| 研究生: |
邱聖真 Chiu, Sheng-Chen |
|---|---|
| 論文名稱: |
新能源汽車發展趨勢下中國車廠之效率分析 An Efficiency Analysis of Chinese Automakers under the Development Trend of New Energy Vehicles |
| 指導教授: |
林泰宇
Lin, Tai-Yu |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 企業管理學系 Department of Business Administration |
| 論文出版年: | 2025 |
| 畢業學年度: | 113 |
| 語文別: | 英文 |
| 論文頁數: | 92 |
| 中文關鍵詞: | 新能源汽車 、中國車廠 、營運效率 、永續發展 |
| 外文關鍵詞: | New Energy Vehicles (NEVs), Chinese Automakers, Operational Efficiency, Sustainable Development |
| 相關次數: | 點閱:32 下載:10 |
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隨著氣候變遷與碳中和目標逐漸成為全球共識,汽車產業正面臨能源轉型的重大壓力。新能源汽車因此應運而生,成為各國政府積極推動的重點產業之一。中國憑藉政策扶持與完整供應鏈優勢,迅速崛起為全球最大新能源車市場。然而,在補貼退場與市場驅動轉型過程中,各車廠效率表現差異顯著,亟需系統性分析以辨識其轉型成效與潛在瓶頸。
本研究採用雙階段資料包絡分析法(Two-stage DEA),建構結合跨期變數與方向性距離函數的 RDM DDF 模型,評估中國 15 家新能源車廠於 2020 至 2022 年間在營運階段和市場與ESG 階段的效率表現,並進一步納入特斯拉作為國際標竿進行比較。研究結果顯示:(1) 共7家車廠三年總效率值皆達 1,包含比亞迪、理想等標竿企業。(2) 電動車導向企業在二階段效率表現皆明顯優於傳統燃油導向企業,顯示新能源導向有助提升效率。(3) 效率於2022年普遍下降,顯示企業在面對外部挑戰,維持轉型成果的能力仍顯不足。(4) 納入特斯拉後,多數企業效率出現明顯下降,凸顯其在營運與永續方面的強勢地位,具標竿參考價值。
本研究揭示中國車廠在新能源趨勢下的效率結構與差異,亦透過進一步之群體分析提供管理與政策建議,期望能協助企業朝向更穩健的永續轉型
As climate change and carbon neutrality goals become a global consensus, the automotive industry is facing mounting pressure to undergo an energy transition. In response, new energy vehicles (NEVs) have emerged as a key industry promoted by governments worldwide. Leveraging policy incentives and a well-established supply chain, China has rapidly become the world’s largest NEV market. However, as government subsidies are gradually phased out and the market becomes the primary driving force, significant disparities in operational efficiency have emerged among automakers, necessitating a systematic analysis to identify transformation outcomes and potential bottlenecks.
This study employs a two-stage Data Envelopment Analysis (DEA) framework, integrating carry-over variables and a Range Directional Measure–Directional Distance Function (RDM DDF) model. The analysis evaluates the operational and market/ESG efficiency of 15 NEV automakers from 2020 to 2022, with Tesla included as an international benchmark. The main findings are as follows: (1) Seven automakers—including BYD and Li Auto—achieved full efficiency across all three years, serving as industry benchmarks. (2) Firms oriented toward electric vehicle production significantly outperformed traditional fuel-oriented automakers, indicating that NEV-oriented strategies contribute to efficiency gains. (3) A general decline in efficiency was observed in 2022, indicating that firms still lack the ability to maintain transformation outcomes when facing external challenges. (4) Upon the inclusion of Tesla in the analysis, most firms exhibited a marked decrease in efficiency, underscoring Tesla’s competitive advantage in operational integration and sustainability performance.
This study reveals structural differences in efficiency under the NEV transition trend and provides management and policy recommendations to support a more stable and sustainable transformation.
Baars, J., Domenech, T., Bleischwitz, R., Melin, H. E., & Heidrich, O. (2021). Circular economy strategies for electric vehicle batteries reduce reliance on raw materials. Nature Sustainability, 4(1), 71-79. https://doi.org/10.1038/s41893-020-00607-0
Baik, Y., Hensley, R., Hertzke, P., & Knupfer, S. (2019). Making electric vehicles profitable. McKinsey. In.
Bibra, E. M., Connelly, E., Gorner, M., Lowans, C., Paoli, L., Tattini, J., & Teter, J. (2021). Global EV Outlook 2021: Accelerating ambitions despite the pandemic.
Bloomberg, N. (2019). Electric vehicle outlook 2019. Bloomberg New Energy Finance.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
Cheng, Y., & Fan, T. (2021). Production coopetition strategies for an FV automaker and a competitive NEV automaker under the dual-credit policy. Omega, 103, 102391. https://doi.org/https://doi.org/10.1016/j.omega.2020.102391
Ding, L., Zhu, X., & Qiu, Y. (2023). Effects of dual-credit policy and subsidy cancellation on decisions in an automotive supply chain. Journal of Cleaner Production, 427, 139143. https://doi.org/https://doi.org/10.1016/j.jclepro.2023.139143
Du, Y., Guo, Z., & Bao, H. (2024). Smooth sailing ahead? Policy options for China's new energy vehicle industry in the post-subsidy era. Energy Research & Social Science, 107, 103359. https://doi.org/https://doi.org/10.1016/j.erss.2023.103359
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the royal statistical society series a: statistics in society, 120(3), 253-281.
Gao, Y., Hu, Y., Liu, X., & Zhang, H. (2021). Can public R&D subsidy facilitate firms’ exploratory innovation? The heterogeneous effects between central and local subsidy programs. Research Policy, 50(4), 104221. https://doi.org/https://doi.org/10.1016/j.respol.2021.104221
Han, J., Guo, J.-E., Cai, X., Lv, C., & Lev, B. (2022). An analysis on strategy evolution of research & development in cooperative innovation network of new energy vehicle within policy transition period. Omega, 112, 102686. https://doi.org/https://doi.org/10.1016/j.omega.2022.102686
He, H., Li, S., Wang, S., Chen, Z., Zhang, J., Zhao, J., & Ma, F. (2021). Electrification decisions of traditional automakers under the dual-credit policy regime. Transportation Research Part D: Transport and Environment, 98, 102956. https://doi.org/https://doi.org/10.1016/j.trd.2021.102956
He, H., Zhang, C., Li, S., Sun, Y., Zhang, J., & Sun, Q. (2022). Dual-credit price variation and optimal electrification timing of traditional automakers: A dynamic programming approach. Journal of Cleaner Production, 353, 131593. https://doi.org/https://doi.org/10.1016/j.jclepro.2022.131593
Hu, J.-L., & Wang, S.-C. (2006). Total-factor energy efficiency of regions in China. Energy Policy, 34(17), 3206-3217.
Hu, S., Liu, Z., Tan, Y., Cheng, X., Chen, Z., & Long, Z. (2022). The status quo and future trends of new energy vehicle power batteries in China — Analysis from policy perspective. Energy Reports, 8, 63-80. https://doi.org/https://doi.org/10.1016/j.egyr.2022.09.082
Huang, B., Li, H., Liu, J., & Lei, J. (2023). Digital technology innovation and the high-quality development of Chinese enterprises: Evidence from enterprise’s digital patents. Economic Research Journal, 58(03), 97-115.
Jiang, Z. (2019). Research on the Levirate Marriage for the Han Chinese during Yuan Dynasty. Asian Social Science, 15(8), 104-104.
Jing, P., Shao, D., Liu, Y., Chen, Y., & Zhang, S. (2025). Linking short- and long-term impacts of the government, consumers, and manufacturers on NEV sales and market share in China. Journal of Retailing and Consumer Services, 82, 104090. https://doi.org/https://doi.org/10.1016/j.jretconser.2024.104090
Lee, J., Hwang, J., & Kim, H. (2022). Different government support effects on emerging and mature ICT sectors. Technological Forecasting and Social Change, 174, 121253. https://doi.org/https://doi.org/10.1016/j.techfore.2021.121253
Li, J. (2020). Charging Chinese future: the roadmap of China's policy for new energy automotive industry. International Journal of Hydrogen Energy, 45(20), 11409-11423. https://doi.org/https://doi.org/10.1016/j.ijhydene.2020.02.075
Lin, B., & Xie, Y. (2024). Effect of renewable energy subsidy policy on firms’ total factor productivity: The threshold effect. Energy Policy, 192, 114241. https://doi.org/https://doi.org/10.1016/j.enpol.2024.114241
Liu, C., Liu, Y., Zhang, D., & Xie, C. (2022). The capital market responses to new energy vehicle (NEV) subsidies: An event study on China. Energy Economics, 105, 105677. https://doi.org/https://doi.org/10.1016/j.eneco.2021.105677
Ma, M., Meng, W., Li, Y., & Huang, B. (2023). Impact of dual credit policy on new energy vehicles technology innovation with information asymmetry. Applied Energy, 332, 120524. https://doi.org/https://doi.org/10.1016/j.apenergy.2022.120524
Pei, L., Kong, H., & Xu, Y. (2023). Government subsidies, dual-credit policy, and enterprise performance: Empirical evidence from Chinese listed new energy vehicle companies. Chinese Journal of Population, Resources and Environment, 21(2), 71-81. https://doi.org/https://doi.org/10.1016/j.cjpre.2023.06.004
Pi, Z., Wang, K., Wei, Y.-M., & Huang, Z. (2024). Transitioning from gasoline to electric vehicles: Electrification decision of automakers under purchase and station subsidies. Transportation Research Part E: Logistics and Transportation Review, 188, 103640. https://doi.org/https://doi.org/10.1016/j.tre.2024.103640
Portela, M. S., Thanassoulis, E., & Simpson, G. (2004). Negative data in DEA: A directional distance approach applied to bank branches. Journal of the operational research society, 55(10), 1111-1121.
Qin, S., & Xiong, Y. (2022). Innovation strategies of Chinese new energy vehicle enterprises under the influence of non-financial policies: Effects, mechanisms and implications. Energy Policy, 164, 112946. https://doi.org/https://doi.org/10.1016/j.enpol.2022.112946
Qin, S., & Xiong, Y. (2024). Differences in the innovation effectiveness of China's new energy vehicle industry policies: A comparison of subsidized and non-subsidized policies. Energy, 304, 132151. https://doi.org/https://doi.org/10.1016/j.energy.2024.132151
Tang, J., & Wu, Q. (2024). Fast or stable: Research on dynamic behaviors of duopoly automakers under the background of energy transformation in the automobile industry. Heliyon, 10(6), e27711. https://doi.org/https://doi.org/10.1016/j.heliyon.2024.e27711
Tavana, M., Izadikhah, M., Di Caprio, D., & Farzipoor Saen, R. (2018). A new dynamic range directional measure for two-stage data envelopment analysis models with negative data. Computers & Industrial Engineering, 115, 427-448. https://doi.org/https://doi.org/10.1016/j.cie.2017.11.024
Wang, N., Shang, K., Duan, Y., & Qin, D. (2023). Carbon quota allocation modeling framework in the automotive industry based on repeated game theory: A case study of ten Chinese automotive enterprises. Energy, 279, 128093. https://doi.org/https://doi.org/10.1016/j.energy.2023.128093
Wang, R., Zhao, X., Wang, W., & Jiang, L. (2021). What factors affect the public acceptance of new energy vehicles in underdeveloped regions? A case study of Gansu Province, China. Journal of Cleaner Production, 318, 128432. https://doi.org/https://doi.org/10.1016/j.jclepro.2021.128432
Wang, Y., Lu, T., & Qiao, Y. (2025). Visible hands: The impact of subsidy withdrawal on new energy vehicle enterprises’ innovation behaviors. Energy Policy, 198, 114466. https://doi.org/https://doi.org/10.1016/j.enpol.2024.114466
Yu, M., Hui, Y., & Pan, H. (2010). Political connections, rent seeking, and the fiscal subsidy efficiency of local governments. Economic Research Journal, 3(1), 65-77.
Zahoor, A., Yu, Y., Zhang, H., Nihed, B., Afrane, S., Peng, S., Sápi, A., Lin, C. J., & Mao, G. (2023). Can the new energy vehicles (NEVs) and power battery industry help China to meet the carbon neutrality goal before 2060? Journal of Environmental Management, 336, 117663. https://doi.org/https://doi.org/10.1016/j.jenvman.2023.117663
Zhang, W., Luo, R., Mao, Q., & Zhu, Z. (2024). Optimal production cooperation strategies for automakers considering different sales channels under dual credit policy. Computers & Industrial Engineering, 187, 109769. https://doi.org/https://doi.org/10.1016/j.cie.2023.109769
Zhao, Y., Jian, Z., & Du, Y. (2024). How can China's subsidy promote the transition to electric vehicles? Renewable and Sustainable Energy Reviews, 189, 114010. https://doi.org/https://doi.org/10.1016/j.rser.2023.114010