Gülçin Büyüközkan

1. Supply chain (SC) refers to the complex network of activities, people, organisations, resources, and information involved in providing a service or product to the consumer. In this network, adop...

E-ticaret ekosistemi; pazar yerleri, çevrim içi perakendeciler, ödeme sistemleri, lojistik şirketleri, platform sağlayıcılar, üreticiler ve markalardan oluşmaktadır. Artan dijitalleşme yatırımları ve tüketici harcamaları ile küresel e-ticaret pazarı giderek büyümektedir. E-ticaret kapsamında teknolojilerin değerlendirilmesi, işletmelerin rekabet gücünü koruyabilmesi, müşteri deneyimini iyileştirebilmesi ve operasyonel verimliliğini artırabilmesi açısından son derece kritik bir süreçtir. Kullanıcıların e-ticaretten başlıca beklentileri uygun fiyat, zaman tasarrufu, ürün çeşitliliği gibi etkenlerdir. Bu sayede kullanıcılar mağazaya gitmeden satın almak istedikleri ürünle ilgili fiyat karşılaştırmasını kısa bir sürede çeşitli ürünler için yapabilir. Bu bağlamda, müşteri ihtiyaçlarının analizi rekabetçi e-ticaret ortamında büyük bir önem kazanmaktadır. E-ticaret kapsamında teknoloji değerlendirilmesi, yalnızca teknik bir gereklilik değil, aynı zamanda stratejik bir yönetim sürecidir. Bu çalışmanın amacı, dijital dünyada gelişen ve değişen e-ticaret uygulamaları için teknolojik gereksinimleri önceliklendirmek ve bu kapsamda bir teknolojik bakış açısı sunmaktadır. Bu kapsamda bu çalışmada yazın taraması ve uzman değerlendirmeleriyle belirlenen e-ticaret kullanıcı ihtiyaçları ve teknolojik gereksinimleri Kalite Fonksiyonu Yayılımı yönteminin temel aracı olan Kalite Evi yaklaşımından yararlanılarak modellenmekte, analiz edilmekte ve elde edilen bulgular yorumlanmaktadır. Müşteri ihtiyaçlarının ağırlıklarını belirlemek için Analitik Hiyerarşi Süreci (AHS) tekniği uygulanmaktadır. E-ticaret teknolojilerinin değerlendirilmesi için bir uygulama gerçekleştirilerek sonuçlar çalışmanın son kısmında paylaşılmaktadır. Çalışmadan elde edilen bulgulara göre uygun fiyat, mobil uyumluluk ve kullanıcı dostu arayüz en önemli müşteri beklentileri olarak karşımıza çıkarken yapay zeka teknolojisi ile büyük veri analitiği en kritik teknolojik gereksinimler olarak bulunmuştur.

The increasing complexity of supply chains in today's globalizing world has increased the importance of effective supply chain management. Consequently, businesses increasingly rely on new technologies to maintain flexibility, efficiency, and competitiveness. In this context, artificial intelligence (AI) technologies have the potential to offer significant opportunities at many critical junctures in supply chain management. The valuable contributions AI algorithms make to effective supply chains in areas such as supplier relationships, logistics planning, inventory management, demand forecasting, and fast and accurate decision-making demonstrate the strategic importance of this technology. However, harnessing the potential of AI technology in supply chain management requires overcoming several challenges, including technical infrastructure, human resource adequacy, data integrity, and security. In this perspective, this study is motivated by the need to identify the critical factors that will enable businesses to overcome these challenges and maximize the effectiveness of AI technologies. Therefore, this study aims to identify, model, and systematically and strategically analyze the key factors affecting the success of integrating AI into the supply chain for an effective supply chain. To this end, a model consisting of four main dimensions and 16 criteria is proposed based on a literature review and expert opinions based on Delphi method. To test the applicability and validity of the proposed model, an application was conducted using a case study in Turkey. The Analytic Hierarchy Process (AHP), one of the multi-criteria decision-making (MCDM) techniques, was used in this application. To overcome the uncertainty, intuition, and hesitancy due to human perception inherent in real- life decision-making processes, the AHP method was extended to interval-valued intuitionistic fuzzy (IVIF) sets. The analysis conducted reveals that elements such as “Strategic Vision”, “Quality of Algorithms” and “Data Security and Compatibility” are of critical importance for effective supply chain management.

Smart cities represent contemporary urbanization paradigms aimed at enhancing efficiency, sustainability, and livability through technology and data-driven solutions. Positioned as a cornerstone for a more equitable and sustainable futu re, smart cities address the pressing challenges of growing urban populations with innovative approaches. However, evaluating their performance requires comprehensive analytical methodologies capable of managing uncertainty and conflicting priorities. This study proposes an integrated hesitant fuzzy linguistic (HFL) multi-criteria decision-making framework to address this need. The methodology combines the HFL Analytic Hierarchy Process (AHP) for determining the relative importance of evaluation criteria and the HFL Evaluation Based on Distance from Average Solution (EDAS) for ranking smart cities. By embracing the flexibility and hesitancy in decision-makers’ judgments, this framework ensures robust and reliable results even under uncertain conditions. The proposed approach is applied to assess and rank smart cities, with Aalborg, Denmark, emerging as the top-performing city. Aalborg's exemplary achievements in sustainable and safe transport systems, pollution control, and environmental protection underscore its leadership in smart city initiatives. This study contributes to the field by providing a scalable and adaptable decision-support tool for policymakers and urban planners, paving the way for more effective smart city performance evaluation.

Collaboration is increasingly recognized as a key enabler of sustainability in complex agri-food systems. This study proposes a novel decision-support framework—2TL-DAD (2-Tuple Linguistic DEMATEL–Axiomatic Design)—to assess which sustainable agriculture models best foster meaningful stakeholder collaboration. The method integrates expert-based linguistic evaluations, causal relationship mapping, and design-performance alignment to provide structured, context-sensitive prioritization. A case study with Turkish experts was conducted to test the model’s applicability and robustness under varying stakeholder priorities. Results reveal that Agroecology and Permaculture consistently outperform other alternatives. The framework offers a flexible tool for supporting policy and strategy design in sustainability transitions, with future potential for adaptation across different decision contexts and criteria.