{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:40:33Z","timestamp":1760244033165,"version":"build-2065373602"},"reference-count":64,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,11,8]],"date-time":"2022-11-08T00:00:00Z","timestamp":1667865600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52072071","No. KYCX22_0285"],"award-info":[{"award-number":["52072071","No. KYCX22_0285"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Postgraduate Research and Practice Innovation Program of Jiangsu Province","award":["52072071","No. KYCX22_0285"],"award-info":[{"award-number":["52072071","No. KYCX22_0285"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>This paper aims to investigate the internal mechanisms of bottlenecks in bike-sharing travel. We perform kernel density analysis to obtain analysis points and areas designated by buffer areas. Additionally, we improve the spatial lag model through Tobit regression, so as to avoid the interference of autocorrelation and to set reasonable constraints for dependent variables. The proposed model distinguishes between bike-sharing demand determined by land use and other built environmental factors, which helps to define and identify bottlenecks in bike-sharing travel. Based on a Bayesian network fault tree, we define the diagnosis mode of evidence nodes to calculate the posterior probabilities and to determine the most sensitive factors for bottlenecks. We use Beijing city as the case study. The results show that the most sensitive factors that induce bottlenecks in bike-sharing travel are few subway stations, few bus stops, few bus lines, a low density of bike lanes, and more serious home\u2013work separation. The findings presented here can enhance the generation of bike-sharing trips in response to bike-sharing development and contribute to adjusting the urban structure and reconstructing the green infrastructure layout.<\/jats:p>","DOI":"10.3390\/ijgi11110551","type":"journal-article","created":{"date-parts":[[2022,11,8]],"date-time":"2022-11-08T10:53:06Z","timestamp":1667904786000},"page":"551","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Modelling Bottlenecks of Bike-Sharing Travel Using the Distinction between Endogenous and Exogenous Demand: A Case Study in Beijing"],"prefix":"10.3390","volume":"11","author":[{"given":"Sun","family":"Chao","sequence":"first","affiliation":[{"name":"Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China"},{"name":"Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China"},{"name":"School of Transportation, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Jian","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China"},{"name":"Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China"},{"name":"School of Transportation, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3102","DOI":"10.1007\/s12205-022-0802-1","article-title":"Estimation of Route Choice Behaviors of Bike-Sharing Users as First- and Last-mile Trips for Introduction of Mobility-as-a-Service (MaaS)","volume":"26","author":"Cho","year":"2022","journal-title":"KSCE J. 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