This study examines the association between Corporate Digital Transformation (CDT) and information asymmetry (ASY) among firms listed on the Stock Exchange of Thailand during 2017–2022. Drawing on agency theory, institutional theory, and resource dependence theory, the study conceptualizes CDT as a portfolio of organization-wide digital initiatives and transformation projects embedded in firms' governance and information infrastructures rather than as isolated technological adoption. CDT is measured using textual analysis of firms' annual reports based on a multidimensional keyword dictionary capturing disclosed digital transformation activities, while information asymmetry is proxied by the effective bid–ask spread. Using firm-level panel data and fixed effects regression models, the analysis documents a negative and marginally significant association between CDT and information asymmetry, suggesting lower information frictions among firms with higher levels of reported digital transformation activity. A series of robustness tests employing alternative measures, estimation strategies, and subsample analyses yield qualitatively consistent results. The study contributes to the project management literature by providing empirical evidence on how sustained digital transformation initiatives, implemented through multiple projects over time, are associated with changes in organizational information environments in an emerging market context. While the findings should be interpreted as indicative rather than causal, they highlight the relevance of managing digital transformation as an integrated project portfolio with implications for transparency and stakeholder communication.

Firms operating in emerging markets deal with volatile and uncertain conditions that force them to continuously adapt and reconfigure their resources. We use the Dynamic Capabilities View as our theoretical lens to investigate how dynamic capabilities work together with digital readiness to affect performance in SMEs that face these turbulent environments. Dynamic capabilities give managers the means to sense changes in their environment, seize new opportunities when they arise, and realign organizational resources as needed. Digital readiness provides the technological infrastructure required to make these strategic and project-level adjustments work in practice. We gathered survey data from 305 food-processing SMEs in Jordan and analyzed the data using Partial Least Squares Structural Equation Modelling. Our results show that dynamic capabilities have a strong positive effect on firm performance. We also found that digital readiness amplifies this effect in important ways. The study contributes to strategic management, operations management, and project management research. It demonstrates that building capabilities while aligning digital tools helps firms navigate environmental uncertainty more effectively. For managers, the findings highlight something important: developing both organizational agility and digital infrastructure can turn turbulent market conditions into competitive advantages. The results offer practical guidance for operations and project managers in SMEs who are working to execute sustainability-oriented operational projects. They show that capability development paired with digital preparedness supports smoother execution and leads to stronger project outcomes.

This study investigates the impact of cash holdings and capital structure on firm valuation in Egypt's emerging market, examining how COVID-19 altered investor perceptions. The research employs explainable machine learning (ML) to uncover non-linear financial thresholds that traditional valuation models overlook. Egyptian listed firms from 2015 to 2022 are analyzed using a Super Learner ensemble (Extremely Randomized Trees, Extreme Gradient Boosting, and a Linear Regression meta-learner) alongside SHapley Additive exPlanations (SHAP) and partial dependence analysis, with the Super Learner's performance compared against conventional methods in assessing financial policy effects on Tobin's Q. Three key findings emerge: (1) Leverage exhibits a non-linear relationship with valuation, where extreme levels (LEV > 1.2) unexpectedly enhance firm value, challenging trade-off theory; (2) Cash holdings demonstrate threshold effects, with optimal value at ~40% of assets and sharply increasing marginal benefits beyond this point; and (3) COVID-19 amplified these dynamics, elevating the liquidity premium while penalizing excessive debt. The Super Learner significantly outperformed traditional statistical and ML models (R² = 0.572 vs. 0.19-0.47). Practical implications suggest that investors and managers in emerging markets should adopt dynamic cash-debt optimization to avoid undervaluation, while policymakers can use ML-driven thresholds to design crisis-responsive regulations. This study contributes to the literature by (1) identifying non-linear thresholds that extend trade-off and pecking order theories, (2) introducing explainable ML to valuation research to balance accuracy and interpretability, and (3) providing novel evidence of COVID-19's structural impact on investor behavior in emerging economies.

This research aims to examine bank specific, market and regulatory determinants of leverage and capital structure based on a panel data of publicly listed Islamic banks in 12 countries over the peri-od 2008-2017. Apart from testing standard corporate finance parameters using both OLS and M-Estimators, this study adds several idiosyncratic and regulatory environment related determinants of leverage unique to Islamic banks. The significance of potential determinants is tested for market and book leverage as well as newly introduced ‘Islamic banking leverage’. Overall, the results show that Islamic banks with higher growth opportunities, tangibility, low profitability and low risk are likely to have a high leverage. Similarly, the findings suggest important role played by debt market conditions, share of investment accounts and regulatory environment in such decisions, providing an evidence of the significance of trade-off and pecking order theory in capital structure in Islamic banks. The results are more robust for market and Islamic banking leverage, rather than book leverage. The findings offer insights to regulators, standard setters and especially Islamic banks regarding parameters to strengthen their capital, enhance resilience and thus contribute to the stability of relevant financial. This paper is among the few extant studies that focus on listed Islamic banks and tests de-terminants based on stock market data.

This study investigates the effect of dividend payout on firms’ future earnings growth (FEG) in Malaysia. We use panel data analysis methodology to determine the effect of dividend payout and other control variables on FEG in 1, 2, 3, 4, and 5 years. Our results show that firm size and payout ratio had significant positive relationship on four out of five dynamic models tested. The remaining factors except of debt ratio are significant at least four out of the five years used in dynamic models in this study. We find evidence that Malaysian firms show mean reversion pattern in their earnings; smaller firms would enjoy greater future earnings growth; increased monitoring from creditors leads to better earnings performance; firms with better investment prospect have greater future growth in earnings; and higher investment in assets leads to higher future earnings growth. The findings show that in Malaysia, managers use dividend as a tool to signal their positive private information about the firms’ future prospect.

The growing field of behavioral economics (BE) has revolutionized the way we look at economic behavior at micro and macro levels. Importance of foreign direct investment (FDI) appeals for analysis of decisions made regarding it to be assessed from expanding view of BE. This research provides overview of previous studies and focuses on the case of Bosnia and Herzegovina (B&H) as representative of emerging markets to investigate motivations for investing into this country by temporarily present foreign companies. Empirical analysis was based on the questionnaire that was disseminated among foreign investors to B&H. Questionnaire contained motivations for investing in B&H, where examined motivation factors were divided in two groups; namely irrational and rational ones. Choice of methodology was narrowed due to moderate sample size, but consisting of quality the sample members. In order to analyze data, descriptive statistics, correlation analysis and regression analysis were used. By regressing two groups of predictors on annual amount of foreign investments to B&H, it was shown that the highest motivation for investing was business instinct.