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http://dx.doi.org/10.13088/jiis.2021.27.3.001

The Effect of Changes in Airbnb Host's Marketing Strategy on Listing Performance in the COVID-19 Pandemic  

Kim, So Yeong (School of Data Science, Kookmin University)
Sim, Ji Hwan (School of Data Science, Kookmin University)
Chung, Yeo Jin (College of Business Administration, Kookmin University)
Publication Information
Journal of Intelligence and Information Systems / v.27, no.3, 2021 , pp. 1-27 More about this Journal
Abstract
The entire tourism industry is being hit hard by the COVID-19 as a global pandemic. Accommodation sharing services such as Airbnb, which have recently expanded due to the spread of the sharing economy, are particularly affected by the pandemic because transactions are made based on trust and communication between consumer and supplier. As the pandemic situation changes individuals' perceptions and behavior of travel, strategies for the recovery of the tourism industry have been discussed. However, since most studies present macro strategies in terms of traditional lodging providers and the government, there is a significant lack of discussion on differentiated pandemic response strategies considering the peculiarity of the sharing economy centered on peer-to-peer transactions. This study discusses the marketing strategy for individual hosts of Airbnb during COVID-19. We empirically analyze the effect of changes in listing descriptions posted by the Airbnb hosts on listing performance after COVID-19 was outbroken. We extract nine aspects described in the listing descriptions using the Attention-Based Aspect Extraction model, which is a deep learning-based aspect extraction method. We model the effect of aspect changes on listing performance after the COVID-19 by observing the frequency of each aspect appeared in the text. In addition, we compare those effects across the types of Airbnb listing. Through this, this study presents an idea for a pandemic crisis response strategy that individual service providers of accommodation sharing services can take depending on the listing type.
Keywords
COVID-19; Sharing economy; Listing description; Text mining; Aspect extraction;
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1 Stylos, N., V. Bellou, A. Andronikidis, and C. A. Vassiliadis, "Linking the dots among destination images, place attachment, and revisit intentions: A study among British and Russian tourists," Tourism Management, Vol.60, (2017), 15~29.   DOI
2 Tew, P. J., Z. Lu, G. Tolomiczenko, and J. Gellatly, "SARS, lessons in strategic planning for hoteliers and destination marketers," International Journal of Contemporary Hospitality Management, Vol.20, No.3(2008).
3 Jin, W., H. H. Ho, and R. K. Srihari, "A novel lexicalized HMM-based learning framework for web opinion mining," Proceedings of the 26th annual international conference on machine learning, (2009), 465~472.
4 Jiang, Y., and B. W. Ritchie, "Disaster collaboration in tourism, Motives, impediments and success factors," Journal of Hospitality and Tourism Management, Vol.31, (2017), 70~82.   DOI
5 Shin, H., and J. Kang, "Reducing perceived health risk to attract hotel customers in the COVID19 pandemic era, Focused on technology innovation for social distancing and cleanliness," International Journal of Hospitality Management, Vol.91, (2020), 102664.   DOI
6 He, W., S. Zha, and L. Li, "Social media competitive analysis and text mining: A case study in the pizza industry," International journal of information management, Vol.33, No.3(2013), 464~472.   DOI
7 Huang, A., C. Makridis, M. Baker, M. Medeiros, and Z. Guo, "Understanding the impact of COVID-19 intervention policies on the hospitality labor market," International Journal of Hospitality Management, Vol.91, (2020), 102660.   DOI
8 Kim, K., O. J. Park, S. Yun, and H. Yun, "What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management," Technological Forecasting and Social Change, Vol.123, (2017), 362~369.   DOI
9 Cahyanto, I., M. Wiblishauser, L. Pennington-Gray, and A. Schroeder, "The dynamics of travel avoidance, The case of Ebola in the US," Tourism Management Perspectives, Vol.20, (2016), 195~203.   DOI
10 Bruno, S., C. Yang, W. Tian, Z. Xie, and Y. Shao, "Exploring the characteristics of tourism industry by analyzing consumer review contents from social media: a case study of Bamako, Mali," Geo-spatial Information Science, Vol.22, No.3(2019), 214~222.   DOI
11 Che, T., Z. Peng, K. H. Lim, and Z. Hua, "Antecedents of consumers' intention to revisit an online group-buying website: A transaction cost perspective," Information & Management, Vol.52, No.5(2015), 588~598.   DOI
12 Cheng, X., S. Fu, and G. J. de Vreede, "A mixed method investigation of sharing economy driven car-hailing services, Online and offline perspectives," International Journal of Information Management, Vol.41, (2018), 57~64.   DOI
13 Lutz, C., and G. Newlands, "Consumer segmentation within the sharing economy, The case of Airbnb," Journal of Business Research, Vol. 88, (2018), 187~196.   DOI
14 Kim, S. B., D. Y. Kim, and K. Wise, "The effect of searching and surfing on recognition of destination images on Facebook pages," Computers in Human Behavior, Vol.30, (2014), 813~823.   DOI
15 Leggat, P. A., L. H. Brown, P. Aitken, and R. Speare, "Level of concern and precaution taking among Australians regarding travel during pandemic (H1N1) 2009, results from the 2009 Queensland Social Survey," Journal of travel medicine, Vol.17, No.5(2010), 291~295.   DOI
16 Lin, W. Y., X. Zhang, H. Song, and K. Omori, "Health information seeking in the Web 2.0 age, Trust in social media, uncertainty reduction, and self-disclosure," Computers in Human Behavior, Vol.56, (2016), 289~294.   DOI
17 Mimno, D., H. M. Wallach, E. Talley, M. Leenders, and A. McCallum, "Optimizing semantic coherence in topic models," Proceedings of the 2011 conference on empirical methods in natural language processing, (2011), 262~272.
18 Fishbein, M., J. Jaccard, A. R. Davidson, I. Ajzen, and B. Loken, "Predicting and understanding family planning behaviors," Understanding attitudes and predicting social behavior, Prentice Hall, New Jersey, 1980.
19 Turban, E., N. Bolloju, and T. P. Liang, "Enterprise social networking: Opportunities, adoption, and risk mitigation," Journal of Organizational Computing and Electronic Commerce, Vol.21, No.3(2011), 202~220.   DOI
20 Chuo, H. Y., "Theme park visitors' responses to the SARS outbreak in Taiwan," Advances in Hospitality and Leisure, Vol.3, (2007), 87~104.   DOI
21 He, R., W. S. Lee, H. T. Ng, and D. Dahlmeier, "An unsupervised neural attention model for aspect extraction," Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1, Long Papers), Vol.1, (2017), 388~397.
22 Ilhan, A., "The challenges of the sharing economy users and the impacts of pandemic (COVID 19)," Economic and Social Development, Book of Proceedings, (2020), 185~192.
23 Kim, J., and J. C. Lee, "Effects of COVID-19 on preferences for private dining facilities in restaurants," Journal of Hospitality and Tourism Management, Vol.45, (2020), 67~70.   DOI
24 Lashley, C., and A. Morrison, In search of hospitality, Routledge, London, 2013.
25 Mimno, D., and A. McCallum, "Topic models conditioned on arbitrary features with Dirichlet-multinomial regression," UAI, Vol. 24, (2008), 411~418.
26 Neuburger, L., and R. Egger, "Travel risk perception and travel behaviour during the COVID-19 pandemic 2020, a case study of the DACH region," Current Issues in Tourism, Vol.24, No.7(2021), 1003~1016.   DOI
27 Ooms, W., J. Bell, and R. A. W. Kok, "Use of social media in inbound open innovation: Building capabilities for absorptive capacity," Creativity and Innovation Management, Vol.24, No.1(2015), 136~150.   DOI
28 Ye, Q., R. Law, B. Gu, and W. Chen, "The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings," Computers in Human behavior, Vol.27, No.2 (2011), 634~639.   DOI
29 UNWTO, World Tourism Barometer, World Tourism Organization, Vol.18, No.2(2020).
30 Wang, W., S. J. Pan, D. Dahlmeier, and X. Xiao, "Recursive neural conditional random fields for aspect-based sentiment analysis," arXiv preprint arXiv,1603.06679, (2016).
31 Zenker, S., and F. Kock, "The coronavirus pandemic -A critical discussion of a tourism research agenda," Tourism management, Vol.81, (2020), 104164.   DOI
32 Wilson, A., V. A. Zeithaml, M. J. Bitner, and D. D. Gremler, Services marketing: Integrating customer focus across the firm, McGraw Hill, New York, 2012.
33 Chang, J. R., M. Y. Chen, L. S. Chen, and S. C. Tseng, "Why customers don't revisit in tourism and hospitality industry?," IEEE Access, Vol.7, (2019), 146588~146606.   DOI
34 Poria, S., E. Cambria, and A. Gelbukh, "Aspect extraction for opinion mining with a deep convolutional neural network," Knowledge-Based Systems, Vol.108, (2016), 42~49.   DOI
35 Slattery, P., "Finding the hospitality industry," Journal of Hospitality, Leisure, Sport and Tourism Education, Vol.1, No.1(2002), 19~28.   DOI
36 Tan, A. H., "Text mining: The state of the art and the challenges," Proceedings of the pakdd 1999 workshop on knowledge discovery from advanced databases, Vol.8, (1999), 65~70.
37 UNISDR, Terminology on Disaster Risk Reduction, United Nations, Geneva, (2009).
38 Zhang, L., Q. Yan, and L. Zhang, "A text analytics framework for understanding the relationships among host self-description, trust perception and purchase behavior on Airbnb," Decision Support Systems, Vol.133, (2020), 113288.   DOI
39 Alan, C. B., S. So, and L. Sin, "Crisis management and recovery, how restaurants in Hong Kong responded to SARS," International Journal of Hospitality Management, Vol.25, No.1(2006), 3~11.   DOI
40 Alamanda, D. T., A. Ramdhani, I. Kania, W. Susilawati, and E. S. Hadi, "Sentiment analysis using text mining of Indonesia tourism reviews via social media," International Journal of Humanities, Arts and Social Sciences, Vol.5, No.2(2019), 43~53.   DOI
41 Al-Saggaf, Y., and P. Simmons, "Social media in Saudi Arabia: Exploring its use during two natural disasters," Technological Forecasting and Social Change, Vol.95, (2015), 3~15.   DOI
42 Bjorkelund, E., T. H. Burnett, and K. Norvag, "A study of opinion mining and visualization of hotel reviews," Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services, (2012), 229~238.
43 Blake, A., and M. T. Sinclair, "Tourism crisis management, US response to September 11," Annals of Tourism Research, Vol.30, No.4(2003), 813~832.   DOI
44 Paek, H. J., T. Hove, H. J. Jeong, and M. Kim, "Peer or expert? The persuasive impact of YouTube public service announcement producers," International Journal of Advertising, Vol.30, No.1(2011), 161~188.   DOI
45 Blei, D. M., A. Y. Ng, and M. I. Jordan, "Latent dirichlet allocation," the Journal of machine Learning research, Vol.3, (2003), 993~1022.
46 Liu, C. H. S., and T. Lee, "Service quality and price perception of service: Influence on word-of-mouth and revisit intention," Journal of Air Transport Management, Vol.52, (2016), 42~54.   DOI
47 Nabity-Grover, T., C. M. K. Cheung, and J. B. Thatcher, "Inside out and outside in, How the COVID-19 pandemic affects self-disclosure on social media," International Journal of Information Management, Vol.55, (2020), 102188.   DOI
48 Reisinger, Y., and F. Mavondo, "Travel anxiety and intentions to travel internationally, Implications of travel risk perception," Journal of travel research, Vol.43, No.3(2005), 212~225.   DOI
49 Nieto Garcia, M., P. A. Munoz-Gallego, G. Viglia, and O. Gonzalez-Benito, "Be social! The impact of self-presentation on peer-to-peer accommodation revenue," Journal of Travel Research, Vol.59, No.7(2020), 1268~1281.   DOI
50 Novelli, M., L. G. Burgess, A. Jones, and B. W. Ritchie, "'No Ebola... still doomed'-The Ebola-induced tourism crisis," Annals of Tourism Research, Vol.70, (2018), 76~87.   DOI
51 Pavlatos, O., H. Kostakis, and D. Digkas, "Crisis management in the Greek hotel industry in response to COVID-19 pandemic," Anatolia, Vol.32, No.1(2021), 80~92.   DOI
52 Richardson, L., "Performing the sharing economy," Geoforum, Vol.67, (2015), 121~129.   DOI
53 Said, C., Window into Airbnb's hidden impact on S.F. - San Francisco Chronicle, 2014. Available at http://www.sfchronicle.com/business/item/Window-into-Airbnb-s-hidden-impact-on-SF-30110.php.
54 Braun-LaTour, K. A., M. J. Grinley, and E. F. Loftus, "Tourist memory distortion," Journal of Travel Research, Vol.44, No.4(2006), 360~367.   DOI
55 Slevitch, L., and A. Sharma, "Management of perceived risk in the context of destination choice," International Journal of Hospitality & Tourism Administration, Vol.9, No.1 (2008), 85~103.   DOI
56 Roberts, M. E., B. M. Stewart, and E. M. Airoldi, "A model of text for experimentation in the social sciences," Journal of the American Statistical Association, Vol.111, No.515(2016), 988~1003.   DOI