A data-driven approach to guest experiences and satisfaction in sharing

ABSTRACT

Accommodation sharing provides unique experiences for tourists. This study collects 33,892 guest reviews of Airbnb. A text analytic approach to deconstruct the nature of sharing experiences is explored. The data-driven approach extracts the following dimensions contributing to the core experiences of sharing, namely, housing, location, host-guest interaction, facility, overall sensation and others. A regression analysis further demonstrates a strong association between attributes of sharing experiences and guest satisfaction. Factors such as room facilities and home experience convey different semantic space and significantly affect guest satisfaction. They serve as hygiene factor and motivator, respectively, confirming the two-factor theory.

KEYWORDS:

• Sharing economy
• experiences
• satisfaction
• text analytics
• Airbnb

Acknowledgments

The authors would like to thank the anonymous referees for their comments to improve this paper. Thanks also go to Dr. Bing Pan from Pennsylvania State University, USA for his advices on this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Central University Foundemental Funds [2242107S10005];National Nature Science Foundation of China [41571133,41711530650,71671038]