Determining factors affecting congestion pricing acceptability

Highlights

• There is relationship between user socio-economic characteristics and CP acceptance.

• Familiarity with CP has an impact on CP acceptability.

• CP acceptability and MAP depend on proposed CP policies.

• Maximum acceptable price for Belgrade CZ usage by a private car is approximately €4.

• On the basis of the distribution of MAP values, car trips in the CZ can be managed.

Abstract

Being aware of the factors affecting users' willingness to accept congestion pricing and pay for central zone usage is of key importance for the successful implementation of the congestion pricing system. Thus, the aim of this paper is to analyze users' attitudes, determine influential variables and define users' preferences toward different congestion pricing policies in the central zone of Belgrade. This study included a comprehensive analysis of factors which can affect the congestion pricing acceptability such as socio-demographic and economic characteristics, patterns of the respondents' movements in relation to the central zone, the respondents’ perception of traffic problems in the central zone, their familiarity with congestion pricing and preferences toward different congestion pricing policies, as well as their preferences toward revenue allocation. Binary logistic regression and structural equation modelling analysis were used to develop appropriate models. The obtained results provide guidelines for decision-makers to consider when defining congestion pricing policy. By following these suggestions, public acceptability would be increased, and the successful implementation of the congestion pricing system would be ensured.

Introduction

With the increase in the number of vehicles in the last few decades, many cities face congestion problems (Pojani and Stead, 2015). Congestion causes numerous negative consequences such as: air pollution, noise, space occupation, delays, fuel waste, traffic accidents as well as the stress of all road users. If negative consequences are converted into monetary units, cities with congestion problems have increased transport, environmental and health costs. It is estimated that for each rush hour a traveller pays an annual “congestion tax” of between $850 and $1600 in lost time and fuel consumption and spends the equivalent of almost 8 workdays each year being stuck in traffic (FHWA, 2006).

Previous studies have indicated that expanding road capacity in the already established urban areas is often ineffective and sometimes counter-effective, as building more roads induces additional demand (Goodwin, 1996; Downs, 2004; Ding and Song, 2012). The only long term solution in the central city zone (CZ) is demand management using different measures and policies. One of these policies is congestion pricing. Congestion pricing (CP) offers an efficient tool of handling congested road traffic flows. The concept of CP is to charge cars for the CZ usage, usually during peak hours, in order to reduce congestion by reducing the number of cars in this area (Giuliano, 1992). In this way, people are motivated to change their transport mode or travel time and use routes which do not pass through the city centre (Rouhani, 2016). It should be underlined that the CP system uses only the so-called „free flow” technologies, i.e. technologies that do not require a change in speed or lane, such as dedicated short range communication multilane free flow (DSRC MLFF), RFID open road tolling (ORT), global navigation satellite system/cellular network or vehicle positioning system (GNSS/CN or VPS), or automated number plate recognition system (ANPR) (Persad et al., 2007; Glavić et al., 2017a, Glavić et al., 2017b; Milenković et al., 2018). Thus, in the CP system, registration and payment are implemented electronically without affecting the flow of traffic.

International experiences suggest that CP has been implemented successfully in a number of countries with developed public transport systems and the existence of alternative routes, such as London, Stockholm, Singapore, Milano, etc. Also, research show that CP brings numerous benefits and positive effects to society in the cities with congestion problems such as increased public transport participation in modal split, transport services improvement, time and fuel savings, air pollution reduction, public health improvement, as well as generated revenue (FHWA, 2008; Eliasson, 2009; Litman, 2011). However, it is very important to point out that successful CP implementation depends on public acceptability, i.e. acceptability is considered the most important barrier in establishing a CP scheme. Implementing the CP system without a strong political support and public acceptance has also been unsuccessful in cities like Hong Kong, New York, Edinburgh, Manchester etc. (Zheng et al., 2014).

On the basis of active CP systems in certain countries, it can be noticed that there are many differences in CP policies. For example, some policies charge on a daily basis while others make charges depending on the number of entrances into the zone. Also, some cities charge for circulation in the area while others charge for access to the area or crossing the area. There are certain differences in the period of the system operation, and in the way of charging the residents of the CZ. For example, in London vehicles used by the CZ residents can register for a 90% discount, while the residents of Milan CZ are allowed 40 free entrances per year after which any additional entrance costs € 2 (price for others is € 5). Bearing this in mind, we can conclude that the CP policy does not solely imply making decisions regarding the introduction of the system. It is a much more complex task which demands dealing with several key issues. Namely, when defining a CP policy, the following questions have to be answered: whether the charges should be based on a daily level or the number of entrances into the zone; whether the price might depend on the number of passengers in the vehicle (2 + policy) and/or the frequency of the zone usage; whether and how the CZ residents would have certain privileges, how much the price should amount to and when the CP should be implemented.

Previous studies have analyzed the relationship between individual factors and users’ willingness to accept CP. Most papers analyzed the impact of socio-demographic (e.g. Odeck and Kjerkreit, 2010; Rentziou et al., 2011; Liu and Zheng, 2013) and economic characteristics (Jakobsson et al., 2000; Liu and Zheng, 2013; Eliasson, 2016). Furthermore, certain papers dealt with the relationship between the perception of congestion problem in the CZ (e.g. Verhoef et al., 1997; Jaensirisak et al., 2005; Eliasson and Jonsson, 2011), revenue allocation (e.g. Farrell and Saleh, 2005; Rentziou et al., 2011; Grisolia et al., 2015), and CP acceptability. Only a few papers analyzed the impact of CP familiarity on CP acceptability, mostly by before-after studies of the implementation of the CP system (e.g. Eliasson and Jonsson, 2011; Nilsson et al., 2016). Other factors considered in the previous studies are residential location (e.g. Zmud and Arce, 2008; Winslott-Hiseliu et al., 2009; Eliasson and Jonsson, 2011) and transport mode usage for entering the CZ (e.g. Rienstra et al., 1999; Rentziou et al., 2011; Zheng et al., 2014).

Considering the low level of service in the CZ of Belgrade, the capital city of Serbia, CP can be considered as one policy-level alternative for tackling the ongoing demand management issues. Mladenovic et al. (2016) have previously observed the question of CP in the CZ of Belgrade from the perspective of the policy transfer theory. The policy transfer theory originates from the fields of political science and public policy. Keeping in mind the importance of public acceptance for the successful implementation of CP, authors of this paper include an analysis of users' attitudes about CP introduction and their maximum acceptable price (MAP) for Belgrade CZ usage. The main aims of this paper are to analyse users' attitudes, determine influential variables, define users' preferences toward different CP, and suggest the transfer of results to future studies of users’ attitudes.

One of the contributions of this paper is reflected in a comprehensive analysis of factors affecting CP acceptability, classified by the authors as demographic and socio-economic characteristics of respondents, patterns of the respondents' movements in relation to the CZ, respondents' perception of traffic problems in the CZ, their familiarity with CP and preferences toward different CP policies, and their preferences toward revenue allocation. First, the study applied the chi-square test of independence to explore the relationship between certain factors and users' willingness to accept the CP implementation. Next, logistic regression and SEM analysis were applied to determine the effect of the analyzed factors on the public acceptability of CP. In addition, SEM analysis also included the analysis of factors which have an impact on MAP. In this paper, special attention was paid to the variables which had been rarely observed and which the authors considered to be crucial factors for CP acceptability. These factors are the variables related to the users’ average monthly income, average monthly mileage, residential location, distance from home to the CZ, transport mode usage, CP familiarity and their preference toward different CP policies. Also, an important contribution of this paper is defining the CP rate policy. Namely, on the basis of the distribution of MAP values, car trips in the CZ can be managed.