IDENTIFIKASI PERTUMBUHAN AIRBNB DAN PENGARUH KEBERADAANYA TERHADAP HARGA PROPERTI (STUDI KASUS : KELURAHAN DAGO, CIUMBULEUIT, DAN HEGARMANAH, KOTA BANDUNG)
The very rapid development of information technology has linearly changed people's behavior, especially in meeting their needs. Sharing economy is a business model to enable product users to get maximum satisfaction at an affordable price. This has become one of the phenomena that occur today...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/51341 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The very rapid development of information technology has linearly changed people's behavior,
especially in meeting their needs. Sharing economy is a business model to enable product users to get
maximum satisfaction at an affordable price. This has become one of the phenomena that occur today,
one of which is Airbnb. Airbnb is an accommodation provider platform that is currently growing rapidly
to become one of the choices for tourists to use its services while they are traveling to tourist
destinations. The location of the Airbnb distribution in a city that tends to be famous in residential
areas, is different from hotels or other accommodations that tend to cluster in downtown areas or in
areas that are tourist areas. These events can cause a change in situation because there are externalities
that can arise because of the activity of Airbnb's short-term leases to improve the local economy,
improve the local economy, improve the environment, increase and increase pollution around
residential areas. Changing the residential area can have a direct impact on the affected property
according to the Hedonic Pricing Methods (HPM) theory. Therefore, research is needed to determine
the existence of Airbnb for certain properties in the city of Bandung, which is the capital of West Java
and one of the main tourist destinations in Indonesia. This study uses spatial analysis that appears
hotspots to see Airbnb's development patterns, then uses service coverage analysis to measure the
distance of the property to facilities and infrastructure, buffer analysis to calculate the range of
influence of airbnb and linear OLS to determine the impact of airbnb on property prices. The results of
this study indicate that there are 3 urban villages that have airbnb listing conditions with good trends
and are always classified as hotspots, namely Dago, Hegarmanah and Ciembuleuit Villages. However,
in these three villages, it was found that what affected property prices was only the structure of the
house such as land prices, number of rooms and land area, it could be stated that the activities of the
existence of airbnb did not have a significant impact on properties in these three vilages. |
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