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    Analyzing the Industry 5. Adoption Barriers in the Pharmaceutical Sector Using an Integrated Fuzzy MCDM Methodology: A Case Study Application for Turkey
    (Springer International Publishing Ag, 2024) Maden, Ayca
    Industry 5.0, emerging as a response to the mechanistic approach of Industry 4.0, seeks to integrate human-centric perspectives with advanced technologies to address global challenges. This transformative concept is reshaping sectors like pharmaceuticals, introducing novel manufacturing paradigms to meet evolving consumer demands. However, the pharmaceutical industry faces adoption barriers hindering its transition to Industry 5.0. This study analyses these barriers within the Turkish pharmaceutical sector using an integrated MCDM methodology. As a result of evaluations obtained from decision-makers, the use of fuzzy numbers was deemed necessary in this study. A key focus of this study involves applying the Fuzzy DEMATEL method to ascertain the significance of critical Industry 5.0 barriers. Additionally, the research expands its analysis by employing the EDAS method to prioritize the functions within a specific company. The EDAS method yielded the following ranking for the functions of the company: manufacturing, regulatory affairs, research and development, quality control and assurance, and sales and marketing. This research contributes to advancing Industry 5.0 implementation strategies, fostering innovation, and enhancing competitiveness within the pharmaceutical sector.
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    Evaluation of Critical Success Factors for Antifragile Supply Chains Using Delphi and Fuzzy QFD Methods
    (Polska Akad Nauk, Polish Acad Sciences, 2024) Maden, Ayca; Ozceylan, Eren; Muhacir, Dilara; Mrugalska, Beata
    The antifragile supply chain (ASC) provides a significant advantage compared to traditional systems, particularly when considering the impacts of unexpected crises such as COVID-19. Such challenging events highlight the value of the ASCs that enable businesses to navigate crises turn these challenges into opportunities, and continuously strengthen their structures. While resilience strategies gain attention, practical studies on ASCs are limited. This study applies a case study to examine critical success factors for ASCs, demonstrating the practical application of the Delphi and Fuzzy QFD method within Boyar Kimya, a textile manufacturer. By understanding the relationships between customer needs and critical success factors, the analysis contributes to determining and effectively implementing ASC strategies. The study concludes by unveiling key success factors, including SC risk management, information sharing, proactive management, efficient knowledge processes, collaboration, and innovation strategies. This research provides a valuable roadmap for enhancing SC efficiency and sustaining a competitive advantage.
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    Evaluation of factors affecting the decision to adopt blockchain technology: A logistics company case study using Fuzzy DEMATEL
    (Ios Press, 2020) Maden, Ayca; Alptekin, Emre
    Blockchain practices have been attracting attention in industries other than financial services, since blockchain is not only an information technology, but also an institutional technology owing to its new currency economics and distributed structures. Today, supply chains, power, and food/agriculture have emerged as promising areas in terms of their potential to incorporate blockchain technology for improving processes and reducing costs. Logistics corporations, especially, have been concentrating on developing efficiency in integrated data, fleet management, and communication issues, to achieve cost advantages. Experts from a well-known logistics company in Turkey contributed to our study by helping to assess critical factors for successful blockchain technology implementation. Our research topic included determining whether blockchain technology is suitable for this company. Fuzzy decision-making trial and evaluation laboratory (DEMATEL) was used to determine and evaluate the critical factors to encourage blockchain technology adoption, based on the company's requirements. For the company experts, the factors affecting the decision to adopt blockchain technology were, in order of priority: cryptocurrency, instant money transfer, privacy, real time processing, smart contract, security, authentication, transparency, immutability, traceability, distributed ledger, reduced delays, and peer-to-peer networks.
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    Evaluation of sustainable metaverse characteristics using scenario-based fuzzy cognitive map
    (Pergamon-Elsevier Science Ltd, 2024) Maden, Ayca; Yucenur, G. Nilay
    Metaverse, a virtual world that is parallel to the real world, has gained significant attention in recent years. This is because of the merging of platforms such as Facebook, Instagram, and WhatsApp under the Meta umbrella, intending to encompass all forms of digital communication and virtual environments. The COVID-19 pandemic has further accelerated this trend, as the need for virtual social interaction has grown due to the cancellation of in-person events. However, creating a metaverse environment parallel to the real world necessitates an exami-nation of its sustainability dimensions, including those from economic, environmental, social, and technological viewpoints. A sustainable metaverse must possess certain characteristics, such as being able to meet high computational demands, being interoperable and scalable, and having appropriate norms and regulations in place. This study aims to evaluate the characteristics of a sustainable metaverse in detail. The Fuzzy Cognitive Map is used to handle negative causal relationships and address the lack of crisp data. Additionally, scenario analysis is conducted to examine the impact of changes in specific characteristics on other characteristics. The results of this study provide valuable insights into the understanding of the metaverse and can serve as a valuable resource for those working to create a sustainable virtual world.
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    Influential factor analysis for cloud computing technology service provider
    (Elsevier Science Inc, 2023) Buyukozkan, Gulcin; Uzturk, Deniz; Maden, Ayca
    Nowadays, computer processes and applications are run on remote Internet servers providing many cloud ser-vices for their users. The increasing number of services, whose features are continually being refreshed, make it challenging to choose the most appropriate option. Evaluation of CCT (Cloud Computing Technology) service providers requires identifying important criteria and their impact on users' decision-making. This paper provides a detailed literature review of these criteria. The method is based on Multi-Criteria Decision-Making (MCDM) since unfavorable and beneficial criteria must be evaluated together to ensure that decision-making is efficient and comprehensive. The process is handled by gathering linguistic expert evaluations on different CCT service providers using a group decision-making (GDM) approach. The 2-Tuple DEMATEL method is applied to reveal the relationships between criteria and dimensions. The weights of the evaluation criteria are determined based on the findings of the empirical study. The impacts of each evaluation criterion are also obtained. The proposed framework enables IT managers and/or related managers to better evaluate CCT services. The empirical findings may produce a guide for users to find out about the system components of CCT. The research results will help companies assess and select the most suitable CCT using linguistic evaluation. The originality of this paper comes from its comprehensive strategical analysis of key factors of CCT to determine standards for service provider assessment. In addition, the researchers recommend the linguistic DEMATEL application, in which decision -makers (DMs) use the linguistic set with which they are comfortable and familiar to assess the relationship between evaluation dimensions and criteria.
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    Location selection for a photovoltaic agricultural with f-PIPRECIA and WASPAS methods: A case study
    (Pergamon-Elsevier Science Ltd, 2025) Yucenur, G. Nilay; Maden, Ayca
    Photovoltaic agriculture stands out as an innovative approach that integrates traditional agricultural practices with solar energy production. This approach aims to enhance sustainability and efficiency by utilizing agricultural land for both energy generation and food cultivation. With escalating energy demands and growing environmental concerns, the significance of photovoltaic agriculture is increasingly recognized. This study addresses the critical issue of selecting optimal locations for such investments in T & uuml;rkiye. Within the framework of this study, we propose a hierarchical multi-criteria decision-making model comprising 6 primary criteria, 26 subcriteria, and 5 alternative locations. The proposed model is navigated using the F-PIPRECIA and WASPAS methods. In the initial phase of our solution, we apply the F-PIPRECIA method in a fuzzy logic environment to assign weights to the 26 sub-criteria. Subsequently, in the second phase, we employ the WASPAS method to evaluate and rank the five alternative locations. The study's findings indicate that Konya province emerges as the most suitable location for establishing photovoltaic agricultural sites in T & uuml;rkiye. Following Konya, Bal & imath;kesir and Malatya provinces were identified as the second and third most suitable options, respectively. These conclusions stem from a comprehensive assessment of factors encompassing climate, environment, economy, society, and risk. The insights derived from this research offer valuable guidance to private and public institutions, investors, and farmers in T & uuml;rkiye, assisting them in identifying the most favourable photovoltaic agricultural areas tailored to diverse criteria.
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    Selection of a sustainable location for waste electrical and electronic equipment recycling plant using Entropy and Evaluation based on Distance from Average Solution
    (Sage Publications Ltd, 2024) Maden, Ayca
    The production and consumption of electronic goods have experienced a significant increase over the years, leading to a substantial surge in the global volume of electronic waste, commonly referred to as Waste Electrical and Electronic Equipment (WEEE). The selection of a sustainable location for WEEE recycling plants plays a crucial role in mitigating environmental concerns, preserving resources and promoting economic development. It signifies a proactive and responsible approach to electronic waste management in the contemporary world. To tackle the challenge of selecting sustainable locations for WEEE recycling plants, this study employed the Entropy and Entropy and Evaluation based on Distance from Average Solution (EDAS) methodologies, evaluating 10 alternative cities in Turkey based on 13 criteria. The selected criteria include land cost, personnel cost, energy cost, availability of labour, government support degree, tax preferences, road network accessibility, number of electronic equipment producers, existence of recycling plants, suitability of land use, population and availability of renewable resources (wind power and solar energy). The Entropy method was employed to calculate the weights assigned to each criterion, whereas the EDAS method was utilized to evaluate the decision alternatives. The results provide region-specific recommendations, such as Antalya for the Mediterranean region and Samsun for the Black Sea region. The literature lacks sufficient research on the selection of sustainable locations for WEEE recycling plants. Furthermore, the utilization of real data enhances the study's credibility and provides practical insights for decision-making. The selection of a sustainable location for a WEEE recycling plant in Turkey not only demonstrates the country's environmental commitment but also sets a global example for responsible waste management.
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    Sequential MCDM methods for site selection of hydroponic geothermal greenhouse: ENTROPY and ARAS
    (Pergamon-Elsevier Science Ltd, 2024) Yucenur, G. Nilay; Maden, Ayca
    With the increasing global population, there is a growing need for agricultural land and an associated impact on greenhouse activities. In response to issues of limited energy and natural resources, the use of hydroponic greenhouses that use renewable energy sources has become increasingly popular. Among these, the use of geothermal energy in hydroponic greenhouses has garnered particular attention. In this study, we propose a sequential solution method that incorporates the Entropy and ARAS methods for the location selection of hydroponic greenhouses heated by geothermal energy. The model considers 5 main criteria, and 21 sub -criteria, and evaluates five alternative cities in Turkey. The weighting of the criteria was established through the Entropy technique. Subsequently, the decision alternatives were ranked using the ARAS method. The results of the study revealed that Denizli province is the most appropriate location for the establishment of a hydroponic geothermal greenhouse in Turkey. The alternative cities of Aydin and Afyonkarahisar were found to be the second and third most suitable provinces respectively. This determination was made based on a thorough evaluation of various factors such as geothermal resources, land availability, and infrastructure. The results of the study align with Turkey ' s potential for using geothermal energy and its existing greenhouse areas. This study highlights the potential for using geothermal energy in the cultivation of crops in Turkey and suggests that the establishment of hydroponic geothermal greenhouses in these provinces can be a viable and sustainable solution for increasing food production. The proposed sequential solution method may serve as a valuable tool for guiding investment decisions related to geothermal greenhouse applications in other countries.