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    Addressing barriers in smart port development: prioritising strategies for effective implementation
    (Taylor & Francis Ltd, 2025) Erdogan, Melike; Seker, Sukran; Aydin, Nezir; Ayyildiz, Ertugrul
    The need for efficient and sustainable logistics solutions has been highlighted as the rapid growth of global trade places extraordinary pressure on port systems. The concept of 'smart-ports' has emerged to leverage technologies such as automation, artificial intelligence, the Internet of Things, and big data analytics to enhance port performance as traditional port operations face challenges such as congestion, resource inefficiency, and environmental concerns. However, various political, economic, technological, social, and environmental barriers prevent the successful implementation of smart ports. This study addresses this gap by focusing on the barriers to developing smart ports, using a strategic framework to prioritise solutions. It contributes to the literature by proposing a hybrid decision-making approach that integrates PESTEL, Stepwise Weight Assessment Ratio Analysis (SWARA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) under fuzzy logic for the first time in the context of smart ports. The study provides a comprehensive roadmap for policymakers and stakeholders to navigate the complexities of smart port implementations successfully. Findings suggest that comprehensive stakeholder engagement for digitalisation, and collaborative governance and regulatory streamlining for smart port development are the most promising strategies.
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    Addressing the challenges of using autonomous robots for last-mile delivery
    (Pergamon-Elsevier Science Ltd, 2024) Ayyildiz, Ertugrul; Erdogan, Melike
    The importance of last-mile delivery (LMD) in today's logistics networks has increased recently due to the rising popularity of e-commerce and home delivery. Various LMD modes, such as drones and autonomous vehicles, have emerged to solve the problems encountered during LMD activities and to reduce human intervention in the process. The purpose of this paper is to determine the challenges that arise when using autonomous delivery robots (ADRs) in LMD. Throughout the research, the challenges have been revealed, categorized into six titles and their significance has been calculated via the intuitionistic fuzzy (IF) pivot pairwise relative criteria importance assessment (PIPRECIA) method in conjunction with PESTEL Analysis. IF-PIPRECIA is employed for the first time in the literature with PESTEL Analysis to evaluate the challenges for the implementation of ADRs in LMD. According to the proposed methodology results, challenges related to Energy consumption, Battery life and energy management, Cybersecurity, Air pollution, and Uncertain return on investment are the most critical factors to consider when implementing ADRs in LMD.
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    A comprehensive risk assessment framework for occupational health and safety in pharmaceutical warehouses using Pythagorean fuzzy Bayesian networks
    (Pergamon-Elsevier Science Ltd, 2024) Ayyildiz, Ertugrul; Erdogan, Melike; Gul, Muhammet
    Risk assessment plays a crucial role in managing occupational health and safety in various industries, including pharmaceutical warehouses. Bayesian Networks (BN) have been widely employed for risk assessment due to their ability to handle uncertainty and quantify risks. However, the traditional BN approach has limitations in dealing with ambiguity and continuous variables. To address this, the fuzzy BN technique, combining fuzzy logic with BN, has emerged as an effective method for risk assessment. In this study, a fuzzy BN model using Pythagorean fuzzy sets is proposed for risk assessment in a pharmaceutical warehouse. The model incorporates 24 identified risk factors, and survey data is used to determine the conditional probabilities of these factors. The novelty of the study lies in the application of Pythagorean fuzzy sets and the development of risk assessment criteria specifically for pharmaceutical warehouses. The results of a comprehensive literature review and the proposed methodology are presented. A real case analysis is conducted, followed by validation and sensitivity analysis. The results provide valuable insights into enhancing occupational health and safety practices in pharmaceutical warehouses. The study contributes to enhancing occupational health and safety practices in pharmaceutical warehouses and provides a framework for future research.
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    A decision support mechanism in the determination of organic waste collection and recycling center location: A sample application for Turkiye
    (Elsevier, 2023) Ayyildiz, Ertugrul; Erdogan, Melike
    The location problem of organic waste collection and recycling plants is a significant concern for policy makers in developing countries. Factors such as rapid population growth, unplanned urbanization, and limited resources pose challenges to the efficient management of organic waste. Inadequate waste disposal practices not only endanger the environment and human health but also hinder the development of sustainable and livable cities. Therefore, it is crucial to address the specific challenges associated with locating organic waste collection and recycling facilities to ensure effective waste management and promote environmental sustainability. This study aims to identify the most appropriate location for an organic waste collection and recycling facility for compost production. This study involves identifying the most influential aspects of organic waste collection and recycling center location selection through a literature review and expert opinion. The Analytical Hierarchy Process (AHP) methodology with fuzzy interval type-2 (T2F) sets is employed to weight the criteria. The COmbinative Distance-based Assessment (CODAS) approach is extended in a T2F environment to better reflect the uncertainty and evaluate the alternative locations. The study concludes by revealing the optimal location for the food waste collection center for Trabzon city in Turkiye. To verify the validity and reliability of the proposed integrated methodology, a comparative analysis was also performed using various decision-making methods.(c) 2023 Elsevier B.V. All rights reserved.
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    Enhancing petroleum logistics with innovative decision support mechanism for fuel tanker selection
    (Springer, 2025) Murat, Miraç; Seyhan, Mehmet; Erdogan, Melike; Ayyildiz, Ertugrul
    Transportation of petroleum-based products is a complex and hazardous logistics process. Selecting the appropriate transportation vehicles for this process is crucial for ensuring safety and efficiency. Therefore, prioritizing selection criteria and choosing the most suitable fuel tanker is essential in reducing potential risks and improving overall fleet operations. Given the many types of tankers available for petroleum product transportation, decision-makers should employ a multi-criteria decision-making (MCDM) approach to identify the best option for their specific needs. This study introduces a novel MCDM approach that combines the Weighted Aggregated Sum Product Assessment (WASPAS) and the Criteria Importance through Intercriteria Correlation (CRITIC) in a Fermatean fuzzy (FF) environment, addressing five main criteria and evaluating five fuel tanker alternatives. Using this approach, the research identified and prioritized key criteria for selecting an appropriate tanker model by providing insights into 24 sub-criteria. The results reveal that tanker price emerges as the most important sub-criterion, leading us to determine the M3 tanker model as the most suitable fuel tanker after carefully evaluating all 24 different sub-criteria. The findings can significantly assist petroleum firms in making informed decisions when choosing fuel tankers by considering various technical, operational, comfort, environmental, and economic factors. The results can also be used to inform policy on fuel distribution. © 2025 Elsevier B.V., All rights reserved.
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    Enhancing resilience in CSCs: a SCOR-integrated fermatean fuzzy AHP approach
    (Emerald Group Publishing Ltd, 2025) Ayyildiz, Ertugrul; Erdogan, Melike
    PurposeThe purpose of this study is to propose a novel framework that utilizes interval-valued fermatean fuzzy analytic hierarchy process (IVFF-AHP) to assess the resilience of circular supply chains (CSC)s. By categorizing resilience-related factors into different levels and determining their weights using IVFF-AHP, the framework aims to provide a comprehensive evaluation of the resilience of CSCs.Design/methodology/approachThe proposed framework integrates the concepts of CSCs, fuzzy multi criteria decision-making (MCDM) methods and the supply chain operations reference (SCOR) model. The SCOR model serves as a basis for identifying the factors relevant to resilience assessment. The framework then employs IVFF-AHP to determine the relative weights of these factors at each level, accommodating the inherent uncertainties and linguistic evaluations associated with assessing resilience.FindingsThe findings of this study highlight the efficacy of the IVFF-AHP-based framework for assessing the resilience of CSCs. By considering multiple factors at different levels and applying fuzzy AHP, the framework provides decision-makers with a comprehensive understanding of the resilience of CSCs. The use of IVFF-AHP enables the effective handling of vague and imprecise information, enhancing the decision-making process.Practical implicationsBy employing IVFF-AHP, decision-makers can better understand the factors influencing the resilience of CSCs and allocate resources accordingly. This enhanced understanding can aid in developing strategies to mitigate risks, enhance adaptability and improve the overall resilience of CSCs.Originality/valueThis study contributes to existing literature by introducing a novel framework that combines IVFF-AHP, CSCs and the SCOR model for assessing resilience. The application of fuzzy MCDM methods to evaluate the resilience of CSCs represents a significant novelty. The integration of the SCOR model further enhances the practical value of the framework, as it provides a standardized reference for identifying resilience-related factors. This research offers a unique and valuable perspective for researchers and practitioners in the field.
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    A fermatean fuzzy SWARA-TOPSIS methodology based on SCOR model for autonomous vehicle parking lot selection
    (Elsevier, 2024) Ayyildiz, Ertugrul; Erdogan, Melike
    Population growth in crowded cities and the resulting increase in vehicle use have led to the problem of insufficient parking. When public parking lots and urban growth are not in coordination, vehicles park on the street and close the crosswalks. In the coming years, this problem will become more complicated with the addition of autonomous vehicles (AVs) to urban traffic. This study addresses the research question of how to effectively select AV parking lots in urban areas experiencing population growth and increased vehicle usage. For this aim, a hybrid Multi-Criteria Decision Making (MCDM) methodology, combining SWARA (Step-wise Weight Assessment Ratio Analysis) and TOPSIS (Technique for Order Preference by Similarity) approaches in a Fermatean Fuzzy (FF) environment is proposed. The decision hierarchy based on the SCOR model has been developed to determine and construct the evaluation criteria. Then, a case study analysis has been applied to selected districts in Istanbul, which is Turkiye's most populous and developing city. Operating expenses, safety and security, and land costs are determined as the most important factors. As a result of the detailed fuzzy analysis, which districts should primarily be chosen for AV parking lots in Istanbul is determined and finally, the robustness and validity of the results obtained by the sensitivity analysis being questioned. The study contributes by providing insights into AV parking lot selection, demonstrating the efficacy of the proposed methodology, and highlighting the importance of addressing this issue in urban planning.
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    An integrated decision support model for effective institutional coordination framework in planning for public transportation
    (Springer, 2023) Bouraima, Mouhamed Bayane; Oyaro, Janet; Ayyildiz, Ertugrul; Erdogan, Melike; Maraka, Ndiema Kevin
    The absence of effective coordination among different institutions involved in planning for public transportation has become a prominent global concern. At present, numerous cities are grappling with the need to establish a customized framework for institutional coordination that aligns with the specific circumstances of each city. Decision-makers encounter obstacles in the form of uncertainty when evaluating strategies aimed at promoting effective institutional coordination in planning for public transportation. In this study, a two-stage model is introduced that integrated the method based on the Step-Wise Weight Assessment Ratio Analysis (SWARA) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method into a unique framework under the interval-valued spherical fuzzy (IVSF) environment to determine the weights of the criteria and ranks the strategies, respectively. A case study of Nairobi is employed to demonstrate the formulation and solution of the problem. A sensitivity analysis was carried out to evaluate the stability of the proposed model. The results of the analysis revealed that the lack of political will and corruption, inadequate participation in planning, and poor vision or plan for the city are the foremost challenges in achieving effective institutional coordination in planning for public transportation. Furthermore, the sensitivity analysis ranked the implementation of good governance principles as the top strategy to overcome these challenges. This study introduces an innovative perspective that specifically targets local governments and tackles the problem of unregulated fragmentation within public transportation agreements among diverse institutions. Furthermore, it provides a framework designed to streamline the implementation of separate public transportation initiatives.
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    Interval valued intuitionistic fuzzy AHP-WASPAS based public transportation service quality evaluation by a new extension of SERVQUAL Model: P-SERVQUAL 4.0
    (Pergamon-Elsevier Science Ltd, 2021) Tumsekcali, Ecem; Ayyildiz, Ertugrul; Taskin, Alev
    Service quality is one of the most important factors that increase the use of public transportation, especially in metropolitan cities such as Istanbul. When evaluating service quality in public transportation systems, one of the most important factors is customer satisfaction. The increase in service quality increases the usage of public transport system utilization and it helps to solve many problems such as traffic congestion, air and noise pollution and energy consumption. For this purpose, the SERVQUAL model is extended with two new criteria related to Industry 4.0 and the pandemic to understand and evaluate the service quality of public transport systems. New criteria added into the SERVQUAL model and a novel P-SERVQUAL 4.0 (Pandemic SERVQUAL 4.0) model is presented. The novel service quality evaluation model is constructed as a three level hierarchical structure to evaluate public transport systems during the pandemic. Then, the evaluation model is modeled as a multi criteria decision making problem and a novel AHP (Analytic Hierarchy Process) integrated WASPAS (Weighted Aggregated Sum Product Assessment) under interval valued intuitionistic fuzzy (IVIF) environment methodology is employed. A real case application to evaluate Istanbul public transport systems is presented in this study. The proposed novel model is applied to evaluate the most used public transportation alternatives such as IETT Bus, Metrobus, Tram, Metro and Marmaray, in Istanbul. By the application of P-SERVQUAL 4.0 model; as a result of this study, Marmaray is determined as the best alternative. The proposed methodology can be used by public or private organizations to improve their strategies and operations to adapt Industry 4.0 and prevent the spread of SARS-CoV-2 (COVID-19). Also, the main limitations and the practical and managerial implications of the study are included in the conclusions.
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    Mapping the Future: Prioritizing Selection Factors for Tomorrow’s Professions
    (Springer Science and Business Media Deutschland GmbH, 2025) Ayyildiz, Ertugrul; Erdogan, Melike; Kesici, Büşra; Aydin, Nezir
    Career selection significantly impacts an individual's financial stability, job satisfaction, and overall quality of life. As industries evolve with technological advancements and digital transformation, understanding the key factors influencing career choices has become increasingly important. This study aims to prioritize the factors affecting future career decisions using a structured multi-criteria decision-making approach. A framework comprising six main criteria and 24 sub-criteria was developed through expert opinions and a literature review. The Spherical Fuzzy Step-wise Weight Assessment Ratio Analysis (SF-SWARA) is applied to assess and rank these factors while accounting for uncertainty. The results indicate that Starting Salary is the most influential factor, followed by Alignment with Personal Goals, emphasizing the role of financial security and personal motivation in career decisions. Conversely, Remote Work Potential was ranked as the least important factor, suggesting that direct workplace interaction and industry-specific requirements remain crucial. © 2025 Elsevier B.V., All rights reserved.
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    A Pythagorean fuzzy number-based integration of AHP and WASPAS methods for refugee camp location selection problem: a real case study for Istanbul, Turkey
    (Springer London Ltd, 2021) Ayyildiz, Ertugrul; Erdogan, Melike; Gumus, Alev Taskin
    There is an increase in the number of people who have changed their country for compulsory reasons due to the wars experienced worldwide. This raises the problem of identifying the regions where these people, called refugees, will live in the countries. In this regard, we determine in this paper where the camps established for refugees living in Istanbul should be located. The presence of many quantitative and qualitative factors which should be handled in determining the best location has enabled this problem to have multi-criteria decision-making structure. In addition, the advantage of fuzzy logic is used to convert the evaluations taken from experts into available numbers and to include them in decision-making process. For this purpose, a novel model with the integration of Pythagorean fuzzy AHP and Pythagorean fuzzy WASPAS methods is proposed for the first time in the literature, to select the best location for the refugee camp. In addition, a comparative analysis is applied to determine the validity of the results obtained and the sensitivity analysis is applied to check the robustness of the model. As a result, the most suitable location for a refugee camp in Istanbul is identified reasonably with the proposed model.
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    Strategic site selection methodology for small modular reactors: A case study in Türkiye
    (Pergamon-Elsevier Science Ltd, 2025) Ayyildiz, Ertugrul; Yildirim, Betul; Erdogan, Melike; Aydin, Nezir
    Selecting the optimal site for Small Modular Reactors (SMRs) ensures operational efficiency and safety and aligns with growing energy demands and environmental goals. Given the unique challenges of climate change and the need for sustainable energy solutions, this study's innovative approach provides critical insights for making informed decisions that balance economic, environmental, and social factors. This study introduces a novel hybrid multi-criteria decision-making (MCDM) approach for selecting optimal sites for SMR in T & uuml;rkiye. The proposed methodology integrates Picture Fuzzy SWARA (PiF-SWARA) and Picture Fuzzy WASPAS (PiF-WASPAS) techniques to address site selection's complexities by evaluating criteria weights and alternative scores. PiFSWARA is employed to determine the relative importance of five main criteria and 28 sub-criteria, providing a nuanced understanding of each criterion's impact. Subsequently, PiF-WASPAS ranks the alternative sites based on these weighted criteria. This approach ensures a robust evaluation by accommodating various uncertainties inherent in the decision-making process. The case study applied to T & uuml;rkiye demonstrates the effectiveness of this method in identifying the most suitable locations for SMRs, highlighting its potential to advance the strategic planning of nuclear energy infrastructure. The study provides valuable insights for policymakers and stakeholders involved in energy planning and development.