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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.

Sustainable strategic management (SSM) is an integrated concept that entails sustainability in the approaches and processes of strategic management. Banking being a rapidly growing industry in service sector, it is reasonably important to study the SSM and its integrated performance. This paper aims to study the sustainable-strategic (SS) factors of Indian banks that affects their endurance and prioritizes the banks based on their sustainable and strategic performance.

This study appertains a sustainable balanced scorecard (SBSC) framework to determine the SS factors and an integrated multicriteria decision making (MCDM) method to weigh the criteria and prioritize the banks' performance.

The criterion weightage signifies sustainability, followed by financial and internal business perspective to be a crucial dimension for the performance of banks. The banks, State Bank of India, HDFC Bank Ltd and Canara Bank are ranked top-most on the SS performance.

The insights from the study on SS factors and banks' performance can be further used by policy-makers and researchers to understand the sustainability assessing factors and focus on making policies and further studies to enhance the performance in this regard.

Banking is one of the potentially growing industry in service sector. It being a major part of economy's sustainable growth, it is essential to assess the SS factors that enhance their sustainable performance. There is dearth of study in this purview, for developing countries like India. Thus, this study critically analyses the strategic sustainability of Indian banking industry to ascertain the SS factors and prioritize the performance of banks based on criterion weightage and bank's SS operations.

This paper aims to investigate the short- and long-run influence of core banking solutions (CBSs) on productive efficiency and identify the presence of potential network externalities arising from CBS adoption. This paper further examines the differential behaviour of long-term effects across the banking structure.

This study uses a panel data set of Indian commercial banks from 2005 to 2021. Economic efficiency is quantified using VRS-based DEA programming algorithms. Productivity changes are measured through an input-oriented, DEA-based Malmquist productivity index. Short- and long-run effects are examined through a finite autoregressive distributed lag model, estimated through a pooled mean-group estimator.

Findings suggest that CBS adoption negatively correlates with cost structure until the first year of adoption. Nevertheless, significant benefits are visible from the third year. Furthermore, such associations are highly susceptible to the industry structure. CBS results in higher incremental benefits for private banks vis-à-vis state-owned banks. Large banks receive significant and quicker productivity improvements from CBS vis-à-vis small banks. Bank age guides CBS–performance associations, highlighting that mature banks may face the issue of legacy infrastructure in CBS adoption. The resultant networking externalities are significant as they enhance the attractiveness of the network, which subsequently augments inter-branch and inter-bank communications.

To the best of the authors’ knowledge, this study is the first to recognise the stickiness of one of the most homogeneously adopted technological innovations in the Indian banking sector. The presence of a conjoint technological network has the potential to enhance the service delivery process and ensure superior returns for Indian banks.

This study empirically demonstrates a contradiction between pillar 3 of Basel norms III and the designation of Systemically Important Banks (SIBs), also known as Too Big to Fail (TBTF). The objective of this study is threefold, which has been approached in a phased manner. The first is to determine the systemic importance of the banks under study; second, to examine if market discipline exists at different levels of systemic importance of banks and lastly, to examine if the strength of market discipline varies at different levels of systemic importance.

This study is based on all the public and private sector banks operating in the Indian banking sector. The Gaussian Mixture Model algorithm has been utilized to classify banks into distinct levels of systemic importance. Thereafter, market discipline has been observed by analyzing depositors' sentiments toward banks' risk (CAMEL indicators). The analysis has been performed by employing the system Generalized Method of Moments (GMM) to estimate models with different dependent variables.

The findings affirm the existence of market discipline across all levels of systemic importance. However, the strength of market discipline varies with the systemic importance of the banks, with weak market discipline being a negative externality of the SIBs designation.

By employing the Gaussian Mixture Model algorithm to develop a framework for categorizing banks on the basis of their systemic importance, this study is the first to go beyond the conventional method as outlined by the Reserve Bank of India (RBI).

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.

Growing concern over sustainability adoption has presented an array of challenges to businesses. While vital to an economy's success, banking is not immune to societal, environmental and economic consequences of business practices. The study has examined the sustainable performance of banking institutions on the suggested multidimensional framework comprising economic, environmental, social, governance and financial dimensions and 52 sustainability indicators. The study benchmarks the significant performance indicators of leading banks indispensable to sustainable banking performance. The findings attempt to address research questions concerning the extent of sustainable banking performance, ranking the sustainability dimensions and indicators and standardizing sustainability adoption metrics.

To determine the responsiveness of the banking industry to sustainability dimensions, content analysis was conducted using NVivo software for the year 2021–2022. Furthermore, a hybrid multicriteria decision-making (MCDM) approach is used by integrating entropy, the technique for order preference by similarity to ideal solution (TOPSIS) and VlseKriterijumska Optimizacija KOmpromisno Resenje (VIKOR) to provide relative weights to performance indicators and prioritize banks based on their sustainable performance. Sensitivity analysis is used to ensure the robustness of results.

In the context of the Indian banking industry, the pattern of sustainability reporting is inconsistent and concentrated on addressing environmental and social concerns. The results of the entropy methodology prioritized “Environmental” sustainability over other selected dimensions while “Financial” dimension has been assigned the least priority in the ranking order. The significant sustainable performance indicators delineated in this study should be used as standards to ensure the accountability and credibility of the sustainable banking industry. Additionally, the research findings will provide valuable inputs to policymakers and regulators to assure better contribution of the banking sector in meeting sustainability goals.

Considering the paucity of studies on sustainable banking performance, this study makes two significant contributions to the literature. First, the suggested multidimensional disclosure model integrating financial and nonfinancial indicators would facilitate banking institutions in addressing the five aspects of sustainability. As one of the first studies in the context of the Indian banking industry, the findings would pave the way for better diffusion of sustainability practices. Second, the inclusion of MCDM techniques prioritizes the significance of sustainability indicators and benchmarks the performance of leading banks to achieve better profits and more substantial growth.

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.

This study aims to develop a customer-centric model based on an online customer experience (OCE) construct relating to e-loyalty, e-trust and e-satisfaction, resulting in improved Net Promoter Score for Indian digital banks.

This study used an online survey method to gather data from a sample of 485 digital banking users, from which usable questionnaires were obtained. The obtained data were subjected to thorough analysis using partial least squares structural equation modelling to further investigate the research hypotheses.

The main factors determining digital banks’ OCE were perceived customer centrality, perceived value and perceived usability. Additionally, relevant constructs were evaluated using importance-performance map analysis.

This study used convenience sampling for the urban population using digital banking services; therefore, the outcome may be generalized to a limited extent. To further strengthen digital banking, it would be valuable to imitate studies in other countries.

There is a lack of research on digital banking and OCE in India; thus, this study will help rectify this issue while providing valuable insights. This study differs from others in that it examines the connections between online customer satisfaction, loyalty, trust and the bottom line of financial institutions using these factors as dependent variables instead of traditional measures.

India’s efforts to achieve large-scale financial inclusion are challenged by growing concerns related to the stability and profitability of the overall banking system. Although a rising dependence on digital finance and the acceptability of wallet-based payments was also visible during the post-demonetisation era and the coronavirus disease 2019 (Covid-19) pandemic, issues related to bank stability and profitability could be addressed through the extension of digital financial services (DFS), making the system more transparent and resilient to internal as well as external perturbations.

The study provides empirical evidence to support the bank digitalisation and extension of DFS to achieve financial inclusion. The impact of digital finance, macroeconomic aspects and microprudential factors (bank specific) on stability is examined for selected Indian banks using quarterly observations spanning 2011Q1–2020Q4. The relationship between banking stability (measured through z-score and Sharpe ratio) is established with digitalisation factors using the instrumental variable regression two-stage least square -based panel regression. Robustness is tested using panel vector autoregression models.

Digital transactions including mobile banking, National Electronic Fund Transfer (NEFT) and Real Time Gross Settlement (RTGS) prove vital and significant in establishing stable banking activity in the Indian context across both public and private banking institutions. Access to broadband services provides a positive impetus in this direction. These issues could be addressed through the extension of DFS making the system more transparent and resilient to internal as well as external perturbations. As an implication, the adoption of innovative means of transaction could empower the financially excluded sections of society.

The novelty of this study is to bring the discussion of digitalisation and bank stability (riskiness) in the Indian context to light. As the first of its kind, this study paves the way for providing an empirical justification for promoting and achieving bank stability through digitalisation in the era of post-demonetisation and Covid-19.