標題: A DATA-DRIVEN MADM MODEL FOR PERSONNEL SELECTION AND IMPROVEMENT
作者: Chuang, Yen-Ching
Hu, Shu-Kung
Liou, James J. H.
Tzeng, Gwo-Hshiung
科技管理研究所
Institute of Management of Technology
關鍵字: human resource development;personnel selection and improvement;data-driven decision-making environment;data-driven multiple attribute decision-making (Data-driven MADM);rough set theory (RST);DEMATEL-based analytical network process (DANP);preference ranking organization method for enrichment evaluation with aspiration level (PROMETHEE-AS)
公開日期: 1-Jan-2020
摘要: Personnel selection and human resource improvement are characteristically multiple-attribute decision-making (MADM) problems. Previously developed MADM models have principally depended on experts' judgements as input for the derivation of solutions. However, the subjectivity of the experts' experience can have a negative influence on this type of decision-making process. With the arrival of today's data-based decision-making environment, we develop a data-driven MADM model, which integrates machine learning and MADM methods, to help managers select personnel more objectively and to support their competency improvement. First, RST, a machining learning tool, is applied to obtain the initial influential significance-relation matrix from real assessment data. Subsequently, the DANP method is used to derive an influential significance-network relation map and influential weights from the initial matrix. Finally, the PROMETHEE-AS method is applied to assess the gap between the aspiration and current levels for every candidate. An example was carried out using performance data with evaluation attributes obtained from the human resource department of a Chinese food company. The results revealed that the data-driven MADM model could enable human resource managers to resolve the issues of personnel selection and improvement simultaneously, and can actually be applied in the era of big data analytics in the future.
URI: http://dx.doi.org/10.3846/tede.2020.12366
http://hdl.handle.net/11536/154840
ISSN: 2029-4913
DOI: 10.3846/tede.2020.12366
期刊: TECHNOLOGICAL AND ECONOMIC DEVELOPMENT OF ECONOMY
Volume: 26
Issue: 4
起始頁: 751
結束頁: 784
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