İZÜ Araştırma ve Akademik Performans Sistemi
DSpace@İZÜ, İstanbul Sabahattin Zaim Üniversitesi’nin bilimsel araştırma ve akademik performansını izleme, analiz etme ve raporlama süreçlerini tek çatı altında buluşturan bütünleşik bilgi sistemidir.
İndekslere Göre Dağılım
Yıllara Göre Dağılım
Türlere Göre Dağılım
Güncel Gönderiler
Öğe Türü: Yayın , A Comparative Analysis of Green Transition Efficiency Among European SMEs(Springer, 2025) Güdelek, Mehmet; Toprak, Biset; Zaim, Selim; Toprak, BisetEnvironmental pollution, resource scarcity, and high energy consumption accelerated in the last decade have made the green transition imperative, and consequently, the European Union (EU) has led the way in implementing green policies. According to recent surveys, SMEs in the EU have made strides toward sustainability since 2018. However, the ongoing transition of SMEs needs to be further strengthened. The European Innovation Council was committed to supporting SMEs with funding to promote Green Deal innovation. Moreover, the Green, Digital, and Competitive SME Index was established to facilitate this transition. Existing literature indicates that research on assessing green transition and variations between or within countries is still in its early stages and demands further investigation. To the authors’ knowledge, no prior study has focused on measuring the green transition efficiency of SMEs. Given the critical importance of SMEs in the adoption of a green growth model, it is crucial to assess the green transition efficiency of SMEs across and within countries. This study addressed this gap by analyzing the green transition efficiency of European SMEs through the Green Transition pillar of the Green, Digital, and Competitive SME Index. In the study, European SMEs’ green transition efficiency was analyzed using various DEA models, including CCR (Charnes, Cooper, and Rhodes), Cross-Efficiency, Aggressive, and Benevolent Models. The findings revealed that Sweden consistently emerged as the top performer, demonstrating strong overall capabilities. The Netherlands and Denmark also frequently ranked highly, indicating strong performance across various metrics. In contrast, Bulgaria, Romania, and Ireland consistently ranked lower, revealing ongoing performance issues. The study's findings indicated that the overall performance of the DEA models closely aligns with the Green Transition pillar of the Green, Digital, and Competitive SME Index.Öğe Türü: Yayın , Reconciling Different Institutional Logics: Institutional Work in Translating Sustainable PSS(Academy of Management, 2025) Bağcı, Rifgi Buğra; Raja, Jawwad Z.; Gölgeci, Ismail; Bağcı, Rıfgı BuğraBusinesses increasingly adopt product-service systems (PSS) to reconcile profit with environmental and social responsibility, yet face significant challenges due to differing institutional logics. This study investigates how these logics shape PSS adoption and the role of institutional work in navigating and translating PSS across contexts. Through a qualitative case study, we identify three institutional logics: commercial, state, and sustainability. These logics are shaped by institutional work in their local context by (1) strategically creating sustainability, (2) maintaining coupling practices, and (3) addressing the disruption trade-off. The present study links institutional logics and work within the context of sustainable PSS adoption.Öğe Türü: Yayın , Enhanced Human Activity Recognition (E-HAR): Leveraging Sensor Fusion, Placement and Algorithmic Strategies for Improved Activity Recognition(Institute of Electrical and Electronics Engineers Inc., 2025) Raza, Muhammad Owais; Bhatti, Sania; Rasheed, Jawad; Aşuroğlu, Tunç; Rasheed, Jawad;Activity recognition, a crucial aspect of healthcare monitoring, relies on accurate data processing from various sensors for effective analysis. This paper proposes a framework Enhanced Human Activity Recognition (E-HAR) to optimize activity recognition systems by integrating sensor fusion techniques and algorithmic selection strategies. Leveraging diverse datasets encompassing multiple sensor types and placements, our study explores the performance of various algorithms across distinct sensor data categories. The framework E-HAR prioritizes Dataset D3, characterized by consistent high performance across algorithms, establishing it as a reliable source for activity recognition model training. Decision Tree (DT) and Multi-Layer Perceptron (MLP) algorithms emerge as versatile choices due to their robustness across datasets. Furthermore, sensor type and placement significantly impact recognition accuracy. Vitals and ankle sensors demonstrate superior performance, emphasizing their efficacy in achieving higher F1 scores. The combination of these sensors showcases the potential for enhanced accuracy through sensor fusion. By outlining an optimal pathway for activity recognition, this research contributes a structured approach for healthcare practitioners and researchers to effectively design and implement activity recognition systems, enhancing the reliability and accuracy of healthcare monitoring in diverse contexts.Öğe Türü: Yayın , Assessing Customer Satisfaction and Loyalty in the Energy Sector Through Service Quality: A Modified SERVQUAL Analysis(Springer, 2025) Çiçeklidağ, Pasa; Nebati, Emine Elif; Gülen, Kemal Güven; Zaim, Selim; Nebati, Emine ElifThis study examines the impact of service quality on customer satisfaction and loyalty in the energy sector using the SERVQUAL model. Key dimensions such as reliability, empathy, and physical features were found to significantly influence customer satisfaction. The research involved an online survey, with data analyzed using Structural Equation Modeling (SEM) to identify both direct and indirect effects of service quality dimensions on customer satisfaction and loyalty. Results show that improving reliability and empathy can notably enhance customer satisfaction, leading to stronger customer loyalty. However, the study acknowledges limitations, such as the generalizability of results due to the online nature of the survey and the study's focus on a specific geographical region. The use of verbal data may also introduce bias, which future research could address by applying more detailed data collection methods and examining sub-factors. The study concludes that energy companies should refine their service strategies to better meet customer expectations, suggesting further research in different regions and sectors.Öğe Türü: Yayın , Assessing and Weighting Key Barriers to Sustainable Manufacturing in Türkiye(Springer, 2025) Avunduk, Zehra Binnur; Toprak, Biset; Kahveci, Eyup; Zaim, Selim; Yilmaz, Mustafa Kemal; Toprak, BisetThe rapid depletion of natural resources, environmental pollution through harmful chemical waste, and the continuous rise in greenhouse gas emissions have made it imperative for industries worldwide to adopt sustainable manufacturing methods. While such methods are increasingly implemented in developed countries, businesses in developing economies face significant challenges in adopting sustainable manufacturing practices. In a developing country like Türkiye, various factors contribute to these challenges. To address this issue, the aim of this research was to prioritize the key barriers to adopting sustainable practices in the Turkish manufacturing industry. The Weight Assessment Ratio Analysis (SWARA) method, a multi-criteria decision-making (MCDM) technique, was employed in this study due to its ease of use, minimal requirement for pairwise comparisons, and ability to enhance expert collaboration in the decision-making process. Four experts evaluated a total of 39 sub-criteria under the main categories of Technological (T), Knowledge & Learning (KL), Social & Environmental (SE), Organizational (O), Economic & Managerial (EM), and Supply Chain Management (SCM). The findings revealed that the top five key barriers in the Turkish manufacturing industry are: (1) lack of awareness of sustainability concepts (KL1), (2) unclear or weak business case and vision (O6), (3) lack of locally conducted awareness programs (KL2), (4) lack of knowledge or training for sustainable manufacturing (KL5), and (5) lack of support from top management (O2). For future studies, it is essential to investigate the effectiveness of targeted strategies designed to address these barriers and facilitate the successful integration of sustainability into manufacturing processes.
