Roles selection: a computational approach using ELECTRE and CFFR based on multi criteria tacit knowledge acquisition

• Main Authors: Yau’mee Hayati, Hj Mohamed Yusof, Ruzaini, Abdullah Arshah, Awanis, Romli
• Format: Conference or Workshop Item
• Language: English
• Published: IOP Publishing 2021
• Subjects: QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/31724/1/Roles%20selection-a%20computational%20approach%20using%20ELECTRE%20and%20CFFR.pdf; http://umpir.ump.edu.my/id/eprint/31724/; https://doi.org/10.1088/1742-6596/1874/1/012090

During the Talent Development Intervention programme, there is a need to provide an effective model to assess awareness, skills and experience among potential academics. To qualify as an Academic Leader or Academic Manager, there are certain characteristics and t raits necessary. However, there is a lack of research on the training of talented academicians to improve and avoid the loss of these characteristics and traits. Lack of this training would also contribute to vacancy positions of Academic Administrator without being hired. This paper aims to formulate and compare the Multi-criteria Decision-Making methods using ELECTRE (Elimination and Choice Expressing Reality) and CFPR (Consistent Fuzzy Preference Relations) based on proposed model of Multi Criteria Tacit Knowledge Acquisition (MC-TKAF). One set of empirical study based on proposed model contain seventeen (17) main criteria's and one hundred eights (108) sub criteria are used to select the best candidate to fill in academic administrator roles. In this study, our focus is to integrate MCDM using CFFR and ELECTRE into implementation of Talent Development Intervention based on MC-TKAF development criteria. This paper also highlighted previous literatures which has shown how MC TKAF is formed and the justification of MCDM technique that will be used. The finding shows that both techniques produce the same results.