埃塞俄比亚亚的斯亚贝巴市的拥堵收费和决定为减少拥堵付费意愿的因素

IF 2.4 Q3 TRANSPORTATION Case Studies on Transport Policy Pub Date : 2024-08-08 DOI:10.1016/j.cstp.2024.101265
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引用次数: 0

摘要

在过去的二十五年里,埃塞俄比亚政府参与了大量的道路建设,作为连续道路发展计划的一部分,这些计划大大增加了道路网络的覆盖范围。然而,加剧交通拥堵的趋势并没有减弱的迹象。因此,司机和乘客在漫长的车流中浪费时间,使现代出行变得不可靠,并因延误而增加了旅行成本。为了遏制这一问题,从业人员或研究人员提出的补救措施大多集中在供给方面。本研究旨在确定驾驶员(从需求方)对假定的减少拥堵项目的支付意愿(WTP)。对亚的斯亚贝巴 Kolfe Keraniyo 子城市九个区段的人口进行了陈述偏好调查。使用基于或然估值法(CVM)的调查问卷,从 1012 名受访者中收集了数据。采用 Tobit 和 Heckman 两步选择模型估算了决定减少拥堵 WTP 的因素。分析结果表明,司机的平均支付意愿估计为每公里 2.7 比尔(0.05 美元)。教育程度、婚姻状况、收入、分段使用和出行频率对结果方程有显著决定作用,而年龄、性别、收入、职业、工作经验、分段使用的规律性和频率则决定了是否参与WTP以接受拥堵定价。确定支付意愿和期望价格可帮助亚的斯亚贝巴市政府为未来任何基于拥堵定价的减少拥堵战略确定基线。
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Congestion charging and factors that determine the willingness to pay for congestion reduction in Addis Ababa City, Ethiopia

Over the last two decades and a half, the Ethiopian government has been involved in extensive road construction as part of successive road development plans that have significantly increased road network coverage. However, the tendencies that worsen congestion show no signs of abating. As a result, drivers and passengers waste time in long traffic lines, rendering modern travel unreliable and increasing travel costs due to delays. To curb the problem, the remedies proposed by practitioners or researchers are mostly centred on the supply side. This study aims to determine drivers’ willingness to pay (WTP) (from the demand side) for a hypothetical congestion reduction project. A stated preference survey was utilised on the population identified in nine segments in Addis Ababa’s Kolfe Keraniyo sub-city. The data was gathered from 1012 respondents using a survey questionnaire based on the contingent valuation method (CVM). Tobit and Heckman two-step selection models were used to estimate factors determining WTP for congestion reduction. Accordingly, the analysis showed that the average amount of willingness to pay by drivers was estimated to be birr 2.7 ($0.05) per km. Education, marital status, income, segment use, and trip frequency significantly determined the outcome equation, while age, gender, income, occupation, work experience, and regularity and frequency of segment use were found to determine the decision to participate in WTP to accept congestion pricing. Identifying the willingness to pay and the desired price can assist the Addis Ababa City Administration in establishing a baseline for any future congestion reduction strategy based on congestion pricing.

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