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In order to avoid enterprise crisis and cause the domino effect, which influences the investment return of investors, the national economy, and financial crisis, establishing a complete set of feasible financial early warning model can help to prevent the possibility of enterprise crisis in advance, and thus, reduce the influence on society and the economy. The purpose of this paper is to develop an efficient financial crisis warning model.

First, the fruit fly optimization algorithm (FOA) is used to adjust the coefficients of the parameters in the ZSCORE model (we call it the FOA_ZSCORE model), and the difference between the forecasted value and the real target value is calculated. Afterward, the generalized regressive neural network (GRNN model), with optimized spread by FOA (we call it FOA_GRNN model), is used to forecast the difference to promote the forecasting accuracy. Various models, including ZSCORE, FOA_ZSCORE, FOA_ZSCORE+GRNN, and FOA_ZSCORE+FOA_GRNN, are trained and tested. Finally, different models are compared based on their prediction accuracies and ROC curves. Furthermore, more appropriate parameters, which are different from the parameters in the original ZSCORE model, are selected by using the multivariate adaptive regression splines (MARS) method.

The hybrid model of the FOA_ZSCORE together with the FOA_GRNN offers the highest prediction accuracy, compared to other models; the MARS can be used to select more appropriate parameters to further improve the performance of the prediction models.

This paper proposes a hybrid model, FOA_ZSCORE+FOA_GRNN which offers better performance than the original ZSCORE model.

The aim of this study is to explore which factors of entrepreneurship and innovation influence economic development under the quadruple helix model, contrasting Southern and Northern Europe.

In this study, secondary data are collected from the Global Entrepreneurship Monitor databases, Organization for Economic Co-operation and Development and Global Competitiveness Index, for four countries in the North and four Southern European countries, for the period from 2007 to 2015. Data was analyzed with SPSS 22.0 software and subjected to several multivariate statistical tests.

The results show a statistically significant difference in the variables of the four quadruple helix model dimensions. This means that Northern European countries (Finland, the Netherlands, Norway and Sweden) display better results on innovation and entrepreneurship than Southern European countries (Spain, Greece, Italy and Portugal). The results also showed that per capita gross domestic expenditure on R&D is positively related to government and university dimensions, with significant differences between Southern and Northern European countries.

It is hoped that this study will contribute to new evidence on the factors of innovation and entrepreneurship that are decisive for economic development. To the traditional quadruple helix model, control variables were added to meet the endogenous characteristics of the countries.

This study aims to examine the effect of gender equality on financial stability and financial inclusion for 14 developing countries using yearly data from 2005 to 2021.

The two-stage least squares regression estimation and the generalized linear model regression estimation were used to investigate the effect of gender equality on financial stability and financial inclusion.

Gender equality has a significant positive effect on financial stability and financial inclusion in developing countries. Gender equality has a significant positive effect on financial stability and financial inclusion in African countries. Gender equality has a significant positive effect on financial stability but not on financial inclusion in non-African countries.

Little attention has been paid to the role of gender equality in promoting financial stability and financial inclusion. The authors address this issue in this study.

The purpose of this paper is to investigate whether and how banks’ financial constraints affect their cash tax avoidance. The authors hypothesize that banks engage in more tax planning to generate additional cash to mitigate their financial constraints.

The authors use a sample of US banks to conduct the panel regression analysis. The authors measure the bank tax avoidance using the cash effective tax rate and measure the bank financial constraints using the Z-score and annual payout ratio. The authors further use the implementation of the Dodd–Frank Act as a quasi-natural experiment to conduct the difference-in-difference analysis.

The authors document that financially constrained banks exhibit lower cash effective tax rates. The authors further show that banks facing greater financial constraints are less likely to pursue tax-saving activities following the Dodd–Frank Act. Moreover, the authors find that non-performing loans increase the influence of financial constraints on tax avoidance, while a financial crisis amplifies the impact of financial constraints on bank cash tax savings.

By extending previous research on financial constraints and tax planning, this paper is the first study to recognize financial constraints, along with the Dodd–Frank Act, as determinants of banks’ tax avoidance. This study informs policymakers about the regulation of tax avoidance in the banking industry and sheds light on possible future research on banks’ tax-planning strategies.

Purpose – This study examines how managerial ability relates to employee productivity using a broad and generalized sample of US firms.

Methodology – This study employs a generalized sample of firm-years from all industries between 1980 and 2013.

Findings – By contending that managers differ in their ability to synchronize management processes and human capital in ways that enhance employee productivity, the authors provide evidence showing that more-able managers are associated with higher employee productivity. In addition, the authors find that high-ability managers moderate the negative relation between uncertain environments (high-technology firms) and employee productivity. Furthermore, the authors decompose employee productivity into employee efficiency components and employee cost components. The authors find a significant positive association between managerial ability and the employee efficiency component, but do not see a significant association between managerial ability and the employee cost component.

Value – The results contribute to the understanding of employee productivity by showing the relation between managerial ability and employee productivity.

This study aims to empirically investigate the impact of political instability on the banking stability of the dual banking system in the Middle East and North African (MENA) countries.

The study measures banking stability with probability of default (PD) and Zscore by employing the generalised method of moment (GMM) between 2007 and 2021 on the dual banking system in the region. The authors further estimate short-long-run situations coupled with a robustness test using a generalised least square (GLS) model.

The authors' findings indicate that institutional factors of political stability, crisis period, high-crisis countries, law and order and macroeconomic indicators influence the two types of banking stability in the region. The authors found the consistency of the factors explaining stability in the region in both short-and long-run situations. Consequently, the study also reveals the adverse effects of crisis periods and high-crisis countries on banking stability.

The results of this study explicitly identify the critical need for sustaining political stability and abiding by laws and order to achieve dual banking stability in the region. Therefore, policymakers may consider allowing the region's banks to operate beyond retail banking since diversification enhances banking stability.

The authors' study balances by employing dual stability measurement in predicting the impact of political instability, law and order and other indicators on the MENA region's two banking models. This study uncovers the effect of the global crisis period on banking stability and high-crisis countries in the region and verifies the models' robustness.

This paper aims to examine whether high levels of financial inclusion is associated with greater financial risk.

The study uses regression methodology to estimate the effect of financial inclusion on financial risk.

The findings reveal that higher account ownership is associated with greater financial risk through high non-performing loans and high-cost inefficiency in the financial sector of developed countries, advanced countries and transition economies. Increased use of debit cards, credit cards and digital finance products reduced risk in the financial sector of advanced countries and developed countries but not for transition economies and developing countries. The findings also show that the combined use of digital finance products with increased formal account ownership improves financial sector efficiency in developing countries while the combined use of credit cards with increased formal account ownership reduces insolvency risk and improves financial sector efficiency in developing countries.

The paper offers several implications for policy and financial regulation. It suggests policies that would reduce the financial risk that financial inclusion poses to the financial sector.

The recent interest in financial inclusion and the unintended consequences of policy-driven financial inclusion in some parts of the world is raising concern about the risks that financial inclusion may introduce to the formal financial sector. Little is known about the risks that financial inclusion may pose to the financial sector.

The purpose of this paper is to describe a study which examined the effects of underwriter reputation market segments on the value relevance of firm specific risk measures in the pricing of initial public offerings (IPOs).

The study abandons the notion of a homogenous market for IPOs and focuses instead on the differential demand for information across identifiable segments of the IPO market in the pre‐market offering period leading to the first day trading closing prices. Ordinary least square (OLS) regressions were used to test the two hypotheses developed in the paper.

It was found that firm‐specific risk measures are associated with the initial trading day returns of IPOs managed by low reputation underwriters, but not those by high reputation underwriters. However, as expected, these risk measures are impounded in initial trading day returns only for a sub‐sample of high‐risk junk IPOs that were marked down in price by the underwriter prior to the offering in order to make them more attractive to investors.

As with all empirical studies the tests are joint tests of the hypotheses stipulated and econometric assumptions underlying OLS. The findings of the study may not be generalized to an unrelated domain.

The findings suggest that ex ante risk measures are useful in picking among junk IPOs those with the best chances of survival, and thus earning an initial trading return on those IPOs.

This is the first study to look at junk IPOs in a systematic manner using a quasi‐experimental design.

Conflicting results have emerged from several past studies as to whether bankruptcy prediction models are able to forecast corporate failure more accurately than auditors’ going‐concern opinions. Nevertheless, the last decade has seen improved modelling of the path‐to‐failure of financially distressed firms over earlier static models of bankruptcy. In the light of the current crisis facing the auditing profession, this study evaluates the efficacy of auditors’ going‐concern opinions in comparison to two bankruptcy prediction models. Bankrupt firms in the U.S. service and trade industry sectors were used to compare model predictions against the auditors’ going‐concern opinion for two years prior to firm failure. The two models are the well‐known Altman (1968) Multiple Discriminant Analysis (MDA) model that includes only financial ratio variables in its formulation and the newer, temporal logit model of Cybinski (2000, 2003) that includes explicit factors of the business cycles in addition to variables internal to the firm. The results show overall better bankruptcy classification rates for the temporal model than for the Altman model or audit opinion.

This paper investigated whether a bank’s popularity and depositors' fear of Google search volume could affect bank deposits and credit.

The authors used two different quarterly data from Google Trends and banking data from 2012 Q1 to 2020 Q1. Based on available data, Google Trends data start from 2012. The authors exclude data after 2020 Q1 because the Covid-19 pandemic arguably increased the volume of Internet users due to shifting behavior to online activities. They merged and cleaned the data by winsorizing at 5 and 95 percentiles to avoid any outlier problems, reaching 74 banks in the sample. They used panel data estimation of quarterly data following Levy-Yeyati et al. (2010) and Trinugroho et al. (2020).

The results show that a higher search volume of a bank’s name leads to higher deposits. A higher search volume of depositor fear reduces deposits and credit. The authors also found that banks with high risk and a high search volume of their name have a significantly lower volume of deposits.

To the best of the authors’ knowledge, not many papers in banking and finance have used Google Trends data to gauge related issues regarding depositors' behavior. The authors have filled a gap in the literature by investigating whether the popularity of Google search and depositors' fear could impact deposits and credit. This study also attempted to establish whether Google Trends data could be a reliable source of information to predict depositors' behavior by using a Zscore to measure bank risk.