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The objective of this study is to examine the moderating effect of microfinance on the digital divide in developing countries.

On the methodology, the econometric method employed to estimate the equation is based on the two-stage least squares (2SLS).

This study confirms that microfinance can play an important role in mitigating the adverse effect of digitalization on poverty.

Thus, governments should prioritize and encourage the integration of digital technologies with robust microfinance systems to effectively combat poverty, given the importance of microfinance.

Given the importance of digital technology to businesses and economic development, we need to search for a better solution that allows digital technology to be further developed but at the same time, is not harmful to the poor. The issue of the poor, either financially or technically can be partially resolved if the poor is given the necessary and sufficient assistance. Therefore, this paper examines whether microfinance can be part of solutions to the digital divide in developing countries.

Data from different countries suggest a higher prevalence of anxiety, depression and suicides among manual and trade workers in the construction industry than in the general population. The present review examines the causes and effects of poor mental health and the effectiveness of interventions to improve manual and trade workers' mental health in the construction industry. It also identifies gaps in research and makes several suggestions for practice and future research.

A systematic literature review was conducted to examine and consolidate evidence reported in 54 relevant journal articles published between 2010 and 2021 on the mental health of manual and trade workers.

Three major themes emerged in the review of the 54 journal articles: causes of poor mental health, effects of poor mental health and interventions to improve mental health. The leading causes of poor mental health among construction manual and trade workers are poor work-life balance, high job demand, poor cultural norms and mental health stigma, chronic bodily pain, lack of social support, workplace injustice and job insecurity. The prominent effects of poor mental health are suicidality, drug and alcohol addiction, poor workplace safety and poor work performance. Moreover, the study found that some of the strategies recently implemented in the construction industry to improve mental health are deemed ineffective, or their effectiveness remains inconclusive.

The review's scope is limited to research on manual and trade workers, and it did not investigate the mental health of construction professionals and construction management students.

The review provides valuable insights into the causes and effects of poor mental health among manual and trade workers and the effectiveness of mental health interventions in the construction industry.

This paper aims to examine the mismatch between multidimensional deprivation and monetary poverty in identifying the poor in Egypt and investigates their determinants empirically.

The paper uses the Alkire-Foster multidimensional poverty measurement method using data from Egypt’s 2017/2018 Household Income, Expenditure and Consumption Survey (HIECS 2017/2018). Using a logistic regression model, the paper assesses the empirical relationship between multidimensional and monetary poverty and their determinants at the aggregate level and by dimension.

The paper demonstrates a significant mismatch between multidimensional and monetary poverty measures, underscoring their complementary nature. Statistics indicate that both measures overlap in classifying 35.81% of Egyptians, whereas monetary poverty ignores 63.12% of multidimensionally poor in at least one dimension. Regression estimates show a significant moderate negative association between expenditure per capita and multidimensional poverty and its dimensions. Moreover, they show that household head’s gender, age, education attainment, marital status, job proficiency, household size and location affect poverty mismatch and match in Egypt.

This paper offers Egyptian policymakers the multidimensional poverty index that enables more efficient designing and targeting of poverty alleviation programs and assessing current poverty alleviation programs to modify them if needed.

To the best of the authors’ knowledge, this study is the first to examine the mismatch between both poverty measures in Egypt, using the recent full data set of HIECS 2017/2018. This paper confirms that depending only on monetary measures can send inaccurate insights for crafting effective social policies. Also, it offers policymakers a comprehensive insight into the country’s poverty landscape, which enable more efficient design, targeting of poverty alleviation programs and monitoring their effectiveness.

The microfinancing sector is infamous for being prone to high credit risks due to loan defaults by its poor borrowers. Conversely, the sector is also criticized for creating debt traps for the poor. The dual nature of these peculiar problems in microfinancing causes the market failure phenomenon. Therefore, the current study explores whether public policy intervention is required to address market failure.

The study undertakes a critical review of existing literature, the news, the policy documents and other publicly available information to shape the viewpoints in this study. Constructive criticism is used to build arguments to arrive at a conceptual framework that depicts how public policy should interact with markets to address the peculiar problems of the microfinancing sector.

The findings indicate that market failure in microfinancing is real and pressing. Therefore, public policy is invited, though in its limited form. While the policy intervention may help the formal microfinancing arena by regulating the interest rates, the policy administration in the informal sector is likely to fail. Therefore, the policy should attempt to create an environment of inclusiveness. Policies that rely on coercion are not recommended. In the long run, subsidies via policy intervention are discouraged. Instead, the policy should motivate the microfinancing sector to become self-reliant.

The study is one of its kind to provide perspectives on specific market failures and policy interventions in microfinancing, particularly in economies where formal and informal sectors coexist and are equally crucial.

The objective of this paper is to examine the profound repercussions of workplace bullying (WB), emotional exhaustion (EE), and psychological distress (PD) on poor job performance (PJP) within the intricacies of Thailand’s healthcare sector. It also seeks to elucidate the moderating influence of COVID-19 burnout (CBO) on these variables.

This paper utilized a quantitative research approach. A total of 230 responses were collected from healthcare workers using convenience sampling during a significant surge of the coronavirus in March 2022. To assess the reliability and correlations between constructs, a dual-stage structural equation modeling (SEM) technique was applied.

During the global health crisis caused by COVID-19, WB and PD were found to positively predict PJP, except for EE. The presence of WB elevated EE and PD among Thai hospital staff. PD and EE partially mediated the relationship between WB and PJP. The positive moderating role of CBO among hospital employees significantly buffered the relationship between WB and EE.

The originality of this study lies in the examination of the poor mental health of Thai healthcare workers during the COVID-19 pandemic. Healthcare reforms are required to protect the mental health of Thai healthcare staff to prevent poor job performance following unprecedented circumstances.

Social housing offers occupants comfort, safety and protection against extreme weather conditions. However, social housing occupants in various regions of Nigeria face various challenges. This paper aims to use a quantitative approach to examine the factors that contribute to the challenges faced by occupants in social housing within a semi-arid climate of Nigeria.

An exploratory cross-sectional survey was used to administer 1,032 copies of structured questionnaires to occupants of social housing in Maiduguri, one of the largest urban centers of the semi-arid climate in Nigeria. A total of 955 responses were retrieved, giving a response rate of 92.5%. The statistical model used in analyzing data was relative importance indices and factor analysis.

The results show that poor quality of FM services provided, poor maintenance of building components, damage to materials and valuables in the Harmattan period and housekeeping problems due to dust deposition in doors, while the poor response to occupants’ complaints/reports is the least among the occupants’ challenges in order of importance. Moreover, the results of the factor analysis further established that inadequate FM services and poor environmental conditions are the two factors contributing to the occupants’ challenges in social housing within the semi-arid climate of Nigeria.

This paper seeks to examine the factors contributing to social housing occupants’ challenges in the semi-arid climate of Nigeria. The paper should inform policymakers, academics and professionals.

Despite being a Muslim-dominated country, Bangladesh has widely embraced traditional microfinance since its inception in the mid-1970s. However, Islamic microfinance, which has a lot to offer to the poor, is still in its infancy and has yet to gain momentum in the country. Therefore, the purpose of this study is to analyze the importance of Islamic microfinance and propose alternative Shariah-compliant microfinance models in Bangladesh.

This study is based on the desk research method, which relies on existing literature to collect secondary data on key concerns of traditional microfinance programs. In addition, institutional-level secondary data were also collected from the Microcredit Regulatory Authority (MRA) of Bangladesh. Guided by the Maqasid-al-Shariah, this study then proposes several Islamic microfinance models to overcome selected challenges faced by the microfinance industry in Bangladesh.

This study suggested three composite Shariah-compliant microfinance models, which are likely to help the underprivileged and thus ensure the achievement of the sustainable development goals in Bangladesh. The first model explained how the operational strategy of incumbent microfinance institutions (MFIs) could be restructured, while the second proposed the organizational strategies for establishing a new MFI. The third model used the notion of Sadaqah (charity) to address the multiple borrowing issues of the industry. Meanwhile, the successful transformation of the conventional microfinance industry to an Islamic one is dependent on the effective collaboration between the regulatory authorities, practitioners and MFIs.

Albeit the paucity of literature on the topic, the findings of this study will guide policymakers/practitioners in designing relevant microfinance models to help transform conventional microfinance into Islamic microfinance in Bangladesh.

This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

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.