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Yayın Developing organizational maturity for effective project management(IGI Global, 2018-03-09) Silvius, A. J.Gilbert; Karayaz, GamzeDespite criticism for their serious shortcomings, maturity models are widely used within organizations. The appropriate applications of these models can lead to organizational and corporate success. Developing Organizational Maturity for Effective Project Management is a critical scholarly publication that explores the successes and failures of maturity models and how they can be applied competently to leadership within corporations. Featuring coverage on a wide array of topics such as project management maturity, agile maturity, and organizational performance, this publication is geared toward professionals, managers, and students seeking current research on the application of maturity models to corporate success.Yayın The modified proactive feedback based flow control scheme for best-effort applications(International Institute of Informatics and Systemics (IIIS), 2007) Dağ, TamerHigh speed networks that are characterized by large bandwidth propagation delay products are expected to support applications with diverse traffic characteristics and Quality of Service (QoS) requirements. Thus, flow control schemes are needed for an efficient usage of the network bandwidth. A proactive feedback (PF) based flow control scheme developed by the author attempts to eliminate the bandwidth mismatch problem seen in such networks by generating and transmitting early feedbacks based on the application characteristics. In this paper, an extension of this scheme to large scale networks is presented. Due to the bottlenecked network nodes, some best effort applications may not be able to use their assigned bandwidth. For such cases, a modified version of the proactive feedback based (MPF) flow control scheme is introduced. It is observed that without affecting the other applications the best effort traffic can be significantly increased.Yayın Readiness and mindset for IT offshoring: Insights from banking and insurance organizations(2009-07-13) Aydın, Mehmet Nafiz; de Groot, Jeroen; Van Hillegersberg, JosIn this research we examine the IT offshore outsourcing (offshoring) practice of a number of leading finance and insurance organizations in the Netherlands. In particular, we investigate the readiness (the state, condition or quality of being ready) and mindset (habits, opinions which affect a person's attitudes) of the organizations for IT offshoring. We examine IT offshoring practice from the process perspective (that is, the dynamics of IT offshoring projects in terms of culture, method use, IT activities, IT governance, knowledge sharing). Among other findings, this research shows that to a greater extent the organizations have realized readiness for method use and mindset for IT activities, and that the overall improvements regarding these aspects have been modest in a two-year period. On the other hand, mindset for dealing with cultural difference has increased while readiness for flexible working, tracking of requirements change, efficient division of work, and systematic communication is still inadequate. Theoretical and practical implications of the findings are further discussed.Yayın Comparing pre-trained and fine-tuned transformer-based models for sentiment analysis in Turkish comments in student surveys(Institute of Electrical and Electronics Engineers Inc., 2025-08-15) Pourjalil, Kajal; Ekin, Emine; Recal, FüsunStudent surveys are essential for evaluating teaching quality and course content, but analyzing open-ended responses is challenging due to their unstructured and multilingual nature. This study applies sentiment analysis to Turkish educational survey responses using three transformer-based models: SAVASY, DBMDZ BERT Base Turkish Cased, and XLM-RoBERTa Base. A labeled dataset of real-world student comments was used, with sentiment labels assigned using the Gemini AI tool to facilitate model fine-tuning. Evaluation metrics included accuracy, F1-score, precision, recall, and confidence scores. Results show that fine-tuning improves sentiment classification, effectively identifying positive, negative, and neutral sentiments. This highlights the value of transformer models in analyzing Turkish student feedback.
