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Tail dependence network of new energy vehicle industry in mainland China

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Abstract

The emerging new energy vehicles (NEV) industry is strategically important for China. How to capture its operating characteristics is a challenging but meaningful work. Considering that physical network (e.g. buyer–supplier) or correlation network (e.g. financial contagion) can provide the effective market information for enterprises in the operations management, we first construct the stock returns-based tail dependence network of the NEV industry by combining the Delta conditional value-at-risk (CoVaR) measure and the triangulated maximally filtered graph (TMFG) algorithm. We then explore the topological structure of the constructed network and obtain the operating characteristics for each enterprise in the whole industrial supply chain and at different levels. The empirical results show that the dependence and influence of different enterprises in the whole industrial supply chain are heterogeneous. In particular, upstream enterprises have closer dependence and faster influence power at all levels. These findings from the NEV industry with 71 listed enterprises would not only help regulators identify enterprises that affect the industry stability, but also help investors reduce risk across different enterprises, and managers can adjust operation strategies to reduce operating risks. On the theoretical side, we extend the network theory to the NEV industry. On the practical side, it is the first to capture the operating characteristics of the NEV industry in mainland China. In addition, on the methodological side, it constructs a new TMFG-CoVaR network.

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Acknowledgements

The authors gratefully acknowledge financial support from the National Natural Science Foundation of China (72171070, 71671056), the Humanity and Social Science Foundation of Ministry of Education of China (19YJA790035), the China Postdoctoral Science Foundation (2021M700380), and the National Statistical Science Research Projects of China (2019LD05).

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Authors and Affiliations

  1. School of Management, Hefei University of Technology, Hefei, 230009, Anhui, People’s Republic of China

    Qifa Xu & Cuixia Jiang

  2. Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, Anhui, People’s Republic of China

    Qifa Xu

  3. School of Economics & Management, University of Science and Technology Beijing, Beijing, People’s Republic of China

    Liukai Wang

  4. York Management School, University of York, Heslington, York, YO10 5DD, UK

    Fu Jia

  5. International Business School, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, People’s Republic of China

    Lujie Chen

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  1. Qifa Xu
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Correspondence to Cuixia Jiang.

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Appendix

Appendix

See Table 11.

Table 11 List of enterprises in NEVs industry
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Xu, Q., Wang, L., Jiang, C. et al. Tail dependence network of new energy vehicle industry in mainland China. Ann Oper Res 315, 565–590 (2022). https://doi.org/10.1007/s10479-022-04729-w

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