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Considering the existing evidence on the impact of female board members on the default risks of an organization, the purpose of this study is to investigate the effect of board gender diversity, alongside institutional characteristics and macroeconomic factors, on the financing costs of microfinance institutions (MFIs).

This study collected unbalanced panel data of 1,190 unique MFIs between 2010 and 2018 from the World Bank. The collected data, which covers a total of 95 developing and emerging countries, was thereafter analyzed using the pooled ordinary least squares and random effects model. To overcome endogeneity and omitted variable bias (e.g. time-invariant variables), the authors have also used the generalized method of moments and fixed effects model, respectively. Different proxies of board gender diversity and sub-sample analysis by regions were further undertaken to examine the robustness of the obtained results.

The findings of this study revealed that board gender diversity has a statistically significant negative effect on the financing costs of MFIs. This suggests that a gender-diverse board can generate cheaper funding for MFIs by minimizing their default risks through effective monitoring and strategic management. Furthermore, the negative impact of board gender diversity on financing costs appears to be more pronounced when there is a minimum of two female board members in the boardroom of MFIs. The results of this study remain consistent and valid regardless of alternate model specifications (e.g. sub-sample analysis, use of alternative proxies of board gender diversity and application of different estimators) and endogeneity issues. Ultimately, the findings in this study reiterate the importance of promoting and implementing gender diversity in the boardroom to minimize the financing costs of MFIs.

This study investigated the relationship between board gender diversity and financing costs of MFIs by using relatively recent and global data. The minimum number of female board members required to significantly reduce the financing costs of MFIs was also identified.

Given the growing emphasis among scholars, practitioners and policymakers on financial sustainability, this study aims to explore the applicability of machine learning techniques in predicting the financial performance of microfinance institutions (MFIs).

This study gathered 9,059 firm-year observations spanning from 2003 to 2018 from the World Bank's Mix Market database. To predict the financial performance of MFIs, the authors applied a range of machine learning regression approaches to both training and testing data sets. These included linear regression, partial least squares, linear regression with stepwise selection, elastic net, random forest, quantile random forest, Bayesian ridge regression, K-Nearest Neighbors and support vector regression. All models were implemented using Python.

The findings revealed the random forest model as the most suitable choice, outperforming the other models considered. The effectiveness of the random forest model varied depending on specific scenarios, particularly the balance between training and testing data set proportions. More importantly, the results identified operational self-sufficiency as the most critical factor influencing the financial performance of MFIs.

This study leveraged machine learning on a well-defined data set to identify the factors predicting the financial performance of MFIs. These insights offer valuable guidance for MFIs aiming to predict their long-term financial sustainability. Investors and donors can also use these findings to make informed decisions when selecting their potential recipients. Furthermore, practitioners and policymakers can use these findings to identify potential financial performance vulnerabilities.

This study stands out by using a global data set to investigate the best model for predicting the financial performance of MFIs, a relatively scarce subject in the existing microfinance literature. Moreover, it uses advanced machine learning techniques to gain a deeper understanding of the factors affecting the financial performance of MFIs.

Islamic banking and microfinance institutions (MFIs) share the core objective of serving the underprivileged. This study aims to investigate whether Islamic banking development facilitates (greases) or hinders (sands) the social mission of MFIs.

Data for 19 countries covering the period 2010–2018 were collected from the World Bank, Bank Focus and International Monetary Funds and analyzed using conventional econometric methods. Endogeneity-corrected techniques and alternative proxies were employed to ensure robust results.

The study revealed that Islamic banking development (proxied by the size of the Islamic banking assets) weakens the depth of outreach of MFIs (measured by average loan size). In countries with growing Islamic banking, MFIs appear to shift their focus toward wealthier clients, potentially due to market saturation among the poor. This is evidenced by MFIs offering larger loans, suggesting a mission drift toward profit maximization. Therefore, it can be inferred that competition from Islamic banks, to some extent, erodes the social mission of MFIs.

This study is among the few to examine the recent and comprehensive relationship between Islamic banking development and the social mission of MFIs.

Digitalization is one of the major factors that fosters economic growth across the world. However, the level of digitalization varies significantly between developed and developing countries, with the latter often lagging behind. To bridge this gap, it is crucial to pinpoint the drivers of digitalization, specifically from the macroeconomic and country-level governance dimensions. Therefore, this study aims to investigate the determinants of digitalization, particularly for countries in Asia and the Pacific region.

Our study utilizes unbalanced panel data from 46 Asian and Pacific countries for the period of 2001–2021. Initially, we analyzed the data using conventional econometric methods, such as pooled ordinary least squares (POLS), random-effects model (REM) and fixed-effects model (FEM). Moreover, we employed endogeneity-corrected techniques and alternative proxies to enhance the robustness and reliability of our findings.

Our findings reveal that economic development progress, government expenditure relative to country size and political stability are key drivers of digitalization. In contrast, corruption at the country level emerges as a significant impediment. Notably, our results remain robust to endogeneity-corrected techniques and alternative proxies of digitalization. Overall, these insights can inform policymakers, helping them to understand the macroeconomic and governance factors shaping digitalization and guide their decision-making toward effective policy interventions.

This study’s empirical findings add significant value to the existing literature by quantifying the impact of macroeconomic and governance factors on digitalization in selected countries. This offers valuable insights for policymakers, particularly in nations with lower levels of digitalization.

Earlier studies on employee turnover have invested enormous scholarly mileage to understand and address human resource challenges. Considering the substantial evidence on the negative and non-linear relationship between employee turnover and firms’ performance, the purpose of this study is to investigate the effects of employee turnover on the social outreach (e.g. breadth of outreach) of microfinance institutions (MFIs), also known as the financial inclusion agenda of the Sustainable Development Goals.

To achieve the study objective, the authors collected unbalanced panel data of 1,391 MFIs, covering a total of 96 economies and a period of 2010–2018. The organizational and macroeconomic data were obtained from the World Bank’s Mix Market and World Development Indicators databases, respectively, and subsequently analysed using the pooled ordinary least squares, random effects model, fixed effects model and generalized method of moments.

Overall, the authors found that employee turnover has a positive impact on the social outreach of MFIs, which suggests that employee turnover reduces organizational blindness and groupthink, potentiates efficiency gains and minimizes retention costs. On the contrary, this study does not find evidence of a non-linear effect of employee turnover on the outreach objectives of MFIs. Meanwhile, these effects were observed to vary depending on the proxy, sub-samples and techniques used in the analysis.

Motivated by the paucity of literature, the study has uniquely investigated the effect of employee turnover on the social outreach objective of MFIs by using relatively recent and global-level data. The study findings can help managers and the human resource departments to make optimum decisions about employee turnover management.

Globally, the COVID-19 pandemic impacts the financial condition and the mental health of millions of workers from various informal sectors. This study aims to look into the hawkers’ community’s mental health and living conditions in Bangladesh during COVID-19.

The researchers have applied the purposive sampling technique to choose ten hawkers from Khulna city, a district in the southern region of Bangladesh. An in-depth interview was taken in the Bengali language in an unstructured manner and lasted 30–40 min per respondent.

The findings showed that the Hawkers’ income reduced, and specifically, during the pandemic, they had earned half of what they usually made before. Besides, they could not open their stores because law enforcement agencies imposed restrictions on opening business centres during the lockdown except for some emergency necessities shops. This restriction led the hawkers to stop selling their products because there was a high chance of spreading the virus through the products they sold. Due to income reduction, they had to eat cheap food, which caused their health problems. Consequently, this community mentally got depressed.

Policymakers in Bangladesh might think about enacting more effective measures to provide some extrinsic and intrinsic support in improving the mental health of the hawkers’ community.

To the best of the authors’ knowledge, this is the first study on the mental of the hawkers’ community during COVID-19.

Despite city authorities in Bangladesh being concerned about urban sustainability, they often face difficulties in addressing predominant urban challenges threatening urban sustainability, due to limited relevant literature. To reduce this gap, this study aims to address the predominant urban challenges and assess their severity levels in four city corporations of Bangladesh, e.g. Rajshahi, Sylhet, Barishal, and Gazipur.

Using a mixed-method approach, this study rigorously analyzed field-level data obtained from 1,200 residents across selected cities using diverse statistical techniques. The quantitative analysis included descriptive analysis, exploratory factor analysis, and chi-square tests, whereas qualitative insights were derived through thematic analysis.

The study uncovered nine predominant urban challenges under two crucial factors “Feeble Urban Management” and “Illicit Activities” that collectively explain 62.20% variance. “Feeble Urban Management” explains 44.17% variance, whereas “Illicit Activities” accounts for 18.13%. Within these challenges, uncontrolled urban sprawl, inadequate disaster management, congested roads, and shabby drainage and waste management pose significant threats to urban sustainability. Illicit activities, manifested by encroachment on water sources, grabbing roadside, destruction of natural properties, and activities undermining social security, compound the urban sustainability issue. Severity analysis reveals Sylhet (54.5%), Rajshahi (46.4%), and Barishal (31.2%) as highly impacted, whereas Gazipur exhibits moderate severity (66.7%).

The findings of this study reveal intrinsic insights into urban challenges in Bangladesh that will provide valuable guidance to city authorities, equipping them to implement integrated and effective initiatives and programs that overcome these predominant urban challenges, with a specific focus on Rajshahi, Sylhet, and Barishal city corporations.

Online shopping around the world is growing exponentially, especially during the COVID-19 pandemic. This study aims to examine how an online customer's purchasing experience influences his/her buying intention and willingness to believe in fraud news, as well as the ripple impact of satisfaction and trust, with gender as a moderator in an emerging economy during COVID-19.

Based on the underpinning of the stimulus-organism-behavior-consequence (SOBC) theory, the research model was developed, and collected data from 259 respondents using convenience samples technique. Next, the data were analyzed using partial least squares-based structural equation modeling (PLS-SEM), SPSS (Statistical Package for the Social Sciences) and Hayes Process Macro.

The study results confirmed that the online shopping experience (OSE) has positive impact on customers' satisfaction (CS), purchase intention (PI) and customer trust (CT); CS has positive effects on trust toward online shopping and their future product PI; future product PI significantly affects customers' propensity to believe and act on fraud news (PBAFN). The finding also states that gender moderates the relationships of CS to PI, OSE to PI and PI to PBAFN, but doesn't moderate the CT to PI relationship.

The study findings will assist policymakers and online vendors to win customers' hearts and minds' through confirming satisfaction, trust and a negative attitude toward fake news, which will lead to customer loyalty and the sustainable development of the industry. Finally, the limitations and future research directions are discussed.

This study aims to explain the effect of entrepreneurial orientation (EO) dimensions on firms’ export performance. The study has considered three dimensions of EO: innovativeness, proactiveness and risk-taking. Export performance has been measured through multifaceted determinants: financial, strategic and satisfaction levels of exporting firms.

To explain the association between such determinants, qualitative face-to-face, in-depth interviews were conducted with the respondents from the apparel manufacturing companies of Bangladesh. The study has also applied a content analysis technique to explore and triangulate the descriptions of EO dimensions on performance.

The research results reveal that EO has a meaningful explanation of export performance from the lived experience of the respondents. The study has also found frequent explanations and indicators about the association of innovativeness and proactiveness on export performance, but the risk-taking dimension has revealed no effects.

The research has different implications on theoretical, managerial and policy-making aspects of EO and export performance. Nevertheless, the findings are based on the opinions of a small sample of entrepreneurs and high-level managers. Thus, it is important to test the generalizability of these findings in future research using a larger sample.

This study indicated product, process and market creation innovativeness. Risks related to product innovation, new market entry and politics are considered for risk-taking measures, while proactive innovation, technology and new market searching are used for measuring proactiveness. Additionally, multifaceted performance determinants have been applied to evaluate export performance. Hence, this study is a unique qualitative analysis with important theoretical, practical and methodological implications.

The aim of this study is to examine the effects of innovativeness (INN), proactiveness, (PRC) and risk-taking (RIT) on the export performance of apparel small and medium-sized enterprises (SMEs) and the role of differentiation and low-cost leadership (LCL) strategies as mediating effects between entrepreneurial orientation (EO) dimensions and the performance of exporting firms. INN, RIT and PRC are considered EO dimensions.

A cross-sectional survey was carried out by providing a questionnaire to the owners, directors and senior managers of the apparel SMEs – the primary data of 550 treated by structural equation modeling (SEM) technique for final data analysis.

The study has revealed the positive dimensional effect of EO on export performance. For the mediation effects of differentiation and LCL, differentiation strategy (DS) positively mediates between INN, PRC and export performance. However, no mediation has been found between RIT and export performance. On the other hand, LCL has found positive effects between INN, RIT and export performance. However, the mediation effect was absent between PRC and export performance.

Limitations/implications- This study has been conducted on only Muslim owners, senior export managers and directors of apparel SMEs in Bangladesh. It has examined the two main competitive strategies as a mediator between EO dimensions and export performance. The findings of this study are based on one country data analysis.

EO, differentiation and low-cost leadership (LCL) strategy are resources and capabilities of an organization to create a competitive advantage to enhance performance. The factors of this research are helpful for SME practitioners.

The direct and indirect effects (differentiation and LCL strategy) of EO dimensions on export performance in an emerging country, i.e. the South-Asia region, is a pioneer study. Therefore, current research has theoretical and managerial implications for the international business and strategic management literature.