Abstract
Due to the uncertainty and complexity of multilinks and multifactors in urban express logistics system, it is very difficult to analyze the risk factors and the correlation among them for urban public security. In this paper, a method combining domain knowledge and data learning is proposed to construct Bayesian network, which can effectively deal with this problem. Based on the literature review and the investigation of transportation companies, this paper summarizes the risk factors to public safety caused by pick up, warehouse storage, transport, and the end distribution in the process of urban express logistics, which are divided into 5 dimensions: management, weather, human, transportation tools and facilities, and goods, including 11 risk factors. In this paper, Interpretative Structural Model is used to construct the initial hierarchical model to describe the complex relationship between factors, and then causal mapping method is used to improve the initial model to transform the structure into the final Bayesian network model. Finally, the sensitivity of one node to other nodes is analyzed based on the incident data. The results show that Bayesian network is effective in improving urban express logistics operation ability and avoiding public safety risks and has a strong generalization ability, which is simple and easy in practical application.
Highlights
There is no unified system of the research on the risk factors affecting the public security of urban express logistics
Mathematical Problems in Engineering analysis of logistics enterprises, such as the risk cost of logistics enterprises [6], logistics outsourcing risk [7], and project logistics risk [8]. ere is no systematic study on the risks and hidden dangers of the whole logistics link to public security. e analysis of risk factors is the primary part of accident prevention because it can provide operational information for logistics-related enterprises and management departments. ey can focus on the potential risks and take preventive measures
Based on the above problems, this paper adopts the method of literature review and the survey of transportation companies to divide the factors that affect the risk of urban logistics into five dimensions: management, weather, human, transportation tools and facilities, and goods, including 11 influencing factors
Summary
Taniguchi et al [1] defined urban logistics as “in the market economy, considering the urban traffic environment, traffic congestion, and energy consumption, while private enterprises to achieve the overall optimal logistics and transport activities process.” Based on the national conditions of China, this paper gives the definition of urban logistics: urban logistics is an activity that takes improving the competitiveness of a city as the core, realizes the optimization of urban logistics and transportation activities through the application of advanced information technology, and tries to reduce the negative impact of logistics activities on urban traffic congestion, traffic environment, and energy consumption. e operation process of urban express logistics involves many links, such as pick up, warehouse storage, transport, and the end distribution, during which the business status is diverse and the risk factors are numerous, which can threaten the public security of the city. e risk of urban public security refers to the force majeure and the possibility of objective existence that threaten the basic values, norms, and interests of urban public domain [2]. e control of urban public security risks should prevent risks and potential harm caused by public security incidents from the source of risk factors. E operation process of urban express logistics involves many links, such as pick up, warehouse storage, transport, and the end distribution, during which the business status is diverse and the risk factors are numerous, which can threaten the public security of the city. Based on the above problems, this paper adopts the method of literature review and the survey of transportation companies to divide the factors that affect the risk of urban logistics into five dimensions: management, weather, human, transportation tools and facilities, and goods, including 11 influencing factors. It helps managers to enhance the scientific nature of risk management decisions, provides a new basis for improving the operational stability of urban logistics, helps to reduce the occurrence of urban public security incidents, and alleviates the potential loss of risks to society, economy, and environment.
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