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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Risk assessment for yachting tourism in China using dynamic Bayesian networks
Yunhao Yao1, Xiaoxing Zhou1, Merle Parmak1
1School of Public Administration & Humanities, Dalian Maritime University, Dalian, Liaoning, P.R. China.
Abstract:
Scientific evaluation of yachting tourism safety risks (YTSRs) is crucial to reducing accidents in this sector. This paper is based on the data of 115 yachting tourism accidents in China's coastal areas from 2008 to 2021. A fishbone diagram and the analytic hierarchy process (AHP) were used to identify the risk factors of yachting tourism from four aspects human, yachting, environmental, and management risk and to construct an evaluation index system. To perform dynamic evaluation, a dynamic evaluation model of YTSRs was built using dynamic Bayesian networks (DBN). The results indicate that human factors, such as the unsafe behavior of yachtsmen and tourists, are the primary risk factors; the risk is higher in summer than in winter, and the Pearl River Delta region has a greater risk of yachting tourism. It is suggested to improve the normal safety risk prevention and control system of yachting tourism, to advocate for multi-subject coordination and co-governance, and to improve the insurance service system so as to provide a guarantee for the safe and healthy development of yachting tourism in China. The findings provide theoretical and practical guidance for marine and coastal tourism safety management, as well as the prevention and control of YTSRs.
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