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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.

With a growing preference for active, authentic, and cultural experiences over traditional ones, creative tourism has garnered significant academic interest. This study offers a comprehensive review of creative tourism research, delineating its evolution, prominent contributors, pivotal areas, and prospective trajectories through a bibliometric analysis.

Employing a bibliometric analysis using the biblioshiny and VOSviewer software, this study systematically reviews 198 articles on creative tourism identified and retrieved from the Scopus database.

A notable increase in creative tourism research is witnessed in recent times, with Portugal and the Netherlands leading in publications and citations, respectively. This review also pinpoints key authors, countries, institutions, and journals shaping the field, and presents emerging themes such as authenticity and creative experience, culture and heritage, urban and rural contexts, and co-creation in creative tourism.

Identifying core research contributors (authors, countries, institutions, journals) and contributions (themes, topics) assists academics in seeking collaborations and shaping future research. Practitioners are advised to adapt these trends (authenticity, co-creation, sustainability) into their strategic planning to meet market demands.

This study offers a seminal review of creative tourism through a bibliometric analysis, a technique that leverages the power of technology (data, software) to engage in retrospection and projection—the hallmark of benchmarking studies across fields, including tourism. Noteworthily, this study provides a detailed summary of the field’s trajectory and significant trends, positioning itself as an essential reference for academic scholars, industry professionals, and policymakers with a keen interest in creative tourism.

This paper aims to provide a conceptual framework containing SERVQUAL original dimensions and add two additional dimensions: patient satisfaction and loyalty in the hospital SQ model that demonstrates the relationship between hospital service quality, patient satisfaction and loyalty from patients’ perspective.

This research conducted a thorough literature review using specific keywords and electronic databases, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Through analysis, the key dimensions of service quality in Indian hospitals were identified, with the addition of patient satisfaction and loyalty as variables. Of 1,000 initially downloaded papers, 497 were included.

While many researchers rely on the SERVQUAL model, some introduce new or modified dimensions, often renaming existing ones. This study identifies the RATER factors as the main dimensions patients use to evaluate hospital services. This study finds a positive relationship between service quality, patient satisfaction and loyalty.

An understanding of how health-care service quality dimensions, directly and indirectly, affect patient satisfaction and loyalty is important for hospital marketing managers. This study helps them take action to improve patient satisfaction, which encourages patients to be loyal.

This research provides a comprehensive framework for measuring health-care service quality, combining SERVQUAL dimensions and new variables. This study offers useful insights for academics and health-care professionals, promoting more accurate measurement and enhancement of service quality. The use of PRISMA in this context is also innovative, as it is less common in administrative health-care research.

This study aims to analyse and understand customer sentiments and perceptions from neobanking mobile applications by using advanced machine learning and text mining techniques.

This study explores a substantial large data set of 330,399 user reviews available in the form of unstructured textual data from neobanking mobile applications. This study is aimed to extract meaningful patterns, topics, sentiments and themes from the data.

The results show that the success of neobanking mobile applications depends on user experience, security features, personalised services and technological innovation.

This study is limited to textual resources available in the public domain, and hence may not present the entire range of user experiences. Further studies should incorporate a wider range of data sources and investigate the impact of regional disparities on user preferences.

This study provides actionable ideas for neobanking service providers, enabling them to improve service quality and mobile application user experience by integrating customer input and the latest trends. These results can offer important inputs to the process of user interaction design, implementation of new features and customer support services.

This study uses text mining approaches to analyse neobanking mobile applications, which further contribute to the growing literature on digital banking and FinTech. This study offers a unique view of consumer behaviour and preferences in the realm of digital banking, which will add to the literature on the quality of service concerning mobile applications.

Knowledge sabotage is an emerging challenge for today’s managers because every second individual is found to be involved in such behaviors. Therefore, to understand the antecedents and consequences of knowledge sabotage, this study aims to investigate the trustful climate toward knowledge-sharing climate through knowledge sabotage. It further investigates the conditional role of destructive personality types in the relationship between trustful climate and knowledge sabotage.

In this quantitative study, the data from 307 employees and their immediate supervisors working in the IT sector of Pakistan were collected on convenience basis. Furthermore, structural equation modeling and hierarchical regression techniques were applied to test the hypotheses.

The findings revealed that individuals’ perception of a trustful climate positively contributes to knowledge-sharing climate, and knowledge sabotage intervenes this relationship. Furthermore, the dark triad (psychopathy, narcissism and Machiavellianism) was noted to moderate the association between trustful climate and knowledge sabotage such that the dark triad strengthens this negative association.

This study suggests using peer/colleagues’ rated scales to measure destructive personality. However, the findings suggest managers involve employees in the decision-making process and work on their skills to develop their trust in organizations and involve knowledge sharing. Conversely, managers are suggested to arrange training/workshops for individuals to understand and overcome their negative personality traits.

Contributing to the novel literature on the most extreme form of counterproductive behavior in the field of knowledge management (i.e. knowledge sabotage), this study, to the best of the authors’ knowledge, is the first of its kind that empirically investigates the conditional role of destructive personalities toward knowledge sabotage in the presence of trustful climate.

This paper aims to investigate the direct and indirect relationship between CEO compensation and earnings management using corporate social responsibility (CSR) as a mediating variable.

This study examines 159 French firms listed on the SBF 250 index, encompassing 1,908 firm-year observations from 2011 to 2022, to investigate the relationship between CEO compensation, CSR and earnings management. We used discretionary accruals as the earnings management measure, under the Kothariet al. model (2005). The direct and indirect effects between CEO compensation and earnings management were tested using structural equation model analysis.

The results reveal that CEO compensation positively influences earnings management. Higher CEO compensation is associated with a greater likelihood of engaging in earnings management practices. CSR was found to partially mediate the relationship between CEO compensation and corporate earnings management. Further analysis indicates that the social and environmental dimensions of CSR contribute significantly to this mediating effect.

The study’s focus on the French institutional context may limit the generalizability of the findings to other regions. In addition, the relatively small sample size, given the limited number of publicly listed firms in France, suggests that extending the study to include other European countries could enhance the robustness of the results.

The findings have practical implications for companies, policymakers and regulators seeking to curb opportunistic managerial behavior. Regulators can develop policies that promote transparency and ethical financial reporting, leveraging CSR as a governance tool to curb earnings manipulation.

This study highlights the ethical concerns of excessive CEO compensation, which may incentivize earnings management and undermine financial transparency. It emphasizes the need for strong CSR practices, particularly in the social and environmental dimensions, to mitigate these issues and align corporate behavior with societal and sustainability goals.

The originality of this paper lies in its exploration of both direct and indirect relationships between CEO compensation and earnings management, with CSR acting as a mediating variable. Unlike previous studies that have primarily focused on the direct link between CEO compensation and earnings management, this research investigates the potential mediating role of CSR in this relationship. In addition, this study distinguishes itself by examining the impact of the structure of CEO compensation on earnings management. While the existing literature has concentrated on total CEO compensation, the effects of its individual components such as fixed and variable compensation remain underexplored.

This research aims to investigate the impact of artificial intelligence (AI) adoption on the innovation dynamics of Chinese manufacturing enterprises, with a specific focus on the intricate interplay with the labor structure.

Leveraging panel data of listed companies from 2010 to 2022, this study employs the two-way fixed effects (TWFE) model to examine the influence of AI adoption on Chinese manufacturing companies' innovativeness. Firm-level AI adoption is measured by constructing a three-dimensional attention, application and absorption index.

The results indicate that (1) AI adoption has a positive impact on both internal innovation capability and external innovation interaction, (2) AI adoption has dual effects on the education and skill structure of labor in manufacturing enterprises and (3) enterprises with a highly educated and skilled workforce exhibit a stronger influence of AI adoption on innovativeness.

This research contributes to the academic and practical discourse by unveiling the underlying mechanisms of AI affecting innovation and introducing a new measurement of the AI adoption index. The findings emphasize the need for a highly educated and skilled workforce to navigate the complexities of AI-driven innovation, offering valuable theoretical and practical implications for policymakers and enterprises.