Evaluate the sustainable marketing strategy to optimal online leasing of new energy vehicles under the background big data economy

PurposeUnder 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/approachThe 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.FindingsWith 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/implicationsThe 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 implicationsAs 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/valueThis 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.

Deep Learning-Based Economic Forecasting for the New Energy Vehicle Industry

Recently the issues of insufficient energy and serious air pollution around the world have been rising. Henceforth, there is a need to carry out a research of new energy. Soon, new energy vehicles will be the mainstream trend, which can not only reduce the burden of consumers due to rising fuel prices but also solve the air pollution problem caused by the exhaust emissions of fuel vehicles. With the rapid development of science and technology, deep learning continues to make breakthroughs, and, in the field of economy with huge information data, we have more powerful weapons available to predict and research important economic data with infinite value, which can not only provide reference information to policy makers but also help enterprises and even economic markets to develop more healthily and sustainably. Therefore, this article uses deep learning algorithms to forecast and analyze the new energy industry, starting from the financial information released by new energy vehicle companies in their annual reports, in order to make basic judgments and help policy makers and enterprises in the new energy vehicle industry.

Research on Consumer purchasing Preference and Marketing Strategy of Electric vehicle industry in China

Electric vehicles are the future. All countries around the world are promoting the construction of new energy vehicles. China is one of the big countries that even set a goal to achieve 100% electric car in 2050. Recently, China’s new energy vehicles appear spurt growth phenomenon, and countless manufacturers frantically expand their turf into the electric vehicle competition. Among many manufacturers, BYD and Tesla, as the two major brands in China, are in fierce competition. In this paper, consumers’ purchasing preferences are investigated through a questionnaire survey, and the current product characteristics of different new energy vehicle companies are also analyzed. Besides, the advantages and disadvantages of Tesla and BYD are mainly analyzed by comparing the marketing strategies. This paper aims to find the development direction and marketing strategies of future new energy vehicles.

Experimental Research on Braking Feedback and Taxiing Feedback System of New Energy Vehicles

This paper took a new energy vehicle feedback system as the research object, aiming to study the energy recovery law of the new energy vehicle under braking feedback and taxiing feedback conditions. Firstly, the braking energy feedback control strategy and different forms of taxiing energy feedback were studied. Then the integration and application of braking energy recovery system were carried out on a pure electric bus and a hybrid electric bus, with each vehicle model corresponding to different integration and test schemes, which provided a guarantee for the relevant test of real vehicle environments. Finally, relevant vehicle experiments were carried out to test the impact of superposition and coordination strategies on the contribution rate of braking energy recovery under a typical Chinese city bus circle and compared the difference in vehicle energy consumption with and without taxi feedback strategy. The test results showed that the coordinated braking energy recovery control strategy can make more effective use of the maximum torque that can be fed back by the motor, and the fuel consumption of the taxiing feedback mode was lower than that of the no taxiing feedback mode under different driving conditions.