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The purpose of this study is to analyze the effect of off-balance sheet activities on the credit risk of African banks.

The theory about the relationship between off-balance sheet activities and bank risk was used to construct a conceptual model of the effect of off-balance sheet on credit risk in an African context. The accounting approach is chosen by collecting accounting data extracted from the annual reports of 24 private and conventional African banks during the period 2010–2019. Both statistical and empirical studies are conducted. The statistical study aims to give a description of sample banks in terms of off-balance sheet activities and key financial indicators. The empirical study has the goal of exploring the correlations between, on the one hand, credit risk and, on the other hand, off-balance sheet ratio and control variables (bank- and country-specific variables). This study is based on dynamic panels using the two-step generalized method of moments technique to estimate regressions between credit risk and the explanatory variables.

The statistical study reveals that sample banks use moderately off-balance sheet activities; most of them use essentially guarantees and letters of credit, have satisfactory financial indicators and are slightly exposed to credit risk. The empirical results from the two-step generalized method of moments technique disclose that off-balance sheet activities have an intensifying effect on the credit risk of African banks. However, the increasing effect can be minimized when African banks use moderately off-balance sheet activities.

Using judiciously off-balance sheet activities does not exacerbate the exposure of African banks to credit risk. Therefore, managers of African banks are recommended to maintain a moderate level of off-balance sheet activities, especially guarantees and letters of credit.

The findings of this study eliminate the opacity about the effect of off-balance sheet activities on credit risk. Moreover, this study fulfills the huge gap in the related literature by completing the scarcity of recent studies, considering all items of the off-balance sheet, focusing on the African context, describing off-balance sheet activities and financial indicators of sample banks due to a statistical study and estimating regressions of dynamic panels between credit risk and both bank-specific and country-specific variables due to a two-step generalized method of moments technique.

The study aims to investigate the presence of herding behavior in the stock market of UK with a special emphasis on news sentiment regarding the economy. The authors focus on the news sentiment because in the current digital era, investors take their decision making on the basis of current trends projected by news and media platforms.

For empirical modeling, the authors use machine learning models to investigate the presence of herding behavior in UK stock market for the period starting from 2006 to 2021. The authors use support vector regression, single layer neural network and multilayer neural network models to predict the herding behavior in the stock market of the UK. The authors estimate the herding coefficients using all the models and compare the findings with the linear regression model.

The results show a strong evidence of herding behavior in the stock market of the UK during different time regimes. Furthermore, when the authors incorporate the economic uncertainty news sentiment in the model, the results show a significant improvement. The results of support vector regression, single layer perceptron and multilayer perceptron model show the evidence of herding behavior in UK stock market during global financial crises of 2007–08 and COVID’19 period. In addition, the authors compare the findings with the linear regression which provides no evidence of herding behavior in all the regimes except COVID’19. The results also provide deep insights for both individual investors and policy makers to construct efficient portfolios and avoid market crashes, respectively.

In the existing literature of herding behavior, news sentiment regarding economic uncertainty has not been used before. However, in the present era this parameter is quite critical in context of market anomalies hence and needs to be investigated. In addition, the literature exhibits varying results about the existence of herding behavior when different methodologies are used. In this context, the use of machine learning models is quite rare in the herding literature. The machine learning models are quite robust and provide accurate results. Therefore, this research study uses three different models, i.e. single layer perceptron model, multilayer perceptron model and support vector regression model to investigate the herding behavior in the stock market of the UK. A comparative analysis is also presented among the results of all the models. The study sheds light on the importance of economic uncertainty news sentiment to predict the herding behavior.

The call for supply chain transparency (SCT), especially the environmental, social and governance (ESG) aspect, is getting increasingly louder. Based on the signaling theory, our study investigates the operational benefit of supply chain transparency in terms of ESG (SCT-ESG). To further clarify the signaling process, the moderating roles of digitalization of the firm and signal strength are also examined.

Longitudinal secondary data from multiple databases are matched and analyzed using ordinary least squares (OLS) regressions to validate the proposed hypotheses.

Results suggest that with SCT-ESG, firms have a weakened disparity between production variance and demand variance, and the supply chain experiences a reduced bullwhip effect. Further, digitalization of the focal company and signal strength reinforce the negative effect of SCT-ESG on the bullwhip effect.

The study integrates the SCT and ESG literature through SCT-ESG, extending benefits of ESG disclosure to the supply chain context. It extends the application of the signaling theory in OSCM by including contextual factors of digitalization and signal strength.

Policymakers are developing government-level pandemic response strategies (GPRS) to assist architecture, engineering and construction (AEC) enterprises. However, the effectiveness of the GPRS has not been assessed. Therefore, this study aims to investigate the interrelationships between GPRS and AEC enterprises. To achieve that aim, the study objectives are to compare GPRS effectiveness between small-medium and large AEC enterprises, develop groupings to categorize interrelated GPRS and evaluate the effectiveness of the GPRS and interrelated constructs.

A systematic literature review and semi-structured interviews with 40 AEC industry professionals were carried out, generating 22 GPRS. Then, questionnaire survey data was collected among AEC professionals. In total, 114 valid survey answers were received and analyzed using the Kruskal–Wallis H test, normalized mean analysis, factor analysis and fuzzy synthetic evaluation.

Small-medium enterprises have four distinct critical GPRS: “form a special task force to provide support in maneuvering COVID-19,” “provide infrastructure investment budgets to local governments,” “develop employee assistance programs that fit all types of working groups” and “diversify existing supply chain.” Large enterprises have two distinct critical GPRS: “provide help in digitalizing existing construction projects” and “mandate COVID-19 as force majeure.” Eighteen GPRS can be categorized into the following five constructs: “market stability and financial aid,” “enterprise capability management,” “supply chain improvement,” “law and policy resources” and “information and workforce management.” The former two constructs are more effective than other GPRS constructs.

This is the first paper that evaluates the effectiveness of GPRS for AEC enterprises, providing new evidence to policymakers for well-informed decision-making in developing pandemic response strategies.

This paper aims to examine the effect of critical mass of women managers on corporate boards on the voluntary disclosure of climate change in a developing country in which the regulations on climate change disclosure is an area of growing research interest.

This study uses logistic panel regression models with a sample of 1,001 firm-years for companies in the Borsa Istanbul 100 Index that were asked to disclose voluntary climate change indicators over the seven-year period from 2014 to 2020 through the Carbon Disclosure Project.

This paper provides evidence from an emerging country that the critical mass of women on the board has no impact on voluntary climate change disclosure. In addition, the presence of independent managers on the board was found to have a significant impact on climate change disclosure. In addition, the results show that larger companies are more likely to report their climate change activities. Large companies are more visible due to their size, are perceived by stakeholders as more polluting and are, therefore, more likely to report on the environment.

The results show that the critical mass of women on the board has no effect on voluntary disclosure of climate change. Empirical tests are still needed to strengthen the overall validity of the critical mass of at least three women on boards in Türkiye.

Despite many valuable insights provided by critical mass theory, very few studies directly address critical mass and voluntary disclosure of climate change. To the best of the authors’ knowledge, this study is the first empirical and comprehensive paper in the Turkish context evaluating critical masses and voluntary corporate climate change giving a comparison between firms listed on financial industry and nonfinancial industry.

This study aims to investigate the impact of board skill diversity (BSD) on corporate environmental responsibility (CER). In addition, this study explores the moderating effects of formal regulatory pressure and informal media pressure.

This study uses Chinese high polluting companies as the sample and uses regression analysis. Robustness checks, including instrumental variable regression, Heckman two-stage model and propensity score matching method, are performed to test the robustness of the results.

The findings suggest that BSD significantly improves CER performance. Both formal regulatory pressure and informal media pressure strengthen the positive impact of BSD on CER. Further channel analyses reveal that BSD improves CER performance by promoting corporate proenvironmental behaviors rather than by restricting environmental violations; skill diversity of executive directors has a more significant effect on CER than that of independent directors. Finally, the moderating effect of regulatory pressure is only significant after the implementation of the Environmental Protection Law, and the moderating effect of media pressure mainly concentrates on negative media coverage.

The involvement of directors with more diverse skills is essential to improve corporate proenvironmental behaviors. Companies should select qualified directors with different skills to further improve their performance on environmental protection and sustainable development.

Regulators and standard-setters should develop efficient guidelines on corporate board governance to enhance the positive role of companies in environmental and sustainable development.

This study broadens the research on the determinants of CER by examining the influence of BSD on CER and the moderating roles of various stakeholder pressures, thereby providing a deeper understanding of corporate environmental performance and sustainable development.

Face is the most intuitive and representative feature at the individual level. Many studies show that beautiful faces help individuals and enterprises obtain economic benefits and form a high economic premium, but the discussion of their potential social value is insufficient. This study aims to focus on the impact of the personal characteristics of executives. It mainly analyzes the impact mechanism of CEO facial attractiveness on corporate social responsibility (CSR) decision-making, clarifying the social value of beauty from the perspective of CSR.

The authors use the regression model to analyze the panel data set, which was conducted by a sample of Chinese publicly listed firms from 2016 to 2018.

The study found that CEOs with high facial attractiveness are more active in fulfilling CSR, which can usually bring higher social benefits. CEOs with beautiful faces are prone to overconfidence, are optimistic about their ability and the future development of the enterprise and are more willing to increase their investment in CSR. CEO duality can positively regulate the positive correlation between a CEO’s facial attractiveness and CSR.

Based on the perspective of upper echelons theory, this paper explores the mechanism of CEO facial attractiveness on CSR. This study enriches the perspective of the upper echelon’s theoretical research and has essential enlightenment for CEO selection and training practice.

The case was developed from secondary sources and interviews with a security analyst. The secondary sources include company annual reports, news reports, analyst reports, industry reports, company websites, stock exchange websites and databases such as Bloomberg and CMIE Prowess.

Increasing competition in product and capital markets has put tremendous pressure on managers to become more cost competitive. To address their firms' uncompetitive cost structures, managers may have to consider dramatic restructuring of their businesses. During 2014–2017, Tata Steel Ltd (TSL) UK considered a series of divestitures and a merger plan to nurse the company back to health. The case considers the economics of the restructuring plan. The case is designed to help students analyze a corporate downsizing program undertaken by a large Indian company in the UK and to highlight the dynamic role of the CFO and governance issues in family firms. It introduces students to issues surrounding a typical restructuring and provides students a platform to practice the estimation of value creation in a restructuring exercise. While some cases on corporate restructuring in the context of developed economies are available, there are very few cases written in an emerging market context. This case bridges that gap. TSL presents a unique opportunity to study corporate restructuring necessitated by a failed cross-border acquisition. It illustrates the potential for value loss in large, cross-border acquisitions. It shows how managerial hubris can prompt family firm owners to overbid in acquisitions and create legacy hot spots. In addition, the case can be used to discuss the causes of governance failures such as weak institutional monitoring and poor legal enforcement in emerging markets that could potentially harm minority shareholders.

The case was developed from secondary sources and interviews with a security analyst. The secondary sources include company annual reports, news reports, analyst reports, industry reports, company websites, stock exchange websites and databases such as Bloomberg and CMIE Prowess.

This paper aims to examine the question, “How do firm-level, home-country and host-country environmental performance (EP) affect the outward foreign direct investment (OFDI) of Chinese multinational enterprises (MNEs)?”

The authors examine the relationships between EP and OFDI propensity and between EP and OFDI intensity using a sample of 359 Chinese firms in industries with a significant environmental footprint between 2009 and 2019 (2,002 firm-year observations) and a Heckman two-stage model.

This study shows that the propensity for OFDI by Chinese MNEs is significantly and positively related to the firm’s prior EP and the country-level EP of China. However, the amount of FDI invested is significantly and positively related to the firm’s prior EP and negatively related to the EP of the host country.

The findings suggest that FDI in a country by an MNE is determined by a combination of firm-level EP, home-country EP and host-country EP. This study finds that the decision to undertake FDI (propensity) and the decision about how much to invest (intensity) are determined by different factors. The propensity for FDI is determined by the home-country EP and firm-level EP. However, the intensity of FDI is determined by a combination of the host country EP and firm-level EP. A limitation is that this study only examines MNEs in China, so the findings may not apply to other countries.

This paper shows that MNEs’ EP is positively related to the propensity and intensity of their OFDI decisions. However, this paper shows that the home-country and host-country EP may also play an important role in determining the propensity or intensity of OFDI.