The impact of COVID-19 on sharing economy in Singapore: Role of customer’s perceived risk
DOI:
https://doi.org/10.54691/bcpbm.v38i.4081Keywords:
COVID-19 Impact, Sharing Economy, Risk Perception, Natural Language Processing.Abstract
The unprecedented COVID-19 pandemic has had a significant impact on the tourism industry. Previous research has studied the perspective of Airbnb hosts, but rarely mentioned the effect on consumer choice. As consumer choices may be driven by their risk perceptions, how COVID-19 may influence is not well-understood. This paper aims to investigate how COVID-19 may change consumer risk perception on different Airbnb listings, and such an impact on risk perception may affect their choices and overall business performance. The paper utilizes large-scale data about customer reviews and listing characteristics from Airbnb Singapore in the years 2019-2021, using NLP techniques to analyze, and extract the change in tourists’ risk perception before and after the outbreak of COVID-19 in Singapore. Comparing the topical content from customer reviews, we find that customers tend to perceive their experience more significantly on cleanliness-related issues since the outbreak of COVID-19. Furthermore, sentiment Analysis is performed to classify customer reviews into positive and negative, respectively, such that all listings are classified according to their valence in the perceived cleanliness. We show that the number of bookings and revenues of listings perceived as clean and not clean by the customers has diverged since the pandemic, i.e., the listings that are perceived clean would receive more bookings and thus accrue more revenues than those that are perceived as not clean. Overall, the research results would provide insight for Airbnb hosts and platforms to manage listings in the post-pandemic era, especially on how to manage and communicate cleanliness-related risks.
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