Small and medium enterprises (SMEs) are vital to the economic development of emerging economies, significantly contributing to employment, innovation, and GDP growth. This study investigates the influence of market competition on SME performance in emerging economies, specifically examining the moderating role of process innovation. Using a sample of 365 SMEs in the western region of Ghana, the research employed a convenience sampling technique to gather data. The analysis utilized partial least square structural equation modeling (PLS-SEM) to explore the relationships between market competition, process innovation, and SME performance. The findings revealed that three direct hypotheses were supported, indicating a positive relationship between market competition and SME performance, while the moderated hypotheses were not supported. These insights provide valuable implications for SME owners, managers, and policymakers.

Behavioral risk management is an increasingly important consideration in investment strategies, as research has shown that investor psychology can significantly impact portfolio performance. This study examines how psychological variables influence investing choices and the effects that these actions have on risk mitigation and overall investment performance. The primary respondents for this study were the employees of Takoradi Technical University. Partial Least Square Structural Modeling was adopted for the data processing, analysis, and testing of the study’s hypotheses. The study’s findings, which were based on a carefully chosen sample of 348 investors, showed that investigating behavioral risk management in investment strategies is an effective method for thoroughly comprehending and utilizing investors’ psychology to maximize risk management procedures and enhance investment results in dynamic financial markets. Seven hypotheses were deemed insignificant, and five were considered significant. This study is limited by its exclusive focus on only one technical university. This study augmented the growing corpus of research on risk management in investment strategies.

This research examines how financial development, energy efficiency and energy inefficiency, green technology, and research and development (R&D) affect environmental conditions and ecological footprint in the Group of Seven (G7) countries. The study combines two theoretical models, including the Environmental Kuznets Curve (EKC) and the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT), within a unified framework. This study addresses a key gap in the literature by examining whether financial development follows a distinct nonlinear environmental pathway beyond the traditional income-based EKC framework. Using annual data from 1994 to 2023, the analysis applies the Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) approach to account for cross-sectional dependence and long-run heterogeneity among G7 economies. The findings indicate that the G7 does not support the traditional EKC hypothesis, although a U-shaped relationship between environmental degradation and financial development exists. Energy-related factors play a central role in shaping environmental outcomes, with energy efficiency and green technology significantly alleviating environmental pressure, and green technology proving to be the most influential among them. While energy inefficiency is associated with greater environmental stress, its effect remains statistically insignificant, suggesting that efficiency improvements are more decisive than reductions in inefficiency. Beyond energy dynamics, financial development and R&D investment also contribute significantly to environmental improvement, highlighting the complementary role of technological progress and financial systems in promoting environmental sustainability. The robustness results confirm the main findings. Overall, the study underscores the critical role of technological innovation and energy efficiency in promoting sustainability and challenges the applicability of the traditional EKC framework in advanced economies. The findings contribute to a deeper understanding of the multifaceted relationships between financial development, energy efficiency and inefficiency, green technology, and R&D, and their implications for sustainable development.

The aim of the article is to verify differences in the perception of selected factors of sustainability among small and medium-sized enterprises (SMEs) in Central Europe. The subjects of analysis are factors such as corporate social responsibility (CSR), business risk sources (market, financial, personnel, and operational), reputation and social media, national support, social changes, and crisis events in business. The questionnaire was completed by 1,090 SMEs from the business environments of Visegrad Group countries. Statistical hypotheses were verified using Z-scores for two population properties. The most negatively perceived factors among owners and managers in the SME segment are national support and legislative changes. The most positively perceived factor is reputation and social media. The country of doing business is a significant factor. The perception of crisis events in business is most negative among Czech SMEs. More than 80% of Hungarian SMEs perceive their companies as sustainable. In comparison with Slovak and Polish SMEs, Hungarian perceptions are more positive in the context of sustainability. The country of doing business is the strongest factor in evaluating CSR indicators. The positive perception of CSR in Czech SMEs (43.9%) is lower than in other countries.

This paper examines how companies in Slovakia and Poland perceive AI tool utilization and report changes in selected performance indicators after AI adoption (annual turnover, BIT, and employee error rates), and whether these assessments differ across firm demographics (country, company size, and length of operation). Using a CAWI survey of 865 firms and a contingency-table framework with Pearson’s chi-square tests and Cramer’s V effect sizes, we observe statistically significant—yet predominantly weak—associations between firm demographics and both AI utilization and self-reported performance changes. The findings provide actionable implications for managers and policy-support institutions seeking to accelerate AI adoption and value realization in central Europe, while acknowledging the limitations of cross-sectional self-reported data.