Journal Articles
Permanent URI for this collectionhttp://10.0.100.92:4000/handle/123456789/21
Browse
5 results
Search Results
Item Cloud vendor selection using choice models based on interactive criteria and varying attitudes of experts(Expert Systems with Applications, 2024-04) Aggarwal, Manish; Krishankumar, Raghunathan; Ravichandran, Kattur Soundarapandian; Hanmandlu, MadasuThe pervasiveness of the Internet coupled with the advantages of cloud have almost made cloud services a necessity for organizations and individuals alike. However, it is a complex decision to choose a cloud vendor because of the large number of criteria and alternatives. Furthermore, the criteria in the case of cloud vendor selection are often interactive (synergic or opposing). To address this need, an approach is presented in this paper to select the most suitable cloud vendor while considering the nuances of human decision making, such as interactive criteria, and varying behavioural characteristics of the decision-makers (DMs). To this end, the recent Choquet logit models are deployed and generalized to add to their modelling abilities. Specifically, the following choice models are developed: generalized Choquet logit, generalized attitudinal Choquet logit, generalized Choquet mixed logit, and generalized attitudinal Choquet mixed logit models. The proposed generalized logit models have the Choquet logit, and the attitudinal Choquet logit models as their special cases. Thus the contributions of this work are two-fold: first an approach is developed to select suitable cloud vendor considering the human nuances and the actual practical aspects of the problem, and secondly a new class of powerful choice models is developed which may be useful in aiding any complex human decision-making, in which the cognitive power of the DM proves to be limited. The method is designed to consider the real nuances of the human decision making such as varying attitudes and varying degree of criteria interaction. The effectiveness of the proposed models in cloud vendor selection is tested through a real world case study from the Indian state of Tamil Nadu. In the case-study, there are 9 cloud vendors in the fray and 4 experts with different attitudes and different suggestions for the best cloud vendor. An approach is developed to solve this problem and a final ranking of the cloud vendors is determined considering experts suggestions. Apart from finding the best cloud vendor, the case study also helps in studying the role of an expert’s attitudinal tendency on his preferences. Thus, concomitantly, the proposed approach also guides how to choose the best alternative based on the opinions of different experts with different attitudinal tendencies, without necessitating a forced consensus.Item Evaluation of sustainable cold chain suppliers using a combined multi-criteria group decision-making framework under fuzzy ZE-numbers(Expert Systems with Applications, 2024-07) Ecer, Fatih; Haseli, Gholamreza; Krishankumar, Raghunathan; Hajiaghaei-Keshteli, MostafaHealth 4.0 actively focuses on cold supply chains (CSCs) due to digital transformation and technological advancements in refrigeration. With the ill effects of climate change and greenhouse gas emissions, countries globally seek sustainable supply chain management. In this context, integrating sustainability with CSCs becomes crucial. Health sectors actively consider CSC for their activities. In this context, to gain potential suppliers for healthcare management, the present work focuses on grading suppliers from the CSC with sustainability factors. Previous related studies on sustainable cold chain supplier selection (CSSS) (i) have not modeled uncertainty effectively, and (ii) have yet to use any approach under fuzzy Z-numbers information. Therefore, this paper developed an integrated framework, including the Logarithm Methodology of Additive Weights (LMAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods based on extended fuzzy Z-numbers. The practicality of the framework is exemplified via a case example within the Indian health sector, and results indicate that job creation, value price, and productivity via renewable resources are the most critical factors. Moreover, regarding the findings, the economic dimension is the foremost pillar for effective selection. Sensitivity and comparison analyses are performed to understand the efficacy of the integrated framework as well. The proposed framework could contribute to the relevant literature due to its capacity to cope with complex decision-making problems and find many application areas in engineering.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.