Abstract: The article examines modern approaches to optimizing production processes through benchmarking. The stages of implementing this method are presented, including data collection and analysis, benchmark selection, metric comparison, and recommendation development. Practical examples of successful benchmarking applications by leading global companies such as Tesla, Toyota, and Siemens are discussed. The benefits of this approach are highlighted, including increased productivity, cost reduction, and improved energy efficiency. The main challenges associated with adapting best practices are identified, and ways to overcome them are proposed. Based on the analysis, recommendations are provided for enterprises aiming for sustainable development and enhanced competitiveness.

Abstract: The article presents modern approaches to improving liquidity in managing a company's debt obligations. Key methods are discussed, including debt restructuring, cash flow management, the use of financial derivatives, and digitalization of processes. A classification of methods based on implementation timelines, complexity, and applicability is provided. Particular attention is given to the use of digital technologies, such as artificial intelligence and blockchain, to enhance forecasting accuracy and automate management. Factors influencing liquidity, including the macroeconomic environment and industry-specific characteristics, are analyzed. The conclusion emphasizes the importance of a comprehensive approach to liquidity management and the implementation of advanced analytical tools.

Abstract: The digital transformation of the global economy has fundamentally reshaped advertising strategies, particularly in the business-to-business (B2B) sector. This article explores the key digital tools used for analyzing the effectiveness of advertising campaigns, focusing on metrics such as Cost Per Lead (CPL), Conversion Rate, and Customer Lifetime Value (CLV). It highlights the integration of web analytics platforms, customer relationship management (CRM) systems, and artificial intelligence (AI)-powered solutions as essential components for optimizing campaign performance and enhancing return on investment (ROI). The study also discusses challenges like data fragmentation and accuracy issues, alongside opportunities presented by emerging technologies such as blockchain and predictive analytics. By adopting a data-driven approach and leveraging advanced tools, B2B companies can improve their competitive positioning and foster stronger client relationships.

Abstract: This article examines the economic impact of social benefits on labor market dynamics, focusing on labor force participation, unemployment rates, and wage adjustments. By analyzing data from multiple countries, the study highlights the diverse outcomes of social benefit programs, emphasizing the importance of their design and implementation. The findings reveal that well-structured benefits can enhance workforce engagement, reduce unemployment, and stabilize wages, while poorly targeted programs may create work disincentives or exacerbate existing labor market challenges. Policymakers are encouraged to adopt a holistic approach, integrating conditional incentives and addressing structural barriers to ensure equitable and effective labor markets. The study concludes with recommendations for aligning social benefit programs with broader labor market strategies to achieve sustainable economic outcomes.

Abstract: Revenue management in small businesses plays a critical role in ensuring financial stability and competitiveness. This article examines key revenue management models and approaches for cost optimization and risk minimization. It describes strategies that enable small businesses to manage their revenues effectively, including the implementation of innovative technologies and digital tools. The article analyzes both internal and external factors impacting revenue, such as economic instability, competition, and business owners' financial literacy. Special attention is given to the risks associated with revenue management and recommendations for minimizing them.

Abstract: The rapid advancement of artificial intelligence (AI) has significantly transformed warehouse operations management. This article examines the practical applications of AI in inventory forecasting, order picking, real-time tracking, and warehouse layout optimization. Key technologies such as predictive analytics, autonomous robots, computer vision, and IoT are discussed, with real-world examples from leading companies like Amazon, Walmart, and DHL. Emerging trends, including blockchain integration and energy optimization, are also explored. The article highlights the benefits of AI-driven solutions, such as increased efficiency, cost reduction, and enhanced decision-making. Despite challenges like high implementation costs and data privacy concerns, the future of AI in warehousing is promising, with potential for hybrid systems to revolutionize supply chain operations. This analysis provides insights into leveraging AI for sustainable and scalable logistics solutions.

Abstract: Effective risk management in construction projects is an essential task that helps reduce costs, improve quality, and meet deadlines. This article explores key methods of risk identification, assessment, and mitigation. Particular attention is given to the use of digital tools such as BIM technologies, IoT, and analytical software, which enhance process automation and forecasting accuracy. Practical examples and graphical analysis demonstrate the prioritization of managing critical risks. The conclusion emphasizes the need for further integration of artificial intelligence and machine learning to improve risk management efficiency and the competitiveness of construction companies.

Abstract: The article explores key sustainable development strategies for energy companies, focusing on the adoption of renewable energy sources (RES), technological innovations, and digitalization. Special attention is given to successful practices of global leaders like NextEra Energy and Iberdrola, which have achieved significant carbon emission reductions. The role of advanced technologies, including artificial intelligence, Internet of Things (IoT), and blockchain, in optimizing operations and improving energy efficiency is analyzed.
Challenges and opportunities in emerging markets are also discussed, where financial and infrastructural barriers hinder RES adoption. Proposed solutions include green bonds, public-private partnerships, and workforce development programs. In conclusion, the article highlights the necessity of collaborative efforts among governments, companies, and research institutions to drive sustainable and innovative development of the energy sector.

Abstract: The article examines the application of behavioral economics principles to forecasting consumer demand. It demonstrates that traditional economic models often fail to explain real consumer decisions, which are influenced by cognitive biases, emotional factors, and social influences. The paper analyzes theoretical approaches, such as the anchoring effect, bounded rationality, and social proof, as well as their practical use by companies like Amazon and Coca-Cola. Special attention is given to the role of digitalization in implementing behavioral economics. The use of machine learning and big data allows identifying consumer behavior patterns and adapting forecasting strategies in real time. Social networks and marketing personalization amplify the impact of behavioral factors on demand, providing companies with competitive advantages. Thus, the article highlights that behavioral economics, combined with modern digital tools, serves as an effective approach to improve demand forecasting accuracy and manage consumer behavior.

Abstract: The article explores the digitalization of project management in the IT sector through case studies and models. It demonstrates how digital tools such as Jira, Trello, and Asana optimize workflows, enhance team efficiency, and reduce project delivery timelines. Key project management methodologies – Agile, Kanban, and Waterfall – are analyzed, highlighting their benefits when integrated with digital platforms.
Special emphasis is placed on the comparative analysis of project timelines and productivity improvements achieved through flexible and iterative approaches. The challenges of digitalization, including resistance to change and the need for workforce upskilling, are also discussed. The study underscores the importance of a strategic approach to technology adoption to achieve sustainable results in IT project management.