A Hybrid Decision Making Framework for Personnel Selection Using BWM, MABAC and PROMETHEE
| Autor: | Lining Xing, Sui-zhi Luo |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Sustainable development
Operations research Computer science Process (engineering) media_common.quotation_subject Personnel selection Computational intelligence 02 engineering and technology Preference Theoretical Computer Science Computational Theory and Mathematics Ranking Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Feature (machine learning) 020201 artificial intelligence & image processing Simplicity Software media_common |
| Zdroj: | International Journal of Fuzzy Systems. 21:2421-2434 |
| ISSN: | 2199-3211 1562-2479 |
| Popis: | Personnel selection plays a vital role in the sustainable development of a company. Generally, both quantitative and qualitative criteria are considered in the personnel selection process. Hence, this research introduces crisp numbers and linguistic neutrosophic numbers (LNNs) simultaneously to express hybrid evaluation information. Then, the multi-attributive border approximation area comparison (MABAC) method is recommended to select ideal personnel because of its simplicity and precision. Some criteria have the feature of non-compensation in real personnel selection, but they are presumed to be compensatory in MABAC. To overcome this limitation, the idea of preference ranking organization method for enrichment evaluations (PROMETHEE) is integrated into MABAC. Besides, the traditional best–worst method (BWM) is modified with linguistic values to obtain the criteria weights more appropriately. As a result, a hybrid decision making framework is constructed to tackle personnel selection issues. Finally, an illustrative example of personnel selection in an IT company is given to show the procedures of the proposed method after the assessment criteria system is built. Moreover, some comparative analyses are made to justify the practicability and strengths of our method. Results demonstrate that the hybrid decision making framework is eligible and helpful for personnel selection in enterprises. |
| Databáze: | OpenAIRE |
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