Yıl 2024,
Cilt: 12 Sayı: 1, 62 - 92, 29.03.2024
Karan Mehta
,
Chetan Panse
Kaynakça
- Adam, M., Croitor, E., Werner, D., Benlian, A., & Wiener, M. (2022). Input control and its signalling effects for complementors’ intention to join digital platforms. Information Systems Journal, 33(3), 437-466. https://doi.org/10.1111/isj.12408
- Airbnb. (2022, August 27). Search Query. Retrieved from Airbnb, https://www.airbnb.co.in/s/Sikkim/homes?tab_id=home_tab&refinement_paths%5B%5D=%2Fhomes&flexible_trip_lengths%5B%5D=one_week&query=Sikkim&place_id=ChIJ--oFWGql5jkRBFqbw1e4xKQ&date_picker_type=calendar&source=structured_search_input_header&search_type=auto
- Alhojailan, M. I., & Ibrahim, M. (2012). Thematic analysis: A critical review of its process and evaluation. WEI International European Academic Conference Proceedings, 1(2011), 8–21.
- Ali, I. (2020). A study on impact of Covid-19 on Indian economy. International Research Journal of Modernization in Engineering, 2(7), 279-283.
- Amaro, S., & Duarte, P. (2013). Online travel purchasing: A literature review. Journal of Travel and Tourism Marketing, 30(8), 755–785. https://doi.org/10.1080/10548408.2013.835227
- Andreu, L., Bigne, E., Amaro, S., & Palomo, J. (2020). Airbnb research: an analysis in tourism and hospitality journals. International Journal of Culture, Tourism, and Hospitality Research, 14(1), 2–20. https://doi.org/10.1108/IJCTHR-06-2019-0113
- Bazeley, P. (2002). The evolution of a project involving an integrated analysis of structured qualitative and quantitative data: From N3 to NVivo. International Journal of Social Research Methodology, 5(3), 229–243. https://doi.org/10.1080/13645570210146285
- Berkwits, M., & Inui, T. S. (1998). Making use of qualitative techniques - from research to practice. Journal of General Internal Medicine, 13(3), 195–199.
- Bommer, W.H., Rana, S., & Milevoj, E. (2022). A meta-analysis of eWallet adoption using the UTAUT model. International Journal of Bank Marketing, 40(4), 791-819. https://doi.org/10.1108/IJBM-06-2021-0258
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Applied Qualitative Research in Psychology, 3(2), 77-101. 10.1191/1478088706qp063oa
- Chang, G., & Caneday, L. (2011). Web-based GIS in tourism information search: Perceptions, tasks, and trip attributes. Tourism Management, 32(6), 1435–1437. https://doi.org/10.1016/j.tourman.2011.01.006
- Cheng, L., Guo, R., Candan, K., & Liu, H. (2022). Effects of multi-aspect online reviews with unobserved confounders: estimation and implication. In Proceedings of the International AAAI Conference on Web and Social Media, 16, 67-78.
- Cheng, M., & Jin, X. (2019). What do Airbnb users care about? An analysis of online review comments. International Journal of Hospitality Management, 76, 58–70. https://doi.org/10.1016/j.ijhm.2018.04.004
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
- Del Chiappa, G., Pung, J. M., Atzeni, M., & Sini, L. (2021). What prevents consumers that are aware of Airbnb from using the platform? A mixed methods approach. International Journal of Hospitality Management, 93, 102775. https://doi.org/10.1016/j.ijhm.2020.102775
- Dey, B., Mathew, J., & Chee-hua, C. (2020). Influence of destination attractiveness factors and travel motivations on rural homestay choice: the moderating role of need for uniqueness. International Journal of Culture, Tourism and Hospitality Research, 14(4), 639–666. https://doi.org/10.1108/IJCTHR-08-2019-0138
- Ding, K., Choo, W. C., Ng, K. Y., & Ng, S. I. (2020). Employing structural topic modelling to explore perceived service quality attributes in Airbnb accommodation. International Journal of Hospitality Management, 91(March), 102676. https://doi.org/10.1016/j.ijhm.2020.102676
- Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y
- El-Masri, M., & Tarhini, A. (2017). Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Educational Technology Research and Development, 65(3), 743–763. https://doi.org/10.1007/s11423-016-9508-8
- Farhadloo, M., & Rolland, E. (2016). Fundamentals of sentiment analysis and its applications. In W. Pedrycz & S.M. Chen (Eds), Sentiment Analysis and Ontology Engineering. Studies in Computational Intelligence, 639(pp. 1–24). Springer, Cham. https://doi.org/10.1007/978-3-319-30319-2_1
- Freire de Mello, L., & de Paula, S. A. (2020). Mass market and the rise of consumption. In W. Leal Filho, A. Azul, L. Brandli, P. Özuyar, & T. Wall (eds), Responsible Consumption and Production. Encyclopedia of the UN Sustainable Development Goals (pp. 453–462). Springer, Cham. https://doi.org/10.1007/978-3-319-95726-5_49
- Fu, Y., Liu, G., Teng, M., & Aggarwal, C. (2017). Unsupervised P2P rental recommendations via integer programming. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Part F1296, 165–173. https://doi.org/10.1145/3097983.3098044
- Gunter, L., Zhu, J., & Murphy, S. A. (2011). Variable selection for qualitative interactions. Statistical Methodology, 8(1), 42–55. https://doi.org/10.1016/j.stamet.2009.05.003
- Guttentag, D. (2016). Why tourists choose Airbnb: A motivation-based segmentation study underpinned by innovation concepts. Doctoral Dissertation, University of Waterloo, Ontario, Canada.
- Guttentag, D. A., & Smith, S. L. J. (2017). Assessing Airbnb as a disruptive innovation relative to hotels substitution and comparative performance expectations. International Journal of Hospitality Management, 64, 1–10. https://doi.org/10.1016/j.ijhm.2017.02.003
- Guttentag, D., Smith, S., Potwarka, L., & Havitz, M. (2018). Why tourists choose Airbnb: A motivation-based segmentation study. Journal of Travel Research, 57(3), 342–359. https://doi.org/10.1177/0047287517696980
- Han, H., Lho, L. H., Raposo, A., Radic, A., & Ngah, A. H. (2021). Halal food performance and its influence on patron retention process at tourism destination. International journal of environmental research and public health, 18(6), 3034. https://doi.org/10.3390/ijerph18063034
- Hao, F., Qiu, R. T. R., Park, J., & Chon, K. (2022). The myth of contactless hospitality service: customers’ willingness to pay. Journal of Hospitality & Tourism Research, 10963480221081781. https://doi.org/10.1177/10963480221081781
- Haridasan, A. C., & Fernando, A. G. (2018). Online or in-store: unravelling consumer’s channel choice motives. Journal of Research in Interactive Marketing, 12(2), 215–230. https://doi.org/10.1108/JRIM-07-2017-0060
- Hasan, M. N. U., & Stannard, C. R. (2023). Exploring online consumer reviews of wearable technology: the owlet smart sock. Research Journal of Textile and Apparel, 27(2), 157-173. https://doi.org/10.1108/RJTA-08-2021-0103
- Herrero, Á., San Martín, H., & Garcia-De los Salmones, M. del M. (2017). Explaining the adoption of social networks sites for sharing user-generated content: A revision of the UTAUT2. Computers in Human Behavior, 71, 209–217. https://doi.org/10.1016/j.chb.2017.02.007
- Ismail, M. N. I., Hanafiah, M. H., Hemdi, M. A., Sumarjan, N., & Azdel, A. A. (2020). Determinants of customer acceptance and usage of mobile hotel reservation apps (MHRA): an exploratory factor analysis. Journal of Tourism, Hospitality & Culinary Arts (JTHCA), 12(1), 1-17.
- Jakkaew, P., & Hemrungrote, S. (2017). The use of UTAUT2 model for understanding student perceptions using Google Classroom: A case study of Introduction to Information Technology course. In 2nd Joint International Conference on Digital Arts, Media and Technology 2017: Digital Economy for Sustainable Growth, ICDAMT 2017, 205–209. https://doi.org/10.1109/ICDAMT.2017.7904962
- Ju, Y., Back, K. J., Choi, Y., & Lee, J. S. (2019). Exploring Airbnb service quality attributes and their asymmetric effects on customer satisfaction. International Journal of Hospitality Management, 77(July), 342–352. https://doi.org/10.1016/j.ijhm.2018.07.014
- Kam, K., So, F., Oh, H., & Min, S. (2018). Motivations and constraints of Airbnb consumers: Findings from a mixed-methods approach. Tourism Management, 67, 224–236. https://doi.org/10.1016/j.tourman.2018.01.009
- Kamboj, S., & Joshi, R. (2021). Examining the factors influencing smartphone apps use at tourism destinations: a UTAUT model perspective. International Journal of Tourism Cities, 7(1), 135-157. https://doi.org/10.1108/IJTC-05-2020-0094
- Karobliene, V., & Pilinkiene, V. (2021). The sharing economy in the framework of sustainable development goals: Case of European union countries. Sustainability (Switzerland), 13(15). https://doi.org/10.3390/su13158312
- Kharde, V., & Sonawane, S. S. (2016). Sentiment analysis of Twitter data: a survey of techniques. International Journal of Computer Applications, 139(11), 5–15. https://doi.org/10.5120/ijca2016908625
- Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223. https://doi.org/10.1287/isre.13.2.205.83
- Laurence, B. (2016). Análise de conteúdo: edição revista e ampliada. São Paulo: Edições.
- Lee, C.K.H., Tse, Y.K., Zhang, M., & Wang, Y. (2023). What have hosts overlooked for improving stay experience in accommodation-sharing? Empirical evidence from Airbnb customer reviews. International Journal of Contemporary Hospitality Management, 35(2), 765-784. https://doi.org/10.1108/IJCHM-12-2021-1544
- Li, C., & Fang, Y. (2022). The more we get together, the more we can save? A transaction cost perspective. International Journal of Information Management, 62(151), 102434. https://doi.org/10.1016/j.ijinfomgt.2021.102434
- Li, G., Law, R., Quan, H., Rong, J., & Roy, X. (2015). Identifying emerging hotel preferences using emerging pattern mining technique. Tourism Management, 46, 311–321. https://doi.org/10.1016/j.tourman.2014.06.015
- Li, Jing, Hudson, S., Kam, K., & So, F. (2019). Exploring the customer experience with Airbnb. International Journal of Culture, Tourism and Hospitality Research, 13(4), 410–429. https://doi.org/10.1108/IJCTHR-10-2018-0148
- Li, J., Moreno, A., & Zhang, D. (2015). Pros vs joes: agent pricing behavior in the sharing economy. Ross School of Business Paper No. 1298. https://doi.org/10.2139/ssrn.2708279
- Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS quarterly, 31(4), 705–737.
- Luo, Y., & Tang, R. (Liang). (2019). Understanding hidden dimensions in textual reviews on Airbnb: An application of modified latent aspect rating analysis (LARA). International Journal of Hospitality Management, 80(July 2018), 144–154. https://doi.org/10.1016/j.ijhm.2019.02.008
- Mao, Z., & Lyu, J. (2017). Why travelers use Airbnb again?: An integrative approach to understanding travelers’ repurchase intention. International Journal of Contemporary Hospitality Management, 29(9), 2464–2482. https://doi.org/10.1108/IJCHM-08-2016-0439
- Megadewandanu, S., Suyoto, & Pranowo. (2017). Exploring mobile wallet adoption in Indonesia using UTAUT2: An approach from consumer perspective. In Proceedings - 2016 2nd International Conference on Science and Technology-Computer, ICST 2016, 11–16. https://doi.org/10.1109/ICSTC.2016.7877340
- Mody, M. A., Suess, C., & Lehto, X. (2017). The accommodation experiencescape: a comparative assessment of hotels and Airbnb. International Journal of Contemporary Hospitality Management, 29(9), 2377–2404. https://doi.org/10.1108/IJCHM-09-2016-0501
- Nikou, S., & Bouwman, H. (2014). Ubiquitous use of mobile social network services. Telematics and Informatics, 31(3), 422–433. https://doi.org/10.1016/j.tele.2013.11.002
- Noncheva, V., Mendes, A. B., & Silva, E. (2009). An approach to variable aggregation in efficiency analysis. International Book Series" Information Science and Computing", 97-104.
- Ohlan, R. (2018). Role of information technology in hotel industry. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 3(2), 277–281.
- Piramanayagam, S., & Kumar, M. P. S. (2020). Determinants of customer’s dissatisfaction: A content analysis of negative online customer reviews on budget segment hotels in India. African Journal of Hospitality, Tourism and Leisure, 9(1), 1–9.
- Polson, N. G., & Sokolov, V. (2017). Deep learning: A Bayesian perspective. Bayesian Analysis, 12(4), 1275–1304. https://doi.org/10.1214/17-BA1082
- Qaddoori, Q. Q., & Breesam, H.K. (2023). Using the pivot pair-wise relative criteria importance assessment (PIPRECIA) method to determine the relative weight of the factors affecting construction site safety performance. International Journal of Safety and Security Engineering, 13(1), 59-68. https://doi.org/10.18280/ijsse.130107
- Quattrone, G., Kusek, N., & Capra, L. (2022). A global-scale analysis of the sharing economy model – an AirBnB case study. EPJ Data Sci., 11(1), 36. https://doi.org/10.1140/epjds/s13688-022-00349-3
- Rabiei-Dastjerdi, H., McArdle, G., & Hynes, W. (2022). Which came first, the gentrification or the Airbnb? Identifying spatial patterns of neighbourhood change using Airbnb data. Habitat International, 125(July), 102582. https://doi.org/10.1016/j.habitatint.2022.102582
- Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2016). Adoption of online public grievance redressal system in India: Toward developing a unified view. Computers in Human Behavior, 59, 265–282. https://doi.org/10.1016/j.chb.2016.02.019
- Ribeiro, M. A., Gursoy, D., & Chi, O. (2022). Customer acceptance of autonomous vehicles in travel and tourism. Journal of Travel Research, 61(3), 620-636. https://doi.org/10.1177/0047287521993578
- Ritchie, B. W., & Jiang, Y. (2019). A review of research on tourism risk, crisis and disaster management: Launching the annals of tourism research curated collection on tourism risk, crisis and disaster management. Annals of Tourism Research, 79(October), 102812. https://doi.org/10.1016/j.annals.2019.102812
- Sainaghi, R. (2020). The current state of academic research into peer-to-peer accommodation platforms. International Journal of Hospitality Management, 89(March), 102555. https://doi.org/10.1016/j.ijhm.2020.102555
- Sánchez-franco, M. J., & Alonso-dos-santos, M. (2021). Exploring gender-based influences on key features of Airbnb accommodations Exploring gender-based influences on key features of Airbnb accommodations. Economic Research-Ekonomska Istraživanja, 34(1), 2484–2505. https://doi.org/10.1080/1331677X.2020.1831943
- Sari, F. O., & Nazli, M. (2021). Exploring the effects of “excessive tourism growth” on public health and ecosystem. Journal of Hospitality and Tourism Insights, 4(1), 1–17. https://doi.org/10.1108/JHTI-04-2020-0060
- Satama, S. (2014). Consumer Adoption of Access-Based Consumption Services - Case AirBnB. Master's Thesis, Department of Marketing, Aalto University, Finland. http://urn.fi/URN:NBN:fi:aalto-201501221450
- Saurkar, A. V., Pathare, K. G., & Gode, S. A. (2018). An overview on web scraping techniques and tools. International Journal on Future Revolution in Computer Science & Communication Engineering, 4(4), 363–367. http://www.ijfrcsce.org/index.php/ijfrcsce/article/view/1529
- Septia Irawan, A., Shahin, B., Wangeshi Njuguna, D., Nellamkuzhi, N. J., Thiện, B. Q., Mahrouseh, N., & Varga, O. (2022). Analysis of content, social networks, and sentiment of front-of-pack nutrition labeling in the European Union on Twitter. Frontiers in Nutrition, 9(April). https://doi.org/10.3389/fnut.2022.846730
- Sharma, M., Antony, R., Sehrawat, R., Contreras, A., & Daim, T. U. (2022). Technology in society exploring post-adoption behaviors of e-service users: Evidence from the hospitality sector/ online travel services. Technology in Society, 68(July 2021), 101781. https://doi.org/10.1016/j.techsoc.2021.101781
- So, K. K. F., Kim, H., & Min, S. (2022). Creating customer value in the sharing economy: an investigation of Airbnb users and their tripographic characteristics. International Journal of Contemporary Hospitality Management, 34(1), 23–45. https://doi.org/10.1108/IJCHM-12-2020-1500
- So, K. K. F., Oh, H., & Min, S. (2018). Motivations and constraints of Airbnb consumers: Findings from a mixed-methods approach. Tourism Management, 67, 224–236. https://doi.org/10.1016/j.tourman.2018.01.009
- Tamilmani, K., Rana, N. P., Nunkoo, R., Raghavan, V., & Dwivedi, Y. K. (2022). Indian Travellers’ Adoption of Airbnb Platform. Information Systems Frontiers, 24(1), 77–96. https://doi.org/10.1007/s10796-020-10060-1
- Tarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017). Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: a structural equation modeling of an extended technology acceptance model. Interactive Learning Environments, 25(3), 306–328. https://doi.org/10.1080/10494820.2015.1122635
- Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: a test of competing models. Information Systems Research, 6(2), 144–176. https://doi.org/10.1287/isre.6.2.144
- Teh, P. L., Low, Y. C., & Ooi, P. B. (2020, November). Viewing Airbnb from Twitter: factors associated with users' utilization. In Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services (pp. 274-281). https://doi.org/10.1145/3428757.3429112
- Teng, Y. M., Wu, K. S., & Liu, H. H. (2015). Integrating Altruism and the Theory of Planned Behavior to Predict Patronage Intention of a Green Hotel. Journal of Hospitality and Tourism Research, 39(3), 299–315. https://doi.org/10.1177/1096348012471383
- Thi, T., Doan, M., Pereira, L. N., & Silva, J. A. (2023). The role of superhost badge in Airbnb hosts’ continuance intention. Anatolia, https://doi.org/10.1080/13032917.2023.2186903
- Tussyadiah, I. P., & Pesonen, J. (2016). Impacts of Peer-to-Peer Accommodation Use on Travel Patterns. Journal of Travel Research, 55(8), 1022–1040. https://doi.org/10.1177/0047287515608505
- Tussyadiah, I. P., & Pesonen, J. (2018). Drivers and barriers of peer-to-peer accommodation stay–an exploratory study with American and Finnish travellers. Current Issues in Tourism, 21(6), 703–720. https://doi.org/10.1080/13683500.2016.1141180
- Uprichard, E. (2009). Introducing cluster analysis: what can it teach us about the case?. In C. C. Ragin Charles & D. Byrne (Eds), The SAGE Handbook of Case-Based Methods (pp. 132–147). Sage Publications.
- Vaismoradi, M., Turunen, H., & Bondas, T. (2013). Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nursing and Health Sciences, 15(3), 398–405. https://doi.org/10.1111/nhs.12048
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. https://doi.org/10.2307/30036540
- Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly: Management Information Systems, 36(1), 157–178. https://doi.org/10.2307/41410412
- von Hoffen, M., Hagge, M., Betzing, J. H., & Chasin, F. (2018). Leveraging social media to gain insights into service delivery: a study on Airbnb. Information Systems and E-Business Management, 16(2), 247–269. https://doi.org/10.1007/s10257-017-0358-7
- Walters, T. (2016). Using thematic analysis in tourism research. Tourism Analysis, 21(1), 107–116. https://doi.org/10.3727/108354216X14537459509017
- Wang, C. (Renee), & Jeong, M. (2018). What makes you choose Airbnb again? An examination of users’ perceptions toward the website and their stay. International Journal of Hospitality Management, 74(March), 162–170. https://doi.org/10.1016/j.ijhm.2018.04.006
- Xi, Y., Ma, C., Yang, Q., & Jiang, Y. (2022). A cross-cultural analysis of tourists’ perceptions of Airbnb attributes. International Journal of Hospitality & Tourism Administration, 23(4), 754–787. https://doi.org/10.1080/15256480.2020.1862014
- Yang, S., & Ahn, S. (2016). Impact of motivation for participation in the sharing economy and perceived security on attitude and loyalty toward Airbnb. International Information Institute (Tokyo). Information, 19(12), 5745–5750.
- Yi, B., Shi, D., Shi, F., & Zhang, L. (2021). Do the flipped impacts of hotels matter to the popularity of Airbnb?. International Journal of Contemporary Hospitality Management, 33(6), 2239–2263. https://doi.org/10.1108/IJCHM-06-2020-0582
- Yi, J., Yuan, G., & Yoo, C. (2020). The effect of the perceived risk on the adoption of the sharing economy in the tourism industry: The case of Airbnb. Information Processing and Management, 57(1), 102108. https://doi.org/10.1016/j.ipm.2019.102108
- Zervas, G., Proserpio, D., & Byers, J. W. (2017). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Journal of Marketing Research, 54(5), 687–705. https://doi.org/10.1509/jmr.15.0204
- Zhang, Z., Chen, R. J. C., Han, L. D., & Yang, L. (2017). Key factors affecting the price of Airbnb listings: A geographically weighted approach. Sustainability (Switzerland), 9(9), 1–13. https://doi.org/10.3390/su9091635
- Zhang, Z., & Fu, R. J. C. (2020). Accommodation experience in the sharing economy: A comparative study of Airbnb online reviews. Sustainability, 12(24), 10500. https://doi.org/10.3390/su122410500
Symmetrical Adoption Pattern of the Digital Sharing Economy
Yıl 2024,
Cilt: 12 Sayı: 1, 62 - 92, 29.03.2024
Karan Mehta
,
Chetan Panse
Öz
Listing spare homes as tourist accommodations on applications like Airbnb has boosted consumers’ adoption of the digital sharing economy (DSE). This research paper aims to develop a variable selection methodology for factors influencing consumers’ adoption intention of DSE applications like Airbnb and UBER. The symmetrical adoption pattern (SAP) will assist industry practitioners in designing an accurate investment pattern for the available resources. The research examines feedback from travellers regarding utilized services to develop SAP. The authors adopt NCapture as a data extraction tool and NVivo 12 as a data analysis tool to develop SAP as a variable selection methodology. Sentiment, thematic, and cluster analysis methods of qualitative analysis were employed to extract 19 distinct variables of SAP out of available data and adapt it into the six constructs of the unified theory of acceptance and use of technology (UTAUT2). By identifying the ideal variable for each construct with SAP, the performed study also aims to broaden the understanding of theories linked to the UTAUT2 model.
Kaynakça
- Adam, M., Croitor, E., Werner, D., Benlian, A., & Wiener, M. (2022). Input control and its signalling effects for complementors’ intention to join digital platforms. Information Systems Journal, 33(3), 437-466. https://doi.org/10.1111/isj.12408
- Airbnb. (2022, August 27). Search Query. Retrieved from Airbnb, https://www.airbnb.co.in/s/Sikkim/homes?tab_id=home_tab&refinement_paths%5B%5D=%2Fhomes&flexible_trip_lengths%5B%5D=one_week&query=Sikkim&place_id=ChIJ--oFWGql5jkRBFqbw1e4xKQ&date_picker_type=calendar&source=structured_search_input_header&search_type=auto
- Alhojailan, M. I., & Ibrahim, M. (2012). Thematic analysis: A critical review of its process and evaluation. WEI International European Academic Conference Proceedings, 1(2011), 8–21.
- Ali, I. (2020). A study on impact of Covid-19 on Indian economy. International Research Journal of Modernization in Engineering, 2(7), 279-283.
- Amaro, S., & Duarte, P. (2013). Online travel purchasing: A literature review. Journal of Travel and Tourism Marketing, 30(8), 755–785. https://doi.org/10.1080/10548408.2013.835227
- Andreu, L., Bigne, E., Amaro, S., & Palomo, J. (2020). Airbnb research: an analysis in tourism and hospitality journals. International Journal of Culture, Tourism, and Hospitality Research, 14(1), 2–20. https://doi.org/10.1108/IJCTHR-06-2019-0113
- Bazeley, P. (2002). The evolution of a project involving an integrated analysis of structured qualitative and quantitative data: From N3 to NVivo. International Journal of Social Research Methodology, 5(3), 229–243. https://doi.org/10.1080/13645570210146285
- Berkwits, M., & Inui, T. S. (1998). Making use of qualitative techniques - from research to practice. Journal of General Internal Medicine, 13(3), 195–199.
- Bommer, W.H., Rana, S., & Milevoj, E. (2022). A meta-analysis of eWallet adoption using the UTAUT model. International Journal of Bank Marketing, 40(4), 791-819. https://doi.org/10.1108/IJBM-06-2021-0258
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Applied Qualitative Research in Psychology, 3(2), 77-101. 10.1191/1478088706qp063oa
- Chang, G., & Caneday, L. (2011). Web-based GIS in tourism information search: Perceptions, tasks, and trip attributes. Tourism Management, 32(6), 1435–1437. https://doi.org/10.1016/j.tourman.2011.01.006
- Cheng, L., Guo, R., Candan, K., & Liu, H. (2022). Effects of multi-aspect online reviews with unobserved confounders: estimation and implication. In Proceedings of the International AAAI Conference on Web and Social Media, 16, 67-78.
- Cheng, M., & Jin, X. (2019). What do Airbnb users care about? An analysis of online review comments. International Journal of Hospitality Management, 76, 58–70. https://doi.org/10.1016/j.ijhm.2018.04.004
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
- Del Chiappa, G., Pung, J. M., Atzeni, M., & Sini, L. (2021). What prevents consumers that are aware of Airbnb from using the platform? A mixed methods approach. International Journal of Hospitality Management, 93, 102775. https://doi.org/10.1016/j.ijhm.2020.102775
- Dey, B., Mathew, J., & Chee-hua, C. (2020). Influence of destination attractiveness factors and travel motivations on rural homestay choice: the moderating role of need for uniqueness. International Journal of Culture, Tourism and Hospitality Research, 14(4), 639–666. https://doi.org/10.1108/IJCTHR-08-2019-0138
- Ding, K., Choo, W. C., Ng, K. Y., & Ng, S. I. (2020). Employing structural topic modelling to explore perceived service quality attributes in Airbnb accommodation. International Journal of Hospitality Management, 91(March), 102676. https://doi.org/10.1016/j.ijhm.2020.102676
- Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y
- El-Masri, M., & Tarhini, A. (2017). Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Educational Technology Research and Development, 65(3), 743–763. https://doi.org/10.1007/s11423-016-9508-8
- Farhadloo, M., & Rolland, E. (2016). Fundamentals of sentiment analysis and its applications. In W. Pedrycz & S.M. Chen (Eds), Sentiment Analysis and Ontology Engineering. Studies in Computational Intelligence, 639(pp. 1–24). Springer, Cham. https://doi.org/10.1007/978-3-319-30319-2_1
- Freire de Mello, L., & de Paula, S. A. (2020). Mass market and the rise of consumption. In W. Leal Filho, A. Azul, L. Brandli, P. Özuyar, & T. Wall (eds), Responsible Consumption and Production. Encyclopedia of the UN Sustainable Development Goals (pp. 453–462). Springer, Cham. https://doi.org/10.1007/978-3-319-95726-5_49
- Fu, Y., Liu, G., Teng, M., & Aggarwal, C. (2017). Unsupervised P2P rental recommendations via integer programming. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Part F1296, 165–173. https://doi.org/10.1145/3097983.3098044
- Gunter, L., Zhu, J., & Murphy, S. A. (2011). Variable selection for qualitative interactions. Statistical Methodology, 8(1), 42–55. https://doi.org/10.1016/j.stamet.2009.05.003
- Guttentag, D. (2016). Why tourists choose Airbnb: A motivation-based segmentation study underpinned by innovation concepts. Doctoral Dissertation, University of Waterloo, Ontario, Canada.
- Guttentag, D. A., & Smith, S. L. J. (2017). Assessing Airbnb as a disruptive innovation relative to hotels substitution and comparative performance expectations. International Journal of Hospitality Management, 64, 1–10. https://doi.org/10.1016/j.ijhm.2017.02.003
- Guttentag, D., Smith, S., Potwarka, L., & Havitz, M. (2018). Why tourists choose Airbnb: A motivation-based segmentation study. Journal of Travel Research, 57(3), 342–359. https://doi.org/10.1177/0047287517696980
- Han, H., Lho, L. H., Raposo, A., Radic, A., & Ngah, A. H. (2021). Halal food performance and its influence on patron retention process at tourism destination. International journal of environmental research and public health, 18(6), 3034. https://doi.org/10.3390/ijerph18063034
- Hao, F., Qiu, R. T. R., Park, J., & Chon, K. (2022). The myth of contactless hospitality service: customers’ willingness to pay. Journal of Hospitality & Tourism Research, 10963480221081781. https://doi.org/10.1177/10963480221081781
- Haridasan, A. C., & Fernando, A. G. (2018). Online or in-store: unravelling consumer’s channel choice motives. Journal of Research in Interactive Marketing, 12(2), 215–230. https://doi.org/10.1108/JRIM-07-2017-0060
- Hasan, M. N. U., & Stannard, C. R. (2023). Exploring online consumer reviews of wearable technology: the owlet smart sock. Research Journal of Textile and Apparel, 27(2), 157-173. https://doi.org/10.1108/RJTA-08-2021-0103
- Herrero, Á., San Martín, H., & Garcia-De los Salmones, M. del M. (2017). Explaining the adoption of social networks sites for sharing user-generated content: A revision of the UTAUT2. Computers in Human Behavior, 71, 209–217. https://doi.org/10.1016/j.chb.2017.02.007
- Ismail, M. N. I., Hanafiah, M. H., Hemdi, M. A., Sumarjan, N., & Azdel, A. A. (2020). Determinants of customer acceptance and usage of mobile hotel reservation apps (MHRA): an exploratory factor analysis. Journal of Tourism, Hospitality & Culinary Arts (JTHCA), 12(1), 1-17.
- Jakkaew, P., & Hemrungrote, S. (2017). The use of UTAUT2 model for understanding student perceptions using Google Classroom: A case study of Introduction to Information Technology course. In 2nd Joint International Conference on Digital Arts, Media and Technology 2017: Digital Economy for Sustainable Growth, ICDAMT 2017, 205–209. https://doi.org/10.1109/ICDAMT.2017.7904962
- Ju, Y., Back, K. J., Choi, Y., & Lee, J. S. (2019). Exploring Airbnb service quality attributes and their asymmetric effects on customer satisfaction. International Journal of Hospitality Management, 77(July), 342–352. https://doi.org/10.1016/j.ijhm.2018.07.014
- Kam, K., So, F., Oh, H., & Min, S. (2018). Motivations and constraints of Airbnb consumers: Findings from a mixed-methods approach. Tourism Management, 67, 224–236. https://doi.org/10.1016/j.tourman.2018.01.009
- Kamboj, S., & Joshi, R. (2021). Examining the factors influencing smartphone apps use at tourism destinations: a UTAUT model perspective. International Journal of Tourism Cities, 7(1), 135-157. https://doi.org/10.1108/IJTC-05-2020-0094
- Karobliene, V., & Pilinkiene, V. (2021). The sharing economy in the framework of sustainable development goals: Case of European union countries. Sustainability (Switzerland), 13(15). https://doi.org/10.3390/su13158312
- Kharde, V., & Sonawane, S. S. (2016). Sentiment analysis of Twitter data: a survey of techniques. International Journal of Computer Applications, 139(11), 5–15. https://doi.org/10.5120/ijca2016908625
- Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223. https://doi.org/10.1287/isre.13.2.205.83
- Laurence, B. (2016). Análise de conteúdo: edição revista e ampliada. São Paulo: Edições.
- Lee, C.K.H., Tse, Y.K., Zhang, M., & Wang, Y. (2023). What have hosts overlooked for improving stay experience in accommodation-sharing? Empirical evidence from Airbnb customer reviews. International Journal of Contemporary Hospitality Management, 35(2), 765-784. https://doi.org/10.1108/IJCHM-12-2021-1544
- Li, C., & Fang, Y. (2022). The more we get together, the more we can save? A transaction cost perspective. International Journal of Information Management, 62(151), 102434. https://doi.org/10.1016/j.ijinfomgt.2021.102434
- Li, G., Law, R., Quan, H., Rong, J., & Roy, X. (2015). Identifying emerging hotel preferences using emerging pattern mining technique. Tourism Management, 46, 311–321. https://doi.org/10.1016/j.tourman.2014.06.015
- Li, Jing, Hudson, S., Kam, K., & So, F. (2019). Exploring the customer experience with Airbnb. International Journal of Culture, Tourism and Hospitality Research, 13(4), 410–429. https://doi.org/10.1108/IJCTHR-10-2018-0148
- Li, J., Moreno, A., & Zhang, D. (2015). Pros vs joes: agent pricing behavior in the sharing economy. Ross School of Business Paper No. 1298. https://doi.org/10.2139/ssrn.2708279
- Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS quarterly, 31(4), 705–737.
- Luo, Y., & Tang, R. (Liang). (2019). Understanding hidden dimensions in textual reviews on Airbnb: An application of modified latent aspect rating analysis (LARA). International Journal of Hospitality Management, 80(July 2018), 144–154. https://doi.org/10.1016/j.ijhm.2019.02.008
- Mao, Z., & Lyu, J. (2017). Why travelers use Airbnb again?: An integrative approach to understanding travelers’ repurchase intention. International Journal of Contemporary Hospitality Management, 29(9), 2464–2482. https://doi.org/10.1108/IJCHM-08-2016-0439
- Megadewandanu, S., Suyoto, & Pranowo. (2017). Exploring mobile wallet adoption in Indonesia using UTAUT2: An approach from consumer perspective. In Proceedings - 2016 2nd International Conference on Science and Technology-Computer, ICST 2016, 11–16. https://doi.org/10.1109/ICSTC.2016.7877340
- Mody, M. A., Suess, C., & Lehto, X. (2017). The accommodation experiencescape: a comparative assessment of hotels and Airbnb. International Journal of Contemporary Hospitality Management, 29(9), 2377–2404. https://doi.org/10.1108/IJCHM-09-2016-0501
- Nikou, S., & Bouwman, H. (2014). Ubiquitous use of mobile social network services. Telematics and Informatics, 31(3), 422–433. https://doi.org/10.1016/j.tele.2013.11.002
- Noncheva, V., Mendes, A. B., & Silva, E. (2009). An approach to variable aggregation in efficiency analysis. International Book Series" Information Science and Computing", 97-104.
- Ohlan, R. (2018). Role of information technology in hotel industry. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 3(2), 277–281.
- Piramanayagam, S., & Kumar, M. P. S. (2020). Determinants of customer’s dissatisfaction: A content analysis of negative online customer reviews on budget segment hotels in India. African Journal of Hospitality, Tourism and Leisure, 9(1), 1–9.
- Polson, N. G., & Sokolov, V. (2017). Deep learning: A Bayesian perspective. Bayesian Analysis, 12(4), 1275–1304. https://doi.org/10.1214/17-BA1082
- Qaddoori, Q. Q., & Breesam, H.K. (2023). Using the pivot pair-wise relative criteria importance assessment (PIPRECIA) method to determine the relative weight of the factors affecting construction site safety performance. International Journal of Safety and Security Engineering, 13(1), 59-68. https://doi.org/10.18280/ijsse.130107
- Quattrone, G., Kusek, N., & Capra, L. (2022). A global-scale analysis of the sharing economy model – an AirBnB case study. EPJ Data Sci., 11(1), 36. https://doi.org/10.1140/epjds/s13688-022-00349-3
- Rabiei-Dastjerdi, H., McArdle, G., & Hynes, W. (2022). Which came first, the gentrification or the Airbnb? Identifying spatial patterns of neighbourhood change using Airbnb data. Habitat International, 125(July), 102582. https://doi.org/10.1016/j.habitatint.2022.102582
- Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2016). Adoption of online public grievance redressal system in India: Toward developing a unified view. Computers in Human Behavior, 59, 265–282. https://doi.org/10.1016/j.chb.2016.02.019
- Ribeiro, M. A., Gursoy, D., & Chi, O. (2022). Customer acceptance of autonomous vehicles in travel and tourism. Journal of Travel Research, 61(3), 620-636. https://doi.org/10.1177/0047287521993578
- Ritchie, B. W., & Jiang, Y. (2019). A review of research on tourism risk, crisis and disaster management: Launching the annals of tourism research curated collection on tourism risk, crisis and disaster management. Annals of Tourism Research, 79(October), 102812. https://doi.org/10.1016/j.annals.2019.102812
- Sainaghi, R. (2020). The current state of academic research into peer-to-peer accommodation platforms. International Journal of Hospitality Management, 89(March), 102555. https://doi.org/10.1016/j.ijhm.2020.102555
- Sánchez-franco, M. J., & Alonso-dos-santos, M. (2021). Exploring gender-based influences on key features of Airbnb accommodations Exploring gender-based influences on key features of Airbnb accommodations. Economic Research-Ekonomska Istraživanja, 34(1), 2484–2505. https://doi.org/10.1080/1331677X.2020.1831943
- Sari, F. O., & Nazli, M. (2021). Exploring the effects of “excessive tourism growth” on public health and ecosystem. Journal of Hospitality and Tourism Insights, 4(1), 1–17. https://doi.org/10.1108/JHTI-04-2020-0060
- Satama, S. (2014). Consumer Adoption of Access-Based Consumption Services - Case AirBnB. Master's Thesis, Department of Marketing, Aalto University, Finland. http://urn.fi/URN:NBN:fi:aalto-201501221450
- Saurkar, A. V., Pathare, K. G., & Gode, S. A. (2018). An overview on web scraping techniques and tools. International Journal on Future Revolution in Computer Science & Communication Engineering, 4(4), 363–367. http://www.ijfrcsce.org/index.php/ijfrcsce/article/view/1529
- Septia Irawan, A., Shahin, B., Wangeshi Njuguna, D., Nellamkuzhi, N. J., Thiện, B. Q., Mahrouseh, N., & Varga, O. (2022). Analysis of content, social networks, and sentiment of front-of-pack nutrition labeling in the European Union on Twitter. Frontiers in Nutrition, 9(April). https://doi.org/10.3389/fnut.2022.846730
- Sharma, M., Antony, R., Sehrawat, R., Contreras, A., & Daim, T. U. (2022). Technology in society exploring post-adoption behaviors of e-service users: Evidence from the hospitality sector/ online travel services. Technology in Society, 68(July 2021), 101781. https://doi.org/10.1016/j.techsoc.2021.101781
- So, K. K. F., Kim, H., & Min, S. (2022). Creating customer value in the sharing economy: an investigation of Airbnb users and their tripographic characteristics. International Journal of Contemporary Hospitality Management, 34(1), 23–45. https://doi.org/10.1108/IJCHM-12-2020-1500
- So, K. K. F., Oh, H., & Min, S. (2018). Motivations and constraints of Airbnb consumers: Findings from a mixed-methods approach. Tourism Management, 67, 224–236. https://doi.org/10.1016/j.tourman.2018.01.009
- Tamilmani, K., Rana, N. P., Nunkoo, R., Raghavan, V., & Dwivedi, Y. K. (2022). Indian Travellers’ Adoption of Airbnb Platform. Information Systems Frontiers, 24(1), 77–96. https://doi.org/10.1007/s10796-020-10060-1
- Tarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017). Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: a structural equation modeling of an extended technology acceptance model. Interactive Learning Environments, 25(3), 306–328. https://doi.org/10.1080/10494820.2015.1122635
- Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: a test of competing models. Information Systems Research, 6(2), 144–176. https://doi.org/10.1287/isre.6.2.144
- Teh, P. L., Low, Y. C., & Ooi, P. B. (2020, November). Viewing Airbnb from Twitter: factors associated with users' utilization. In Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services (pp. 274-281). https://doi.org/10.1145/3428757.3429112
- Teng, Y. M., Wu, K. S., & Liu, H. H. (2015). Integrating Altruism and the Theory of Planned Behavior to Predict Patronage Intention of a Green Hotel. Journal of Hospitality and Tourism Research, 39(3), 299–315. https://doi.org/10.1177/1096348012471383
- Thi, T., Doan, M., Pereira, L. N., & Silva, J. A. (2023). The role of superhost badge in Airbnb hosts’ continuance intention. Anatolia, https://doi.org/10.1080/13032917.2023.2186903
- Tussyadiah, I. P., & Pesonen, J. (2016). Impacts of Peer-to-Peer Accommodation Use on Travel Patterns. Journal of Travel Research, 55(8), 1022–1040. https://doi.org/10.1177/0047287515608505
- Tussyadiah, I. P., & Pesonen, J. (2018). Drivers and barriers of peer-to-peer accommodation stay–an exploratory study with American and Finnish travellers. Current Issues in Tourism, 21(6), 703–720. https://doi.org/10.1080/13683500.2016.1141180
- Uprichard, E. (2009). Introducing cluster analysis: what can it teach us about the case?. In C. C. Ragin Charles & D. Byrne (Eds), The SAGE Handbook of Case-Based Methods (pp. 132–147). Sage Publications.
- Vaismoradi, M., Turunen, H., & Bondas, T. (2013). Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nursing and Health Sciences, 15(3), 398–405. https://doi.org/10.1111/nhs.12048
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. https://doi.org/10.2307/30036540
- Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly: Management Information Systems, 36(1), 157–178. https://doi.org/10.2307/41410412
- von Hoffen, M., Hagge, M., Betzing, J. H., & Chasin, F. (2018). Leveraging social media to gain insights into service delivery: a study on Airbnb. Information Systems and E-Business Management, 16(2), 247–269. https://doi.org/10.1007/s10257-017-0358-7
- Walters, T. (2016). Using thematic analysis in tourism research. Tourism Analysis, 21(1), 107–116. https://doi.org/10.3727/108354216X14537459509017
- Wang, C. (Renee), & Jeong, M. (2018). What makes you choose Airbnb again? An examination of users’ perceptions toward the website and their stay. International Journal of Hospitality Management, 74(March), 162–170. https://doi.org/10.1016/j.ijhm.2018.04.006
- Xi, Y., Ma, C., Yang, Q., & Jiang, Y. (2022). A cross-cultural analysis of tourists’ perceptions of Airbnb attributes. International Journal of Hospitality & Tourism Administration, 23(4), 754–787. https://doi.org/10.1080/15256480.2020.1862014
- Yang, S., & Ahn, S. (2016). Impact of motivation for participation in the sharing economy and perceived security on attitude and loyalty toward Airbnb. International Information Institute (Tokyo). Information, 19(12), 5745–5750.
- Yi, B., Shi, D., Shi, F., & Zhang, L. (2021). Do the flipped impacts of hotels matter to the popularity of Airbnb?. International Journal of Contemporary Hospitality Management, 33(6), 2239–2263. https://doi.org/10.1108/IJCHM-06-2020-0582
- Yi, J., Yuan, G., & Yoo, C. (2020). The effect of the perceived risk on the adoption of the sharing economy in the tourism industry: The case of Airbnb. Information Processing and Management, 57(1), 102108. https://doi.org/10.1016/j.ipm.2019.102108
- Zervas, G., Proserpio, D., & Byers, J. W. (2017). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Journal of Marketing Research, 54(5), 687–705. https://doi.org/10.1509/jmr.15.0204
- Zhang, Z., Chen, R. J. C., Han, L. D., & Yang, L. (2017). Key factors affecting the price of Airbnb listings: A geographically weighted approach. Sustainability (Switzerland), 9(9), 1–13. https://doi.org/10.3390/su9091635
- Zhang, Z., & Fu, R. J. C. (2020). Accommodation experience in the sharing economy: A comparative study of Airbnb online reviews. Sustainability, 12(24), 10500. https://doi.org/10.3390/su122410500