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The aim of this study is to investigate the effect of income and geographic diversification on the double bottom line of microfinance institutions (MFIs) in Middle East and North Africa (MENA) countries where conventional and Islamic MFIs coexist. The idea is to explore whether diversification impacts MFIs' financial performance and outreach differ for Islamic microfinance.

The authors test the effect of diversification and business models of MFIs on their performance and poverty outreach. The authors’ data set is an unbalanced panel sample of 81 (Islamic and conventional) MFIs in MENA countries covering 1999–2018, comprising 743 MFI-year observations.

The authors find that increasing income diversification in microfinance and focusing on rural areas decreases the financial performance of MFIs in MENA countries. Islamic MFIs benefit from income diversification by increasing their financial performance. The results provide evidence of a nonlinear relationship between income diversification and the financial performance of MFIs. Although conventional MFIs improve their depth of outreach by diversifying their income, Islamic MFIs have a lower breadth of outreach because they show a higher degree of income diversification.

This research contributes to the ongoing debate of whether MFIs should focus on or diversify their services to Islamic microfinance. Therefore, the findings of this study are practically crucial for MFIs' stakeholders to understand the contribution of diversification strategies in improving the Islamic MFIs to achieve both financial and social objectives.

To the best of the authors’ knowledge, it is the first research that addresses the impact of diversification strategies in Islamic microfinance. Additionally, using a panel data set of conventional and Islamic MFIs in MENA countries spanning 1999–2018, this study provides empirical evidence on the diversification versus focus issue from the microfinance industry and the subset of Islamic microfinance.

The purpose of this paper is to provide preliminary efficiency assessment of Arab microfinance institutions (MFIs) within the period 2002–2012. Microfinance is defined as the provision of financial services to poor and low-income households and their microenterprises on a sustainable basis.

The authors first present the main features of microfinance in the Middle East and North Africa (MENA) region. Second, based on a simple of 72 microfinance institutions issued from ten countries of the region, they develop a bootstrap–data envelopment analysis (bootstrap–DEA) framework to measure Arab MFIs’ efficiency. Finally, they apply parametric and non-parametric tests to compare the performance and identify factors that contribute to the efficiency of Arab Islamic microfinance institutions.

Efficiency scores of the MENA region exhibit high variability, both across time and countries. Significant difference in efficiency was found due to MFI age or regulation. Results also reveal the ability of Arab MFIs to combine social and financial performance and their solidity in time of crisis.

In this paper, the authors apply DEA–bootstrap method on a large sample of Arab MFI with special look at the peer group differences. Unlike most previous relevant studies, the paper overcomes many of the drawbacks of the DEA method by using, in addition to the DEA–bootstrap approach, a test of return to scale and a combination of three procedures to detect outliers. Furthermore, this paper analyses the efficiency of MFI in the MENA region in the light of financial crises and Arab Spring.

The overall functioning of this system is based on two approaches: construction and supervision. The first is conducted entirely by the machine, and the second requires the intervention of the designer to collaborate with the machine. The morphological translation of urban rules is sometimes contradictory and may require additional external relevance to urban rules. Designer arbitration assists the artificial intelligence (AI) in accomplishing this task and solving the problem.

This paper provides a method of computational design in generating the optimal authorized bounding volume which uses the best target values of morphological urban rules. It examines an intelligent system, adopting the multi-agent approach, which aims to control and increase urban densification by optimizing morphological urban rules. The process of the system is interactive and iterative. It allows collaboration and exchange between the machine and the designer. This paper is adopting and developing a new approach to resolve the distributed constraint optimization problem in generating the authorized bounding volume. The resolution is not limited to an automatic volume generation from urban rules, but also involves the production of multiple optimal-solutions conditioned both by urban constraints and relevance chosen by the designer. The overall functioning of this system is based on two approaches: construction and supervision. The first is conducted entirely by the machine and the second requires the intervention of the designer to collaborate with the machine. The morphological translation of urban rules is sometimes contradictory and may require additional external relevance to urban rules. Designer arbitration assists the AI in accomplishing this task and solving the problem. The human-computer collaboration is achieved at the appropriate time and relies on the degree of constraint satisfaction. This paper shows and analyses interactions with the machine during the building generation process. It presents different cases of application and discusses the relationship between relevance and constraints satisfaction. This topic can inform a chosen urban densification strategy by assisting a typology of the optimal authorized bounding volume.

The human-computer collaboration is achieved at the appropriate time and relies on the degree of constraint satisfaction with fitness function.

The resolution of the distributed constraint optimization problem is not limited to an automatic generation of urban rules, but involves also the production of multiple optimal ABV conditioned both by urban constraints as well as relevance, chosen by the designer.

This study aims to explore the mediating role of corporate social responsibility (CSR) committees in the relationship between board characteristics and environmental, social and governance (ESG) performance, specifically within the Middle East and North Africa (MENA) region.

Based on a panel of 178 firms spanning 2015–2022, the analysis uses Baron and Kenny’s (1986) mediation approach, supplemented by structural equation modeling (SEM) path analysis for robustness.

The findings demonstrate that CSR committees play a significant mediating role in the impact of board size, expertise and gender diversity on ESG performance. Furthermore, the study confirms the direct, positive influence of both board characteristics and the presence of CSR committees on ESG performance, underscoring their strategic importance in fostering sustainability in this regional context.

The findings highlight the strategic importance of diversifying and enhancing board skills to improve ESG performance. Companies are encouraged to recalibrate their governance frameworks to leverage the mediating influence of CSR committees and promote sustainable business practices.

By demonstrating the positive effect of CSR committees on ESG performance, this study aligns with global trends in responsible business conduct and highlights the importance of corporate governance in addressing environmental and social challenges. This alignment is critical for achieving sustainable development goals and reinforcing stakeholder trust in the region.

This research provides novel empirical insights into the mediating effect of CSR committees within the MENA region, offering a unique contribution to the discourse on corporate governance and sustainability. By highlighting region-specific governance dynamics that shape ESG outcomes, it deepens the understanding of effective governance practices.