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The Analysis of Blocking Behavior and Pricing: The Case of Airbnb

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  • Yifeng Peng

Abstract

Over the years, as people's lives have improved, our need for transportation and accommodation has increased, driving the rapid growth of the sharing economy. Some well-known network sharing platforms, such as Uber, Drip and Airbnb, provide a large number of convenient options for users with transactional needs, make more use of idle tourism, accommodation and other resources. Sharing economy platforms continue to improve the content and format of their products, but at the same time, the future of sharing platforms and the difficulty of competition is a concern as more platform companies become involved and prices become more transparent. Under this circumstance, optimizing product pricing has become an urgent need for many sharing economy platforms. In this paper, we take Airbnb as the starting point and conduct an empirical analysis of the blocking behavior of homeowners based on proprietary data to explore the factors that affect their product supply. We find that price, number of beds, and listing type all have a significant impact on blocking houses. After that, we conducted further research on price factors and developed a model aiming at profit maximization to obtain the best pricing range for the region and provide suggestions for pricing strategies. Â

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  • Yifeng Peng, 2020. "The Analysis of Blocking Behavior and Pricing: The Case of Airbnb," Business & Entrepreneurship Journal, SCIENPRESS Ltd, vol. 9(1), pages 1-1.
    • Handle: RePEc:spt:busent:v:9:y:2020:i:1:f:9_1_1
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    References listed on IDEAS

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    1. Samuel P. Fraiberger & Arun Sundararajan, 2015. "Peer-to-Peer Rental Markets in the Sharing Economy," Working Papers 15-19, NET Institute.
    2. Chiara Farronato & Andrey Fradkin, 2018. "The Welfare Effects of Peer Entry in the Accommodation Market: The Case of Airbnb," NBER Working Papers 24361, National Bureau of Economic Research, Inc.
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