THE DEVELOPMENT MODELS OF CHINA’S NEW ENERGY VEHICLE INNOVATION CONSORTIUMS: CASE ANALYSES OF CHANGAN
Volume 3, Issue 1, Pp 11-18, 2026
DOI: https://doi.org/10.61784/jtfe3068
Author(s)
TianChen Yang
Affiliation(s)
Shanghai University of Engineering Science, Shanghai 201620, China.
Corresponding Author
TianChen Yang
ABSTRACT
Against the strategic backdrop of the "dual carbon" goals, the new energy vehicle (NEV) industry has become a core sector driving energy transition and low-carbon development in the transportation sector. Innovation consortia, as collaborative innovation organizations integrating enterprises, universities, research institutes, and government resources, are of great significance for breaking through key generic technologies and enhancing industrial innovation capabilities. This study selects Changan Automobile as a case study, comprehensively employing case analysis and evolutionary game models to systematically investigate the internal and external challenges it faces in the process of building an NEV innovation consortium, the cooperation mechanisms it adopts, and its game strategies. By constructing a two-party game model between the enterprise and research institutions, the analysis focuses on the impact of key parameters such as total cooperation benefits and profit distribution ratios on the stability of bilateral cooperation. The findings reveal that: the increase in cooperation benefits and the fairness of the distribution mechanism are core elements for the stable operation of innovation consortia; the technology integration and resource coordination capabilities of leading enterprises play a dominant role in the consortium's effectiveness; and the design of systematic cooperation mechanisms (including benefit distribution, risk sharing, breach penalties, and communication and coordination mechanisms) constitutes an important foundation for ensuring the long-term development and sustained innovation capability of the consortium. Accordingly, this paper proposes managerial recommendations such as establishing a reasonable benefit distribution mechanism, increasing government investment in R&D, and accelerating the formation of innovation consortia, aiming to provide theoretical support and practical references for the collaborative innovation and high-quality development of China's NEV industry.
KEYWORDS
Innovation consortium; Industry-university-research collaboration; Evolutionary game theory; Collaborative innovation
CITE THIS PAPER
TianChen Yang. The development models of China’s new energy vehicle innovation consortiums: case analyses of Changan. Journal of Trends in Financial and Economics. 2026, 3(1): 11-18. DOI: https://doi.org/10.61784/jtfe3068.
REFERENCES
[1] Ren Qiuzhen, Li Jinkai, Johan Albrecht. Toward circular economy: Implementing circular economy strategies to reduce carbon emissions in Chinese cities. Business Strategy and the Environment, 2025, 34(1): 914-931. DOI: 10.1002/bse.4019.
[2] Bergougui B, Murshed S M, Shahbaz M, et al. Towards secure energy systems: Examining asymmetric impact of energy transition, environmental technology and digitalization on Chinese city-level energy security. Renewable Energy, 2025, 238: 121883. DOI: 10.1016/j.renene.2024.121883.
[3] Mahdad M, Roshani S. The open innovation kaleidoscope: navigating pathways and overcoming failures. Review of Managerial Science, 2025, 19(6): 1637-1668. DOI: 10.1007/s11846-024-00804-7.
[4] Serrano-Ruiz J C, Ferreira J, Jardim-Goncalves R, et al. Relational network of innovation ecosystems generated by digital innovation hubs: a conceptual framework for the interaction processes of DIHs from the perspective of collaboration within and between their relationship levels. Journal of Intelligent Manufacturing, 2025, 36(3): 1505-1545. DOI: 10.1007/s10845-024-02322-5.
[5] Jialin Shen, Zhang Qi, Tian Shuoshuo. Decarbonization pathways analysis and recommendations in the green steel supply chain of a typical steel end user-automotive industry. Applied Energy, 2025, 377: 124711. DOI: 10.1016/j.apenergy.2024.124711.
[6] Godfrey Yeung, Liu Yi. Hybrid governance of joint ventures in transitional economies: The case of Guangzhou Automobile Group in China. Review of International Political Economy, 2023, 30(3): 1177-1201. DOI: 10.1080/09692290.2022.2062033.
[7] Schuhmacher A, Gassmann O, Bieniok D, et al. Open innovation: A paradigm shift in pharma R&D? Drug Discovery Today, 2022, 27(9): 2395-2405. DOI: 10.1016/j.drudis.2022.05.018.
[8] Cheng Qiang, Peng Chun, Wan Huaxin, et al. How to realize digital knowledge innovation through digital technology? A perspective based on knowledge digitization and inter-organizational knowledge sharing. Technology in Society, 2025, 82: 102905. DOI: 10.1016/j.techsoc.2025.102905.
[9] Rahman H A, Karunakaran A, Cameron L D. Taming platform power: Taking accountability into account in the management of platforms. Academy of Management Annals, 2024, 18(1): 251-294. DOI: 10.5465/annals.2022.0090.
[10] Basole R C, Park H, Seuss C D. Complex business ecosystem intelligence using AI-powered visual analytics. Decision Support Systems, 2024, 178: 114133. DOI: 10.1016/j.dss.2023.114133.
[11] Lv L, Zhao A. A Multi-party Evolutionary Game Study of Green Behaviour of Construction Industry Practitioners considering Consumer Preferences. Energy, 2025: 137866. DOI: 10.1016/j.energy.2025.137866.
[12] Zhao Hui, Cheng Xian, Gao Jing, et al. A study on risk sharing of smart city PPP projects based on EW-G1 and TOPSIS-UT: a case study in China. Kybernetes, 2025, 54(3): 1470-1494. DOI: 10.1108/K-05-2023-0824.
[13] Zhu Yuchen. Research on evolutionary game of digital twin data information sharing based on blockchain technology. Measurement and Control, 2025, 58(1): 24-49. DOI: 10.1177/00202940241245035.
[14] Xie Deru, Zhang Huiqin, Zhang Yuxiang, et al. Applications of autonomous driving technology in ride-hailing service platform: based on multi-party evolutionary game analysis. Computers & Industrial Engineering, 2025: 111339. DOI: 10.1016/j.cie.2025.111339.
[15] Hanisch M, Graf‐Vlachy L, Haeussler C, et al. Kindred spirits: Cognitive frame similarity and good faith provisions in strategic alliance contracts. Strategic Management Journal, 2025, 46(2): 436-469. DOI: 10.1002/smj.3660.
[16] Song Yu, Chen Bo, Wang Xinyi. Cryptocurrency technology revolution: are Bitcoin prices and terrorist attacks related? Financial innovation, 2023, 9(1): 29. DOI: 10.1186/s40854-022-00445-3.
[17] Micek G, Gwosdz K, Kocaj A, et al. The role of critical conjunctures in regional path creation: a study of Industry 4.0 in the Silesia region. Regional Studies, Regional Science, 2022, 9(1): 23-44. DOI: 10.1080/21681376.2021.2017337.
[18] Nie Shiqi, Cao Xiaojing, Li Zilong, et al. Supply chain digitization in the net-zero era: The impact of digital technology, renewable energy, and infrastructure. Energy Economics, 2025, 144: 108403. DOI: 10.1016/j.eneco.2025.108403.
[19] Tollefson J. What the rise of ‘arpa-everything’will mean for science. Nature, 2021, 595: 483-484. DOI: 10.1038/d41586-021-01878-z.
[20] Li Qiang, Ulissi U, Liang Zibin, et al. Progress and Prospect of Industrialization of Sodium‐Ion Battery in China. Advanced Energy Materials, 2025: e04877. DOI: 10.1002/aenm.202504877.
[21] Yao Yongzheng, Tan Luyao, Chen Fang, et al. Hydrogen energy industry in China: The current status, safety problems, and pathways for future safe and healthy development. Safety Science, 2025, 186: 106808. DOI: 10.1016/j.ssci.2025.106808.
[22] Marti C L, Liu Huimin, Kour G, et al. Leveraging artificial intelligence in firm-generated online customer communities: a framework and future research agenda. Journal of Service Management, 2024, 35(3): 438-458. DOI: 10.1108/JOSM-10-2023-0443.
[23] Di Kaixiong, Xu Runhan, Liu Zuankuo, et al. How do enterprises’ green collaborative innovation network locations affect their green total factor productivity? Empirical analysis based on social network analysis. Journal of Cleaner Production, 2024, 438: 140766. DOI: 10.1016/j.jclepro.2024.140766.
[24] Eisenhardt K M, Graebner M E. Theory building from cases: Opportunities and challenges. Academy of management journal, 2007, 50(1): 25-32. DOI: 10.5465/amj.2007.24160888.
[25] Davis J P, Eisenhardt K M, Bingham C B. Developing theory through simulation methods. Academy of management review, 2007, 32(2): 480-499. DOI: 10.5465/amr.2007.24351453.
[26] Jacobides M G, Cennamo C, Gawer A. Towards a theory of ecosystems. Strategic management journal, 2018, 39(8): 2255-2276. DOI: 10.1002/smj.2904.

Download as PDF