Modeling collusion-proof port emission regulation of cargo-handling activities under incomplete information

- We emphasize the impacts of incomplete information on port emission regulation modeling.
- We introduce a risk-averse EM as a supervisor in the collusion-proof regulation model.
- The collusion-proof port charge and capacity rules for an inefficient operator are distorted.
- The incomplete information causes lower emission level and smaller port capacity.
- The downward regulation distortion may be alleviated in the collusion-proof mechanism.

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.