共享经济下个人出行行为的预测转变:来自消费者出行方式偏好的证据

IF 3.4 3区 经济学 Q1 ECONOMICS
Stephen Youngjun Park, Hyunhong Choi, Yasemin Boztuğ, HyungBin Moon
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引用次数: 0

摘要

新型出行服务对市场的影响不仅改变了消费者的出行行为,也与传统的交通方式产生了各种冲突。获得社会共识,制定适合不同交通方式的政策和市场策略至关重要。本研究的目的是通过研究消费者对交通方式的偏好和选择来预测未来的交通市场。具体而言,本研究采用混合多元离散-连续极值模型定量识别消费者对各类交通方式的态度。除了评估消费者对不同交通方式的偏好和使用选择外,本研究还通过市场模拟来预测未来的交通市场,探讨了交通方式之间的复杂关系。研究结果表明,共享出行服务在交通运输市场中具有巨大的潜力,并确定了出租车和共享出行服务之间的互补效应。预期由此产生的政策影响可以促进运输部门的可持续发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Transition of Personal Travel Behavior in a Sharing Economy: Evidence From Consumer Preferences of Travel Modes

The impacts of new mobility services on the market have led changes in consumer's travel behavior but also to various conflicts with the traditional transportation modes. Gaining social consensus, deriving policy and market strategies suitable for the different transportation modes is crucial. This study's objective is to make predictions about future transportation markets by examining consumers' preferences and choices regarding transportation mode. Specifically, this study employs the mixed multiple discrete-continuous extreme value model to quantitatively identify consumers' attitudes towards various types of transportation modes. In addition to evaluating consumer preferences and usage choices of different transportation modes, the study examines the intricate relationship between transportation modes by using market simulations to forecast future transportation markets. The results show significant potential of shared mobility services in the transportation market and identify complementary effects between taxi and ride-sharing services. It is expected that policy implications derived can contribute to sustainably developing the transportation sector.

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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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