-0416

This study aims to conceptualize the characteristics of artificial intelligence (AI) dogs while exploring their applications in tourism and hospitality settings.Design/methodology/approachThe total of 30 in-depth interviews were conducted, and data were analyzed through thematic analysis.FindingsThis study proposed differences between AI dogs and real dogs and human-like robots, core characteristics of AI dogs’ functions, a matrix of appearance and expectation regarding intelligence for AI dogs and human-like robots, the relationship between ethical barriers and task complexity, adoptions of AI dogs in different user segments and practical applications in hospitality and tourism settings, such as restaurants, city tour guides, extended-stay resorts and event organizations.Research limitations/implicationsThis research advances the field of tourism and hospitality studies by introducing the new concept of AI dogs and their practical applications. This present study adds new insights into the opportunities and contexts of human–robot interaction in the field of tourism and hospitality.Originality/valueTo the best of the authors’ knowledge, this research is one of the first studies of AI dogs in tourism and hospitality.

Saputra, Fachri Eka; Buhalis, Dimitrios; Augustyn, Marcjanna M.; Marangos, Stefanos

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-03-2024-0171

Anthropomorphism plays a crucial role in the deployment of human-like robots in hospitality and tourism. This study aims to propose an anthropomorphism-based typology of artificial intelligence (AI) robots, based on robot attributes, usage, function and application across different operational levels.Design/methodology/approachFollowing the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist, the research was conducted in two stages. A search strategy was implemented to explore anthropomorphism-based AI robots and to develop a robot typology.FindingsThis study provides a comprehensive typology of anthropomorphism-based AI robots used in tourism and hospitality and classifies them into four types, namely, chatbots, mechanoids, humanoids and android robots. Each type features distinct functions and applications.Practical implicationsThe findings can assist companies in using anthropomorphic robots to improve service and strengthen competitiveness. This study offers valuable insights to managers for deploying AI robots across diverse service sectors.Originality/valueThis research provides a novel typology of hospitality and tourism AI robots and extends the understanding of anthropomorphism in human–robot interaction. This typology encompasses both virtual and physical robots, providing clarity on their attributes, usage, functions and applications across diverse areas of hospitality operations.

Parvez, M. Omar; Eluwole, Kayode Kolawole; Lasisi, Taiwo Temitope

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-10-2023-0307

This study aims to investigate tourists’ intentions to use hotel service robots with a focus on safety and hygiene. It examines the impact of perceived safety, health awareness and service assurance on consumer engagement and robot usage.Design/methodology/approachSurvey data from 275 participants with experience in robotic service were analyzed using structural equation modeling (SEM). The study used purposive sampling and collected data via the Prolific platform, using SEM and SmartPLS Ver. 3.0 for analysis.FindingsResults indicate customers prioritize safety and hygiene, valuing effective service responses and cleanliness. Perceived robotic safety and service assurance positively influence personal engagement, with a preference for service robots among female guests.Research limitations/implicationsWhile emphasizing the importance of safety and service assurance in hotel robotics, the study acknowledges limitations in personalization and conclusive use of service robots.Originality/valueThis research contributes to understanding the role of perceived safety in service robot usage, highlighting the significance of user trust and comfort in human–robot interactions. It also explores the novel connection between service assurance and service robots, offering insights into robotic performance reliability in user-centric contexts.

Chang, Sue-Ting

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-10-2023-0316

Service robots offering low-contact services are trending in the hospitality industry. Nevertheless, there is limited empirical research on consumer perspectives. Using the stimulus-organism-response (SOR) model, this study aims to investigate consumer acceptance of service robots and explores the relationships among stimuli (coolness and affinity), organisms (utilitarian and hedonic value) and responses (behavioral intention).Design/methodology/approachThis study uses a purposive sampling method and conducts a questionnaire survey in restaurants with service robots in Taiwan. A total of 554 valid responses are analyzed, and confirmatory factor analysis and structural equation modeling are performed.FindingsThe findings reveal that coolness and affinity positively influence utilitarian and hedonic values, whereas utilitarian and hedonic values positively affect behavioral intention. Additionally, these values mediate how coolness and affinity impact behavioral intentions, showing that coolness more significantly influences hedonic value, while affinity has a greater effect on utilitarian value.Originality/valueAs a theoretical basis, the SOR model examines the relationships among stimulus, organism and response. This study comprehensively investigates the factors influencing consumer perception toward service robots, testing the applicability of this theory in the food and beverage industry and expanding its practical value. Additionally, the author introduces the “fit” concept, indicating that, for maximum effect, coolness pairs best with hedonic value and affinity with utilitarian value.

Song, Xiaoxiao; Gu, Huimin; Ling, Xiaodie; Ye, Weijiao; Li, Xiaofei; Zhu, Zhisheng

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-12-2023-0428

Drawing on the Service Robot Acceptance Model (sRAM) proposed by Wirtz et al. (2018), this study aims to examine how functional and social-emotional antecedents affect relational elements and the critical functions that trust and rapport play in robot acceptance in hotel services. Additionally, this study incorporates customer characteristics into the modified sRAM.Design/methodology/approachConsistent partial least squares (PLSc) was used to test the proposed model utilizing data collected from 456 Chinese customers.FindingsThe results indicated that effort expectancy and performance expectancy positively affect hotel guests’ trust toward and rapport with service robots. However, the effect of social influence on trust and rapport is insignificant. Additionally, perceived humanness and perceived social interactivity positively influence rapport, and perceived social presence positively affects both trust and rapport. Furthermore, trust and rapport positively influence hotel guests’ acceptance of service robots. The results also revealed the moderating role of age.Originality/valueThis study contributes to service robot literature by providing insights into how functional and social-emotional factors affect relational factors and the key role of relational factors in robot acceptance based on the sRAM. This study also advances this body of knowledge by highlighting the moderating effect of age.

Wang, Xiaoyu; Chen, Mengxi; Wang, Zhiyan; Law, Chun Hung Roberts; Zhang, Mu

2024 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-11-2023-0367

This study aims to investigate the affordances of service robots (SRs) in hotels and their effects on frontline employees (FLEs).Design/methodology/approachPurposive and referral samplings methods were used to conduct 28 semistructured interviews with hotel FLEs, and the transcribed manuscript was analyzed based on grounded theory.FindingsThe study identifies six dimensions of SR affordances: physical, sensory, task, safety, social and emotional affordances. The main effects of SR affordances on FLEs involve reducing work stress and mental fatigue and increasing positive emotions in the psychological aspects of FLEs. In terms of behavioral aspects, shifts in task priorities and enhancements in SR usage behaviors were observed. Accordingly, a mechanistic framework was revealed through which SR affordances influence FLEs via direct and indirect interactions between FLEs and SRs.Originality/valueThis paper expands robotics research from a supply-side perspective and is one of the few studies to investigate SR affordances in the field of hospitality research. Findings of this study provide practical guidelines for designing and implementing SRs to support hotel FLEs in their daily work.