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The present study aims to comprehensively examine the impact of the Union Bank of Switzerland (UBS) takeover of Credit Suisse on the banking and financial services sector in the Indian stock market. To fully comprehend the impact of the event, the study separately investigates the response of private sector banks, public sector banks, overall banking companies and financial services companies to the takeover of the second-largest financial institution in Switzerland.

The study employs event study methodology, using the market model, to analyze the event's impact on Indian banking and financial services sector stocks. The data consists of daily closing prices of companies included in the Nifty Private Bank Index, Nifty PSU Bank Index, Nifty Bank Index and Nifty Financial Services Index from the National Stock Exchange (NSE). Furthermore, cross-sectional regression analysis has been conducted to explore the factors that drive abnormal returns.

The empirical findings of the study suggest the event had a heterogeneous impact on the stock prices of Indian banks and financial services companies. While public sector banks experienced a significant negative impact on select days within the event window, the overall Indian banking sector and financial services companies also witnessed notable declines. In contrast, Indian private sector banks were relatively resilient, exhibiting minimal effects. However, the cumulative effect is found to be insignificant for all four categories across different event windows. The study also observed that the cumulative abnormal returns (CARs) were significantly influenced by certain variables during different event windows.

To the best of the authors' knowledge, the present study is the earliest attempt that investigates the impact of the UBS takeover of Credit Suisse on the Indian banking and financial services sector using event study methodology and cross-sectional regression model.

In the backdrop of an increase in market-based banking activities, this paper aims to study operational efficiency of Indian banking sector during 2009–2010 through 2017–2018 considering Capital Gain and Gain from Forex Market (as desirable outputs) and Slippage (as undesirable byproducts) simultaneously, along with Advances – a desirable output considered in the traditional banking performance assessment literature. This enables to have an assessment of performance (as captured by the measured efficiency scores) of Indian Banks following an alternative viewpoint about the banking activities. The authors also explain such efficiency scores in terms of bank-specific factors, banking industry competition scenario and interest rate channel.

Using data envelopment analysis (DEA) method, the authors estimate six alternatives but interlinked operational efficiency scores (TES) of the Indian domestic commercial banks. In the second stage, they explain such TES in terms of bank-specific factors, banking industry competition scenario and interest rate channel.

The authors observe that the private sector banks as a group outperform those under public ownership. Moreover, although the private sector banks could maintain somewhat consistency in their operational efficiency performance over the sample period, public sector banks clearly show a declining tendency. The second stage econometric estimation results show that the priority sector lending has a negative effect on efficiency. Interestingly, the authors get varying results for the relationship between maturity and efficiency score depending on banks’ strategies on stressed assets management. Furthermore, the analyses result that banks are not so efficient in managing relatively larger-volume loans. It is also observed that banks’ efficiency positively depends on the Credit-to-Deposit (CD) ratio. It is found that the overall operational efficiency of the banks to manage their credit risk portfolio improves with a reduction in the lending rate (LR). However, the interaction of lending activities and capital market shows that with the increase in LR, corporate borrowers may switch to capital market to explore for desired funds, which may induce the banking sector to investment in capital markets and create a positive market sentiment.

Literature, although scanty, is there dealing stressed assets of a bank as some undesirable byproducts of its operational and business activities. However, such literature mostly done within the traditional framework of banking business activities and modern market-based business activities are almost absent in the literature. The authors have done it in the present study.

The study examines whether the Basel-III regulations impact the financial performance, operational efficiency and resilience of Indian banks. Further, the study tests whether there is a variance in the impact between private- and public-sector banks.

The study uses panel data regression on data from 16 private- and 12 public-sector banks from the years 2016–2022. Random-effect estimation is used, and robust standard errors are calculated.

The main findings indicate that the Basel-III regulations related to capital and leverage boost public-sector banks' financial performance and resilience. However, a similar impact is not detected in the case of private-sector banks.

The findings signify that the Basel-III framework does not address the differences between public and private-sector banks. Therefore, the policy implications are of practical importance and indicate that Basel-III regulations should not be considered a one-size-fits-all type of bank. Instead, policymakers should consider the structural differences between private and public-sector banks concerning Basel-III regulations.

The study addresses a significant limitation of the Basel-III regulations, which, in their current state, somehow fail to account for the differences between the public- and private-sector banks.

The banking industry faces increasing scrutiny from stakeholders regarding its environmental and social impacts, given its crucial role in fostering economic growth. Banks have been encouraged to adopt environmental, social and governance (ESG) practices to mitigate risks and safeguard their reputation. However, the effectiveness of ESG sensitivity within the banking industry is contingent upon ownership and structural factors. The extent to which banks can integrate ESG considerations into their operations and decision-making processes may vary based on their ownership structures. Therefore, this study aims to examine if the impact of ESG on the performance of Indian banks varies between private and public sector banks.

The study employs six years of panel data from two separate samples of 12 private sector banks and 10 public sector banks in India. It utilises fixed and random effect estimation techniques with robust standard errors to derive accurate and reliable econometric results.

The main findings of this study reveal intriguing insights into the relationship between ESG factors and bank performance, considering the influence of ownership structure. For private sector banks, the ESG composite score, particularly the social dimension, negatively impacts financial performance. However, there is a contrasting positive effect on efficiency. In contrast, public sector banks demonstrate a positive and significant association between the environmental score and return on equity and non-performing assets.

The findings highlight the need for tailored strategies that align with ownership structure to achieve sustainable financial and societal outcomes in the banking industry. Furthermore, it emphasises the need for private-sector banks to streamline their ESG initiatives, especially in the social dimension, to mitigate negative impacts on their financial performance.

This study introduces a novel dimension by addressing the “one size fits all” bias in prior research that overlooked bank ownership differences when examining the impact of ESG factors on bank performance.

This study examines the dynamics of financial institution development among economies in sub-Saharan Africa (SSA) and how volatility in forex-adjusted price of key globally traded, commodities and macroeconomic risk influence such development.

The study is based on data collected from the period starting 2001 to 2019 for relevant variables; and the empirical test was performed using the two-step system generalized method of moments (TSS-GMM) estimation method.

Empirical estimates suggest that volatility in forex-adjusted prices of crude oil and cocoa are inimical to development of financial institutions among economies in the sub-region. On the other hand, volatility in the price of gold is found to have a significant positive effect on development of financial institutions. Additionally, political instability is found to exacerbate the adverse effect of volatility in the price of globally traded commodities on the development of financial institutions in the sub-region.

The study verifies how volatility in forex-adjusted prices of key traded commodities on the global market influence development of financial institutions in the sub-region. Additionally, the study examines the impact of macroeconomic risk, a principal component analysis (PCA) constructed index on the development trajectory of financial institutions. Finally, the authors examine the moderating role of institutional quality and political instability in the relationship in question.

This study aims to systematically review the literature on happiness at work (HAW) by analysing existing studies, identifying relevant themes in HAW research and evaluating the methodologies used in the literature.

The study used a systematic review process, following the guidelines and principles outlined in the updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement 2020 and checklist. Articles were collected from six databases: Emerald insight, Taylor & Francis Online, Science Direct, Wiley Online Library, Springer and MDPI. Subsequently, systematic review was performed on 41 HAW articles published in 29 different journals between 2010 and 2022. The authors only considered articles that were either indexed by Scopus or in the Academic Journal Guide (AJG) list.

The study identified six major themes, assessed the operationalisation of HAW and analysed the research methodologies and statistical tools used in the sample studies. Majority of the articles discussed the antecedents of HAW followed by the HAW as a mediator. There is a high heterogeneity in the operationalisation of HAW in the reviewed articles. Moreover, majority of the studies have prioritised service sectors over the industrial sectors.

This study represents the first comprehensive review of the existing literature on HAW by using a systematic review methodology.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

This current study draws a comparison between the performance indicators of public sector banks (PSBs) and private sector banks (or non-PSBs) in India. The study controls for the impact of COVID-19.

The study uses strongly balanced panel data for seven years of 12 PSBs and 10 non-PSBs from the Nifty PSU Bank Index and Nifty Private Bank Index. The study applies panel data methodology to arrive at the results.

The study demonstrates that the behavior of indicators of performance and returns volatility for PSBs and non-PSBs differs substantially. While factors like capital adequacy ratio (CAR), cost management (COST), liquidity (LIQ), inflation and economic growth exhibit a similar impact on both categories of Indian banks, the effect of credit risk (RISK), market power (POWER) and COVID-19 on performance and returns stability is different for PSBs and non-PSBs.

There is a limited sample size of banks in India.

PSBs and non-PSBs need distinct treatments when calibrating performance indicators.

The performance and stability of banks are essential for society at large, the depositors and the investors.

The study provides vibrant implications for insight for banks to calibrate the variables that determine performance and stability, regulators and policymakers for effective governance of the banking ecosystem and effective utilization of public funds and capital. The findings are relevant for policymaking today, when the government is considering the privatization of a few PSBs.

The novel coronavirus (COVID-19) has caused financial stress and limited their lending agility, resulting in more non-performing loans (NPLs) and lower performance during the II wave of the coronavirus crisis. Therefore, it is essential to identify the risky factors influencing the financial performance of Indian banks spanning 2018–2022.

Our sample consists of a balanced panel dataset of 75 scheduled commercial banks from three different ownership groups, including public, private and foreign banks, that were actively engaged in their operations during 2018–2022. Factor identification is performed via a fixed-effects model (FEM) that solves the issue of heterogeneity across different with banks over time. Additionally, to ensure the robustness of our findings, we also identify the risky drivers of the financial performance of Indian banks using an alternative measure, the pooled ordinary least squares (OLS) model.

Empirical evidence indicates that default risk, solvency risk and COVAR reduce financial performance in India. However, high liquidity, Z-score and the COVID-19 crisis enhance the financial performance of Indian banks. Unsystematic risk and systemic risk factors play an important role in determining the prognosis of COVID-19. The study supports the “bad-management,” “moral hazard” and “tail risk spillover of a single bank to the system” hypotheses. Public sector banks (PSBs) have considerable potential to achieve financial performance while controlling unsystematic risk and exogenous shocks relative to their peer group. Finally, robustness check estimates confirm the coefficients of the main model.

This study contributes to the knowledge in the banking literature by identifying risk factors that may affect financial performance during a crisis nexus and providing information about preventive measures. These insights are valuable to bankers, academics, managers and regulators for policy formulation. The findings of this paper provide important insights by considering all the risk factors that may be responsible for reducing the probability of financial performance in the banking system of an emerging market economy.

The empirical analysis has been done with a fresh perspective to consider unsystematic risk, systemic risk and exogenous risk (COVID-19) with the financial performance of Indian banks. Furthermore, none of the existing banking literature explicitly explores the drivers of the I and II waves of COVID-19 while considering COVID-19 as a dependent variable. Therefore, the aim of the present study is to make efforts in this direction.

The paper aims to craft a non-parametric composite value for the board quality of Indian banks where the weights can be assigned endogenously.

The study employed a non-parametric data envelopment analysis (DEA)-based novel extension known as the benefit of doubt approach. To measure the strength of the Indian bank corporate board in terms of board efficiency (BEF), the study used a mixed approach, i.e. first, the study calculates the percentile ranks of the five attributes that the study assumes are the characteristics of the strong board including board size, number of outside directors, frequency of meetings, non-duality leadership and board gender diversity. Thereafter, the study performs the benefit-to-doubt approach to finally measure the efficiency of the board.

The findings of the study establish that the methodological framework present in the study to measure the strength of the board in terms of BEF has been a much superior method over the other weighted and non-weighted linear average methods.

This methodology aids the shareholders, investors and regulatory bodies in rating the Indian banks based on their strength in terms of better monitoring boards and ensuring a smooth agent–owner relationship.

The benefit of doubt approach has been a unique and novel methodology to craft the composite value for any multidimensional phenomenon. One of the major benefits of using this approach is that it assigns the weights endogenously to each dimension and thereafter collectively determines the efficiency of such a phenomenon.