Yazar "Stevic, Zeljko" seçeneğine göre listele

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    A comprehensive MCDM assessment for economic data: success analysis of maximum normalization, CODAS, and fuzzy approaches
    (Springer, 2024) Baydas, Mahmut; Yilmaz, Mustafa; Jovic, Zeljko; Stevic, Zeljko; Ozuyar, Sevilay Ece Gumus; Ozcil, Abdullah
    The approach of evaluating the final scores of multi-criteria decision-making (MCDM) methods according to the strength of association with real-life rankings is interesting for comparing MCDM methods. This approach has recently been applied mostly to financial data. In these studies, where it is emphasized that some methods show more stable success, it would be useful to see the results that will emerge by testing the approach on different data structures more comprehensively. Moreover, not only the final MCDM results but also the performance of normalization techniques and data types (fuzzy or crisp), which are components of MCDM, can be compared using the same approach. These components also have the potential to affect MCDM results directly. In this direction, in our study, the economic performances of G-20 (Group of 20) countries, which have different data structures, were calculated over ten different periodic decision matrices. Ten different crisp-based MCDM methods (COPRAS, CODAS, MOORA, TOPSIS, MABAC, VIKOR (S, R, Q), FUCA, and ELECTRE III) with different capabilities were used to better visualize the big picture. The relationships between two different real-life reference anchors and MCDM methods were used as a basis for comparison. The CODAS method develops a high correlation with both anchors in most periods. The most appropriate normalization technique for CODAS was identified using these two anchors. Interestingly, the maximum normalization technique was the most successful among the alternatives (max, min-max, vector, sum, and alternative ranking-based). Moreover, we compared the two main data types by comparing the correlation results of crisp-based and fuzzy-based CODAS. The results were very consistent, and the Maximum normalization-based fuzzy integrated CODAS procedure was proposed to decision-makers to measure the economic performance of the countries.
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    A New Integrated Multi-Criteria Decision-Making Model for Sustainable Supplier Selection Based on a Novel Grey WISP and Grey BWM Methods
    (Mdpi, 2022) Ulutas, Alptekin; Topal, Ayse; Pamucar, Dragan; Stevic, Zeljko; Karabasevic, Darjan; Popovic, Gabrijela
    Supplier selection is an important task in supply chain management, as suppliers have a vital role in the success of organisations in a supply chain. Sustainability has emerged as a solution to decreasing resources and increasing environmental and social problems in the past few decades. It has been applied to various industrial operations, one of them is supplier selection, to mitigate unwanted effects in the future. Sustainable supplier selection is a complicated multi-criteria decision making problem, including several criteria from economic, environmental, and social perspectives. To deal with subjective judgements of decision makers, fuzzy and grey methods are widely used in multi-criteria decision making, In the case of small, limited, and incomplete data, the grey theory provides satisfactory results, compared to fuzzy methods. Therefore, this study is an integrated method including grey Best-Worst Method (BWM) and grey Weighted Sum-Product (WISP) for choosing the most sustainable supplier for a textile manufacturer, which includes three main criteria and twelve sub-criteria. According to the result of the proposed model, the supplier with the best performance was determined to be the supplier with the SP2 coded. The results of the developed model were shown to the experts, and the accuracy of the results was confirmed. According to the experts, a higher amount of product can be purchased from the supplier with the SP2 code, and a tighter relationship can be worked with this supplier. The contributions of this study are: (1) Develop a new grey MCDM model called Grey WISP. (2) Create a new integrated MCDM model with grey theory, BWM, and WISP methods that can be applied to assess supplier sustainability using this hybrid model. The proposed model can be used not just for selecting sustainable suppliers, but also for any other decision problems that have multiple criteria and alternatives. The findings suggest that the Grey WISP method achieved accurate results.
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    A new integrated rough multi-criteria decision-making model for enterprise resource planning software selection
    (Peerj Inc, 2024) Cao, Bing; Jin, Yongsheng; Uluta, Alptekin; Topal, Ayse; Stevic, Zeljko; Karabasevic, Darjan; Sava, Cipriana
    Enterprise resource planning (ERP) is widely used to boost the total market power of businesses. The wrong selection is one of the key reasons why ERP installations fail. Due to the complexity of the business environment and the range of ERP systems, choosing an ERP system is a complex and time-consuming procedure. ERP alternatives may be assessed using several criteria, so the ERP selection process may be considered a multicriteria decision-making (MCDM) problem. In this study, the rough best worst method (BWM) was used to determine criteria weights, while the newly developed rough integrated simple weighted sum product (WISP) was used to rank ERP alternatives. Results suggest that the SFT -4 coded software is regarded as the best option, followed by SFT -5, SFT -6, SFT -2, SFT -3, and SFT -1. Results of the newly developed rough WISP method are compared to those of existing rough techniques in the sensitivity analysis. The differences between them have been found to be negligible. The outcomes show how effectively developed rough BWM and WISP integrated method performs in terms of ERP selection with usability, accuracy, ease of use, and consistency. This study will help decision-makers in a context where ERP is implemented choose the best ERP software for different sectors.
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    Supply Chain Management (SCM) Breakdowns and SCM Strategy Selection during the COVID-19 Pandemic Using the Novel Rough MCDM Model
    (Wiley-Hindawi, 2023) Stevic, Zeljko; Ulutas, Alptekin; Korucuk, Selcuk; Memis, Salih; Demir, Ezgi; Topal, Ayse; Karamasa, Caglar
    Supply chain management (SCM) is deeply affected by the COVID-19 pandemic besides breakdowns occurred in all sectors. Nowadays, managers need techniques for protecting supply chains from serious and costly disruptions, establishing permanent relationships with the customers and partners and preventing breakdowns throughout the process. Each firm needs to determine SCM strategies to be prepared for breakdowns in an intense competitive environment. With COVID-19, the change in business and trade environments has taken a different dimension, and it has revealed a new relationship between the efforts to perpetuate supply chains and strategies for supply chain management and enabled new models. In this study, it is aimed to prioritize the factors that lead to SCM breaks needed in project management and the realization of projects, and to choose the most successful SCM strategy considering COVID-19. For this purpose, rough SWARA was used for weighting factors and rough MARCOS was used for the alternative selection. According to the findings, the transportation capacity factor was found to be the most important factor leading to SCM breakdowns. The most ideal supply chain management strategy has been the collaborative supply chain management strategy. In the food manufacturing sector, the study can be considered as a roadmap in terms of preventing supply chain management breaks during the COVID-19 process and helping to ensure a sustainable production. As another theoretical and practical importance of the study, it is aimed to propose a robust, powerful, and practical decision-making model that can cope with the current uncertainties.