TY - JOUR
T1 - Modeling collusion-proof port emission regulation of cargo-handling activities under incomplete information
AU - Zheng, Shiyuan
AU - Ge, Ying En
AU - Fu, Xiaowen
AU - Nie (Marco), Yu
AU - Xie, Chi
N1 - Funding Information:
The authors would like to thank the anonymous referees for their very helpful comments and suggestions. This work was supported in part by the National Science Foundation of China (Nos. 71402094 , 71402095 and 71671110 ) and the Innovation Program of the Shanghai Municipal Education Commission (No. 15ZS046 ). The authors are also grateful for the support of the Lloyd's Register Foundation, a charity that helps to protect life and property by supporting engineering-related education, public engagement, and the application of research.
Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2017/10
Y1 - 2017/10
N2 - This study models the emission regulation of a port's cargo-handling activities when the regulatory government agency lacks complete information on the cost of reducing emissions for the port. The goal is to identify rules for determining the optimal port charge and capacity to allow port emissions to be regulated in an environment with incomplete information. We evaluate the effect of introducing a risk-averse environmental monitor as a supervisor to provide the government with additional information (a signal) on the port operator's emission reduction cost. To prevent the environmental monitor from colluding with the port operator, we develop a collusion-proof regulation scheme based on the principal–agent theory. The scheme is modeled as a bi-level problem faced by the government and the monitor. We find that, compared to the case with complete information, collusion-proof regulation do not distort optimal port charges only when the port operator is efficient and has low emission reduction costs. When distortion does occur, it depends on the monitor's degree of risk aversion and the accuracy of the signal about emission reduction cost. Besides, information asymmetry leads to less cargo throughput, a lower emission level, and reduced port capacity. Such regulation-induced downward distortion can be either alleviated or aggravated by the collusion-proof regulation, depending on the quality of the information received by the environmental monitor. Our theoretical models are tested using a case study based on container terminals in the Port of Shanghai. The numerical results suggest that a risk-averse environmental monitor can improve port user's social welfare in the presence of imperfect information.
AB - This study models the emission regulation of a port's cargo-handling activities when the regulatory government agency lacks complete information on the cost of reducing emissions for the port. The goal is to identify rules for determining the optimal port charge and capacity to allow port emissions to be regulated in an environment with incomplete information. We evaluate the effect of introducing a risk-averse environmental monitor as a supervisor to provide the government with additional information (a signal) on the port operator's emission reduction cost. To prevent the environmental monitor from colluding with the port operator, we develop a collusion-proof regulation scheme based on the principal–agent theory. The scheme is modeled as a bi-level problem faced by the government and the monitor. We find that, compared to the case with complete information, collusion-proof regulation do not distort optimal port charges only when the port operator is efficient and has low emission reduction costs. When distortion does occur, it depends on the monitor's degree of risk aversion and the accuracy of the signal about emission reduction cost. Besides, information asymmetry leads to less cargo throughput, a lower emission level, and reduced port capacity. Such regulation-induced downward distortion can be either alleviated or aggravated by the collusion-proof regulation, depending on the quality of the information received by the environmental monitor. Our theoretical models are tested using a case study based on container terminals in the Port of Shanghai. The numerical results suggest that a risk-averse environmental monitor can improve port user's social welfare in the presence of imperfect information.
KW - Collusion-proof
KW - Incomplete information
KW - Port emission regulation
KW - Principal–agent theory
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U2 - 10.1016/j.trb.2017.04.015
DO - 10.1016/j.trb.2017.04.015
M3 - Article
AN - SCOPUS:85026884600
SN - 0191-2615
VL - 104
SP - 543
EP - 567
JO - Transportation Research, Series B: Methodological
JF - Transportation Research, Series B: Methodological
ER -