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The research investigates how goal contagion impacts the acceptance of digital technologies and also explores the moderating effect of COVID-19 and survival instinct within the interconnection between goal contagion and the acceptance of digital technologies. The research has undertaken partial least squares structural equation modeling to identify the direct as well as moderating effects based on a sample of 250 individuals across diverse firms in Bangladesh. The research also involved the Importance-Performance Map Analysis approach (IPMA) to explore key areas of importance and performance, thus providing a holistic understanding of key factors impacting the acceptance of digital technologies. Then, an ANN model analysis was used to determine how important the components determined by the PLS-SEM study were in terms of relative influence. The study revealed that others’ behavior and situational context have a significant impact on goal contagion. The outcome also showed that goal contagion has a significant impact on the acceptance of digital technologies; besides, survival instinct and COVID-19 have a statistically significant moderating effect between goal contagion and the acceptance of digital technologies. The IPMA findings showed that COVID-19 and goal contagion are the most important factors for the acceptance of digital technologies. The ANN findings revealed that situational context is the most contributing construct for goal contagion. The findings also demonstrated that COVID-19 and goal contagion are the most influential constructs for the acceptance of digital technologies. The findings of this research contribute significantly to the relevant knowledge by promoting a theoretical framework for comprehending the factors that influence the acceptance of digital technologies. Furthermore, this research illustrates valuable insights for companies that are planning to make strategic decisions regarding their digital technologies.

Employee promotion in State-Owned Commercial Bank (SOCB) and Private Commercial Bank (PCB) depends on Key Determining Factors (KDF). The study aims to identify these factors. The objective is to compare the impact of KDF on employee promotion between SOCB and PCB. The study finds that Education, Qualifications, Job performance and Skills do not impact promotion in SOCB, whereas Experiences, Tenures, Work ethics and Dependability determine employee promotion in PCB. Social relationships and interpersonal relationships both influence employee promotion at PCB. Bias and Favouritism exist from a certain level in SOCB, whereas the study unveils a strong presence of Bias and Favouritism in PCB. There is no presence of Age, Gender and Ethnicity in employee promotion in SOCB, while PCB experienced a mixed influence of Age, Gender and Ethnicity on employee promotion. While there is no influence of Union Status, Firm Size on employee promotion in PCB, an indirect influence on employee promotion has been observed in this study. Luck and External factors both influence employee promotion in SOCB and PCB. Seniority is maintained up to a certain level in SOCB, after that, both merit and seniority is considered whereas performance plays a pivotal role in employee promotion in PCB.

Our way of life has evolved due to the advent of AI. Artificial intelligence (AI) is already having an impact on many parts of the industry and will likely find additional uses in the future. This research study investigates the students' readiness to adopt AI. An exploratory research design undergirds this investigation. A questionnaire (based on a prior study) survey was used to gather data. The SPSS and AMOS Graphics are used to conduct EFA and CFA. 387 respondents were taken into consideration for the study. In this investigation, the KMO value is 0.839. Factor loading is larger than 0.45, with 22 items. This study extracts five components: educational content (EC), institutional facilities (IF), artificial intelligence awareness (AW), acceptance barriers (AB), and usage/application (AP). The Eigen values of those components are 5.056, 2.420, 1.640, 1.411, and 1.000, explaining 52.4% of the total variation. The CFA model fit findings show that CMIN/DF=2.360, GFI= 0.0.913, AGFI= 0.884, CFI= 0.880, RMSEA=0.05, SRMR=0.05, Hoelter's N returns value at 5% significant level = 195 and at 1% significant level = 210, Chi square= 372.870, df=158, p=0.000. Today, AI may boost tertiary students' productivity. Engaging pupils with technology in our country helps determine their AI interests. The study shows how educational content, institutional facilities, artificial intelligence knowledge, acceptance hurdles, and usage/application affect students' preparedness to adopt AI. This research will help higher education authorities to introduce IT infrastructure, teach students to understand AI technology, and inspire future academics to contribute to this era of intelligent robots.

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 aims to explore the effect of foreign direct investment on the educational attainment.  This paper employed the POLS and 2SLS models. In Pooled Ordinary Least Square Model, educational attainment in primary, lower secondary, upper secondary and masters’ level have the significant positive relationship with foreign direct investment. In Two stage Least Square Model, educational attainment in primary, lower secondary, upper secondary, tertiary and masters’ level have the significant positive relationship with foreign direct investment. This study contributes to look at the impact foreign direct investment on educational attainment. Panel data from 38 Asian countries was gathered for this study, which spanned the years 2011 to 2022. The study results have important policy implications as they are directly linked to the United Nations’ Sustainable Development Goals (SDGs) Target 4.1, which aims to guarantee that all girls and boys get free, equitable, and high-quality primary and secondary education by 2030, resulting in relevant and effective learning outcomes.

This study investigates the relationship between corporate governance and firm performance in the Bangladeshi insurance sector, focusing on variables like board independence, female directors, audit committee size, leverage, and firm age. Using a sample of 42 insurance firms from 2017 to 2021, regression analysis is employed to assess these relationships. The findings show that board independence positively impacts performance, while audit committee size, leverage, and firm age have negative effects. Female directors exhibit a marginal but weak positive influence. This research contributes to the literature by providing empirical evidence from a developing economy, where limited studies exist. It also offers insights into governance practices in emerging markets. The implications suggest that policymakers and corporate leaders in Bangladesh should prioritize enhancing board independence, managing leverage, and promoting gender diversity to improve performance. Future research could explore causal relationships and extend the analysis to other sectors or emerging markets, considering cultural and regulatory factors.

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.

Environmental, Social, and Governance (ESG) -related information has become a primary non-financial consideration for investors. Carbon Auditing has emerged as a significant accounting framework for providing ESG information. As climate change intensifies, the demand for transparent and accurate carbon auditing has risen. This Study aims to understand how emerging carbon auditing could proactively prevent future scandals, e.g., Volkswagen's Diesel gate Scandal, and mitigate environmental risks. This paper examines the level at which carbon auditing effectively curbs emissions, considering Volkswagen's "Dieselgate" scandal as a case study. It assesses how well carbon auditing works in controlling environmental risks and discusses how enhancements in carbon accounting in the future can help avoid such scandals. The Study was conducted through case study analysis and scenario analysis. The Study found that the Diselgate Scandal reduced share prices, raised awareness through Academia, and produced some policy implications. Scenario 1 analysis shows that a lack of carbon auditing triggers environmental degradation, leading to financial losses. On the other hand, in scenario 2, the Study shows that continuous monitoring leads to long-term financial stability.

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.

This study examines the relationship between audit quality and tax avoidance practices among listed banking companies in Bangladesh. The investigation utilized secondary data from the published annual reports of 36 listed banks on the Dhaka Stock Exchange, covering the period from 2018 to 2022. Therefore, the final dataset consists of 170 firm-year observations. In this research, audit quality was measured using four different variables: audit fees, audit tenure, the presence of a Big4 audit firm, and the disclosure of Key Audit Matters (KAM). The findings indicate that both the audit fees and KAM disclosure have a statistically significant positive relationship with tax avoidance. Conversely, while the presence of a Big4 auditor and audit tenure also demonstrate a positive relationship with tax avoidance, but this relation is not statistically significant. These findings suggest that rigorous auditing practices are essential for maintaining tax compliance within financial systems. Conducting audits with integrity, thoroughness, and adherence to professional standards can significantly impact tax compliance. Furthermore, the results highlight the need for tax authorities to identify and close the tax loopholes that companies exploit for tax avoidance. Promoting collaboration between regulatory bodies, tax authorities, and auditing firms is necessary to reduce tax avoidance activities by the firms. 

Financial inclusion aims to include the unbanked population in the official financial system. To quickly serve the unbanked population, this study aims to investigate the concept of agent banking as a means of financial inclusion and to assess the elements that influence the acceptance of agent banking in Bangladesh. The study also covered the main advantages of agent banking and pertinent barriers to its adoption. Using a basic judgmental sampling technique, 195 respondents from the Chittagong region made up the study's sample. Face-to-face interviews and a structured questionnaire were used to collect the data. The impact was investigated using statistical measures such as mean, standard deviation, correlation, and regression. Kendall's W test, also known as Kendall's coefficient of concordance, was utilized to evaluate the benefits and drawbacks of accepting agent banking in this study. According to the result, there is a significant positive correlation between acceptance of agent banking and independent variables - perceived trust, convenience, perceived risk, awareness, and service quality. The study also found that easy banking is the key reason for agent banking, marked by the respondents, followed by the nearest location and adding new customers. Lack of training is the major challenge, followed by a lack of logistic support and cyber security risk in implementing agent banking in Bangladesh.

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.

Bangladesh is an extremely adverse affected country over the world related to environment and ecology due to global warming so that Bangladesh economy experienced many serious problems for global warming. The study is planned by addressing this burning issue and identifying gaps in knowledge after reviewing related literature. The aim of this dissertation is to look into sustainable banking practice, i.e., green banking practice by selected banks. To achieve the aim of the thesis, it is focused on major impact of selected green banking practice on banks profitability and also showed the problems, prospect, suggestion & recommendations for selected banks & stakeholders. In this study, the secondary data are collected from annuals reports during 2011-18 of selected commercial banks. The statistical techniques are used, i.e., descriptive statistics, graphic presentations, ANOVA, linear regression and regression for panel data in Gretl, etc. After analyzing the data, the results of this study inform us of empirical understanding that is there are a poor impact on profitability, i.e., ROA, ROE, and ROI by independent variables i.e., GFI, CRF, OB, GT and GAC of the selected SCBs & PCBs over the study period, because the variation of ROA is only 24% and Variation of ROI is only 39% by independent variables, at the same time ROE has low negative correlations with independent variables because Rho is ?0.235. The comparative position of PCBs is better than SCBs, but both selected SCBs and PCBs' performance are found below satisfactory in most of the aspects of the study during 2011-18.