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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.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

This study aims to focus on the five most relevant and discursive emerging technologies in accounting (cloud computing, big data and data analytics, blockchain, artificial intelligence (AI) and robotics process automation [RPA]). It investigates the adoption and use of these technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey.

The study investigates the adoption and use of emerging technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey. This study considers the said nature and characteristics of emerging technologies and proposes a model using the factors that have been found to be significant and most commonly investigated by existing prior technology-organization-environment (TOE)-related technology adoption studies. This survey applies the TOE framework and examines the influence of significant and most commonly known factors on Canadian firms’ intention to adopt the said emerging technologies.

Study results indicate that Canadian accounting professionals’ self-assessed knowledge (about these emerging technologies) is more theoretical than operational. Cloud computing is highly used by Canadian firms, while the use of other technologies, particularly blockchain and RPA, is reportedly low. However, firms’ intention about the future adoption of these technologies seems positive. Study results reveal that only the relative advantage and top management commitment are found to be significant considerations influencing the adoption intention.

Study findings confirm some results presented in earlier studies but provide additional insights from a new perspective, that of accounting professionals in Canada. The first limitation relates to the respondents. Although accounting professionals provided valuable insights, their responses are personal views and do not necessarily represent the views of other professionals within the same firm or the official position of their accounting departments or firms. Therefore, the exclusion of diverse viewpoints from the same firm might have negatively impacted the results of this study. Second, this study sample is limited to Canada-based firms, which means that the study reflects only the situation in that country. Third, considering the research method and the limit on the number of questions the authors could ask, respondents were only asked to rate the impact of these five technologies on the accounting field and to clarify which technologies are used.

This study’s findings confirm that the organizational intention to adopt new technology is not primarily based on the characteristics of the technology. In the case of emerging technology adoption, the decision also depends upon other factors related to the internal organization. Furthermore, although this study found no support for the effect of environmental factors, it fills a gap in the literature by including the factor of vendor support, which has received little attention in prior information technology (IT)/ information system (IS) adoption research. Moreover, in contrast to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study findings may serve as a guide for researchers, practitioners, firms and other stakeholders, particularly technology providers, interested in learning about emerging technologies’ adoption and use in Canada and/or in a relevant context. Contrary to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study provides insights into the said technologies’ actual adoption and improves the awareness of firms and stakeholders to the effect of some constructs that influence the adoption of these emerging technologies in accounting.

Knowledge sharing enables a firm’s absorptive capacity to reconfigure its dynamic capabilities to sense, track and recognise embryonic business opportunities. Entrepreneurial opportunity recognition triggers entrepreneurs to invest in and upgrade their knowledge practices to improve entrepreneurial performance. This study aims to examine the relationship between knowledge sharing and absorptive capacity on entrepreneurial orientation as well as the moderating effect of opportunity recognition and the mediating effect of absorptive capacity.

A quantitative cross-sectional research design was applied to data from Algerian small and medium-sized enterprise managers in middle- to top-management positions. The final analysis using smart PLS included 246 respondents.

Knowledge sharing positively influenced entrepreneurial orientation and absorptive capacity. In addition, the findings reveal that entrepreneurial orientation positively influences entrepreneurial performance, and opportunity recognition strengthens the relationship between entrepreneurial orientation and entrepreneurial performance. Entrepreneurial orientation and absorptive capacity have partial mediating effects.

This study focuses on how firms create and share developed knowledge to enable absorptive capacity to fit a level of entrepreneurial orientation. This study validates the vital impact of opportunity recognition as a leading motivation for entrepreneurial orientation. The results highlight an important area of research and suggest that firms should focus on knowledge sharing to boost entrepreneurial outcomes.

The notions of entrepreneurship, absorptive capacity and knowledge sharing are extended by building on dynamic capability theory. Knowledge sharing increases absorptive capacity, which drives superior entrepreneurial orientation outcomes.

This paper aims to increase understanding of pertinent exogenous and endogenous antecedents that can reduce data privacy breaches.

A cross-sectional survey was used to source participants' perceptions of relevant exogenous and endogenous antecedents developed from the Antecedents-Privacy Concerns-Outcomes (APCO) model and Social Cognitive Theory. A research model was proposed and tested with empirical data collected from 213 participants based in Canada.

The exogenous factors of external privacy training and external privacy self-assessment tool significantly and positively impact the study's endogenous factors of individual privacy awareness, organizational resources allocated to privacy concerns, and group behavior concerning privacy laws. Further, the proximal determinants of data privacy breaches (dependent construct) are negatively influenced by individual privacy awareness, group behavior related to privacy laws, and organizational resources allocated to privacy concerns. The endogenous factors fully mediated the relationships between the exogenous factors and the dependent construct.

This study contributes to the budding data privacy breach literature by highlighting the impacts of personal and environmental factors in the discourse.

The results offer management insights on mitigating data privacy breach incidents arising from employees' actions. Roles of external privacy training and privacy self-assessment tools are signified.

Antecedents of data privacy breaches have been underexplored. This paper is among the first to elucidate the roles of select exogenous and endogenous antecedents encompassing personal and environmental imperatives on data privacy breaches.

This study aims to provide a comprehensive analysis of various approaches to the residential property market evolution modelling and to examine the macroeconomic fundamentals that have shaped this market development in Ukraine in recent years.

The study uses a comprehensive data set encompassing relevant macroeconomic indicators and historical apartment prices. Multifactor linear regression (MLR) and ridge regression (RR) models are constructed to identify the impact of multiple predictors on apartment prices. Additionally, the ARIMAX model integrates time series analysis and external factors to enhance modelling and forecasting accuracy.

The investigation reveals that MLR and RR yield accurate predictions by considering a range of influential variables. The hybrid ARIMAX model further enhances predictive performance by fusing external indicators with time series analysis. These findings underscore the effectiveness of a multidimensional approach in capturing the complexity of housing price dynamics.

This research contributes to the real estate modelling and forecasting literature by providing an analysis of multiple linear regression, RR and ARIMAX models within the specific context of property price prediction in the turbulent Ukrainian real estate market. This comprehensive analysis not only offers insights into the performance of these methodologies but also explores their adaptability and robustness in a market characterized by evolving dynamics, including the significant influence of external geopolitical factors.

In the context of investment decisions, the intricate interplay between exogenous shocks and their influence on investor confidence significantly shapes their behaviors and, consequently, their outcomes. Investment decisions are influenced by uncertainties, exogenous shocks as well as the sentiments and confidence of investors, factors typically overlooked by decision-makers. This study will meticulously examine these multifaceted influences and discern their intricate hierarchical nuances in the sentiments of industrial entrepreneurs during the COVID-19 pandemic.

Employing the robust framework of the generalized linear latent and mixed models (GLLAMM), this research will thoroughly investigate individual and group idiosyncrasies present in diverse data compilations. Additionally, it will delve deeply into the exogeneity of disturbances across different sectors and regions.

Relevant insights gleaned from this research elucidate the adverse influence of exogenous forces, including pandemics and financial crises, on the confidence of industrial entrepreneurs. Furthermore, a significant discovery emerges in the regional analysis, revealing a notable homogeneity in the propagation patterns of industrial entrepreneurs' perceptions within the sectoral and regional context. This finding suggests a mitigation of regional effects in situations of global exogenous shocks.

Within the realm of academic inquiry, this study offers an innovative perspective in unveiling the intricate interaction between external shocks and their significant impacts on the sentiment of industrial entrepreneurs. Furthermore, the utilization of the robust GLLAMM captures the hierarchical dimension of this relationship, enhancing the precision of analyses. This approach provides a significant impetus for data-informed strategic directions.

This study delves into the transformation of UAE-Israel relations, which transitioned from a long-term rivalry to a formal peace agreement in 2020. It aims to uncover the multifaceted elements that influenced both nations’ pursuit of bilateral negotiations, with a special emphasis on the role of unofficial collaboration.

Employing a case study approach, the research traces the evolution of the UAE-Israel ties, mapping their progression from covert collaborations to public accords. This exploration is set against a backdrop of political, economic, and societal factors that have historically characterized the broader Israel-Arab conflict. Real-world dynamics and theoretical constructs are analyzed in tandem to derive comprehensive insights.

Key drivers for the transformation of UAE-Israel relations included the threat from Iran, internal disturbances, economic stresses, and the strategic advantages of discreet diplomacy. Exogenous catalysts like the Covid-19 pandemic and Israel's annexation plans in 2019-2020 played pivotal roles, capitalizing on pre-existing covert collaborations and shared regional interests. Constructive strategies, notably inducements, effectively reshaped their adversarial relationship. The resultant U.S.-mediated agreement conferred strategic, security, economic, and diplomatic benefits to both parties. Importantly, the potency of conengagement conflict management strategy, especially when bolstered by exogenous factors and growing mutual interest, emerged as a game-changer in terminating longstanding rivalries.

This study offers a unique perspective on Israel-UAE relations, emphasizing the significance of covert engagements, inducements, and the innovative conengagement strategy in conflict resolution. By examining a relationship devoid of direct armed conflict, the research underscores the interplay of economic, political, and societal factors in reshaping rivalries. This case study serves as a testament to the potential for transformative change in enduring disputes when the right conditions and strategies align, supplementing conventional perspectives and offering valuable implications for policy and mediation initiatives in the Middle East.

In an effort to position higher education institutions to survive in this fiercely competitive environment, the paper aims to identify the direct and indirect relationships between higher education institutional positioning and exogenous factors (student engagement, employability, technology adaptation, teaching quality, and moral values).

A cross-sectional data was collected from 1,015 students studying in the pre-final year of graduation or post-graduate course/program from various educational institutions that were shortlisted based on the Indian NAAC and NIRF rankings. Thereafter, robust assessment criteria of PLS-SEM were used for model assessment and computation of results.

The findings revealed that to develop the greatest platform for upcoming young talent, higher educational institutional positioning ought to be addressed as a priority, which in turn will result in better living standards for upcoming generations.

Framing strategies for urban students can never match those living in rural areas, as they are deprived of money due to their level of upbringing from childhood, which creates a high difference in the psychological mindset of students while choosing a career path.

The higher positioning of educational institutions clearly reflects the authentic learning environment, with professionalism leading to better student engagement with best industry practice.

Research novelty is highlighted as a more focused and streamlined approach to students’ career development and institution branding by reanalyzing and grouping various concepts of institutional positioning into a single model.

The purpose of this study is to examine the impact of the shift towards a circular economy and marketing strategies on the collaborative purchasing behaviour of consumers in India. The study uses the theory of planned behaviour (TPB) and the marketing mix to understand the factors affecting a consumer’s intention to participate in collaborative consumption (CC).

A Web-based survey was conducted, and 349 valid responses were analysed using AMOS (Analysis of Moment Structures) structural equation modelling. The study emphasised the impact of price, promotion and perceived behaviour control on CC and provided direction and advice for companies that rent and swap apparel.

According to the study, promotion and perceived behaviour control are the two key characteristics that significantly impact a consumer’s willingness to participate in CC in India. The study also found that perceived behaviour control plays a significant direct role in behavioural usage. These findings emphasise the impact of price, promotion and perceived behaviour control on CC and offer direction and advice for companies that rent and swap apparel.

This article can be used to evaluate the business in different countries and can be developed further. It does, however, have some restrictions. Because most respondents are from northern and central India, in addition, some respondents are from the southwestern and southern regions, especially in the Mumbai and Chennai locales. Hence, the geographical sample was not diverse in terms of demographics. Furthermore, the gender identity of the respondents might essentially affect how the authors interpret customer buying behaviour, but the study missed this. Researchers could enhance this by using various sampling techniques and ensuring that other demographic characteristics are considered in the future. Furthermore, the survey could not distinguish between online and in-person transactions.

The study provides practical advice for companies that rent and swap apparel, emphasising the impact of price, promotion and perceived behaviour control on consumer willingness to participate in CC. The findings suggest that companies can improve consumer participation by focusing on promotion and perceived behaviour control. In addition, the significance of perceived behaviour control on behavioural usage highlights the importance of empowering consumers to control their decisions to participate in CC.

To the best of the authors’ knowledge, this study is one of the first to examine the factors influencing consumer willingness to participate in CC in the context of the shift towards a circular economy in India. By examining the impact of the TPB and the marketing mix on consumer intention, the study provides valuable insights for companies that rent and swap apparel. The findings highlight the importance of promotion and perceived behaviour control in shaping consumer behaviour and provide practical direction for companies to promote and market their products effectively. The study adds to the existing knowledge on the circular economy and the role of CC in reducing waste and promoting sustainability.