Internet of Things and Artificial Intelligence in the Hotel Industry: Which Opportunities and Threats for Sensory Marketing?

Pelet, Jean‐Éric; Lick, Erhard; Taieb, Basma

doi:10.1007/978-3-030-18911-2_20

Cited by 14 publications

(12 citation statements)

References 20 publications

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“…It is of profound importance to understand determining attributes from customers’ perspectives, and this study successfully validated five proposed underlying dimensions which form individuals’ perceived performance of a smart hotel. Furthermore, our results showed customers’ attitudes were built by perceived performance which is coherent with the extant research [ 18 , 38 , 41 ]. Therefore, professionals in the smart hotel should proactively seek various ways to enhance these identified underlying dimensions of perceived performance.…”

Section: Discussionsupporting

confidence: 91%

“…Their analysis results showed that the performance of halal-friendly destination is highly and positively associated with tourists’ attitudes. Pelet, Lick, and Taieb [ 41 ] explored the opportunities of AI and IoT as a digital tool in relation to guests’ sensory experiences in 4- and 5-star hotels and confirmed its positive impact on individual responses such as attitude and satisfaction. Zhang and Qi [ 18 ] conducted the quantitative research for robotic hotels based on five underlying dimensions of customer expectation (i.e., tangibles, reliability, responsiveness, assurance, and empathy) and the analysis results found their significant association with attitude.…”

Section: Review Of the Literaturementioning

confidence: 99%

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Smart Hotels and Sustainable Consumer Behavior: Testing the Effect of Perceived Performance, Attitude, and Technology Readiness on Word-of-Mouth

Kim

Lee

Han

2020

IJERPH

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Many recent studies with the topic of innovative technologies have been executed in the viewpoint of adoption/readiness of one specific cutting-edge technology in the hospitality industry. Unlike with the existing studies, the present research comprehensively dealt with consumers’ perceived performance of a smart hotel and explored its influence on the formation of attitude and word-of-mouth intention. Furthermore, this study encompassed drivers of technology readiness (optimism and innovativeness) as critical moderators. Our analysis results confirmed that the perceived performance of a smart hotel is essential in generating individuals’ favorable attitudes and positive word-of-mouth intentions. The moderating roles of optimism and innovativeness were also found in the link between perceived performance and attitude. Theoretical value and managerial contributions were discussed through unpinning the structural relationships among study variables in the smart hotel context.

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Section: Discussionsupporting

confidence: 91%

Section: Review Of the Literaturementioning

confidence: 99%

Smart Hotels and Sustainable Consumer Behavior: Testing the Effect of Perceived Performance, Attitude, and Technology Readiness on Word-of-Mouth

Kim

Lee

Han

2020

IJERPH

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“…Machine learning does mining and clustering opinions, and helps hotel managers in quickly responding to the reviews turning unsatisfied customers into loyal customers. The mining of opinion can be feature-based like, aspect-based sentimental analysis, where aspect is extracted and aspect sentiment is classified (Pelet, et al, 2019).…”

Section: Machine Learning Applications In the Hotel Industry And Resementioning

confidence: 99%

“…(Moon, Jung, Lee, & Choi, 2015) Used ANN to predict the energy consumption in a hotel room (Antonio, et al, 2017) Produced a cancellation prediction system, based on a machine-learning model. (Casteleiro-Roca, et al, 2018) The machine learning model predicted power demand with 98 % accuracy in advance of 24 h. (Pelet, et al, 2019) Reported the cost and technological experience as an obstacle to AI (Antonio, et al, 2019) Machine learning implementation predicted the booking cancellation accuracy of over 84%. (Yi, 2019) Reported improved the hotel's financial efficiency and reduced unnecessary costs on implementing AI.…”

Section: P a G Ementioning

confidence: 99%

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Application of Machine Learning in the Hotel Industry: A Critical Review

Alotaibi

2020

Journal of Association of Arab Universities for Tourism and Hos

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Study purpose-The hotel industry like any other industry is witnessing a change due to information and communication technology. However, this change is quite slow. Many researchers in recent time have garnered interest in exploring and implementing the new technologies of artificial intelligence and machine learning in the hotel industry. Therefore, the purpose of this study is to give insights on the role of ML and its integrated technologies in the hotel industry. Design/Methodology/Approach-The study has critically reviewed articles published from 2010 to 2020. To achieve the research objective, the study seeks to answer three main research questions related to the existing literature; RQ1: Where does the hotel industry implement machine learning? RQ2: What are the machine learning techniques used in the hotel industry? RQ3: Which countries are using machine learning in the hotel industry? Findings-The study found that machine learning is helpful in demand forecasting, price forecasting, booking cancellation prediction, financial efficiency, and work efficiency. The machine learning algorithms outperform in the forecast accuracy against the statistical models. The countries at the forefront in machine learning technologies are China and USA. The other countries should take the cue from them and implement machine learning in their hotels Originality of the research-This research conducts exploratory analysis to identify the extent of scientific community knowledge and awareness on machine learning in the hotel industry. To the best of the authors' knowledge, no prior researcher has conducted a similar study specifically in the hotel industry.

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Digital Transformation in Tourism: An Intelligent Information System Proposition for Hotel Organizations

Yaman

Başeğmez

2022

Intelligent Systems in Digital Transformation

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Internet of Things and Artificial Intelligence in the Hotel Industry: Which Opportunities and Threats for Sensory Marketing?

Cited by 14 publications

References 20 publications

Smart Hotels and Sustainable Consumer Behavior: Testing the Effect of Perceived Performance, Attitude, and Technology Readiness on Word-of-Mouth

Smart Hotels and Sustainable Consumer Behavior: Testing the Effect of Perceived Performance, Attitude, and Technology Readiness on Word-of-Mouth

Application of Machine Learning in the Hotel Industry: A Critical Review

Digital Transformation in Tourism: An Intelligent Information System Proposition for Hotel Organizations

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