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This study aims to examine whether two periods of extreme market conditions – the governance crisis and Sarbanes-Oxley Act regulatory shock of 2002 and the 2007–2008 global financial crisis – incrementally impacted the self-fulfilling prophecy effect, by examining the propensity of US firms receiving going concern modification (GCM) opinions to go bankrupt relative to their non-GCM distress risk-matched counterparts during these two crisis periods.

To assess the potential influence of the governance/regulatory shock of 2002 and the global financial crisis moderate or mitigate the self-fulfilling prophecy effect, the authors use multivariate logit analysis, regressing t + 1 bankruptcy status on time t GCM and other bankruptcy determinants, interacting crisis period dummies with the GCM variable.

GCM firms were more likely to declare bankruptcy than their distressed non-GCM counterparts, confirming prior research documenting the existence of a self-fulfilling prophecy effect. The authors also find that the self-fulfilling prophecy effect was exacerbated by the governance crisis/Sarbanes-Oxley Act regulatory shock, but not the global financial crisis, a financial/banking sector shock.

This study contributes to the financial crisis and auditing literatures by examining whether exogenous shocks exacerbate the self-fulfilling prophecy effect. The present analysis and findings have implications for future academic research related to systemic shocks and for auditors in documenting the inducement effect arising from the issuance of GCMs during crisis periods.

The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

The author identifies the traits of consumer resilience in emerging markets, classifies these major traits into five categories and analyses the influence relationships among them with distinctive focus on the psychological and personal resilience aspects.

The influence relations among the traits of consumer resilience from an expert perspective were identified with typical focus on electronic supply chains, and later the same was analysed through an intelligent influence modelling method, the grey causal modelling (GCM).

The major traits were analysed using the GCM, where the cause–consequence relations were observed for various objectives and the situational effects are noted. By constructing a magnitude plot and further a causal magnitude table, the important influence traits of consumer resilience for the considered case were observed and the same were auxiliary validated using an interpretive structural modelling (ISM) based approach.

As perceived from the results, it is evident that social support and recommendations from customers emerge as the principal influence traits of consumer resilience from an expert perspective, considering the case. The study can be further extended empirically to validate the findings.

Altogether, the author can recommend for practitioners that the influence of family, society, friends, peers as well as ratings from the customers can determine the level of consumer resilience. Hence, practitioners of customer relationship management can focus on improving the product and brand awareness among customers, so that more customers may recommend for typical products.

Consumer resilience depend on several factors, where the author has identified 25 major traits of the same and classified them into five major categories, including individual psychological factors, individual attitudes, individual socio demographic factors, micro environmental factors and macro environmental factors and the influence relations among them were studied from an expert perspective.

The researchers aim to investigate the role of psychological capital (PsyCap) in facilitating intrinsic motivation and goal-commitment among employees at the workplace, affecting outcome variables, namely, in-role and extra-role job performance.

Data were collected from 640 employees working in the information technology sector of India. Covariance-based structural equation modeling (CB-SEM) was used to test the hypothesized relationships.

Analysis revealed a significant positive impact of PsyCap on the two behavioral facets of job performance. Intrinsic motivation and goal-commitment were found mediating the influence of PsyCap on the two facets of job performance.

The information technology sector is characterised by continuous change. It requires voluntary prosocial behavior from employees, where the employees are expected to display multifaceted job performance behaviors, where they go beyond their job duties to cater for the dynamics of the IT sector. The present study provides means by which intrinsic motivated and goal-committed behavior are facilitated for both the in-role and extra-role job performance.

The present study is among the few preliminary studies that have provided evidence that intrinsic motivation and goal-commitment are the two variables which aid PsyCap in predicting both the prescribed and voluntary job performance behaviors.

The study aims to highlight the barriers faced by the entrepreneurs toward achieving sustainability in business and innovation cultivation by offering solutions for academicians, practitioners and policymakers. The study uses the resource-based view (RBV) theory to discuss how an organization’s resources and capabilities influence the competitive ambience and barriers faced by entrepreneurs.

The present research uses grey-causal modelling (GSC) to analyse the barriers against successful entrepreneurship.

The research focuses on the usefulness of dynamic capabilities, managing and cooperating resources in the entrepreneurship setting. The paper highlights the importance of resource gathering and nurturing as a method to combat scarcity. This research further identifies that financial limitations, regulatory obstacles, challenges to sourcing qualified labour, poor infrastructure and technology, limited mentorship opportunities, lack of scalability, low initial cost barriers in product development and risk-averse attitudes are the major factors hindering entrepreneurs from obtaining sustainable business and innovation.

The contribution of this research to the literature is that it assesses RBV theory within the realm of entrepreneurship, providing a different perspective on resources and capabilities as well as the challenges faced by entrepreneurs. The systematic approach to the analysis and prioritization of various barriers is innovative, and it adds knowledge in this area.

There is a wealth of literature on the financing structure of a company. For this reason, the authors considered it useful to present a theoretical and empirical literature review of classical and new theories of the financial structure. The purpose of this study is to realize on a panel of 15 nonfinancial Moroccan companies listed on the Casablanca Stock Exchange, over a period of 11 years.

The results obtained indicate that only a few variables from financial theory have an important role in the financing policy of Moroccan companies. The authors have presented the positive role of size and self-financing on the debt ratio. The analysis of the effects of profitability shows in this study that it is negative related on the debt ratio which asserts the predictions of the pecking order theory. Also, the age of the company and the growth opportunities explain the level of indebtedness.

Econometric analysis is used to ascertain the nature of the financial structure of listed companies. For this purpose, a large number of companies listed on the Casablanca stock exchange were used.

The authors have presented the positive role of size and self-financing on the debt ratio. Regarding the influence of profitability, this analysis shows that it is negative related on the debt ratio which asserts the predictions of the pecking order theory. Also, the age of the company and the growth opportunities explain the level of indebtedness.

The study aims to work on two objectives, first to provide a theoretical foundation along with ongoing trend in the field of green human resource management (GHRM) and employee green creativity (EGC) in the hospitality and tourism industry. Second, the study also proposes a conceptual research model to understand the dynamics of the relationship between GHRM and EGC for future studies.

The study uses multi-method approach, systematic literature review and bibliometric analysis is performed on published work on GHRM and EGC. This study initially shortlisted 52 publications from multiple databases, which was refined to 11 Scopus-indexed papers, which discussed both GHRM and EGC attributes in a hospitality context. VOSviewer and advance excel software's are being used to perform the analysis.

The systematic literature review concluded that very limited studies have been conducted on GHRM and EGC in the hospitality context and it has recently gained prominence during the covid pandemic. While bibliometric analysis also identified h-index authors with their co-authorship network, citations and keywords matrix and the changing trends in the domain of GHRM and EGC in hospitality and tourism industry. The analysis also highlights the individual and organisational factors influencing the relation between GHRM and EGC.

This study is the first to conduct a systematic literature review and bibliometric analysis on GHRM and EGC in hospitality and tourism sector. Moreover the paper also provides researchers with an in-depth summary of the available literature and a blue print for future studies on GHRM and EGC.

The author explores the challenges to implementation of Industry 5.0 in the manufacturing sector, considering the developing economy context and studying the causal relationships among factors using an advanced causal modelling technique, the Grey Influence Analysis (GINA). The challenges were further classified based on importance and their influencing power.

The author uses the novel causal modelling technique of GINA to study and understand the influence relations among the challenges to implementation of Industry 5.0.

Based on the results from the expert response-based study in the Indian manufacturing industry, it is seen that the Regulatory challenges (RGC) appear to be the most important challenge that needs to be tackled first, while implementing Industry 5.0. Integration with existing systems and Ethical challenges (ETC) emerge as the second and third most important in the category of challenges, as per the results from the GINA analysis.

The RGC and the ETC need to be addressed prior to implementation and it is necessary to check whether the technologies comply with regulations and whether it creates serious job displacements. While implementation, the challenges with integration to existing systems can be appropriately tackled.

As a practical implication of the study, the author suggests that a proactive and reactive approach can be adopted to implement the Industry 5.0 concepts to reality. The RGC can be viewed for the adoption of technology, integration challenges can be viewed by understanding the existing systems, and ETC can be addressed by understanding the workforce in combination with technologies.

The shift in focus on sustainability and resilience has transformed the conventional industries to think beyond efficiency and productivity, toward being more responsible to society. The study analyzes the challenges to implementation of Industry 5.0 and the causal relations among them considering an expert response-based study.

The choice of crops to produce at a location depends to a large degree on the climate. As the climate changes and food demand evolves, farmers may need to produce a different mix of crops. This study assesses how much cropland may be subject to such upheavals at the global scale, and then focuses on China as a case study to examine how spatial heterogeneity informs different contexts for adaptation within a country.

A global agricultural economic model is linked to a cropland allocation algorithm to generate maps of cropland distribution under historical and future conditions. The mix of crops at each location is examined to determine whether it is likely to experience a major shift.

Two-thirds of rainfed cropland and half of irrigated cropland are likely to experience substantial upheaval of some kind.

This analysis helps establish a global context for the local changes that producers might face under future climate and socioeconomic changes. The scale of the challenge means that the agricultural sector needs to prepare for these widespread and diverse upheavals.