Yazar "Ecer, Fatih" seçeneğine göre listele

Listeleniyor 1 - 3 / 3
  • Küçük Resim Yok
    Öğe
    Evaluation of third-party logistics service providers for car manufacturing firms using a novel integrated grey LOPCOW-PSI-MACONT model
    (Pergamon-Elsevier Science Ltd, 2024) Ulutas, Alptekin; Topal, Ayse; Gorcun, Omer Faruk; Ecer, Fatih
    Automotive businesses often delegate logistical tasks to third-party logistics (3PLs) service providers to acquire a competitive edge in the dynamic market. Nevertheless, selecting the most suitable third-party logistics (3PL) partner is a multifaceted undertaking that needs careful evaluation of several criteria and alternatives. This research aims to introduce an integrated grey Multiple Criteria Decision Making (MCDM) framework for automotive businesses to deal with the multidimensional 3PL selection decision problem. This framework incorporates an enhanced Preference Selection Index (PSI), Logarithmic Percentage Change-driven Objective Weighting (LOPCOW), and Mixed Aggregation by Comprehensive Normalization Technique (MACONT). The LOPCOW-G and grey PSI (PSI-G) methods extract the criterion weights, whereas the MACONT-G method ranks the alternatives. The suggested framework's practicality is shown by conducting a case study about evaluating and selecting a third-party logistics (3PLs) provider. The findings indicate that the parameters of significant importance are skilled workforce (0.0977), financial strength (0.0901), and IT-IS competence (0.0839). Furthermore, TPL4 has been recognized as the most optimum option with a value of 0.4797. The MACONT-G model is as well compared against other grey MCDM techniques to assess the validity of the proposed model. The Pearson correlation coefficient between MACONT-G and the other models based on grey sets is 0.958, suggesting a significant and positive link. Furthermore, it is worth noting that a sensitivity analysis has been conducted to validate the accuracy and reliability of the created framework. In conclusion, this study has identified managerial and policy implications that might assist policymakers and executives in effectively evaluating 3PL providers.
  • Küçük Resim Yok
    Öğe
    Fermatean fuzzy framework based on preference selection index and combined compromise solution methods for green supplier selection in textile industry
    (Taylor & Francis Ltd, 2024) Pamucar, Dragan; Ulutas, Alptekin; Topal, Ayse; Karamasa, Caglar; Ecer, Fatih
    This work aims to enhance the efficiency and dependability of the green supplier selection process by developing a decision support tool. Thereby, a novel fuzzy group multi-criteria decision-making approach based on the Preference Selection Index (PSI) and Combined Compromise Solution (CoCoSo) methods under the Fermatean Fuzzy (FF) environment for green supplier selection is proposed. The primary novelties and contributions are: (i) for the first time, the FF-PSI model is developed to extract the priority weight values of criteria, (ii) an improved FF-CoCoSo methodology is proposed, and (ii) the FF-PSI-CoCoSo framework is offered for resolving challenging real-life problems. To present the framework's practicality, a real-case study evaluating six suppliers concerning nine drives under economics, environmental, and technological aspects in a textile company in Turkey is conducted. The results indicate that green warehousing is the most essential driver for green suppliers, followed by recycling and damaged product ratio. A detailed sensitivity and comparison check is further conducted to display the solidity and effectiveness of the proposed framework. The suggested framework offers a reliable solution for green supplier selection and a precise sustainable rating of suppliers. Moreover, it can be addressed to solve various challenging real-world problems.
  • Küçük Resim Yok
    Öğe
    Telescopic forklift selection through a novel interval-valued Fermatean fuzzy PIPRECIA-WISP approach
    (Pergamon-Elsevier Science Ltd, 2024) Gorcun, Omer Faruk; Ulutas, Alptekin; Topal, Ayse; Ecer, Fatih
    Telescopic forklifts stand apart from other forklift types, boasting numerous benefits. They offer notable advantages, such as enhanced manoeuvrability, accessibility to elevated areas, versatility, and the capacity to operate at high speeds. Choosing appropriate telescopic forklifts can substantially enhance operational efficiency and efficacy within the industry. Concurrently, it can bolster business competitiveness by expediting logistical processes, yielding notable cost reductions. Nonetheless, the intricacy and specificity inherent in these machines complicate the decision-making process for stakeholders. Furthermore, conflicting criteria, the continuous evolution of manufacturers' models, and the industry's intricate nature compound the selection challenges. Hence, there is a pressing need for a resilient, dependable, and practical decision-making framework capable of adeptly navigating uncertainties to yield reliable and coherent outcomes. This study aimed to develop an integrated decision-making model based on interval-valued Fermatean fuzzy (IVFF) sets to respond to these requirements and address this critical decision-making problem in the relevant industry, which is also significantly affected by complex uncertainties. This work, therefore, introduces an integrated methodology for decisionmaking, IVFF-PIPRECIA and IVFF-WISP techniques. IVFF-PIPRECIA determines criteria importance weights, whereas IVFF-WISP identifies optimal alternatives. A case study in the textile industry validates the framework's practicality. Purchase price emerges as the primary criterion, exceeding 500 thousand euros for telescopic forklifts, followed closely by load-carrying capacity. The second alternative proves to be the best option. Comparative and sensitivity analyses confirm the model's credibility. The approach effectively handles decisionmaking uncertainties, yielding competitive outcomes. It can be applied to diverse engineering problems. Insights from this study assist users in selecting optimal equipment and may inform forklift manufacturers in improving machinery. Future research could focus on establishing real-time operational data collection frameworks for these vehicles.