| Title |
Enhancing Operating Efficiency in China's High-End Equipment Manufacturing Industry: Insights from Listed Enterprises |
| ID_Doc |
68622 |
| Authors |
Zheng, Y; Luo, M |
| Title |
Enhancing Operating Efficiency in China's High-End Equipment Manufacturing Industry: Insights from Listed Enterprises |
| Year |
2023 |
| Published |
Sustainability, 15, 11 |
| DOI |
10.3390/su15118694 |
| Abstract |
The high-end equipment manufacturing industry is a strategic sector for China's manufacturing transformation and upgrading. However, this industry is facing a series of challenges, such as insufficient innovation capabilities and poor business operations. This paper uses the super-efficiency SBM model to calculate the operating efficiency of listed companies in this industry from a micro perspective and conducts in-depth multi-angle analysis of their operating efficiency. Furthermore, Tobit regression is utilized to identify the factors that affect operating efficiency. The aim is to provide a pathway for companies in this industry to achieve efficiency maximization and sustainable development. The research shows that the average operating efficiency of high-end equipment manufacturing companies was around 0.7 from 2016 to 2021, and nearly 70% of companies were in a non-DEA efficient state. The operating efficiency of the intelligent manufacturing equipment industry is far higher than other industries, and the western region has great development potential. In addition to government subsidies, factors such as company age, equity concentration, regional GDP, and regional openness all have a positive impact on the operational efficiency of high-end equipment manufacturing companies. This paper combines the characteristics of the equipment manufacturing industry and analyzes their operating efficiency from multiple dimensions, providing decision support and pathways for the high-quality and efficient development of this industry. |
| Author Keywords |
high-end equipment manufacturing; operating efficiency; super-efficiency SBM; government subsidies |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:001006273800001 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Sciences; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
https://www.mdpi.com/2071-1050/15/11/8694/pdf?version=1685339342
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