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This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

This study explores how auditors' emotions, specifically negative moods triggered by flight delays, impact auditing quality.

Utilizing flight delays during audit assignments as a mood indicator, weather conditions at departure airports serve as an instrumental variable to provide a robustness check between flight delays and audit outcomes, employing a two-stage least squares model.

The findings suggest that such negative moods improve auditing effort and quality, as evidenced by reduced future accounting restatements and increased audit fees. The positive effect of flight delays on auditing quality is consistent across different tests and measures.

This study highlights the significance of auditors' emotional states on their professional performance, indicating a unique angle on auditing quality research by focusing on the emotional well-being of auditors as influenced by external factors such as flight delays.

Information technology as a source of information and decision-making has wider acceptance in contemporary times. Studies have identified the importance of electronic word of mouth (eWOM) and its impact on decision-making. The primary objective of this research is to investigate the relationship between eWOM (pre-travel), destination image (post-visit), tourist satisfaction and eWOM intentions post the COVID-19 crisis. This study is important as it is anticipated that in the post-pandemic world, tourists would seek well-being-enhancing experiences more often than any other form of tourism.

Data were collected through an online questionnaire circulated over a period of six months from November 2020 to April 2021. Non-probability purposive sampling technique was used.

The results depicted that wellness destination’s image has a significant influence on wellness tourists’ satisfaction level and their eWOM intentions. Furthermore, it also came to light that the satisfaction level of wellness tourist satisfaction was found to be significantly influencing their eWOM intentions. The mediating role of wellness tourists’ satisfaction was found to be significant from destination image (post-visit) to eWOM intentions. COVID-19 pandemic perceived health risk was also found to be significantly moderating the relationship between eWOM (pre-travel) and eWOM intentions.

Pre-travel online information about a wellness destination is an important determinant of travel decisions, especially during the COVID-19 crisis. This empirical study proves that effective use of this information can advance a destination’s marketing efforts and ensure future demand.

Literature on the board diversity of Islamic banks (IB) found limited knowledge of the “deep-level” attribute. This study aims to explain the impact of the board diversity attributes (education levels, educational backgrounds and the interactions between these two attributes of diversity) on profitability.

The research sample is 37 fully flagged IBs from five Southeast Asian countries, covering nine years (2010–2019). Data were analyzed using the two-step system generalized moment (2SYS-GMM) method.

We found that the cognitive conflict between the board of directors (BOD) and the Shariah Supervisory Board (SSB), which has heterogeneity in its education level and educational background, positively affects profitability. These results reinforce the resources dependence theory (RDT) approach that having boards with heterogeneous characteristics is beneficial for IB.

The findings of this study would offer useful information for Islamic banking authorities to revise or formulate rules and guidelines and make a greater effort to implement corporate governance (CG) reform measures by determining educational level and background as a requirement to become a member of a BOD or an SSB.

This paper contributes in three ways: (1) we use the “deep-level” diversity attributes of the BOD and the SSB, (2) it focuses on cognitive conflict in boards by presenting the expertise diversity of the BOD and SSB and (3) we interact with the level of education to evaluate the effect of a cognitive conflict.

This hypothetical case study aims to revisit the classical model given by Henri Fayol whereby he put forward a set of 14 principles to guide managers in decision-making across organizations. The case study showcases the dilemma in which the top manager of an automobile company finds himself when some of the very basic principles – on which the whole discipline of management is founded – are ignored. It will also serve as an aid for faculty members in B-Schools to teach students the significance of basic management principles postulated many years back which stand relevant even in contemporary times.

This case study is based on a hypothetical scenario in the corporate world. Different incidents in a fictitious automobile manufacturing firm are presented and the corresponding principles given by Henri Fayol are inferred.

This case study highlights that decision-making gets complicated if fundamental principles of management are not complied with. The decision taken during each and every situation which has been discussed in this case study is contrary to the correct course of action as propounded by Fayol. Modern-day managers must acknowledge the relevance and importance of these principles for achieving success in business.

This case study underscores that even in this volatile business environment where most of the management practices are technology-driven, we cannot disregard the most elementary rules of management. The managers working at different levels in the organizational hierarchy may be guided to make the right decisions in situations similar to the ones described.

This study aims to measure impact of several firm-specific factors on alternative measures of leverage. The authors also aim to study impact of the subprime crisis on such associations.

The authors utilized an unbalanced panel data of 973 firm-year observations on 47 UK listed non-financial firms for the years 1990–2019. Book-based and market-based long-term and total leverage measures have been used as explained variables. The explanatory variables are profitability, size, two measures of growth, asset tangibility, non-debt tax shields, firm age and product uniqueness. Fixed effect and random effect models with clustered robust standard errors have been utilized for data analysis. To find the effect of subprime crisis, original dataset was split to create pre-crisis and post-crisis datasets.

The authors find that profitability significantly reduces leverage while firms having more tangible assets use significantly more debt in capital structure. Firm size and non-debt tax shield have statistically insignificant positive impact on leverage. Having more unique products reduces use of external debt, albeit insignificantly. Growth, when measured as market-to-book ratio, has inconsistent impact, whereas capital expenditure insignificantly reduces leverage. Age is found to be an insignificant predictor of leverage. After the subprime crisis, firms started relying more on internal fund instead of external debt, more particularly short-term debt. Having more collateral is gradually becoming more important for availing external debt.

Data limitations restrict generalization of the findings.

This is one of the pioneering attempts to show how subprime crisis altered the theoretical domain of capital structure research in the UK.

This study specifically seeks to investigate the strategic implementation of machine learning (ML) algorithms and techniques in healthcare institutions to enhance innovation management in healthcare settings.

The papers from 2011 to 2021 were considered following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. First, relevant keywords were identified, and screening was performed. Bibliometric analysis was performed. One hundred twenty-three relevant documents that passed the eligibility criteria were finalized.

Overall, the annual scientific production section results reveal that ML in the healthcare sector is growing significantly. Performing bibliometric analysis has helped find unexplored areas; understand the trend of scientific publication; and categorize topics based on emerging, trending and essential. The paper discovers the influential authors, sources, countries and ML and healthcare management keywords.

The study helps understand various applications of ML in healthcare institutions, such as the use of Internet of Things in healthcare, the prediction of disease, finding the seriousness of a case, natural language processing, speech and language-based classification, etc. This analysis would help future researchers and developers target the healthcare sector areas that are likely to grow in the coming future.

The study highlights the potential for ML to enhance medical support within healthcare institutions. It suggests that regression algorithms are particularly promising for this purpose. Hospital management can leverage time series ML algorithms to estimate the number of incoming patients, thus increasing hospital availability and optimizing resource allocation. ML has been instrumental in the development of these systems. By embracing telemedicine and remote monitoring, healthcare management can facilitate the creation of online patient surveillance and monitoring systems, allowing for early medical intervention and ultimately improving the efficiency and effectiveness of medical services.

By offering a comprehensive panorama of ML's integration within healthcare institutions, this study underscores the pivotal role of innovation management in healthcare. The findings contribute to a holistic understanding of ML's applications in healthcare and emphasize their potential to transform and optimize healthcare delivery.

Monocytes are a leukocytes’ subset that plays an important role in immunity. Protein kinase B (AKT) is involved in monocytes' survival, proliferation and differentiation. Using phorbol 12-myristate 13-acetate (PMA) as an inducer for cell line U937 differentiation into macrophage-like cells may be used as a model for cancer cell therapy or other biomedical research studies. The authors investigated the Akt1 signaling pathway's involvement with PMA as a differentiating agent and survival in the U937 cell line.

PMA was utilized to stimulate the differentiation of the U937 cell line into macrophage-like cells at a concentration of 10 nM. Akt1-phosphorylated Serine 473, Bad-phosphorylated Serine 136 and Caspase9-phosphorylated Serine 196 were tested by flow cytometry for the involvement of the Akt1 signaling pathway during differentiation in addition to the expression of CD14, CD206 and CD83. DNA cell cycle variation analysis was done using PI staining and cell viability and apoptosis detection using Annexin V and PI flow cytometry.

There was a decrease in phosphorylated Akt1 and Bad activation and an increase in Caspase9 activation, with an increase in surface markers CD14, CD206 and CD83 acquired by PMA-differentiated cells. DNA cell cycle analysis revealed cell accumulation in the G2/M phase and fewer cells in the S phase of PMA-induced U937. Apoptosis induction for Ly294002 or Wortmannin-inhibited cells and part of PMA-induced cells were detected.

These results may be used to create a model for biomedical research studies and advance the understanding of the mechanism involving differentiation of the U937 cell line.

This research aims to determine to what extent corporate social responsibility (CSR) actions developed by bank entities in Spain improve the vulnerable customers' emotions and quality perception of the banking service. Consequently, this increases the quality of their relationship regarding satisfaction, trust and engagement.

Data from 734 vulnerable banking customers were analyzed through structural equations modeling (EQS 6.2) to test the relationships of the proposed variables.

Vulnerable customers' emotional disposition exerts a strong influence on their perceived service quality. The antecedent effect is concentrated primarily on the CSR towards the client, with a residual secondary weight on the CSR towards society. These positive service emotions are determinants of the outcome quality perceived by vulnerable customers, directly in terms of higher satisfaction and trust and indirectly through engagement.

This research contributes to understanding how financial service providers should adapt to the specific characteristics and needs of vulnerable clients by adopting a strategy of approach, personalization and humanization of the service that seems to move away from the actions implemented by the banking industry in recent years.

This study has adopted a theoretical and empirical perspective on the impact of CSR on service emotions and outcome quality of vulnerable banking customers. Moreover, banks can adopt a dual conception of CSR: a macro and external scope toward society and a micro and internal scope toward customers.