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The purpose of this study is to examine the relationship between the corporate social responsibility (CSR) performance of job-hopping executives at their former and subsequent firms.

We conduct regression analyses using a sample of firms listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2020 to examine whether CSR performance is similar from one firm to the next as executives switch jobs.

We find a positive relationship between the CSR performance of former and subsequent firms under job-hopping executives. This relationship is the strongest in the year of the job switch; it weakens in the second year and eventually disappears in the third year. In addition, we show that this relationship benefits different CSR stakeholder groups and is contingent on executive and subsequent firm attributes and job-hopping characteristics. Furthermore, we demonstrate that firms that hire a new chief executive officer from a firm with a strong track record in CSR, the new firm experiences a significant surge in CSR performance compared with firms that do not experience such a shock.

This study has implications for executive hiring decisions.

This study extends the understanding of CSR determinants through the lens of inter-organisational ties associated with job-hopping executives.

The early care and education (ECE) workforce plays a pivotal role in shaping early childhood developmental trajectories and simultaneously experiences significant mental health disparities. The purpose of this study is to investigate how social determinants of health and external stressors are associated with the mental health of ECE staff, which represent a low-resourced segment of the workforce; how psychological capital (psycap) can mitigate these associations.

The authors administered an 89-item survey to 332 ECE staff employed in 42 Head Start centers in the USA. The authors ran three hierarchical linear regression models to analyze associations between social determinants of health, external sources of stress, psycap and potential moderation effects and mental health outcomes.

Individuals experiencing greater finance-related stress reported 0.15 higher scores on the depression scale and 0.20 higher scores on the anxiety scale than those experiencing less finance-related stress (p < 0.05). Individuals experiencing greater work-related stress reported 1.26 more days of poorer mental health in the past month than those experiencing less work-related stress (p < 0.01). After controlling for all sociodemographic variables and sources of stress, psycap was significantly and negatively associated with depressive symptomology (b-weight = −0.02, p < 0.01) and the number of poor mental health days reported in the past month (b-weight = −0.13, p < 0.05). Moderation models suggest that higher levels of psycap may mitigate the association between work-related stress and the number of poor mental health days reported in the past month (b-weight = −0.06, p = 0.02).

The implications of these findings suggest a need for policy change to mitigate social determinants of health and promote pay equity and multi-level interventio ns that target workplace-related stressors and psycap to combat poor mental health of the ECE workforce.

The main purpose of this study is to test for the interaction effect of digital literacy in the relationship between financial technologies (FinTechs) of biometrics and mobile money and digital financial inclusion among the unbanked poor women, youth and persons with disabilities (PWDs) in rural Uganda.

Covariance-based structural equation modeling was used to construct the interaction effect using data collected from the unbanked poor women, youth and PWDs located in the four regions in Uganda as prescribed by Hair et al. (2022).

The findings from this study are threefold: first; the results revealed a positive interaction effect of digital literacy between FinTechs of biometrics and mobile money and digital financial inclusion. Second; the results also confirmed that biometrics identification positively promotes digital financial inclusion. Lastly; the results showed that mobile money positively promotes digital financial inclusion. A combination of FinTechs of biometrics and mobile money together with digital literacy explain 29% variation in digital financial inclusion among the unbanked poor women, youth and PWDs in rural Uganda.

The data for this study were collected mainly from the unbanked poor women, youth and PWDs. Further studies may look at data from other sections of the vulnerable population in under developed financial markets. Additionally, the data for this study were collected only from Uganda as a developing country. Thus, more data may be obtained from other developing countries to draw conclusive and generalized empirical evidence. Besides, the current study used cross sectional design to collect the data. Therefore, future studies may adopt longitudinal research design to investigate the impact of FinTechs on digital financial inclusion in the presence of digital literacy across different time range.

The governments in developing countries like Uganda should support women, youth, PWDs and other equally vulnerable groups, especially in the rural communities to understand and use FinTechs. This can be achieved through digital literacy that can help them to embrace digital financial services and competently navigate and perform digital transactions over digital platforms like mobile money without making errors. Besides, governments in developing countries like Uganda can use this finding to advocate for the design of appropriate digital infrastructures to reach remote areas and ensure “last mile connectivity for digital financial services' users.” The use of off-line solutions can complement the absence or loss of on-line network connectivity for biometrics and mobile money to close the huge digital divide gap in rural areas. This can scale-up access to and use of financial services by the unbanked rural population.

This paper sheds more light on the importance of digital literacy in the ever complex and dynamic global FinTech ecosystem in the presence of rampant cyber risks. To the best of the authors' knowledge, limited studies currently exist that integrate digital literacy as a moderator in the relationship between FinTechs and digital financial inclusion, especially among vulnerable groups in under-developed digital financial markets in developing countries. This is the novelty of the paper with data obtained from the unbanked poor women, youth and PWDs in rural Uganda.

This study aims to establish marketing practices which predict business performance of architecture firms within the Nigerian Construction Industry (NCI) to address the sustained poor business performance of firms, which affects allied professionals as many projects in the built environment depend on design proposals from architects.

Survey responses from 86 firms were used to model business performance measured as total revenue of the firms from 40 commonly deployed marketing practices in construction.

Two-thirds of the marketing practices most used by architectural firms were ineffective in predicting business performance. The model also explains up to half the variance in business performance (37.4–49.9%), supporting the view that marketing in the CI affects business performance. Researching client needs and competitors emerged as the only significant positive predictor of business performance (β = 0.827, p = 0.043). Using social media (β = −1.247, p = 0.004), regular participation in awards/competitions (β = −1.420, p = 0.013) and inclusion of political offers in bids (β = −1.050, p = 0.016) negatively predicted business performance.

Architecture and allied professional bodies in Nigeria need to rethink existing restrictions regarding marketing based on traditional code of ethics in light of present-day realities of digital and internet business environments. Principals and management of architecture firms require a paradigm shift in deploying the appropriate marketing practices, especially as it relates to research regarding changing client expectations and current competition within the NCI.

The study established marketing practices which model business performance and demonstrate their value in a framework for improving the financial sustainability of architecture firms within the NCI.

The COVID-19 pandemic has wrought havoc on economies around the world. The purpose of this study is to learn about the distributional impacts of the pandemic.

The authors contribute new theoretical and empirical evidence on the distributional impacts of the pandemic on different income groups in a multicountry setting. The authors analyze rich individual-level survey data covering 6,082 respondents from China, Italy, Japan, South Korea, the United Kingdom and the United States. The results are robust to various econometric models, including ordinary least squares (OLS), Tobit and ordered probit models with country-fixed effects.

The authors find that while the outbreak has no impact on household income losses, it results in a 63% reduction in the expected own labor income for the second-poorest income quintile. The pandemic impacts are most noticeable for savings, with all the four poorer income quintiles suffering reduced savings ranging between 5 and 7% compared to the richest income quintile. The poor are also less likely to change their behaviors regarding immediate prevention measures against COVID-19 and healthy activities. The authors also found countries to exhibit heterogeneous impacts.

Designing tailor-made social protection and health policies to support the poorer income groups in richer and poorer countries can generate multiple positive impacts that help minimize the negative and inequality-enhancing pandemic consequences. These findings are relevant not only for COVID-19 but also for future pandemics.

The authors theoretically and empirically investigate the impacts of the pandemic on poorer income groups, while previous studies mostly offer empirical analyses and focus on other sociodemographic factors. The authors offer a new multicountry analysis of several prevention measures against COVID-19 and specific health activities.

Although risk culture is a key determinant for an effective risk management, identifying the risk culture of a firm can be challenging due to the abstract concept of culture. This paper proposes a novel approach that uses unsupervised machine learning techniques to identify significant features needed to assess and differentiate between different forms of risk culture.

To convert the unstructured text in our sample of banks' 10K reports into structured data, a two-dimensional dictionary for text mining is built to capture risk culture characteristics and the bank's attitude towards the risk culture characteristics. A principal component analysis (PCA) reduction technique is applied to extract the significant features that define risk culture, before using a K-means unsupervised learning to cluster the reports into distinct risk culture groups.

The PCA identifies uncertainty, litigious and constraining sentiments among risk culture features to be significant in defining the risk culture of banks. Cluster analysis on the PCA factors proposes three distinct risk culture clusters: good, fair and poor. Consistent with regulatory expectations, a good or fair risk culture in banks is characterized by high profitability ratios, bank stability, lower default risk and good governance.

The relationship between culture and risk management can be difficult to study given that it is hard to measure culture from traditional data sources that are messy and diverse. This study offers a better understanding of risk culture using an unsupervised machine learning approach.

The global financial crisis (GFC) of 2007–2008 had far-reaching consequences for the global economy, triggering widespread economic turmoil. We use the event-study method to investigate whether investors priced the effect of significant events before the Lehman Brothers' bankruptcy in European and Asia-Pacific banks. Abnormal returns on the event days range from −4.32% to 5.03% in Europe and −5.13% to 6.57% in Asia-Pacific countries. When Lehman Brothers went bankrupt on September 15, 2008, abnormal returns averaged the lowest at −4.32% in Europe and −5.13% in Asia-Pacific countries. The significant abnormal returns show that Lehman Brothers' collapse was a turning point, and investors paid attention to the precrisis events as warning signs of the oncoming crisis.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

The developmental relation of informal mentoring within the organization could aid in tiding over the challenges that arise with change. The purpose is to explore the relationship between informal mentoring within the organization and change supportive behaviour to put forth a framework describing the catalytic and a priori role of informal mentoring within the organization in augmenting change readiness and facilitating change supportive behaviour for a successful organizational change.

Drawing on the appraisal theory of stress coping, the paper put forward a conceptual framework describing the mechanisms through which informal mentoring within the organization leads to change supportive behaviour among the individuals.

The conceptual model explains how informal mentoring within the organization develops optimism, resilience, self-efficacy and trust and facilitates change readiness among the individuals, which leads to change supportive behaviours in them. The paper also describes the influence of poor change management history and organizational identity threat on the relations.

The paper explains the underexplored relationship between mentoring and change readiness. It also sheds light on the importance of exploring the micro-foundations of a macro-level phenomenon. Further research should focus on the differential effect of different forms of mentoring on change readiness.

The paper is developed based on the review of extant literature and applying the theoretical lens of appraisal theory of stress coping to the phenomenon. The paper explains the micro-foundation of the phenomenon and describes how informal mentoring would lead to a change supportive behaviour among the individuals.

This study aims to analyse the condition of the elderly in poor households which includes two things. The first is the characteristics of the elderly in poor households and the effect of poverty on the economic activities of the elderly.

This research uses secondary data from the 2020 National Social Economic Survey.

Poverty status of households is proven to have an effect on the participation of the workforce and the work participation of the elderly. The poor elderly tend to have a greater chance of participation in economic activities than the non-poor elderly. The absence of pension and old age insurance also causes the elderly to continue working until old age. Working is one of the survival mechanisms for the elderly.

This research has analysed the two population problems, which are the aging population and poverty.