Driving Factors Behind Airbnb Pricing - A Multilinear Regression Analysis

Abstract: With a high increase of users in the world's ever expanding sharing economy, Airbnb has become a customary solution in short term rentals of accommodations. In this market, it is the host's job to choose a pricing which sufficiently corresponds to what tenants are willing to pay. There can be multiple methods of choosing the price but this study aims to determine and evaluate which factors have a significant impact on short term rental pricing of housing and to what degree. By modelling this issue, the reader can make a better understanding of what to pay or charge for an accommodation. This study also serves as ground work for further investigations exploring nested and multi-leveled factors. The study is limited to the Spanish short term rental market, taking a more in-depth look at the cities of Barcelona, Madrid and Palma. Moreover, listings between 2015 and 2017 are considered in the study. In the end, factors identified as significant on accommodation pricing were Entire Home, Accommodates, Bathrooms, Review Scores Rating etc.. Some of the factors are interchangeable as they have a miniscule effect on the accommodation pricing. Conversely, Entire Home and Accommodates is seen as absolute necessities for the model as they, together, explain two-thirds of the variations in price.