Search Results (650)

Driven by the digital transformation of territorial spatial governance, traditional urban planning is irreversibly shifting towards a data-driven empirical paradigm. However, constrained by mimetic isomorphism and path dependence, many geography-based regional universities remain trapped in an educational dilemma: they overemphasize morphological representation while marginalizing quantitative decision-making, fostering a structural mismatch between graduate competencies and industry demands. To explore a systematic pathway out of this dilemma, this study chronicles a three-year pedagogical intervention utilizing a mixed-methods design with a historical control cohort (N = 275) within the urban planning program of Gansu Agricultural University—a regional institution situated in a less-developed frontier where territorial renewal demands macro-spatial synthesis over aesthetic forms. The intervention strategically redefined the graduate competency profile as “spatial data analysts”, constructing a pedagogical model comprising foundational algorithmic training, cross-disciplinary faculty collaboration, and real-world Project-Based Learning (PBL), coupled with a restructured, evidence-based evaluation system. Longitudinal tracking and quantitative analyses indicate a structural alignment with elevated educational efficacy. At the macro level of employment trajectories, the proportion of graduates securing knowledge-intensive data positions experienced a structural shift, rising from a baseline of 14.5% to 42.5%, reflecting an enhanced capacity to capitalize on expanding societal demands. At the meso level of practical competence, the award rate in high-level professional competitions increased by 35.4%. At the micro cognitive level, the new evaluation mechanism is associated with a successful redirection of students’ cognitive resources toward algorithmic logic and policy translation (p < 0.001) while highly significantly enhancing their self-efficacy in tackling complex, wicked engineering problems (p < 0.001). Rather than isolating pure causal mechanics, this study interprets these systemic gains as a contextual realignment of academic supply. It provides a context-sensitive, reproducible methodological reference for cultivating professional distinctiveness and reshaping the spatial planning education system in the digital era. Full article

Background/Objectives: Large language models (LLMs) and generative AI are rapidly being integrated into healthy ageing initiatives for tasks ranging from companionship and cognitive support to personalised health advice and reduction in social isolation among older adults. Current ethical discussions predominantly address bias, privacy, and accuracy, leaving unresolved three critical governance questions: How do LLM sentiments towards transformative technologies diverge from human values in ageing contexts? What epistemic status do LLM outputs hold when applied to geriatric care? When is trust in those outputs justified for older adults? And who bears responsibility when AI-informed decisions affect functional ability or well-being? Methods: The framework was developed through normative conceptual analysis, synthesizing philosophical principles of medical knowledge and trust, ethical theories of responsibility, empirical evidence on LLM sentiment divergence, digital ageism, and applications of AI in geriatric care (structured searches in PubMed, PhilPapers, and relevant databases, January 2020–March 2026). Results: The integrated framework produces (i) adaptation of SAIA for multidimensional evaluation of human–machine value convergence specific to healthy ageing values (functional ability, autonomy, dignity, equity); (ii) a four-tier classification of LLM outputs tailored to geriatric scenarios; (iii) conditions for warranted trust calibrated to age-related vulnerabilities such as cognitive decline and digital divide; and (iv) responsibility allocation via RACI models with testable hypotheses linking governance design to trust calibration and patient safety outcomes. Conclusions: Without explicit societal alignment and epistemic governance, generative AI risks reinforcing benevolent ageism, automation bias, and responsibility gaps in healthy ageing. The 2025–2027 period offers a decisive window to shape institutional norms that place functional capacity, human dignity, and value convergence at the centre of AI deployment in geriatric care. Full article

In 2020, evaluators within the Research Centers in Minority Institutions (RCMIs) program proposed a conceptual framework identifying four primary evaluation targets: scientific productivity, scientific collaboration, professional growth, and research resources. This study extends prior work by capturing the contextual and process-oriented dimensions of program impact. This reflective practice-based project examines how non-quantitative approaches complement traditional metrics to better characterize RCMI outcomes. Evaluators representing ten RCMI sites participated in a multi-site case study guided by three questions addressing: (1) qualitative evidence of impact beyond metrics; (2) challenges and successes in implementation of non-quantitative methods; and (3) potential expansion of evaluation targets. Evaluators provided descriptive responses, generating a 22-page dataset that was analyzed thematically. Thirteen non-quantitative evaluation domains emerged: investigator consultations, investigator productivity, investigator success, community partnerships, intra-RCMI collaborations, implementation of team science, career progression, programmatic support, mentoring support, impact on RCMI affiliates, intellectual resources, physical resources, and faculty hires. Key challenges included inconsistent data capture and limited evaluation resources, while successes highlighted improved cross-site learning and visibility of program impact. Findings support retaining the original evaluation targets while expanding the framework to include institutional transformation, equitable research environments, and longitudinal societal impact. A conceptual map was developed to depict how mixed methods that include non-quantitative approaches can yield RCMI evaluations that expand upon the current approach, which relies primarily on quantitative data. The authors recommend quantitative targets and non-quantitative strategies to provide context, communicate evidence of success, and inform programmatic changes to deepen the findings and strengthen the rigor of RCMI evaluation practices. Full article

Background/Objectives: The dental profession is undergoing significant transformation driven by societal changes, technological advancements, evolving patient expectations, and increased attention to sustainability. These developments challenge traditional notions of dental competence and highlight the need for educational frameworks that support adaptability and longitudinal professional development. The aim of this study was to develop a contextually grounded competence framework for undergraduate dental education through an iterative, multi-method process informed by key educational stakeholders. Methods: A multi-method approach was used, combining a preparatory phase (literature review, interviews) with a development phase (drafting and workshops) that was revisited in response to feedback, followed by iterative voting rounds that prompted further minor revisions. A deductive exploratory mapping analysis aligned the emerging framework with existing intended learning outcomes across the curriculum. Results: The multi-method process produced descriptions of a framework that deliberately integrates roles, skills, and attributes to capture key dimensions of professional competence in dentistry. The framework includes six domains: ‘Evidence-informed’, ‘Decision-maker’, ‘Communicator’, ‘Acting with professional conduct’, ‘Health ambassador’, and ‘Collaborator and leader’. Across voting rounds, the domains were generally rated between ‘neutral’ and ‘very important’, with each round prompting minor revisions. Mapping suggested alignment between the overarching framework and the detailed curriculum. Conclusions: This study presents the outcome of a structured, exploratory multi-method process to develop a locally relevant competence framework, integrated into a dental education. The participatory design supported clarity and relevance. While sharing similarities with existing frameworks, the new framework also includes differences. The term ‘professional conduct’ was preferred rather than ‘professionalism’, and the domains ‘collaborator and leader’ and ‘decision-maker’ were identified as relevant according to employer expectations. Although the work was based locally at one dental school, the approach may be transferable to similar contexts. Full article

This study investigates the role of the Massive Transformative Purpose (MTP) in shaping corporate brand identity and guiding brand management strategies in Exponential Organizations (ExOs). It examines how the MTP aligns internal and external brand dimensions, enhances stakeholder engagement, and drives societal impact, positioning it as a central element in ExO brand management. This study employs a qualitative multiple-case study methodology focusing on two ExOs: Airbnb, a digital-native hospitality company, and Mylia, a transformative learning enterprise. Semi-structured interviews with senior executives were triangulated with internal and external data to examine how the MTP drives strategy, culture, and stakeholder engagement. This allowed the application of the Corporate Brand Identity Matrix for exploring the different corporate brand identities and the relative nuances. The findings show that the MTP is essential to shaping ExOs’ corporate brand identity. It unifies organizational purpose, culture, and strategy, creating a cohesive identity that resonates both internally and externally. Embedding the MTP into daily practices fosters alignment, guides decision-making, strengthens stakeholder relationships, and shapes value propositions that distinguish ExOs while addressing stakeholder needs. The research bridges gaps in the literature on corporate brand identity, organizational purpose, and the unique characteristics of ExOs. It introduces the MTP Management Model, which integrates ExO-specific attributes to provide deeper insights into how these organizations align operational structures and brand identity with their transformative purpose. While the multiple-case study approach offers in-depth insights, the findings are context-specific and may not be fully generalizable across industries. The MTP Management Model provides a clear framework to integrate essential attributes, ensuring organizational coherence, effective communication, and enhanced competitiveness. Full article

This study examines how digital transformation in higher education institutions (HEIs) contributes to public value creation, moving beyond efficiency-oriented narratives toward broader societal outcomes. Using a PRISMA-ScR approach, the study systematically reviews 47 peer-reviewed articles published between 2013 and 2025 across major academic databases. The review maps the evolution of scholarship and identifies the key mechanisms through which digital transformation influences public value. The findings reveal three interrelated dimensions shaping outcomes: digital competencies, institutional readiness, and governance alignment. Digital competencies enable the effective adoption and use of technologies, while institutional readiness—comprising digital infrastructure, leadership capacity, and organizational culture—acts as a mediating condition influencing implementation success. Governance alignment, including regulatory coherence, accountability mechanisms, and stakeholder engagement, plays a moderating role in determining whether digital transformation initiatives generate inclusive and socially beneficial outcomes. In addition to positive outcomes such as improved access, service quality, and transparency, the review identifies critical risks—including digital inequality, data governance challenges, and algorithmic bias—that may constrain public value creation, particularly in resource-constrained and Global South contexts. Building on these findings, the study develops the Global Digital Transformation—Public Value Creation (G-DTPVC) framework as an evidence-synthesized model derived from the reviewed literature. The framework specifies key constructs, causal relationships, and indicative measures to support future empirical research and policy application. By linking digital transformation processes in HEIs to broader public value outcomes and Sustainable Development Goals (SDGs 4, 9, and 16), this study advances theoretical understanding and provides actionable, context-sensitive guidance for policymakers and institutional leaders seeking to foster inclusive, accountable, and resilient higher education systems. Full article

The accelerating convergence of geopolitical volatility, technological disruption, environmental stress, and societal transformation has rendered traditional strategic management frameworks insufficient. Organizations now operate in environments defined not only by disruptions with existential implications but by wickedness—conditions in which problems are ambiguous, stakeholders disagree, and solutions reshape the challenge itself. Building on the premise that strategy itself is a wicked problem, this article advances a central claim: organizational resilience is best understood as an architectural capability largely grounded in humanity-based identity. Unlike organizational structure, mission, or even current strategy, each of which may be transient in turbulent environments, organizational identity, which is a construct that derives from individuals and humanity, provides an enduring basis for harmonizing the organization and its environment. Utilizing the lens of “humanity”—in its two dimensions of humankind and humaneness—we synthesize research on wicked problems, organizational identity, dynamic capabilities, modular design, alliances and smart power, and hybrid intelligence. We then propose an integrative model linking humanity-driven identity to resilience through three vectors—Inspirational Transformative Ambition, Innovative Value Networks, and Hybrid Intelligence Ecosystems—operationalized via a recently developed diagnostic tool. Finally, we offer corroborative evidence for the “Business of Humanity” logic, arguing that aligning humankind (opportunity across the full market spectrum) with humaneness (values-based evaluation) strengthens resilience by expanding opportunity sets while enhancing legitimacy, trust, and stakeholder alignment. Full article

Universities are increasingly expected to contribute to societal and environmental challenges, yet the concept of the fourth mission remains fragmented and weakly operationalized in the literature. This study aims to develop a measurement framework for the fourth mission of universities. The research adopts a theory-driven qualitative design based on a systematic literature review, synthesizing contributions on community engagement, social innovation, sustainability and institutional embeddedness. Building on this synthesis, the study develops a three-level conceptual model that integrates an institutional framework, core fourth mission processes and transformative impact domains. The core processes are structured around community engagement, co-creation and social innovation, and knowledge diffusion and local application, while the model explicitly links these processes to societal challenges and environmental sustainability outcomes. Furthermore, the model is operationalized through a structured indicator system applicable in document-based analysis, supported by a four-point scoring scale capturing the depth of institutionalization. An illustrative pilot test was also conducted using the example of one university faculty. The study contributes by clarifying the boundaries of the fourth mission and offering an operational framework that shifts attention from output-based measurement to universities’ transformative societal roles. Full article

The fundamental purpose of education—preparing new generations to be contributing members of society—remains constant, yet achieving this has become increasingly complex amid multifaceted technological, cultural, economic, and social transformations. Educational leaders worldwide continuously seek innovative pedagogical models addressing diverse learner needs and rapid societal changes. However, this article challenges the assumption that educational quality requires constant novelty, arguing that solutions lie in the innovative integration of established pedagogical theories developed over the past 150 years by scholars such as Dewey, Vygotsky, Piaget, Feuerstein, Gardner, Freire, and others. The article’s primary objective is to encourage education leaders and teacher educators to reconceptualize innovation by prioritizing pedagogical integration over continuous adaptation to rapidly expanding domain-specific knowledge and emerging technologies. Accordingly, this article employs a conceptual synthesis of major pedagogical approaches to equip educators with theoretical foundations and practical tools to foster learner independence, critical thinking, and holistic development across cognitive, emotional, and social domains. It will also promote inclusion through a practical framework integrating pedagogical theories, addressing diversity from a dual perspective, recognizing that both teachers and learners bring unique characteristics, strengths, and needs. Moreover, developing independent learners requires empowering teachers to cultivate unique professional methodologies grounded in integrated pedagogical understanding, so that a shift from innovation-centered to integration-centered teacher education may serve as a sustainable path toward educational quality and academic excellence. Full article

Increasing societal awareness of mental health challenges has significantly reduced stigma surrounding psychological disorders, encouraging greater numbers of individuals to seek professional support, which has placed unprecedented pressure on mental health services, with institutions ranging from educational establishments to emergency services implementing systematic screening protocols to identify individuals requiring intervention. However, the growing demand for rapid, accurate diagnosis continues to strain limited professional resources. Our study introduces an innovative machine learning framework for mental disorder detection using electroencephalography (EEG) signals processed through Welch’s power spectral density estimation. Unlike conventional Fast Fourier Transform (FFT) approaches, our method generates refined two-dimensional spectrograms capturing brain wave amplitudes (in dB) alongside precise peak frequency identification. This computationally efficient periodogram variant enables robust feature extraction suitable for real-time diagnostic applications while reducing model training overhead. Preliminary analysis demonstrates the Welch Transform’s superior signal characterization compared to standard FFT periodograms, revealing distinct neurophysiological patterns associated with various mental health conditions. The approach maintains high computational efficiency, supporting potential deployment in clinical screening environments. Full article

In the face of intensifying socio-ecological crises, there is a growing debate about how processes of societal transformation can be shaped. Education for Sustainable Development (ESD), particularly in its transformative orientation (ESD 3), is widely regarded as a key lever in this context. While ESD 3 gets increasingly differentiated in educational theory, its disciplinary grounding remains insufficiently specified. This article addresses this gap by examining which structural characteristics of sustainability issues must be exhibited to enable individual and societal transformation. Drawing on Integral Sustainability Science, sustainability-related transformation processes are differentiated along internal (the meaning-making and culture domain) and external dimensions (the behavior and systems domain), integrating both factual systemic interrelations and normative perspectives of meaning and interpretation. On this basis, sustainability issues are characterized by internal and external complexity as well as controversiality. These features are brought together in the 3C Framework for Sustainable Learning and extended by the dimension of individual and collective contingency. As societal transformation unfolds through social negotiation processes under conditions of (double) contingency, transformative education aims to foster a deeper understanding of sustainability issues and to enable learners to perceive themselves as part of societal transformation processes and to participate in collective negotiations under conditions of uncertainty. Full article

Over the past three decades, artificial intelligence (AI) has substantially reshaped marketing research and practice, yet the discipline has not established a systematic understanding of its evolutionary trajectory and intellectual structure. A bibliometric analysis of 1923 Scopus publications (1992–2025) was conducted using CiteSpace to explore collaboration patterns, conceptual development, and thematic organization. It identified six evolutionary stages with accelerating innovation cycles, starting with neural networks (1992–2000) and ending with generative AI (2024–2025), with research attention per stage compressing from approximately 9 years to just 2 years. The analysis of the collaboration network shows that the key contributors are India, China, the USA, and the UK. Co-citation analysis indicates that there are three thematic dimensions with seven clusters, namely: (i) AI technological foundations and capabilities, (ii) AI marketing applications and transformation, and (iii) responsible AI governance and ethics. It suggests a Three-Force Evolutionary Framework, which combines technology-push, market-pull, and governance-moderator forces to describe the dynamics of the field. This framework shows that the Regulatory Awakening of 2018 (e.g., GDPR and the Cambridge Analytica incident) guided, not limited, innovation, and highlighted the critical personalization–privacy paradox on which modern developments are based. It identifies three priority research directions: generative AI in creative marketing, consumer trust in the personalization–privacy paradox, and organizational adaptation to fast innovation cycles. This study provides scholars with a comprehensive knowledge map, practitioners with strategic imperatives for responsible AI adoption, and policymakers with evidence that well-designed regulation accelerates innovation by balancing commercial value with societal concerns. Full article

Living Labs offer immersive learning in Higher Education Institutions (HEIs), yet their core nature and value for competency development remain underexplored, particularly from the perspective of lab leaders. To address the knowledge gap, this study examines the perspectives of lab leaders on the potential of living labs as dynamic learning settings. Specifically, it explores two dimensions: (1) how living labs structure learning processes, and (2) the influence of collaboration with societal partners on learning outcomes, framed by the Quadruple Helix Model (academia, industry, government, and community). The study adopts a qualitative research design via semi-structured interviews with seven laboratory leaders across five well-established living labs in Finnish Universities of Applied Sciences. Interview transcripts were analyzed using Julius.ai and in vivo coding to identify and categorize themes. The respondents highlighted that in their experience, combining physical and digital settings often facilitates experiential, reflective, and innovative learning while equipping students with practical skills and competencies that improve their employability. Furthermore, the respondents reported that engagement with stakeholders fosters co-creation and well-rounded innovation. These collaborations also help ensure that the living labs can effectively sustain their operation, offering students the opportunities to engage in globally relevant issues such as digital transformation. Nonetheless, obstacles include resource limitations, maintaining enduring teamwork, and adjusting to rapid technological changes. The paper concludes that living labs serve as supplementary instruments and their adoption can help match academic learning curricula and practices with industry needs, while also enhancing student learning in preparation for the world of work. Full article

This paper explores the behavioural change process initiated within the Gdańsk Coastal City Living Lab (CCLL)—a site-based effort, initiated under the H2020 SCORE project and significantly deepened through the Horizon Europe PRO-CLIMATE project—through the lens of transforming human–nature relationships for sustainable urban biodiversity conservation. While SCORE established the technical baseline for Nature-based Solutions (NbSs), PRO-CLIMATE provides the critical behavioural framework to ensure these solutions are socially adopted and sustained. Located in a flood-prone coastal city, the Gdańsk CCLL addresses the critical need for nature-based solutions (NbSs) in minimizing the negative impacts of climate change, particularly pluvial flooding. At the heart of this initiative is a participatory change process facilitated by local Change Agents in collaboration with key stakeholders across water management, local government, academia, and civil society. Drawing on interdisciplinary insights from social science, the paper uses the Nature Futures Framework to analyse how conservation actions are influenced by the relational, intrinsic, and instrumental values that stakeholders and residents attach to nature. The paper situates these values in the Gdańsk context and examines how they shape motivations and willingness to engage in urban NbS, such as green roofs, retention parks, and rainwater gardens. The study presents qualitative findings from stakeholder engagement workshops, Change Agents’ reflections, and support mechanisms from behavioural change experts. It evaluates how behavioural change was facilitated through shared vision building, feedback loops, and trust-based relationships, and how barriers were negotiated. A key contribution of the paper is the exploration of how bottom-up and top-down processes intersect in urban adaptation strategies and how behavioural change frameworks can be designed to institutionalise sustainable human–nature interactions in urban governance. The Gdańsk case offers transferable insights for other cities facing climate vulnerabilities while striving to embed biodiversity conservation into everyday practice. Full article

Large Language Models (LLMs) have become foundational to modern Artificial Intelligence (AI), enabling advanced reasoning, multimodal understanding, and scalable human-AI interaction across diverse domains. This survey provides a comprehensive review of major proprietary and open-source LLM families, including GPT, LLaMA 2, Gemini, Claude, DeepSeek, Falcon, and Qwen. It systematically examines architectural advancements such as transformer refinements, mixture-of-experts paradigms, attention optimization, long-context modeling, and multimodal integration. The paper further analyzes alignment and safety mechanisms, encompassing instruction tuning, reinforcement learning from human feedback, and constitutional frameworks, and discusses their implications for controllability, reliability, and responsible deployment. Comparative analysis of training strategies, data curation practices, efficiency optimizations, and application settings highlights key trade-offs among scalability, performance, interpretability, and ethical considerations. Beyond synthesis, the survey introduces a structured taxonomy and a feature-driven comparative study of over 50 reconstructed LLM architectures, complemented by an interactive visualization interface and an open-source implementation to support transparency and reproducibility. Finally, it outlines open challenges and future research directions related to transparency, computational cost, data governance, and societal impact, offering a unified reference for researchers and practitioners developing large-scale AI systems. Full article