Exploring the equity performance of bike-sharing systems with disaggregated data: A story of southern Tampa

• Published in: Transportation research. Part A, Policy and practice Policy and practice, 2019-12, Vol.130, p.529-545
• Main Authors: Chen, Zhiwei, Guo, Yujie, Stuart, Amy L., Zhang, Yu, Li, Xiaopeng
• Format: Article
• Language: English
• Subjects: Bike-sharing; Disaggregated data; Equity analysis; Tour-based analysis
• ISSN: 0965-8564; 1879-2375
• DOI: 10.1016/j.tra.2019.09.048

•Propose a methodological framework for assessing the equity performance of bike sharing systems.•Model Individual accessibility to activity locations using bike-sharing as the mode of transportation.•Analyze equity performance from the perspective of both horizontal and vertical equity through a series of equity measures.•Carry out a case study with real data from the Coast Bike Share system in southern Tampa. The rising adoption of bike-sharing systems brings significant benefits to individuals and society as a whole. However, whether these benefits are distributed throughout society in a fair manner is still an open question. This study presents a methodological framework for assessing the equity performance of bike-sharing systems, with Coast Bike Share system in southern Tampa as a case study. The framework integrates three different datasets: bike-sharing infrastructure, individual travel itineraries and individual sociodemographic attribute data. With these datasets, we model individual accessibility to activity locations using bike-sharing as the mode of transportation by analyzing the “walking-cycling-walking” process of a bike-sharing trip and the trip-chaining behavior in individuals’ travel itineraries. Further, a series of equity measures are used to analyze equity performance from the perspective of both horizontal and vertical equity. To assess horizontal equity, we apply the Lorenz curve, Gini index and mapped geographic differences. For vertical equity, we compare descriptive statistics by group, perform analysis of variance, and calculate the subgroup inequality index using disaggregated data. Results reveal that accessibility to bike-sharing is not evenly distributed among individuals in the population, within the geographic space, and among different sociodemographic groups of southern Tampa. Further, our results also highlight the need to incorporate high-resolution disaggregated data and tour-based analysis to address the equity performance of bike-sharing systems.