African Scientific Journal

FDI and Inclusive Development What Institutional Levers to Reduce Regional Inequalities A Comparative Study

LEBTAR Youness, ZNASNI Mourad, YAHYAOUI Rachid, MALAININE Mohamed Limame — Tue, 15 Jul 2025 00:00:00 +0000

Abstract:

This study investigates the institutional mechanisms through which Foreign Direct Investment (FDI) contributes to inclusive development and reduces regional inequalities in Sub-Saharan Africa. Focusing on three representative countries Nigeria, South Africa, and Ethiopia this research adopts an Autoregressive Distributed Lag (ARDL) panel model over the period 2011 to 2024 to examine the long-run and short-run relationships between regional inequality and key explanatory variables: FDI inflows, GDP per capita, institutional quality, and infrastructure investment. The results reveal that while FDI reduces spatial disparities in Nigeria and South Africa, it exacerbates them in Ethiopia, where investment is spatially concentrated. Furthermore, institutional quality and infrastructure investment consistently demonstrate significant negative effects on regional inequality, highlighting the critical role of governance and territorial planning in ensuring inclusive development. The findings emphasize the need for differentiated policy approaches that integrate economic, institutional, and spatial dimensions of development, and call for stronger regional governance frameworks to harness FDI for equitable growth. The study offers actionable policy recommendations and contributes to the growing literature on spatial justice and developmental state strategies in Africa.

Keywords: Regional inequality; Inclusive development; Foreign direct investment (FDI); Institutional quality; Infrastructure; ARDL model; Sub-Saharan Africa; Nigeria; South Africa; Ethiopia; Spatial disparities.

Bibliometric Analysis of Artificial Intelligence Applications in Human Resource Management (2010–2025): Mapping Global Research Trends and Organizational Implications

Nabila EL BOUKHARI, Mounia FILALI — Tue, 15 Jul 2025 00:00:00 +0000

Abstract

Purpose: In this study, we seek to systematically chart the intellectual structure of AI applications in HRM based on a bibliometric approach from 2010 to 2025 as an item. This study implies a positivism epistemological stance, identifying publication trends within a positivist perspective, using structured data and statistical tools to reveal generalized patterns within the academic literature. It analyses the development of the literature, top contributors, thematic networks and collaboration ties, and concludes with consideration of the findings for the field of industrial organizations. Finally, the reasoning for this study goes deductive using a general database analyzed to drive findings that are interpreted to draw specific conclusions about thematic evolution in this field.

Design/methodology/approach: A total of 354 peer-reviewed articles were systematically extracted from the Scopus database using a targeted search query. combining AI and HRM-related terms. This bibliometric dataset constitutes the empirical sample of the study. The extraction process was governed by inclusion criteria such as language (English), document type (articles only), and relevance to HRM-AI topics. The analysis was conducted using Bibliometrix (R package) for performance indicators as a quantitative analysis and VOSviewer for co-occurrence and co-authorship visualizations and thematic mapping. The study focuses on five research questions addressing productivity trends, influential entities, thematic clusters, international collaboration, and research gaps. Explanatory variables of this study include publication year, country origin, document affiliation, author productivity and citation count.

Findings: The results show a sharp increase in publication volume post-2018, indicating increasing academic interest in the intersection between AI and HRM, with strong contributions from institutions with items in the USA, UK, and India. Six major thematic clusters were identified, spanning AI adoption in HRM, decision-making, systematic reviews, ethical considerations, and education-related topics. However, regional imbalances persist, particularly with the underrepresentation of African and MENA contexts. Additionally, the literature often overlooks function-specific HR practices and lacks multidisciplinary depth. This bibliometric mapping concludes that valuable insights for researchers to understand the evolving landscape of AI integration on HRM.

Practical implications: By linking findings to the domain of Industrial Organization, the study highlights how AI reshapes decision-making structures, reallocates managerial authority, and influences organizational power dynamics. These insights inform both academic discourse and HR policy design.

Originality/value: This is one of the few papers that provides a longitudinal bibliometric mapping of AI-HRM research. It offers an organized agenda for future work to promote inclusiveness by geographic scope, discriminant-level detail, and disciplinary integration.

Keywords: Artificial Intelligence, Human Resource Management, Bibliometric Analysis, Industrial Organization, Co-word Mapping, Decision-Making Structures.

De l’intelligence artificielle à la gestion des ressources humaines augmentée : une revue critique des évolutions des pratiques et des défis au Maroc et dans le monde

DADI Nabil — Thu, 17 Jul 2025 00:00:00 +0000

Résumé

Cet article examine l’utilisation et l’impact de l’intelligence artificielle (IA) sur la gestion des ressources humaines (GRH) dans une perspective à la fois internationale et marocaine. La méthodologie adoptée basée sur une revue de littérature critique couvrant les travaux récents (2018–2025), cette approche permet d’identifier les tendances dominantes, les convergences et les divergences entre les différentes sources académiques et professionnelles. Il vise à comprendre comment l’IA transforme les différentes fonctions RH (recrutement, formation, gestion des carrières, etc.) et quels en sont les avantages et les défis. Les études analysées montrent que l’IA peut améliorer l’efficacité des processus RH en automatisant les tâches routinières, en optimisant la prise de décision grâce à l’analyse des données, et en permettant une meilleure adéquation entre les profils des candidats et les postes. Cependant, l’intégration de l’IA dans la GRH soulève également des enjeux majeurs, notamment les biais algorithmiques, la résistance au changement de la part du personnel, et la nécessité de développer de nouvelles compétences au sein des équipes RH pour exploiter ces technologies. En dépit d’un intérêt croissant pour ces outils, notamment au Maroc, leur adoption reste limitée à certaines applications spécifiques. Notre travail met en lumière la nécessité d’une articulation entre l’innovation technologique et le respect des valeurs humaines, et propose des pistes de recherche futures pour accompagner une implantation réussie de l’IA en GRH.

En conclusion, cet article souligne que l’intégration réussie de l’IA en GRH dépend d’un équilibre entre innovation technologique, gouvernance responsable et développement continu des compétences.

Mots clés : : Intelligence artificielle ; gestion des ressources humaines ; transformation digitale ; avantages ; défis ; Maroc

Abstract

This article examines the use and impact of artificial intelligence (AI) on human resource management (HRM) from both international and Moroccan perspectives. The adopted methodology is based on a critical literature review covering recent studies (2018–2025), which allows for the identification of prevailing trends, as well as points of convergence and divergence across academic and professional sources. The objective is to understand how AI is transforming key HR functions such as recruitment, training, and career management along with the associated benefits and challenges. The findings suggest that AI can enhance HR process efficiency by automating routine tasks, improving decision-making through data analysis, and enabling better alignment between candidate profiles and job requirements. However, the integration of AI in HRM also raises significant concerns, including algorithmic bias, employee resistance to change, and the need to develop new skills within HR teams to effectively leverage these technologies. Despite growing interest in AI tools particularly in Morocco their adoption remains limited to specific use cases. This study highlights the importance of balancing technological innovation with the preservation of human values, and offers future research directions to support the successful implementation of AI in HRM.
In conclusion, the article emphasizes that the effective integration of AI in HRM relies on maintaining a balance between technological advancement, responsible governance, and continuous skills development

Keywords : Artificial intelligence; human resource management; digital transformation; benefits; challenges; Morocco