Search Results (9,817)

Higher education institutions (HEIs) play a vital role in shaping sustainability mindsets and fostering awareness of planetary health and social responsibility. However, research on how community-based learning affects Malaysian students’ knowledge and attitudes in this area remains limited. This exploratory study, conceptually informed by a theory of change (ToC), examines students’ perceived knowledge and attitudes, alongside descriptively reported behaviours, related to sustainability values and social responsibility within a community service learning initiative at Sunway University (SU). A mixed-methods online survey was administered to undergraduate students enrolled in the “Community Service for Planetary Health (MPU 3422)” course to evaluate programme-related learning outcomes and engagement. Based on 52 valid responses, preliminary analysis suggests that students reported moderate to strong perceived knowledge and positive attitudes towards planetary health. A strong positive association between perceived knowledge and attitudes was observed. Behavioural responses indicate variability in students’ engagement, suggesting that positive knowledge and attitudes do not necessarily correspond to consistent behavioural participation. To our knowledge, this study offers an initial empirical exploration of the integration of the KAB and ToC frameworks as conceptual lenses, with a primary focus on knowledge and attitudes, within a Malaysian higher education service learning context, contributing to the understanding of sustainability education in this setting. The findings offer insights into how experiential, community-based learning relates to sustainability awareness and value formation, while highlighting the need for further research to examine how these may translate into sustained behavioural outcomes. Full article

Smart retail adoption (SRA) is widely seen as a way to improve operations. But how it affects business performance (BP) is still unclear. This study builds a framework using information theory and the Technology–Organization–Environment (TOE) framework. We use data from 220 Chinese retail firms (2012–2023). Our analysis shows that SRA significantly improves BP. It does so by first reducing incomplete information (measured by analyst forecast dispersion, AFD) and then lowering uncertainty (UNC). These two factors work in sequence. Technological conditions (TECH), organizational conditions (ORG), and environmental conditions (ENV) all strengthen this effect. SRA also has strong long-term benefits. The effect is greater in non-state-owned firms, large firms, firms in central China, and those that rely mainly on offline channels. This study explains how SRA boosts BP and offers practical insights for retail transformation. Full article

Knowledge management platforms are increasingly important for strengthening governance, scientific collaboration, and evidence-based decision making in complex regional networks. This study analyses the prospective intention to adopt two strategic digital mechanisms of the Amazon Cooperation Treaty Organization (OCTA): the Amazon Regional Observatory (ORA) and the Network of Amazonian Research Centres (REDCIA). Adapting the Unified Theory of Acceptance and Use of Technology (UTAUT) to a pre-implementation context, the study focuses on performance expectancy, social influence, and facilitating conditions, while operationalizing these constructs through a Knowledge, Attitudes, and Practices (KAP) survey. Using a quantitative, non-experimental, cross-sectional design, penalized ordinal logistic regression models were estimated from 162 responses collected from institutional actors and experts across eight Amazonian jurisdictions. The results show that social influence is the only statistically significant predictor of intention to use in both mechanisms, whereas performance expectancy and facilitating conditions are not significant in the estimated models. These findings suggest that, in the Amazonian cooperation context, adoption is driven less by individual evaluations of utility or technical feasibility than by institutional legitimacy, peer expectations, and collaborative norms. The study contributes to the information systems literature by providing an ex ante analytical approach for assessing technology acceptance in the absence of an operational artefact. It also offers practical guidance for OCTA by highlighting the importance of change management, political endorsement, and network-based incentives to support future implementation. Full article

This study analyzes transformative collaborative learning as a management innovation in a community-based service ecosystem in Phrom Kiri, Thailand. Leveraging Transformative Learning Theory and Service-Dominant Logic, the study employs qualitative participatory methods (i.e., multi-stakeholder workshops, focus groups, and field observations) to document the dynamic processes through which learning, interactions, and institutional changes evolve. These findings demonstrate how collectively informed strategies for sustainability challenges engendered collective learning processes that led to an alteration of actors’ assumptions, mobilization of shared understanding, and facilitated new governance practices driven by multi-dimensional value drives in response to accumulating disconnects. These reflect the rise of participatory governance mechanisms, the intermediation between actors to create synergies, and the anchoring of institutional frameworks into local contexts to allow for value generation both in economic terms and social ones. Our case study shows that transformative learning can be more than just a cognitive change, also enabling community-level management innovations. It finds that sustainable development of local service ecosystems relies on the formation, institutionalization, and promotion of collaborative practices that facilitate the alignment of stakeholders’ interests and competencies. By conceptualizing transformative collaborative learning as a key mechanism to understand how management innovation and value co-creation unfold in community-based development, this research advances sustainability and management literature. Full article

The interaction between crude oil prices and exchange rates is central to understanding global financial stability and macro-economic balances. Contrary to traditional static analyses, the heterogeneous market hypothesis argues that market participants have different time horizons and that multi-scale analysis is necessary to capture dynamic changes in crisis periods. This study examines volatility spillovers between WTI crude oil and the Russian ruble using wavelet coherence, phase difference, and predictive information flow analysis in a time–frequency framework. The analysis separates short-term [2–32 days] transient shocks from long-term [32–256 days] structural changes. Findings show that a negative spillover, initially led by WTI, with evidence of dynamic, frequency-dependent leadership shifts during the 2020 shock, was interpreted as a result of the overnight price gap and a failure of microstructural synchronisation. With the outbreak of the 2022 Russia–Ukraine war, the relationship shifted to a strong, positive, and high-intensity risk transfer, consistent with contagion theory. Crucially, by 2024, a structural decoupling emerged due to geoeconomic fragmentation, signalling that the ruble no longer exhibits traditional petro-currency behaviour. These results offer critical signals for policymakers regarding reserve management and for market participants regarding new liquidity risks. Full article

Research on dishonest behavior within organizational contexts has expanded rapidly in recent years. However, the structural organization of dominant explanatory mechanisms within this literature remains insufficiently clarified. This study provides a theory-informed bibliometric analysis focusing on a deliberately selective segment of the workplace dishonesty literature. Rather than attempting an exhaustive census, the study maps a corpus centered on dominant socio-cognitive and organizational explanatory frameworks in order to examine how these mechanisms are positioned, interconnected, and evolving within this theory-filtered segment. To ensure a transparent and reproducible review process, the study was conducted in accordance with the PRISMA 2020 guidelines, which guided the identification, screening, and eligibility assessment of the literature. Drawing on a systematically constructed corpus retrieved from Web of Science and Scopus and covering the period 1989–2025, the bibliometric analysis was conducted using Biblioshiny 4.5.2 on a final dataset of 679 documents. The analysis integrates performance indicators with science-mapping techniques, including keyword co-occurrence networks, thematic mapping, multiple correspondence analysis, thematic evolution, and global citation analysis. The findings indicate that this theory-based subset of the literature has developed steadily over time alongside a clearer structuring of publication outlets. Conceptually, it remains largely organized around a small number of recurring mechanisms, most notably ethical climate and moral disengagement. Thematic analyses suggest a degree of theoretical stabilization alongside diversification within this selected corpus, while factorial mapping suggests recurring contrasts between cognitive, normative, and organizational explanatory logics. From a longitudinal dynamic perspective, the mapped patterns suggest a possible movement toward more context-sensitive and governance-oriented perspectives; however, this should be interpreted as an inferential reading of this selected corpus. Overall, the findings suggest that, within this corpus, unethical workplace behavior is increasingly conceptualized as a context-dependent socio-cognitive phenomenon shaped by justificatory mechanisms, organizational environments, and performance-related pressures. This review contributes to the fields of behavioral ethics and organizational behavior by providing a structured reading of this specific body of work, clarifying its conceptual organization, identifying its main developmental trajectories, and outlining a theoretically grounded future research agenda for this selected body of literature. Full article

The government’s adoption of cloud computing is critical for digital transformation, but it faces persistent concerns over information security, privacy, governance, and risk. This study examines the factors influencing a government’s intention to adopt cloud services, adapting the Unified Theory of Acceptance and Use of Technology (UTAUT) with constructs tailored to the public sector. A cross-sectional survey was conducted across 90 Nigerian government organisations, producing 230 valid responses from IT professionals, administrators, and policy personnel. The statistical analysis of the data was conducted using SPSS and structural equation modelling in AMOS. Validity and reliability were confirmed through composite reliability, Cronbach’s alpha, and discriminant validity measures. Findings show that privacy (β = 0.11, p < 0.05), governance framework (β = 0.34, p < 0.001), performance expectancy (β = 0.38, p < 0.001), and information security (β = 0.10, p < 0.05) significantly influence government intention to adopt cloud services. Performance expectancy emerged as the strongest predictor. Contrary to expectations, perceived risk did not significantly moderate the relationships, and interaction terms were non-significant. The final model explained 45% of the variance in adoption intention (R² = 0.45). The study highlights the importance of strengthening governance frameworks, emphasising tangible performance outcomes, and positioning information security and privacy as an enabler of adoption rather than a barrier. By adapting UTAUT to the government context and disentangling the role of perceived risk, the study offers both theoretical refinement and practical guidance for policymakers aiming to accelerate digital transformation and secure cloud adoption. Full article

This study examines the validity of the Spanish version of the Scientific Epistemic Beliefs (SEB) Questionnaire among university students in northeastern Mexico, considering multiple sources of evidence. The SEB measures four dimensions of epistemic beliefs: Source, Certainty, Development, and Justification. Data from pilot (n = 150) and main (n = 791) samples were analyzed using Exploratory and Confirmatory Factor Analyses (EFA, CFA), Item Response Theory (IRT), and Differential Item Functioning (DIF). The results provided evidence consistent with a four-factor model, with adequate internal consistency (α = 0.85) and acceptable-to-good fit indices (CFI = 0.944, TLI = 0.936, RMSEA = 0.067, SRMR = 0.071) for a 22-item scale. IRT analyses indicated strong item discrimination, with Source and Certainty covering a broad range of the latent trait, while Development and Justification were more informative at lower to moderate levels. DIF analyses indicated negligible differences in item functioning by gender and academic semester, with minor DIF detected across faculties. Non-parametric analyses identified statistically significant but small differences, with females scoring slightly higher across all dimensions and variations also observed across academic semesters and faculties. Descriptive comparisons with published international data provide contextual evidence within a broader cross-cultural framework. Full article

Cognitive load theory-informed curriculum design in health sciences education refers to the purposeful organisation of teaching strategies and learning materials based on the principles of Cognitive Load Theory (CLT), a framework developed by John Sweller in the late 1980s. CLT is grounded in cognitive psychology and recognises that the working memory has a limited capacity for processing new information. It identifies three types of cognitive load: intrinsic load, which refers to the inherent complexity of the material being learned; extraneous load, which results from ineffective instructional design or irrelevant information; and germane load, which reflects the mental effort directed toward understanding, integrating, and organising information into long-term memory. In health sciences education, students frequently engage with tasks that require the simultaneous processing of multiple interacting elements, placing high demands on working memory at specific points in time. This includes foundational biomedical sciences such as anatomy, physiology, and pathophysiology extending to applied clinical skills, diagnostic reasoning under uncertainty, health service management within complex systems, and ethically grounded decision-making. Without thoughtful instructional design, learners may be overwhelmed by excessive information and cognitive demands, which can hinder understanding, retention, and performance. Applying CLT-informed strategies, educators can reduce unnecessary cognitive burden, sequence learning activities to align with learners’ cognitive capacity, and promote deeper learning. This approach supports more effective knowledge acquisition and transfer and is particularly valuable in content dense academic environments such as medicine, nursing, allied health education, public health and health service management education. Therefore, integrating CLT-informed principles into curriculum design can help optimise learning experiences and support the development of competent health professionals. Full article

Violations of Bell inequalities are commonly interpreted as evidence for nonlocal influences or as constraints on realist descriptions. We show that the failure of Bell-type factorizability arises naturally when observable outcomes are obtained through a non-injective mapping from an underlying configuration space. In this setting, the standard factorization assumption can be viewed as an implicit requirement that observable variables admit a jointly factorizable completion at the underlying level. We demonstrate that this requirement need not hold when the mapping from underlying configurations to observables is many-to-one. The resulting breakdown of probabilistic factorization does not rely on superluminal dynamics or hidden causal influences, but follows from information loss under projection. Observable outcomes correspond to equivalence classes of underlying configurations, preventing the assignment of independent local variables. We illustrate this mechanism with an explicit toy model producing Bell–CHSH violations while preserving operational no-signalling and statistical independence of measurement settings. The model is not intended to reproduce quantum correlations quantitatively, and may exceed the Tsirelson bound; its role is to isolate the structural origin of the violation. This analysis does not contradict Bell’s theorem, but identifies a class of effective descriptions for which its factorizability assumption does not apply. The framework preserves locality at the underlying level, introduces no additional hidden-variable dynamics, and does not modify quantum mechanics. It clarifies how classical factorization is recovered in regimes where the effective mapping becomes approximately injective. In the operator language of quantum theory, the same mechanism admits a natural reformulation in terms of reduction to an effective observable subalgebra by a noncommutative conditional expectation. Full article

Digital governance in higher education represents a complex systemic challenge, shaped by the intricate interplay of socio–economic–political contexts, technological infrastructures, and multiple stakeholders. Yet existing scholarship tends to examine these factors in isolation, lacking an integrated theoretical lens capable of capturing their systemic interdependencies and dynamic interactions. This study addresses this gap by drawing on the Social–Ecological Systems (SES) framework—a well-established systems theory for analyzing coupled social and ecological dynamics—to construct an integrated analytical framework for university digital governance. The framework organizes governance into three interconnected dimensions: external contexts, internal systems, and interaction effects. External contexts—including technological ecosystems and socio–economic–political factors—shape opportunities and constraints for universities. Internal systems, comprising resource systems, resource units, governance structures, and actors, form a complex network through information flows, resource flows, and institutional arrangements. Interaction effects emerge from these networks and are observed in both social outcomes and ecological outcomes, encompassing both positive and negative dimensions. The framework advances theory by extending the SES perspective to higher education, integrating multiple governance elements, and operationalizing core variables for measurement. Practically, it provides universities with a systematic tool for diagnosing digital governance performance, identifying gaps, and guiding optimization, while also supporting cross-institutional benchmarking and longitudinal monitoring. Future research should empirically test the framework, refine the operational indicators, and explore its applicability across diverse institutional and cultural contexts. Full article

Situated within Saudi Arabia’s Vision 2030 transformation agenda, this study examines the performance implications of sustainable logistics practices (SLPs) and the mediating role of Management Information Systems (MIS). Although achieving a “double bottom line” is a central premise of sustainable supply chain management, its realization in state-driven emerging economies remains unclear. Drawing on the Natural Resource-Based View and Stakeholder Theory, a structural equation model is tested using survey data from 372 logistics and supply chain professionals in Saudi Arabia. The model assesses the effects of Green Transportation, Sustainable Packaging, and Sustainable Waste Management on Environmental Sustainability and Economic Performance. The results reveal a clear “Economic Performance paradox.” While all three practices significantly enhance Environmental Sustainability, only Sustainable Waste Management directly improves Economic Performance. Moreover, Green MIS significantly mediates the relationship between sustainable logistics practices and Environmental Sustainability but shows no direct or mediating effect on Economic Performance. This indicates a prevailing compliance-oriented use of MIS, where firms prioritize environmental monitoring and reporting over operational optimization. This study demonstrates that the double bottom line is not automatic, but contingent on practice type and institutional context. By providing firm-level evidence from Saudi Arabia, the study extends sustainable logistics and information systems research and offers contextually grounded insights for managers and policymakers. Full article

This paper extends the metacybernetic framework by grounding its conceptual descriptions in first principles of information physics. We demonstrate that for living systems to organise efficiently under uncertainty, they must adhere to a strict recursive pattern, a “fractal seed” originating in the third-order interaction between potential and action. By utilising Fisher Information Field Theory (FIFT) within an Informational Realism paradigm, we formalise this process through variational analysis on an implicate–explicate manifold. Under a rigorous informational parsimony constraint (a functional analogue of the holographic principle), we treat the J-field as the dispositional reservoir of latent potential and the I-field as the operative field of structured configurations, and show how their autopoietic coupling generates the system’s Potential–Actuation trait poles as a scale-invariant viability structure This coupling reveals that the boundary substructure, which encodes the holographic content, directly conditions the emergent superstructure through a deterministic parity rule inherited from the dyadic logic of the minimal generic living system represented by ${\widehat{\theta }}_2$. Drawing on the application of Fisher Information, we show that maintaining informational parsimony requires the system’s architecture to oscillate: odd-numbered orders express two traits (dyads), whereas even-numbered orders express three (triads). This produces a canonical 2–3–2–3–2 sequence, preventing a combinatorial explosion of traits as systemic depth increases. We present the Cogitor5 model as a complete fifth-order exemplar of this rule, demonstrating how this rhythmic structural pattern enables self-evolution, systemic coherence, and collective intelligence in both biological and artificial agencies. Full article

Background/Objectives: Medical chatbots are increasingly integrated into healthcare to facilitate patient communication, often under the assumption that they reduce stigma and foster the disclosure of sensitive information. However, empirical support for this effect remains inconsistent. Drawing on online disinhibition theory, this study introduces the concept of machine-mediated disinhibition (MMD) to examine whether chatbot consultations elicit greater disclosure than human-mediated or face-to-face interactions. Methods: A scenario-based, between-subjects experiment (n = 373) compared three modes: face-to-face, human-through-computer, and chatbot. Results: Results revealed no evidence of increased disinhibition in the chatbot condition. Conversely, participants were significantly less willing to disclose sensitive health information to chatbots than to humans. Conclusions: These findings suggest that in high-stakes healthcare contexts, trust-related concerns override disinhibition effects, leading to avoidance rather than openness. This study challenges the prevailing assumption that AI agents inherently facilitate disclosure and highlights the critical need for further research on trust in AI-mediated medical communication. Full article

With the in-depth advancement of the “Digital China” initiative, policies and research discourses related to the digital economy have continued evolved, making it necessary to systematically examine their stage-specific characteristics and underlying logic from a long-term perspective. Accordingly, this study adopts information society theory as the analytical framework and selects the annual series of reports on China’s digital economy development published by the China Academy of Information and Communications Technology (CAICT) from 2015 to 2024 as the research corpus. Using text mining techniques and Latent Dirichlet Allocation (LDA) topic modeling, this paper conducts a longitudinal examination of the stage-wise systemic evolution of key topics in China’s digital economy development. The findings indicate that over the past decade, the topic structure of China’s digital economy has followed a clear evolutionary trajectory, progressing from “informatization-driven development” to “platform expansion,” and subsequently to “data factors and institutional governance.” In the early stage, the focus was on information infrastructure development and industrial integration; the middle stage shifted toward the platform economy and enterprise growth; more recently, the emphasis has increasingly been placed on the construction of data factor markets and the improvement of governance frameworks. This process of topic evolution not only reflects changes in the practical forms of the digital economy but also reveals the ongoing adjustment of the state’s cognitive framework and governance logic regarding digital economy development. These findings provide empirical evidence for understanding the systemic evolution of China’s digital economy over time. By identifying the stage-specific pathways of China’s digital economy, this study extends the application of information society theory within this context and provides new empirical evidence for understanding the evolutionary logic underlying high-quality digital economy development. Full article