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This study aims to conduct a systematic review of the existing literature on export promotion and foreign market entry strategies for small and medium enterprises (SMEs).

This study incorporates systematic literature review by using bibliometric technique and content analysis of 195 scholarly papers published between 2000 and 2024 obtained from Scopus database, using the PRISMA principles and a methodological framework.

The use of quantitative analysis has shown dynamic patterns in publication trends, characterized by notable increases in recent years. These trends align with the changing dynamics of the global economy and shifting priorities in international commerce. The study reveals thematic frameworks using author collaboration analysis, word cloud visualizations and a thematic map, providing insights into a significant motor, niche and developing issues that shape the discussion on the international growth of SMEs.

It offers significant insights that can benefit academics, policymakers and practitioners who are interested in understanding and navigating the intricate terrain of export promotion and market access strategies specifically tailored for small firms.

To the best of the authors’ knowledge, the study is the first of a kind that presents a systematic examination of the existing body of knowledge on the internationalization of SMEs.

This study aims to evaluate linear mixed data sampling (MIDAS), nonlinear artificial neural networks (ANNs) and a hybrid approach for exploiting high-frequency information to improve low-frequency gross domestic product (GDP) forecasting. Their capabilities are assessed through direct forecasting comparisons.

This study compares quarterly GDP forecasts from unrestricted MIDAS (UMIDAS), standalone ANN and ANN-enhanced MIDAS models using five monthly predictors. Rigorous empirical analysis of recent US data is supplemented by Monte Carlo simulations to validate findings.

The empirical results and simulations demonstrate that the hybrid ANN-MIDAS performs best for short-term predictions, whereas UMIDAS is more robust for long-term forecasts. The integration of ANNs into MIDAS provides modeling flexibility and accuracy gains for near-term forecasts.

The model comparisons are limited to five selected monthly indicators. Expanding the variables and alternative data processing techniques may reveal further insights. Longer analysis horizons could identify structural breaks in relationships.

The findings guide researchers and policymakers in leveraging mixed frequencies amidst data complexity. Appropriate modeling choices based on context and forecast horizon can maximize accuracy.

Enhanced GDP forecasting supports improved policy and business decisions, benefiting economic performance and societal welfare. More accurate predictions build stakeholder confidence and trust in statistics underlying critical choices.

This direct forecasting comparison offers unique large-scale simulation evidence on harnessing mixed frequencies with leading statistical and machine learning techniques. The results elucidate their complementarity for short-term versus long-term modeling.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

This paper explored the different strategies for international expansion that small and medium sized enterprises

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

This paper provides evidence that the banking sector reforms of 2004 and 2009 enhanced prudential performance of the banking industry and financial system stability in Nigeria.

This study uses regression analysis with regime shift to confirm results from tests of two means and variances model to examine the effectiveness of banking sector reforms in Nigeria.

Evidence from the regression model agrees with findings from the test of means model (not controlling for trend effects) that capital to assets ratio rose while non-performing loan ratio declined after the reforms, and that capital to earning assets ratio rose when trend effects were accounted for. Both the regression model and the tests of means model controlling for trend effects show that return on asset, return on equity and return on earning assets ratios declined after the reforms.

This paper evaluated the effectiveness of banking sector reforms in Nigeria using models that avoid weaknesses that besieged many previous studies. It however used data covering 1983–2020 period, due to data availability. A larger scope of data may improve the results, and future research may re-examine this theme as more data become available. Furthermore, banking stability issues could be examined using specialised techniques such as the generalised autoregressive conditional heteroscedasticity model and related family.

These results suggest that the reforms led to improvement in the sector’s resilience (risks-absorbing capacity) and asset quality, and that profitability had not been the primary focus of the reforms.

The authors recommend that regulatory and supervisory authorities in Nigeria continue to implement and improve on banking sector reforms for a more resilient and functional banking system. As a contribution to social research, this study shows that studies on policy evaluation should be located within appropriate theoretical framework: the theory of change. It shows that an appropriate use of attribution analysis and contribution analysis within this theoretical framework engenders robust analysis and results. Otherwise, the analytical findings would be erroneous and policy advice misguided.

The statistical significance of our findings establishes that the banking sector reforms in Nigeria have been effective in promoting financial system stability in Nigeria. By deploying both the test of means with and without trend effects (an attribution analysis) and the multivariate regression analysis with regulatory shift (a contribution analysis), and relying more on the later for its superiority, this study contributes to the body of knowledge in that, it not only determined the true effects of banking sector reforms in Nigeria for appropriate policy guidance but also demonstrated that, in research, an inappropriate methodology produces results that may diverge from the more accurate ones that were derived from the correct methodology.