Understanding Guests’ Multisentiment Responses to Hotel Innovation

Technological innovation has been consistently acknowledged as the driving force for organizational success and a potential means of fostering positive customer emotions. Drawing on technological determinism, this mixed-methods research takes a step further to assess the sociotechnical dynamics of technology within a hotel innovation process on the basis of customers’ emotional responses. Study 1 analyzes the influence of hotel innovation activities on consumers’ multisentiment traits by gauging online reviews of a smart hotel using deep learning. Furthermore, to diagnose changes in sentiments that correspond to changes in hotel innovations, we adopted a longitudinal design to contrast pre- and postinnovation stages. Study 2 takes a qualitative approach to unlock the reasons that lie behind the mixed positive and negative sentiment responses to changes. The evidence from this investigation points to the double-edged impact of innovation. More importantly, they reflect technological somnambulism—in which customers do not seem to be sufficiently conscious of their choice of technology—highlighting the peril of the smart service encounter turning a hospitality oasis with rich human interactions into an artificial intelligence (AI)–dominated environment.

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Publication Details

Journal
Cornell Hospitality Quarterly
Published
2025-11-10
DOI
https://doi.org/10.1177/19389655251379457
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
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article

Understanding Guests’ Multisentiment Responses to Hotel Innovation

Y. Li, IpKin Anthony Wong, Danni Sun, GuoQiong Ivanka Huang et al.
1 citations
Cornell Hospitality Quarterly
AI in Service Interactions
2.48
article

Understanding Guests’ Multisentiment Responses to Hotel Innovation

Y. Li, IpKin Anthony Wong, Danni Sun, GuoQiong Ivanka Huang, D. H. Zhang
article en
1 citations

Abstract

Technological innovation has been consistently acknowledged as the driving force for organizational success and a potential means of fostering positive customer emotions. Drawing on technological determinism, this mixed-methods research takes a step further to assess the sociotechnical dynamics of technology within a hotel innovation process on the basis of customers’ emotional responses. Study 1 analyzes the influence of hotel innovation activities on consumers’ multisentiment traits by gauging online reviews of a smart hotel using deep learning. Furthermore, to diagnose changes in sentiments that correspond to changes in hotel innovations, we adopted a longitudinal design to contrast pre- and postinnovation stages. Study 2 takes a qualitative approach to unlock the reasons that lie behind the mixed positive and negative sentiment responses to changes. The evidence from this investigation points to the double-edged impact of innovation. More importantly, they reflect technological somnambulism—in which customers do not seem to be sufficiently conscious of their choice of technology—highlighting the peril of the smart service encounter turning a hospitality oasis with rich human interactions into an artificial intelligence (AI)–dominated environment.

Cornell Hospitality QuarterlyVol. 67(2)
Hong Kong Polytechnic University (HK), Sun Yat-sen University (CN), The University of Melbourne (AU), University of Macau (MO), Chinese University of Hong Kong, Shenzhen (CN), City University of Macau (MO)
Openalex Percentile: Top 8%
AI in Service Interactions
2.48
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Understanding Guests’ Multisentiment Responses to Hotel Innovation — Y. Li, IpKin Anthony Wong, et al. · Cornell Hospitality Quarterly (2025) | TGRS Research Map | TGRS