Browsing by Author "Gorcun, Omer Faruk"

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Citation - WoS: 7
Citation - Scopus: 7
3d Printer Selection for the Sustainable Manufacturing Industry Using an Integrated Decision-Making Model Based on Dombi Operators in the Fermatean Fuzzy Environment
(Mdpi, 2024) Gorcun, Omer Faruk; Zolfani, Sarfaraz Hashemkhani; Kucukonder, Hande; Antucheviciene, Jurgita; Pavlovskis, Miroslavas; Business Administration; 01. Kadir Has University
Three-dimensional printers (3DPs), as critical parts of additive manufacturing (AM), are state-of-the-art technologies that can help practitioners with digital transformation in production processes. Three-dimensional printer performance mostly depends on good integration with artificial intelligence (AI) to outperform humans in overcoming complex tasks using 3DPs equipped with AI technology, particularly in producing an object with no smooth surface and a standard geometric shape. Hence, 3DPs also provide an opportunity to improve engineering applications in manufacturing processes. As a result, AM can create more sustainable production systems, protect the environment, and reduce external costs arising from industries' production activities. Nonetheless, practitioners do not have sufficient willingness since this kind of transformation in production processes is a crucial and irrevocable decision requiring vast knowledge and experience. Thus, presenting a methodological frame and a roadmap may help decision-makers take more responsibility for accelerating the digital transformation of production processes. The current study aims to fill the literature's critical theoretical and managerial gaps. Therefore, it suggests a powerful and efficient decision model for solving 3DP selection problems for industries. The suggested hybrid FF model combines the Fermatean Fuzzy Stepwise Weight Assessment Ratio Analysis (FF-SWARA) and the Fermatean Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (FF-RAFSI) approaches. The novel FF framework is employed to solve a critical problem encountered in the automobile manufacturing industry with the help of two related case studies. In addition, the criteria are identified and categorized regarding their influence degrees using a group decision approach based on an extended form of the Delphi with the aid of the Fermatean fuzzy sets. According to the conclusions of the analysis, the criteria "Accuracy" and "Quality" are the most effective measures. Also, the suggested hybrid model and its outcomes were tested by executing robustness and validation checks. The results of the analyses prove that the suggested integrated framework is a robust and practical decision-making tool.
Citation - WoS: 20
Citation - Scopus: 22
Analysis of efficiency and performance of global retail supply chains using integrated fuzzy SWARA and fuzzy EATWOS methods
(Springer, 2022) Gorcun, Omer Faruk; Zolfani, Sarfaraz Hashemkhani; Canakcioglu, Mustafa; Business Administration; 01. Kadir Has University
The current paper aims to fill the two severe and significant gaps in the literature related to global retail chains. First, it presents the criteria set identified by performing comprehensive fieldwork together with experts highly experienced and have extensive knowledge of the retailing industry and a detailed literature review. Secondly, it proposes a robust, applicable, and powerful novel integrated MCDM framework dealing with many complicated uncertainties. As one of the significant practical and managerial implications, the current paper highlights the significance of sustainable retailing operations to better global retail chains. After the proposed model was implemented, a comprehensive sensitivity analysis was performed to test the validation of the model and its obtained results. According to the validation test results, A12 Walmart&ASDA has remained the best option for all scenarios. It has been observed that there are slight changes that did not change the overall results in the ranking performance of some decision alternatives. As a result, the analysis results prove that the proposed integrated fuzzy approach can be applied to solve highly complex decision-making problems encountered in various fields and the retailing industry.
Citation - WoS: 1
Citation - Scopus: 1
Application of the Fuzzy Mcdm Model for the Selection of a Multifunctional Machine for Sustainable Waste Management
(Mdpi, 2025) Duan, Yu; Stevic, Zeljko; Novarlic, Boris; Zolfani, Sarfaraz Hashemkhani; Gorcun, Omer Faruk; Subotic, Marko; Business Administration; 01. Kadir Has University
In the sustainability concept, one of the most important areas is sustainable waste management, a system that significantly impacts both economic and social well-being. The aim of this paper is to create a unique model that can contribute to better and more promising waste management in local governments in order to increase the level of sustainability. The scientific contribution and novelty of this research is reflected in developing the Fuzzy M-FullEX (Modified Fuller's triangle approach extended) method for defining fuzzy weight coefficients of criteria and its integration with the Fuzzy ROV (range of value) method for ranking multifunctional machines. The unique model developed in this study encompasses 10 criteria and seven alternative solutions, including the two aforementioned Fuzzy MCDM (multi-criteria decision-making) methods and the Bonferroni operator for averaging expert assessments. The results of the Fuzzy M-FullEX-Fuzzy ROV model based on the preferences of three experts define the best multifunctional machine for efficient and sustainable waste management, which is the Venieri. The rankings are as follows: M1 > M3 > M2 > M4 > M5 > M6 > M7. The obtained results were confirmed through extensive analysis (sensitivity, comparative analysis, correlation coefficients, different matrix size) and discussion.
Citation - WoS: 11
Citation - Scopus: 13
Assessing and Selecting Sustainable Refrigerated Road Vehicles in Food Logistics Using a Novel Multi-Criteria Group Decision-Making Model
(Elsevier Science inc, 2024) Gorcun, Omer Faruk; Tirkolaee, Erfan Babaee; Kucukonder, Hande; Gargf, Chandra Prakash; Business Administration; 01. Kadir Has University
In recent years, food loss and waste (FLW) have become an essential issue at the top of the international community's agenda. Since more people are afflicted by this problem every day, the global population would be forced into poverty and starvation without finding an immediate solution. Therefore, in order to decrease FLW, well-designed and sustainable food and cold supply chains (FCSCs) are needed. Additionally, refrigerated transportation systems can be crucial in developing sustainable supply chains. According to some empirical research, the technological capabilities of reefer vehicles or trailers differ significantly. Thus, selecting the reefer vehicle is a complex decision-making problem and selecting appropriate reefer vehicles may have a critical role in constructing successful supply chain systems and reducing food waste and loss. The current research proposes an efficient, robust and practical decision-making framework that can overcome uncertainties to tackle this decision-making problem. The managerial and strategic implications of the study also aid in decreasing FLW and restructuring FSC for industrial context and support to the UN's sustainable development goals (SDGs). Later, an exhaustive sensitivity analysis was conducted to examine the developed model's validity and application, confirming the model's robustness and dependability.
Assessing the Renewable Energy Sources for Sustainable Energy Generation Systems: Interval-Valued Q-Rung Orthopair Fuzzy SWARA-TOPSIS
(Pergamon-Elsevier Science Ltd, 2026) Gorcun, Omer Faruk; Aytekin, Ahmet; Korucuk, Selcuk; Tirkolaee, Erfan Babaee
Renewable Energy Sources (RESs) help decarbonize power systems, but selecting among them is a challenging decision problem due to multiple, often conflicting, technical, economic, environmental, and health-related criteria. Consequently, numerous studies in the literature have attempted to address this decision-making issue using objective, subjective, and fuzzy decision-making procedures. However, there are still unaddressed research gaps in the literature, particularly regarding the explicit modeling of expert hesitation and ambiguity in real-world RES selection cases. The current study develops a decision-making model based on Step-wise Weight Assessment Ratio Analysis (SWARA) and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) methods integrated with Interval-Valued q-Rung Orthopair Fuzzy Sets (IV-q-ROFSs) to fill these gaps. Unlike previous studies that have predominantly applied conventional fuzzy MCDM techniques, our model introduces the first integration of IV-q-ROFS into RES selection. This novelty enables a more accurate representation of expert hesitation and uncertainty. The study is applied to a real industrial case in Turkey, where six RES alternatives are evaluated across 43 criteria by five senior experts under the supervision of a three-member professionals' board. Furthermore, the structured robustness check and systematic literature mapping ensure that the proposed approach is methodologically robust and practically relevant for policymakers and energy planners. The application results of the developed model demonstrate that the estimated energy production potential of the RES and the effects of carcinogens generated from utilizing these energy sources are the critical factors influencing the selection of the most appropriate RESs. Solar energy ranked first among the alternatives. The applicability and validity of the developed model are examined by a comprehensive robustness check consisting of tests of sensitivity, comparison, and resilience to the rank reversal problem. Overall, the study provides (i) a novel methodological framework integrating IV-q-ROFS with SWARA and TOPSIS, (ii) empirical evidence from a comprehensive real-world RES selection case, and (iii) policy-relevant insights into the drivers of renewable energy adoption.
Citation - WoS: 46
Citation - Scopus: 55
The Blockchain Technology Selection in the Logistics Industry Using a Novel Mcdm Framework Based on Fermatean Fuzzy Sets and Dombi Aggregation
(Elsevier Science Inc, 2023) Gorcun, Omer Faruk; Pamucar, Dragan; Biswas, Sanjib; Business Administration; 01. Kadir Has University
Logistics is a sophisticated system involving third-party logistics (3PL) providers, freight forwarders, warehousing companies, and transport service producers in various transport modes, such as road, rail, air, maritime, and multimodal transportation. Furthermore, it is possible to add customs clearance agencies, insurance companies, banks, and relevant institutions and organizations to the system. Effective logistics systems must sustainably provide customers with quality and satisfactory logistics services using data shared over advanced technologies. Nevertheless, data and information on logistics are usually challenging to collect, process, and understand, as they are primarily unstructured, unreachable, and unstandardized. Blockchain is a new and advanced technology promising to eliminate or mitigate the adverse effects of these difficulties. However, blockchain technology practices in the logistics industry are extraordinarily scarce; and a few blockchain platforms have attempted to produce solutions for a few large-scale and global logistics firms. Hence, the digital transformation process involving blockchain technology for a logistics company encounters the challenge of selecting an appropriate blockchain platform for the logistics industry's needs. Although studies have been carried out in the relevant literature to select a suitable blockchain platform for various industries, few of these studies dealt with selecting the best blockchain platform for the logistics industry. Hence, experimental studies on choosing the proper blockchain platform in the logistics industry that tries to manage outstandingly complicated relations and linkages among stakeholders are currently inadequate. The current study presents a novel, robust, practical, and powerful decision-making tool that can also overcome highly complex uncertainties to identify the most feasible blockchain technology for the logistics industry. The robustness of the study's findings is validated with comprehensive sensitivity and comparative analyses.
Citation - WoS: 2
Citation - Scopus: 2
Blockchain-Enabled Healthcare Supply Chain Management: Identification and Analysis of Barriers and Solutions Based on Improved Zero-Sum Hesitant Fuzzy Game Theory
(Pergamon-Elsevier Science Ltd, 2025) Razavian, Seyed Behnam; Tirkolaee, Erfan Babaee; Simic, Vladimir; Ali, Sadia Samar; Gorcun, Omer Faruk; Business Administration; 01. Kadir Has University
Blockchain technology has emerged as a transformative approach in the health sector, enhancing efficiency, transparency, and security in Healthcare Supply Chain Management (HSCM). It addresses critical issues such as data privacy, traceability, and fraud reduction, providing a secure and reliable platform. However, significant barriers to its implementation must be overcome to ensure effective healthcare supply chain operations. This study proposes a two-stage decision-making model for identifying barriers and optimizing blockchain adoption solutions in HSCM under uncertainty. The first stage employs the Hesitant Fuzzy Best-Worst Method (HFBWM) to prioritize barriers. Compared to traditional methods such as Analytic Hierarchy Process (AHP), HFBWM achieves high accuracy with fewer pairwise comparisons. In the second stage, the Improved Zero-Sum Hesitant Fuzzy Game Theory (IZSHFG) model, based on the Weighted Sum Operator (WSO) under Hesitant Fuzzy Sets (HFSs), determines the optimal combination of strategies for blockchain application in HSCM. The challenges are modeled as one player and the solutions as another, with the decision matrix established using WSO under HFS. The obtained results indicate the worst-case scenario involves the simultaneous occurrence of four critical barriers: "Lack of Sufficient Knowledge about Blockchain in HSCM" (0.011217), "Lack of Access to Skilled Technical Personnel" (0.025457), "High Maintenance and Support Costs" (0.056076), and "Security Risks of Patients' Data" (0.069367). These findings highlight the need for targeted strategies to address these barriers, ensuring blockchain's successful integration into HSCM.
Citation - WoS: 25
Citation - Scopus: 27
Container Vessel Selection for Maritime Shipping Companies by Using an Extended Version of the Grey Relation Analysis (gra) With the Help of Type-2 Neutrosophic Fuzzy Sets (t2nfn)
(Pergamon-Elsevier Science Ltd, 2022) Zolfani, Sarfaraz Hashemkhani; Gorcun, Omer Faruk; Kundu, Pradip; Kucukonder, Hande; Business Administration; 01. Kadir Has University
Contrary to expectations, based on occurring changes in customer behaviours related to consuming and shopping triggered by the pandemic, the global container shipping market has continued to grow during COVID 19. Experts estimate that these increases will continue in the future due to changing consumption habits. However, container shipping companies (CSCs) may soon encounter many troubles and challenging situations. They have an extremely fragile structure and may be entirely unprotected when they encounter unexpected situations sourced from external factors. (i.e., due to grounding of a ship, complete blockage of the Suez channel for three weeks can be given as a clear example of that). Hence, selecting an appropriate container vessel type can help construct a healthier container shipping system less influenced by adverse conditions for decision-makers and practitioners. Besides, it can provide a more effective and productive maritime transportation environment for all stakeholders. However, selecting a proper container vessel type is a complicated decision-making problem since many conflicting criteria and complex ambiguities exist. The current paper proposes an extended version of the GRA technique with the help of type-2 neutrosophic fuzzy sets (T2NFN) for capturing and processing uncertainties better than the traditional MCDM frameworks. According to the obtained results, C6, container carrying capacity, is the most influential criterion and the type of post-Suezmax container vessel is the best option for the CSCs, as it provides advantages at a satisfactory level for almost all criteria than others. After the proposed model was applied, a comprehensive sensitivity analysis (SA) was performed to test the validity of the T2NFN GRA approach. The results of SA approve the applicability, effectivity, and robustness of the model.
Citation - WoS: 15
Citation - Scopus: 16
Determining the factors affecting transportation demand management and selecting the best strategy: A case study
(Elsevier Sci Ltd, 2024) Aytekin, Ahmet; Korucuk, Selcuk; Gorcun, Omer Faruk; Business Administration; 01. Kadir Has University
Demand management in transportation services, as well as demand sustainability, demand planning, and demand implementation are critical components in service quality and environmental sustainability. It is evident that developing a transportation system, particularly one responsive to society's aspirations and demands, will result in long-term and sustainable success for enterprises. Transportation demand management and strategies can produce alternative perspectives at a desirable and sufficient level to handle problems in the field while considering the obstacles. Considering the elements influencing transportation demand management in logistics enterprises, this study aims to evaluate factors affecting transportation demand management and select the best strategy. The study was carried out on logistic firms with a corporate identity in the Turkish province of Samsun (Turkiye), engaged in international transportation activities to define the criteria affecting transportation demand management and select the best transportation demand strategy. The constituents from the literature review were analyzed using the q-rung orthopair fuzzy MCDA methodology. "Freight Transportation" was determined to be the most crucial measure affecting transportation demand management, while "Competition Legislation and Regulations Regulation" was the least important factor. The rapid expansion in the number of companies participating in freight transport and their capacity was evaluated as the essential aspect for the relevant logistics companies in transport demand management. The "Strategy for Prioritizing High Occupancy Vehicles" is the best transportation strategy based on the weights of the transportation demand management factors. Because of the implementation of this strategy in logistics organizations, this study is regarded as a significant indicator of competitiveness to ensure efficiency and effectiveness. The defined transport demand strategy also represents an exemplary model of the measures that need to be developed to increase the demand preference for sustainable transport.
Citation - WoS: 14
Citation - Scopus: 16
Efficiency Analysis Technique With Input and Output Satisficing Approach Based on Type-2 Neutrosophic Fuzzy Sets: a Case Study of Container Shipping Companies
(Pergamon-Elsevier Science Ltd, 2023) Zolfani, Sarfaraz Hashemkhani; Gorcun, Omer Faruk; Canakcioglu, Mustafa; Tirkolaee, Erfan Babaee; Business Administration; 01. Kadir Has University
This work tries to discuss and evaluate the advantages and superiorities of the extended Efficiency Analysis Technique with Input and Output Satisficing (EATWIOS) method based on Type-2 Neutrosophic Fuzzy Numbers (T2NFNs). The suggested model is maximally stable and robust by considering sensitivity analysis results which demonstrates a new performance analysis approach based on T2NFN sets. The proposed model deals with the input and output criteria and considers existing uncertainties arising from insufficient information and the dy-namic structure of the industries. The model's basic algorithm has a unique structure compared to the previous performance analysis technique, and it does not require applying additional weighting techniques to identify the criteria weights. To the best of our knowledge, the extended version of the EATWIOS technique based on the T2NFN set is presented for the first time. The developed model provides reasonable and logical results to practitioners because it deals with satisfactory outputs instead of optimal outputs. This model is an immensely strengthened version of the EATWIOS technique, as the T2NFN sets treat predictable and unpredictable un-certainties. The suggested T2NFN-EATWIOS is then applied to a real-world assessment problem in the container shipping industry. The obtained results are pretty reasonable and logical. Moreover, the results of a compre-hensive sensitivity analysis with three stages approve the robustness of the suggested model.
Citation - WoS: 1
Citation - Scopus: 2
Electric Vehicle Selection for Industrial Users Using an Interval-Valued Intuitionistic Fuzzy Copras-Based Model
(Springer, 2024) Gorcun, Omer Faruk; Simic, Vladimir; Kundu, Pradip; Ozbek, Asir; Kucukonder, Hande; Business Administration; 01. Kadir Has University
According to reports from international bodies such as the World Health Organization and the United Nations, transportation is one of the leading contributors to environmental pollution and climate change. Electric vehicles present a practical solution to reducing emissions, particularly for industrial users. However, industrial users' selection of electric vehicles involves different dynamics than individual users, making it a more complex process for companies. This paper aims to evaluate the selection criteria for electric vehicle fleets among industrial users using a novel multi-criteria decision-making framework based on interval-valued intuitionistic fuzzy sets. The model assesses various factors influencing industrial users' decisions and ranks the available electric vehicle options accordingly. The results indicate that driving range, purchase price, and charging time are the most influential factors in the decision-making process. Furthermore, the findings confirm that the Tesla Model S P100D is the most suitable option for industrial users, given its superior performance in these critical criteria.
Citation - WoS: 36
Citation - Scopus: 39
Evaluating and Selecting Sustainable Logistics Service Providers for Medical Waste Disposal Treatment in the Healthcare Industry
(Elsevier Sci Ltd, 2023) Gorcun, Omer Faruk; Aytekin, Ahmet; Korucuk, Selcuk; Tirkolaee, Erfan Babaee; Business Administration; 01. Kadir Has University
Health institutes are structurally growing depending on the population increase and escalating demands for health services. As a negative result, the health industry produces more healthcare waste daily. Its efforts and resources cannot be sufficient to dispose of such medical wastes as the quantity and variety continue to increase. Therefore, developing solution partnership relations with logistics service providers specialized in collecting, storing, and disposing healthcare waste may be a beneficial and fruitful step for solving this problem. However, the evaluation and selection of service suppliers for healthcare waste disposal may not always result in success. Hence, the present work develops a robust integrated methodology on the basis of Step-wise Weight Assessment Ratio Analysis (SWARA) and COmplex PRoportional ASsessment (COPRAS) techniques based on Interval-Valued Fermatean Fuzzy Sets (IVFFSs) for healthcare decision-makers to make more rational and optimal decisions concerning service supplier selection. The proposed model based on the IVFFSs can also overcome incredibly complicated uncertainties in the assessment processes. A large-scale international hospital chain in Turkey is investigated using the developed methodology to find reasonable and logical solutions to assess and select the best Medical Waste Disposal and Logistics (MWDL) firm. It is revealed that the most important criterion is Storage Conditions where Republic Services, Inc is the most successful supplier of MWDL. Finally, theoretical and practical implications are discussed in detail in order to provide useful managerial insights and decision aids to assist in improving the sustainability of healthcare industry.
Evaluating Green Marketing Practices in the Logistics Industry Under Type-2 Neutrosophic Fuzzy Environment
(Elsevier Sci Ltd, 2025) Gorcun, Omer Faruk; Ul Ain, Noor; Kucukonder, Hande; Durmusoglu, Serdar Salih; Uray, Nimet; Tirkolaee, Erfan Babaee
The logistics industry is under increasing pressure to implement Green Marketing (GM) strategies in response to growing environmental concerns and rising stakeholder expectations. Although international organizations and governments encourage the adoption of sustainability, practical decision support tools for executing GM strategies, particularly within logistics Small and Medium-Sized Enterprises (SMEs), remain underdeveloped. This study tries to advance the literature by introducing a novel hybrid Multi-Criteria Decision-Making (MCDM) framework that uniquely integrates Delphi, CRiteria Importance Through Inter-criteria Correlation (CRITIC), and Mixed Aggregation by cOmprehensive Normalization Technique (MACONT) methods with Type-2 Neutrosophic Numbers (T2NNs). Unlike prior fuzzy MCDM studies, this integration simultaneously incorporates subjective and objective weighting, preserves ordinal consistency, and explicitly manages higher-order uncertainty. The model is applied to evaluate the GM performance of logistics SMEs in Turkey, identify key evaluation criteria, and rank firms accordingly. Among the evaluated criteria, "Land usage" and "Investment in reducing greenhouse gas emissions" emerged as the most influential, while "Omsan Logistics" is identified as the top-performing firm in GM practices. The model's reliability is then confirmed through a two-phase sensitivity analysis, demonstrating robustness across different scenarios. The findings of this work provide significant implications for logistics managers, policymakers, and researchers aiming to enhance environmental performance and make informed decisions in complex and ambiguous operational environments.
Citation - WoS: 31
Citation - Scopus: 34
EVALUATING LOGISTICS VILLAGES IN TURKEY USING HYBRID IMPROVED FUZZY SWARA (IMF SWARA) AND FUZZY MABAC TECHNIQUES
(Vilnius Gediminas Tech Univ, 2021) Hashemkhani Zolfani, Sarfaraz; Gorcun, Omer Faruk; Kucukonder, Hande; Business Administration; 01. Kadir Has University
Positioning in the right location for organizing logistics activities is a determinative factor in the aspect of costs, effectivity, productivity, and performance of these operations carried out by logistics firms. The proper logistics village selection is a crucial, complicated, and time-consuming process for decision-makers who have to make the right and optimal decision on this issue. Decision-makers need a methodological frame with a practical algorithm that can be implemented quickly to solve these decision-making problems. Within this scope, the current paper aims to present an evaluation tool, which provides more reasonable and reliable results for decision-makers to solve the logistics village selection problem that is very complicated and has uncertain conditions based on fuzzy approaches. In this study, we propose the Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA), a modified and extended version of the traditional fuzzy Step-Wise Weight Assessment Ratio Analysis (F-SWARA) to identify the criteria weights. Also, we suggest applying the fuzzy Multi-Attributive Border Approximation area Comparison (F-MABAC) technique to determine the preference ratings of the alternatives. This combination has many valuable contributions. For example, it proposes to use a more reliable and consistent evaluation scale based on fuzzy sets. Hence, decision-makers can perform more reliable and reasonable pairwise comparisons by considering this evaluation scale. Besides, it presents a multi-attribute evaluation system based on the identified criteria weights. From this perspective, the proposed model is implemented to evaluate eight different logistics village alternatives with respect to nine selection criteria. According to the analysis results, while A8 is the most appropriate option, C1 Gross National Product (GNP) is the most significant criterion. A comprehensive sensitivity analysis was performed to test the robustness and validation of the proposed model, and the results of the analysis approve the validity and applicability of the proposed model. As a result, the suggested integrated MCDM framework can be applied as a valuable and practical decisionmaking tool to develop new strategies and improve the logistics operations by decision-makers.
Citation - WoS: 5
Citation - Scopus: 2
Evaluating the Deep Learning Software Tools for Large-Scale Enterprises Using a Novel Todiffa-Mcdm Framework
(Elsevier, 2024) Gligoric, Zoran; Gorcun, Omer Faruk; Gligoric, Milos; Pamucar, Dragan; Simic, Vladimir; Kucukonder, Hande; Business Administration; 01. Kadir Has University
Deep learning (DL) is one of the most promising technological developments emerging in the fourth industrial revolution era for businesses to improve processes, increase efficiency, and reduce errors. Accordingly, hierarchical learning software selection is one of the most critical decision-making problems in integrating neural network applications into business models. However, selecting appropriate reinforcement learning software for integrating deep learning applications into enterprises' business models takes much work for decision-makers. There are several reasons for this: first, practitioners' limited knowledge and experience of DL makes it difficult for decision-makers to adapt this technology into their enterprises' business model and significantly increases complex uncertainties. Secondly, according to the authors' knowledge, no study in the literature addresses deep structured learning solutions with the help of MCDM approaches. Consequently, making inferences concerning criteria that should be considered in an evaluation process is impossible by considering the studies in the relevant literature. Considering these gaps, this study presents a novel decision-making approach developed by the authors. It involves the combination of two new decision-making approaches, MAXC (MAXimum of Criterion) and TODIFFA (the total differential of alternative), which were developed to solve current decision-making problems. When the most important advantages of this model are considered, it associates objective and subjective approaches and eliminates some critical limitations of these methodologies. Besides, it has an easily followable algorithm without the need for advanced mathematical knowledge for practitioners and provides highly stable and reliable results in solving complex decision-making problems. Another novelty of the study is that the criteria are determined with a long-term negotiation process that is part of comprehensive fieldwork with specialists. When the conclusions obtained using this model are briefly reviewed, the C2 "Data Availability and Quality" criterion is the most influential in selecting deep learning software. The C7 "Time Constraints" criterion follows the most influential factor. Remarkably, prior research has overlooked the correlation between the performance of Deep Learning (DL) platforms and the quality and accessibility of data. The findings of this study underscore the necessity for DL platform developers to devise solutions to enable DL platforms to operate effectively, notwithstanding the availability of clean, high-quality, and adequate data. Finally, the robustness check carried out to test the validity of the proposed model confirms the accuracy and robustness of the results obtained by implementing the suggested model.
Citation - WoS: 2
Citation - Scopus: 2
Evaluating the Financial Credibility of Third-Party Logistic Providers Through a Novel Frank Operators-Driven Group Decision-Making Model With Dual Hesitant Linguistic Q-rung Orthopair Fuzzy Information
(Pergamon-elsevier Science Ltd, 2025) Sarkar, Arun; Gorcun, Omer Faruk; Ecer, Fatih; Senapati, Tapan; Kucukonder, Hande; Business Administration; 01. Kadir Has University
In the relevant literature, there is no study dealing with the financial credibility of third-party logistic providers with the help of decision-making frames. Further, there are no criteria to evaluate the third-party logistics providers' creditworthiness in practice, and decision-makers in the banks consider their judgments and experiences to assess the demand of the logistics firms. This study proposes a multi-criteria group decision-making framework through a dual hesitant linguistic q-rung orthopair fuzzy (DHLq-ROF) set to manage uncertainties more effectively and make a theoretical contribution to the academic literature. For ranking, the score function and accuracy function are defined. Additionally, some novel operational laws based on Frank t-norms and t-conorms are defined for DHLq-ROF numbers. A wide range of generalized aggregation operators, such as DHLqROF Frank weighted averaging, DHLq-ROF Frank weighted geometric, DHLq-ROF Frank generalized weighted averaging, and DHLq-ROF Frank generalized weighted geometric operators, are also investigated. Beyond that, several prominent characteristics of the proposed operators are studied. It is applied to a financial credibility problem for a multinational organization to demonstrate the introduced model's applicability. Considering the results obtained regarding the importance of the criteria, the most crucial criterion is market indebtedness, followed by fleet vehicle structure and current rate criteria, respectively. The results indicate that UPS, Kuhne & Nagel and DHL Deutsche Post are the best third-party logistic providers. The sensitivity analysis shows that the framework possesses favourable flexibility and effectiveness. Thanks to the framework's ability to produce practical solutions to challenging decision-making problems, it can be reliably preferred in engineering and other fields.
Citation - WoS: 9
Citation - Scopus: 11
Evaluation of container port sustainability using WASPAS technique using on type-2 neutrosophic fuzzy numbers
(Pergamon-Elsevier Science Ltd, 2023) Kaya, Sema Kayapinar; Kundu, Pradip; Gorcun, Omer Faruk; Business Administration; 01. Kadir Has University
According to the common opinion in the literature, the sustainability of container ports is a tremendously complex topic owing to the maritime sector's excessively dynamic form and many highly complex, predictable and unpredictable uncertainties in this industry. The current paper proposes two powerful, practical, inspiring approaches to fill these gaps. It proposes a novel type-2 neutrosophic fuzzy numbers (T2NFNs) based Delphi method to determine the criteria logically and optimal and extends the WASPAS technique based on the T2NFNs for evaluating the alternatives. The current paper presents practical managerial implications that many stakeholders can consider, such as port authorities, ship owners, logistics service providers, governments, and local authorities, when making strategic and managerial decisions. In addition, the results of a comprehensive sensitivity analysis performed to test the robustness and applicability of the model approve the validity of the proposed T2NFN-based integrated approach.
Citation - WoS: 6
Citation - Scopus: 7
Evaluation of Crawler Cranes for Large-Scale Construction and Infrastructure Projects: an Intuitionistic Fuzzy Consensus-Based Approach
(Elsevier, 2025) Gorcun, Omer Faruk; Saha, Abhijit; Ecer, Fatih; Business Administration; 01. Kadir Has University
Choosing the proper and best crawler crane is a complicated decision-making issue due to several conflicting criteria and vagueness in the construction and project logistics industries. This decision-making problem has become compounded due to insufficient studies on crawler crane selection in the relevant literature. The current study introduces an intuitionistic fuzzy consensus-based complex proportional assessment model (IF-c-COPRAS) developed to address the existing research gaps and identify the best and most suitable crawler crane. The acquired conclusions revealed that the most potent criterion influencing the crawler crane selection is "job potential," with a weighted score of 0.7665, followed by "periodic control and inspection" and "crane model year." Once the following findings of the paper regarding crawler crane variants are evaluated, the crawler crane manufactured by Liebherr Co. is the most feasible alternative, with a relative significance score of 0.8324. These outcomes provide sensible implications and insights for practitioners and decision-makers in the construction and project logistics (overweight/oversized cargo lifting and transport firms) industries, providing an applicable guideline for improving the quality of construction operations. Additionally, crane manufacturers can consider these managerial and policy implications and insights to improve the abilities and quality of the crawler cranes they produce.
Citation - WoS: 10
Citation - Scopus: 18
Evaluation of Industry 4.0 Strategies for Digital Transformation in the Automotive Manufacturing Industry Using an Integrated Fuzzy Decision-Making Model
(Elsevier Sci Ltd, 2024) Gorcun, Omer Faruk; Mishra, Arunodaya Raj; Aytekin, Ahmet; Simic, Vladimir; Korucuk, Selcuk; Business Administration; 01. Kadir Has University
The current paper proposes a methodological frame to identify the best Industry 4.0 (I4) strategy for the automotive manufacturing industry as a roadmap for companies to make a more straightforward digital transformation. We noticed a critical research gap when we performed an extensive literature review. Although there are many studies available that assess the readiness of companies for I4, only a few deal with decision -making in terms of sustainable development, and none have applied that to the automotive industry. Practitioners can apply the proposed model to determine the strategy based on technological developments in I4. The current paper proposes an extended version of the combined compromise solution approach with the help of the picture fuzzy sets. According to the paper 's results, by using the proposed model, developing a new business model based on technological improvements is the best strategy for the digital transformation of the automotive industry. Also, the lack of research and development implementations on I4 implementation is the most influential factor. Hence, practitioners in the automotive industry know the significance of research and development in reaching successful results for digital transformation. The acquired outcomes of the paper show that developing technology -based new business models is the best strategy for the automotive manufacturing industry concerning digital transformation instead of accommodating traditional business models and high technology utilization.
Citation - WoS: 15
Citation - Scopus: 13
Evaluation of Public Transportation Systems for Sustainable Cities Using an Integrated Fuzzy Multi-Criteria Group Decision-Making Model
(Springer, 2023) Kundu, Pradip; Gorcun, Omer Faruk; Garg, Chandra Prakash; Kucukonder, Hande; Canakcioglu, Mustafa; Business Administration; 01. Kadir Has University
In this era of increasing demand for mobility and rapid urban growth, there is a pressing need for a public transit system that is safe, fast, reliable, well-connected, and sustainable. Furthermore, it is essential to reduce the external costs associated with urban transportation, including environmental pollution, noise, congestion, and accidents, to foster sustainable cities. Choosing the right urban transportation system can meet this goal, but it is not an accessible business for decision-makers in the face of several conflicting criteria and ambiguities in the evaluation process. To cope with this, the current paper suggests a multi-criteria group decision-making (MCGDM) framework consisting of fuzzy BWM (Best-Worst method) and fuzzy MAIRCIA (Multi-Attribute Ideal-Real Comparative Analysis) techniques. This extended MCGDM approach has been applied to evaluate six urban transport systems, namely, Trams, Light Rail Trams, Metro (Subway), Bus Rapid Transport, Commuter Trains, and Public Buses based on 11 selection criteria which we have determined after consultation with highly experienced professionals. The fuzzy BWM technique is employed to identify the weights of the criteria. The fuzzy MAIRCA technique is utilized for ranking the alternatives using the calculated weights of the criteria. The proposed approach's validation has been examined with an extensive robustness check. The study is conducted from a general perspective, i.e., not restricted to a particular city. However, with the identified selection criteria, the proposed decision-making procedure can be repeated for a specific city considering any specific requirements, constraints, or limitations of that city.