The Diversity and Evolution Process of Bus System Performance in Chinese Cities: An Empirical Study

Abstract

Bus system performance varies from city to city, and experience clearly indicates that simply increasing the size of bus fleet cannot always improve bus system performance. It is therefore necessary to identify the major variables of bus system performance in different cities and implement a diversity improvement strategy based on actual problems that cities are facing. Two new indicators, annual average bus trips per capita and average daily ridership per bus, are proposed to respectively describe two aspects of bus system performance: willingness to travel and operational efficiency. According to these two indicators, 645 cities in China are classified into four types: cities with good performance in both aspects; in only one aspect; and in neither aspect. Then, based on panel data attained during 2002-2008, the impacts of the variables on willingness to travel and operational efficiency in different city types are analyzed by the variable coefficient model. The results show that the impacts of urban geography, economic conditions, and bus system facility vary among the four city types. Bus ownership ratio has a significant positive impact on improving willingness to travel for the cities with insufficient bus system facility. However, the impact decreases in the cities with well-developed facilities, whereas the operational efficiency suffers from negative impact due to the excess in bus system facility. In addition, the development characteristics of the OPEN ACCESSSustainability 2014, 6 7752 cities that are improved both in willingness to travel and operational efficiency in each city type during 2002-2008 are discussed. The findings can help local governments make more specific, reasonable and efficient strategies to promote bus system performance.

Space‒Time Evolution Analysis of the Nanjing Metro Network Based on a Complex Network

“…Mohammed et al (2013) [10] describe a simulation model of bus network evolution based on Geographic Information System (GIS), which successfully identifies bus lines prone to frequency changes. Chen et al (2014) [11] proposed the average annual bus trip per capita and the average daily trip per bus, describing two aspects of bus system performance: travel intention and operation efficiency. Based on these two indicators, a variable coefficient model was used to analyze the impact of each variable on the travel intention and operational efficiency of different types of cities.…”

When Expectation Meets Satisfaction: Examining Users and Non-users Perceived Expectations towards Public Bus Services

“…It must be noted that, the factors that influence PB improvements are multidimensional (Geng, et. al., 2016: 2017, Chen, X. et. al., 2014, Morris & Guerra, 2015, Acker et.…”

“…al., 2014, Morris & Guerra, 2015, Acker et. al., 2016 and, since what make public buses attractive varies from city to city, it is therefore vital for policy-makers in the transport industry to identify the major variables which influence PB attraction and satisfaction in different cities and implement these strategies based on the actual challenges that those cities are facing to promote PB usage (Chen, X. et. al., 2014).…”

“…Not only does PBs help in mitigating traffic congestion, its dependence on electricity contribute to making green environment a reality. PBs are energy efficient, making it environmentally friendly (Chen, X. et. al., 2014).…”

“…While many studies talk about the "why" PB must be made attractive to meet satisfaction, only few of the literature talks about the "how" to improve public buses to make it attractive and satisfactory to commuters. Study proves that, over the years, the number of PBs have increased rapidly, but does not reflect ridership (Chen, X. et. al., 2014).…”