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Article
Publication date: 16 August 2019

Xueyan Yang, Changxi Ma, Changfeng Zhu, Bo Qi, Fuquan Pan and Chengming Zhu

For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the…

3117

Abstract

Purpose

For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.

Design/methodology/approach

The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.

Findings

By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.

Originality/value

Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.

Details

Journal of Intelligent and Connected Vehicles, vol. 2 no. 1
Type: Research Article
ISSN: 2399-9802

Keywords

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Article
Publication date: 11 January 2022

Tang Daifen

Under the big data background, there are many influencing factors for investors of new energy vehicles (NEV), and government subsidies promote the sustainable development of the…

757

Abstract

Purpose

Under the big data background, there are many influencing factors for investors of new energy vehicles (NEV), and government subsidies promote the sustainable development of the new energy vehicle industry. Therefore, the purpose of the study is to provide solutions for the sustainable development of NEV.

Design/methodology/approach

The sustainable marketing strategy of NEV in China is put forward. This paper first analyzes the subsidy policy effect of NEV under the background of big data. It then establishes the online optimal leasing strategy under multiple strategy choices and the online leasing strategy of multiple vehicles under the inflation market.

Findings

With the fixed cost of NEV in each lease period, the optimal competition ratio of online decision-makers will continue to decrease with the increase of the difference between prepaid funds and government subsidies. In the decision-making of renting and purchasing multiple vehicles, the general strategy competition ratio is 2.922, while the optimal competition ratio of the online renting and purchasing strategy proposed by the research is 2.723.

Research limitations/implications

The research is limited by the limited data and information collected, so the optimal decision-making model has some limitations. The authors need to find more representative data to optimize the model.

Practical implications

As an emerging industry, NEV have developed rapidly in recent years. Based on the online algorithm and competitive ratio theory, this paper solves the decision-making problem of operators and gives the optimal strategy to promote the green development of the new energy vehicle industry.

Originality/value

This paper proposes the optimal strategy for online investors of new energy vehicle operators by combining online algorithm and competitive ratio theory. The numerical analysis results of the optimal online model under multi strategy selection show that with the same difference between prepaid funds and government subsidies, the time point will be delayed and the time point will be advanced as the cost of leasing NEV in each period increases.

Details

Journal of Enterprise Information Management, vol. 35 no. 4/5
Type: Research Article
ISSN: 1741-0398

Keywords

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