The impact of parking pricing on mode choice

运输工程 可持续运输 业务 模式选择 交通拥挤 城市化 模式(计算机接口) 订单(交换) 过程(计算) 拥挤收费 需求管理 环境经济学 持续性 计算机科学 公共交通 经济 工程类 经济增长 财务 生态学 宏观经济学 生物 操作系统
作者
Nataša Vidovič,Jelena Simićević
出处
期刊:Transportation research procedia [Elsevier BV]
卷期号:69: 297-304 被引量:17
标识
DOI:10.1016/j.trpro.2023.02.175
摘要

Over the past decades global urbanization has led to the rapid growth of cities. Mobility needs of inhabitants along with their emphasised car dependency have led to the constant increase in car ownership, while transport infrastructure hasn't followed this growth sufficiently. The consequences of this supply and demand imbalance are the numerous negative effects, such as: traffic congestion, time delays, illegal parking, emissions of pollutants, frustrations of drivers, etc. Having in mind that the essence of these problems lies in excessive car usage, policies contributing to the greater share of more sustainable transport mode are increasingly applied in transport management process nowadays. In this sense, parking policies, particularly parking charging, have proven to be very effective, supporting the implementation of sustainable transport goals in urban areas. It is well-known that parking charge can impact different patterns of user behaviour. For example, it can impact the user's choice of parking location or transport mode, trip destination, etc. Therefore, in order to properly define parking prices, it is necessary to understand the way users respond to them. Despite the importance of this topic, user response to parking policies has not yet been sufficiently examined. This paper aims to partially fill this gap. The aim of this paper is to investigate the parking price impact on user's choice of transport option based on the applied logistic regression, taking into account their socio-economic characteristics as well as trip characteristics. Transport options included the use of passenger car on the one hand and the use of more sustainable transport modes (public transport, taxi, walking) on the other. To fit the model we use data obtained by interviewing the users of one parking garage in Belgrade central area by revealed and stated preference methods.
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