Journal Articles
Permanent URI for this collectionhttp://10.0.100.92:4000/handle/123456789/21
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Item Hyperbolic fuzzy set decision framework for construction contracts integrating CRITIC and WASPAS for dispute mitigation(Automation in Construction, 2025-06) Zavadskas, Edmundas Kazimieras; Krishankumar,Raghunathan; Ravichandran,Kattur Soundarapandian; Vilkonis, Arvydas; Antucheviciene, JurgitaThe paper attempts to mitigate disputes during drafting of a construction contract by presenting a decision framework. The research questions considered are to set the main criteria involved and their relative importance in contract clauses selection and evaluate the priority of different contract clauses. In response, the paper presents an integrated framework involving hyperbolic fuzzy data, CRiteria Importance Through Intercriteria Correlation (CRITIC) method for criteria weight calculation, and query-based Weighted Aggregated Sum Product ASsessment (WASPAS) method for determining personalized priority of contract clauses. Results infer that work termination, customer reserve, guarantee periods and responsibilities of contractor/customer are the key criteria, and contract under the Fédération Internationale des Ingénieurs-Conseils (FIDIC) Yellow Book is of top priority. Such integrated framework serves as supplement to contractors and customers for prompt and rational decision-making by reducing human intervention, managing uncertainty, and reducing bias/subjectivity. In the future, plans are made to include a priori information into the decision framework.Item Evaluating smart grid investment drivers and creating effective policies via a fuzzy multi-criteria approach(Renewable and Sustainable Energy Reviews, 2025-02) Dinçer, Hasan; Krishankumar, Raghunathan; Yüksel, Serhat; Ecer, FatihIt is critical to determine which factors impact more smart grid investments and which smart grid investment policy is more suitable for renewable energy projects. Nonetheless, a limited amount of research has focused on this topic, meaning a new study is needed to fill this gap and aid in making decisions under ambiguities. Thus, this research proposes a novel fuzzy group decision-making framework. Twelve drivers are examined through the fuzzy weighted decision-making trial and evaluation laboratory (F–DEMATEL–W) methodology. Subsequently, four smart grid investment policies are ranked using fuzzy weighted aggregated sum product assessment (F–WASPAS). Hence, one of the novelties of this research is the proposal of a robust decision-making tool named F–DEMATEL–W–WASPAS. Other novelties are: (i) the importance of the indicators/criteria is methodically determined by considering pairwise interactions and weights of experts; (ii) both individualistic expert-driven weight vector and cumulative weight vector of indicators are determined; (iii) alternative policies are ranked with minimum decision parameters; (iv) drivers that are crucial for the effectiveness of smart grid investment are determined with their causal relationship, and (v) smart grid investment policies are ranked reliably. The findings demonstrate that cyber security, sufficient legal procedures, and financial viability are the foremost drivers to increase the effectiveness of smart grid investments. Moreover, encouraging sustainable energy production using financial incentives is the foremost policy, followed by exchanging surplus electricity for the system owners. The work may contribute to the ongoing discussion on designing smart grid investment policies for renewable energy projects.Item Analysis of critical success factors of Quality 4.0 implementation in manufacturing SMEs using best–worst method(The TQM Journal, 2024-12-19) Vinodh,Sekar; Wankhede, Vishal Ashok; Muruganantham, GanesanPurpose To attain a competitive edge, it is essential to realize the significant critical success factors (CSFs) that contribute to the adoption of Quality 4.0 (Q4.0) in manufacturing organizations. Therefore, the study aimed to analyze CSFs for Q4.0 implementation in manufacturing small and medium-sized enterprises (SMEs) using multi-criteria decision-making (MCDM) tool. Design/methodology/approach The present study begins with a systematic literature review of past studies about Q4.0 implementation in manufacturing, followed by the identification of CSFs. Further, a case study was conducted wherein 42 CSFs identified were grouped into five dimensions. Best–worst method is a MCDM tool applied as a solution methodology for the analysis of CSFs based on expert opinion and priority order of CSFs attained. Findings The priority order of CSFs is obtained. Based on the findings, significant CSFs are “Data prediction and Analytics,” “Organizational culture towards Quality 4.0” and “Machine to Machine communication.” Practical implications The shifting market dynamics incorporate Q4.0 inclusion for realizing zero defects and high traceability in automotive SMEs. The present study offers implications for industry managers and practitioners by delivering insights on how Q4.0 could be serving automotive systems and CSFs that industry authorities need to pay attention to effectively adopt Q4.0 in the current quality systems. The study will facilitate industry practitioners to meticulously examine CSFs for Q4.0 toward the improvement of SME performance. Originality/value The identification of CSFs for Q4.0 adoption in manufacturing SMEs, along with the prioritization of CFSs using the MCDM tool, is the original contribution by the authors.