Advanced Journal of Management, Humanity and Social Science

Abstract This study examines the impact of microfinance services on the financial sustainability and performance of medium-sized enterprises (SMEs) in Mazar-e-Sharif, Afghanistan, using data from 100 firms selected through systematic random sampling. The primary objective is to assess how microcredit access, savings services, and entrepreneurial development training affect return on assets (ROA) and financial sustainability (FS), while controlling for firm age and size. Data were collected via structured questionnaires administered to SME owners/managers, with reliability confirmed by Cronbach's alpha of 0.780 (N=100 items) and content validity established through review by 10 Afghan microfinance experts. Analysis employed descriptive statistics, Pearson correlation matrices, and multiple linear regression models following established SME research methodologies. The first regression model revealed that internal finance (β=0.012, t=10.78, p<0.001) and trade credit (β=0.008, t=7.23, p<0.001) significantly enhance ROA (R²=0.61, F=24.37, p<0.001), while non-institutional finance shows a negative effect (β=-0.130, p=0.017). The second model demonstrated strong positive impacts of microcredit (β=0.287, t=5.02, p<0.001), savings services (β=0.214, t=3.67, p=0.01), and entrepreneurial training (β=0.176, t=3.11, p=0.002) on financial sustainability (R²=0.65, Adj. R²=0.62, F=28.45, p<0.001), with larger/younger firms benefiting most. Nine of ten hypotheses were supported, underscoring microfinance's comprehensive role (financial + non-financial services) in fragile economies. Policy recommendations include government investment in energy infrastructure, transportation networks, and SME training programs to enhance competitiveness. These findings offer actionable insights for post-conflict development strategies.

Abstract The rapid integration of artificial intelligence (AI) systems into core societal institutions—from criminal justice and welfare administration to employment and border governance—has generated unprecedented challenges for international human rights law. This article examines three intersecting dimensions of the AI-human rights nexus: the contested question of AI legal personhood, the allocation of responsibility for AI-induced harms across complex value chains, and the evolving architecture of global AI governance. Drawing on the Council of Europe's Framework Convention on Artificial Intelligence (2024), the UN Guiding Principles on Business and Human Rights as applied to AI (2025), and emerging regulatory frameworks including the EU AI Act, this analysis argues that granting legal personhood to AI systems is neither necessary nor desirable for effective accountability. Instead, a functional approach that mandates human rights due diligence throughout the AI lifecycle, establishes accessible remedy mechanisms for affected individuals, and promotes regulatory coherence across jurisdictions offers a more promising pathway. The article synthesises findings from a doctrinal analysis of 45 international legal instruments, UN reports, and scholarly sources to propose a rights-based governance framework centred on mandatory human rights impact assessments, independent oversight, and meaningful stakeholder engagement with affected communities.