This study examines the moderating effect of firm size on the relationship between innovation and firm performance of small and medium enterprises in 29 countries in Eastern European and Central Asia. The study also investigates whether the impact of innovation in products and processes on firm performance is affected by financial capital. The method applied is partial least square structural equation modelling. The findings indicate that firm size and the financial capital both moderate and mediate the impact of innovation on firm performance, positively or negatively. The findings have implications for decision makers by highlighting the significance of firm size and financial sources when planning to introduce innovations to enhance firm performance.

In the digital era, the advent of new asset classes like cryptocurrencies and the application of advanced analytical tools have significantly reshaped portfolio management. This study employs Data Envelopment Analysis (DEA) to assess the efficiency of range-rebalanced investment portfolios incorporating diverse assets such as cryptocurrencies, major currencies, technology securities, and commodities. The analysis spans from October 1, 2016, to June 30, 2022, evaluating various rebalancing strategies including Allowed Range, Threshold, Drifting Mix, and Tactical approaches during different market conditions, including pre-COVID-19, during COVID-19, and post-COVID-19 periods. The findings highlight the superiority of strategic rebalancing, particularly combining high-value cryptocurrencies with technology securities, in enhancing portfolio performance and risk management. This research provides valuable insights for optimizing asset allocation in the dynamic financial landscape, underscoring the importance of strategic rebalancing in maximizing returns while managing risk.

This study examines the perceptions of competence-oriented educational practices in the digital age among business school students from European and Asian cultures. The statement emphasizes the need for essential competencies and maintaining a balance between study and personal life. The study sampled 800 undergraduate students, equally in Thailand and Bulgaria, to assess the impact of key competencies, digital literacy, and the integration of digital technologies on students’ educational choices. The findings revealed significant differences in how students from these two regions perceive the importance of these factors. Thai students tend to emphasize a balanced set of competencies but are less inclined to value digital skills as highly as their Bulgarian counterparts. In contrast, Bulgarian students place a greater emphasis on digital competencies, reflecting the European education system’s broader integration of digital literacy into its curricula. The evidence suggests that a global trend towards the recognition of digital technologies is crucial for achieving a study–life balance with minimal differences between the regions in this regard. This convergence suggests an emerging global consensus on the role of digital education in promoting lifelong learning. The authors recommend incorporating region-specific teaching philosophies to improve student engagement and promote a healthy study–life balance.

Purpose: This study investigates how financial and entrepreneurial capability configurations differentiate internationalized from domestically oriented Thai SMEs. By adopting a decision-science perspective, the study identifies the capability patterns that shape firms’ strategic international orientation. Design/methodology/approach: This research, which utilizes survey and financial data from 179 Thai SMEs (2021–2023), employs an inductive machine learning approach based on Extreme Gradient Boosting (XGBoost). The analytical framework integrates profitability, liquidity, leverage, operational efficiency, international experience, team readiness, market knowledge, and institutional connectivity. Feature importance scores and confirmatory statistical tests are used to validate differentiating capability structures. Findings: Internationalized SMEs are characterized by stronger financial agility, higher profitability, disciplined leverage, and more efficient resource utilization, together with entrepreneurial preparedness reflected in international experience, risk tolerance, team coordination, and institutional embeddedness. Localized SMEs, by contrast, display liquidity-heavy but lower-dynamism profiles, weaker network engagement, and more limited organizational readiness. Practical implications: The findings suggest that SME support should move beyond finance-only assistance and address capability alignment. Programs that strengthen financial agility, team readiness, international market knowledge, digital channels, and institutional networks may improve SME readiness for international engagement. Originality/value: The study contributes to international business theory by reframing SME internationalization as a selective and configurational process rather than a linear or binary outcome. It extends the resource-based view by emphasizing capability bundles rather than isolated resources and contributes to the dynamic capabilities perspective by showing how financial, entrepreneurial, and institutional capabilities are associated with SMEs’ differentiated participation in international markets.

Financial markets are connected, and several articles illustrate a network of financial markets. This study shows the connectedness of the economic sector in emerging markets, Indonesia, Malaysia, and Thailand, by the Granger causality graph. Moreover, the CNN-LSTM, a hybrid machine learning approach, was applied to make a prediction based on the connectedness of economic sectors. As a result, CNN-LSTM improves prediction accuracy in most sectors of each country, showing the interdependence among assets in the same market. On the other hand, the network's isolated sector cannot gain more precise predictions in the Thailand stock market. However, the isolated sector gained a better prediction score in Malaysia, emphasizing that machine learning can extract non-linear relationships compared to traditional statistics. On the other hand, the noisy path of the interconnected structure deteriorates forecasting performance as connected sectors in the Malaysian market cannot improve the accuracy of the prediction. As most sectors gain a better prediction score, incorporating the interaction among asset returns, especially economic activities connection, should be used for testing the asset pricing model.