With the gradual popularization of smart devices and the prosperity of Internet technology, the domestic automobile industry is also undergoing a shift from traditional power to new energy. Although the existing new energy technology has been widely used in the automotive field, there is still a certain gap between our country's overall new energy technology innovation capability and developed countries. Finding a business model suitable for the development of new energy vehicles has become a key factor in promoting the development of the new energy vehicle industry. Therefore, this article mainly discusses the path research of data mining analysis technology in the business model innovation of new energy vehicles. First, list the current status of the existing traditional business models of 100 new energy automobile companies, and then analyze the car sales data of the A company in the 100 companies in the past five years. The total annual car sales of A company have gradually increased, from 5512 in 2017 to 9070 in 2020. In just four years, the sales of cars have increased by nearly 3500. To a certain extent, data mining technology provides decision-making support for the continuous innovation of business models of new energy automobile enterprises and brings more automobile sales to enterprises.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Path of Data Mining and Analysis Technology in New Energy Vehicle Business Model Innovation


    Additional title:

    Lecture Notes on Data Engineering and Communications Technologies


    Contributors:
    Atiquzzaman, Mohammed (editor) / Yen, Neil (editor) / Xu, Zheng (editor) / Wu, Xu (author)

    Conference:

    International conference on Big Data Analytics for Cyber-Physical-Systems ; 2021 ; Shanghai, China December 28, 2021 - December 29, 2021



    Publication date :

    2021-12-10


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English