American Journal of Business and Operations Research

The growing complexity of financial decision-making in Small and Medium-Sized Enterprises (SMEs) necessitates advanced predictive models capable of accurately forecasting financial outcomes such as revenue, profit margins, and cash flow. Despite the availability of various machine learning models, there remains a need for optimization techniques that enhance model accuracy, generalization, and efficiency. This paper addresses this gap by applying metaheuristic optimization strategies to improve the performance of baseline financial forecasting models, particularly the Logarithmic Transformation (LogTrans) model. We propose the integration of several state-of-the-art metaheuristic algorithms, including Simulated Simulated Annealing (SSO), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WAO), and others, to optimize hyperparameters and perform feature selection. Our results demonstrate that the optimized SSO + LogTrans configuration outperforms all other models, achieving a remarkable Mean Squared Error (MSE) of 1.95E-07, a Root Mean Squared Error (RMSE) of 4.42E-04, and a high R-squared (R²) value of 0.966. These findings indicate that metaheuristic-driven optimization significantly improves predictive accuracy and generalization capability in SME financial decision-making models. The implications of this study extend beyond SMEs, offering potential applications in industries such as banking, investment, and insurance, where precise financial forecasting is critical. Furthermore, our approach highlights the importance of metaheuristics in the automated optimization of machine learning models, paving the way for further advancements in real-time decision support systems for dynamic financial environments.

Non-governmental non-profit organizations (NGOs) play a critical role in addressing social challenges and supporting sustainable socio-economic development. The effectiveness of their activities largely depends on the quality of project management systems. While developed countries have established advanced institutional and managerial frameworks for NGO project implementation, many developing countries, including Uzbekistan, continue to face limitations related to funding, professional capacity, and monitoring mechanisms. The aim of this study was to assess international best practices in NGO project management and identify applicable directions for improving project effectiveness in Uzbekistan. A comparative analytical approach was applied using secondary data from the United States, Canada, Germany, Norway, Sweden, and Uzbekistan. The analysis focused on public funding volumes, adoption of international project management standards, monitoring and evaluation effectiveness, and the share of certified project managers. The results demonstrate a significant performance gap between Uzbekistan and developed economies. The study concludes that systematic integration of international standards, strengthened monitoring systems, and professional certification are essential for improving NGO project effectiveness.

Retail payment providers must decide whether to invest in consumer activation, merchant acceptance, or both. This study compares those signals using published country tables from the European Central Bank’s 2024 Study on the Payment Attitudes of Consumers in the Euro Area. Across 20 countries, the share of point-of-sale transactions paid without cash correlates with the share of respondents preferring noncash methods (r = 0.65) and with the share of transactions where noncash payment was available (r = 0.70). Leave-one-country-out prediction error falls from 11.67 percentage points for a country-mean benchmark to 9.54 with preference alone, 8.91 with acceptance alone, and 8.89 with both. Adding account ownership yields 8.58, a modest further gain. Latvia, Portugal, and Slovakia combine above-median noncash preference with above-median reports of cashless payment refusal. Germany illustrates the limits of a simple market screen: its observed noncash use exceeds the model’s held-out estimate by 26.03 points. The results support using demand and acceptance as complementary market diagnostics, followed by local transaction research before investment. The analysis describes associations among national aggregates and does not identify a causal effect of merchant acceptance.

This study analyzes the system of factors affecting production efficiency in the context of increasing production efficiency under conditions of innovative economic development. The research emphasizes rational resource use as a key driver of sustainable industrial growth and competitiveness. Based on a system approach, efficiency factors are classified into macro- and micro-levels, as well as internal and external environments, with a particular focus on controllable micro factors. Using the input–output framework and a case-oriented analysis of porcelain production, the paper identifies labor, capital, raw materials, energy, technology, and inventory management as the most influential internal factors. The findings show that coordinated management of these factors, supported by feedback mechanisms and strategic resource management, can significantly improve productivity, reduce costs, and enhance product quality.

This article examines the role of renewable energy (RES) as a key driver of the ESG transformation of Uzbekistan's energy sector and industrial clusters. Based on data from international organizations and specialized analytical reviews, the electricity sector's high dependence on natural gas (approximately 76% of generation in 2023) heightens energy security and sustainability risks amid declining gas production and rising electricity demand. An integrated framework for ESG energy transition management (ESG KPIs + scenario-based effects model) is proposed as a methodological solution, focusing on industrial cluster chains (textiles, construction materials, chemicals/metallurgy, and agro-industrial processing). An assessment of the economic effects of replacing gas-fired power generation with RES is conducted under a scenario in which target benchmarks are achieved by 2030 (scaling RES to 21–27 GW and increasing the share of RES in the electricity supply). The results show that the introduction of renewable energy sources in combination with energy efficiency at the cluster level can provide a sustainable economic effect through the release of gas (alternative cost of fuel), a reduction in electricity costs and losses, an increase in investment attractiveness, and access to “green” financing in the logic of the national green taxonomy.

International recruitment exposes universities and host regions to concentrated cross-border demand, yet published dashboards rarely disclose the joint distribution of source countries and institutions. This study turns the November 2024 Open Doors state fact sheets into a reproducible market-risk screen for 50 U.S. states and the District of Columbia. These markets contain 1,126,079 international students and $43.817 billion in estimated regional expenditure in 2023/24. The median state’s largest source market accounts for 28.5% of students; its largest receiving institution accounts for 32.2%. Sharp bounds calculated from the separately published margins show that, in 48 of 51 markets, a positive share must both come from one of the five leading origins and attend one of the leading institutions. The median guaranteed overlap is 32.0% of a state’s international students; Arizona’s is 68.4%. An illustrative 10% decline in each state’s largest origin implies $1.511 billion in expenditure exposure across the 51 markets under a constant-spending assumption, led by California ($233.1 million) and New York ($229.9 million). The bounds identify segments requiring institutional cross-tabs; the scenario is neither a forecast nor a measure of university revenue. The analysis supplies an auditable way to prioritize recruitment diversification and market-level due diligence with public business data.

One of the key areas of the green economy in Uzbekistan's agriculture is the development of organic farming. The purpose of the article is to develop organic agriculture based on the use of natural methods of crop cultivation, the rejection of chemical fertilizers and pesticides, and the use of biological plant protection products. At the same time, in connection with the “green” economy, which is one of the most pressing tasks not only in our country, but also in the world economy, work is underway to develop the green economy in our country and in the world, as well as to analyze international cooperation.