Evaluation of financing efficiency of strategic emerging industries in the context of green development: evidence from China.

Environ Sci Pollut Res Int

School of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 211106, People's Republic of China.

Published: September 2022

Strategic emerging industries are key areas to transform the traditional industrial model of high pollution, high energy consumption, and high emissions. This paper focuses on the measurement of financing efficiency of strategic emerging industries. On the one hand, in order to overcome the interference of external environment and statistical error existing in the traditional single data envelope model, the SSBM-BOOT five-stage model is proposed. On the other hand, Malmquist index method and Luenberger productivity method are combined to evaluate dynamic efficiency, which select Beijing-Tianjin-Hebei listed companies' data. The results show that (1) external environmental factors play a significant role in financing efficiency. The empirical results of the SSBM-BOOT five-stage model show that environmental factors "raise" the efficiency value of the whole Beijing-Tianjin-Hebei region. (2) Based on the revised data and the overall and decomposition results of SBM-ML index, it can be seen that the regional industry is still in the stage of scale expansion, and the financing efficiency depends on technological innovation that needs to be improved. Finally, the paper puts forward the concrete strategies of creating industrial development environment, promoting technological innovation, and establishing green investment and financing mechanism.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11356-022-20014-6DOI Listing

Publication Analysis

Top Keywords

financing efficiency
16
strategic emerging
12
emerging industries
12
efficiency strategic
8
ssbm-boot five-stage
8
five-stage model
8
environmental factors
8
technological innovation
8
efficiency
6
evaluation financing
4

Similar Publications

Missing values arise routinely in real-world sequential (string) datasets due to: (1) imprecise data measurements; (2) flexible sequence modeling, such as binding profiles of molecular sequences; or (3) the existence of confidential information in a dataset which has been deleted deliberately for privacy protection. In order to analyze such datasets, it is often important to replace each missing value, with one or more letters, in an efficient and effective way. Here we formalize this task as a combinatorial optimization problem: the set of constraints includes the of the missing value (i.

View Article and Find Full Text PDF

Background: Intelligent assistive technologies (IAT) have become more common in dementia care. Ethical reflection on technology-assisted dementia care (TADC) has focused so far mainly on individual and interpersonal implications (e.g.

View Article and Find Full Text PDF

In biomedical studies, gene-environment (G-E) interactions have been demonstrated to have important implications for analyzing disease outcomes beyond the main G and main E effects. Many approaches have been developed for G-E interaction analysis, yielding important findings. However, hierarchical multi-label classification, which provides insightful information on disease outcomes, remains unexplored in G-E analysis literature.

View Article and Find Full Text PDF

Multi-view learning aims on learning from the data represented by multiple distinct feature sets. Various multi-view support vector machine methods have been successfully applied to classification tasks. However, the existed methods often face the problems of long processing time or weak generalization on some complex datasets.

View Article and Find Full Text PDF

In order to solve the limitations of flipped classroom in personalized teaching and interactive effect improvement, this paper designs a new model of flipped classroom in colleges and universities based on Virtual Reality (VR) by combining the algorithm of Contrastive Language-Image Pre-Training (CLIP). Through cross-modal data fusion, the model deeply combines students' operation behavior with teaching content, and improves teaching effect through intelligent feedback mechanism. The test data shows that the similarity between video and image modes reaches 0.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!