Sustained operational efficiency analysis of loss-making high-tech manufacturing enterprises
Bibliographic Data
| ID | 6455565 |
|---|---|
| Authors | Xu Tian (0000-0001-8153-268X, corresponding author), Yan Wang (0009-0009-9633-0023), Hongying Li (0009-0005-9926-7200) |
| Year | 2025 |
| Volume | 10 |
| Pages | 101500-101500 |
| Publication date | 2025-11-11 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Futures (JOURNAL) |
| Journal identifiers | ISSN: 2666-1888 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.sftr.2025.101500 |
| OpenAlex | W7104601295 |
| Language | EN |
| References cited | 22 |
In order to evaluate the sustained operating efficiency of Chinese listed loss-making high-tech manufacturing enterprises and how the environment affects their operating efficiency, this study employs a three-stage Data Envelopment Analysis (DEA) model. It seeks to measure the sustained operating efficiency of 472 listed loss-making high-tech manufacturing enterprises from 2015 to 2020. The results indicate that the external environment enhances the overall efficiency of high-tech manufacturing enterprises facing significant loss-making. Most loss-making enterprises in the eastern, central, and western regions are relatively ineffective, with little notable difference between them. In addition, there is an inverse relationship between the number of loss-making and enterprise efficiency. Enterprises with state-owned equity are less susceptible to environmental influences. Still, there is no significant difference in the influence of enterprises with high or low ownership concentration. Moreover, the analysis of slack variables reveals that the low efficiency of loss-making enterprises is primarily due to severe redundancy in employees and Research and Development (R&D) inputs. However, various environmental variables significantly impact enterprise operating efficiency in different directions. Based on the above conclusions, relevant suggestions regarding environmental, government, and enterprise aspects are put forward
Data envelopment analysis · Equity (law · Manufacturing · Operational efficiency · Order (exchange · Panel data · Redundancy (engineering · Efficiency Analysis Using DEA · Quality and Supply Management · Working Capital and Financial Performance
| Citation velocity | historical |
|---|---|
| Highly cited | No |