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This study examines the correlation between industry-specific loan disbursement and profitability in the banking sector of Bangladesh, with a particular focus on the influence of targeted lending on profitability. The study examines the impact of different variables such as total assets, total revenue, non-performing loans, and sector-specific loans (agricultural, transportation, construction, textile, pharmaceuticals, and food procurement), on profit after tax (PAT) by analyzing data from 41 commercial banks between 2009 and 2022. By employing various techniques such as Pooled Ordinary Least Squares (POLS), Two-Stage Least Squares (2SLS), and the Generalized Method of Moments (GMM), we have determined that total assets have a noteworthy adverse effect on PAT in both POLS and 2SLS models. Conversely, construction loans have a positive influence on PAT in these models. The total revenue consistently has a favorable effect on the profit after tax (PAT) in all models. In the GMM model, transportation loans and textile loans have a notable adverse effect on PAT, but pharmaceutical loans have a slight favorable effect. The presence of non-performing loans, total loans, agricultural loans, and food procurement loans does not have a substantial impact on the profitability after tax (PAT) in any of the models. So overall total revenue, construction loan and pharmaceutical loan have a positive impact on PAT and total assets, transportation loan and textile loan have a negative impact on PAT. This study emphasizes the significance of strategic lending in underdeveloped industries and provides practical implications for banking professionals and regulators to identify high-risk lending sectors and devise measures to improve long-term profitability. 

This paper investigates the factors that form bank risks in Bangladeshi state-owned banks. As a representation of bank risk, non-performing loans have been considered the dependent variable for this study. The relevant data have been extracted from six state-owned banks in Bangladesh from 2013 to 2022. The final dataset consists of 60 firm-year observations. The ordinary least square (OLS) regression with robust standard errors model is utilized to find the relationship of bank risks with determinants like asset size, efficiency, liquidity, profitability, leverage ratio, capital adequacy ratio, and loan to asset ratio. The findings say that bank size and loan-to-asset ratio have a highly significant positive relationship with bank risk, whereas profitability, capital adequacy ratio, and bank efficiency have a significant negative association with bank risk. On the other hand, leverage and liquidity are negatively and positively correlated with no statistical significance. To check the study's robustness, another proxy of bank risk, loan loss provision has been used and the results are almost similar. State-owned banks operate in every economy with a different mindset than the general commercial banks. Hence, policymakers should take necessary initiatives based on this study to bring down the high bank risks in state-owned banks in Bangladesh.

This study investigates the impact of some variables such as total revenue, total assets, total liabilities, total deposits, total unclassified loans, total classified loans, standard loans, special mention account loans, sub-standard loans, doubtful loans, and bad and loss loans on profit before tax. Unbalanced Panel Data were collected from the website of 45Commercial Bank of Bangladesh from the year 2010 to 2018. Ordinary Least Square (OLS), Pooled Ordinary Least Square (POLS), Driscoll-Kraay (DK), Second Stage Least square (2SLS), Generalized Methods of Moments (GMM) methods are used in this study. This research found that total revenue had a significant positive relationship with profit before tax in all the models except DK and GMM models. Total unclassified loans had a significant positive relationship and total liabilities had a significant negative relationship with profit before tax in all the models. Special mention account loans had a significant positive relationship with profit before tax in OLS and DK models and total classified loans had a significant positive relationship with profit before tax in GMM model.

Research Originality: This study investigates the relationship between inventory management and profitability within the textiles industry in Bangladesh, emphasizing the key factors that significantly enhance the industry's profitability. Research Objectives: This analysis investigates how various factors, including total assets, total equity, total revenue, share capital, retained earnings, finished items, work in progress, and raw materials, impact profit after tax (PAT). Research Methods: The data spans from 2011 to 2023 and encompasses 46 textile companies listed on the Dhaka Stock Exchange (DSE). To conduct this study, different models like Pooled Ordinary Least Square (POLS), Second Stage Least Square (2SLS), Generalized Method of Moments (GMM) are utilized. Empirical Results: Through the application of techniques including Pooled Ordinary Least Squares (POLS), Two-Stage Least Squares (2SLS), and the Generalized Method of Moments (GMM), we have established that total assets exhibit a significant negative correlation with PAT in both the POLS and 2SLS models. On the other hand, there is a notable positive correlation between total revenue and retained earnings on PAT across all 2SLS, POLS, and GMM models. The share capital shows a negative correlation with PAT in all three models: 2SLS, POLS, and GMM. The main independent variable, which is our fundamental focus, shows that finished goods have a positive correlation with PAT; however, this correlation lacks significance. The raw materials exhibited a negative correlation with PAT, and this relationship is significant. The correlation between Packing Materials and PAT is notably positive. This study highlights the importance of strategies that could facilitate sustainable growth in the textile industry.

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.

Research Originality: This study investigates the relationship between inventory management and profitability within the textiles industry in Bangladesh, emphasizing the key factors that significantly enhance the industry's profitability. Research Objectives: This analysis investigates how various factors, including total assets, total equity, total revenue, share capital, retained earnings, finished items, work in progress, and raw materials, impact profit after tax (PAT). Research Methods: The data spans from 2011 to 2023 and encompasses 46 textile companies listed on the Dhaka Stock Exchange (DSE). To conduct this study, different models like Pooled Ordinary Least Square (POLS), Second Stage Least Square (2SLS), Generalized Method of Moments (GMM) are utilized. Empirical Results: Through the application of techniques including Pooled Ordinary Least Squares (POLS), Two-Stage Least Squares (2SLS), and the Generalized Method of Moments (GMM), we have established that total assets exhibit a significant negative correlation with PAT in both the POLS and 2SLS models. On the other hand, there is a notable positive correlation between total revenue and retained earnings on PAT across all 2SLS, POLS, and GMM models. The share capital shows a negative correlation with PAT in all three models: 2SLS, POLS, and GMM. The main independent variable, which is our fundamental focus, shows that finished goods have a positive correlation with PAT; however, this correlation lacks significance. The raw materials exhibited a negative correlation with PAT, and this relationship is significant. The correlation between Packing Materials and PAT is notably positive. This study highlights the importance of strategies that could facilitate sustainable growth in the textile industry.

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.

This paper investigates the factors that form bank risks in Bangladeshi state-owned banks. As a representation of bank risk, non-performing loans have been considered the dependent variable for this study. The relevant data have been extracted from six state-owned banks in Bangladesh from 2013 to 2022. The final dataset consists of 60 firm-year observations. The ordinary least square (OLS) regression with robust standard errors model is utilized to find the relationship of bank risks with determinants like asset size, efficiency, liquidity, profitability, leverage ratio, capital adequacy ratio, and loan to asset ratio. The findings say that bank size and loan-to-asset ratio have a highly significant positive relationship with bank risk, whereas profitability, capital adequacy ratio, and bank efficiency have a significant negative association with bank risk. On the other hand, leverage and liquidity are negatively and positively correlated with no statistical significance. To check the study's robustness, another proxy of bank risk, loan loss provision has been used and the results are almost similar. State-owned banks operate in every economy with a different mindset than the general commercial banks. Hence, policymakers should take necessary initiatives based on this study to bring down the high bank risks in state-owned banks in Bangladesh.

This study examines the correlation between industry-specific loan disbursement and profitability in the banking sector of Bangladesh, with a particular focus on the influence of targeted lending on profitability. The study examines the impact of different variables such as total assets, total revenue, non-performing loans, and sector-specific loans (agricultural, transportation, construction, textile, pharmaceuticals, and food procurement), on profit after tax (PAT) by analyzing data from 41 commercial banks between 2009 and 2022. By employing various techniques such as Pooled Ordinary Least Squares (POLS), Two-Stage Least Squares (2SLS), and the Generalized Method of Moments (GMM), we have determined that total assets have a noteworthy adverse effect on PAT in both POLS and 2SLS models. Conversely, construction loans have a positive influence on PAT in these models. The total revenue consistently has a favorable effect on the profit after tax (PAT) in all models. In the GMM model, transportation loans and textile loans have a notable adverse effect on PAT, but pharmaceutical loans have a slight favorable effect. The presence of non-performing loans, total loans, agricultural loans, and food procurement loans does not have a substantial impact on the profitability after tax (PAT) in any of the models. So overall total revenue, construction loan and pharmaceutical loan have a positive impact on PAT and total assets, transportation loan and textile loan have a negative impact on PAT. This study emphasizes the significance of strategic lending in underdeveloped industries and provides practical implications for banking professionals and regulators to identify high-risk lending sectors and devise measures to improve long-term profitability. 

This study investigates the impact of some variables such as total revenue, total assets, total liabilities, total deposits, total unclassified loans, total classified loans, standard loans, special mention account loans, sub-standard loans, doubtful loans, and bad and loss loans on profit before tax. Unbalanced Panel Data were collected from the website of 45Commercial Bank of Bangladesh from the year 2010 to 2018. Ordinary Least Square (OLS), Pooled Ordinary Least Square (POLS), Driscoll-Kraay (DK), Second Stage Least square (2SLS), Generalized Methods of Moments (GMM) methods are used in this study. This research found that total revenue had a significant positive relationship with profit before tax in all the models except DK and GMM models. Total unclassified loans had a significant positive relationship and total liabilities had a significant negative relationship with profit before tax in all the models. Special mention account loans had a significant positive relationship with profit before tax in OLS and DK models and total classified loans had a significant positive relationship with profit before tax in GMM model.