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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.

This research aims to analyze the impact of efficient working capital management on the profitability of the manufacturing firm in Bangladesh. Fifty-two manufacturing companies listed with Dhaka Stock Exchange (DSE) have been selected randomly from 2012 to 2017. Return on Assets (ROA) and Return on Equity (ROE) are used as indicators of profitability, while the inventory conversion period (ICP), the average collection period (ACP), the average payment period (APP), and the Cash Conversion Cycle (CCC) are used as the independent variables which are used as a measurement of working capital management of the firm. Ordinary Least Squares regression models and Pearson's Correlation are used to establish the relationship between working capital management and profitability. The results revealed a significant negative relation between ROA and CCC, ACP; a significant negative relationship exists between ROE and CCC, APP. Manufacturing companies can increase profitability by decreasing the cash conversion cycle, average payment period, and average collection period. It also revealed that ICP is also positively related to ROA and ROE. Therefore, this research concludes that efficiently and effectively managing working capital is very important for increasing manufacturing companies' profitability.

This study aims to explore key drivers of tourism sustainability practices and their impact on the sustainable competitive performance of the tourism accommodation industry. The study adopts an exploratory research design under qualitative research, using semi-structured interviewing of owners and managers of tourism accommodation firms using the TOE framework and RBV theory. The findings reveal that technological sustainability expertise, executive sustainability support, organizational resources and capability, service intermediary sustainability practices, collaborative innovation adoption capability, tourism sustainability regulatory policy, and sustainability practices perceived by residents are the key drivers of TSP. The outcomes also show that tourism sustainability practices have a positive impact on the SCP of accommodation firms. This study makes a theoretical contribution to the literature on tourism sustainability by exploring how TOE antecedents motivate firms to adopt sustainability practices as product innovation, which in turn enhance SCP. Also, this study provides strong backing for the premises of the TOE framework, and RBV theory offers valuable practical insights for managers and owners. This will aid in identifying the pivotal factors influencing TSP and SCP, enabling the implementation of innovative strategies to enhance firm competitiveness. Also, the research can help the government and policymakers formulate sustainable tourism policies to promote tourism innovations. The adoption of sustainable practices has been a focal point for both academic researchers and professionals in the tourism industry. However, there has been insufficient exploration of the TOE drivers that facilitate the integration of tourism sustainability within the context of TAFs in a developing country. Therefore, this study aims to fill this gap in knowledge.

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.

The novelty and advancement of technology have explored new avenues in the education sectors. Now e-learning has blended with face-to-face learning to increase its effectiveness. An integrated model is being proposed in this study to measure the continuance usage intention of students adopting e-learning services. With the constructs of ECM (confirmation, perceived usefulness), perceived ease of use and perceived self-efficacy proposed to measure their effect on satisfaction. Besides, to explore the impact of quality features on satisfaction and continuance intention, three major determinants of D&M’s ISS model such as system quality, service quality and information quality included in this study. 410 responses collected to do quantitative analysis. The PLS-SEM analysis showed that perceived ease of use has the strongest effect on perceived usefulness, followed by perceived self-efficacy on perceived ease of use and satisfaction with continuance intention.The study reveals that challenges in developing countries are unique and drives the learners differently than developed countries. The growing e-learning industry requires widespread research from national and institutional perspectives for holistic development in the Bangladesh education market.

The growing prevalence of mental health issues, particularly depression and suicidal thoughts, points to the need to develop automated tools capable of detecting such sentiments from online communication. This study addresses some critical challenges by introducing a novel sentiment analysis framework for Bangla text, aimed at classifying content into non-depressive, depressive, and suicidal categories. We propose a hybrid deep learning model leveraging the strengths of transformer-based architectures, designed to manage long textual sequences effectively, a critical aspect in the context of natural language processing. Our model integrates RoBERTa (Robustly Optimised BERT Pre-Training Approach) with a Self-Attention Network (SAN), creating a synergistic framework for nuanced sentiment detection in Bangla social media posts, comments, and articles. This method addresses the scarcity of Bangla specific datasets by utilising a dataset curated for the study. The results demonstrate the superiority of our model, achieving an accuracy of 82.58%, alongside precision, recall, and F1-scores of 82%. Subsequently, it emphasises the potential for the proposed model to support early identification of mental health concerns, thereby enabling timely interventions and contributing to mental health awareness and prevention efforts. In the future, deploying the model as a real-time chatbot or browser extension could scan Bangla social media for depressive, non-depressive, and suicidal content and alert professionals to the risk factors.

Recent evidence indicates that citizens exhibit low involvement in financial activities within formal financial institutions. Therefore, this study explores how Digital Financial Literacy (DFL) influences savings in formal financial institutions. Using data from the Global Findex Database 2021 and the Standard & Poor’s Global FinLit Survey 2014, covering 135 countries, the study applies multiple regression analysis to assess how DFL predicts savings in formal financial institutions, while controlling for various country-level factors. The results show that among the three dimensions of digital financial literacy, financial skills and behaviors positively affect savings. In contrast, financial attitudes like trust in financial institutions and confidence in managing financial matters negatively affect savings behavior. Overall, financial literacy explains 78.8% of the variation in savings at the formal financial institutions across countries, with cross-validation supporting the robustness of the findings. This study contributes to existing literature by integrating several digital and segmented dimensions of financial literacy and enhancing external validity by including a broad range of countries for cross-country generalization in financial inclusion research.  

This study investigates the relationship between banks' corporate governance practice and its impact on financial sustainability. In this study, twenty-four private commercial banks' data have been analyzed from 2014 to 2023. Our investigations included a variety of econometric models, including cross-sectional GLS, fixed effect, random effect, and pooled OLS. In our study, we found that including women on the Board of directors plays a positive role in ensuring the financial sustainability of banking sectors in Bangladesh. Apart from that, increasing the participation of independent directors on the board of directors, expenditures in research and development in the best banking practices, and inflation positively increase banks' profitability, which translates into financial sustainability. This finding is consistent with the findings of the random effect model. On the other hand, whenever we used ROE as an explained variable, we found that both in pooled OLS  and random effect methods, board diversity, CEO tenure, firms audited by the big four firms, and inflation have a positive association with ROE. In the fixed effect method, we observed that audit committee size and ownership concentration play a vital role in explaining the financial sustainability of private commercial banks in Bangladesh. In the FGLS method, We found that CEO tenure, age of the firm, firms audited by the big four firms, presence of the independent director on the board, and inflations significantly impact the financial sustainability of commercial banks of Bangladesh.

There are growing concerns about ongoing digital innovation in the private sector, which poses the possibility of central banks losing their autonomy and even being backward in payment efficiency. Hence, CBDC has become the reality of central banks with several economies' ongoing digitalization and adaptation. This review explores the growing literature on CBDC design, its emergence, variations, potentials, and challenges for smooth future applications. It addressed research articles and gray literature to accumulate the current implementation concerns. Findings show that CBDC poses prospects for exploiting emerging technology, efficient payment systems, tax collections, and tracking illegal financial activities. However, there were mixed expectations regarding financial inclusion, financial stability, bank runs, disintermediation, monetary policy, privacy, security, technology, sustainability, and regulatory framework. Finally, as CBDCs will reduce the influence of private money creation and digital alternatives, they ensure that the central bank remains at the center of the financial system in the future. 

This paper examines the exchange rate pass-through (ERPT) and its impact on home inflation in Bangladesh, particularly in the post-pandemic era. Examining important economic factors including the nominal exchange rate (NER), money supply (M2), industrial production (IP), and global commodity index (GCI) using monthly data from January 2002 to August 2023 helps one to grasp their combined influence on consumer price inflation (CPI). By means of Johansen cointegration and Vector Error Correction Model (VECM) approaches, the study reveals important short-term and long-term dynamics. Contrary to patterns in many emerging nations, the results show that changes in exchange rates have apparently little impact on home prices. Rather, changes in the money supply and world commodities prices mostly influence inflation; the latter becomes a major factor. The study also exposes an unexpected positive link between industrial production and CPI, implying complexity in Bangladesh's production-driven economic structure. Moreover, this investigation underlines how complex monetary expansion, external commodities shocks, and devaluation of money interact to shape inflationary pressures. These results offer legislators important new perspectives and support strong monetary policies and focused involvement in world commodities markets to help to lower inflation. This study clarifies ERPT in developing countries and provides direction on inflation control techniques for Bangladesh.