Operating Efficiency Evaluation of China Listed Automotive Firms: 2012–2016

Huichen Jiang, Liyan Han, Yongbin Ding and Yifan He
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Huichen Jiang: School of Economics and Management, Beihang University, Beijing 100191, China
Liyan Han: School of Economics and Management, Beihang University, Beijing 100191, China
Yongbin Ding: School of Economics and Management, Beihang University, Beijing 100191, China
Yifan He: International College, Zhengzhou University, Henan 450052, China

Sustainability, 2018, vol. 10, issue 1, 1-22

Abstract: As one of the important pillar industries in China, the automotive industry (i.e., the traditional vehicle and the new energy vehicle (NEV) sub-industries) plays a significant role in the national economy and social development. In this paper, by using the fixed assets, intangible assets, the operating expenses, and the number of employee as inputs and the operating income as output, we conduct efficiency evaluations based on data envelopment analysis (DEA) and Malmquist models, and measure the efficiency of listed automotive firms with the panel data of 77 listed A-share firms spanning from 2012 to 2016, statically and dynamically. The results show that the five-year average Malmquist indices of all the listed firms slightly decreased due to the decline of the technical change and the improvement of the efficiency change. We subdivide the automotive industry into the traditional vehicle and NEV industries, and find that the NEV industry performed better than the traditional one. We combine the industry development and efficiency evaluation, and believe that the NEV will be a new driving force of the economy.

Keywords: data envelopment analysis (DEA); Malmquist model; operating efficiency; automotive industry; new energy vehicle; traditional vehicle; total factor productivity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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