SunlongNgouv / Hubway-Bike-share

Hubway Bike Share was a SQLite3 analytics project focusing on traffics of the bike utilizations in each station and across stations. The project also illustrated user patterns and preference to strategize user experience enhancement.

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Hubway-Bike-share

Prepared by Sunlong Ngouv

Date: April 09th, 2020

Introduction:
Hubway Bike-share originates from Boston and was launched in April 21st, 2011. The Bike-share networks locate in three bound neighborhood cities such as Cambridge, Somerville and Brookline with more than 100 stations and 1,000 bikes and was also supported by Harvard University with 11 stations across Cambridge, Alston and Longwood areas. In 2019, the Hubway was re-launched under ‘Bluebikes’ brand after the company joint partnership with Blue-Cross-Blue-Shield of Massachusetts and started up with 3,000 bikes.

In order to use the Hubway bike, a commuter have to register as either annual or casual member. To be an annual member, so called ‘registered’, you have to purchase annual ticket with $99 through online and receive a key to unlock a bike at any Hubway station. For the casual member, so called ‘casual’, you can purchase day-pass ticket from any station by credit card with $2.5 per trip or $10 for two hours within 24-hour period after purchase. However, the service is free for any trip less than 30 minutes.
Source:
Video: https://www.youtube.com/watch?v=oCdjMpmzTuM
Website Bluebike: https://www.bluebikes.com/blog/bluebikes-coming-soon
Website Hubway: https://www.thehubway.com

Case Study
The Hubway case study consists of two data frames: trips and stations. There are 142 stations corresponding to 1164 bike-shares, and took place in four municipalities such as Boston, Cambridge, Somerville and Brookline.

Goal of this case study is to identify two business insights and one recommendation to the Hubway company for improvement.

About

Hubway Bike Share was a SQLite3 analytics project focusing on traffics of the bike utilizations in each station and across stations. The project also illustrated user patterns and preference to strategize user experience enhancement.


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