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| Title: | 中國新能源汽車產業發展現狀及前景探析— DEA和神經網路模型
Analysis on the Current Development Status and Prospect of China`s New Energy Vehicle Industry — Based on DEA and Neural Network Model |
| Authors: | 黃舒平
Huang, Shu-Ping |
| Contributors: | 廖四郎
Liao, Szu-Lang
黃舒平
Huang, Shu-Ping |
| Keywords: | 新能源汽車
生產效率
資料包絡分析法
神經網路模型
New Energy Vehicles
Productive Efficiency
DEA
Neural Network |
| Date: | 2022 |
| Issue Date: | 2022-02-10 12:54:37 (UTC+8) |
| Abstract: | 在能源危機和環境污染的背景之下，新能源汽車憑藉其節能減排的優勢，在發展初期便得到了國家的大力扶持，隨著其市場規模的迅速擴張，國家補貼力度逐漸減小，且產業發展戰略已由“政策推動”逐漸轉變為“市場拉動”，但新能源汽車仍存在著相關基礎設施不完善、電池續航能力差等問題，還需要政府加強基礎設施建設，及相關企業加大研發力度。在政府的補貼扶持及企業的研發投入皆有限的情況下，該產業未來是否能可持續發展，則需要瞭解其投入-產出比。
本文將基於三階段DEA-Malmquist和BP神經網路模型，以中國新能源汽車上市公司為研究對象進行實證分析。首先，利用資料包絡分析法分別從靜態和動態分析中國新能源汽車產業的發展現狀；繼而，利用神經網路模型進行場景類比，預測中國新能源汽車產業未來發展的可能趨勢；最後，針對研究結果進一步探討促進該產業可持續發展的相應對策。
實證結果顯示，2016年為中國新能源汽車產業的轉折點，2013至2016年間，中國新能源汽車上市公司技術效率均值穩步提高，2017年後，則開始逐年降低，近幾年產業的規模報酬也呈現出遞減的狀態，產業動態效益亦是呈下降的趨勢。除此之外，中國新能源汽車產業未來五年的效率預測值從整體角度看，同樣是下跌的走向，可見近年來距離產業發展有效狀態的差距逐步增大，找出相應解決辦法改善現狀實為重中之重。
Under the background of energy crisis and environmental pollution, new energy vehicles are strongly supported by the state at the early stage of development by virtue of their advantages in energy conservation and emission reduction. With the rapid expansion of the market scale of the industry, the national subsidy has decreased gradually. The industrial development strategy has been gradually transformed from "Policy-driven" to "Market-driven". However, there are still some problems about new energy vehicles, such as imperfect infrastructure and poor battery life. In the case of limited government subsidies and enterprises` investment in research and development, the sustainable development of the industry is determined by the input-output ratio.
The paper is based on the Three-stage DEA-Malmquist and the BP neural network model. Chinese listed companies about new energy vehicles are taken as the research subject for empirical analysis. Firstly, the development status of the Chinese new energy vehicle industry is analyzed through data envelopment analysis from static and dynamic aspects. Then, the neural network model is adopted to simulate the scene and predict the possible development trend of the Chinese new energy vehicle industry in the future. Finally, the corresponding countermeasures to promote the sustainable development of the industry are further discussed.
The empirical results show that the year of 2016 was the turning point of the Chinese new energy vehicle industry. From 2013 to 2016, the average technical efficiency of Chinese listed companies about new energy vehicles grew steadily. It began to decrease year by year after 2017. In recent years, the return to scale and the dynamic benefits of the industry has also been in a decreasing state. In addition, the predicted efficiency of the Chinese new energy vehicle industry in the next five years is also on a downward trend from an overall perspective. It can be seen that the gap from the effective state of industrial development has gradually increased in recent years. It is vital to make corresponding solutions to improve the status. |
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| Description: | 碩士
國立政治大學
金融學系
108352037 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0108352037 |
| Data Type: | thesis |
| DOI: | 10.6814/NCCU202200102 |
| Appears in Collections: | [金融學系] 學位論文
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