The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
What drives purchase intention on Airbnb? Perspectives of consumer reviews, information quality, and media richness
Abstract
Abstract The owners of idle assets and their potential users create economic benefits through providing or sharing idle assets or skills, and this process has been formalized and monetized at large scales by companies such as Uber, Airbnb, USpace and others. This research seeks to understand the factors affecting the purchase intention on Airbnb users in terms of five key factors: rating, rating volume, review, information quality, and media richness. ANOVA and path analysis are used to test the relationships of these factors with perceived value, satisfaction and purchase intention. Results indicate that perceived value and satisfaction are key determinants of intention to buy, while rating volume, review, information quality, and media richness are important precursors. In addition, gender and usage experiences with Airbnb are also used to classify the sample to assess the difference between each classification. The results of this study can provide a useful reference to researchers and firms and individuals working in the sharing economy.
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Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
On the Evaluation of Structural Equation Models
Bagozzi, R. P., & Yi, Y. (1988) · Journal of the Academy of Marketing Science · doi:10.1007/bf02723327 · Cited by 26,163
SERVQUAL: A multiple-Item Scale for measuring consumer perceptions of service quality
Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1988) · Zenodo · doi:10.5281/zenodo.14579729 · Cited by 21,118
The Effect of Word of Mouth on Sales: Online Book Reviews
Chevalier, J. A., & Mayzlin, D. (2006) · Journal of Marketing Research · doi:10.1509/jmkr.43.3.345 · Cited by 6,003
A national customer satisfaction barometer: the Swedish experience
Fornell, C. (1992) · Journal of Marketing · doi:10.2307/1252129 · Cited by 5,641
The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry
Zervas, G., Proserpio, D., & Byers, J. W. (2017) · Journal of Marketing Research · doi:10.1509/jmr.15.0204 · Cited by 2,376
Price Determinants on Airbnb: How Reputation Pays Off in the Sharing Economy
(2017) · Journal of Self-Governance and Management Economics · doi:10.22381/jsme5420173 · Cited by 206
Travel web-site design: Information task-fit, service quality and purchase intention
Dedeke, A. (. (2016) · Tourism Management · doi:10.1016/j.tourman.2016.01.001 · Cited by 171
Cited by
Zhu, L., Li, H., Wang, F.-K., He, W., & Tian, Z. (2020) · Aslib Journal of Information Management · doi:10.1108/ajim-11-2019-0308 · Cited by 369
Wandoko, W., & Panggati, I. E. (2022) · Journal of Relationship Marketing · doi:10.1080/15332667.2022.2035198 · Cited by 48
Reputation portability – quo vadis?
Hesse, M., & Teubner, T. (2020) · Electronic Markets · doi:10.1007/s12525-019-00367-6 · Cited by 39
Metadata
- Authors
- Chen, C.-C., & Chang, Y.-C.
- Venue
- Telematics and Informatics
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 35
- Issue
- 5
- Pages
- 1512-1523
- ISSN
- 0736-5853 (ISSN-L)
- OpenAlex
- W2794681491
- Cited by
- 336
- References
- 8
- FWCI
- 50.42
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chen, C.-C., & Chang, Y.-C. (2018). What drives purchase intention on Airbnb? Perspectives of consumer reviews, information quality, and media richness. Telematics and Informatics. https://doi.org/10.1016/j.tele.2018.03.019
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