A Fuzzy Analytical Hierarchy Process for Evaluation of Knowledge Management Effectiveness in Research Centers

Nahavandi, Bijan; Homayounfar, Mahdi; Daneshvar, Amir

doi:10.13033/ijahp.v15i1.978

Cited by 3 publications

(1 citation statement)

References 67 publications

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“…In the decision analysis literature, fuzzy logic methods have been developed in order to eliminate these uncertainties. Building on the success of classical fuzzy logic sets (Zadeh, 1996) (Atanassov, 1986), neutrosophic fuzzy sets (Smarandache, 2003), and hesitant fuzzy sets (Torra, 2010) have been proposed to yield effective solutions to deal with vagueness in many decision making problems (Akman et al, 2022;Nahavandi et al, 2023, Poveda, 2023. A more recent addition is the concept of spherical fuzzy sets, introduced by Gündoğdu and Kahraman (2019).…”

Section: Ivsf-ahpmentioning

confidence: 99%

Integrated Methodology for the Assessment of Industry 4.0 Maturity Level

Kılıç,

Kalender,

Korkmaz

et al. 2023

IJAHP

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The ability to adapt to changes in information and communication technologies is essential for all organizations. Companies that fail to correctly perceive the need for these changes and delay their implementation are doomed to disappear. In this context, the term Industry 4.0 is used to refer to digital improvement studies. It aims to increase profitability by reducing production costs without increasing the focus areas of companies. Determining the level of digitalization is as important as completing the digitalization infrastructure to bring Industry 4.0 to life. In this way, companies can determine their current digitalization status and maintain their competitiveness. They can also decide the steps needed to implement Industry 4.0. Currently, there are many methods and models used to determine the level of digitalization. However, this study takes a distinctive approach by aiming to develop an integrated methodology tailored for quantifying Industry 4.0 maturity in companies. To begin, the dimensions used within the Industry 4.0 maturity assessment were extracted from the literature. Then, a focus group approach was utilized by experts to eliminate the unimportant dimensions. Next, Interval-Valued Spherical Fuzzy AHP (IVSF-AHP) was used to determine the importance weights of the determined dimensions. Finally, the Industry 4.0 maturity level of an aviation/defense company was calculated by applying the proposed methodology based on the data collected via the questionnaire. Therefore, this proposed methodology provides a potent instrument for accurately appraising progress in digital transformation, refining strategies, and securing success in an evolving technology-driven environment.

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Section: Ivsf-ahpmentioning

confidence: 99%

Integrated Methodology for the Assessment of Industry 4.0 Maturity Level

Kılıç,

Kalender,

Korkmaz

et al. 2023

IJAHP

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Use of the TTA-DIVAYANA Concept to Improve the Weight of Decision Makers in the TOPSIS Method as an Effort to Optimize Evaluation Results

Divayana,

Adiarta,

Suyasa

et al. 2023

Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology

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Analysis of Intelligent Decision Support Systems and a Multi Criteria Framework for Assessment

Wang,

Liang

2023

JEBI

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The act of decision-making lies at the core of human existence and shapes our interactions with the surrounding environment. This article investigates the utilization of artificial intelligence (AI) techniques in the advancement of intelligent decision support systems (IDSS). It builds upon prior research conducted in the decision-making field and the subsequent development of decision support systems (DSS) based on that knowledge. The initial establishment of the fundamental principles of classical DSS is undertaken. The subsequent emphasis is directed towards the integration of artificial intelligence techniques within IDSS. The evaluation of an IDSS, as well as any other DSS, is a crucial undertaking in order to gain insights into the system's capabilities and identify areas that require enhancement. This article presents a review conducted on this significant yet insufficiently investigated subject matter. When utilized in conjunction with DSS, AI techniques such as intelligent agents, artificial neural networks (ANN), evolutionary computing, case-based reasoning, and fuzzy logic provide valuable assistance in defining complex practical challenges, which are mostly time-critical, encompass extensive and scattered data, and can derive advantages from sophisticated reasoning.

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A Fuzzy Analytical Hierarchy Process for Evaluation of Knowledge Management Effectiveness in Research Centers

Cited by 3 publications

References 67 publications

Integrated Methodology for the Assessment of Industry 4.0 Maturity Level

Integrated Methodology for the Assessment of Industry 4.0 Maturity Level

Use of the TTA-DIVAYANA Concept to Improve the Weight of Decision Makers in the TOPSIS Method as an Effort to Optimize Evaluation Results

Analysis of Intelligent Decision Support Systems and a Multi Criteria Framework for Assessment

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