Business Mafia Proposal

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PROPOSAL

POSTER

APPLICATION

RESEARCH PAPER

Project Motivation

A significant proportion of Airbnb hosts rent out portions of their own homes to generate additional side income. Instead of relying on a robust approach when setting prices, they tend to do so intuitively, relying on gut feeling. Our group hopes to offer these homeowners an alternative way to price their listings - through an amalgamation of factors such as their listing's geographical location and its relationship with Downtown Seattle.

However, the primary challenge here is simplifying and summarising the technical, complex analytics techniques into layman terms; it would require breaking down the technical jargon associated with it. In order to carry this out effectively, we created an RShiny Application which would guide owners systematically through the thought process. This would allow owners to not only derive the final proposed listing price, but also better understand our thought process and methodology behind the derivation of the price.

Project Objective

Through our project, we aim to:

1. Derive individual walking distance between various key attractions and Airbnb listings in Downtown Seattle
2. Analyse the spatial relationships between various key locations and Airbnb listings in Downtown Seattle to determine if the listing's location to key places affect its listing price
3. Through the use of Local Geographical Weighted Regression (GWR) Model, we hope to help Airbnb owner(s) determine the better pricing for their listing(s).

Our Datasets

Data	Source	Data Description	Source URL	Data Type
Seattle Open Airbnb Data	Inside Airbnb	Information on all Airbnb listings found within Downtown Seattle, last scrapped on 15 November 2018	http://insideairbnb.com/get-the-data.html	CSV File
Common Place Name (CPN)	City of Seattle Open Data Portal	A point feature class showing common place names and corresponding locations in Seattle.	https://data.seattle.gov/Land-Base/Common-Place-Names-CPN-/599c-9ddc	CSV File
City Clerk Neighbourhoods	Seattle.gov	Displays the 20 Large City Clerk neighborhood boundaries, along with their smaller neighborhood boundaries.	https://data.seattle.gov/dataset/City-Clerk-Neighborhoods/926y-cwh9	SHP File
Zoning (Generalized)	Seattle GIS Open Data	A polygon feature class showing zoning areas. It also provides information on the type of zoning such as Downtown, Major Institutions, Manufacturing/Industrial, Multifamily, Neighbourhood/Commercial, Residential/Commercial and Single Family.	https://data-seattlecitygis.opendata.arcgis.com/datasets/a85e74dac41d43cab5a8b840558c4d77_3?page=15	SHP File

Literature Review

Sources:

1. https://towardsdatascience.com/airbnb-rental-listings-dataset-mining-f972ed08ddec
2. https://www.airbnbcitizen.com/the-airbnb-community-in-seattle/
3. https://stanleyadion.shinyapps.io/AmazeingCrop/

Literature Review 1: Airbnb Rental Listings Dataset Mining

Literature's outcome: An exploratory analysis of Airbnb's Data to understand the rental landscape in New York City

Project Storyboard

Project Timeline