Browsing by Author "Tirkolaee, Erfan Babaee"

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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: 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: 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: 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.
An Integrated Decision-Making Framework to Evaluate the Route Alternatives in Overweight/Oversize Transportation
(Pergamon-Elsevier Science Ltd, 2026) Gorcun, Omer Faruk; Kundu, Pradip; Kucukonder, Hande; Dogan, Gurkan; Tirkolaee, Erfan Babaee; 01. Kadir Has University; Business Administration
Overweight and oversized transport (O&OT) has become one of the most critical elements of project logistics, driven by advancements in transportation and lifting technologies that now allow high-volume loads to be moved across long distances. This type of transportation operation, also called abnormal transportation, is greatly affected by technical factors such as the weight and geometry of the load, road surface, axle load limitations, slope, and ground strength, as well as external variables such as weather conditions, traffic density, and legal regulations. In planning and operational processes, Decision-Makers (DMs) and practitioners who plan and execute operations without adequately considering these factors and variables can lead to delays in operations, serious risks, and loss of productivity. This research proposes a flexible decision support model that integrates Step-wise Weight Assessment Ratio Analysis (SWARA) and Logarithmic Percentage Change-driven Objective Weighting (LOPCOW), and a ranking technique; i.e., Mixed Aggregation by Comprehensive Normalization Technique (MACONT) techniques to address the decision problems related to route selection, one of the most critical problems in transporting heavy and bulky loads, and to produce reasonable solutions. The proposed model significantly reduces information losses by processing subjective and objective information and integrating subjective (SWARA) and objective (LOPCOW) methods. Unlike traditional ranking approaches, the MACONT method combines three different normalization techniques to determine the ranking performance of alternatives. In this way, it provides more reliable and accurate results by reducing the deviations of the results provided by the single normalization technique. In addition, it shows each alternative's good and bad performance compared to the others and is more convincing about the results obtained. According to the results obtained by applying the proposed model, fuel consumption (0.096) is determined as the most effective and critical factor in selecting the route on which heavy and bulky loads will be transported. In this context, choosing routes that allow lower fuel consumption can contribute to reducing carbon emissions and external costs arising from transportation. The extensive robustness and validation check to test the proposed model prove that the proposed model is a reliable, robust, and practical decision-making tool for making reasonable and rational decisions in O&OT.
Citation - WoS: 3
Citation - Scopus: 3
Sustainability performance assessment of freight transportation modes using an integrated decision-making framework based on m-generalized q-neutrosophic sets
(Springer, 2024) Gorcun, Omer Faruk; Tirkolaee, Erfan Babaee; Aytekin, Ahmet; Korucuk, Selcuk; Business Administration; 01. Kadir Has University
The freight transport industry is one of the primary sectors responsible for excessive energy consumption and greenhouse gas emissions. Restructuring international and domestic freight transport chains based on sustainability and green transportation is critical for practitioners and policymakers to reduce pressure on the logistics and transportation industries. This study aims to develop a mathematical model for selecting the most appropriate transportation type, and accordingly, the optimal route in transportation operations to improve the sustainability performance of the freight transportation industry. Therefore, the main goal is to choose the most suitable route and transportation type which contributes to create a more eco-friendly and sustainable transportation system. For this purpose, Neutrosophic Number-based Delphi (NN-Delphi), m-Generalized q-Neutrosophic Sets (mGqNSs)-based Stepwise Weight Assessment Ratio Analysis (MGqNS-SWARA) and mGqNSs-based Additive Ratio Assessment (mGqNS-ARAS) are developed and implemented to set the influential criteria, compute the weights of these criteria, and identify the sustainability performance of the freight mode variants, respectively. According to the final results, "Cargo security" and "Accident rates" are the most important criteria with a relative importance score of 0.0237, contributing to the sustainability of load transport modes. Moreover, "Maritime Transport Mode" is identified as the most sustainable transportation type with a relative importance score of 0.7895. Finally, it is revealed that there is a positive relationship between maritime transport and sustainability.