Search Results (507)

Artificial Intelligence (AI) is increasingly embedded in project management within the financial sector, yet existing research remains fragmented and largely focused on isolated technical applications. A systemic understanding of how AI reshapes financial project management as an integrated socio-technical capability is still lacking. This study addresses this gap through a systematic literature review of 62 peer-reviewed articles (2022–2025), combined with BERTopic-based thematic analysis supported by large language model-assisted topic representation. The findings reveal the emergence of Agentic AI as a dominant theme, marking a shift from analytical support tools toward autonomous and collaborative agents embedded in project processes. While predictive analytics and automation are relatively mature, governance-oriented and human-centric dimensions remain underdeveloped and weakly integrated. This study contributes by: (1) presenting a computationally enhanced systematic mapping study that integrates a systematic literature review with BERTopic-based topic modelling to map the evolving research landscape; (2) identifying Agentic AI as a pivotal interface between technical execution and strategic governance; and (3) proposing a socio-technical target architecture that offers a structured roadmap for AI-enabled transformation in financial project management systems. Full article

The complexity of the Water–Energy–Food (WEF) Nexus demands a comprehensive framework for its implementation, particularly concerning place-based governance and sustainable transitions. In this work, the WEF Nexus is conceptualized through the lens of Socio-Technical Systems Transition Theory and its interconnections with geo-ecological system components, enabling its recognition as a place-based Socio-Technical–Ecological meta-System (STES). The UN Sustainable Development Goals (SDGs) are introduced as landscape drivers of the WEF Nexus, as they acknowledge the crucial role of society, technology and ecological systems in its interconnected domains. A novel integrated methodology to develop the WEF Nexus as a STES transition is presented, encompassing literature review, qualitative analysis, conceptual mapping, and multi-stakeholder co-creation. This theoretical framework was empirically tested and improved across selected case studies on hydrological basins in Africa within the ONEPlanET Horizon Europe Project. Both leverageable subsystems and promising transitional innovation assets were identified. The transitional X-Curve assisted in the discussion in the empirical context of ONEPlanET to generalise the findings and the visual presentation of the identified pathways. The methodology that resulted is suitable for supporting a concrete exploration of systemic mapping, analysis, and planning towards a sustainable WEF Nexus in complex geographies, facilitated through multi-stakeholder engagement and co-creation. Full article

Small- and medium-sized enterprises (SMEs) increasingly rely on digital technologies to sustain innovation, yet limited empirical evidence explains how business intelligence capabilities translate into superior innovation outcomes, particularly in emerging economy contexts. Addressing this gap, this study examines the direct and indirect effects of business intelligence capabilities on innovation performance by unpacking the mediating role of knowledge management capability and the moderating role of data-driven decision making within an integrated Resource-Based View and Knowledge-Based View framework. Conceptually, the study advances prior research by clarifying the complementary roles of these theoretical perspectives: the Resource-Based View explains what strategic digital resources firms possess, the Knowledge-Based View explains how these resources are transformed into organizational knowledge through knowledge management capability, and data-driven decision making explains when these capabilities are effectively converted into innovation outcomes. Data were collected through a survey of 316 owners and senior managers of small- and medium-sized hotels operating in Amman, Jordan, and analyzed using partial least squares structural equation modeling (PLS-SEM) as the primary analytical technique. The results indicate that business intelligence capabilities exert a significant positive effect on innovation performance, with this relationship largely transmitted through knowledge management capability, demonstrating that the value of business intelligence lies in its integration into organizational knowledge processes rather than in data availability alone. Moreover, data-driven decision making strengthens the relationship between business intelligence capabilities and innovation performance, functioning as an execution-level capability that enhances the conversion of digital and knowledge-based resources into innovation outcomes. To further validate the robustness of the findings, a post-hoc moderated mediation analysis using Hayes’ PROCESS macro version 4.2 was conducted as a confirmatory analysis. By conceptualizing business intelligence, knowledge management, and data-driven decision making as an interconnected socio-technical capability system, this study advances digital innovation theory and offers actionable insights for SME managers seeking to orchestrate capabilities for innovation under resource constraints. Full article

In conditions of liquid modernity, marked by accelerated technological change, the virtualization of essential services, and the erosion of stable institutional support, digital participation in later life is less a matter of initial access than of continuously renegotiating engagement within unstable socio-technical environments. While established technology adoption models such as TAM, UTAUT, and STAM have provided robust explanations of cognitive and age-related determinants of adoption, they remain limited in accounting for the relational processes through which technological engagement is learned, stabilized, and sustained over time. This article advances a relational perspective on technology appropriation by foregrounding the role of warm experts—trusted informal supporters who mediate learning, interpretation, and adaptation in everyday contexts. Moving beyond dyadic understandings of assistance, the paper conceptualizes mediation as a distributed ecology of roles embedded within relational networks that both enable and constrain digital inclusion. Building on this perspective, the study proposes the Relational Technology Appropriation Model (RELTAM) as a general multi-level architecture integrating individual determinants, relational mediation processes, and network-level support configurations within a dynamic framework of appropriation. The Relational (Older Adult) Technology Appropriation Model (REL(OA)TAM) is introduced as a context-specific instantiation of this broader framework, calibrated to the distinctive conditions of later life. By incorporating temporal instability and mediation ecologies as structural components, REL(OA)TAM offers a socially grounded account of digital inclusion as an ongoing process of adaptive negotiation within the fluid and uncertain conditions of liquid modernity. Full article

This article examines how artificial intelligence and algorithmic systems are reconfiguring truth regimes in digital societies, introducing the concept of “Artificial Truth” to describe an emerging form of epistemic governance where knowledge production and validation become infrastructural functions of sociotechnical systems. The study develops an integrated theoretical framework combining Foucault’s notion of truth regimes, Bourdieu’s theory of symbolic capital and fields, and Actor-Network Theory’s constructivist approach. Through conceptual analysis, the article investigates how algorithmic recommendation systems, generative AI, and automated fact-checking operate as epistemic devices that actively shape what is recognized as credible, authoritative, and true in public discourse. The analysis reveals three fundamental transformations: (1) the restructuring of trust economies, with epistemic authority shifting from institutional expertise to platform-native capital based on engagement metrics and affective proximity; (2) the emergence of generative AI as an epistemic actor producing “synthetic truth” through linguistic fluency rather than propositional understanding; (3) the institutionalization of computational veridiction in algorithmic fact-checking systems that translate situated epistemic judgments into probabilistic classifications presented as neutral. These dynamics configure a regime where truth is evaluated less by correspondence with reality and more by computational plausibility and platform integration. The article’s primary contribution lies in providing a unified theoretical framework for understanding contemporary transformations of epistemic authority, moving beyond disinformation studies to analyze AI as an epistemic actor. By integrating classical sociological perspectives with Science and Technology Studies, it conceptualizes algorithmic systems as epistemic infrastructures that embody specific power relations, restructure symbolic capital economies, and distribute epistemic authority asymmetrically, with profound implications for democratic knowledge, citizen epistemic agency, and public sphere pluralism. Full article

This study introduces a novel risk detection and control system to enhance social stability in major construction projects. Utilizing a heterogeneous cellular automaton model, the system simulates complex interactions among project stakeholders to identify and mitigate Social Stability Risks (SSR). Integrating the Ignorant–Latent–Malcontent–Recovered (ILMR) framework, the model applies principles from epidemiology to predict and manage the spread of social stability risks. Simulation results demonstrate the model’s effectiveness in reducing the number of malcontent and ignorant individuals while increasing the recovered category, stabilizing the social environment around large projects. This approach helps manage immediate risks and improves long-term social acceptance and sustainability of engineering projects. By bridging risk management with advanced simulation techniques, this research contributes to major construction projects by providing a robust framework for managing complex social dynamics, thereby enhancing project success and stakeholder satisfaction. The findings underscore the potential of integrating innovative technological tools with traditional risk management strategies to address the socio-technical challenges of large-scale engineering projects. Full article

Water towers are historically significant hydraulic infrastructures that evolved from simple masonry structures to technologically advanced and architecturally expressive forms. This study presents a typological and material analysis of water towers, focusing on their construction techniques, durability, and potential for adaptive reuse. The research combines visual inspection, archival and bibliographic research, and photographic documentation, of selected European and Italian examples for comparative insights on design and materials choices. Data were collected and organized according to parameters such as construction materials, structural type, tank and roof form, access system, and current function. Assessments were conducted following the UNI EN 16096, providing a structured framework to evaluate heritage value, material conditions, and adaptive reuse potential. Main results demonstrate that water towers, beyond their original hydraulic function, retain significant technical, architectural, and cultural value, offering opportunities for adaptive reuse as cultural, educational, residential, or community spaces. Key findings identify material vulnerabilities, structural challenges (including wind, seismic, and thermo-hygrometric effects), and possibilities for sustainable interventions that respect historical authenticity. The study highlights how systematic typological assessment and documentation can guide evidence-based conservation and support innovative reuse strategies, integrating heritage preservation with urban regeneration and community engagement. Water towers exemplify the intersection of engineering, architecture, and cultural heritage, and their conservation requires a multidisciplinary approach between technical performance, material preservation, and socio-cultural significance. Finally, the implemented procedure is proposed as a methodological framework replicable and scalable for assessing similar infrastructures in other contexts. Full article

Sports have progressively incorporated technological advances, yet while the impact on performance and broadcasting is remarkable, the application of Artificial Intelligence (AI) in sports refereeing appears residual. A closer examination of prior research suggests that this limited development reflects deeper conceptual patterns within the field. While existing research on AI in sports officiating has predominantly conceptualized the field under an accuracy-optimization paradigm (focusing on decision precision, visual attention patterns, referee fatigue, and performance enhancement), there is a systematic lack of theoretical and empirical work that frames officiating as a broader socio-technical ecosystem. In particular, the literature does not provide conceptual models addressing (i) AI-assisted risk prevention and athlete safety as a core officiating function, (ii) human–AI task redistribution in cognitively overloaded and hybrid evaluative environments (e.g., disciplines such as artistic gymnastics or bodybuilding, where technical execution and aesthetic judgment are simultaneously assessed), and (iii) the redefinition of the referee’s role when AI operates as an anticipatory or real-time alert system rather than merely as a post hoc verification tool. Thus, the gap is not only one of application but of knowledge production: the dominant paradigm optimizes decision accuracy, yet it leaves the question of how AI can transform refereeing responsibilities, cognitive load distribution, and safety governance within competitive ecosystems under-theorized. This exploratory study adopts a Human–Computer Interaction (HCI) perspective to contrast existing initiatives with the practical expectations of professional referees. The methodology comprises two pillars: a systematic literature review following PRISMA guidelines and qualitative experimentation involving professional referees using focus groups and affinity diagrams techniques. From an initial total of 1251 records retrieved across five academic databases (2019–2025), 1122 articles were analyzed after applying strict inclusion/exclusion criteria. The findings provide preliminary support for our hypothesis of a significant underutilization gap, showing that research is concentrated on accuracy systems, while high-potential areas identified as critical by experts, such as athlete safety, represent only 0.6% of the analyzed literature. The study contributes a conceptual framework based on five categories established by experts, according to the identified use cases, providing guidance for future AI integration and interdisciplinary research in the sports officiating ecosystem. Based on the results, we point to future applications and lines of research aimed at integrating AI as a tool for sports refereeing. Full article

We argue that mainstreaming Nature-based Solutions (NbS) requires alignment of diverse value systems and integrated, cross-sectoral collaboration, and we present the necessary conditions for increasing practical implementation. NbS are increasingly recognised as effective strategies to protect critical infrastructures against climate change impacts while enhancing them by delivering ecological, social, and economic benefits. Despite growing policy support, the integration of NbS into mainstream infrastructure planning remains limited due to siloed responsibilities and decision making, entrenched institutional structures that favour grey infrastructure, and challenges in balancing short-term risks with long-term value. We examine if and how NbS mainstreaming in the infrastructure sector could be enabled. Building on insights into infrastructure governance and innovation mainstreaming, we explore perceptions and engagement with NbS and opportunities for strengthening co-governance and collaborative decision making in the Dutch infrastructure domain. A critical insight is that NbS must be understood as part of a broader socio-ecological–technical system rather than isolated interventions. This results in requirements for more integrated approaches to governance and planning as well as assessment. Asset managers in particular could play a pivotal role by adopting holistic performance assessments that consider co-benefits and trade-offs. Full article

This study examines the governance of digitalization in municipal administration, with a focus on city planning services, specifically spatial planning, building permits, and geodata management, in a large Swedish municipality. Digitalization is understood here not as the adoption of isolated technologies, but as organizational and process-oriented transformation enabled by digital systems such as GIS platforms, case management systems, and digital planning information. While national policy frameworks set ambitious digitalization goals, previous research shows that local authorities often face significant obstacles, including fragmented processes, technical limitations, and complex governance structures. These challenges create a persistent gap between strategic ambitions and daily work practices. This study employs a qualitative case study approach drawing on semi-structured interviews with employees in technical, operational, and strategic roles, as well as an analysis of policy documents and internal process descriptions. Using a socio-technical perspective, the analysis applies the Technology–Organization–Environment (TOE) framework to examine how digital systems, organizational structures, and external institutional demands interact in practice. The findings highlight substantial challenges related to system integration, data quality, uneven digital competencies, and the ongoing disconnect between strategic goals and operational realities. The study emphasizes the need for clearer governance structures, stronger cross-functional collaboration, and work practices that bridge technical and organizational dimensions. Building on the empirical analysis, the study proposes a conceptual framework that extends the TOE framework by identifying three interrelated structural mechanisms: technological lock-in, organizational inertia, and institutional uncertainty. This framework contributes theoretically by deepening the understanding of socio-technical digitalization dynamics in local government. Practically, it provides municipalities with an analytical tool to assess and reflect on their digitalization conditions. Full article

Engineering education often emphasizes technical competencies while underemphasizing and devaluing the social, ethical, and political contexts of engineering systems. This gap is particularly pronounced in middle-year courses, where students develop technical fluency but rarely confront the sociotechnical complexity of real-world problems. We propose sociotechnical judgment as a framework to help students see the intimately intertwining nature of technical knowledge and social, ethical, and contextual reasoning, using energy systems—particularly offshore wind—as an illustrative domain. We designed three course-integrated case studies in thermodynamics, circuits, and statics/dynamics to embed sociotechnical judgment in middle-year engineering courses. These cases include pedagogical strategies, such as project-based learning, problem-based learning, and role-play exercises connecting technical analysis with social, environmental, and policy considerations. The design of these case studies is rooted in real-world problems surrounding U.S. offshore wind, engineering science learning outcomes, and ABET student outcomes. In these pedagogies, we have created opportunities for students to analyze technical systems while engaging with social, ecological, and political factors. Offshore wind projects, including turbine siting, transmission system design, and efficiency trade-offs, provide opportunities to operationalize sociotechnical reasoning in authentic, regionally relevant contexts. Sociotechnical judgment provides a practical framework for bridging technical competency and contextual reasoning in engineering education. Integrating sociotechnical cases into core courses will prepare students to navigate complex, real-world systems through engagement with ethical, social, and environmental considerations inherent in engineering practice. Full article

Large language model-based virtual patients (LLM-VPs) are an emerging simulation tool for health professions education, but their design and integration into curricula are not well characterized. This scoping review mapped how LLM-VPs are being used for simulated clinical learning across health professions. Following a protocol registered on OSF, we searched MEDLINE, EMBASE, CENTRAL, Scopus, and Web of Science to 11 April 2025, per PRISMA-ScR guidelines, and included 21 studies that used LLMs to generate virtual patients for simulated clinical encounters. Data were extracted on technical design, fidelity domains, curricular integration, human factors, and Technology Acceptance Model constructs, and synthesized narratively. Most studies (n = 11) were pilot or feasibility evaluations with small samples (median 21) and used GPT-based models with dynamic text chat. Integration was limited to 10 studies that operated as pilots, 7 as electives, and 3 as core curricular components. The outcomes focused on Level 2 learning (clinical reasoning and preclinical OSCE performance), with predominantly self-report assessments. No studies reported Level 3 or 4 outcomes. Fidelity was strongest in cognitive, socio-cultural, and emotional domains, and 11 studies reported hallucinations or inaccurate outputs. LLM-VPs appear feasible and well-received but remain early-stage, underscoring the need for fidelity-aligned design and more rigorous, longitudinal evaluations. Full article

Armed conflict management increasingly demands new normative and strategic frameworks that preserve human life while maintaining effective deterrence capabilities. This study develops a multidisciplinary framework for rethinking armed conflict through the concept of just peace, integrating theology, ethics, law, technology, and empirical communication analysis. The research analyzes 7957 YouTube videos from NATO, the United Nations, and the Vatican, published over two years, employing semantic network analysis, modularity-based community detection, and sentiment analysis to identify emerging discourse patterns around peace, technology, and regulatory complexity. The findings suggest that contemporary socio-technological conditions are increasingly framed in ways that open a discursive space for rethinking conflict management beyond exclusive reliance on large-scale lethal force. Positive messaging correlates with higher audience engagement, while concepts such as law, ethics, religion, and technical standards emerge as interconnected regulatory domains. The study concludes that just peace is not naïve pacifism but a strategic, normatively grounded reorientation in contemporary deterrence thinking. Effective implementation requires integrated regulatory frameworks combining legal norms, ethical principles, religious values, and technical standards. The evolving technological landscape may allow deterrence systems to move beyond exclusive reliance on lethal force toward more humane and efficient conflict-management mechanisms. Full article

Lithium is a critical mineral for traction batteries and a cornerstone of the sustainable transition toward low-carbon transportation. Understanding the supply–demand dynamics and resource-saving potential of lithium is essential for advancing circular economy goals and ensuring the long-term stability of the electric vehicle (EV) industry. This study develops an integrated lithium forecast framework by coupling a System Dynamics (SD) model with dynamic Material Flow Analysis (MFA) and multi-scenario pathways. To ensure robust conclusions, the model is validated against historical data, and a multi-level sensitivity analysis is conducted to address the inherent uncertainties of evolving socio-technical assumptions over a ten-year horizon. The simulation results reveal that under the baseline scenario, China’s EV stocks and annual lithium demand will grow by 8.3 and 4.7 times from 2024 to 2035, respectively. This rapid expansion poses a significant sustainability challenge, as cumulative demand will deplete 50–71% of China’s domestic lithium reserves by 2035. Despite a projected supply–demand gap of 110–120 kt/yr, the study identifies critical pathways for resource decoupling and circularity. Technology-driven interventions, such as enhancing energy density and extending battery lifespan, can reduce primary lithium demand by up to 18.9%. Furthermore, optimizing the closed-loop recycling system can contract the supply–demand gap by 31–39%, demonstrating the pivotal role of secondary resource recovery in building a resilient supply chain. Despite this reduction, a persistent reliance on international markets remains inevitable. These findings provide a quantified scientific foundation for policymakers, emphasizing that lithium security requires a synergistic transition from volume-based subsidies to resource efficiency mandates and standardized, formal closed-loop recycling systems. Full article

The electricity supply system faces major challenges. The physical and social vulnerability of the monoculture of hierarchical, centralized systems urgently requires radical transformation of their organizational structures as well as their infrastructures. These transformations to low carbon are often characterized as ‘decentralization’. However, decentralization is a process that only signifies a move away from centralized models. This does not necessarily result in a decentralized architecture, but rather a model in which the dominance of ‘commercial private’ combined with ‘monopolistic public’ is replaced by cooperation and community. The research question is: what will be the design of future electricity grids after the transformation? The integration of distributed renewable resources and the growing need for resilience requires great diversity and flexibility from socio-technical smart grids. These involve digitization, enabling the transformation of power grids into networks of clustered, self-healing microgrids with distributed energy systems: generation, storage, transmission, demand response, and internal energy management. Several fundamentals of Common Pool Resources theory (Ostrom) on the analysis of sustainable management of natural resources are reviewed on their relevance: the Socio-Ecological System framework, distinct property regimes, the Polycentricity concept, and the Institutional Analysis and Development (IAD) framework. The transformation leads to ‘distributed’ rather than ’decentralized’ models. Governance no longer takes place from a single control point, but from many, spread across multiple levels, similar to ecosystems. End users play a key role and become partly coproducing prosumers. Governance is polycentric rather than decentral. The IAD provides as its most important condition that, at the legislative level, there must be minimum recognition of the right of ‘renewable energy communities’ to organize themselves as microgrids. This is immediately the biggest social acceptance challenge, as the current monoculture incorporates several lock-ins: incumbent powerful actors, centralized hierarchical control legislation, and obstructive market conditions, including taxing systems. Full article