<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In the face of increasingly fierce competition for talents, strengthening the cultivation of high-potential talent echelon and improving the core competitiveness of enterprises have become the most serious, urgent and realistic issues. The competency iceberg model and the talent echelon construction process are combined in this paper, and a talent competency model and a hierarchical thesaurus are established. For the influencing factors and comprehensive evaluation of talent competency elements in enterprise talent ladder construction, this paper introduces the entropy weight and TOPSIS methods for assessment. It explores the relevant factors of talent competency through multiple linear regression model. The research example is Enterprise Z, and appropriate research data is gathered through questionnaires to examine the development of enterprise talent echelon construction based on multidimensional data analysis technology. The study found that among the elements of talent competency, the weight of knowledge and skills reaches 0.3718, and the highest relative closeness of the ten middle managers is 0.798. The enterprise’s talent competency will significantly increase by 0.772 percentage points when the job evaluation process rises by 1 percentage point. The enterprise talent ladder construction needs to improve the corresponding job assessment process, establish a sustainable talent reserve system, and smooth career development channels to effectively enhance the enterprise talent ladder construction capacity.</p>
</abstract>

In the face of increasingly fierce competition for talents, strengthening the cultivation of high-potential talent echelon and improving the core competitiveness of enterprises have become the most serious, urgent and realistic issues. The competency iceberg model and the talent echelon construction process are combined in this paper, and a talent competency model and a hierarchical thesaurus are established. For the influencing factors and comprehensive evaluation of talent competency elements in enterprise talent ladder construction, this paper introduces the entropy weight and TOPSIS methods for assessment. It explores the relevant factors of talent competency through multiple linear regression model. The research example is Enterprise Z, and appropriate research data is gathered through questionnaires to examine the development of enterprise talent echelon construction based on multidimensional data analysis technology. The study found that among the elements of talent competency, the weight of knowledge and skills reaches 0.3718, and the highest relative closeness of the ten middle managers is 0.798. The enterprise’s talent competency will significantly increase by 0.772 percentage points when the job evaluation process rises by 1 percentage point. The enterprise talent ladder construction needs to improve the corresponding job assessment process, establish a sustainable talent reserve system, and smooth career development channels to effectively enhance the enterprise talent ladder construction capacity.

Research on enterprise talent ladder construction strategy based on multidimensional data analysis methodology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In the face of increasingly fierce competition for talents, strengthening the cultivation of high-potential talent echelon and improving the core...

Research on enterprise talent ladder construction strategy based on multidimensional data analysis methodology

Publié en ligne: 03 mai 2024

Pages: -

Reçu: 07 avr. 2024

Accepté: 19 avr. 2024

DOI: https://doi.org/10.2478/amns-2024-0949

Mots clés
Competency model, Entropy weight method, TOPSIS method, Relative closeness, Talent echelon

© 2024 Qiulin Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on enterprise talent ladder construction strategy based on multidimensional data analysis methodology

Publié en ligne: 03 mai 2024

Pages: -

Reçu: 07 avr. 2024

Accepté: 19 avr. 2024

DOI: https://doi.org/10.2478/amns-2024-0949

Mots clésCompetency model, Entropy weight method, TOPSIS method, Relative closeness, Talent echelon

© 2024 Qiulin Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Competency model, Entropy weight method, TOPSIS method, Relative closeness, Talent echelon