Abstract
An effective evaluation of the index system of talent growth factors can lay a solid foundation to build the talent pool, as well as select and establish talents. In this study, based on the theory of “Man-Machine-Environment” system engineering (MMESE), the MMESE talent growth factor index system is proposed and verified for its effectiveness by comparing it with the traditional system. Based on the text-free grammar and transformation function, expert judgments of talent growth factor indexes were transformed into hesitation fuzzy language terms, namely, pertinence, systematicness, practicability, foresight, and dynamics, which were then used to create a dataset to describe the comprehensive evaluation of the index system. The entropy of hesitation fuzzy language terms adopts the algorithm, which calculates the index weights according to the relative entropy values and adjusts the expert weights with the expert group consensus model. The expert evaluation information was weighed and transformed into the corresponding probability language combination which was calculated as the comprehensive evaluation result of the talent growth factor index system.
Highlights
In the 21st century, the talent shortage is one of the main bottlenecks in human resource development across the world, which would affect global, economic, and social growth
In addition to the unbalanced growth of economic development, the main reason for the global talent shortage is the lack of scientific and effective talent evaluation methods and a reasonable talent training model. erefore, it is of great significance for the global talent training strategic plans to carry out research on the index system of talent growth factors and build a scientific and effective comprehensive evaluation index system for talents
Liu [3] classified the factors affecting the growth of innovative talents into four categories, namely, personal quality, education, working environment, social system, and innovative culture. e study demonstrated that the current management system is insufficient to cultivate scientific and technological talents in China
Summary
In the 21st century, the talent shortage is one of the main bottlenecks in human resource development across the world, which would affect global, economic, and social growth. In the comprehensive evaluation method of the index system, based on the text-free grammar and conversion function, the expert’s judgment language on the talent growth factor index is converted into hesitant fuzzy language terms, and the hesitant fuzzy language term set is used to express the single characteristic evaluation information of the index system, that is, pertinence, systematic, complete, practical, forward-looking, and dynamic. On this basis, the expert group consensus model is used to further adjust the weight of experts, and the evaluation information given by the experts is weighted and integrated and transformed into the corresponding probabilistic language combination, and the expected value of the probabilistic language combination is calculated as the comprehensive evaluation result of the talent growth factor index system, so as to realize the qualitative comprehensive evaluation of the index system
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