The travel and tourism sector is one of the most impacted sectors during the COVID-19 pandemic. Existing limited studies often focused on assessing the flow of travellers and economic patterns. However, scant work evaluates customers’ perceptions and evaluation of the services offered during the COVID-19 pandemic. This study examines customers’ perceptions and emotions by evaluating their experiences shared through online reviews. The online reviews of the customers on the hotel (41,687 reviews) and airline (9,574 reviews) sectors were analysed via text mining and sentiment analysis techniques. The study results reveal that most customers exhibit a positive attitude towards the services in the hotel sector, while 50% of the airline reviews were negative. The results indicated that ‘anticipation’ and ‘trust’ are the customers’ most expressed emotions. This study provides important insights for restoring the hotel and airline sectors from the effect of COVID-19.
AlaeiA. R., BeckenS., & StanticB. (2019). Sentiment analysis in tourism: Capitalizing on big data. mJournal of Travel Research, 58(2), 175–191. https://doi.org/10.1177/0047287517747753
2.
BaileyA. A. (2005). Consumer awareness and use of product review websites. Journal of Interactive Advertising, 6(1), 68–81. https://doi.org/10.1080/15252019.2005.10722109
3.
BermpohlF., Pascual-LeoneA., AmediA., MerabetL. B., FregniF., GaabN., AlsopD., SchlaugG., & NorthoffG. (2006). Dissociable networks for the expectancy and perception of emotional stimuli in the human brain. Neuroimage, 30(2), 588–600. https://doi.org/10.1016/j.neuroimage.2005.09.040
4.
BhattacherjeeA. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921
5.
BiswasB., SenguptaP., & ChatterjeeD. (2020). Examining the determinants of the count of customer reviews in peer-to-peer home-sharing platforms using clustering and count regression techniques. Decision Support Systems, 135, 113324.
6.
Chatterjee,S. (2019). Explaining customer ratings and recommendations by combining qualitative and quantitative user generated contents. Decision Support Systems, 119, 14–22.
7.
ChatterjeeS., & MandalP. (2020). Traveler preferences from online reviews: Role of travel goals, class and culture. Tourism Management, 80, 104108. https://doi.org/10.1016/j.tourman.2020.104108
8.
CooperM. (2005). Japanese tourism and the SARS epidemic of 2003. Journal of Travel & Tourism Marketing, 19(2), 117–131. https://doi.org/10.1300/J073v19n02_10
9.
DuanW., CaoQ., YuY., & LevyS. (2013, January7–10). Mining online user-generated content: Using sentiment analysis technique to study hotel service quality. Proceedings of the 46th Annual Hawaii International Conference on System Sciences. https://doi.org/10.1109/HICSS.2013.400
10.
DurukanT., BozaciI., & HamsiogluA. B. (2012). An investigation of customer behaviours in social media. European Journal of Economics, Finance and Administrative Sciences, 44(44), 148–159.
11.
Fernández-MoralesA., Cisneros-MartínezJ. D., & McCabeS. (2016). Seasonal concentration of tourism demand: Decomposition analysis and marketing implications. Tourism Management, 56, 172–190. https://doi.org/10.1016/j.tourman.2016.04.004
12.
FerranteM., Lo MagnoG. L., & De CantisS. (2018). Measuring tourism seasonality across European countries. Tourism Management, 68, 220–235. https://doi.org/10.1016/j.tourman.2018.03.015
13.
FilieriR., RaguseoE., & VitariC. (2021). Extremely negative ratings and online consumer review helpfulness: The moderating role of product quality signals. Journal of Travel Research, 60(4), 699–717.
14.
GilbertD. T., & WilsonT. D. (2007). Prospection: Experiencing the future. Science, 317, 1351–1354. https://doi.org/10.1126/science.1144161
15.
GourA., AggarwalS., & ErdemM. (2021). Reading between the lines: Analyzing online reviews by using a multi-method Web-analytics approach. International Journal of Contemporary Hospitality Management, 33(2), 490–512. https://doi.org/10.1108/IJCHM-07-2020-0760
16.
GösslingS., ScottD., & HallC. M. (2020). Pandemics, tourism and global change: A rapid assessment of COVID-19. Journal of Sustainable Tourism, 29(1), 1–20. https://doi.org/10.1080/09669582.2020.1758708
17.
GrupeD. W., & NitschkeJ. B. (2013). Uncertainty and anticipation in anxiety: An integrated neurobiological and psychological perspective. Nature Reviews Neuroscience, 14, 488–501. https://doi.org/10.1038/nrn3524
18.
HuF., TeichertT., DengS., LiuY., & ZhouG. (2021). Dealing with pandemics: An investigation of the effects of COVID-19 on customers’ evaluations of hospitality services. Tourism Management, 85, 1–13. https://doi.org/10.1016/j.tourman.2021.104320
19.
HuF., TeichertT., LiuY., LiH., & GundyrevaE. (2019). Evolving customer expectations of hospitality services: Differences in attribute effects on satisfaction and re-patronage. Tourism Management, 74, 345–357. https://doi.org/10.1016/j.tourman.2019.04.010
KimD. J. (2012). An investigation of the effect of online consumer trust on expectation, satisfaction, and post-expectation. Information Systems and e-Business Management, 10(2), 219–240. https://doi.org/10.1007/s10257-010-0136-2
22.
KimS. S., GuoY., & AgrusaJ. (2005). Preference and positioning analyses of overseas destinations by mainland Chinese outbound pleasure tourists. Journal of Travel Research, 44(2), 212–220. https://doi.org/10.1177/0047287505278979
23.
Kim,S., Kim,J., & Park,S. (2021). The effects of perceived value, website trust and hotel trust on online hotel booking intention.
24.
KirilenkoA. P., StepchenkovaS. O., KimH., & LiX. (2018). Automated sentiment analysis in tourism: Comparison of approaches. Journal of Travel Research, 57(8), 1012–1025. https://doi.org/10.1177/0047287517729757
25.
LaiI. K. W., & HitchcockM. (2017). Sources of satisfaction with luxury hotels for new, repeat, and frequent travelers: A PLS impact-asymmetry analysis. Tourism Management, 60, 107–129. https://doi.org/10.1016/j.tourman.2016.11.011
26.
LeeJ. S., & ChoiM. (2020). Examining the asymmetric effect of multi-shopping tourism attributes on overall shopping destination satisfaction. Journal of Travel Research, 59(2), 295–314. https://doi.org/10.1177/0047287519832373
27.
LeeC. K., SongH. J., BendleL. J., KimM. J., & HanH. (2012). The impact of non-pharmaceutical interventions for 2009 H1N1 influenza on travel intentions: A model of goal-directed behavior. Tourism Management, 33(1), 89–99. https://doi.org/10.1016/j.tourman.2011.02.006
28.
LiC., McCabeS., & SongH. (2017). Tourist choice processing: Evaluating decision rules and methods of their measurement. Journal of Travel Research, 56(6), 699–711.
29.
LiS., WangY., FilieriR., & ZhuY. (2022), Eliciting positive emotion through strategic responses to COVID-19 crisis: Evidence from the tourism sector. Tourism Management, 90, 104485.
30.
LockwoodA., & PyunK. (2020). Developing a scale measuring customers’ servicescape perceptions in upscale hotels. International Journal of Contemporary Hospitality Management, 32(1), 40–59. https://doi.org/10.1108/IJCHM-04-2017-0208
31.
MaE., ChengM., & HsiaoA. (2018). Sentiment analysis—A review and agenda for future research in hospitality contexts. International Journal of Contemporary Hospitality Management, 30(11), 3287–3308. https://doi.org/10.1108/IJCHM-10-2017-0704
32.
MunarA. M., & JacobsenJ. K. S. (2014). Motivations for sharing tourism experiences through social media. Tourism Management, 43, 46–54. https://doi.org/10.1016/j.tourman.2014.01.012
33.
NaldiM. (2019). A review of sentiment computation methods with R packages. ArXiv. https://arxiv.org/abs/1901.08319
34.
NilashiM., AsadiS., Minaei-BidgoliB., Ali AbumallohR., SamadS., GhabbanF., & AhaniA. (2021). Recommendation agents and Information sharing through social media for coronavirus outbreak. Telematics and Informatics, 61, 2–13. https://doi.org/10.1016/j.tele.2021.101597
35.
OliverR. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469. https://doi.org/10.1177/002224378001700405
36.
RanasingheR., DamunupolaA., WijesundaraS., KarunarathnaC., NawarathnaD., GamageS., & IdroosA. A. (2020). Tourism after corona: Impacts of COVID 19 pandemic and way forward for tourism, hotel and mice industry in Sri Lanka. https://doi.org/10.2139/ssrn.3587170
37.
RayA., BalaP. K., & JainR. (2021). Utilizing emotion scores for improving classifier performance for predicting customer’s intended ratings from social media posts. Benchmarking: An International Journal, 28(2), 438–464. https://doi.org/10.1108/BIJ-01-2020-0004
38.
RheeH. T., & YangS. B. B. (2015). Does hotel attribute importance differ by hotel? Focusing on hotel star-classifications and customers’ overall ratings. Computers in Human Behavior, 50, 576–587. https://doi.org/10.1016/j.chb.2015.02.069
39.
RittichainuwatB. N., & ChakrabortyG. (2009). Perceived travel risks regarding terrorism and disease: The case of Thailand. Tourism Management, 30(3), 410–418. https://doi.org/10.1016/j.tourman.2008.08.001
40.
ŠegotaT., & MihaličT. (2018). Elicitation of tourist accommodation demand for counter-seasonal responses: Evidence from the Slovenian Coast. Journal of Destination Marketing and Management, 9, 258–266. https://doi.org/10.1016/j.jdmm.2018.02.002
41.
ShinH., & KangJ. (2020). Reducing perceived health risk to attract hotel customers in the COVID-19 pandemic era: Focused on technology innovation for social distancing and cleanliness. International Journal of Hospitality Management, 91, 102664.
42.
SigalaM. (2020). Tourism and COVID-19: Impacts and implications for advancing and resetting industry and research. Journal of Business Research, 117, 312–321.
43.
SpenceA. M. (1973). Time and communication in economic and social interaction. Quarterly Journal of Economics, 87(4), 651–660.
44.
SpenceM. (2002). Signaling in retrospect and the informational structure of markets. The American Economic Review, 92(3), 434–459.
45.
SrivastavaP. R., SenguptaK., KumarA., BiswasB., & IshizakaA. (2021). Post-epidemic factors influencing customer’s booking intent for a hotel or leisure spot: An empirical study. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-03-2021-0137
46.
STR. (2020). U.S. hotel RevPAR forecasted to drop 50.6% for 2020. https://str.com/press-release/us-hotel-revpar-forecasted-drop-50-point-6-2020
47.
TalwarS., DhirA., KaurP., & MantymakiM. (2020). Why do people purchase from online travel agencies (OTAs)? A consumption values perspective. International Journal of Hospitality Management, 88, 102534.
48.
TokarchukO., BarrJ. C., & CozzioC. (2022), How much is too much? Estimating tourism carrying capacity in urban context using sentiment analysis. Tourism Management, 91, 104522.
49.
ThelwallM., KevanB., GeorgiosP., DiC., & ArvidK. (2010). Sentiment strength detection in short informal text. Journal of the American Society for Information Science and Technology, 61(12), 2544–2558.
50.
UNWTO. (2020). International tourist arrivals could fall by 20–30% in 2020. https://www.unwto.org/news/international-tourism-arrivals-could-fall-in-2020
51.
WangJ., LiY., WuB., & WangY. (2021a). Tourism destination image based on tourism user generated content on internet. Tourism Re-view, 86(1), 125–137. https://doi.org/10.1108/TR-04-2019-0132
52.
WangY., ZhangM., LiS., McLeayF., & GuptaS. (2021b). Corporate responses to the coronavirus crisis and their impact on electronic-word-of-mouth and trust recovery: Evidence from social media. British Journal of Management, 32(4), 1184–1202.
53.
WenZ., HuiminG., & KavanaughR. R. (2005). The impacts of SARS on the consumer behaviour of Chinese domestic tourists. Current Issues in Tourism, 8(1), 22–38. https://doi.org/10.1080/13683500508668203
54.
XuX. (2018). Does traveler satisfaction differ in various travel group compositions? Evidence from online reviews. International Journal of Contemporary Hospitality Management, 30(3), 1663–1685. https://doi.org/10.1108/IJCHM-03-2017-0171
55.
YuJ., & EggerR. (2021). Tourist experiences at overcrowded attractions: A text analytics approach. In WörndlW., KooC., & StienmetzJ. L. (Eds.), Information and communication technologies in tourism 2021 (pp. 231–243). Springer.
56.
YuM., LiZ., YuZ., HeJ., & ZhouJ. (2021). Communication related health crisis on social media: A case of COVID-19 outbreak. Current Issues in Tourism, 24(19), 2699–2705. https://doi.org/10.1080/13683500.2020.1752632
