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    A new hybrid model based on rough step-wise weight assessment ratio analysis for third-party logistics selection
    (Springer, 2022) Ulutas, Alptekin; Topal, Ayse
    Increasing competition as a result of globalization has forced the businesses to increase efficiency by focusing on the core competencies. This led businesses to outsource logistics. As a result, most of the businesses started to use third-party logistics (3PLs). There are various and conflicting criteria involved in 3PL selection, thus the selection of 3PL is a complex task for businesses. There are several methods in the literature used for 3PL selection, most of them are multi-criteria decision-making methods. A new hybrid model including Rough step-wise weight assessment ratio analysis (SWARA), Rough preference selection Index (RPSI), and Rough improved operational competitiveness rating analysis (IOCRA) has been used to select optimal third-party logistics providers in this study. There are two contributions to this study. First one is the development of a new hybrid rough model for 3PL selection. Second one is addressing the 3PL selection decision problem with newly developed Rough PSI and Rough IOCRA methods. Using this model and conducting a comprehensive analysis, the best option as a 3PL provider may be determined as a partner for logistics. The model effectiveness has been tested in a real case with a textile business and several 3PL providers.
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    An Application of Fuzzy Integrated Model in Green Supplier Selection
    (HINDAWI LTD, 2019) Ulutas, Alptekin; Topal, Ayse; Bakhat, Rim
    Sustainability term has not only become increasingly important globally for individual companies, but also become important for whole supply chains. The selection of supplier is a significant decision for the sustainability of supply chains. Literature review revealed that supplier selection is made traditionally based on economic attributes which are insufficient for sustainability of supply chains as sustainability requires taking economic, environmental, and social issues into account. For this purpose, this paper proposes determining the green supplier selection attributes and then developing a methodology for assessment and ranking of green suppliers based on determined attributes. The first contribution of this study is to propose a novel method, which is FROV (fuzzy extension of range of value) to literature. The latter is to utilize fuzzy extension of preference selection index (FPSI) to identify the weights of attributes. The third is to develop a novel fuzzy multiattribute decision-making model consisting of FPSI and FROV to determine the best supplier for a Turkish textile company.
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    Assessment of Collaboration-Based and Non-Collaboration-Based Logistics Risks with Plithogenic SWARA Method
    (Mdpi, 2021) Ulutas, Alptekin; Meidute-Kavaliauskiene, Ieva; Topal, Ayse; Demir, Ezgi
    Background: Uncertainty is the major source of hazards, and it is present in a wide range of business activities. Due to the high level of unpredictability in logistics operations, the logistics sector has traditionally operated in a high-risk environment. These risks have become considerably more complicated as the corporate environment has changed in recent years, such through globalization, environmental concerns, and changes in demand. As a result, in order for a logistics firm to thrive, it is necessary to evaluate and assess the risks associated with logistics. Methods: The Plithogenic Stepwise Weight Assessment Ratio Analysis (SWARA) has been used in this study to assess the logistics risks. The logistics risk considered in this study are transportation-related risks, purchasing-related risks, inventory-related risks, information-related risks, packaging-related risks, operational-related risks, geographical location-related risks, natural disaster-related risks, and organization-related risks. Results: The most significant logistics risks are found to be Inventory-Related Risks, while the least significant are Geographical Location-Related Risks. When compared to the standard SWARA approach, the Plithogenic SWARA method may be employed in group decision-making issues without losing information. Conclusions: The proposed technique will help logistics professionals make informed decisions and manage and analyze risks more efficiently. This study will also contribute to the literature as it is the first time that logistical risks have been addressed by utilizing the Plithogenic SWARA technique.
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    Location selection for logistics center with fuzzy SWARA and CoCoSo methods
    (Ios Press, 2020) Ulutas, Alptekin; Karakus, Can Bulent; Topal, Ayse
    Logistics centers are home to many and varied facilities, such as storage, transportation of goods, handling, reassembling, clearing, disassembling, quality control, social services and providing accommodation, so on. Providing logistical activities from one location can provide some macro advantages, as well as regional development in developing countries. For the micro level, logistics center selection has an effective role in increasing the operational efficiency and decreasing the costs of the firms. While the wrong location selection for logistics center affects the operations and costs of the companies negatively, the optimal location selection increases the performance, competitiveness, profitability of the firms and reduces the costs of the firms. Since many different qualitative and quantitative criteria are considered in the selection of the logistics center, this selection problem is an MCDM problem. A new integrated MCDM model is proposed to solve this problem for Sivas province in Turkey. This study presents two contributions to the literature. Firstly, the number of studies related to CoCoSo method is limited in the literature, therefore, the CoCoSo method is proposed in this study. Secondly, a new integrated GIS-based MCDM model comprising fuzzy SWARA and CoCoSo is introduced to literature to address the location selection problem for a logistics center. In this study, the results of CoCoSo method and the resulfts of other MCDM methods (COPRAS, VIKOR, ARAS, MOORA, and MABAC) are compared to test the accuracy of results obtained by CoCoSo. Besides, the criteria weights are changed and the possible changes in the results are tracked.
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    Prioritization of Logistics Risks with Plithogenic PIPRECIA Method
    (Springer Science and Business Media Deutschland GmbH, 2022) Ulutaş, Alptekin; Topal, Ayse; Karabasevic, Darjan; Stanujkic, Dragisa; Popovic, Gabrijela; Smarandache, Florentin
    Rapidly changing markets, actors, new legal regulations, information and data intensity have increased uncertainty, and as a result, businesses that want to continue operating in the market need to pay more attention to risk criteria. Risk can be explained as unplanned event which affects a business’s overall performance. Logistics practices that develop and change continuously show a great variety such as weather and road accidents to faults in operations. Logistics risks have important roles in supply chains efficiency as the risks in logistics may adversely affect all parts of the supply chains and lead to decreases in business performances. Multi-criteria decision making methods are commonly used in risk prioritisation. In this study, a newly developed method called Plithogenic PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) Method is used to prioritise logistics risks. For identifying weights, data were collected from three experts in the logistics field. Six logistics risks were considered and according to the results of Plithogenic PIPRECIA Transportation-related risk is determined as the most significant risk. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.