Browsing by Author "Turan, Hakan"

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Citation - WoS: 1
Analyzing Critical Success Factors of Sustainable Knowledge Management: an Interval-Valued Neutrosophic Approach
(Mdpi, 2024) Çaloğlu Büyükselçuk, Elif; Bulak, Muhammet Enis; Buyukselcuk, Elif Caloglu; Endüstri Mühendisliği Bölümü
Knowledge management (KM) is a structured approach that includes the organized procedures of generating, capturing, arranging, storing, retrieving, distributing, and harnessing an organization's knowledge resources to attain its goals and improve its effectiveness. Encountering uncertainty and managing imprecise information are fundamental aspects of KM that cannot be avoided. In this context, sustainable KM aims to solve these issues and address prioritizing the long-term sustainability and efficiency of knowledge-related processes within an organization. The aim of this study is to structure a sustainable KM concept for organizations and identify the most common critical success factors (CSFs) with a novel analytical approach. In this context, the Interval-Valued Neutrosophic methodology, which is one of the multi-criteria decision methods (MCDMs), was adopted to evaluate and weight the determined CSFs. Four main headings-KM, environmental, economical, and social criteria-are evaluated along with their subfactors. Our findings show that KM is found to be the most important, and environmental factors followed KM. When the results are examined in terms of subfactors, cleaner production is found to be the most significant, with a global weight value of 11.13.
Evaluation of the Barriers to Maintenance 4.0 for the Textile Industry via Pythagorean Fuzzy SWARA
(MDPI, 2025) Turan, Hakan; Buyukselcuk, Elif Caloglu
Maintenance 4.0 studies have become a focus for managers and employees when developing effective and efficient maintenance policies. In this study, the barriers to Maintenance 4.0 applications in the textile industry are investigated, and these barriers are weighted using the Stepwise Weight Assessment Ratio Analysis (SWARA) method based on Pythagorean fuzzy numbers. Solutions to address these barriers are presented. As a result of this study, Organizational and Managerial emerged as the most important main criterion. Operational was identified as the second most significant main criterion, followed by Technical Competence. Data-Related and Cybersecurity ranked fourth in terms of importance. On the other hand, Human Resources and Training and Financial were found to be the least important main criteria. These two criteria received lower importance scores compared to the others, with Financial being the criterion with the lowest overall significance. Sensitivity analyses were performed for six different scenarios by changing the importance weights of the decision-makers. The ranking of the criteria only slightly changed with the weights; this means that the results obtained in Case 1 are robust and reliable. Even in Case 6, where the expert weight ratios were completely reversed, the results did not change significantly. This highlights an important point regarding the reliability of the assessment.