Search Results (7,858)

This study investigates the determinants of financial performance among Micro, Small, and Medium Enterprises (MSMEs) in Indonesia, addressing the critical issues of low accountability and limited access to capital. Grounded in the Resource-Based View and Dynamic Capabilities Theory, the research examines the impact of accounting information systems, management knowledge capability, and digital platform capability on financial performance, mediated by digital innovation. A quantitative approach was employed, utilizing a cluster random sampling survey of 403 MSME owners across Indonesia’s major islands. Data were analyzed using Structural Equation Modeling (SEM) with AMOS software. The results reveal that accounting information systems, management knowledge capability, and digital platforms significantly enhance financial performance. Notably, digital platform capability emerged as the most potent driver. Furthermore, digital innovation proved to be a vital mediator, transforming management knowledge and platform capabilities into tangible financial outcomes. The study concludes that while digital tools provide essential infrastructure, innovation serves as the critical mechanism for unlocking value. These findings suggest that MSMEs must transition from passive technology adoption to active digital innovation to achieve sustainable financial success in the digital economy. Full article

Surgical resection of liver and lung metastases in breast cancer is increasingly considered a viable option for select patients with oligometastatic disease. Historically regarded as palliative, surgery is now supported by retrospective data suggesting potential survival benefits, particularly in patients with hormone receptor-positive or HER2-positive tumors, long disease-free intervals, and limited metastatic burden. This narrative review summarizes recent evidence on the surgical management of breast cancer metastases to the liver and lung, with a focus on patient selection, perioperative outcomes, and long-term survival. Liver metastasectomy has shown 5-year overall survival rates of up to 60% in well-selected patients, while pulmonary metastasectomy is associated with comparable outcomes when resection is complete and nodal involvement is absent. Minimally invasive techniques and non-surgical approaches, such as microwave ablation and stereotactic radiotherapy, expand treatment options for patients unfit for surgery. The review also explores emerging tools influencing surgical decision-making, including circulating tumor DNA for minimal residual disease detection, transcriptomic profiling to predict organotropism, and artificial intelligence (AI)-driven platforms that assist with surgical planning and multidisciplinary case evaluation. While prospective validation remains limited, these technologies may help redefine surgical candidacy through biologically informed algorithms. Ultimately, the integration of surgery within a multimodal, personalized treatment strategy—guided by systemic control, tumor biology, and evolving digital tools—represents an evolving and biologically informed direction for rigorously selected patients with visceral breast cancer metastases. Full article

Cognitive warfare is a hybrid threat that combines information manipulation with psychological influence, often amplified by digital platforms and synthetic media. Conventional cybersecurity tooling is optimized for technical intrusion and offers limited support for anticipating and responding to influence operations. This paper presents a conceptual framework that structures cognitive warfare threats with General Morphological Analysis (GMA) and links plausible configurations to indicator profiles and response playbooks. We first conduct a PRISMA-informed literature review (2018–2025) to derive a five-dimensional taxonomy (actor, tactic, medium, target, objective). We then apply cross-consistency assessment to remove implausible state-pair combinations and obtain a reduced library of internally consistent scenarios. To support analyst-guided triage, we outline an AI-enabled workflow that maps observable signals to taxonomy states, matches events to scenarios, and prioritizes responses via an auditable, policy-set risk score. Finally, we illustrate the framework on three publicly documented cases and show how each case maps to scenario vectors, indicators, and playbooks. No end-to-end system implementation or performance metrics are reported; the contribution is the structured scenario library and the traceable mapping from observations to response guidance. Full article

Digitalization is increasingly reshaping business models, yet the mechanisms through which specific digital technologies influence business model transformation in renewable energy remain insufficiently understood. Unlike prior research that treats digitalization and business models separately or focuses on macro-level impacts, this study examines how digital technologies affect business model components—value creation, value delivery, and value capture—in renewable energy firms and the extent to which they drive business model adaptation, evolution, or innovation. It aims to combine insights from the literature on digitalization, sustainability, and business models. Through a systematic literature review following the four-phase PRISMA methodology, 32 peer-reviewed studies were analyzed using a combination of descriptive, bibliometric, and Gioia-based thematic coding analyses to identify structures and patterns across the dataset. The analysis introduces a functional grouping perspective, linking digital technologies to business model components, and business model changes. Findings reveal that the same technology can enable multiple, overlapping transformation pathways and that outcomes vary depending on how technologies are implemented and embedded within firm operations. This study contributes theoretically by integrating a functional technology lens and sustainability lens with business model change typologies—a novel integrative framework absent from the prior literature. It practically provides a framework to help renewable energy firms move toward sustainability-oriented reconfiguration of business models by prioritizing and integrating digital tools effectively, thereby enhancing competitive advantage and accelerating value capture from digitalization. This paper closes with directions for future research on technology-enabled business model change. Full article

This article aims to synthesize the current ecosystem of open-source tools for Integrated Circuit (IC) design, covering the entire digital design flow from Register-Transfer Level (RTL) description to fabricable layouts. The survey categorizes and analyzes tools across major stages of design, including code-generation tools, logic synthesis, simulation, and physical design flow. Special emphasis is given to the fabricable open-source Process Design Kit (PDK), which enables the physical realization of open-hardware projects. By examining interoperability, limitations, and maturity across this toolchain, the article provides a comprehensive overview of the Electronic Design Automation (EDA) landscape and identifies the research and educational opportunities that arise from democratizing silicon design through open and reproducible workflows. Full article

The increasing use of integrated renewable energy sources (RESs) is undoubtedly reshaping the structure of power systems. In such conditions, achieving energy efficiency and sustainability requires the development and integration of digital solutions to manage energy flows and assets optimization. This paper aims to provide a comprehensive review of the successful integration of artificial intelligence (AI) in the energy sector, particularly in relation to the high penetration of renewable energy. The paper presents trends and potential scenarios in the digitalization of energy, along with the associated challenges. It analyzes particular applications of AI tools in strategic areas of the energy sector. Five key areas of the energy sector are identified where AI tools are applied: forecasting electricity generation from RES; forecasting demand and price fluctuations on the electricity spot market; the real-time management of energy flows and assets in active microgrids; and data processing and analyzing, and general industrial direction. The article also attempts to summarize the current status, goals, key areas, and activities in the irreversible transformation of power structures into digital intelligent ones. This digital transformation is a gradual process with consecutive steps. To improve understanding and clarity, the authors present a three-phase roadmap of AI adoption. To develop an adequate AI integration strategy, it is necessary to understand the technologies, algorithms, hierarchical structure, and connections within this structure. Accordingly, the article presents a taxonomy of the hierarchical structure of AI. The subsequent step involves the sequential construction of a digitalization model. Here, the authors consider it necessary to present a 4-layer structure model of AI energy democracy. Finally, through a comparative analysis of different types of intelligent applications for energy problem solving, guidelines are provided for successful decision making in compliance with the specified harmonized standards and protocols. Full article

The advancement of digital technologies such as photogrammetry, 3D scanning, Geographic Information Systems (GISs), and artificial intelligence has profoundly transformed archaeology by enabling more accurate documentation, analysis, and visualization of cultural heritage. These tools facilitate evidence preservation, enhance research processes, and broaden the possibilities for interpreting and disseminating archaeological knowledge. This scoping review synthesizes recent progress in the application of digital technologies for the reconstruction of archaeological evidence, emphasizing their main impacts on archaeological research while addressing existing challenges, limitations, and future perspectives, particularly focusing on the integration of artificial intelligence. A systematic review of the scientific literature was conducted using the PRISMA^® methodology, analyzing documents retrieved from databases such as Scopus, PubMed, IEEE Xplore, and ScienceDirect. One hundred and sixteen papers were selected, with a Cohen’s Kappa coefficient of 0.463 ensuring the reliability of the selection process. The findings reveal that the integration of digital technologies is redefining archaeological reconstruction methods and expanding the horizons of historical and heritage knowledge, requiring collaborative, ethical, and interdisciplinary approaches to achieve a more accurate, accessible, and sustainable archaeology in the future. Full article

Against the backdrop of the digital economy reshaping the global competitive landscape and the urgent demand for sustainable development, how data factors drive startups to break through resource constraints, achieve a niche leap, and realize long-term sustainable growth has become a critical issue of common concern in academia and policy circles. Drawing on resource orchestration theory and the dynamic capability view, this study constructs a theoretical framework of “Data Factor Allocation→Digital Capability Integration→Niche Leap→Sustainable Growth” and conducts an empirical test, using 412 technology-based startups as samples. The findings are as follows: (1) Data factor allocation (encompassing scenario-based access, lightweight tool penetration, and ecological sharing) exerts a significant inverted U-shaped relationship impact on both digital capability integration and the startup niche leap (range of quadratic term coefficients for core dimensions: −0.165~−0.203, p < 0.01), with turning points between 3.41 and 3.72 on a 5-point scale. Excessive data investment may trigger risks of capability hollowing and niche lock-in, hindering sustainable growth. (2) Digital capability integration (including technology application, resource coordination, and dynamic adaptation capabilities) plays a non-linear mediating role, with mediation proportions ranging from 18.7% to 32.4%. Among them, the technology application capability exhibits the highest transmission efficiency between lightweight tool penetration and the niche leap (32.4%), thereby promoting sustainable value creation. (3) The moderating effect of data governance maturity is heterogeneous: governance adaptability significantly strengthens the mediating path of the technology application capability (β = 0.187, p < 0.01) and security compliance enhances the transmission efficiency of the resource coordination capability (β = 0.165, p < 0.01), while the moderating effect of open sharing is insignificant. These findings provide a dynamic framework for the non-linear and sustainable leap of startups by integrating two core theories. They offer a decision-making basis for enterprises to optimize data allocation strategies (e.g., controlling allocation thresholds to avoid resource waste) and for governments to improve governance policies (e.g., data vouchers, trusted data spaces), thereby facilitating the implementation of the “Data Factor × Innovation and Entrepreneurship × Sustainable Development” initiative and promoting the sustainable growth of the digital economy ecosystem. Full article

This study explores how digital media ecosystems shape collective visions of the future under conditions of rapid technological innovation and the growing influence of artificial intelligence (AI). Drawing on a large corpus of social media content comprising 50,036,592 tokens, the research examines institutional narratives and user-generated responses through a hybrid methodological framework. This framework combines information-wave detection, network analysis, semantic and associative modeling (TextAnalyst 2.32), and interpretation supported by a large language model (GPT-5). The methodological contribution of the study lies in the integration of network-based and semantic algorithms with AI-driven analytical tools for the examination of large-scale textual data. The findings indicate that media discourses about the future operate as key mechanisms through which societies interpret the environmental, social, and economic consequences of technological change. Institutional actors promote multiple future-oriented models that often conflict with one another at both discursive and practical levels. In contrast, user-generated content reflects widespread fear, skepticism, and distrust. Prominent themes include nostalgia for the past, anxiety about socio-economic and environmental consequences, and concerns related to expanding forms of digital control. The analysis also reveals divergent perspectives on urban development. Positive narratives emphasize ecological balance, a comfortable urban environment, thoughtfully designed mixed-use development, and solutions to transportation challenges. Negative narratives, by contrast, focus on over-densification, environmental degradation, and the erosion of privacy in technologically saturated urban spaces. Full article

Urban hydrological risks are endangering vulnerable populations, particularly in densely populated metropolitan areas undergoing rapid land use transformation. This study uses geospatial analysis to identify zones in the Athens metropolitan area that are prone to surface water accumulation and stream flow development during extreme rainfall events. Two spatial indices were developed by integrating digital elevation models, flow accumulation, slope, aspect, the topographic wetness index, and classified road network data: a Surface Water Accumulation Index and a Stream flow Pathway Index. Roads were categorized based on their orientation relative to the direction of the slope, which allowed for an assessment of their influence on hydrological flow. Both indices were classified into five risk levels representing gradients of hydrological vulnerability. The spatial patterns revealed by this analysis show strong correlations with flood-prone areas and natural drainage systems. These insights are essential for guiding urban planning efforts aimed at reducing hydrological hazards, particularly for at-risk groups such as the homeless. This approach offers a valuable tool for promoting sustainable, socially inclusive landscape management. Full article

Digital calendars are interactive representations of time that shape both scheduling outcomes and the micro-process of searching, verifying, and revising candidate placements. We examine calendar horizon—whether weekend time is visible in the default week view—as a boundary affordance in scheduling interfaces. Using eye tracking and interaction logs, we model each scheduling episode as a sequence of placement attempts and align gaze to each attempt, partitioning it into Early/Mid/Late phases and summarizing attention across structural AOIs (task panel, calendar grid, and the weekend column when present). Two experiments used drag-and-drop and dropdown slot-picking; weekend visibility was manipulated within the dropdown interface, while evening slots remained available. Across 105 participants (1018 task episodes), AttemptsCount ranged from 1 to 7. AttemptsCount predicted gaze-based process cost: each additional attempt corresponded to ~56% more total fixation duration. Personal tasks required more attempts than work tasks and elicited stronger Late-phase weekend verification when the weekend was visible. Horizon cues also shifted boundary outcomes: hiding the weekend reduced weekend placements and increased reliance on evening scheduling, indicating displacement into adjacent time regions. These findings position calendar horizon as a design lever that shapes both process (verification) and outcomes (boundary placements), with implications for calendar UIs and mixed-initiative scheduling tools. Full article

Sustainability education increasingly calls for innovative learning environments that help learners recognize ecological interdependencies and challenge anthropocentric worldviews. Everyday multispecies relationships, such as with companion animals, often underexplored, offer opportunities for cultivating ecological literacy and care. This paper introduces Augmented Ecological Relating (AER), an approach that combines Augmented Reality (AR) with embodied inquiry to explore multispecies perspectives. Going beyond embodied inquiry, AER specifies how digital augmentation can systematically support learners’ iterative noticing, ethical reasoning, and action within everyday multispecies ecosystems. We draw on a virtual summer workshop for adolescents in which participants used AR filters simulating dog and cat vision to investigate their pets’ sensory worlds. We used qualitative case study methods to examine how AR tools mediated human youths’ noticing, inquiry, and reflection. We found that the AR filters used in the study’s context enabled participants to critically reconsider pet behaviors within home ecologies. Participants recognized companion animals as ecological beings with distinct sensory experiences, explored interconnections among humans, animals, and environments, and reflected on ethical responsibilities in multispecies relationships. Through iterative inquiry, youth moved beyond companionship to sustainability-oriented perspectives grounded in relational care, systems thinking, and practical action. By embedding digital augmentation into everyday contexts, AER enabled learners to engage with more-than-human perspectives, fostering ecological awareness, ethical reflection, and sustainability literacy in accessible, meaningful ways. Full article

Diabetes mellitus is a growing global health challenge, and digital health technologies offer new opportunities to support self-management. Mobile applications can benefit both patients and healthcare professionals; however, awareness and integration of these tools into community pharmacy practice remain limited. As accessible frontline providers, pharmacists are well positioned to promote digital health, yet their readiness and engagement require further investigation. A cross-sectional survey was conducted among community pharmacists in Serbia using a structured questionnaire. Developed through a consensus-based process, the instrument assessed pharmacists’ awareness, attitudes, and experiences with digital health technologies, focusing on mobile applications for diabetes self-management. Only 15.8% of pharmacists were aware of such applications, and 2.4% reported receiving relevant training. Higher digital health technology literacy was associated with greater awareness, confidence, and preference for digital learning. Most participants supported expanding pharmacists’ roles in advising patients on digital tools and expressed interest in structured education and official guidance. These findings indicate limited awareness and training in mobile health applications among community pharmacists. Enhancing digital competencies through targeted education and structured guidance may facilitate greater integration of digital tools into routine pharmacy practice and strengthen pharmacists’ roles in chronic disease management. Full article

The accelerated integration of Generative Artificial Intelligence (GenAI) tools such as ChatGPT is transforming learner engagement, instructional design, and institutional governance in education. This systematic literature review synthesizes theory-driven scholarship on GenAI adoption and pedagogical use through the Antecedents–Decisions–Outcomes (ADO) framework, examining how cognitive, motivational, technological, and institutional factors collectively shape implementation and learning outcomes. Drawing primarily on the Technology Acceptance Model (TAM), Self-Determination Theory (SDT), and Institutional Theory, the review integrates complementary insights from Constructivist Learning and Diffusion of Innovations perspectives to conceptualize how antecedents influence decision-making and outcomes across educational settings. The findings indicate that learner motivation, perceived usefulness, digital literacy, and institutional readiness constitute key antecedents affecting GenAI adoption. Decision processes—spanning instructional design, ethical regulation, and pedagogical adaptation—mediate how these antecedents translate into practice. Outcomes reveal a dual trajectory: GenAI enhances personalization, feedback, and self-regulated learning, yet introduces challenges related to ethical ambiguity and overreliance. The review offers a conceptually integrated synthesis that bridges motivational, technological, and organizational perspectives, advancing a theoretical roadmap for ethical and sustainable GenAI adoption. For educators and policymakers, the findings emphasize transparent governance, faculty capacity-building, and equitable access to ensure that innovation remains aligned with pedagogical integrity and human-centered values. Full article

Emerging digital technologies are increasingly embedded in consumer-facing financial services, reshaping how users experience, evaluate, and engage with AI-mediated interactions. This paper investigates how the perceived sociality of AI Digital Human Advisors influences user experience in digital financial services. Sociality—defined as the extent to which users perceive an AI Digital Human Advisor as a socially capable actor (e.g., responsive, relational, and role-embedded) rather than a purely functional tool—was experimentally manipulated across four controlled behavioral experiments simulating interactions on financial platforms. The results from four controlled experimental simulations consistently demonstrate that, under controlled interaction conditions, high-sociality AI advisors significantly enhance both utilitarian and hedonic value. Social presence was found to partially mediate these effects, revealing the psychological mechanism through which social cues embedded in emerging AI technologies are transformed into experiential value. Furthermore, two boundary conditions were identified: communication style and usage context. Communication framed around task completion amplified the influence of sociality on utilitarian value, whereas interaction styles emphasizing social connection strengthened its effect on hedonic value. Likewise, purchase-related scenarios heightened functional perceptions, while browsing situations elicited stronger emotional responses. By situating AI Digital Human Advisors within the broader context of emerging digital technologies, these findings extend Social Response Theory into AI-mediated financial environments and provide insights into how technologically enabled social cues shape consumer experience and behavior in digital finance. Full article