Explore publications.

University students commonly undergo activities in their educational and social environments that may affect their psychological adjustment. Emotional Intelligence (EI) acts as a protective component in preventing psychological adjustment difficulties. Hopelessness acts as a risk factor in the dimension of psychological adjustment. Little research exists in the context of Bangladesh in the intersection of EI and hopelessness. The present research aimed to explore the effects of EI and hopelessness in predicting psychological adjustment of the students at Chittagong University. A cross-sectional survey design was adopted. A total of 100 students aged 18-25 years old, comprising 50 men and 50 women selected randomly from different departments/institutes of Chittagong University. Data was gathered utilizing a Personal Information Form (PIF), Bangla version of the EI Scale (EIS), Hopelessness Scale (BHS), & Bangla Adult Personality Assessment Questionnaire (PAQ). SPSS 16.0 was used to perform the analysis of the information gathered. The inferential statistics revealed moderate to high levels of EI (M = 129.07, SD = 12.84) but low levels of hopelessness (M = 4.55, SD = 3.51) and moderate levels of psychological adjustment (M = 137.28, SD = 25.00). There was a negative correlation between EI measures of hopelessness (r = -.54, p < 0.01) and psychological adjustment (r = -.67, p < 0.01) but a positive association between hopelessness and psychological adjustment (r = 0.50, p < 0.01). Using the regression analysis, psychological adjustment was significantly predicted by the measures of EI (β = -.56, p < 0.01) but hopelessness (β = 0.19, p < 0.05) when taken together explaining 47% of the total variability of psychological adjustment (R² = 0.47, p < 0 EI serves as a protective factor for psychological adjustment in university students, while hopelessness serves as a risk factor for the psychological adjustment of university students. These factors may influence the enhancement of psychological adjustment.

This paper explores the relationship between environmental, social, and governance performance (ESGP) and firm value in both emerging and developed economies, with the moderating impact of environmental uncertainty and competitive advantage. Using secondary unbalanced data spanning from 2011 to 2022, we examine both the direct and non-linear effects of ESG performance on firm value, employing advanced econometric estimation techniques such as two-step system GMM (2sGMM) and two-stage least square (2SLS). The analysis finds that: (1) ESG performance positively influences firm value in both Chinese and US banks, and the results remain valid after robustness test; (2) The results also confirm that ESG performance non-linearly influence firm value across the samples, with an inverted U-shape relationship; (3) Additionally, we further investigate the moderating effects of environmental uncertainty and competitive advantage, uncovering that environmental uncertainty dampens the ESGP-firm value relationship, while competitive advantage further amplifies it. This study contributes to the understanding of how ESG performance can act as strategic assets that align managerial and stakeholder interests, and improve firm performance, by underpinning agency, stakeholder, and the resource-based view theory. Practical insights are also provided for policymakers, regulators, and financial institutions regarding the use of ESGP as a competitive tool in uncertain and dynamic market environments.

The financial performance of banks relies heavily on properly utilizing their capital. However, bank ownership can have varying effects on the relationship between financial performance and capital. This study delves into this relationship by examining the impact of ownership on financial performance and bank capital. The study analyzes data from 44 commercial banks in Bangladesh and uses a two-step system generalized method of moments to address heteroscedasticity and autocorrelation issues. Unlike previous studies, this study confirms the significant effect of ownership on the relationship between bank financial performance and bank capital. The study's main findings are: (1) an inverted U-shaped relationship exists between bank capital and financial performance, implying that increasing capital can improve and reduce financial performance. (2) Private and Islamic commercial banks perform better than state-owned and conventional banks. (3) private-owned and Islamic commercial banks with higher capital are more likely to achieve higher profitability and financial success, while state-owned and conventional commercial banks with higher capital show lower profitability and weaker financial performance. Overall, this study offers significant practical implications for academics, researchers, and regulators interested in leveraging these findings.

This paper attempts to reveal how several credit risk factors are affecting the profitability of commercial banks considering the econometric models estimated with Random effect, Fixed effect, Pooled OLS and Cross-sectional Generalized least square (GLS) method followed by dynamic panel data model estimated with one-step GMM (generalized methods of moments) approach to incorporate the issue of endogeneity, unobserved heterogeneity and profit persistence of data set collected from annual report of banks covering from year 2010 to 2019 in Bangladesh. We have also adopted several diagnostic checks such as Model specification test, test of heteroskedasticty, cross sectional dependence test followed by test of autocorrelation and unit root test to examine the validity of the models selected for this study. The first part of our empirical investigation of the estimated models considering all methods reveals that out of all the independent credit risk factors such as Total loans to total assets ratio, Total loans to equity ratio, NPL to total loans, NPL to Total equity ratio, Provision for loan losses to total equity, total equity to total assets ratio, Total loans to total deposits ratio and provision for loan losses to NPL ratio, only provision for loan losses to NPL ratio is significantly affecting the dependent variable measured with NIM (Net interest margin) ratio of banks under fixed effect method. The next part of our empirical results of estimated models considering same methods divulges that NPL to total loans ratio, NPL to Total equity ratio and Provision for loan losses to total equity are also significantly affecting the dependent variable measured with ROE (Return on equity) of banks. The third segment of our empirical findings of estimated models considering same approaches shows that only NPL to total loans ratio is statistically significant under all methods but the NPL to total equity ratio is significant under fixed effect and GLS method and Provision for loan losses to total equity is significant under GLS method only in explaining the changes in ROA (Return on equity) measuring profitability of banks. Further investigation reveals that the dynamic impact of the said credit risk factors on profitability measured with ROE of banks has been successfully adopted by one-step system GMM approach considering all conditions required for estimation.