Proceedings of the 2024 9th International Conference on Social Sciences and Economic Development (ICSSED 2024)

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Research on the Digital Transformation Path of the Automotive Industry Driven by Big Data

——Multi case analysis based on grounded theory

Authors
Danyu Zhu1, *
1Wuhan University of Technology, Wuhan, 430070, China
*Corresponding author. Email: 1991218289@qq.com
Corresponding Author
Danyu Zhu
Available Online 23 July 2024.
DOI
10.2991/978-94-6463-459-4_82How to use a DOI?
Keywords
digital transformation; Transformation path; Rooted theory
Abstract

The development of technology and the increase in demand are driving the digital transformation of China's automotive industry. Digital technology is fully integrated into the entire lifecycle operation system of automotive companies. Therefore, the Chinese automotive industry urgently needs to seek high-quality and efficient digital transformation paths. This article is based on the grounded theory to sort out and analyze the development paths of three typical new energy vehicle companies in China at different stages, and concludes that: firstly, big data drives the digital transformation of the automotive industry mainly through key link transformation and basic element empowerment to promote the optimization and restructuring of the automotive industry chain; Secondly, the transformation of key links is the core of promoting the optimization and reconstruction of the automotive industry chain, and the empowerment of basic elements provides basic resources for promoting the automotive industry chain; Thirdly, innovation in the value proposition of on chain enterprises includes strategic collaboration and resource sharing, both of which play an intermediary role in promoting the optimization and reconstruction of the automotive industry chain through big data technology, improving the efficiency of enterprise transformation.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 9th International Conference on Social Sciences and Economic Development (ICSSED 2024)
Series
Advances in Economics, Business and Management Research
Publication Date
23 July 2024
ISBN
10.2991/978-94-6463-459-4_82
ISSN
2352-5428
DOI
10.2991/978-94-6463-459-4_82How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Danyu Zhu
PY  - 2024
DA  - 2024/07/23
TI  - Research on the Digital Transformation Path of the Automotive Industry Driven by Big Data
BT  - Proceedings of the 2024 9th International Conference on Social Sciences and Economic Development (ICSSED 2024)
PB  - Atlantis Press
SP  - 726
EP  - 732
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-459-4_82
DO  - 10.2991/978-94-6463-459-4_82
ID  - Zhu2024
ER  -