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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.

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.