Investigating users’ perspectives on the development of bike-sharing in Shanghai

High levels of car dependence have caused tremendous challenges for sustainable transport development. Transport planners, therefore, seek ways of replacing motor vehicles, as well as increasing the proportion of active travel. The bike-sharing scheme can be seen as an effective way of doing so, particularly in Asian cities. The aim of this paper is to investigate users’ perspectives on the development of bike-sharing using Shanghai as an example. Semi-structured interviews are used to examine the main factors motivating and impeding the development of the bike-sharing scheme in Shanghai. Our findings show that convenience, saving time and financial savings are the major motivations; whereas problems with bicycles being poorly maintained and abused by users, operational issues, financial issues and an unsuitable business model are the major obstacles. In addition, the findings also suggest that a public and private partnership could be the best option for running a sustainable bike-sharing scheme with clear areas of responsibility. Financial incentives, a bicycle-friendly infrastructure, regular operational management and supportive policies should be prioritised. In order to achieve the targets set by the Shanghai Master Plan 2035, transport planners and policymakers should integrate the bike-sharing scheme within the wider active travel system

Investigating users’ perspectives on the development of bike-sharing in Shanghai

High levels of car dependence have caused tremendous challenges for sustainable transport development. Transport planners, therefore, seek ways of replacing motor vehicles, as well as increasing the proportion of active travel. The bike-sharing scheme can be seen as an effective way of doing so, particularly in Asian cities. The aim of this paper is to investigate users’ perspectives on the development of bike-sharing using Shanghai as an example. Semi-structured interviews are used to examine the main factors motivating and impeding the development of the bike-sharing scheme in Shanghai. Our findings show that convenience, saving time and financial savings are the major motivations; whereas problems with bicycles being poorly maintained and abused by users, operational issues, financial issues and an unsuitable business model are the major obstacles. In addition, the findings also suggest that a public and private partnership could be the best option for running a sustainable bike-sharing scheme with clear areas of responsibility. Financial incentives, a bicycle-friendly infrastructure, regular operational management and supportive policies should be prioritised. In order to achieve the targets set by the Shanghai Master Plan 2035, transport planners and policymakers should integrate the bike-sharing scheme within the wider active travel system

Prediction of bike-sharing trip counts: comparing parametric spatial regression models to a geographically weighted XGBoost algorithm

Regression models are commonly applied in the analysis of transportation data. This research aims at broadening the range of methods used for this task by modeling the spatial distribution of bike-sharing trips in Cologne, Germany, applying both parametric regression models and a modified machine learning approach while incorporating measures to account for spatial autocorrelation. Independent variables included in the models consist of land use types, elements of the transport system and sociodemographic characteristics. Out of several regression models with different underlying distributions, a Tweedie generalized additive model is chosen by its values for AIC, RMSE, and sMAPE to be compared to an XGBoost model. To consider spatial relationships, spatial splines are included in the Tweedie model, while the estimations of the XGBoost model are modified using a geographically weighted regression. Both methods entail certain advantages: while XGBoost leads to far better values regarding RMSE and sMAPE and therefore to a better model fit, the Tweedie model allows an easier interpretation of the influence of the independent variables including spatial effects

Advances on Smart Cities and Smart Buildings

Modern cities are facing the challenge of combining competitiveness at the global city scale and sustainable urban development to become smart cities. A smart city is a high-tech, intensive and advanced city that connects people, information, and city elements using new technologies in order to create a sustainable, greener city; competitive and innovative commerce; and an increased quality of life. This Special Issue collects the recent advancements in smart cities and covers different topics and aspects