Proceedings of the 2022 International Conference on Computer Science, Information Engineering and Digital Economy (CSIEDE 2022)

Evaluation of Agricultural Science and Technology Talents Competitiveness Based on Analytic Hierarchy Process

Authors
Qi Wang1, *
1Liaoning Science and Technology Talents Strong Province Strategic Development ResearchCenter, 110167, Shenyang, China
*Corresponding author. Email: 1850508590@qq.com
Corresponding Author
Qi Wang
Available Online 30 December 2022.
DOI
10.2991/978-94-6463-108-1_23How to use a DOI?
Keywords
Analytic Hierarchy Process; Agricultural Science and Technology Talents; Competitiveness; Index System; Weight
Abstract

With the rapid development of the market economy, scientific and technological innovation has become an important factor affecting market competitiveness. Establishing a team of high-tech innovative talents has a direct impact on the development of China’s agricultural economy. The evaluation of agricultural science and technology talent competitiveness is an effective means to measure the level of agricultural science and technology talent competition. At present, the evaluation index system of the current evaluation method of agricultural technology talent competitiveness is not perfect. The consistency coefficient between the evaluation results and the actual situation is low in practical application, which can not truly reflect the situation of agricultural technology talent competitiveness. Based on this, this paper puts forward the research on the competitiveness evaluation of agricultural science and technology talents based on the analytic hierarchy process. According to the factors affecting the competitiveness of agricultural science and technology talents, this paper selects the evaluation index, builds the evaluation index system of talent competitiveness, uses the analytic hierarchy process to scale the index, and calculates the index weight. Quantitative analysis of talent competitiveness was carried out by using the evaluation function, and the level of talent competitiveness was determined to complete the qualitative evaluation of agricultural science and technology talent competitiveness. The experiment proves that the consistency coefficient of the evaluation results of the method designed in this paper and the actual situation is higher than that of the traditional method, which provides strong theoretical support for the evaluation of the competitiveness of agricultural science and technology talents.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 International Conference on Computer Science, Information Engineering and Digital Economy (CSIEDE 2022)
Series
Advances in Computer Science Research
Publication Date
30 December 2022
ISBN
10.2991/978-94-6463-108-1_23
ISSN
2352-538X
DOI
10.2991/978-94-6463-108-1_23How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Qi Wang
PY  - 2022
DA  - 2022/12/30
TI  - Evaluation of Agricultural Science and Technology Talents Competitiveness Based on Analytic Hierarchy Process
BT  - Proceedings of the 2022 International Conference on Computer Science, Information Engineering and Digital Economy (CSIEDE 2022)
PB  - Atlantis Press
SP  - 204
EP  - 212
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-108-1_23
DO  - 10.2991/978-94-6463-108-1_23
ID  - Wang2022
ER  -