In the face of current environmental, social, and economic crises, the ecological transition of food systems represents a major challenge. In this context, stakeholder engagement is a key element to consider in supporting the transformation of food systems toward more sustainable models. At the same time, digital technologies such as artificial intelligence, the Internet of Things, and blockchain are transforming food supply chains by strengthening traceability, transparency, and efficiency in food-related decision-making. This article presents a scientific literature review with the aim of understanding the relationships between blockchain technology, stakeholder engagement, and the ecological transition of food systems. Drawing on work from management sciences, computer science, and development studies, this study reviews the concepts of digital transformation, stakeholder engagement, ecological transition, and food systems. While blockchain is often presented as a technological solution, this narrative review highlights the importance of adoption conditions, governance, and the participation of all actors involved in food systems. The results make it possible to propose a conceptual framework suggesting that blockchain could play an enabling role in fostering stakeholder engagement in the implementation of the ecological transition of food systems. This paper opens avenues for empirical researches on the contributions and application of blockchain in transition projects.

Social media is a crucial tool for small business owners to interact with their customers and influence consumer behavior in a rapidly evolving digital landscape.

This study investigates the influence of digital storytelling and brand resonance on the purchase intentions of consumers who engage with Egyptian small business owners on social media platforms. Methodology: This study utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the expected relationships based on survey data collected from 123 social media users in Egypt. The findings indicate that brand resonance serves as a stronger predictor of purchase intention, although both digital storytelling and brand resonance exhibit positive and significant effects. The intention to purchase is significantly affected by the narrative structure and the perceived ethics of digital storytelling elements. The impact of perceived aesthetics is minimal. Furthermore, the dimensions of attitudinal attachment and sense of community exhibit no significant direct effect, whereas active engagement and behavioral loyalty are identified as the most significant aspects of brand resonance. The model explains a significant amount of the variance in purchase intention (R2 = 0.817), highlighting the necessity of enhancing strong consumer-brand interactions within social media contexts. The findings enhance the current literature on digital marketing and branding by providing evidence from an emerging market context, suggesting that narrative alone is insufficient to influence purchase behavior unless it is converted into authentic brand resonance. The findings have significant implications for entrepreneurs aiming to enhance customer engagement, loyalty, and purchase intention through the use of authentic and ethical storytelling strategies.

Ghana’s data centre ecosystem faces persistent infrastructure, regulatory, and human-capacity challenges that limit its capacity to support data warehousing and enterprise analytics. Guided by the Technology-Organisation-Environment (TOE) framework, this study examines how technological, organisational, and environmental constraints influence the development and performance of data-driven systems within the country. A mixed-methods approach was adopted, combining qualitative interviews with key stakeholders and analysis of infrastructure indicators such as power reliability, connectivity, and data centre capacity. The findings reveal four major barriers: unreliable electricity supply, high operational costs associated with cooling, fragmented regulatory frameworks, and a shortage of skilled technical personnel. These challenges contribute to fragmented data environments, limited interoperability, and reduced effectiveness of data warehousing systems. Financial constraints and weak data governance practices further limit the adoption of advanced analytics and artificial intelligence technologies. As a result, organisations struggle to leverage data as a strategic asset. The study highlights the need for coordinated policy reforms, investment in digital infrastructure, and targeted capacity development. It contributes to the literature by applying the TOE framework to a resource-constrained context and by offering practical insights to strengthen enterprise analytics capabilities in Ghana.

The gig and platform economies' explosive expansion has completely changed the nature of traditional work relationships and the function of human resource management (HRM). Instead of using traditional supervisory structures, digital platforms are depending more and more on independent contractors, freelancers, and contingent labor who are handled by algorithmic systems. This change has made it more difficult for businesses to develop HRM strategies that maintain flexibility and efficiency while guaranteeing employee engagement, well-being, and performance. The current study creates an integrated paradigm that looks at how algorithmic openness, perceived organizational support, and AI-enabled HRM practices affect gig worker outcomes. The study suggests that engagement and well-being mediate the relationship between HRM practices and gig worker performance, drawing on Social Exchange Theory, Job Demands–Resources (JD-R) theory, and platform ecosystem perspectives.

It is suggested that data be gathered from platform-based gig workers in various service industries using a quantitative study design. To test the proposed relationships, structural equation modeling with SmartPLS is recommended. By applying HRM theory to non-traditional employment arrangements and highlighting the significance of ethical and sustainable HR practices in digitally mediated work environments, the study adds to the growing body of literature on the future of work. The results should show that while AI-enabled HR solutions increase productivity, they still need organizational support and transparency to improve worker outcomes. For businesses looking to efficiently manage gig workers while guaranteeing long-term workforce sustainability, the study offers theoretical and practical consequences.

In recent years, there has been increasing attention toward sustainability practices and the integration of Environmental, Social and Governance practices into operational strategies and investment decisions. Despite the growing interest from policymakers, managers, investors and other stakeholders, the financial consequences of adopting ESG initiatives remain unclear, generating inconclusive empirical evidence about their impact on overall firm financial performance.

Considering the current landscape, the aim of thi

.s study is to investigate the influence of the combined Environmental, Social and Governance (ESG) score on firms’ investment returns. It compares Financial (FI) and Non-Financial Institutions (NFI), underscoring the effect of ESG initiatives on investment performance across sectors. The research also sheds light on the MENA region as it is insufficiently addressed and is currently transitioning to adopting ESG frameworks.

To achieve this objective, Generalized Method of Moments (GMM) regression is applied on a panel dataset of 89 listed FI and NFI in the Middle East and North Africa (MENA) region spanning 2010-2022 to assess the impact of combined ESG on Total Investment Returns (TIR) in the examined sectors. The findings reveal that the impact of the combined ESG score is sector-dependent, having heterogeneous effect within the contexts of FI and NFI.

This study contributes to current literature theoretically by empirically examining the effect of ESG scores on TIR, while accounting for sectoral differences in the underrepresented MENA region. The findings also provide practical implications for various users. For policymakers, it highlights the need to create a standardized ESG evaluation framework as well as mandating consistent and periodic disclosure of ESG information. Enhanced transparency in understanding ESG dynamics and their impact on TIR provides managers and investors with more reliable information, enabling them to make more informed decisions.

As countries address the threat of climate change, many developing economies are diversifying their resources. Understanding the association between progress in green innovation and stock market valuation is therefore important for the transition to a low-carbon economy. This study examines the influence of green innovation at the country level on the market value of domestic listed firms across 11 Middle East and North Africa (MENA) countries from 2014 to 2023. The findings reveal a paradoxical relationship between innovation and market valuation. Although a positive correlation suggests that sustainability signals stock market strength, the regression results indicate a negative, statistically significant effect when heterogeneity and endogeneity are controlled for. These results indicate that country heterogeneity matters and that green innovation currently imposes a short-term financial burden rather than generating a valuation premium in MENA stock markets. This may reflect high costs and the reallocation of resources towards conventional energy and research and development (R&D), positioning these economies in the early phase of the transition to a low-carbon economy. This paper contributes to the literature by identifying green innovation development as a significant determinant of stock market valuation. It also suggests that policymakers should prioritise policy-led development, including intellectual property protection, R&D subsidies, and tax credits, to offset transition costs and help green innovation to strengthen stock market resilience and achieve low-carbon economies in the MENA region.

Health diplomacy has emerged as a central mechanism for advancing global health objectives, facilitating international cooperation, and addressing health inequities in an increasingly interconnected world. This systematic review examines the contemporary landscape of health diplomacy, with particular emphasis on how localization strategies and export-oriented manufacturing frameworks are reshaping diplomatic health engagement. A comprehensive search of the Scopus database using terms encompassing health diplomacy, medical diplomacy, pharmaceutical diplomacy, global health governance, health foreign policy, soft power health, vaccine diplomacy, health aid, and health cooperation yielded 1,228 records. Following a two-stage screening process guided by PRISMA principles, filtering first for review article type and then for social science and interdisciplinary perspectives, 23 articles were identified, of which 13 directly relevant to the core themes of health diplomacy, governance, localization, and equity were included in the qualitative synthesis. Findings indicate that health diplomatic strategies broadly cluster around four actor-driven roles: state-facilitated vaccine and pharmaceutical diplomacy, aid and soft-power diplomacy, multilateral governance mechanisms, and localization and capacity-building initiatives. Significant challenges emerge across all clusters, including geopolitical power asymmetries, vaccine nationalism, governance deficits within international organizations, and persistent dependency relationships in pharmaceutical manufacturing. Mixed results are observed across dimensions of social, economic, and environmental upgrading, with equity outcomes frequently subordinated to national strategic interests. This review argues that effective health diplomacy requires a multi-scalar, actor-inclusive approach that integrates local manufacturing capacity, transparent multilateral governance, and equity-centered frameworks to achieve durable global health outcomes.

This study examines the evolving role of Artificial Intelligence (AI) in Business Process Outsourcing (BPO) by integrating a systematic literature review with k-means text clustering enriched with large language model sentence embeddings, SBERT. Reviewing 21 studies published between 2015 and 2026, the research identifies eight thematic directions shaping AI adoption in BPO: AI use in SMEs, AI outsourcing models, generative AI–enabled transformation, crowdsourcing for data and competency development, impacts of AI on job restructuring, ethical and social considerations in impact sourcing, trade-offs between in house and proprietary AI models, and emerging competency requirements for future professionals. Using SBERT embeddings and k-means clustering, the study uncovers dominant patterns of scholarly focus, revealing that SMEs increasingly rely on outsourced AI services to overcome resource constraints, while larger organizations deploy AI to optimize operations, enhance decision making, and restructure governance models. Findings also show that Generative AI is reshaping workforce roles and accelerating hybrid human–AI collaboration, yet raising concerns around ethics, privacy, and digital security. The study contributes a data-driven synthesis of AI-related research trends in the BPO domain and proposes a set of future research directions addressing human–AI collaboration, regulatory frameworks, SME adoption roadmaps, next-generation BPO models, workforce transformation, AI platform selection criteria, and cybersecurity resilience. Overall, the results highlight AI's central role in transforming global outsourcing ecosystems and underscore the need for strategic, responsible, and capability-driven adoption.

In an era of rapid change and resulting economic disparities, particularly among emerging economies, artificial intelligence (AI) and digital transformation are crucial for navigating these shifts. This study highlights that digital transformation necessitates AI to achieve Sustainable Development Goals (SDGs). This underscores the importance of research exploring the synergistic relationship between AI and digital transformation as key drivers for achieving the SDGs in emerging economies. While previous studies have addressed these two technologies separately, this study employs an empirical framework based on ordinary least squares (OLS) data analysis of 25 emerging markets in the year 2023, using data available from the World Bank. The findings indicate that increased AI readiness is associated with improved governance efficiency, leading to better SDG outcomes. The results emphasize that for AI to become a true driver of sustainable development, policy frameworks must prioritize AI capabilities and good governance to mitigate the risks of the new digital expansion. This analysis provides a roadmap for policymakers to align investments with long-term environmental and social justice.

Gamification in human resource management (HRM) is emerging as a valuable tool for enhancing performance and engagement among educators in Egypt's education sector. By applying game design elements within HRM systems—such as points, leaderboards, badges, and rewards— educational institutions can create a more dynamic and motivating work environment. A survey involving 151 HR professionals will explore the integration of gamification in key HR functions and assess its perceived impact on employee performance. Preliminary findings indicate a significant positive effect of gamification on employee outcomes, though there are challenges to implementation, including alignment with organizational culture and issues of fairness and engagement. The study aims to provide practical insights for designing effective gamification strategies in HRM within Egyptian educational settings.

This paper explores how ethical AI governance within human resource management can strengthen organisational strategy in an era of rapid digital transformation. As organisations increasingly integrate AI into recruitment, performance management, and decision‑making systems, concerns arise regarding fairness, transparency, and employee trust. The study employs a qualitative empirical study to examine how responsible AI practices can be designed and implemented within HRM. Key findings indicate that ethical AI governance is perceived as essential for enhancing organisational credibility, supporting fair talent processes, and reducing risks associated with bias and excessive monitoring. The analysis also shows that HRM plays a strategic role in aligning AI use with organisational values, shaping capability development, and fostering a culture that balances technological efficiency with human‑centred principles. The paper offers practical guidance for HR practitioners seeking to implement responsible AI policies that contribute to sustainable organisational performance.

Worker remittances constitute Egypt's largest single source of foreign exchange, yet the country's merchandise trade balance has remained structurally in deficit throughout a period of sustained remittance growth. This paper investigates whether remittance inflows worsen Egypt's trade balance, whether financial development moderates this relationship, and whether the trade balance responses to positive and negative remittance shocks are symmetric.

Using quarterly time series data spanning 2006Q1 to 2025Q3 — 79 observations encompassing four exchange rate regime shifts and three IMF programme episodes — the study estimates a Nonlinear Autoregressive Distributed Lag (NARDL) model that decomposes remittances into positive and negative partial sum series, incorporates an explicit remittance–financial development interaction term, and controls for structural breaks associated with the 2016 EGP float, the 2022–2023 parallel market crisis, and the 2024 IMF Extended Fund Facility.

The bounds test confirms long-run cointegration among all model variables. A one percentage point increase in remittances as a share of GDP is associated with a 3.228 percentage point deterioration in the trade balance in the long run, consistent with the boomerang hypothesis. Financial development significantly attenuates this effect in the short run, though the long-run moderating channel remains constrained by Egypt's historically shallow credit markets. A Wald test confirms strong asymmetry: remittance surges inflict larger and more persistent trade balance damage than equivalent contractions provide relief, with each boom–bust cycle leaving a residual structural deterioration. The 2016 EGP float emerges as the dominant structural break, exerting a coefficient of −5.548 that dwarfs all other determinants.

These findings imply that policies maximising remittance inflows carry a hidden trade balance cost not offset during downturns. Expanding household access to domestic financial instruments and diversifying Egypt's export base are identified as necessary conditions for breaking the remittance–trade balance trap under the current IMF programme.

Climate change, political-social-economic-ecological and sustainability issues are 21^st Century realities, which call for innovative teaching/learning processes in teaching Economics for it to be a vehicle for sustainability learning. There is a need to consciously develop a structure of economics knowledge and education (curriculum and teaching approaches) that provides students with a foundation for sustainability transition, so that students become change agents while they learn. A transdisciplinary approach was used for sustainability learning in an Economics module where guest lectures were presented by a local Municipality and a local businessperson to link some economic theories to some socio-economic-political-ecological sustainability issues, and how the Agricultural sector and Government handle such issues. This allowed for a more holistic understanding and helped students to develop flexible thinking for problem-solving solutions that are crucial for addressing sustainability challenges in an ever-evolving world. Adopting transdisciplinary approaches to teaching Economics for sustainability learning have a complementary role to the traditional discipline-specific ways of teaching Economics because sustainability challenges are complex and dynamic, and thus require integrating diverse perspectives and knowledge by using different knowledge sources.

Purpose: This study introduces the concept of the AITIM Bridge, an innovative model that explains the ways in which the outputs generated by an artificial intelligence system might be incorporated into strategic talent management systems to ensure the sustainable development of athletes in sport. This study addresses the gap between AI-enabled talent identification and the organisational processes governing athlete development, wellbeing, and retention through a structured interdisciplinary synthesis of sport management, artificial intelligence, and organisational literature (Moher et al., 2009; Tranfield et al., 2003; Torraco, 2005). The current investigation was designed to address the gap between the potential offered by the use of AI in talent identification and the organisational processes through which athlete development, wellbeing, and retention are managed.

Design/methodology: The qualitative-dominant systematic literature review was conducted using the PRISMA method, thematic comparison, cross-study pattern analysis, and conceptual integration, searching the Scopus, Web of Science, SPORTDiscus, and Google Scholar databases, and using the inclusion criteria to identify relevant literature published between 2005 and 2025.

Findings: The literature is fragmented across three relatively disconnected areas of sport management, artificial intelligence, and organisational studies, with the areas of talent management and athlete wellbeing and retention being relatively less well-represented in the literature. The literature on the use of AI in talent identification focuses on the efficiency and data capture potential offered by the technology, while the literature on talent management focuses on the need for interdisciplinary support and organisational fit, although little attention is given to the mediation process by which the outputs generated by the technology might be filtered before being fed into the athlete development process.

Practical implications and conclusions: The AITIM Bridge is an innovative model that explains the ways in which the outputs generated by an artificial intelligence system might be incorporated into strategic talent management systems to ensure the sustainable development of athletes in sport. The model recasts the use of AI as an organisational competency, rather than an autonomous recruitment tool, and provides sport organisations with the opportunity to develop a system through which the use of technology might be governed.