Evaluation and Classification of Overseas Talents in China Based on the BWM for Intuitionistic Relations

Yang, Qing; Zhang, Zaisheng; You, Xinshang; Tong, Chen

doi:10.3390/sym8110137

Cited by 25 publications

(9 citation statements)

References 41 publications

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“…Further, because of its high consistency and the limited amount of pairwise comparisons required, BWM is applied in different real‐world cases such as failure mode and effects analysis, 39,40 decision‐making in the judgment of scientific journal and investment projects, 41 water scarcity management in arid regions, 42 evaluation and classification of overseas talents in China, 43 multi‐criteria sustainability assessment of technologies urban sewage sludge, 44 assessing the social sustainability of supply chains management, 45 risk assessment framework for business continuity management systems, 46 decision‐making in web service selection, 47 selection of the mobile phone, 18,32 and determining the location of facilities 48,49 . Enthusiastic readers can refer to [50] to study more about the current advancements in the BWM and its applications.…”

Section: Literature Surveymentioning

confidence: 99%

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Hasan¹,

Ashraf

Khan

2021

Int J of Intelligent Sys

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The best‐worst method (BWM) is a multi‐criteria decision‐making (MCDM) approach for solving several types of real‐life decision‐making problems. The basic BWM determines the priority order by pairwise comparisons of the best and worst criteria. The strength of the preference assigned via numerical value for linguistic interpretations of relative comparisons ranges from 1 to 9, representing preferences among the criterion. However, the amount of strength is entirely dependent on the choice of the decision‐makers. Though expert's opinions may differ due to various reasons such as incomplete information, lack of knowledge, ambiguity in linguistic terms, and so forth. Therefore, it is highly likely that the expert may provide multiple viewpoints for the preferences values. Thus, this study proposes a novel extension of the BWM named the multi‐choice best‐worst method (MCBWM), dealing with the concept of multiple choices of preference relations to compare the criterion. The MCBWM overcomes the limitation of BWM, where the pairwise preferences in the comparisons are multi‐choice parameters rather than single parametric values. Multiple real‐world MCDM applications are illustrated in experimental studies to show the quality, performance, and applicability of our proposed MCBWM. A detailed comparative analysis of the proposed approach has been done with the well‐known existing decision‐making techniques and their optimal results are compared. The proposed method offers a new direction for the MCDM approaches for solving real‐life problems.

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Section: Literature Surveymentioning

confidence: 99%

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Hasan¹,

Ashraf

Khan

2021

Int J of Intelligent Sys

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“…Guo and Zhao 24 extended the BWM to fuzzy environments. Yang et al 25 extended the BWM to the I-BWM by introducing intuitionistic preference relations. Ahmadi et al 26 studied social sustainability importance in supply chains using BWM by involving 38 experts.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Depending on Eq. ( 14 ) and the definition to measure the distance between two IMNs 25 , we have the following transformation function f for any IMN : …”

Section: A Novel Two-sided Decision Making Modelmentioning

confidence: 99%

Two-sided matching based on I-BTM and LSGDM applied to high-level overseas talent and job fit problems

Yang

You

Zhang

2021

Sci Rep

Self Cite

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With the increasing number of overseas talent tasks in China, overseas talent and job fit are significant issues that aim to improve the utilization of this key human resource. Many studies based on fuzzy sets have been conducted on this topic. Among the many fuzzy set methods, intuitionistic fuzzy sets are usually utilized to express and handle the evaluation information. In recent years, various intuitionistic fuzzy decision-making methods have been rapidly developed and used to solve evaluation problems, but none of them can be used to solve the person-job fit problem with intuitionistic best-worst method (BWM) and TOPSIS methods considering large-scale group decision making (LSGDM) and evaluator social network relations (SNRs). Therefore, to solve problems of intuitionistic fuzzy information analysis and the LSGDM for high-level overseas talent and job fit, we construct a new hybrid two-sided matching method named I-BTM and an LSGDM method considering SNRs. On the one hand, to express the decision-making information more objectively and reasonably, we combine the BWM and TOPSIS in an intuitionistic environment. Additionally, we develop the LSGDM with optimized computer algorithms, where the evaluators’ attitudes are expressed by hesitant fuzzy language. Finally, we build a model of high-level overseas talent and job fit and establish a mutual criteria system that is applied to a case study to illustrate the efficiency and reasonableness of the model.

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“…Xue et al [25] introduced intervalvalued intuitionistic fuzzy MABAC approach for material selection. Yang et al [26] evaluated overseas talents in China using BWM. Zavadskas et el.…”

Section: Literature Reviewmentioning

confidence: 99%

A new integrated fuzzy MCDM approach and its application to wastewater management

Dursun

2018

ijisae

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This paper proposes a fuzzy multi-criteria group decision making methodology that combines 2-tuple fuzzy linguistic representation model, linguistic hierarchies, Decision Making Trial and Evaluation Laboratory (DEMATEL) method and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The multi-granular linguistic information obtained from decision-makers are unified and aggregated employing linguistic hierarchies and 2-tuple fuzzy linguistic representation model. The weights of the criteria are calculated employing DEMATEL method, which enables to consider inner dependencies among criteria. Then, fuzzy TOPSIS method is utilized to rank the alternatives. The developed methodology is able to handle information in a decision making problem with multiple information sources. Furthermore, it enables managers to deal with heterogeneous information without loss of information. The developed methodology is used to determine the most suitable wastewater treatment (WWT) alternative for Istanbul, the largest city of Turkey that is also listed among the world's most crowded cities.

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Evaluation and Classification of Overseas Talents in China Based on the BWM for Intuitionistic Relations

Cited by 25 publications

References 41 publications

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Two-sided matching based on I-BTM and LSGDM applied to high-level overseas talent and job fit problems

A new integrated fuzzy MCDM approach and its application to wastewater management

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