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This paper aims to investigate the role of corporate governance on the bank profitability of Indian banks vis-à-vis South Asian Association for Regional Cooperation (SAARC) nations.

For the Corporate Governance Index, the authors examined board accountability, transparency and disclosure and audit committee, while Tobin’s Q, return on equity and return on assets are used to measure the bank’s profitability. The study used a two-stage analysis based on balanced panel data for robust findings. Sample of this study consists of 60 commercial banks from India and 60 banks from SAARC nations for the period of 2009–2021. This study used panel regression and a generalized method of moment approach using the CAMELS framework on banking industry-specific variables to determine their respective impacts.

The findings of this study suggest that board accountability is positive and significantly affects the profitability of banks as indicated by return on assets, return on equity and Tobin’s Q. In contrast, the audit committee has a positive and insignificant impact on return on assets, return on equity and Tobin’s Q, while transparency and disclosure have a negative and significant impact on these metrics. Furthermore, the country dummy result shows a significant positive impact on all the bank performance parameters, implying that Indian banks have the highest degree of convergence with corporate governance as compared to other SAARC nations.

This study provides insight to the regulators, policymakers and financial institutions to evaluate the role of corporate governance in emerging economies. However, the findings of the study should be interpreted with caution, as the results are sensitive to the disparity between India and other SAARC nations' government policies, climatic circumstances and cultural or religious traditions.

To the best of the authors’ knowledge, this is the first attempt to gauge the performance of Indian banks vis-à-vis SAARC nations using the CAMELS framework approach. Further, findings of this study suggest some novel evidence tying corporate governance quality with the profitability of banks among SAARC nations.

The purpose of this paper is to elucidate the social information processing theory, which is extended by the (1) effect of whistleblowing education on whistleblowing intentions, (2) simultaneous examination of the indirect relationship between whistleblowing education and whistleblowing intentions via moral identity and (3) relativism in influencing this mediation.

Multi-wave data collected at three internals from bank employees (n = 294) were analyzed to test the proposed model.

Results of the study demonstrate that whistleblowing education favorably influences whistleblowing intentions directly as well as through moral identity. Relativism serves as the buffer in the indirect effects of whistleblowing education on whistleblowing intentions through moral identity attenuating these indirect effects in individuals with dominant relativism level.

This study strives to extend the whistleblowing education and whistleblowing intentions literature by unpacking a moral identity mechanism through which whistleblowing education kindles whistleblowing intention and relativism as boundary condition to attenuate such motivation.

This study aims to investigate the efficiency of Indian commercial banks from 2002 to 2018 using the stochastic frontier analysis.

This study uses the parametric approach of the stochastic frontier to examine the technical efficiency of banks acknowledging exogenous shocks, omitted variables and measurement errors, filling a gap in the existing financial literature. The scope of this study was constrained to 71 scheduled commercial banks to make it manageable and productive with 1,036 observations.

The results show that the mean technical efficiency of new private banks remained constant at 92.7% during the study period because of technology diffusion in banking systems. The technical efficiency of the nationalized, old private and foreign banks has enhanced over the period because of the efficient utilization of various innovative information technology services such as mobile banking, cheque truncation system, magnetic ink character recognition. However, the foreign banks are still laggards with a mean technical efficiency of 81.7%. The empirical findings suggest that new private sector banks depict higher efficiency than nationalized, old private and foreign banks.

This study’s sample represents all categories of banks (public, private and foreign) including the banks that merged or consolidated during the period of study. To achieve the desired results, the authors incorporate the consolidated and merged banks in their data set. Further, the authors excluded all scheduled small finance banks and scheduled payment banks from their analysis, as these entities commenced operations post-2015. Additionally, the authors also excluded regional rural banks because of their distinct mandate aimed at servicing the rural populace and agricultural sector.

This study contributes to the literature on the performance of conventional banks in general and emerging markets, in particular, using the most recent data and covering a relatively long period using the stochastic frontier approach.

This paper examines the profitability and performance measurement of U.S. regional banks during the period 1994–2011, using the GMM estimator technique. Our study extends prior research by including several factors not previously considered using U.S. data.

We use bank-specific, industry-specific, and macroeconomic determinants of profitability contemporaneous with our performance indicators. We follow the accounting fundamental analysis path in explaining the bank performance.

Among the performance measures, the efficiency ratio and provisions for credit losses are negatively and equity scaled by assets is positively related to profitability. However, these relationships either reverse (efficiency ratio and provisions for credit losses) or become insignificant (equity scaled by assets) when the target becomes change in profitability. The level of nonperforming assets is negatively related to profitability across all measures of profitability used. Macroeconomic variables are largely unrelated to profitability during the year they are measured. However, they have a significant relationship with earnings change measures, suggesting they have a lagged effect on profitability. The slope of the yield curve is especially strong in this regard.

We use our determinants to model changes in bank profitability one year ahead, in addition to including several factors not previously considered, using the predictive focus of the fundamental analysis research.

Recent literature has highlighted the importance of human resource management, knowledge management, and technical innovation as key elements for achieving competitive advantage. Furthermore, research has shown a positive relationship between these three variables. However, empirical research on this issue is still scarce. This paper analyzes those linkages using structural equation modeling with data collected from 373 Spanish firms. The findings show that there is a relationship among the variables, although it is more complex than described in previous studies.

In recent times, mobile banking has become the best alternative for transactions associated with payments like bills, fees, and peer-to-peer payments. Therefore, the pace of adoption is increasing day after other. However, the numbers of customers are not equal to the expectations as there are several challenges and threats hindering in the way of excellence and growth of mobile banking. Therefore, this chapter has been written purposively to address all the elements that are associated with the use of mobile banking with special emphasis on Pakistan and other developing sides of Asia. In fact, concern towards Asian sides is mandatory as the continent has the massive charm to attract users towards the use of mobile banking, but there is a need for proper policy and concern from stakeholders in order to give a push to the technology, which is fruitful for society, environment, as well as economy. The study includes an in-depth discussion on factors that need attention to make the study implicative and thorough for conducting further research in the field of Fin-Tech and mobile banking.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

This study aims to determine the factors that influence the actual behavior of Islamic digital banking customers based on the users’ perspectives during the recovery from the COVID-19 pandemic crisis.

This study used a causal exploratory method with quantitative and qualitative approaches presented in two parts. The first study (Study 1) was empirical testing of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) used WARP-partial least square by modifying the variables of customer trust and satisfaction. A. Hayes’s PROCESS procedures were applied to examine the moderating effects of age, gender and experience. The second study (Study 2) explored the obstacles and solutions to improve digital banking services. The survey was conducted on 897 Islamic bank customers throughout Indonesia.

The results showed that all the hypotheses about the direct effect of the modification of the UTAUT2 model were supported empirically except for the effect of price value and hedonic motivation on behavioral intention, and there was just one moderating effect in this study. The other results show that 35 factors became obstacles to using digital banking.

This study had limited qualitative data collection techniques that were less deep and comprehensive. This happened because respondents were given complete confidence to fill in the open questions without any follow-up to customer answers. For further research, an in-depth interview method can be added to crucial information from the customer and expert side to get in-depth and complementary data regarding constraints and solutions. This study only used a sample of customers of Islamic banks; further research is expected to use customers of Islamic banks and conventional banks to compare their preferences for digital banking.

This study offered seven strategies that could encourage increased digital banking transactions to accelerate crisis management, mitigate cybercrime and communicate the positive impact of digital banking effectively and efficiently.

This study offered seven strategies that could encourage increased transactions using digital banking to accelerate crisis management, mitigate cybercrime and communicate the positive impact of digital banking effectively and efficiently.

Most of the existing studies focused on the modification model of the UTAUT2 model. The study is unique because it has proposed the obstacle and solution to improve digital banking service in Islamic Bank in Indonesia.

Risk assessment is imperative for disaster risk reduction. The risk is rooted to various physical, social, economic, demographic and environmental factors that determine the probable magnitude of loss during an extreme event. By way of bringing a conceptual model into practice, this paper aims to examine the flood risk of the Srinagar city.

The “risk triangle” model has been adopted in the present investigation evaluating parameters, reflective of hazard (intensity), exposure (spatial) and vulnerability (sensitivity) using Landsat-8 operational land imager scene (10 September 2014), global positioning system, Cartosat-1 digital elevation model and socioeconomic and demographic data (Census of India, 2011). The authors characterise flood hazard intensity on the basis of variability in water depth during a recent event (September 2014 Kashmir flood); spatial exposure as a function of terrain elevation; and socioeconomic structure and demographic composition of each municipal ward of the city as a determinant factor of the vulnerability. Statistical evaluation and geographic information system-based systematic integration of all the multi-resolution data layers helped to develop composite flood risk score of each ward of the city.

Principal deliverable of this study is flood risk map of the Srinagar city. The results reveal that approximately 46 per cent of the city comprising 33 municipal wards is at high risk, while rest of the area, i.e. 17 and 37 per cent, exhibit moderate and low levels of risk, constituting 23 and 12 municipal wards, respectively. It is very likely that the municipal wards expressing high risk may witness comparatively more damage (impact) during any future flood event. Thus, there is a need of planned interventions (structural and non-structural) to minimise the emergent risk.

Very rare attempts have been made to bring theoretical models of disaster research in practice; this is mainly because of the complexities associated with the data (selection, availability and subjectivity), methodology (integration, quantification) and resolution (spatial scales). In this direction, this work is expected to have considerable impact, as it provides a clear foundation to overcome such issues for the studies aiming at disaster risk assessment. Furthermore, using varied primary and secondary data, this paper demonstrates the relative (municipal wards) flood risk status of the Srinagar city, which is one of the key aspects for flood hazard mitigation.

China–Pakistan Economic Corridor (CPEC) is a framework of regional connectivity in which employees have to work in a cross-cultural environment. This study has extended the leader-member exchange theory by investigating the mediating role of employee commitment (EC) between the relationship of leader-member exchange (LMX) and employee's work-related behaviors.

PLS-SEM technique was used to test the model by utilizing a multi-wave/two-source data collected from employees and their supervisors (n = 500) working in different energy projects of CPEC.

According to the results/findings, LMX has a significant positive impact on employee commitment, employee performance (EP) and open-minded discussions, but insignificant impact on innovative work behaviour (IWB). Mediating role of employee commitment was significant between the relationship of LMX with EP and open-minded discussions, but insignificant with the IWB.

The study contributes empirical evidence to understanding the leader-member exchange relationship among Chinese managers and Pakistani workers. It also contributes to the LMX theory literature by investigating the effect of LMX on followers' outcomes (employee performance, IWB, open-minded discussions) through employee commitment.