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This study aims to investigate how specific graduate attributes relate to university students’ employability and entrepreneurial intentions, with a focus on higher education institutions in the United Arab Emirates (UAE). The research distinguishes between traditional and emerging attributes and examines their predictive value for distinct post-graduation pathways. A quantitative, cross-sectional survey design was adopted. Data were collected from 524 undergraduate students and analysed using multivariate multiple regression to assess the simultaneous effects of nine graduate attributes. The findings reveal that employability intention is significantly are associated with goal-directed behaviour, continuous learning, problem-solving, and the ability to present and apply information. Entrepreneurial intention, on the other hand, is more strongly predicted by enterprising behaviour, analytical thinking, and artificial intelligence literacy. Some attributes, such as ethical responsibility and interactive communication, were not significant predictors. University prestige had a minor but significant effect on employability intention, while the presence of a university incubator showed no significant relation. This study contributes to the theoretical development of graduate attribute frameworks by validating digital-era competencies and empirically distinguishing between employability and entrepreneurial orientations. It offers practical insights for higher education institutions seeking to develop curricula that better prepare graduates for diverse career outcomes.

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ABSTRACT SMEs in developing economies operate under persistently volatile environments where economic instability, regulatory uncertainte and technological disruptions threaten their survival. Here, sustainability shifts from long-term environmental or socioeconomic performance to strategic resilience. In this study, we investigate how dynamic capabilities condition the effect of business environmental forces on SME sustainability in Nigeria. Grounded in contingency and dynamic capability theory, this study adopts a quantitative, cross-sectional survey design using data from 285 Nigerian SMEs. It examines the direct effects of economic, legal and technological environmental forces, as well as the moderating roles of sensing and seizing, and learning and reconfiguration capabilities, on SME strategic resilience using PLS-SEM. The results show that economic, legal and technological turbulence significantly affect SME strategic resilience, with legal turbulence emerging as the strongest constraint. Findings further reveal that dynamic capabilities–sensing and seizing, learning and reconfiguration–significantly moderate the effect of environmental turbulence on SME strategic resilience and strengthen SME capacity in absorbing shocks, reconfiguring resources and sustaining operations under disruptions. This study contributes by reframing SME sustainability as strategic resilience amid environmental turbulence, differentiating external pressures into economic, legal and technological dimensions, and showing how dynamic capability bundles condition SME strategic resilience in a highly volatile developing-economy context. This study offers insights relevant to other emerging economies characterised by institutional instability, policy unpredictability and uneven technological development. It also broadens understanding of contingency and dynamic capability theory in developing economies and positions dynamic capabilities as vital for resilience-building, not just competitive advantage.

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Understanding how structural change drives long-run growth requires jointly considering the dynamics of productive and scientific specialisations, and science-industry alignment. This paper develops and tests a unified framework that integrates evolutionary, structuralist, complexity, and innovation-systems perspectives to assess how productive and scientific specialisations, science-industry alignment, diversification, and global value chain integration shape economic performance. To operationalize this framework, we construct new indicators, including a Science-Industry Matching (SIM) index, measures of dynamic entry and relatedness density, and specialisation-based diversity indices, and apply them to a panel of up to 142 countries over 2000-2018/2023. Estimation relies on country fixed effects with Driscoll-Kraay standard errors to address heteroskedasticity, autocorrelation, and cross-sectional dependence. The results reveal that persistent specialisation in high- and medium-high-tech industries fosters growth, while low-tech dependence constrains it. Scientific specialisation in enabling fields such as mathematics, physics, chemistry, and energy/environmental sciences supports growth, but excessive concentration risks lock-in. Science-industry alignment enhances growth in advanced economies with strong absorptive capacity but penalises weaker systems. Industrial diversification often dilutes resources, whereas scientific diversification consistently promotes growth by broadening the knowledge base for recombination. Finally, integration into global value chains is growth-enhancing in developing economies, while advanced economies can sustain higher domestic value added without significant penalties.

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This study provides a comprehensive quantitative review of the determinants of aggregate productivity growth using bibliometric and network-based methods. Drawing on 523 peer-reviewed articles published between 1973 and 2024 in Scopus and Web of Science, the study systematically maps the intellectual foundations, research fronts, and conceptual evolution of the field. Results show that research has remained overwhelmingly macro-focused, with 85%-90% of studies addressing aggregate-level determinants. Innovation, institutions, and technology diffusion dominate the literature, while firm-level (microeconomic) explanations, though increasing since the mid-2000s, remain secondary, largely addressing resource allocation. Competition, firm-level innovation, and organizational capabilities are underexplored despite their relevance for aggregate outcomes. By combining co-citation, bibliographic coupling, and keyword co-occurrence analyses, the study reveals the multilevel structure of productivity research, illustrating how macro theories, meso-level sectoral mechanisms, and micro-level firm dynamics interact. These findings highlight the limits of macro-centric explanations of productivity slowdowns and underscore the need to explore cross-level mechanisms, firm heterogeneity, and institutional interactions. This study offers a novel methodological benchmark and a structured agenda for research and policy, aiming to enhance productivity growth.