To pay or not to pay? Understanding public acceptance of congestion pricing: A case study of Nanjing

Aya Selmoune; Zhiyuan Liu; Jinwoo Lee; Aya Selmoune; Zhiyuan Liu; Jinwoo Lee

doi:10.3934/era.2022209

Electronic Research Archive

2022, Volume 30, Issue 11: 4136-4156. doi: 10.3934/era.2022209

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To pay or not to pay? Understanding public acceptance of congestion pricing: A case study of Nanjing

1.
Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, China
2.
The Cho Chun Shik Graduate School of Mobility, Korea Advanced Institute of Science and Technology, South Korea

Received: 16 June 2022 Revised: 22 August 2022 Accepted: 24 August 2022 Published: 19 September 2022

Congestion pricing has been unquestionably recognized as an efficient strategy for managing traffic demand following the successful introduction of such schemes in a number of cities. However, the lack of political and public acceptance can be blamed for the nonexecution of congestion pricing projects in numerous cities around the world. This paper sheds light on the impacts of congestion pricing and the factors influencing its public acceptance. Our research was aimed to answer the following questions: (ⅰ) What are the factors that can influence public acceptance of congestion pricing? (ⅱ) What are the impacts of implementing a congestion pricing scheme? (ⅲ) How can we overcome the barriers that currently stand in the way of public acceptance of congestion pricing? To answer these questions, we developed a case study combining stated preference and revealed preference data collected in Nanjing, China. The study analyzes the acceptance of congestion pricing and the factors influencing it, such as socioeconomics, the perceived impact, fairness and public transit-related factors. We compare logistic regression and artificial neural network models to gain a deeper knowledge of the important factors and investigate the respondents' attitudes. The results revealed that the perceived impacts on congestion, the environment, trips to the city center, revenue allocation, public transportation price satisfaction, annual income, fairness, car ownership and travel frequency, along with the efficiency and capacity of public transport systems, need to be included when evaluating individuals' acceptance of congestion pricing. Among these, the perceived impacts on congestion and the environment, fairness and revenue allocation to public transportation are the most significant factors. Moreover, we offer further qualitative insight into the individual, economic and social impacts of congestion pricing. This paper provides decision- and policy-makers with important advice on how to promote public acceptance when considering the implementation of a congestion pricing scheme.
- congestion pricing,
- public acceptance,
- machine learning,
- logistic regression,
- artificial neural networks,
- transport policy
Citation: Aya Selmoune, Zhiyuan Liu, Jinwoo Lee. To pay or not to pay? Understanding public acceptance of congestion pricing: A case study of Nanjing[J]. Electronic Research Archive, 2022, 30(11): 4136-4156. doi: 10.3934/era.2022209

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Abstract

Congestion pricing has been unquestionably recognized as an efficient strategy for managing traffic demand following the successful introduction of such schemes in a number of cities. However, the lack of political and public acceptance can be blamed for the nonexecution of congestion pricing projects in numerous cities around the world. This paper sheds light on the impacts of congestion pricing and the factors influencing its public acceptance. Our research was aimed to answer the following questions: (ⅰ) What are the factors that can influence public acceptance of congestion pricing? (ⅱ) What are the impacts of implementing a congestion pricing scheme? (ⅲ) How can we overcome the barriers that currently stand in the way of public acceptance of congestion pricing? To answer these questions, we developed a case study combining stated preference and revealed preference data collected in Nanjing, China. The study analyzes the acceptance of congestion pricing and the factors influencing it, such as socioeconomics, the perceived impact, fairness and public transit-related factors. We compare logistic regression and artificial neural network models to gain a deeper knowledge of the important factors and investigate the respondents' attitudes. The results revealed that the perceived impacts on congestion, the environment, trips to the city center, revenue allocation, public transportation price satisfaction, annual income, fairness, car ownership and travel frequency, along with the efficiency and capacity of public transport systems, need to be included when evaluating individuals' acceptance of congestion pricing. Among these, the perceived impacts on congestion and the environment, fairness and revenue allocation to public transportation are the most significant factors. Moreover, we offer further qualitative insight into the individual, economic and social impacts of congestion pricing. This paper provides decision- and policy-makers with important advice on how to promote public acceptance when considering the implementation of a congestion pricing scheme.

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