Search Results (149)

This study examines the interplay among ICT skills, perceptions of employability, and entrepreneurial intention among university students, focusing on how generic and scarce ICT competencies influence their confidence in employment opportunities and their inclination toward entrepreneurial intentions. Drawing on the Theory of Planned Behaviour, the study explores how digital competencies shape entrepreneurial attitudes, perceived feasibility, and behavioural readiness. A quantitative research approach was adopted, and data were collected using a convenience sampling method from 117 university students enrolled in ICT-related programmes. A reliability analysis, exploratory factor analysis, correlation analysis, regression analysis, and chi-square tests were used to examine the relationships among ICT skills, employability perceptions, and entrepreneurial constructs. Findings reveal that students possess strong generic ICT skills and high self-efficacy, suggesting confidence in their general capabilities and labour market readiness. However, scarce ICT skills were found to be unevenly distributed across departments and campuses, indicating disparities in access to advanced technical training. Regression results show that both generic ICT skills (β = 0.27, p < 0.01) and scarce ICT skills (β = 0.34, p < 0.001) significantly predict employability (R² = 0.29), while generic (β = 0.29, p < 0.01) and scarce ICT skills (β = 0.46, p < 0.001) significantly influence perceived feasibility (R² = 0.41). Furthermore, employability (β = 0.31, p < 0.01) and perceived feasibility (β = 0.25, p < 0.05) significantly predict entrepreneurial intention (R² = 0.27). The results also show strong entrepreneurial desirability among students, yet perceived feasibility remains comparatively low, highlighting a gap between entrepreneurial aspiration and perceived capability. Importantly, advanced ICT competencies strengthen students’ confidence in their ability to pursue entrepreneurial activities. The study concludes that strengthening scarce ICT competencies, experiential entrepreneurship education, and industry collaboration within higher education institutions is essential for enhancing graduate employability and entrepreneurial potential in South Africa. Full article

The integration of generative artificial intelligence (GAI) into digital learning environments is a profound socio-technical transformation. While GAI promises enhanced accessibility and efficiency, it simultaneously obscures the human creativity and intellectual labour that underpins digital knowledge production. This opacity limits creators’ visibility into how their work is used, evaluated, and monetised. This review application work investigates how several leading large language models, including ChatGPT (GPT-4o), Gemini (1.5 Flash), and DeepSeek (V3), interact with a creative platform hosting over 300 original essays, poems, and artworks from various human creatives. Our review reveals that despite clear evidence of models engaging with original materials, standard platform analytics of the average creative record no attribution, referrals, or traceable interaction from their end, rendering creators’ labour invisible. This compels critical examination of knowledge provenance and power within AI-mediated education. To address this, we propose a socio-technical framework, Chujoyi-TraceNet, not as a technical fix, but a mechanism to re-centre ethics, justice, and recognition in digital governance. By integrating real-time tracking, blockchain-enabled licensing, and metadata watermarking, Chujoyi-TraceNet operationalises the principles of equitable attribution. This study argues for a re-imagining of digital ecosystems in education, one that links the technical act of attribution to broader debates on digital labour, platform ethics, and the pursuit of social justice, thereby contributing to more democratic and accountable learning media in the era of Industry 4.0 and 5.0. Full article

The accelerated expansion of artificial intelligence (AI) is reshaping economic systems, labour markets and democratic life, giving rise to hybrid human–AI societies. In this context, education becomes a strategic arena for enabling sustainable and socially just transitions within the Fourth Industrial Revolution. This article examines how digital competence can be reconceptualized to prepare future citizens and educators for these emerging societal configurations, with particular attention to the Ibero-American context. A conceptual framework is proposed that integrates algorithmic literacy, critical data awareness, AI ethics, human–AI collaboration skills, and civic and socio-emotional capacities as core dimensions of “next-decade” digital competence. Methodologically, the study combines three complementary approaches: (a) a structured review of interdisciplinary literature on AI, digital competence and sustainability; (b) an analysis of international and regional policy documents and competence frameworks relevant to Ibero-America; and (c) selected empirical insights drawn from the first author’s doctoral research on digital competence and AI use in teacher education. The findings reveal significant tensions between rapid AI adoption and persistent structural inequalities in the Global South, while identifying key leverage points for aligning teacher education, public policy and institutional strategies with the Sustainable Development Goals. The proposed framework aims to support policymakers, universities and international organizations in fostering inclusive and sustainable AI-driven social change while mitigating new forms of exclusion and dependency. Full article

Road maintenance remains one of the most resource-intensive and hazardous operations in infrastructure management. Traditional inspection practices rely heavily on manual labour and discrete procedures, often resulting in limited scalability, operator exposure to traffic hazards, and inefficiencies in data collection. This paper presents a novel automated methodology that integrates Unmanned Aerial Vehicles (UAVs) and autonomous mobile robots (AMRs) to enable automated inspection and measurement of road assets through a digital twin (DT) system. The system leverages data fusion and real-time synchronisation between field agents and a centralised digital twin to monitor the retro-reflectivity of vertical and horizontal signage, detect obstacles and vegetation, and support data-driven maintenance planning. A case study conducted on the Italian highway network demonstrated improvements in operational safety, inspection efficiency, and measurement consistency. The results confirm that the integration of UAVs and AMRs within a digital twin framework can significantly improve sustainability, productivity, and workers’ safety in road maintenance operations. Full article

This article examines how algorithmic mediation reshapes social trust and solidarity in the post-secular age. Historically grounded in shared moral horizons shaped by religion, tradition, and communal practices, trust has increasingly been displaced by technocratic governance, market rationality, and algorithmic systems that mediate work, cognition, communication, and political life. Through a critical analysis of contemporary developments—including algorithmic labour management, neurotechnology, large language models, digital public spheres, technological sovereignty, and global AI governance—the article argues that algorithmic mediation intensifies the fragility of trust by instrumentalizing human agency, fragmenting public reason, and concentrating power within opaque technological infrastructures. Against technological determinism and purely procedural approaches to ethics, the article advances a normative framework rooted in solidarity and the common good. Drawing on post-secular perspectives, a retrieval of natural law normativity, and the resources of Catholic Social Teaching, it contends that trust cannot be sustained through efficiency, prediction, or regulation alone. Instead, social trust depends upon relational goods—dignity, responsibility, participation, and truth—that resist reduction to data-driven optimization. Reclaiming solidarity therefore requires re-embedding AI within moral horizons capable of guiding technological development toward integral human flourishing. In this sense, the governance of AI emerges not merely as a technical challenge but as a decisive moral and political task for post-secular societies. Full article

Production diseases in dairy cattle impose economic and welfare burdens, yet few studies quantify costs using on-farm cases. This study aimed to estimate costs and lost revenues at the individual-animal level in 10 German dairy farms (average of 592 cows; 9694 kg marketed milk/cow/year; 32.9% culling rate). Each farm was visited for three weeks; diseased cows and calves were examined by a trained veterinarian. Diagnoses, treatments, labour times, and outcomes were recorded, and costs calculated for labour, products, veterinary and orthopaedic services, discarded milk, decreased milk yield, culling, book loss, and reduced carcass value. In total, 1272 single-animal cases were included: 68% were stand-alone diseases, 11% involved multiple diagnoses within one organ system, and 21% affected several organ systems. When several diseases occurred in the same animal, total costs and lost revenues were greater than the sum of stand-alone cases, indicating compounding effects. High-impact conditions included mastitis, claw disorders, left displaced abomasum, and multimorbidity; per-case losses ranged from €43 (digital dermatitis) to >€1200 (left displaced abomasum with complications). Labour and culling-related costs were higher than reported, and productivity losses exceeded treatment costs in many cases. Findings support farm-level decision-making, prevention, and parameterization of future dynamic models. Full article

This study maps European countries’ resilience to cognitive warfare by developing a cross-national composite measure. The framework integrates three pillars: information ecology, institutional-digital capacity, and socioeconomic context—drawing on a systemic perspective linking social structures to societal functions. Publicly available secondary indicators are compiled from online sources for EU (European Union) and EEA (European Economics Area) states. The dataset is examined through descriptive analysis, association testing, multivariate modelling, dimensionality reduction to derive a composite resilience score, and unsupervised clustering to produce a country typology. Indicators capture governance effectiveness, e-government maturity, public-sector AI (Artificial Intelligence) readiness, digital connectivity and infrastructure, media freedom and broader media-ecosystem quality, academic freedom, and socioeconomic vulnerabilities such as youth labour market exclusion. Results show that resilience aligns most strongly with institutional capacity and governance performance; a healthy ecology acts as a reinforcing layer. Digital infrastructure appears necessary but insufficient without capable, credible institutions and coherent public policy. Socioeconomic vulnerabilities tend to erode resilience and heighten susceptibility to hostile cognitive influence. The study concludes that policy efforts should prioritise governance integrity and effectiveness, end-to-end digital government, responsible public-sector AI capability, and safeguards for media and academic autonomy, alongside measures that improve youth inclusion. Full article

Graduate employability has become a central concern for higher education institutions as labour markets undergo rapid transformation driven by digitalisation, technological change, and evolving organisational practices. Universities are increasingly expected to equip graduates with a broad range of employability skills and to collaborate with industry to enhance labour market readiness. However, existing research on employability skills development and university-industry collaboration remains fragmented across disciplines, contexts, and stakeholder perspectives. This systematic review synthesises evidence on how universities prepare their graduates for the labour market through employability skills development and university-industry collaboration. Following PRISMA guidelines, 84 journal articles and conference papers published between 2015 and 2025 were identified through a systematic search of the Scopus database and analysed thematically. The findings reveal that graduate employability is conceptualised as a multidimensional and context-dependent construct encompassing discipline-specific, transversal, digital, career management, and professional disposition-related skills. Employability skills development is most strongly supported through pedagogical approaches that emphasise authentic engagement with professional contexts, including work-integrated learning, project- and challenge-based learning, and technology-mediated collaboration. Reported outcomes extend beyond immediate employment metrics to include enhanced confidence, skills acquisition, employability awareness, curriculum relevance, and organisational learning. However, the effectiveness and sustainability of these initiatives are shaped by structural and institutional conditions, including policy frameworks, resourcing, partnership coordination, and equity of access. The review contributes an integrative synthesis that connects employability skills, pedagogical design, and university-industry collaboration, and outlines implications for policy, educational practice, and future research. Full article

This study investigates how pandemic-induced digitalisation, understood as the transition to remote work combined with the enforced use of digital tools and the reconfiguration of tasks and digital skills at the job level, has affected job security and job quality in Portugal. In 2022, a nationwide survey was administered to employees in companies registered in the country, yielding 2001 valid responses through a stratified random sampling strategy that ensured representation across different firm sizes. Structural equation modelling (PLS-SEM) was used to examine the relationships between digitalisation (independent construct) and perceived job quality and job security (dependent constructs), while controlling for demographic, organisational, and work-regime characteristics. Digitalisation had a significant positive effect on perceived job quality but no systematic effect on perceived job security. The results also revealed more positive perceptions of job security among women, employees in smaller firms, and those working on-site, whereas directors and workers in the Lisbon Metropolitan Area reported greater negative effects. These findings underscore the importance of contextual factors in shaping how workers experience digitalisation and provide evidence to inform public policies aimed at promoting job security and job quality in a post-COVID-19 labour market. Full article

Demographic ageing, a topic that is intensively addressed in the scientific literature, significantly influences the functioning of economic systems. Demographic ageing directly impacts the labour supply, productivity, savings, investments and the sustainability of public finances through pressure on pension and health systems. However, the efforts of ageing societies to transform and adapt to this demographic challenge through economic restructuring and innovation are recognized. Starting from the growing interest shown in the link between the demographic transformation of a society and the economic impact, the study carries out a bibliometric analysis on a dataset of 934 documents included in the OpenAlex platform, selected by filtering scientific publications according to a set of predefined criteria. The analysis of thematic clusters, co-authorship and bibliographic coupling reveals an increase in interdisciplinary research and a shift in emphasis from classical macroeconomic effects on the labour market and the financial system towards multidimensional transformations of the economic and social system, in which demographic transformation is no longer just a constraint but also a challenge towards progress through the integration of digitalization, automation and transition to AI-based economic systems to support economic development. Full article

Despite significant advances in digital surveying technologies, Heritage Building Information Modelling (HBIM) remains constrained by labour-intensive processing, fragmented classification systems, and limited standardised pathways for integrating Artificial Intelligence (AI). The absence of a systematic and standardised roadmap for AI adoption has limited both academic progress and industrial implementation. This paper proposes a comprehensive AI implementation roadmap for automated HBIM, developed through iterative research and empirical experimentation on UK heritage case studies. Building upon Design Science Research (DSR) principles, the roadmap delineates the critical dependencies among classification systems, data acquisition, algorithmic segmentation, and geometry generation, while embedding the Five HBIM Motivations, revival, restoration, restitution, retrofit, and resilience, as the primary structuring device for project intent. The study synthesises experimental findings into a practical, ISO 19650-aligned framework capable of guiding AI integration at both strategic and operational levels. An AI-enabled HBIM Execution Plan is presented as an implementation mechanism, enabling project teams to align digital workflows with heritage objectives, classification structures, and computational capacities. Evaluation through expert interviews confirms the roadmap’s feasibility, adaptability, and potential to enhance documentation efficiency, semantic richness, and interdisciplinary collaboration. The paper contributes a robust, scalable, and standards-compliant methodology for embedding AI in HBIM, offering a pivotal reference for the UK cultural heritage sector and a template for international replication. Full article

Generative artificial intelligence increasingly mediates how individuals interpret information, perform cognitive tasks, and participate in economic and political life. While such systems promise efficiency and expanded access to knowledge, their societal effects are unevenly distributed. This article develops the concept of societal bifurcation to explain an emerging structural divergence between a cognitively resilient minority, capable of integrating AI reflectively, and a cognitively dependent majority, whose reliance on automated interpretation reduces interpretative autonomy. Drawing on contemporary empirical evidence from cognitive science, labour research, and human–AI interaction studies, the article shows how unstructured AI use diminishes metacognitive monitoring and inflates confidence, while labour-market restructuring amplifies differences in adaptability and resilience. These cognitive and economic dynamics interact with an increasingly fragile democratic information environment shaped by synthetic communication and declining epistemic trust. The article argues that these processes form a self-reinforcing sociotechnical mechanism through which cognitive dependency, economic inequality, and democratic vulnerability become mutually constitutive. By conceptualising societal bifurcation as a distinct analytical framework, the article contributes to sociological and science and technology studies debates on inequality, agency, and governance in AI-mediated societies, while highlighting the importance of sustaining interpretative autonomy in the age of generative AI. Full article

This study analyses the adoption of artificial intelligence (AI) in enterprises in Slovakia in comparison with the EU27 and examines its relationship with labour productivity from the perspective of long-term economic sustainability. Using harmonised Eurostat data for the period 2021–2024, the analysis applies descriptive statistics, gap analysis, dynamics of change, correlation analysis, and an illustrative regression model. The results show that although AI adoption in Slovakia increased across all enterprise size classes, it consistently remained below the EU27 average. Labour productivity developments in Slovakia were characterised by substantial short-term volatility and did not show a stable association with AI diffusion. Both correlation and illustrative regression results confirm the absence of an immediate statistical relationship between AI adoption and productivity at the aggregate level. These findings suggest that potential productivity improvements associated with AI adoption are likely to depend on complementary investments in organisational transformation, digital skills, and institutional capacity. The study provides empirical evidence for a small open economy within the EU and offers policy-relevant insights into how AI adoption is more likely to support long-term economic sustainability than short-term performance gain. Full article

The digital carbon footprint denotes the environmental impact generated by digital technologies throughout their lifecycle. Industry 4.0 manufacturing environments rely extensively on data processing, information storage, and artificial intelligence, thereby increasing energy demand and associated carbon emissions. These conditions have intensified interest in Green AI, particularly in applications such as predictive maintenance and collaborative human–machine systems. This research investigates determinants of behavioural intention to adopt Green AI through an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model tailored to Industry 4.0 and sustainability contexts. The framework incorporates performance expectancy, Industry 4.0 eligibility, technology influence, digital manufacturing competence, sustainability conditions, Green AI recognition, and green manufacturing concern. Data were obtained from an anonymous survey of 1003 Generation Z students enrolled in technical disciplines and preparing for manufacturing-oriented careers. Relationships among constructs were analysed using partial least squares structural equation modelling (PLS-SEM). The model demonstrates strong explanatory and predictive capability. Adoption intention is primarily associated with performance expectancy, Industry 4.0 eligibility, and digital manufacturing competence, while sustainability-oriented perceptions play a contextual rather than direct behavioural role. The study offers a domain-specific empirical extension of UTAUT within pre-workforce technical education rather than proposing a new acceptance theory. The findings reflect intention formation prior to labour-market entry and require validation in operational manufacturing settings before broader generalisation. Full article

The rapid expansion of the gig economy is reshaping work globally, producing both new opportunities and significant challenges for workers across diverse regions. This scoping review mapped global evidence on gig workers’ experiences between 2018 and 2024, following PRISMA-ScR guidelines. A comprehensive search of academic databases (EBSCOhost, Scopus, Sage, Springer, Taylor & Francis, Wiley, and Google Scholar) was conducted, yielding 1986 records, of which 26 met the inclusion criteria. Data were charted and synthesised to identify patterns in how gig workers describe their work experiences within broader socioeconomic and platform-based structures. Three interconnected themes emerged. First, freedom and flexibility remain central attractions of gig work, particularly for younger workers who value autonomy, scheduling control, and opportunities for combining multiple income streams. Second, gig work experiences vary significantly across demographic and geographic contexts, revealing unequal pathways shaped by gender, education, skill, migration status, and national labour-market conditions. Third, across all gig-work categories, workers reported precarity, including inconsistent income, job insecurity, algorithmic surveillance, limited benefits, and emotional strain. Taken together, the findings illustrate how autonomy and vulnerability coexist within the gig economy, highlighting the importance of policies and supports that address intersecting forms of inequality and promote safe, stable, and dignified work in a rapidly evolving labour landscape. Full article