Gaziantep University (Turkish: Gaziantep Üniversitesi) is a public university in Gaziantep, Turkey. Gaziantep University has 10 faculties, containing a total of 22 academic departments, with a strong emphasis on scientific and technological research.Gaziantep is the largest trade and industrial center in the west of Southeastern Turkey. Gaziantep University was founded as a state university on 27 June 1987, but higher education on campus began in 1973 when the institute was an extension campus of the Middle East Technical University. The main campus is located at Gaziantep, which is close to the city centre, with its extension campuses situated in the neighbouring cities.The objectives of the university are:The University of Gaziantep enrolled 24,406 undergraduates, 482 postgraduate students, and employed 1,048 faculty members in the 2008/09 school year. The language of instruction at the Gaziantep University is English.Gaziantep University ranks the thousandth in Times Higher Education World University Rankings from 2020-2021.
This study uses high-frequency price data to analyze risk connectivity among 15 cryptocurrencies, focusing on moments such as volatility, skewness, kurtosis, and jumps during the pre-COVID-19 era, the COVID-19 epidemic, and Russian-Ukrainian tensions. The results indicate that Ethereum Classic is a major shock transmitter in all periods, and this effect becomes more pronounced during geopolitical crises. In contrast, Stellar, Tezos, and Tron are important shock absorbers, particularly during market volatility. Jump risk analysis confirms the dominance of Ethereum Classic and its capacity to increase spillover risks during crises. For higher-order moments, the findings reveal that Bitcoin, Ethereum, and Dash are significant transmitters of skewness spreads, whereas Dash and Eos are significant transmitters of kurtosis spreads. Jump risk analysis confirms the dominance of Ethereum Classic and its capacity to increase spillover risks during crises. These findings highlight the need for targeted risk management strategies adjusted to cryptocurrency market dynamics.
The increasing recognition of mathematics teacher educators (MTEs) as a distinct field of inquiry has led to calls for systematic, data-driven analyses of thematic developments and research trends. Despite growing interest, no large-scale review has examined the evolution of MTE research. Addressing this gap, this study applies latent Dirichlet allocation (LDA) to identify 17 research themes in 579 Scopus-indexed publications and employs time series analysis (TSA) to track their progression. TSA findings reveal three key phases in MTE research: emergence, expansion, and divergence. While professional growth and pedagogical approach remain central, topics like STEM, task, technology, and social justice are gaining traction, whereas assessment, belief, and knowledge are in decline. By mapping these thematic shifts over time, this study provides a longitudinal perspective on MTE scholarship and highlights directions for future research.
This study examines extreme tail-risk spillovers among energy-intensive cryptocurrencies (Bitcoin, Bitcoin Cash, Ethereum, Ethereum Classic, Litecoin, Monero), three major green assets (S P Green Bond Index, S P Global Clean Energy Index, S P ESG Leader Index), and two key commodities (Gold, WTI Crude Oil) across quantiles and frequency horizons. Using a quantile–frequency connectedness framework, we evaluate spillover patterns during bullish, bearish, and stable market conditions, with emphasis on the COVID-19 pandemic and Russia–Ukraine conflict. Results show that cryptocurrencies—particularly Bitcoin and Ethereum—are dominant short-term net transmitters during periods of elevated volatility. Conversely, green assets and commodities, especially Gold, consistently act as net receivers, reflecting stability during market stress. Spillovers weaken and relationships normalize under tranquil conditions. While Gold and WTI absorb short-term shocks, they become balanced over longer horizons. Overall, cryptocurrencies exert short-run influence, whereas traditional and green assets demonstrate long-term resilience, offering important implications for portfolio diversification and risk management.
The increasing importance of sustainability goals necessitates that technology management processes be addressed with a holistic approach encompassing environmental, social, and institutional dimensions, rather than focusing solely on economic performance. While technology plays a key role in achieving sustainable development goals, effective management of this process requires long-term, strategic policies. Developing these policies entails integrating sustainability principles into technology management through multi-stakeholder participation. However, existing literature remains limited in providing structured decision models that integrate sustainability criteria into technology management decision mechanisms. This study presents an integrated decision-making framework for evaluating Sustainable Technology Management (STM) criteria. The study fills a distinct gap in the literature by addressing the Delphi-Analytic Hierarchy Process (AHP) integration within the context of STM criteria and systematically integrating the institutional dimension into the decision model in a measurable manner. In the first stage of the study, candidate criteria were identified through a comprehensive literature review; in the second stage, these criteria were finalized through a two-round Delphi process conducted with a panel of experts representing different stakeholder groups. In the final stage, the weights of the final criteria were calculated using the AHP method. The findings indicate that the institutional criteria hold a dominant priority compared to other criteria, with the support programs and incentives sub-criterion playing a particularly strategic role. The proposed model provides a systematic, applicable, and analytical decision-support framework for policymakers and decision-makers.
In recent years, transition to renewable energy has emerged as a vital strategy for achieving sustainable development and reducing environmental degradation. Only when backed by a solid institutional and macroeconomic context can economic growth serve as a stimulus for the development of renewable energy. In the same way, reducing income inequality increases the affordability, accessibility, and societal support needed for a just energy transition. Environmental protection expenditures play a complementary role by stimulating innovation, reducing regulatory uncertainty, and enhancing institutional capacity for long-run sustainability. Furthermore, indicating environmental stress, a decreasing load capacity factor emphasizes how urgent it is to accelerate the use of renewable energy. This study looks at how transition to renewable energy in OECD economies is affected by economic growth, income inequality, environmental protection expenditures, and load capacity factor between 2000 and 2021 using the common correlated effects mean group (CCEMG) estimator and its regularized extension (rCCE). The results indicate that while economic growth has a detrimental impact on green energy transition in Italy, Estonia, and Ireland, it has a favorable impact in Belgium. Income inequality has a detrimental impact on Belgium's and the Netherlands' green energy transition. The Czech Republic's green energy transition is positively impacted by environmental protection expenditures; however, Germany and Ireland are negatively impacted. In Spain and the United Kingdom, load capacity factor has a favorable impact on green energy transition. On the other hand, this element has a detrimental impact on Italy's shift to green energy. The study includes country-based policy recommendations within the findings.
