Journal of Hospitality and Tourism Technology

Li, Nao; Yang, Xiaoyu; Wong, IpKin Anthony; Law, Rob; Xu, Jing Yang; Zhang, Binru

2023 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-03-2021-0099

This paper aims to classify the sentiment of online tourism-hospitality reviews at an aspect level. A new aspect-oriented sentiment classification method is proposed based on a neural network model.Design/methodology/approachThis study constructs an aspect-oriented sentiment classification model using an integrated four-layer neural network: the bidirectional encoder representation from transformers (BERT) word vector model, long short-term memory, interactive attention-over-attention (IAOA) mechanism and a linear output layer. The model was trained, tested and validated on an open training data set and 92,905 reviews extrapolated from restaurants in Tokyo.FindingsThe model achieves significantly better performance compared with other neural networks. The findings provide empirical evidence to validate the suitability of this new approach in the tourism-hospitality domain.Research limitations/implicationsMore sentiments should be identified to measure more fine-grained tourism-hospitality experience, and new aspects are recommended that can be automatically added into the aspect set to provide dynamic support for new dining experiences.Originality/valueThis study provides an update to the literature with respect to how a neural network could improve the performance of aspect-oriented sentiment classification for tourism-hospitality online reviews.

Demir, Mahmut; Yaşar, Emre; Demir, Şirvan Şen

2023 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-04-2021-0105

This study aims to examine the relationship between digital transformation (DigiTr), innovation and human resources planning (HRP) in hotels to investigate the impact of DigiTr on innovations and HRP and to test the mediating impact of innovation on the DigiTr-HRP relationship.Design/methodology/approachThe authors used a quantitative research method in this study, specifically by conducting a hybrid face-to-face and online survey to collect data from 462 human resources (HR) managers, department managers and HR professionals at four- and five-star hotels in Turkey. The structured questionnaire assessed DigiTr, innovations in business models, services and processes and quantitative and qualitative changes in HR. The authors used covariance-based structural equation modeling to test the hypotheses.FindingsDigiTr affected both innovations and HR planning in hotels, and also the effect of innovations on HR planning. In addition, DigiTr and innovations increased qualitative changes in HR planning but reduced quantitative changes. Finally, innovations mediated the relationship between DigiTr and HR planning.Practical implicationsThese findings indicate that employers and employees need to be aware of developments in employment in the tourism industry, as these can significantly impact HR planning via DigiTr and innovations.Originality/valueThis study differs from the existing literature by providing empirical evidence to fill the knowledge gap regarding how DigiTr and innovation affect HR planning.

Cui, Yuan; Kim, Seungwoon; Feng, Shi

2023 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-05-2021-0140

This study aims to explore the success factors of tourism performing arts (TPA) programs by analyzing a large data set of online reviews.Design/methodology/approachA total of 195,230 reviews from Ctrip.com were collected and preprocessed. A deep learning method was leveraged to estimate the similarity between words. Then, regression analysis was conducted to determine success factors.FindingsThis study extracted four positive and two negative factors affecting tourist satisfaction with tourism performance arts. The results demonstrate that the tourists paid the most attention to the traditional Chinese cultural aspects, audiovisual effects and the actors’ performing enthusiasm.Research limitations/implicationsDespite this study’s large data set, the focused was only on Chinese reviews. It would be useful and interesting to compare the success factors of tourism performance arts programs offered in different countries.Practical implicationsThe study findings can contribute to the development of TPA programs to attract tourists to travel destinations.Originality/valueThis study demonstrates that analyzing online reviews of TPA through text mining technology is an effective method of understanding tourist satisfaction.

Alma Çallı, Büşra; Çallı, Levent; Sarı Çallı, Didar; Çallı, Fatih

2023 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-09-2021-0266

The purpose of this study is to examine how consumers perceive the importance of using robot technologies for 12 services evaluated under two categories considering the technology acceptance model (TAM).Design/methodology/approachThe conceptual model analysis used structural equation modeling with the partial least squares estimation method, considering 638 responses.FindingsThe results revealed that the perceived importance (PI) of robotic service delivery tasks under “room division” and “food and beverage and secondary services” affect perceived usefulness (PU) and perceived ease of use (PEOU) differently. Besides, PEOU and PU significantly influence attitudes toward using robot-staffed hotels.Research limitations/implicationsThe nonprobability convenience sampling method was used as the data collection method. Future studies that prefer probabilistic methods will open a different perspective for evaluating the results.Practical implicationsThis study’s empirical findings reveal which robot-delivered services are found significant by the customers and contribute to increased customer satisfaction and loyalty. In addition, it guides accurate demand and investment planning for the tourism and hospitality industry in the post-COVID-19 era.Originality/valueTo the best of the authors’ knowledge, previous literature has not tested or confirmed the effects of PI related to two groups of robotic service delivery tasks on utilitarian variables. This study contributes to the literature by examining how different robotic service delivery tasks are linked to the TAM framework in a hotel setting.