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Understanding behavioral effects of tradable mobility credit scheme: An experimental economics approach
Abstract The concept of Tradable Mobility Credit scheme (TMC) has been explored as an innovative Active Traffic and Demand Management (ATDM) strategy using economic instruments. In a general TMC scheme, a Central Authority Agency (CAA) issues a certain amount of mobility credits to eligible travelers. Credits are charged if the travelers take specific routes while the credits can also be traded in between of travelers in a market. An online interactive experiment, within which human participants extensively interact with each other and with intelligent virtual agents in credit trading and route choice stages, is conducted in this study. Hypothesized behavioral effects that characterize responses to TMC in personal car use domain, including loss aversion, immediacy effect and learning effect, are observed. Next, simulated experiments under various credit demand/supply situations, with only virtual agents, are conducted. The results show the proposed TMC scheme is fairly efficient and financially sustainable. Fast market equilibrium convergence is observed as well. The future TMC scheme design could accommodate the insights from this empirical study. In the meantime, the experiment platform could serve as a handy data collection tool that could be portable for any future studies involving online interactions and collective choices in transportation realm.
Highlights An online experiment is conducted to testify behavioral effects in tradable credit scheme. Loss aversion is observed that losses loom larger than gains in tradable credit scheme. Immediacy effect is observed that people overspend credits at the start of period. Learning effect is observed that people adaptively adjust their bidding strategies. The proposed tradable mobility credit scheme is fairly efficient and financially sustainable.
Understanding behavioral effects of tradable mobility credit scheme: An experimental economics approach
Abstract The concept of Tradable Mobility Credit scheme (TMC) has been explored as an innovative Active Traffic and Demand Management (ATDM) strategy using economic instruments. In a general TMC scheme, a Central Authority Agency (CAA) issues a certain amount of mobility credits to eligible travelers. Credits are charged if the travelers take specific routes while the credits can also be traded in between of travelers in a market. An online interactive experiment, within which human participants extensively interact with each other and with intelligent virtual agents in credit trading and route choice stages, is conducted in this study. Hypothesized behavioral effects that characterize responses to TMC in personal car use domain, including loss aversion, immediacy effect and learning effect, are observed. Next, simulated experiments under various credit demand/supply situations, with only virtual agents, are conducted. The results show the proposed TMC scheme is fairly efficient and financially sustainable. Fast market equilibrium convergence is observed as well. The future TMC scheme design could accommodate the insights from this empirical study. In the meantime, the experiment platform could serve as a handy data collection tool that could be portable for any future studies involving online interactions and collective choices in transportation realm.
Highlights An online experiment is conducted to testify behavioral effects in tradable credit scheme. Loss aversion is observed that losses loom larger than gains in tradable credit scheme. Immediacy effect is observed that people overspend credits at the start of period. Learning effect is observed that people adaptively adjust their bidding strategies. The proposed tradable mobility credit scheme is fairly efficient and financially sustainable.
Understanding behavioral effects of tradable mobility credit scheme: An experimental economics approach
Tian, Ye (Autor:in) / Chiu, Yi-Chang (Autor:in) / Sun, Jian (Autor:in)
Transport Policy ; 81 ; 1-11
29.05.2019
11 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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