IDENTIFICATION OF THE EFFECT OF SPATIAL VARIANCE ON AIRBNB PRICING USING A SPATIAL MULTISCALE GEOGRAPHICALLY WEIGHTED REGRESSION APPROACH (CASE STUDY: BANDUNG CITY AND BADUNG REGENCY)

• Main Author: Agustina, Althea
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/66105
• Institution: Institut Teknologi Bandung

The rapid development of technology in the era of disruption invites changes in the economic field. Sharing economy exists because technology is developing with the intention of helping people in managing their immovable assets to generate economic value through one of the platforms, namely Airbnb Airbnb is an accommodation provider platform that provides a choice of diverse property types, varied prices and offers facilities that are different from traditional accommodation providers, namely hotels. However, regarding pricing strategies in determining Airbnb rental prices requires a study in order to compete with traditional accommodation prices. Pricing strategy is done using several variables that have a relationship such as bedrooms, occupancy rate, overall rate, location of Airbnb listings and others. However, often the spatial or location aspects of Airbnb listings are ignored in setting an Airbnb rental price. Therefore, this study was conducted to identify the influence of spatial variables on Airbnb pricing using spatial multiscale Geographically Weighted Regression (MGWR) approach. The study areas analyzed are Bandung City and Badung Regency which have different spatial characteristics for the two regions. This is done by analyzing Hedonic Pricing Methods (HPM) and analyzing the range of services to identify the proximity of Airbnb locations with several tourist sites and restaurants. The results of this study showed that the global regression model is better than the MGWR model. However, the results of this study cannot be used in different delineations because the geographical conditions in each region have their own uniqueness.