DTimes: Bike-sharing may change house rentals around Shanghai Metro stations

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DTimes: Bike-sharing may change house rentals around Shanghai Metro stations

PR Newswire

BEIJING, Dec. 14, 2017 /PRNewswire/ -- DTimes in collaboration with ofo have jointly launched a research paper on Discovering the Future Core Living Areas in Cities and released their 2017 Report on Travelling within 1 Kilometer around Shanghai Metro Stations by Bike-sharing. After analyzing the riding statistics of shared bikes, they connected shared bikes to the key urban residential areas around metro stations, to determine how many changes this new transportation method has brought to cities and the life of city residents.

Bike-sharing will expand the key urban residential areas around metro stations to a radius of at least 1000m

Before shared bikes appeared, amenities around metro stations only covered a radius of 500m, which was based on walking distance. However, after the emergence or shared bikes, the number and supply of transport vehicles has changed considerably: the service radius around metro stations has expanded, and the living areas of city residents, especially the new generation of consumers, has been redefined.

The changes brought about by bike-sharing are substantial: the residential areas around 90% of Shanghai metro stations have expanded; the supplied radius of bike-sharing around 275 out of 304 metro stations (where transfer stations have only been counted once) has already exceeded 500m. From the Inner to the Outer Rings, the areas covered are increasingly expanding. Shared bikes are seamlessly linking areas around metro stations, extending over almost all of the Middle Ring.

Bike-sharing influence value on living areas has increased

On weekdays, shared bikes are mainly used for urban commuting. From the riding data collected by ofo bicycle users, the riding order volume manifests an obvious tidal effect: the peaks appear between 7:00 to 9:00 a.m. as well as between 5:00 to 7:00 p.m., the rush hours of urban commuting, similar to the performance of public transportation.

By analyzing the riding data, we can see that bike-sharing has the greatest influence on the life and work of YAs (young adults). Based on the characteristics of these two different riding uses, living areas and working areas can be differentiated. The distribution of working areas shows the choices of enterprises and job-seekers. Once the core areas are enlarged, the value of more office buildings can be enhanced, and their attraction can be greater as well.

Accommodation is another key aspect of urban life areas. With the appearance of shared bikes, more communities can be connected to metro stations. Shared bikes will improve the efficiency of urban public transportation, improving the living experience as a whole; furthermore, as house market prices (rent or private) are highly sensitive to areas around metro stations, the market value of these houses whose communities have been included in core living areas will be affected to some extent.

According to the riding usage data of ofo bicycles, 249 city residents go to their working places around metro stations by riding shared bikes, and 252 residents make use of the shared bikes to travel to their living places around metro stations.

Based on the order volume, the average order volume in residential areas is 10% higher than in office areas, indicating the increasing number of people who live near metro stations and choose shared bikes. This not only shows that bike-sharing has a greater impact in residential areas, it also indicates that the value of houses for renting or selling will also be affected.

House rentals around 52 metro stations are more likely to change

If residential areas change, all related business aspects will also be affected. Considering the age groups of riders, market sensitivity, and proximity to life, we can list the changes in the housing market brought about by bike-sharing.

House rentals are heavily affected by their distance to metro stations. In accordance with rental rough data from DTimes City Database, it can be noticed that the farther the distance of a house to metro stations is, the cheaper the rent becomes. Since riding shared bikes shortens the time for people to travel back and forth to the metro stations, an increasing number of houses are included in the areas around metro stations, so the rental difference of houses whose distance to metro stations are different will be reduced.

About DTimes

A data-specialized content & community platform under China Business Network, boasts of its data research, professional data analysis and visualization community. The platform provides insights into consumer society by connecting data, institutions and people.

The main products include two commercial research programs Next50 and Project MetroCity, as well as a community of data professionals and amateurs.

DTimes has over 100,000 regular readers & users with an average monthly page view of 6.2 million as of June 2017.

Awarded most valuable media account TOP 10 presented by Tencent Finance and selected into the long list of 2016 Kantar's Information is Beauty Award, DTimes is long-time strategic partnership of Shanghai Open Data Applications (SODA) and official data partner of UNDP's Geek for Good Open Design Challenge.

Website: www.dtcj.com 
WeChat: DTcaijing



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