Understanding the Operational Efficiency of Bicycle-Sharing Based on the Influencing Factor Analyses: A Case Study in Nanjing, China

With the expansion of urban scale and the growth of urban population, the bicycle-sharing system has been greatly helping grease the wheels of convenience and diversity of citizens' travel. Nevertheless, there are a set of additional problems, including imbalance of supply and demand at rental...

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Main Authors: Beibei Hu, Yunfeng Gao, Jiechen Yan, Yue Sun, Yang Ding, Ji Bian, Xianlei Dong, Huijun Sun
Format: Article
Language:English
Published: Hindawi-Wiley 2021-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2021/8818548
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spelling doaj-6835773ddda24ec78b276cd13f29af3f2021-02-15T12:52:41ZengHindawi-WileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/88185488818548Understanding the Operational Efficiency of Bicycle-Sharing Based on the Influencing Factor Analyses: A Case Study in Nanjing, ChinaBeibei Hu0Yunfeng Gao1Jiechen Yan2Yue Sun3Yang Ding4Ji Bian5Xianlei Dong6Huijun Sun7School of Business, Shandong Normal University, Jinan, ChinaSchool of Business, Shandong Normal University, Jinan, ChinaSchool of Business, Shandong Normal University, Jinan, ChinaSchool of Business, Shandong Normal University, Jinan, ChinaSchool of Business, Shandong Normal University, Jinan, ChinaSchool of Business, Shandong Normal University, Jinan, ChinaSchool of Business, Shandong Normal University, Jinan, ChinaKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, ChinaWith the expansion of urban scale and the growth of urban population, the bicycle-sharing system has been greatly helping grease the wheels of convenience and diversity of citizens' travel. Nevertheless, there are a set of additional problems, including imbalance of supply and demand at rental stations and low utilization of system operation, which have disrupted the travel experience of consumers, the profitability of businesses, and the coordination of government. In this study, we take Nanjing as an example to measure the operating efficiency of bicycle-sharing by calculating the capacity utilization rate (CUR). Afterwards, based on the IC card data of bicycle-sharing users, we statistically analyzed the traffic inflow and outflow at rental stations. Besides, this paper discusses the factors influencing the use of bicycle-sharing, by introducing the method of sampling stepwise regression into the study of rental situation and geographical environment. The results are as follows: (1) demand for bicycle-sharing is higher on weekdays than on weekends, especially during the morning and evening rush hours. (2) The daily average capacity utilization rate of bicycle-sharing is less than 0.08, indicating that the system is not efficient enough. During morning and evening rush hours, only less than 10% of rental stations have high inflow and outflow, and there is an imbalance of inflow and outflow for the same rental station at different times of the day. (3) The stepwise regression results show that the inflow and outflow of bicycle-sharing rental stations are mainly affected by the distribution of traffic, education, entertainment, medical, and other functional zones near the stations. These findings could provide relevant government departments and enterprises with strategies and suggestions for the efficient and healthy operation of the urban bicycle-sharing system.http://dx.doi.org/10.1155/2021/8818548
collection DOAJ
language English
format Article
sources DOAJ
author Beibei Hu
Yunfeng Gao
Jiechen Yan
Yue Sun
Yang Ding
Ji Bian
Xianlei Dong
Huijun Sun
spellingShingle Beibei Hu
Yunfeng Gao
Jiechen Yan
Yue Sun
Yang Ding
Ji Bian
Xianlei Dong
Huijun Sun
Understanding the Operational Efficiency of Bicycle-Sharing Based on the Influencing Factor Analyses: A Case Study in Nanjing, China
Journal of Advanced Transportation
author_facet Beibei Hu
Yunfeng Gao
Jiechen Yan
Yue Sun
Yang Ding
Ji Bian
Xianlei Dong
Huijun Sun
author_sort Beibei Hu
title Understanding the Operational Efficiency of Bicycle-Sharing Based on the Influencing Factor Analyses: A Case Study in Nanjing, China
title_short Understanding the Operational Efficiency of Bicycle-Sharing Based on the Influencing Factor Analyses: A Case Study in Nanjing, China
title_full Understanding the Operational Efficiency of Bicycle-Sharing Based on the Influencing Factor Analyses: A Case Study in Nanjing, China
title_fullStr Understanding the Operational Efficiency of Bicycle-Sharing Based on the Influencing Factor Analyses: A Case Study in Nanjing, China
title_full_unstemmed Understanding the Operational Efficiency of Bicycle-Sharing Based on the Influencing Factor Analyses: A Case Study in Nanjing, China
title_sort understanding the operational efficiency of bicycle-sharing based on the influencing factor analyses: a case study in nanjing, china
publisher Hindawi-Wiley
series Journal of Advanced Transportation
issn 0197-6729
2042-3195
publishDate 2021-01-01
description With the expansion of urban scale and the growth of urban population, the bicycle-sharing system has been greatly helping grease the wheels of convenience and diversity of citizens' travel. Nevertheless, there are a set of additional problems, including imbalance of supply and demand at rental stations and low utilization of system operation, which have disrupted the travel experience of consumers, the profitability of businesses, and the coordination of government. In this study, we take Nanjing as an example to measure the operating efficiency of bicycle-sharing by calculating the capacity utilization rate (CUR). Afterwards, based on the IC card data of bicycle-sharing users, we statistically analyzed the traffic inflow and outflow at rental stations. Besides, this paper discusses the factors influencing the use of bicycle-sharing, by introducing the method of sampling stepwise regression into the study of rental situation and geographical environment. The results are as follows: (1) demand for bicycle-sharing is higher on weekdays than on weekends, especially during the morning and evening rush hours. (2) The daily average capacity utilization rate of bicycle-sharing is less than 0.08, indicating that the system is not efficient enough. During morning and evening rush hours, only less than 10% of rental stations have high inflow and outflow, and there is an imbalance of inflow and outflow for the same rental station at different times of the day. (3) The stepwise regression results show that the inflow and outflow of bicycle-sharing rental stations are mainly affected by the distribution of traffic, education, entertainment, medical, and other functional zones near the stations. These findings could provide relevant government departments and enterprises with strategies and suggestions for the efficient and healthy operation of the urban bicycle-sharing system.
url http://dx.doi.org/10.1155/2021/8818548
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