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Keywords = overseas talents’ evaluation and classification

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18 pages, 931 KB  
Article
Evaluation and Classification of Overseas Talents in China Based on the BWM for Intuitionistic Relations
by Qing Yang, Zaisheng Zhang, Xinshang You and Tong Chen
Symmetry 2016, 8(11), 137; https://doi.org/10.3390/sym8110137 - 23 Nov 2016
Cited by 28 | Viewed by 5578
Abstract
Efficient utilization of human resources is an important force for the sustainable development of society and the economy. Against the backdrop of the development of economic globalization, the Chinese Government is presently implementing the strategy of “Strengthening the Nation with Talent” to assist [...] Read more.
Efficient utilization of human resources is an important force for the sustainable development of society and the economy. Against the backdrop of the development of economic globalization, the Chinese Government is presently implementing the strategy of “Strengthening the Nation with Talent” to assist the exploitation and management of human resources. Overseas talents have recently become an important resource. How to scientifically evaluate and classify overseas talents has become an important research topic, and it is necessary to seek a systematic decision aid. This paper introduces a novel methodology to evaluate and classify overseas talents in China under the intuitionistic relations environment. Firstly, we determine the weighted values of decision makers and criteria through defining geometry consistency. Secondly, we construct a non-linear Best-Worst-Method (BWM) model with intuitionistic preference relations. A highlight of this BWM model for intuitionistic relations is taking both positive and negative aspects into consideration, which is different from the original BWM. Finally, the proposed methodology is applied to an illustrative example of overseas talent evaluation, indicating the simultaneous efficiency and practicability of the method. Full article
(This article belongs to the Special Issue Scientific Programming in Practical Symmetric Big Data)
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