Affiliations: [a]
Yango University, Fuzhou, China
| [b]
Department of Management Sciences, R.O.C. Military Academy, Kaohsiung, Taiwan
| [c]
Department of Civil Engineering, R.O.C. Military Academy, Kaohsiung, Taiwan
Correspondence:
[*]
Corresponding author. Kuei-Hu Chang, Department of Management Sciences, R.O.C. Military Academy, Kaohsiung 830, Taiwan. Tel.: +886 7 7403060; Fax: +886 7 7403060; E-mail: [email protected].
Abstract: Personnel selection issues can be viewed as a complicated multicriteria decision-making (MCDM) problem. Choosing the most appropriate personnel directly influences an organization’s competitiveness and its sustainable development. Thus, the personnel selection problem is a critical issue for an organization’s success. However, such dilemmas involve quantitative and qualitative factors. Moreover, deciding on how to allocate limited resources toward cultivating talent increases the difficulty of personnel selection problems. This issue can not be solved effectively by arithmetic average-based methods. To address these issues, this paper combines the minimal variance order weighted averaging (OWA) operator and importance-performance analysis (IPA) to improve personnel selection. The advantages of the proposed method can deal with quantity and qualitative factors simultaneously in the process of personnel selection, consider the ordered weights between assessment attributes, and establish an IPA grid to provide the reference for decision-making by the management. Finally, an empirical case study of selection of higher-education students is applied to illustrate our method. Compared with the arithmetic average and interval 2-tuple linguistic VIKOR methods, our results indicated that the proposed method generates a more accurate and reasonable ranking of personnel.
Keywords: Decision analysis, human resource management, 2-tuple linguistic representation model, minimal variance OWA, importance performance analysis
