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Analysis of Technological Innovation Efficiency in Listed New Energy Vehicle Enterprises Under the Carbon Neutrality Framework Based on Two-Stage Dynamic Network DEA and a GRA Model

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Bibliographic Details
Title: Analysis of Technological Innovation Efficiency in Listed New Energy Vehicle Enterprises Under the Carbon Neutrality Framework Based on Two-Stage Dynamic Network DEA and a GRA Model
Authors: Zhihua Ruan, Zhikun Liu
Source: World Electric Vehicle Journal, Vol 16, Iss 11, p 635 (2025)
Publisher Information: MDPI AG, 2025.
Publication Year: 2025
Collection: LCC:Electrical engineering. Electronics. Nuclear engineering
LCC:Transportation engineering
Subject Terms: new energy vehicles, technological innovation efficiency, two-stage dynamic network (DEA), grey relational analysis (GRA), Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Transportation engineering, TA1001-1280
Description: Technological innovation and the efficiency of resource allocation in Chinese new energy vehicle enterprises represent critical factors influencing the sustainable development of the industry. By applying a two-stage dynamic network DEA model to analyze the comprehensive and stage-specific technological innovation efficiency of 13 A-share-listed new energy vehicle enterprises between 2017 and 2024, this study reveals that both overall and phase-specific innovation efficiencies remain below optimal levels. Moreover, the average technological R&D efficiency across these firms is found to be lower than their average achievement transformation efficiency, highlighting the urgent need to improve innovation performance in this sector. Grey relational analysis of influencing factors identifies six key determinants of technological innovation efficiency: the shareholding ratio of the largest shareholder, R&D investment intensity, the proportion of employees holding bachelor’s degrees or higher, management capability, return on equity, and total asset turnover. In comparison, government subsidies and total assets exhibit relatively limited influence on technological innovation efficiency.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2032-6653
Relation: https://www.mdpi.com/2032-6653/16/11/635; https://doaj.org/toc/2032-6653
DOI: 10.3390/wevj16110635
Access URL: https://doaj.org/article/b5b0ce0bb2514f78b7166cb888a68bfb
Accession Number: edsdoj.b5b0ce0bb2514f78b7166cb888a68bfb
Database: Directory of Open Access Journals
Description
Abstract:Technological innovation and the efficiency of resource allocation in Chinese new energy vehicle enterprises represent critical factors influencing the sustainable development of the industry. By applying a two-stage dynamic network DEA model to analyze the comprehensive and stage-specific technological innovation efficiency of 13 A-share-listed new energy vehicle enterprises between 2017 and 2024, this study reveals that both overall and phase-specific innovation efficiencies remain below optimal levels. Moreover, the average technological R&D efficiency across these firms is found to be lower than their average achievement transformation efficiency, highlighting the urgent need to improve innovation performance in this sector. Grey relational analysis of influencing factors identifies six key determinants of technological innovation efficiency: the shareholding ratio of the largest shareholder, R&D investment intensity, the proportion of employees holding bachelor’s degrees or higher, management capability, return on equity, and total asset turnover. In comparison, government subsidies and total assets exhibit relatively limited influence on technological innovation efficiency.
ISSN:20326653
DOI:10.3390/wevj16110635