Research Article
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Year 2022, Volume: 8 Issue: 1, 49 - 67, 30.06.2022
https://doi.org/10.26650/jot.2022.8.1.1038566

Abstract

References

  • Adebanjo, D., Teh, P.-L., & Ahmed, P. K. (2016). The impact of external pressure and sustainable management practices on manufacturing performance and environmental outcomes. International Journal of Operations & Production Management, 36 , 995–1013.
  • Ahani, A., Nilashi, M., Yadegaridehkordi, E., Sanzogni, L., Tarik, A. R., Knox, K., Samad, S., & Ibrahim, O. (2019). Revealing customers’ satisfaction and preferences through online review analysis: The case of canary islands hotels. Journal of Retailing and Consumer Services, 51 , 331–343.
  • Ahmad, S. Z., Bakar, A. R. A., Faziharudean, T. M., & Zaki, K. A. M. (2015). An empirical study of factors affecting e-commerce adoption among small- and medium-sized enterprises in a developing country: Evidence from malaysia. Information Technology for Development, 21 , 555–572.
  • Akbik, A., Bergmann, T., Blythe, D., Rasul, K., Schweter, S., & Vollgraf, R. (2019). Flair: An easy-to-use framework for state-of-the-art nlp. In NAACL 2019, 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations) (pp. 54
  • Alrawadieh, Z., Alrawadieh, Z., & Cetin, G. (2021). Digital transformation and revenue management: Evidence from the hotel industry. Tourism Economics, 27(2), 328–345.
  • Beldona, S., & Cobanoglu, C. (2007). Importance-performance analysis of guest technologies in the lodging industry. Cornell Hotel and Restaurant Administration Quarterly, 48, 299–312.
  • Berezina, K., Bilgihan, A., Cobanoglu, C., & Okumus, F. (2016). Understanding satisfied and dissatisfied hotel customers: Text mining of online hotel reviews. Journal of Hospitality Marketing & Management, 25, 1–24.
  • Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python: analyzing text with the natural language toolkit. ” O’Reilly Media, Inc.”.
  • Bulchand-Gidumal, J., Meli´an-Gonz´alez, S., & L´opez-Valc´arcel, B. G. (2011). Improving hotel ratings by offering free wi-fi. Journal of Hospitality and Tourism Technology, 2, 235–245.
  • Calheiros, A. C., Moro, S., & Rita, P. (2017). Sentiment classification of consumer-generated online reviews using topic modeling. Journal of Hospitality Marketing & Management, 26, 675–693.
  • Chevers, D. A., & Spencer, A. J. (2017). Customer satisfaction in jamaican hotels through the use of information and communication technology. Worldwide Hospitality and Tourism Themes, 9, 70–85. –59).
  • Chua, A. Y., & Banerjee, S. (2016). Helpfulness of user-generated reviews as a function of review sentiment, product type and information quality. Computers in Human Behavior, 54, 547–554.
  • Cobanoglu, C., Berezina, K., Kasavana, M. L., & Erdem, M. (2011). The impact of technology amenities on hotel guest overall satisfaction. Journal of Quality Assurance in Hospitality & Tourism, 12, 272 – 288.
  • Davras, O., & Caber, M. (2019). Analysis of hotel services by their symmetric and asymmetric effects on overall customer satisfaction: A comparison of market segments. International Journal of Hospitality Management, 81, 83–93.
  • Ezzaouia, I., & Bulchand-Gidumal, J. (2020). Factors influencing the adoption of information technology in the hotel industry. an analysis in a developing country. Tourism Management Perspectives, 34, 100675.
  • Fang, B., Ye, Q., Kucukusta, D., & Law, R. (2016). Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics. Tourism Management, 52, 498–506.
  • Gao, B., Li, X., Liu, S., & Fang, D. (2018). How power distance affects online hotel ratings: The positive moderating roles of hotel chain and reviewers’ travel experience. Tourism Management, 65, 176–186.
  • Geetha, M., Singha, P., & Sinha, S. (2017). Relationship between customer sentiment and online customer ratings for hotels - an empirical analysis. Tourism Management, 61, 43–54.
  • Ham, S., Gon Kim, W., & Jeong, S. (2005). Effect of information technology on performance in upscale hotels. International Journal of Hospitality Management, 24, 281–294.
  • He, W., Tian, X., Tao, R., Zhang, W., Yan, G., & Akula, V. (2017). Application of social media analytics: a case of analyzing online hotel reviews. Online Inf. Rev., 41, 921–935.
  • HuggingFace (2021a). Translation Models - Hugging Face huggingface.co. https://huggingface.co/models?pipeline_tag=translation&sort=downloads. [Online; accessed 21-November-2021].
  • HuggingFace (2021b). Zero-shot Classification Models - Hugging Face huggingface.co. https://huggingface.co/models?pipeline_tag=zero-shot-classification&sort=downloads. [Online; accessed 21-November-2021].
  • Hutto, C. J., & Gilbert, E. (2014). Vader: A parsimonious rule-based model for sentiment analysis of social media text. In ICWSM.
  • Khoo-Lattimore, C., Mura, P., & Yung, R. (2019). The time has come: a systematic literature review of mixed methods research in tourism. Current Issues in Tourism, 22, 1531–1550.
  • Kim, D., Hong, S., Park, B.-J., & Kim, I. (2020). Understanding heterogeneous preferences of hotel choice attributes: Do customer segments matter? Journal of Hospitality and Tourism Management, 45, 330–337.
  • Kim, W. G., & Ham, S. (2006). The impact of information technology implementation on service quality in the hotel industry. Information Technology in Hospitality, 4, 143–151.
  • Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., Stoyanov, V., & Zettlemoyer, L. (2019). BART: denoising sequence-to-sequence 585 pre-training for natural language generation, translation, and comprehension. CoRR, abs/1910.13461.
  • Li, H., Ye, Q., & Law, R. (2013). Determinants of customer satisfaction in the hotel industry: An application of online review analysis. Asia Pacific Journal of Tourism Research, 18, 784–802.
  • Liu, Y., Teichert, T., Rossi, M., Li, H., & Hu, F. (2017). Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews. Tourism Management, 59, 554–563.
  • Loria, S. (2018). textblob documentation. Release 0.15, 2, 269.
  • Lu, W., & Stepchenkova, S. (2012). Ecotourism experiences reported online: Classification of satisfaction attributes. Tourism Management, 33, 702–712.
  • Melian-Gonzalez, S., & Bulchand-Gidumal, J. (2016). A model that connects information technology and hotel performance. Tourism Management, 53, 30–37.
  • Mihalic, T., & Buhalis, D. (2013). Ict as a new competitive advantage factorcase of small transitional hotel sector. Economic and business review, 15, 33–56.
  • Moliner-Velazquez, B., Fuentes-Blasco, M. and Gil-Saura, I. (2019), "The role of ICT, eWOM and guest characteristics in loyalty", Journal of Hospitality and Tourism Technology, Vol. 10 No. 2, pp. 153-168.
  • Nunkoo, R., Teeroovengadum, V., Ringle, C. M., & Sunnassee, V. (2020). Service quality and customer satisfaction: The moderating effects of hotel star rating. International Journal of Hospitality Management, 91, 102414.
  • Nusair, K. K., Bilgihan, A., & Okumus, F. (2013). The role of online social network travel websites in creating social interaction for gen y travelers. International Journal of Tourism Research, 15, 458–472.
  • Padma, P., & Ahn, J. (2020). Guest satisfaction & dissatisfaction in luxury hotels: An application of big data. International Journal of Hospitality Management, 84, 102318.
  • Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2020). Exploring the limits of transfer learning with a unified text-to-text transformer. Journal of Machine Learning Research, 21, 1–67.
  • Ruan, Y. (2020). Perceived host-guest sociability similarity and participants’ satisfaction: Perspectives of airbnb guests and hosts. Journal of Hospitality and Tourism Management, 45, 419–428.
  • Ryssel, R., Ritter, T., & Gemünden, H. G. (2004). The impact of information technology deployment on trust, commitment and value creation in business relationships. Journal of Business & Industrial Marketing, 19, 197–207.
  • Shin, S., Du, Q., Ma, Y., Fan, W., & Xiang, Z. (2021). Moderating effects of rating on text and helpfulness in online hotel reviews: an analytical approach. Journal of Hospitality Marketing & Management, 30, 159–177.
  • Sigala, M. (2003). The information and communication technologies productivity impact on the uk hotel sector. International Journal of Operations & Production Management, 23, 1224–1245.
  • Siguaw, J. A., Enz, C. A., & Namasivayam, K. (2000). Adoption of information technology in u.s. hotels: Strategically driven objectives. Journal of Travel Research, 39, 192–201.
  • Sirirak, S., Islam, N., & Khang, D. B. (2011). Does ict adoption enhance hotel performance. Journal of Hospitality and Tourism Technology, 2, 34–49.
  • Statista (2021). Tripadvisor: number of reviews 2020 — Statista. https://www.statista.com/statistics/684862/tripadvisor-number-of-reviews/. [Online; accessed 21-November-2021].
  • Velazquez, B. M., Blasco, M. F., & Saura, I. G. (2015). Ict adoption in hotels and electronic word-of-mouth. Academia-revista Latinoamericana De Administracion, 28, 227–250.
  • Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., Davison, J., Shleifer, S., von Platen, P., Ma, C., Jernite, Y., Plu, J., Xu, C., Scao, T. L., Gugger, S., Drame, M., Lhoest, Q., & Rush, A. M. (2020). Transformers: State-of-the-art natural language processing. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations (pp. 38–45). Online: Association for Computational Linguistics.
  • Xiang, Z., Schwartz, Z., Gerdes, J. H., & Uysal, M. (2015). What can big data and text analytics tell us about hotel guest experience and satisfaction? International Journal of Hospitality Management, 44, 120–130.
  • Xu, X., & Li, Y. (2016). The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: A text mining approach. International Journal of Hospitality Management, 55, 57–69.
  • Xu, X., Li, Y., & Lu, A. C. C. (2019a). A comparative study of the determinants of business and leisure travellers’ satisfaction and dissatisfaction. International Journal of Services and Operations Management, 33, 87–112.
  • Xu, X., Liu, W., & Gursoy, D. (2019b). The impacts of service failure and recovery efforts on airline customers’ emotions and satisfaction. Journal of Travel Research, 58, 1034–1051.
  • Ye, Q., Li, H., Wang, Z., & Law, R. (2014). The influence of hotel price on perceived service quality and value in e-tourism: An empirical investigation based on online traveler reviews. Journal of Hospitality & Tourism Research, 38, 23–39.
  • Yin, W., Hay, J., & Roth, D. (2019). Benchmarking zero-shot text classification: Datasets, evaluation and entailment approach. CoRR, abs/1909.00161.
  • Zaied, A. N. H. (2012). Barriers to e-commerce adoption in egyptian smes. International Journal of Information Engineering and Electronic Business, 4, 9–18.
  • Zhang, T., Seo, S., & Ahn, J. A. (2019). Why hotel guests go mobile? examining motives of business and leisure travelers. Journal of Hospitality Marketing & Management, 28, 621–644.
  • Zhang, X., Yu, Y., Li, H., & Lin, Z. (2016). Sentimental interplay between structured and unstructured user-generated contents: An empirical study on online hotel reviews. Online Inf. Rev., 40, 119–145.
  • Zhao, Y., Xu, X., & Wang, M. (2019). Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews. International Journal of Hospitality Management, 76, 111–121.

Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction

Year 2022, Volume: 8 Issue: 1, 49 - 67, 30.06.2022
https://doi.org/10.26650/jot.2022.8.1.1038566

Abstract

Online hotel reviews are a rich source of information regarding drivers of customer satisfaction or dissatisfaction with hotel services. In this paper, we study the impact of information and communication technologies (ICT) on the satisfaction of customers of 144 Algerian hotels through the analysis of 11310 online user reviews. The methodology adopted is based on the analysis of the sentiments expressed in the user reviews from one of the most used travel platforms, TripAdvisor. The results indicate that sentiment towards ICT contributes to satisfaction but not as much as sentiment towards other non-ICT services. Furthermore, we identified individually which ICTs contribute to satisfaction. We found that ICTs related to booking, comfort and entertainment were the ones that significantly contributed to satisfaction, while ICT related to safety and security did not. We believe that this study contributes to the literature because it uses innovative natural language processing techniques as opposed to traditional questionnaire-based approaches. Moreover, this study was conducted in a developing country where ICT adoption differs from that of developed countries.

References

  • Adebanjo, D., Teh, P.-L., & Ahmed, P. K. (2016). The impact of external pressure and sustainable management practices on manufacturing performance and environmental outcomes. International Journal of Operations & Production Management, 36 , 995–1013.
  • Ahani, A., Nilashi, M., Yadegaridehkordi, E., Sanzogni, L., Tarik, A. R., Knox, K., Samad, S., & Ibrahim, O. (2019). Revealing customers’ satisfaction and preferences through online review analysis: The case of canary islands hotels. Journal of Retailing and Consumer Services, 51 , 331–343.
  • Ahmad, S. Z., Bakar, A. R. A., Faziharudean, T. M., & Zaki, K. A. M. (2015). An empirical study of factors affecting e-commerce adoption among small- and medium-sized enterprises in a developing country: Evidence from malaysia. Information Technology for Development, 21 , 555–572.
  • Akbik, A., Bergmann, T., Blythe, D., Rasul, K., Schweter, S., & Vollgraf, R. (2019). Flair: An easy-to-use framework for state-of-the-art nlp. In NAACL 2019, 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations) (pp. 54
  • Alrawadieh, Z., Alrawadieh, Z., & Cetin, G. (2021). Digital transformation and revenue management: Evidence from the hotel industry. Tourism Economics, 27(2), 328–345.
  • Beldona, S., & Cobanoglu, C. (2007). Importance-performance analysis of guest technologies in the lodging industry. Cornell Hotel and Restaurant Administration Quarterly, 48, 299–312.
  • Berezina, K., Bilgihan, A., Cobanoglu, C., & Okumus, F. (2016). Understanding satisfied and dissatisfied hotel customers: Text mining of online hotel reviews. Journal of Hospitality Marketing & Management, 25, 1–24.
  • Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python: analyzing text with the natural language toolkit. ” O’Reilly Media, Inc.”.
  • Bulchand-Gidumal, J., Meli´an-Gonz´alez, S., & L´opez-Valc´arcel, B. G. (2011). Improving hotel ratings by offering free wi-fi. Journal of Hospitality and Tourism Technology, 2, 235–245.
  • Calheiros, A. C., Moro, S., & Rita, P. (2017). Sentiment classification of consumer-generated online reviews using topic modeling. Journal of Hospitality Marketing & Management, 26, 675–693.
  • Chevers, D. A., & Spencer, A. J. (2017). Customer satisfaction in jamaican hotels through the use of information and communication technology. Worldwide Hospitality and Tourism Themes, 9, 70–85. –59).
  • Chua, A. Y., & Banerjee, S. (2016). Helpfulness of user-generated reviews as a function of review sentiment, product type and information quality. Computers in Human Behavior, 54, 547–554.
  • Cobanoglu, C., Berezina, K., Kasavana, M. L., & Erdem, M. (2011). The impact of technology amenities on hotel guest overall satisfaction. Journal of Quality Assurance in Hospitality & Tourism, 12, 272 – 288.
  • Davras, O., & Caber, M. (2019). Analysis of hotel services by their symmetric and asymmetric effects on overall customer satisfaction: A comparison of market segments. International Journal of Hospitality Management, 81, 83–93.
  • Ezzaouia, I., & Bulchand-Gidumal, J. (2020). Factors influencing the adoption of information technology in the hotel industry. an analysis in a developing country. Tourism Management Perspectives, 34, 100675.
  • Fang, B., Ye, Q., Kucukusta, D., & Law, R. (2016). Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics. Tourism Management, 52, 498–506.
  • Gao, B., Li, X., Liu, S., & Fang, D. (2018). How power distance affects online hotel ratings: The positive moderating roles of hotel chain and reviewers’ travel experience. Tourism Management, 65, 176–186.
  • Geetha, M., Singha, P., & Sinha, S. (2017). Relationship between customer sentiment and online customer ratings for hotels - an empirical analysis. Tourism Management, 61, 43–54.
  • Ham, S., Gon Kim, W., & Jeong, S. (2005). Effect of information technology on performance in upscale hotels. International Journal of Hospitality Management, 24, 281–294.
  • He, W., Tian, X., Tao, R., Zhang, W., Yan, G., & Akula, V. (2017). Application of social media analytics: a case of analyzing online hotel reviews. Online Inf. Rev., 41, 921–935.
  • HuggingFace (2021a). Translation Models - Hugging Face huggingface.co. https://huggingface.co/models?pipeline_tag=translation&sort=downloads. [Online; accessed 21-November-2021].
  • HuggingFace (2021b). Zero-shot Classification Models - Hugging Face huggingface.co. https://huggingface.co/models?pipeline_tag=zero-shot-classification&sort=downloads. [Online; accessed 21-November-2021].
  • Hutto, C. J., & Gilbert, E. (2014). Vader: A parsimonious rule-based model for sentiment analysis of social media text. In ICWSM.
  • Khoo-Lattimore, C., Mura, P., & Yung, R. (2019). The time has come: a systematic literature review of mixed methods research in tourism. Current Issues in Tourism, 22, 1531–1550.
  • Kim, D., Hong, S., Park, B.-J., & Kim, I. (2020). Understanding heterogeneous preferences of hotel choice attributes: Do customer segments matter? Journal of Hospitality and Tourism Management, 45, 330–337.
  • Kim, W. G., & Ham, S. (2006). The impact of information technology implementation on service quality in the hotel industry. Information Technology in Hospitality, 4, 143–151.
  • Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., Stoyanov, V., & Zettlemoyer, L. (2019). BART: denoising sequence-to-sequence 585 pre-training for natural language generation, translation, and comprehension. CoRR, abs/1910.13461.
  • Li, H., Ye, Q., & Law, R. (2013). Determinants of customer satisfaction in the hotel industry: An application of online review analysis. Asia Pacific Journal of Tourism Research, 18, 784–802.
  • Liu, Y., Teichert, T., Rossi, M., Li, H., & Hu, F. (2017). Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews. Tourism Management, 59, 554–563.
  • Loria, S. (2018). textblob documentation. Release 0.15, 2, 269.
  • Lu, W., & Stepchenkova, S. (2012). Ecotourism experiences reported online: Classification of satisfaction attributes. Tourism Management, 33, 702–712.
  • Melian-Gonzalez, S., & Bulchand-Gidumal, J. (2016). A model that connects information technology and hotel performance. Tourism Management, 53, 30–37.
  • Mihalic, T., & Buhalis, D. (2013). Ict as a new competitive advantage factorcase of small transitional hotel sector. Economic and business review, 15, 33–56.
  • Moliner-Velazquez, B., Fuentes-Blasco, M. and Gil-Saura, I. (2019), "The role of ICT, eWOM and guest characteristics in loyalty", Journal of Hospitality and Tourism Technology, Vol. 10 No. 2, pp. 153-168.
  • Nunkoo, R., Teeroovengadum, V., Ringle, C. M., & Sunnassee, V. (2020). Service quality and customer satisfaction: The moderating effects of hotel star rating. International Journal of Hospitality Management, 91, 102414.
  • Nusair, K. K., Bilgihan, A., & Okumus, F. (2013). The role of online social network travel websites in creating social interaction for gen y travelers. International Journal of Tourism Research, 15, 458–472.
  • Padma, P., & Ahn, J. (2020). Guest satisfaction & dissatisfaction in luxury hotels: An application of big data. International Journal of Hospitality Management, 84, 102318.
  • Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2020). Exploring the limits of transfer learning with a unified text-to-text transformer. Journal of Machine Learning Research, 21, 1–67.
  • Ruan, Y. (2020). Perceived host-guest sociability similarity and participants’ satisfaction: Perspectives of airbnb guests and hosts. Journal of Hospitality and Tourism Management, 45, 419–428.
  • Ryssel, R., Ritter, T., & Gemünden, H. G. (2004). The impact of information technology deployment on trust, commitment and value creation in business relationships. Journal of Business & Industrial Marketing, 19, 197–207.
  • Shin, S., Du, Q., Ma, Y., Fan, W., & Xiang, Z. (2021). Moderating effects of rating on text and helpfulness in online hotel reviews: an analytical approach. Journal of Hospitality Marketing & Management, 30, 159–177.
  • Sigala, M. (2003). The information and communication technologies productivity impact on the uk hotel sector. International Journal of Operations & Production Management, 23, 1224–1245.
  • Siguaw, J. A., Enz, C. A., & Namasivayam, K. (2000). Adoption of information technology in u.s. hotels: Strategically driven objectives. Journal of Travel Research, 39, 192–201.
  • Sirirak, S., Islam, N., & Khang, D. B. (2011). Does ict adoption enhance hotel performance. Journal of Hospitality and Tourism Technology, 2, 34–49.
  • Statista (2021). Tripadvisor: number of reviews 2020 — Statista. https://www.statista.com/statistics/684862/tripadvisor-number-of-reviews/. [Online; accessed 21-November-2021].
  • Velazquez, B. M., Blasco, M. F., & Saura, I. G. (2015). Ict adoption in hotels and electronic word-of-mouth. Academia-revista Latinoamericana De Administracion, 28, 227–250.
  • Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., Davison, J., Shleifer, S., von Platen, P., Ma, C., Jernite, Y., Plu, J., Xu, C., Scao, T. L., Gugger, S., Drame, M., Lhoest, Q., & Rush, A. M. (2020). Transformers: State-of-the-art natural language processing. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations (pp. 38–45). Online: Association for Computational Linguistics.
  • Xiang, Z., Schwartz, Z., Gerdes, J. H., & Uysal, M. (2015). What can big data and text analytics tell us about hotel guest experience and satisfaction? International Journal of Hospitality Management, 44, 120–130.
  • Xu, X., & Li, Y. (2016). The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: A text mining approach. International Journal of Hospitality Management, 55, 57–69.
  • Xu, X., Li, Y., & Lu, A. C. C. (2019a). A comparative study of the determinants of business and leisure travellers’ satisfaction and dissatisfaction. International Journal of Services and Operations Management, 33, 87–112.
  • Xu, X., Liu, W., & Gursoy, D. (2019b). The impacts of service failure and recovery efforts on airline customers’ emotions and satisfaction. Journal of Travel Research, 58, 1034–1051.
  • Ye, Q., Li, H., Wang, Z., & Law, R. (2014). The influence of hotel price on perceived service quality and value in e-tourism: An empirical investigation based on online traveler reviews. Journal of Hospitality & Tourism Research, 38, 23–39.
  • Yin, W., Hay, J., & Roth, D. (2019). Benchmarking zero-shot text classification: Datasets, evaluation and entailment approach. CoRR, abs/1909.00161.
  • Zaied, A. N. H. (2012). Barriers to e-commerce adoption in egyptian smes. International Journal of Information Engineering and Electronic Business, 4, 9–18.
  • Zhang, T., Seo, S., & Ahn, J. A. (2019). Why hotel guests go mobile? examining motives of business and leisure travelers. Journal of Hospitality Marketing & Management, 28, 621–644.
  • Zhang, X., Yu, Y., Li, H., & Lin, Z. (2016). Sentimental interplay between structured and unstructured user-generated contents: An empirical study on online hotel reviews. Online Inf. Rev., 40, 119–145.
  • Zhao, Y., Xu, X., & Wang, M. (2019). Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews. International Journal of Hospitality Management, 76, 111–121.
There are 57 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Salma Cherdouh 0000-0002-6215-1045

Abdenacer Kherri This is me 0000-0003-2923-5922

Ayoub Abbaci This is me

Salim Kebir This is me 0000-0002-7101-6523

Publication Date June 30, 2022
Submission Date December 20, 2021
Published in Issue Year 2022 Volume: 8 Issue: 1

Cite

APA Cherdouh, S., Kherri, A., Abbaci, A., Kebir, S. (2022). Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction. Journal of Tourismology, 8(1), 49-67. https://doi.org/10.26650/jot.2022.8.1.1038566
AMA Cherdouh S, Kherri A, Abbaci A, Kebir S. Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction. Journal of Tourismology. June 2022;8(1):49-67. doi:10.26650/jot.2022.8.1.1038566
Chicago Cherdouh, Salma, Abdenacer Kherri, Ayoub Abbaci, and Salim Kebir. “Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction”. Journal of Tourismology 8, no. 1 (June 2022): 49-67. https://doi.org/10.26650/jot.2022.8.1.1038566.
EndNote Cherdouh S, Kherri A, Abbaci A, Kebir S (June 1, 2022) Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction. Journal of Tourismology 8 1 49–67.
IEEE S. Cherdouh, A. Kherri, A. Abbaci, and S. Kebir, “Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction”, Journal of Tourismology, vol. 8, no. 1, pp. 49–67, 2022, doi: 10.26650/jot.2022.8.1.1038566.
ISNAD Cherdouh, Salma et al. “Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction”. Journal of Tourismology 8/1 (June 2022), 49-67. https://doi.org/10.26650/jot.2022.8.1.1038566.
JAMA Cherdouh S, Kherri A, Abbaci A, Kebir S. Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction. Journal of Tourismology. 2022;8:49–67.
MLA Cherdouh, Salma et al. “Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction”. Journal of Tourismology, vol. 8, no. 1, 2022, pp. 49-67, doi:10.26650/jot.2022.8.1.1038566.
Vancouver Cherdouh S, Kherri A, Abbaci A, Kebir S. Using Sentiment Analysis of Online Hotel Reviews To Explore the Effect of Information and Communication Technologies on Hotel Guest Satisfaction. Journal of Tourismology. 2022;8(1):49-67.