2022
DOI: 10.3390/math10020173
|View full text |Cite
|
Sign up to set email alerts
|

Approaches to Efficiency Assessing of Regional Knowledge-Intensive Services Sector Development Using Data Envelopment Analysis

Abstract: The sector of knowledge-intensive services is one of the fastest-growing sectors in the present-day economy of knowledge, which explains the scientific interest in developing methods of its quantitative assessment. The object of the research is the development of new approaches to the mathematical modeling of the efficiency of the regional knowledge-intensive services sector, based on a distance function approach to assess productivity changes. An approach was proposed to analyze the efficiency of this sector … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
2
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
4

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(2 citation statements)
references
References 40 publications
0
2
0
Order By: Relevance
“…This is typical for all regions with a Ce coefficient higher than 4. It should be noted, the specifics of the Russian innovation space is that the development of regions of Russia is characterized by high unevenness in various aspects, particularly in the innovation activity efficiency [28].…”
Section: Mesolevelmentioning
confidence: 99%
“…This is typical for all regions with a Ce coefficient higher than 4. It should be noted, the specifics of the Russian innovation space is that the development of regions of Russia is characterized by high unevenness in various aspects, particularly in the innovation activity efficiency [28].…”
Section: Mesolevelmentioning
confidence: 99%
“…Ghiyasi et al [24] have developed an inverse DEA for assessing the performance of 130 public hospitals in Iran. The DEA and Malmquist productivity techniques were combined by Firsova et al [25] to assess the efficiency of the knowledge-intensive services sector. Ashuri et al [26] have developed a new DEA model for benchmarking building energy use.…”
mentioning
confidence: 99%