EconPapers    
Economics at your fingertips  
 

Innovative coupling and coordination: Automobile and digital industries

Shengjia Zhou, Junhao Wang and Bing Xu

Technological Forecasting and Social Change, 2022, vol. 176, issue C

Abstract: The coupling and coordination of automobile and digital industries are crucial for developing these industries and to promote the high-quality development of the automobile industry. In this study, a coupling evaluation model and a backpropagation (BP) neural network model were used to construct the coupling evolution trend of the coordinated development of these industries. The results showed that China's automobile and digital industries are coupled. 2018 was the turning point from uncoordinated to coordinated. It is predicted that the coupling coordination development degree will increase from 0.572 in 2019 to 0.739 in 2022. The main contribution of growth came from research and development investment in the automobile industry and fixed asset investment in the digital industry, which is a factor of development potential. However, the characteristic contribution of the digital industry comprised development efficiency, development potential, development scale, and development structure in the decreasing order, whereas the characteristic contribution of the automobile industry comprised the aforementioned parameters in the increasing order. The research results allow the development of industrial policies for the coupling and coordination of these industries.

Keywords: Automobile industry; Digital industry; Coupling coordination degree; BP neural network prediction (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162522000294
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:176:y:2022:i:c:s0040162522000294

DOI: 10.1016/j.techfore.2022.121497

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:tefoso:v:176:y:2022:i:c:s0040162522000294