TY - JOUR
T1 - Understanding behavioral effects of tradable mobility credit scheme
T2 - An experimental economics approach
AU - Tian, Ye
AU - Chiu, Yi Chang
AU - Sun, Jian
N1 - Funding Information:
This research was supported by the Natural Science Foundation of China [ U1764261 ], the National Key Research and Development Plan of China [ 2018YFB1600800 ], Shanghai Sailing Program [ 19YF1451200 ], and Fundamental Research Funds for the Central Universities [ 22120180622 ].
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/9
Y1 - 2019/9
N2 - 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.
AB - 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.
KW - Agent-based modeling and simulation
KW - Behavioral economics
KW - Experimental economics
KW - Immediacy effect
KW - Loss aversion
KW - Tradable mobility credits
UR - http://www.scopus.com/inward/record.url?scp=85066990519&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85066990519&partnerID=8YFLogxK
U2 - 10.1016/j.tranpol.2019.05.019
DO - 10.1016/j.tranpol.2019.05.019
M3 - Article
AN - SCOPUS:85066990519
VL - 81
SP - 1
EP - 11
JO - Transport Policy
JF - Transport Policy
SN - 0967-070X
ER -