title: Effectiveness of maritime safety control in different navigation zones using a spatial sequential DEA model: Yangtze River case.
abstract: This paper aims to analyze the effectiveness of maritime safety control from the perspective of safety level along the Yangtze River with special considerations for navigational environments. The influencing variables of maritime safety are reviewed, including ship condition, maritime regulatory system, human reliability and navigational environment. Because the former three variables are generally assumed to be of the same level of safety, this paper focuses on studying the impact of navigational environments on the level of safety in different waterways. An improved data envelopment analysis (DEA) model is proposed by treating the navigational environment factors as inputs and ship accident data as outputs. Moreover, because the traditional DEA model cannot provide an overall ranking of different decision making units (DMUs), the spatial sequential frontiers and grey relational analysis are incorporated into the DEA model to facilitate a refined assessment. Based on the empirical study results, the proposed model is able to solve the problem of information missing in the prior models and evaluate the level of safety with a better accuracy. The results of the proposed DEA model are further compared with an evidential reasoning (ER) method, which has been widely used for level of safety evaluations. A sensitivity analysis is also conducted to better understand the relationship between the variation of navigational environments and level of safety. The sensitivity analysis shows that the level of safety varies in terms of traffic flow. It indicates that appropriate traffic control measures should be adopted for different waterways to improve their safety. This paper presents a practical method of conducting maritime level of safety assessments under dynamic navigational environment.
authors.affiliation: Intelligent Transport Systems Research Center (ITSC), Wuhan University of Technology, Wuhan 430063, China; Engineering Research Center for Transportation Safety (ERCTS, MoE), Wuhan University of Technology, Wuhan, China; National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan, China; Centre for Marine Technology and Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Portugal.
authors.forename: Bing
authors.initials: B
authors.lastname: Wu
authors.affiliation: Intelligent Transport Systems Research Center (ITSC), Wuhan University of Technology, Wuhan 430063, China; Engineering Research Center for Transportation Safety (ERCTS, MoE), Wuhan University of Technology, Wuhan, China; National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Centre for Marine Technology and Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Portugal.
authors.forename: Jinfen
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Manchester Business School, University of Manchester, Manchester M60 1QD, UK.
authors.forename: Emanuel Emil
authors.initials: EE
authors.lastname: Savan
authors.affiliation: Intelligent Transport Systems Research Center (ITSC), Wuhan University of Technology, Wuhan 430063, China; Engineering Research Center for Transportation Safety (ERCTS, MoE), Wuhan University of Technology, Wuhan, China; National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan, China.
authors.forename: Xinping
authors.initials: X
authors.lastname: Yan
mesh_terms: D000056:Accident Prevention; D002681:China; D006801:Humans; D008962:Models, Theoretical; D045483:Rivers; D012449:Safety; D012767:Ships; D062206:Spatial Analysis
keywords: DEA Model; Grey relational analysis; Maritime safety; Navigational environment factors; Spatial sequential frontiers