Data-Driven Insights from 10,000 Reviews: Fostering Sustainability through Rapid Adaptation to Guest Feedback
Abstract
:1. Introduction
2. Materials and Methods
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Hotel Runner Blog. Available online: https://blog.hotelrunner.com/key-factors-influencing-the-preferences-of-luxury-hotel-guests/ (accessed on 10 February 2024).
- Gallup. Available online: https://news.gallup.com/businessjournal/175568/economy-luxury-matters-hotel-guests.aspx (accessed on 10 February 2024).
- Cornell School of Hotel Administration. Hotel Performance Impact of Socially Engaging with Consumers. Available online: https://sha.cornell.edu/faculty-research/centers-institutes/chr/research-publications/hotel-performance-impact-socially-engaging-with-consumers/ (accessed on 11 February 2024).
- Padma, P.; Ahn, J. Guest satisfaction & dissatisfaction in luxury hotels: An application of big data. Int. J. Hosp. Manag. 2020, 84, 102318. [Google Scholar] [CrossRef]
- Cornell School of Hotel Administration. How Hotels Can Benefit from Bad Reviews. Available online: https://business.cornell.edu/hub/2017/02/13/hotels-benefit-bad-reviews/ (accessed on 11 February 2024).
- TrustYou. Available online: https://www.trustyou.com/blog/research/top-guest-reviews-sources-2022 (accessed on 11 February 2024).
- Kumar, J.; Maidullah, S. The impact of hotel responses to online negative reviews on consumers’ purchase intention. Enlightening Tourism. Pathmaking J. 2022, 12, 213–242. [Google Scholar] [CrossRef]
- Chatterjee, S. Drivers of helpfulness of online hotel reviews: A sentiment and emotion mining approach. Int. J. Hosp. Manag. 2019, 85, 102356. [Google Scholar] [CrossRef]
- Ye, Q.; Law, R.; Gu, B. The Impact of Online User Reviews on Hotel Room Sales. Int. J. Hosp. Manag. 2009, 28, 180–182. [Google Scholar] [CrossRef]
- Cornell School of Hotel Administration. The Impact of Social Media on Lodging Performance. Available online: https://sha.cornell.edu/wp-content/uploads/sites/4/2019/03/anderson-social-media.pdf (accessed on 11 February 2024).
- Gao, L.; Bai, X. A unified perspective on the factors influencing consumer acceptance of internet of things technology. Asia Pac. J. Mark. Logist. 2014, 26, 211–231. [Google Scholar] [CrossRef]
- Ali, F. Hotel website quality, perceived flow, customer satisfaction and purchase intention. J. Hosp. Tour. Technol. 2016, 7, 213–228. [Google Scholar] [CrossRef]
- Patil, D.R.; Rane, N.L. Customer experience and satisfaction: Importance of customer reviews and customer value on buying preference. Int. Res. J. Mod. Eng. Technol. Sci. 2023, 5, 3437–3447. [Google Scholar] [CrossRef]
- Füller, J.; Matzler, K. Customer delight and market segmentation: An application of the three-factor theory of customer satisfaction on life style groups. Tour. Manag. 2008, 29, 116–126. [Google Scholar] [CrossRef]
- Guerreiro, J.; Rita, P. How to predict explicit recommendations in online reviews using text mining and sentiment analysis. J. Hosp. Tour. Manag. 2020, 43, 269–272. [Google Scholar] [CrossRef]
- Zvarevashe, K.; Olugbara, O.O. A framework for sentiment analysis with opinion mining of hotel reviews. In Proceedings of the 2018 Conference on Information Communications Technology and Society (ICTAS), Durban, South Africa, 8–9 March 2018; IEEE: Piscataway, NY, USA, 2018; pp. 1–4. [Google Scholar] [CrossRef]
- Li, X.; Hitt, L.M. Price effects in online product reviews: An analytical model and empirical analysis. MIS Q. 2008, 32, 809–831. [Google Scholar] [CrossRef]
- Mauri, A.G.; Minazzi, R. Web reviews influence on expectations and purchasing intentions of hotel potential customers. Int. J. Hosp. Manag. 2013, 34, 99–107. [Google Scholar] [CrossRef]
- Park, D.H.; Lee, J.; Han, I. The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. Int. J. Electron. Commer. 2007, 11, 125–148. [Google Scholar] [CrossRef]
- Xie, K.L.; Zhang, Z.; Zhang, Z. The business value of online consumer reviews and management response to hotel performance. Int. J. Hosp. Manag. 2014, 43, 1–12. [Google Scholar] [CrossRef]
- Sayfuddin, A.; Chen, Y. The signaling and reputational effects of customer ratings on hotel revenues: Evidence from tripadvisor. Int. J. Hosp. Manag. 2021, 99, 103065. [Google Scholar] [CrossRef]
- Gaur, L.; Afaq, A.; Solanki, A.; Singh, G.; Sharma, S.; Jhanjhi, N.Z.; Le, D.N. Capitalizing on big data and revolutionary 5G technology: Extracting and visualizing ratings and reviews of global chain hotels. Comput. Electr. Eng. 2021, 95, 107374. [Google Scholar] [CrossRef]
- Zhang, X.; Kim, H.S. Customer experience and satisfaction of Disneyland hotel through big data analysis of online customer reviews. Sustainability 2021, 13, 12699. [Google Scholar] [CrossRef]
- Raguseo, E.; Vitari, C. The Effect of Brand on the Impact of e-WOM on Hotels’ Financial Performance. Int. J. Electron. Commer. 2017, 21, 249–269. [Google Scholar] [CrossRef]
- Gumussoy, C.A.; Koseoglu, B. The effects of service quality, perceived value and price fairness on hotel customers’ satisfaction and loyalty. J. Econ. Bus. Manag. 2016, 4, 523–527. [Google Scholar] [CrossRef]
- Behl, A.; Gaur, J.; Pereira, V.; Yadav, R.; Laker, B. Role of big data analytics capabilities to improve sustainable competitive advantage of MSME service firms during COVID-19–A multi-theoretical approach. J. Bus. Res. 2022, 148, 378–389. [Google Scholar] [CrossRef]
- Breuer, H.; Fichter, K.; Lüdeke-Freund, F.; Tiemann, I. Sustainability-oriented business model development: Principles, criteria and tools. Int. J. Entrep. Ventur. 2018, 10, 256–286. [Google Scholar] [CrossRef]
- Waas, T.; Hugé, J.; Block, T.; Wright, T.; Benitez-Capistros, F.; Verbruggen, A. Sustainability assessment and indicators: Tools in a decision-making strategy for sustainable development. Sustainability 2014, 6, 5512–5534. [Google Scholar] [CrossRef]
- Egan, D.; Haynes, N.C. Manager perceptions of big data reliability in hotel revenue management decision making. Int. J. Qual. Reliab. Manag. 2019, 36, 25–39. [Google Scholar] [CrossRef]
- Melián-Alzola, L.; Fernández-Monroy, M.; Hidalgo-Peñate, M. Hotels in contexts of uncertainty: Measuring organisational resilience. Tour. Manag. Perspect. 2020, 36, 100747. [Google Scholar] [CrossRef] [PubMed]
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Gîngioveanu Lupulescu, M.G.; Dincă, V.M.; Taranu, S.-D.; Blănuță, B.A. Data-Driven Insights from 10,000 Reviews: Fostering Sustainability through Rapid Adaptation to Guest Feedback. Sustainability 2024, 16, 2759. https://doi.org/10.3390/su16072759
Gîngioveanu Lupulescu MG, Dincă VM, Taranu S-D, Blănuță BA. Data-Driven Insights from 10,000 Reviews: Fostering Sustainability through Rapid Adaptation to Guest Feedback. Sustainability. 2024; 16(7):2759. https://doi.org/10.3390/su16072759
Chicago/Turabian StyleGîngioveanu Lupulescu, Mihnea Grigoraș, Violeta Mihaela Dincă, Silvia-Denisa Taranu, and Bianca Alexandra Blănuță. 2024. "Data-Driven Insights from 10,000 Reviews: Fostering Sustainability through Rapid Adaptation to Guest Feedback" Sustainability 16, no. 7: 2759. https://doi.org/10.3390/su16072759