This paper investigates strategies to address climate change by promoting sustainable energy technologies and consumption practices. It examines renewable energy sources such as solar, wind, and geothermal and their potential to reduce greenhouse gas emissions. The study also explores energy optimization techniques, focusing on genetic algorithms (GAs) and smart energy systems like smart grids and microgrids, which enhance energy efficiency and sustainability. The research highlights the role of the circular economy in fostering sustainable consumption through recycling and waste management. Furthermore, the paper explores the economic trade-offs between energy consumption and environmental harm, focusing on the impact of both renewable and fossil fuel energies. A dual methodological approach is employed: first, an endogenous growth model excluding environmental factors, followed by a modified version incorporating environmental considerations. Using a continuous genetic algorithm and data from 2000 to 2025, the study forecasts the optimal trajectory for renewable energy’s share in global energy consumption under two scenarios. The findings suggest that by 2025, renewable energy could represent 82.4% of the total energy consumption under environmental constraints, up from the current share of 45%. This growth is hindered by challenges like droughts, which impact hydropower production. The study concludes that achieving a sustainable energy transition requires comprehensive policies integrating renewable energy expansion, energy efficiency, and environmental protection. These findings provide important insights into optimizing energy pathways for economic growth and environmental sustainability. They also serve as a foundation for future research and policy recommendations, aiming to ensure a low emission future by balancing the need for energy consumption with the preservation of the environment.

Environmental, social, and governance (ESG) factors are crucial in evaluating a company’s value. High ESG scores reflect ethical practices, social responsibility, and effective governance. This paper examines the impact of ESG criteria on firm value within the airline industry, focusing on their influence on operational efficiency, risk reduction, and financial performance. Using panel data analysis, the study evaluates ESG scores from 32 airline companies over the period of 2018–2023, with an explanatory power of 36.5%. The research explores how integrating environmental, social, and governance factors into strategic management can foster sustainable competitive advantage. It focuses on utilizing internal resources, meeting the needs of various interested parties, and balancing financial, social, and environmental performance. The findings indicate that while ESG practices enhance firm value through improved efficiency and risk management, they do not always lead to higher short-term firm value. Moreover, the study underscores the significance of governance in the airline industry, where robust governance structures can mitigate risks but may also increase costs. This research contributes to the literature by providing empirical evidence of the link between ESG performance and firm value in the airline industry, emphasizing the importance of integrating ESG principles into strategic management for long-term sustainability and financial success.

Today, having just leadership or entrepreneurship qualities by business managers is not enough for success of enterprises. Managers need to have both leadership and entrepreneurship qualities in order to be successful. At this point, the concept of entrepreneurial leadership emerges. Entrepreneurial leadership is a new and modern type of leadership that is a combination of leadership qualities and spirit of entrepreneurship. In addition, entrepreneurial leadership is creating new products, new processes and expansion opportunities in existing businesses, working in social institutions and dealing with ignored social issues, participating in social and political movements, contributing to the change of current services and policies implemented by civil society organizations and governments. In recent times, entrepreneurial leadership has become a new phenomenon in business management that needs to be discussed. In this regard, in this study, the importance of entrepreneurial leadership is emphasized by examining the concept of entrepreneurial leadership within a theoretical framework.

This study presents a novel approach to managing the cost–time–quality trade-off in modern agriculture by integrating fuzzy logic with a genetic algorithm. Agriculture faces significant challenges due to climate variability, economic constraints, and the increasing demand for sustainable practices. These challenges are compounded by uncertainties and risks inherent in agricultural processes, such as fluctuating yields, unpredictable costs, and inconsistent quality. The proposed model uses a fuzzy multi-objective optimization framework to address these uncertainties, incorporating expert opinions through the alpha-cut technique. By adjusting the level of uncertainty (represented by alpha values ranging from 0 to 1), the model can shift from pessimistic to optimistic scenarios, enabling strategic decision making. The genetic algorithm improves computational efficiency, making the model scalable for large agricultural projects. A case study was conducted to optimize resource allocation for rice cultivation in Asia, barley in Europe, wheat globally, and corn in the Americas, using data from 2003 to 2025. Key datasets, including the USDA Feed Grains Database and the Global Yield Gap Atlas, provided comprehensive insights into costs, yields, and quality across regions. The results demonstrate that the model effectively balances competing objectives while accounting for risks and opportunities. Under high uncertainty (α = 0\alpha = 0α = 0), the model focuses on risk mitigation, reflecting the impact of adverse climate conditions and market volatility. On the other hand, under more stable conditions and lower market volatility conditions (α = 1\alpha = 1α = 1), the solutions prioritize efficiency and sustainability. The genetic algorithm’s rapid convergence ensures that complex problems can be solved in minutes. This research highlights the potential of combining fuzzy logic and genetic algorithms to transform modern agriculture. By addressing uncertainties and optimizing key parameters, this approach paves the way for sustainable, resilient, and productive agricultural systems, contributing to global food security.

İşletmeler Yapay Zekâ (YZ) uygulamalarını kullanarak aynı anda birçok müşteriyle iletişime geçebilmektedir. YZ uygulamaları farklı birçok sektörde kullanılmaktadır. Günümüzde en yaygın kullanılan YZ uygulamalarından biride chatbotlardır. Chatbot ile müşterilerin isteklerine daha hızlı dönüş yapılarak esnek çözümler üretilebilmektedir. Chatbotlar banka müşterileri ile daha hızlı ve etkin bir iletişim kurulması açısından oldukça önemlidir. Chatbotlar mobil ve internet bankacılığında verimliliği artırmakta, bankacılık işlemlerinde maliyet tasarrufu sağlayarak süreçlerin daha hızlı gerçekleşmesini sağlamaktadır. Müşterilere daha hızlı dönüş yapılarak müşteri memnuniyeti artırılmaktadır. Bu amaçla çalışmada banka müşterilerinin YZ’ye yönelik tutumlarının YZ destekli hizmet veren chatbotlara ilişkin algıladıkları fayda düzeyleri ile YZ destekli chatbot uygulamalarını kullanmaya yönelik davranışsal niyetleri üzerindeki etkisi araştırılmaktadır. Türkiye’nin çeşitli illerinde ikamet eden 509 katılımcıdan anket yöntemi ile veri toplanmıştır. Elde edilen veriler ile geçerlilik ve güvenirlik testleri yapıldıktan sonra çalışmanın hipotezleri Yapısal Eşitlik Modellemesi ile test edilmiştir. Analiz sonucunda YZ’ye yönelik tutumun chatbottan algılanan faydayı pozitif yönde anlamlı olarak etkilediği; algılanan faydanın da davranışsal niyeti anlamlı olarak etkilediği belirlenmiştir. YZ’ye yönelik tutumun da davranışsal niyeti pozitif yönde anlamlı olarak etkilediği tespit edilmiştir. YZ’ye yönelik tutumun davranışsal niyet üzerindeki etkisinde algılanan faydanın yüksek aracılık rolü bulunduğu bulgusuna ulaşılmıştır.

This study offers a comprehensive analysis of the performance and systemic dynamics of green finance investments in environmentally sustainable technologies from 2000 to 2025, complemented by scenario-based projections extending to 2050. Empirical results indicate a consistent increase in portfolio returns—from 5.2% in 2000 to 11.8% in 2025—accompanied by a significant reduction in annualized volatility, declining from 8.1% to 3.0%. Concurrently, the portfolio’s sustainability score improved from 0.45 to a full alignment score of 1.00, reflecting a strategic shift towards high-impact green assets. Building on these observed trends, this study introduces the Eco-Financial Resonance Theory (EFRT), an original conceptual framework that interprets sustainable transitions as emergent phenomena arising from resonant interactions among four interdependent domains: financial flows, technological innovation, policy and regulation, and environmental outcomes. Scenario analyses highlight the pivotal roles of policy ambition and innovation pathways in shaping long-term risk-return profiles, with optimistic forecasts projecting returns exceeding 40% by 2050, alongside markedly reduced risks. Regional analysis reveals persistent disparities, underscoring the necessity for context-specific strategies to enhance systemic coherence. Beyond its theoretical contributions, EFRT offers actionable insights for investors and policymakers aiming to align profitability with ecological sustainability. Collectively, these findings position green finance not merely as a niche or ancillary activity but as a transformative mechanism for enabling scalable and resilient sustainability transitions amid accelerating global environmental challenges.