Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Book Part Information and Communication Technology for E-Regions(IGI Global, 2008) Velibeyoǧlu, Koray; Yigitcanlar, TanInformation and communication technologies (ICTs) are essential components of the knowledge economy, and have an immense complementary role in innovation, education, knowledge creation, and relations with government, civil society, and business within city regions. The ability to create, distribute, and exploit knowledge has become a major source of competitive advantage, wealth creation, and improvements in the new regional policies. Growing impact of ICTs on the economy and society, rapid application of recent scientific advances in new products and processes, shifting to more knowledge-intensive industry and services, and rising skill requirements have become crucial concepts for urban and regional competitiveness. Therefore, harnessing ICTs for knowledge-based urban development (KBUD) has a significant impact on urban and regional growth (Yigitcanlar, 2005). In this sense, e-region is a novel concept utilizing ICTs for regional development. Since the Helsinki European Council announced Turkey as a candidate for European Union (EU) membership in 1999, the candidacy has accelerated the speed of regional policy enhancements and adoption of the European regional policy standards. These enhancements and adoption include the generation of a new regional spatial division, NUTS-II statistical regions; a new legislation on the establishment of regional development agencies (RDAs); and new orientations in the field of high education, science, and technology within the framework of the EU’s Lisbon Strategy and the Bologna Process. The European standards posed an ambitious new agenda in the development and application of contemporary regional policy in Turkey (Bilen, 2005). In this sense, novel regional policies in Turkey necessarily endeavor to include information society objectives through efficient use of new technologies such as ICTs. Such a development seeks to be based on tangible assets of the region (Friedmann, 2006) as well as the best practices deriving from grounding initiatives on urban and local levels. These assets provide the foundation of an e-region that harnesses regional development in an information society context. With successful implementations, the Marmara region’s local governments in Turkey are setting the benchmark for the country in the implementation of spatial information systems and e-governance, and moving toward an e-region. Therefore, this article aims to shed light on organizational and regional realities of recent practices of ICT applications and their supply instruments based on evidence from selected local government organizations in the Marmara region. This article also exemplifies challenges and opportunities of the region in moving toward an e-region and provides a concise review of different ICT applications and strategies in a broader urban and regional context. The article is organized in three parts. The following section scrutinizes the e-region framework and the role of ICTs in regional development. Then, Marmara’s opportunities and challenges in moving toward an e-region are discussed in the context of ICT applications and their supply instruments based on public-sector projects, policies, and initiatives. Subsequently, the last section discusses conclusions and prospective research. © 2025 Elsevier B.V., All rights reserved.Article An Alternative Software Benchmarking Dataset: Effort Estimation With Machine Learning(Elsevier Science Inc, 2026) Yurum, Ozan Rasit; Unlu, Huseyin; Demirors, OnurEffort estimation plays a vital role in software project planning, as accurate estimates of required human resources are essential for success. Traditional estimation models often depend on historical size and effort data, yet organizations frequently struggle to access reliable effort records. Public benchmarking datasets like ISBSG offer useful data but may lack coverage or involve licensing fees. To address this issue, we previously introduced a free, extendable benchmarking dataset that integrates functional size and effort data extracted from 18 studies. In this study, we examine the effectiveness of our dataset for predictive effort estimation and compare it with the widely used ISBSG dataset. Our analysis includes 337 records from our dataset and 732 ISBSG projects, focusing on those with COSMIC size data. We first developed and compared models using linear regression and nine machine learning algorithms - Bayesian Ridge, Ridge Regression, Decision Tree, Random Forest, XGBoost, LightGBM, k-Nearest Neighbors, Multi-Layer Perceptron, and Support Vector Regression. Then, we selected the best-performing models and applied them to an unseen evaluation dataset to assess their generalization performance. The results show that machine learning performance varies based on evaluation method and dataset characteristics. Despite having fewer records, our dataset enabled more accurate predictions than ISBSG in most cases, highlighting its potential for effort estimation. This study demonstrates the viability of our dataset for building predictive models and supports the use of machine learning in improving estimation accuracy. Expanding this dataset could offer a valuable, open-access resource for organizations seeking effective and lowcost estimation solutions.Conference Object Citation - WoS: 1Citation - Scopus: 1Towards the Construction of a Software Benchmarking Dataset Via Systematic Literature Review(IEEE, 2024) Yurum, Ozan Rasit; Unlu, Huseyin; Demirors, OnurEffort estimation is a fundamental task during the planning of software projects. Prediction models usually rely on two essential factors: software size and effort data. Measuring the size of the software can be done at various stages of the project with desired accuracy. Nevertheless, the industry faces challenges when it comes to collecting reliable actual effort data. Consequently, organizations encounter difficulties in establishing effort prediction models. Benchmarking datasets are available, but, in most cases, they have huge variances that make them less useful for effort prediction. In this study, we aimed to answer whether creating a software benchmarking dataset is possible by gathering the data from the literature. To the best of our knowledge, a comprehensive dataset that gathers the functional size and effort data of the studies from the literature is unavailable. For this purpose, we performed a systematic literature review to find studies that include projects measured with the COSMIC Functional Size Measurement (FSM) method and the related effort. As a result, we formed a dataset including 337 records from 18 studies that shared the corresponding size and effort data. Although we performed a limited search, we created a larger dataset than many datasets in the literature. In light of our review, we obtained that most studies did not share their dataset, and many lacked case details such as implementation environment and the scope of software development life cycle activities included in the effort data. We also compared the dataset with the ISBSG repository and found that our dataset has less variation in productivity. Our review showed the applicability of creating a software benchmarking dataset is possible by gathering the data from the literature. In conclusion, this study addresses gaps in the literature through a cost-free and easily extendable dataset.