Assessment and improvement of EPA's penalty policy: From the perspective of governments' and ships' behaviors. (April 2021)

• Record Type: Journal Article
• Authors: Li, Lingyue; Gao, Suixiang; Yang, Wenguo; Xiong, Xing
• Is Part Of: Transport policy. Volume 104(2021)
• Page Start: 18
• Page End: 28
• Publication Date: 2021-04
• Subjects: Maritime transportation -- Emission control areas -- Penalty policy assessment -- Game theory; Transportation and state -- Periodicals; Transportation -- Rates -- Periodicals; 388
• DOI: 10.1016/j.tranpol.2021.02.004
• Languages: English
• ISSNs: 0967-070X

Abstract

Abstract: As a basis and guarantee for the effective enforcement of emission control area regulations, penalty policies play an important role in preventing violations. To more clearly understand the effectiveness of penalty policies, this paper proposes two assessment indicators and assesses Environmental Protection Agency's (EPA's) penalty policy based on the behaviors of governments and ships. By establishing an evolutionary game model that considers the competitive relationships between ships, we obtain evolutionary stable strategies. Furthermore, we quantitatively assess the effectiveness of EPA's penalty policy for different routes and ship types, and discuss the impacts of accurate penalty fine calculations. Finally, recommendations on penalty policy implications are proposed. The results of this paper show that EPA's penalty policy is less effective overall and that its effectiveness differs for different routes and ship types. Fortunately, the effectiveness of EPA's penalty policy can be improved by accurately calculating penalty fines, and using Automatic Identification System data to pre-identify violations and determine penalty fines is a potential way to improve EPA's penalty policy. Highlights: Establish two indicators to evaluate the effectiveness of penalty policies. Utilize game theory to describe the strategic interactions between governments and ships. Assess EPA's penalty policy for different routes and ship types based on proposed indicators. Propose using AIS data to pre-identify violations and determine penalty fines.