Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01c821gn75f
Title: Deconstructing Airbnb: Pricing, Seasonality, and Optionality in the Sharing Economy
Authors: Tang, Timothy
Advisors: Mulvey, John
Department: Operations Research and Financial Engineering
Certificate Program: Center for Statistics and Machine Learning
Finance Program
Center for Statistics and Machine Learning
Center for Statistics and Machine Learning
Class Year: 2020
Abstract: The rapid growth of Airbnb, a virtual platform that allows users to quickly and efficiently rent and lease property, has caused significant disruption in the hospitality and real estate markets. Blurring the lines between hotel, rental, and residential properties, its short-term nature, accessibility, and versatility make it a promising resource for information-gathering and potential investment. We examine the relationship between Airbnb and broader economic factors by creating a regime-based market model through conventional economic metrics. We then use Monte Carlo simulation to evaluate pricing and listing strategies for a potential Airbnb property.
URI: http://arks.princeton.edu/ark:/88435/dsp01c821gn75f
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Operations Research and Financial Engineering, 2000-2019

Files in This Item:
File Description SizeFormat 
TANG-TIMOTHY-THESIS.pdf1.5 MBAdobe PDF    Request a copy


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.