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This paper aims to explore the intention to adopt the Metaverse in Islamic banks, with a particular focus on evaluating perceived usefulness, ease of use, user satisfaction and the influence of religiosity. Integrating the technology adoption model (TAM) and religiosity intention model, this study will dissect the multidimensional aspects influencing the acceptance of Metaverse technologies.

Surveying Islamic bank professionals in Jordan, this study used a structured questionnaire and data augmentation to analyze Metaverse adoption factors. Using partial least squares-structural equation modeling, the relationships between ease of use, usefulness, religiosity and satisfaction were explored.

The study identifies pivotal relationships among perceived usefulness, ease of use, user satisfaction and religiosity in the context of adopting metaverse technologies in Islamic banks in Jordan. Evidence highlights the dominant role of perceived usefulness and ease in influencing both intention to use and satisfaction levels. Religiosity, while not a direct influencer, plays a collaborative role, underscoring a balanced mix of technological and religious elements that will potentially shape the adoption trajectory of metaverse technologies within this specific banking sector.

Integrating metaverse technologies in Islamic banks necessitates balancing technological advances with Sharia compliance. The study underscores the importance of aligning user experience with religious values and fostering innovation within Islamic ethical guidelines.

This study uniquely integrates the TAM and religiosity-intention model to explore metaverse adoption in Islamic banks, unveiling a nuanced interplay between technology and religious values. It offers practical insights for tailoring innovations in the Islamic financial ecosystem.

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 comprehensive insolvency model tailored to Islamic banks, ensuring alignment with Shariah principles throughout pre-insolvency, bankruptcy and post-bankruptcy stages.

The research adopts a qualitative research method, using a desktop research approach. Primary sources and secondary sources are examined to gather information and draw conclusions.

This study presents a comprehensive insolvency model designed for Islamic banks, rooted in Shariah principles. The model covers pre-insolvency, bankruptcy (taflis) and post-bankruptcy stages, incorporating key Shariah parameters to ensure adherence to Islamic finance principles. It addresses challenges such as adapting to dynamic financial landscapes and varying interpretations of Shariah principles. Notably, the model recognizes the separate legal personality of Islamic banks and emphasizes transparency, fairness and compliance with religious obligations. In the post-bankruptcy stage, directors are urged to voluntarily settle remaining debts, aligning with ethical and Shariah-compliant standards.

The study contributes to the stability and growth of Shariah-compliant financial systems by extending insolvency principles to Islamic banks, providing a foundation for future research and policymaking specific to this context.

This study examines the association between internal corporate governance mechanisms (i.e. board of directors and audit committee) and the information value of bank earnings. The authors comparatively assess this association across different bank types, Islamic versus conventional banks. The authors also investigate the mediating effect of Shariah governance.

The authors utilize a unique and an international sample of 723 bank-year observations representing 100 listed banks from 16 countries during the period 2007–2015. The authors investigate the characteristics of the board of directors and audit committee (i.e. size and independence) and employ three core analyses for earnings informativeness (i.e. earnings persistence, cash flow predictability and reliability of loan loss provisions). Additional analyses address Shariah supervisory boards’ (SSBs’) size, financial expertise and multiple outside directorships. The authors use the random-effect Generalised Least Squares (GLS) estimation technique and provide several robustness checks and sensitivities.

The authors find that, on average, having large and independent boards (and audit committees) increases the informativeness of reported earnings for banks. Conditional on bank type, our results report strong evidence for differential effects across the two alternative banking systems. In Islamic banks, large and independent board of directors (and audit committees) is positively associated with all measures of information value. There is insignificant evidence for conventional banks. However, SSBs show no significant effect on the reported earnings’ informativeness.

This is the first study, to the best of our knowledge, that empirically and comparatively assesses the information value of reported earnings in association with effective internal governance while recognizing the institutional characteristics of different bank types. The authors offer new insights to policymakers, investors and other stakeholders located within countries operating on a dual banking system. The results could help regulators to improve their rules/guidance related to double-layer governance and financial reporting quality.

The study aims to estimate the impact of the vigilant board independence (BIND) dimension that potentially neutralises the unfair influence of chief executive officer duality (CEODU) on Indian public banks' performance.

The study takes into account the fixed-effects model to investigate the potential moderating effect of BIND in the relationship between CEODU and Indian bank performance. The econometric model is also robust against heteroscedasticity, serial correlation and cross-section dependence issues to ensure that the model is free from such biases. The study also addresses the major issue of endogeneity via vector autoregression and performs the analysis by considering one period lag of the explanatory variables.

The findings demonstrate that CEODU does not always lead to a negative outcome on the performance until or unless the board is monitored by the effective presence of outside directors.

The regulatory bodies consider the results to strengthen board capital where CEODU can benefit a business entity if vigilance BIND is present at or above a threshold point.

The study evaluated an under-researched role of BIND as a moderator that undermines the negative influence of CEODU on the performance of Indian banks. The study also establishes that the CEO's contribution to performance increases when the number of outside directors is at or above a certain threshold.

Islamic banking has undergone significant adaption since its inception. This study aims to investigate why and how Islamic banks adapt their services, using participatory financing as evidence.

A qualitative study is designed, using working capital financing and commodity operations financing in Pakistan as analytical units. The data for each analytical unit is analyzed using a qualitative content analysis, while the findings are synthesized using a cross-case synthesis method.

Findings suggest that participatory financing has undergone extensive adaptation in the Islamic banking industry of Pakistan, in the wake of resolving constraints to participatory financing and increasing its viability. Consequently, participatory finance has emerged as an attractive and viable option in Pakistan. These findings suggest that unlike in the past, where Islamic banks used to buffer themselves from the environment and ignore the market demands, they have learned to respond effectively to the market demands and the challenges posed by the environment.

Findings suggest that the adaptation strategy is more effective than the migration strategy, because it enables the financial service systems to reduce the underlying risks by avoiding emergent threats and eradicating the inherent weaknesses.

The extant literature provides a generalized view on the adaptation process that Islamic banks undergo to comply with their environment. However, it is limited in terms of conceptualizing the adaptations and innovations in their products and the underlying structural variations. The present study fills this gap.

The purpose of the paper is to explore the long-run impact of board governance and bank performance on executive remuneration. More specifically, the study addresses two objectives. First, the authors investigate the long-run relationship between pay and performance hold for the Indian banking industry. Second, the authors explore the moderating role of the board in explaining the relationship between executive pay and performance.

The study uses multivariate panel co-integration approaches, i.e. fully modified and dynamic ordinary least square, to explain the co-integrating relationship between executive pay, governance and performance of Indian banks. The analysis is conducted for the period from 2005 to 2018.

The results of co-integration tests reveal a long-run relationship between executive pay, board governance and bank performance. The long-run estimates produce evidence in favour of the dynamic agency theory, suggesting that the implications of asymmetric information can be mitigated by associating the current executive pay with the bank performance in the previous periods. The finding of this study reveals that improvements in the board quality serve as a monitoring tool to constrain excessive pay and moderate the executives’ pay. Furthermore, the interaction of performance and board governance negatively impacts pay, supporting a substitution approach. It implies that setting optimal pay packages for executives necessitates enhanced and efficient board governance practices.

The study recommends significant policy implications for regulators and the board of directors that executive pay significantly responds to the bank’s performance and good board governance practices in the long run.

This paper provides novel evidence of long-run pay-performance-governance relation using a panel co-integration approach.

Academic research has intensively analyzed the relationship between market concentration or market power and banking stability but provides ambiguous results, which are summarized under the concentration-stability/fragility view. We provide empirical evidence that the mixed results are due to the difficulty of identifying reliable variables to measure concentration and market power.

Using data from 3,943 banks operating in the European Union (EU)-15 between 2013 and 2020, we employ linear regression models on panel data. Banking market concentration is measured by the Herfindahl–Hirschman Index (HHI), and market power is estimated by the product-specific Lerner Indices for the loan and deposit market, respectively.

Our analysis reveals a significantly stability-decreasing impact of market concentration (HHI) and a significantly stability-increasing effect of market power (Lerner Indices). In addition, we provide evidence for a weak (or even absent) empirical relationship between the (non)structural measures, challenging the validity of the structure-conduct-performance (SCP) paradigm. Our baseline findings remain robust, especially when controlling for a likely reverse causality.

Our results suggest that the HHI may reflect other factors beyond market power that influence banking stability. Thus, banking supervisors and competition authorities should investigate market concentration and market power simultaneously while considering their joint impact on banking stability.

Islamic Insurance (Takaful) played a dynamic role in Islamic Social Finance (ISF). The popularity of the Takaful concept is being increased with each passing day. To describe the process, it is important to understand past areas of research, research differences, areas of unknown Takaful research, as well as the existing data. However, the purpose of the paper is to provide a comprehensive analysis of the development of qualitative research by carefully examining the nature of science and aspects of social relations in ISF.

Field, concerns with analysing and measuring the scholarly literature, quantitative characteristics of sciences and scientific technologies are known as scient metrics. This research includes queries such as “Islamic Insurance”, “Takaful” and “Shariah Insurance” as a reference in “Article title, Abstract and Keywords” based on Scopus from 2002 to 2022. This analysis was conducted in February 2022. The Bibliometrics, R-Studio, VOSviewer and Excel software are used to analyse the collected data and apply the bibliometric analysis.

The gist of the results and findings is that there are clear research gaps in the existing literature on Takaful. The available research on this subject does cover historical background, concept and models of Takaful and customer satisfaction towards Takaful model. Very important areas such as use of technology for bringing innovation in Takaful products and Shariah issues in existing practice and their solutions were not found in the present literature on Takaful.

This is the comprehensive research article to examine current literature on Takaful with bibliometric analysis. Results and potential areas of this research could be much helpful for scholars and researchers to create more dynamic improvements in the scientific development of Takaful in ISF.

A stroke is a serious, life-threatening condition that occurs when the blood supply to a part of the brain is cut off. The earlier a stroke is treated, the less damage is likely to occur. One of the methods that can lead to faster treatment is timely and accurate prediction and diagnosis. This paper aims to compare the binary integer programming-data envelopment analysis (BIP-DEA) model and the logistic regression (LR) model for diagnosing and predicting the occurrence of stroke in Iran.

In this study, two algorithms of the BIP-DEA and LR methods were introduced and key risk factors leading to stroke were extracted.

The study population consisted of 2,100 samples (patients) divided into six subsamples of different sizes. The classification table of each algorithm showed that the BIP-DEA model had more reliable results than the LR for the small data size. After running each algorithm, the BIP-DEA and LR algorithms identified eight and five factors as more effective risk factors and causes of stroke, respectively. Finally, predictive models using the important risk factors were proposed.

The main objective of this study is to provide the integrated BIP-DEA algorithm as a fast, easy and suitable tool for evaluation and prediction. In fact, the BIP-DEA algorithm can be used as an alternative tool to the LR model when the sample size is small. These algorithms can be used in various fields, including the health-care industry, to predict and prevent various diseases before the patient’s condition becomes more dangerous.