Fuzzy delphi method: Issues and challenges
The Fuzzy Delphi Method (FDM) is the modified and enhanced version of the classical Delphi technique. Improvement was made to rectify the imperfection of traditional Delphi Method (DM) that leads to low convergence in retrieving outcomes, loss of important information, and long progress of investigation. Nevertheless, this approach has been employed in various application domains, including humanities, management, business, physical science, and engineering. Furthermore, the literature has exposed numerous key issues in relation to the existing FDM that need to be resolved with regard to the classical DM. Hence, the analysis obtained from the existing literature highlighted two key issues, which were; i) most FDM ignored certain important characteristics of DM, and ii) lack of explanation on how FDM obtained controlled feedback with the lack of iteration process. Additionally, it was observed that there had been lack of comparison between decision outcomes obtained based on FDM and the decision outcomes obtained from the traditional DM.
Development of Multi Criteria Tacit Knowledge Acquisition Framework (MC-TKAF) to Support Talent Development Intervention Program in A Malaysian Comprehensive University
In Higher Education Institutions (HEI), the process of retaining leadership succession is critical since it has involved the process in choosing the right person. The purpose is to steer the institutions to sustain organizations’ excellence for academic leadership and management (ALM) position. Many ALM of Malaysia HEIs are struggling to find the right successor to replace their roles as they do not have yet any firm criteria in evaluating the competence among their potential successors in their home institutions. This study aims to propose a multi criteria tacit knowledge acquisition framework (MC-TKAF) for supporting talent development intervention program in Malaysia HEIs. It will be based on cognitive apprenticeship, socialization and informal learning theory which mostly used in acquiring knowledge from expertise to overcome talent bottleneck among novice. The main process of this study will use Fuzzy Delphi among ALM in Malaysian HEIs to get consensus judgement about the right indicator to evaluate tacit knowledge competence. Three phases involved are: Phase 1 is to analyze the existing Tacit Knowledge Acquisition (TKA) by finding the suitable parameters to construct intended framework, Phase 2 is to use the findings in Phase 1 in order to develop a new framework of Tacit Knowledge Acquisition Framework (TKAF) that suits with HEI environment. Finally, Phase 3 is to evaluate the practicality of Tacit Knowledge Acquisition Framework (TKAF) by using Multi Criteria Decision Making (MCDM) approach in supporting Talent Development Intervention Program. The objective of this paper is to propose the multi criteria tacit acquisition framework by using MCDM technique as a talent performance indicator. This paper basically will focus on Phase 1 of the research design. The constructed indicators in this paper could be served as a reference for the HEI industries to establish applicable talent performance indicators according to the properties of each TKA used. the acquisition the acquisition
Selection of logistics service provider: An analytic network process (ANP) approach
This article presents a comprehensive methodology for the selection of a logistic service provider. The proposed methodology consists of two parts: (i) preliminary screening of the available providers, and (ii) analytic network process (ANP)-based final selection. The criteria, which are relevant in the selection of a provider, have been identified and used to construct an ANP model. Thereafter, the application of ANP for the final selection of a provider has been demonstrated through an illustrative example. The results of this example indicate that compatibility between the user and the provider companies is the most important determinant, which influences the final selection process. This approach also enables the decision-makers to better understand the complex relationships of the relevant attributes in the decision-making, which may subsequently improve the reliability of the decision.