Search Results (3,807)

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 study focuses on the argument that greenwashing behavior (GWB) among key stakeholders leads to the degradation of governance networks in large-scale construction projects. Grounded in opportunism theory, a cross-scale computational model is developed by integrating a four-party evolutionary game with differential dynamics to capture the co-evolution of stakeholder strategies and network states. The results indicate that GWB exhibits free-riding and herd-like characteristics, and that governance networks possess a degradation equilibrium. Sensitivity analysis based on 50,000 Monte Carlo simulations shows that the frequency of GWB by subcontractors has the greatest impact on network degradation (sensitivity range: 0 to −0.98), followed by general contractors (0 to −0.38), while the influence of supervisory roles is relatively weaker. In contrast, contractual penalties demonstrate limited effectiveness (sensitivity range: −0.08 to 0.06), whereas reputational loss exerts a stronger inhibitory effect (up to −0.5 during the mid-stage evolution). These findings suggest that contract-based governance alone is insufficient to constrain GWB, thereby challenging the conventional assumption of its effectiveness. The results highlight the necessity of shifting from contract-centric governance toward reputation-based and market-oriented mechanisms to effectively mitigate GWB and enhance the resilience of green construction governance. 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

Artificial intelligence (AI) tools are increasingly integrated into mathematics education, yet most reviews emphasize achievement rather than how AI shapes mathematical thinking. This scoping review mapped literature published between 2020 and 2026 on AI-supported mathematics learning through three cognition frameworks: APOS (Action–Process–Object–Schema), Sfard’s process–object duality and reification, and Conceptual Image theory. Searches were conducted in Scopus, Web of Science, ERIC, PsycINFO, Education Source, and IEEE Xplore, followed by duplicate removal and Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR)-aligned screening. Twenty-one peer-reviewed studies met inclusion criteria (18 empirical studies plus three theoretically oriented studies). Evidence growth accelerated after 2022, with most studies situated in secondary and higher education. Large language models (LLMs) and Intelligent Tutoring Systems (ITS) were the most frequently investigated modalities. Across studies, AI commonly supported theoretically inferred action-level execution and procedural management (APOS) via adaptive feedback, hinting, and stepwise scaffolding, and it often broadened learners’ conceptual images through multiple representations and generated explanations. However, these interpretations were necessarily cautious, because very few studies directly operationalized theory-linked conceptual mechanisms such as process internalization, object encapsulation, reification, or alignment between conceptual images and formal definitions. In LLM-supported contexts, gains in explanation quality coexisted with risks of procedural outsourcing when students relied on generated solutions without prior reasoning. By contrast, ITS-based environments more often supported tightly structured procedural engagement, suggesting that different AI modalities afford different forms of cognitive support and risk. Overall, AI’s conceptual impact appears to depend less on tool availability and more on instructional orchestration (task design, prompting, and teacher mediation). The findings also suggest that sustainability-related dimensions—particularly learner agency, transparency of AI support, and equitable participation—are closely connected to whether AI use promotes durable conceptual learning rather than superficial performance gains. Future research should operationalize cognitive transitions, assess structural understanding, and report AI-use conditions transparently to support cumulative, theory-driven synthesis. Full article

Although identity development is often framed as a task of adolescence, identity continues to evolve across the life course. Midlife, in particular, involves significant role change, reflection, and meaning-making, yet women’s midlife identity development within religious contexts remains understudied. Using life course and narrative identity frameworks, this qualitative study examined how women navigate identity shifts during midlife within a family-centered faith context. In-depth semi-structured interviews were conducted with 30 women aged 38–69 who identified as practicing members of The Church of Jesus Christ of Latter-day Saints in six countries. A grounded theory analysis revealed three interrelated processes, identity disruption, re-evaluation, and revision, while anchoring identity in core sources of meaning. Faith and purpose provided continuity across transitions, supporting coherence, resilience, and growth. These findings challenge deficit-based models and position midlife as a generative period of ongoing identity development. Full article

The contemporary media landscape has sustained a substantial transformation with the rise of AI-driven algorithmic platforms that enable activist organizations to produce and disseminate their own forms of political communication and campaigns. This study examines the YouTube channel of Code Pink, a prominent U.S.-based anti-war and social justice organization, to explore how activist media practices intersect with contemporary forms of journalism. Over a one-month period, video transcripts from the organization’s YouTube channel were analyzed using NVivo 15, employing a hybrid qualitative approach that combined inductive and deductive coding. Deductive codes were informed by sustained observation of the channel over one year (short and long videos on YouTube, TikTok, and X), supplemented by engagement with relevant news coverage, while inductive coding followed grounded theory principles, allowing themes to emerge directly from the transcripts. Large Language Models (LLMs) were employed as exploratory analytic tools to support AI-assisted qualitative analysis, complementing manual coding processes. The analysis focuses on how Code Pink frames political events and U.S. foreign policy through confrontational interviews, protest documentation, and the dissemination of commentary to online audiences. Findings suggest that the organization’s video content operates simultaneously as political activism, protest performance, and quasi-journalistic reporting. Activists frequently adopt journalistic techniques—including interviewing political figures, providing on-the-ground commentary, and framing narratives around public accountability—while also advancing explicit ideological positions that challenge dominant media narratives. The study highlights how platform-based activist media blurs the boundaries between journalism, advocacy, and political performance, contributing to the construction of alternative public narratives in the digital age. Full article

Farmland management rights (FMR) mortgage lending has been advanced as a central instrument of rural credit reform in China, yet the program has consistently failed to sustain itself in the absence of direct government facilitation. Drawing on five national and provincial pilot counties in Henan Province, this study investigates the structural factors underlying this sustainability failure. We employ a sequential mixed-methods design: grounded theory analysis of in-depth interviews, policy documents, and media reports from five focal sites to inductively construct a constraint framework, followed by structural equation modeling (SEM) validation using 1055 survey responses. Our grounded theory analysis identifies three internal constraint categories—property rights insecurity, a thin secondary land market, and subject-level agricultural risk—and one external environmental constraint, which together produce a state of mutual non-recognition: neither financial institutions nor farming households regard FMR as legitimate collateral. Notably, the effect of collateral acceptance on farmer mortgage willingness is statistically insignificant, revealing that demand-side barriers are more deeply entrenched than supply-side institutional improvements alone can resolve. These findings challenge the premise that legal formalization of land rights is sufficient to generate market-driven credit activity, and call attention to the equally important role of institutional ecosystem development—encompassing land markets, appraisal capacity, supervisory infrastructure, and rural credit culture. The insights carry direct relevance for developing economies exploring land-backed agricultural credit as a rural finance strategy. Full article

The rapid proliferation of generative artificial intelligence (GenAI) tools has created an urgent need for instruments to evaluate their educational value as teachers, faculty, administrators, and instructional designers consider adopting them. While rubrics exist to assess mobile applications and virtual reality tools, no comparable instrument has been developed specifically for large language models (LLMs) and AI media generators. The authors reviewed existing evaluation rubrics for edtech and GenAI tools, with edtech meaning digital tools that support ethical teaching to improve student learning and GenAI referring to neural networks that simulate human interactions by contextualizing relevant content based on learning needs. Grounded in Waks’ framework, the resulting Edu-GenAI Rubric comprises multiple dimensions organized into five domains: the Instrumental, Technical, Hedonic, Use, and Beneficial values. Dimensions include accuracy, productivity, personalization, citation, user interface, user experience, sharing, storage, and ethical dimensions encompassing data privacy, data transparency, guardrails, fair use, and algorithmic discrimination. The Edu-GenAI Rubric offers decision-makers with a preliminary, theory-informed instrument for evaluating GenAI tools in educational contexts that can be applied to institutional adoption decisions, developer benchmarking, and future research. Full article

This paper presents a theoretically grounded integration of deterministic Q-learning with relational game theory (QLRG) for efficiently identifying minimal winning coalitions in Online Social Networks (OSNs). We address the fundamental challenge that coalition formation is NP-hard under traditional approaches by leveraging structural properties of relational dependencies and Armstrong’s axioms to transform the problem into one solvable in polynomial time. Our framework reduces the state space from exponential O(2ⁿ) to O(n²) through a sufficient statistic representation based on coalition size, follower reach, and terminal status, while achieving O(n⁴) time complexity under deterministic, static, and sufficiently symmetric influence structures. The QLRG framework introduces three critical innovations: (1) a principled agent selection mechanism derived directly from the Q-function that eliminates heuristic weight tuning; (2) a formal Boost action defined through temporal closure operators that captures influence spread dynamics; and (3) a constrained MDP formulation that enforces relational consistency through action elimination rather than penalty terms. We prove that the Bellman optimality operator forms a contraction mapping, guaranteeing deterministic convergence to optimal policies with established rates of O(1/√k) for decreasing learning rates or linear convergence up to bias for constant rates. To bridge the gap between this idealized model and the asymmetry inherent in real OSNs, we further develop a cluster-based sufficient statistics approach. By partitioning the network into communities with bounded internal variation, we relax the global symmetry requirement while preserving polynomial state space complexity, and obtaining a single within-community swap changes the optimal Q-value by at most ε_i/(1−γ), which is a local Lipschitz continuity result. The implications of this are both theoretical and practical, and they form the bedrock for relaxing the global symmetry assumption in the QLRG framework. Empirical validation on synthetic networks satisfying the symmetry assumption demonstrates that QLRG consistently identifies minimal winning coalitions matching the optimal solutions found by exhaustive search, while operating with polynomial-time complexity. Unlike conventional approaches, our framework simultaneously satisfies four critical properties: deterministic convergence, policy optimality, minimal coalition identification, and computational tractability. The work bridges computational social science and operations research, providing a mathematically rigorous foundation for strategic decision-making in influencer marketing and coalition formation. While the framework requires symmetry assumptions that may only hold approximately in real-world OSNs, it establishes an idealized baseline for future extensions addressing stochasticity, dynamics, and partial observability. This research represents a paradigm shift from empirical improvements to theoretically grounded convergence guarantees for coalition formation problems, demonstrating how structural mathematical insights can transform intractable problems into efficiently solvable ones without sacrificing solution quality. 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

Amid escalating global crises, tourism sustainability is threatened by heightened industry vulnerability, yet the intrinsic coupling of tourism industry vulnerability (TIV) and resilience (TIR) remains underexplored via systemic theoretical frameworks. This study aimed to define TIV/TIR as industry-specific constructs and develop an integrated analytical model grounded in dissipative structure theory to characterize tourism systems’ crisis responses. We selected Southwest China’s ethnic minority regions (Guizhou, Guangxi, Yunnan) as cases, using 2015–2024 prefecture-level panel data to explores the spatio-temporal differentiation characteristics of TIV/TIR. Results revealed severe COVID-19-induced TIV surges in 2020–2021, followed by rapid TIR rebounds; TIV and TIR exhibited a significant negative correlation with regional heterogeneity. Most cities showed high TIV–low TIR, with Guizhou displaying negative TIV-TIR spatial autocorrelation and Guangxi–Yunnan showing TIR clustering; inter-city TIV disparities widened while TIR levels converged, leading to a low-vulnerability, balanced-resilience tourism system by 2024. This research introduces the novel sensitivity-adaptive capacity-recovery (SACR) framework, advancing understanding of TIV-TIR dynamics and providing targeted empirical insights for tourism resilience building and sustainable development in resource-dependent destinations. Full article

Background/Objectives: Diet is implicated in the high burden of mental health on society, and research examining associations between these two fields is growing. However, qualitative explorations are lacking, especially within culturally diverse settings. This study aims to explore the beliefs on the mechanisms of the relationship between diet, food systems, and mental health, and the lived experience of such, through a case study of one Caribbean Small Island Developing State, to inform culturally grounded public health strategies that integrate nutritional and psychological well-being. Methods: Fifteen interviews with food system stakeholders and five focus groups with the general public were conducted. Transcripts were analyzed using a grounded theory approach with a critical realist epistemological stance. Results: Four major categories centered on beliefs of mechanistic effects of diet on mental health, as well as broader perspectives of the relationship between food systems, food experiences, and mental health. Participants believed that (1) unhealthy diets of processed and chemically treated foods contribute to poor mental health and that (2) food insecurity is a key threat to mental health, but they also believed that (3) consumption of locally produced foods and (4) residing in agricultural communities can be beneficial to mental health. Conclusions: Participants recognize that diet influences mental health through physiological, social, and structural pathways, but this connection is threatened by rising dependence on imported, processed foods. Along with complementary quantitative research, the findings highlight the potential of expanding nutritional health literacy and clinical guidance and strengthening local food systems and traditional diets for mental well-being among Caribbean Small Island Developing States. Full article

China’s rural public open spaces (POS) are largely governed as common-pool resources through self-organized collective arrangements, often regarded as a viable pathway to sustainable commons management. Yet, in practice, these systems remain prone to overuse and under-maintenance, reflecting collective action failures associated with the tragedy of the commons. The governance of rural POS therefore constitutes a complex social–ecological problem shaped by the interplay of institutional rules, biophysical conditions, and user–stakeholder interactions. Taking Taigu District in Shanxi Province—characterized by heterogeneous social–ecological contexts and collective action dilemmas—as the empirical case, this study develops a meso-level baseline model to identify the key conditions (design principles) for sustainable rural POS governance. Adopting an expert-based epistemological approach, 24 specialists in rural governance (scholars, planners, and local administrators) were engaged. Grounded in commons and collective action theories within the Social–Ecological Systems (SES) framework and informed by Transaction Cost Economics (TCE), the study operationalizes a Delphic Hierarchy Process (DHP), combining three rounds of Delphi to establish consensus on governance conditions with the Analytic Hierarchy Process (AHP) to derive their relative weights. The model specifies 14 governance conditions across four interrelated dimensions: ecological (e.g., clearly defined resource boundaries and congruence between resource characteristics and user needs), institutional (e.g., simple and enforceable rules, accessible conflict-resolution mechanisms, accountable monitoring, and calibrated external support), social (e.g., social capital, leadership capacity, clearly defined user boundaries, and group interdependence), and interactional (e.g., resource dependence, equity in benefit distribution, and supply–demand alignment). It further clarifies their relative importance and systemic interdependencies. By operationalizing commons design principles within a meso-level analytical framework, the study advances their empirical application in rural planning and offers five targeted managerial implications to strengthen institutional robustness and the long-term sustainability of self-governed rural POS. Full article

We performed a theoretical analysis (the PBE-D2/DNP level of the density functional theory with the use of the DSPP pseudopotentials) of the geometries, bonding and frontier orbital energies, spin and charge distribution for the entire series (from La to Lu) of lanthanide atoms interacting with I_h−C₈₀ cage, for both η⁵ and η⁶ exohedral coordination patterns. In certain regards, the exohedral η⁵ and η⁶ coordination of Ln atoms to the C₈₀ fullerene cage exhibits similar qualitative and semi-quantitative trends (the bonding strength, shortest Ln^…C distances, charge and spin of lanthanide atoms). The most interesting aspect is the molecular spin of the complexes, where we observed different patterns of ferromagnetic and antiferromagnetic coupling. Three complexes represent an extreme, when the antiferromagnetic coupling results in zero or close-to-zero molecular spin. In some cases, the molecular spin is a simple sum of 2 e of the isolated C₈₀ cage and the spin of an isolated Ln atom. However, the most common situation is when another 2 e spin adds: it is best illustrated with Eu (spin of 7 e for the atomic ground state), where the molecular spin of its η⁵ and η⁶ complexes is not about 9 e but reaches almost 11 e. Full article

Value co-creation among diverse actors in digital innovation ecosystems (DIEs) exhibits characteristics of high complexity and dynamic evolution. Grounded in the Quadruple Helix Theory, this study develops a conceptual model that interlinks “supervisory guides, knowledge providers, technology transformers, and user demand parties.” This model is defined by organizational oversight as its nexus, knowledge and technology as its foundation, outcome transformation as its core, and user needs as its orientation. Building upon this conceptual foundation, we establish a four-party evolutionary game model involving “innovation regulators (government), innovation producers (academic/research institutions), innovation decomposers (enterprises), and innovation consumers (users).” This analytical framework is then applied to systematically investigate the dynamic evolutionary mechanisms and collaborative pathways for value co-creation in DIEs. We construct the payoff matrix and replicator dynamics to derive the system’s Evolutionarily Stable Strategies (ESSs). Numerical simulations via MATLAB R2023b identify the stability conditions for each party’s strategic choices and unravel the influence mechanisms of key parameters. The results demonstrate nine distinct ESSs, categorized into three types: low-level stability, regulation-dominated transitional stability, and high-level cooperative stability. While the agents’ initial strategies do not alter the system’s final equilibrium state, they significantly impact the speed of evolutionary convergence. Critical factors—including regulators’ intervention costs, subsidy and penalty mechanisms, producers’ and decomposers’ cooperation and default costs, and consumer feedback behaviors—collectively drive the system toward the ideal (1, 1, 1, 1) equilibrium. Theoretically, this study enriches the perspective on multi-agent collaboration in value co-creation by introducing a dynamic quantitative analytical framework, thereby addressing a notable gap in the literature. Practically, it provides actionable insights for mechanism design and a solid foundation for policy optimization, aiming to foster a synergistic governance system that integrates “regulatory guidance, market incentives, and social feedback.” Full article