Airbnb was founded in 2008 by Brian Chesky, Joe Gebbia, and Nathan Blecharczyk as AirBed & Breakfast, an online marketplace and hospitality service for short-term lodging. Being one of the primary drivers in the emerging concept of smart tourism, Airbnb acts as a broker, gaining commissions from each booking. The rental properties incorporate apartments, homes, boats, and more. Airbnb had a valuation of $35 billion, over 150 million total number of users and over 6 million listings in more than 191,000 cities globally. Airbnb is unique in the sharing economy due to the peer-to-peer interaction between a host and a consumer and the ability for the host to set their own listing price. The major role of Airbnb is then to create and manage the marketplace where hosts can list their properties and guests can discover unique accommodations globally.
Airbnb generates revenue by charging its guests and hosts fees for arranging stays: hosts are charged 3% of the value of the booking, while guests are charged 6%-12% per the nature of the booking. The host lists a property which the consumer then chooses out of the thousands of Airbnb listings across one location that best suits the individual needs. When hosts are setting the price for their listing, Airbnb provides them with a price recommendation. As a rental ecosystem, Airbnb generates tons of data, price variations across rentals and host-guest interactions in the form of reviews. Airbnb has continued to innovate and improve their price recommendation tool to be more dynamic. Using dynamic pricing provides a more effective price recommendation tool to Airbnb hosts. The type of accommodation that initially was never be available to the general public became readily available. This has caused a plethora of research to examine the attributes of multiple Airbnb accommodations. In order to understand its distribution and corresponding determinate in a specific country, we studied the relationship between Airbnb listing price per night in Singapore and this country's demographics.
Airbnb generates revenue by charging its guests and hosts fees for arranging stays: hosts are charged 3% of the value of the booking, while guests are charged 6%-12% per the nature of the booking. The host lists a property which the consumer then chooses out of the thousands of Airbnb listings across one location that best suits the individual needs. When hosts are setting the price for their listing, Airbnb provides them with a price recommendation.
As a rental ecosystem, Airbnb generates tons of data, price variations across rentals and host-guest interactions in the form of reviews. Airbnb has continued to innovate and improve their price recommendation tool to be more dynamic. Using dynamic pricing provides a more effective price recommendation tool to Airbnb hosts. The type of accommodation that initially was never be available to the general public became readily available.
This has caused a plethora of research to examine the attributes of multiple Airbnb accommodations. In order to understand its distribution and corresponding determinate in a specific country, this project focuses on the relationship between Airbnb listing price per night in Singapore and this country's demographics to understand the rental landscape in Singapore through various visualizations and Machine Learning Regression models.
Steps:
- Data Methology and Analysis i. Preprocessing
- Visualization
- Machine Learning Regression
- Identify efficiency