Predicting A New Hotel Rating System by Analysing UGC Content from Tripadvisor: Machine Learning Application to Analyse Service Robots Influence

Calero-Sanz, Jorge; Orea-Giner, Alicia; Villacé-Molinero, Teresa; Muñoz-Mazón, Ana; Moraleda, Laura Fuentes

doi:10.1016/j.procs.2022.01.307

Cited by 14 publications

(8 citation statements)

References 30 publications

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“…Hotels have been pioneers in the use of robots in customer service (Tussyadiah, 2020) and online reviews represent a powerful means to track the customer experience with service robots in hotel operations . This reasoning is supported by the growing body of literature on the topic (e.g., Calero-Sanz et al, 2022;Tung & Au, 2018;Yu, 2020).…”

Section: Methodsmentioning

confidence: 88%

The impact of service robots on customer satisfaction online ratings: The moderating effects of rapport and contextual review factors

Borghi,

Mariani,

Vega

et al. 2023

Psychology and Marketing

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Recent research has established a positive relationship between the use of service robots powered by artificial intelligence in hospitality firms and customer satisfaction online ratings, a particularly important form of electronic word of mouth. However, it is not clear if and how this relationship is augmented or diminished by moderating factors. In this study, we examined four potential moderators by using machine learning and natural language processing techniques to analyze 20,166 online reviews of hotels that had implemented service robots. We had four key findings. First, a positive service robot‐satisfaction rating relationship was further enhanced by improved customer‐service robot rapport during the service encounter. Second, higher customer effort focused on service robots in a review reduced the service robot‐satisfaction rating relationship. Third, posting reviews using a mobile device (vs. other devices) showed higher satisfaction ratings. Finally, customers' prior experience in writing online reviews was unrelated to the service robot‐satisfaction rating relationship. Taken together, these results suggest that service robots should be designed to be interactive and encourage customers to build rapport, for example, by service robots engaging in conversational flows. Moreover, customers should be nudged to use their mobile devices to post timely reviews on their positive human–robot interactions.

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Section: Methodsmentioning

confidence: 88%

The impact of service robots on customer satisfaction online ratings: The moderating effects of rapport and contextual review factors

Borghi,

Mariani,

Vega

et al. 2023

Psychology and Marketing

View full text Add to dashboard Cite

show abstract

“…The hospitality sub-sector received considerable attention from the literature, perhaps because guests are increasingly expecting and demanding technology-mediated services [ 74 ]. Two studies [ 38 , 41 ] address the service automation process to measure guests’ expectations and satisfaction regarding service delivery robots. Following [ 37 ], explore the role of digital skills in human resources.…”

Section: Findings and Discussionmentioning

confidence: 99%

The implications of industry 4.0 for the tourism sector: A systematic literature review

Rodrigues,

Breda,

Rodrigues

2024

Heliyon

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“…Because of the importance of analysing visitors' experiences through big data, machine learning is applied for visitation pattern prediction and experience evaluation (Calero-Sanz et al, 2022). The application of AI to analyse and visualise these data brings an opportunity for museums and cultural institutions to understand their audiences better and create personalised and engaging experiences (French and Villaespesa, 2019).…”

Section: Cultural Tourism and The Role Of Experience-based Technologi...mentioning

confidence: 99%

“…The services sector has gradually adopted Industry 4.0 tools, as well as technologies such as robots, AI and service automation (Ruel and Njoku, 2020;Samala et al, 2020). However, services sector requires taking a step further towards Industry 5.0 tools (Calero-Sanz et al, 2022). Cultural institutions (e.g.…”

Section: Introductionmentioning

confidence: 99%

Cultural tourist and user experience with artificial intelligence: a holistic perspective from the Industry 5.0 approach

Orea-Giner

Muñoz-Mazón

Villacé-Molinero

et al. 2022

JTF

Self Cite

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PurposeThe purpose of this paper is to analyse the future of the implementation of artificial intelligence (AI) technologies in services experience provided by cultural institutions (e.g. museums, exhibition halls and cultural centres) from experts’, cultural tourists’ and users’ point of view under the Industry 5.0 approach.Design/methodology/approachThe research was conducted using a qualitative approach, which was based on the analysis of the contents obtained from two roundtable discussions with experts and cultural tourists and users. A thematic analysis using NVivo was done to the data obtained.FindingsFrom a futuristic Industry 5.0 approach, AI is considered to be more than a tool – it as an integral part of the entire experience. AI aids in connecting cultural institutions with users and is beneficial since it allows the institutions to get to know the users better and provide a more integrated and immersive experience. Furthermore, AI is critical in establishing a community and nurturing it daily.Originality/valueThe most important contribution of this research is the theoretical model focused on the user experience and AI application in services experiences of museums and cultural institutions from an Industry 5.0 approach. This model includes the visitors’ and managers’ points of view through the following dimensions: the pre-experience, experience and post-experience. This model is focused on human–AI coworking (HAIC) in museums and cultural institutions.

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Predicting A New Hotel Rating System by Analysing UGC Content from Tripadvisor: Machine Learning Application to Analyse Service Robots Influence

Cited by 14 publications

References 30 publications

The impact of service robots on customer satisfaction online ratings: The moderating effects of rapport and contextual review factors

The impact of service robots on customer satisfaction online ratings: The moderating effects of rapport and contextual review factors

The implications of industry 4.0 for the tourism sector: A systematic literature review

Cultural tourist and user experience with artificial intelligence: a holistic perspective from the Industry 5.0 approach

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