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Free-floating bike-sharing systems allow users to unlock nearby bikes and leave the bikes at any authorized parking area, acting as a time-saving approach for solving the first/last mile problem by connecting trip origins/destinations to metro stations (i.e., bike-and-ride). Inspired by a recent study uncovering the scaling-free phenomenon on the bike-sharing mobility network, this paper addresses the following question: does the power-law distribution also appear in bike-and-ride activities? How does the unbalanced usage pattern of bike-and-ride vary by time and space? To answer the questions, we examine one-week trip orders of free-floating bike sharing in Beijing. We find that the unbalance activities of bike-and-ride show a similar segmented scaling-free feature displaying a first sub-linear regime followed by another super-linear regime on weekdays and weekends. The unbalanced features on weekdays are more substantial than those on weekends and uncovered by the time-varying unbalance in different regimes. Moreover, the unbalanced state corresponding to each metro station obeying non-stationary and dramatically changing peak hours on weekdays suggests that commuting between the suburban and urban areas may be the primary source of the unbalance usage of bike-and-ride in Beijing. Our findings can improve the efficient redistribution of bike-sharing supply and promote the coupling efficiency among transportation modes. • The statistic of access and egress trips connecting with metro stations are explored. • The essential unbalance characteristics of bike-and-ride's temporal and spatial analyses are presented. • Our results improve the efficient redistribution of bike-sharing supply and promote the coupling efficiency among transportation modes. [ABSTRACT FROM AUTHOR]

Due to the urban industrial transformation and upgrading in China, the relationship between residential and employment spaces in large cities has changed significantly, resulting in an increasingly prominent job–housing separation phenomenon. Based on the taxi GPS trajectory data, this paper firstly analyzes the time and space distribution of job–housing–travel and the commuting characteristics of residents. Then, we construct the evaluation index systems of regional jobs–housing–taxi demand and regional social development level for Beijing. After calculating the weight of each index by using an entropy weight method, we analyze the coupling relationship between regional taxi demand and social development by building the coupling coordination degree model (CCDM). Conclusions are as follows: Firstly, it shows imbalance of space distribution of taxi orders in different administrative and functional areas. The order quantity gradually decreases from the main urban area to the edge, with the most in the living area, accounting for 46.23% of the total orders. Secondly, the daily variation trend of taxi orders in different functional areas is significantly different. During the morning rush hour, taxi orders flow out of residential areas and into office areas; however, during the evening rush hour, they flow out of the office and into the living area. For example, the residence area has a higher proportion of getting on passengers during the morning rush hour, which is 1.46 times that of the getting off ones. Thirdly, a low coupling coordination degree is observed between the regional social development level and the job–housing–taxi demand in Beijing, with a gradually decreasing from the main urban area to the outside, which is mainly caused by the imbalance between supply and demand. Therefore, it is suggested that the relevant government departments should formulate specific control schemes to traffic congestion according to local commuting features, and promote job–housing balance. Meanwhile, the taxi resources are supposed to be allocated reasonably by the striving to information symmetry, to promote the coordination and sustainability between the regional job–housing–taxi demand and social development level. • Administrative and functional areas' taxi orders are spatially imbalanced. • In the morning rush, taxi orders flow from residential to office; the reverse applies during the evening rush. • Congestion has more impact on commuting time than on commuting distance. • A low-degree coupling coordination between RJTD and RSTL in Beijing is observed and decreases outward from main urban areas. [ABSTRACT FROM AUTHOR]