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Feasibility Analysis of Green Travel in Public Transportation: a Case Study of Wuhan

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Feasibility Analysis of Green Travel in Public Transportation: a Case Study of Wuhan sustainability Article Feasibility Analysis of Green Travel in Public Transportation: A Case Study of Wuhan Junjun Zheng, Yi Cheng, Gang Ma *, Xue Han and Liukai Yu Economics and Management School, Wuhan University, Wuhan 430072, China; [email protected] (J.Z.); [email protected] (Y.C.); [email protected] (X.H.); [email protected] (L.Y.) * Correspondence: [email protected] Received: 3 July 2020; Accepted: 11 August 2020; Published: 12 August 2020 Abstract: The demand to alleviate urban traffic and reduce air pollution puts forward high requirements for green travel in public transportation. Thus, study of the feasibility of urban green travel in public transportation is necessary. This study focuses on it from two aspects: City level by complex network and individual level by structural equation model. As for the former, point of interest data on the spatial distribution of urban public transportation in Wuhan city are quantitatively analyzed. Then, a complex network of public transportation in Wuhan is constructed by using the Space L method, and the network characteristics are analyzed. Results show that accessibility coverage is mainly concentrated in the central urban area, and two significant central nodes exist, namely, Linshi and Zhaohu stations. At the individual level, 354 valid questionnaires and the structural equation model were used to explore the factors affecting individual intention of public transportation. Behavioral perceptual outcome, behavioral attitudes, and subjective norms have positive influences on the behavioral intention of public transportation, among which the behavioral attitudes are the most significant, and the subjective norms had the lowest influence. Some suggestions are proposed for Wuhan to improve urban accessibility and for individuals to increase green travel in public transportation. Keywords: complex network; green travel; structural equation model; theory of planned behavior 1. Introduction 1.1. Context Public transportation can alleviate urban air pollution problems and has attracted extensive attention from governments of various countries [1]. Urban areas, urban population density, public facilities construction, and spatial distribution constantly develop and change, followed by the diversification and complexity of people’s value orientation, desire evolution, and behavior choices in aspects, such as food, clothing, housing, and transportation. How to guarantee public transportation at a city level effectively is a difficult problem. As shown in Figure1, China’s urbanization is in a period of rapid development, but the supply growth of urban public facilities and infrastructure services does not fully match with urbanization development. Sustainability 2020, 12, 6531; doi:10.3390/su12166531 www.mdpi.com/journal/sustainability Sustainability 2020, 12, 6531 2 of 22 Sustainability 2020, 12, 6531 2 of 22 Sustainability 2020, 12, 6531 2 of 22 Figure 1. China’s urban area and urban population density. (Source: China Statistical Yearbook). Figure 1. China’s urban area and urban population density. (Source: China Statistical Yearbook). GivenFigure the 1. China’srapid increase urban area of andurban urban areas population and po denspulation,ity. (Source: urban China facilities Statistical and publicYearbook). transport servicesGiven have the developed rapid increase gradually, of urban as shown areas in and Figure population, 2. 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Therefore, scientific and reasonable space network planning is crucial for improving urban environmental quality [2]. Figure 2. Changes of urban public transport services in China. (Source: China Statistical Yearbook). Figure 2. Changes of urban public transport services in China. (Source: China Statistical Yearbook). Figure 2. Changes of urban public transport services in China. (Source: China Statistical Yearbook). Sustainability 2020, 12, 6531 3 of 22 Sustainability 2020, 12, 6531 3 of 22 Figure 3. Passenger volume change of urban public transport in China. (Source: China FigureStatistical 3. Passenger Yearbook). volume change of urban public transport in China. (Source: China Statistical Yearbook). Obviously, the construction of urban rail lines requires a large amount of social resources andObviously, government the financial construction revenue. of urban Therefore, rail lines resources requires in a urban large amount rail public of social transport resources are mainly and governmentconcentrated financial in the central revenue. urban Therefore, areas of first-tierresources and in second-tier urban rail citiespublic and transport radiate toare the mainly remote concentratedurban areas. in However, the central the urban lines currently areas of first-tier in operation and aresecond-tier still limited. cities Residents and radiate in large-sized to the remote and urbanmedium-sized areas. However, cities have the lines a large currently demand in for operat conveniention are still and limited. punctual Residents public transport in large-sized resources; and medium-sizedtherefore, the cities distribution have a oflarge urban demand public for transport convenient resources and punctual is unbalanced public transport and geographically resources; therefore,different tothe a certaindistribution extent of [3 ].urban Spatial public distribution transport features resources are essential is unbalanced [4,5], but and previous geographically studies on differentspatial analysis to a certain are fewextent and [3]. mostly Spatial from distribution the macro features description, are essential such as satellite[4,5], but maps. previous Ren etstudies al. [1 ] onused spatial the China–Brazilanalysis are few Earth and Resources mostly from Satellite-02B the macro to description, analyze land-use such as change. satellite Moreover, maps. Ren complex et al. [1]network used the theory China–Brazil can analyze Earth the reliability Resources of Satell networksite-02B and to evaluate analyze node land-use importance change. [6 ].Moreover, However, complexfor the construction network theory of green can travelanalyze network, the reliability it is generally of networks only simulation, and evaluate not node combined importance with actual [6]. However,data, used for to the construct construction an actual of green effective travel network.
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