The Analysis for the Scale and Efficiency of China¡¯s Major Automotive Enterprises Based on DEA Model

Zheng Fei and Li L. Z

Journal of Mathematics Research, 2018, vol. 10, issue 2, 129-139

Abstract: This paper uses Data Envelopment Analysis (DEA) to measure the scale and efficiency of 28 major automotive enterprises in Chinese, and the results show that at this stage, large automobile manufacturers of China are under-produced and the production is too scattered, and the overall efficiency of automobile manufacturers is low. One of the main reasons is that because of the low technical efficiency value, the technological innovation capability of enterprises needs to be strengthened. The other reason is that the low efficiency of a large number of enterprises lowers the overall efficiency level. There is a positive correlation between the scale and efficiency of automobile manufacturers. Whether it is the horizontal comparison between different enterprises (nature) or the vertical comparison between the same enterprises, all show that compared with small-scale enterprises, large-scale manufacturing enterprises not only have higher scale efficiency but also have higher technical efficiency. With the expansion of production scale, the scale of enterprises and technical efficiency have improved, which shows that for the automotive industry, compared with other factors, economies of scale is the main factor that affects the automotive industry, and not only is it reflected in the scale but also in technological innovation. Therefore, when formulating policies, the relevant departments should support the development of large-scale enterprises, encourage mergers and acquisitions among enterprises, increase R&D investment, support technological innovation, and set up a scientific market exit mechanism to reduce exit costs, such as guiding the transformation of enterprises and establish a competition mechanism for the survival of the fittest.

Keywords: DEA, automotive enterprises, scale; technical efficiency, scale efficiency (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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