Search Results (1,206)

The grocerant represents an emerging hybrid retail–foodservice format integrating grocery shopping, prepared meals, and in-store dining. Although practically significant, the academic literature remains limited and dispersed. This PRISMA-informed semi-systematic review synthesizes 16 studies—including direct grocerant research and adjacent work on retail innovation, prepared foods, and digital food retail—to clarify the current state of knowledge. The review followed structured database searches, citation tracking, title/abstract screening, and full-text eligibility assessment. Three main perspectives emerged. First, consumer-focused studies emphasize customer experience, food healthiness, multidimensional perceived value (functional, hedonic, social, and financial), brand prestige, in-store dining behavior, and loyalty. Second, strategic research positions grocerants within retail format innovation and competitive convergence between grocery and restaurant sectors. Third, operational perspectives link grocerants to prepared-food systems, retail food environments, and omnichannel transformation. Major gaps include limited operational and comparative research, geographic concentration, and weak digital integration. The review suggests that grocerants function as evolving systems where convenience, experience, branding, and digital transformation converge. Full article

Drought remains a persistent challenge affecting agricultural and pastoral livelihoods, particularly in dryland mixed crop–livestock systems. Water Monitoring and Early Warning Systems (WM-EWS) have increasingly been promoted as tools for delivering climate information services and supporting drought-related decision-making. However, empirical understanding of how users perceive and engage with such systems in pastoral contexts remains limited. This study explores stakeholder perceptions regarding the usefulness and operational relevance of a WM-EWS implemented in the Borana zone of Ethiopia. A mixed-methods approach was employed, combining survey data from 71 purposively selected mixed stakeholders with qualitative insights obtained through focus group discussions and key informant interviews. Findings indicate that respondents widely reported using WM-EWS information for water-related decision-making and perceived the system as useful in supporting drought preparedness and adaptive responses. Participants associated WM-EWS use with perceived changes in areas such as livestock management, access to water-related information, and coordination among stakeholders. Respondents also reported adopting multiple coping strategies, including early livestock sales, strategic herd mobility, and engagement with external support mechanisms. Respondents perceived fewer conflicts over water resources and greater engagement from humanitarian actors following WM-EWS implementation. Overall, the study provides exploratory insights into stakeholder experiences, perceived usefulness, and operational relevance of user-centered WM-EWS in drought-prone pastoral systems. The findings contribute to understanding how pastoral communities engage with climate information services while highlighting the need for future research using objective and longitudinal approaches to assess system effectiveness more rigorously. Full article

Although climate change is increasingly recognized as a material risk for firms, the extent to which climate-related risks are operationally integrated into enterprise risk management (ERM) processes remains unclear. This article presents a structured literature review to answer the question of how firms have integrated climate risk assessment, considering both physical and transition risks, into ERM processes. Following the PRISMA 2020 protocol, 22 published articles from Web of Science and Scopus, published between 2018 and 2026, were included in the review. Articles covering financial institutions, as well as policy-only and sectoral-only studies, were excluded. The articles were screened through five eligibility criteria: firm-level focus, governance, risk assessment, climate risk management and/or ERM, and type of climate risk. All articles were assessed by two researchers to reduce bias, and Cohen’s kappa was calculated. Following coding and qualitative analysis, the findings indicate that firms have advanced governance structures, disclosure practices, and analytical assessment tools for climate risk assessment, while operational integration into ERM systems remains limited. Results also reveal persistent integration gaps, including strategic–operational disconnection, temporal and methodological mismatches, symbolic implementation, and systemic and knowledge barriers. These challenges constrain the effective translation of climate risk information into risk management practices and strategic planning. Overall, the study, based only on academic literature, concludes that climate risk integration is still incomplete and weakly embedded within ERM systems. In the expanding regulatory landscape, particularly with IFRS S2, the study provides a baseline for understanding current firm-level practices and future developments in climate risk integration at the academic level. Full article

The optoelectronic information industry is a strategic high-tech industry with wide applications. Compared with developed countries, China’s optoelectronic information industry presents a situation of “strong application and weak technology”. Evaluating the innovation capability of the optoelectronic information industry is the foundation for making scientific development plans. This study provides a methodology for evaluating the provincial innovation capability of the optoelectronic information industry to guide its high-quality development. This article applies multi-attribute utility theory to study the evaluation index system and comprehensive evaluation of the innovation capacity of China’s provincial optoelectronic information industry. Through extensive data collection and matching relationship analysis, an evaluation index system with both sequential decomposition and hierarchical interleaved structure was established, which includes four dimensions and 20 underlying indicators. To better reflect the gap in innovation capability across different provinces, a scientific piecewise non-zero nonlinear utility function model was established. According to the matching relationship between the subsystems and the underlying indicators of innovation capability, a weighted arithmetic mean comprehensive evaluation index model of innovation capability was developed. An empirical study of the optoelectronic information industry’s innovation capability in typical Chinese provinces was conducted using this comprehensive evaluation index model. The results show that Guangdong Province, Beijing Municipality, Jiangsu Province, Zhejiang Province, and Shandong Province ranked in the top five. The innovation capability of China’s optoelectronic information industry needs to be enhanced by strengthening the development of the investment mechanism, optimizing product development and promotion, improving the efficiency improvement mechanism, and solidifying the environmental support system. Full article

Renewable energy sources, such as solar thermal and photovoltaic, geothermal, biomass, hydropower, and wind, offer significant sustainability advantages. Yet the sector still faces difficulties in several areas that tend to reduce the efficiency of these new energy forms. Some of these challenges include inconsistent electricity supply, the diffuse nature of renewable energy sources, which makes them difficult to exploit, and the inconsistent and unpredictable nature of electricity supply, which has repercussions for renewable energy markets. Although Industry 4.0 is inherently energy-intensive, its positive contribution to renewable energy systems may outweigh its costs. Consequently, this study conducts a scoping review on the role of digital technologies in renewable energy systems. It focuses on open-access conference papers, journal articles, and book chapters published between 2020 and 2026, selected from scientific platforms and databases such as IEEE Xplore, ScienceDirect, SpringerLink, and Scopus. A multi-stage screening process and a summary sheet for a set of 89 selected articles were produced to extract the necessary information. The results show that Industry 4.0 influences renewable energy systems at the design and installation stage in predictive maintenance, efficient management, and energy security. Meanwhile, Industry 4.0 in renewable energy systems still faces negative externalities that can be categorised as political, financial, infrastructural, environmental, human, security, and technological. To address these challenges, which tend to become entangled in cycles of negative reinforcement, the paper suggests defining standardised, clear, strict, and stable frameworks at the political, legal, regulatory, and environmental levels to overcome most challenges associated with the digital transformation of renewable energy. The study also recommends flexible, inclusive strategic planning that accounts for the digital maturity of the renewable energy system. From these perspectives, the study contributes to the literature by addressing the role of Industry 4.0 technologies in renewable energy systems from a strategic and coordinated perspective, from both human and technological standpoints. It also offers managerial and policy implications by supporting innovation in renewable energy systems on the one hand and contributing to policy and regulatory decision-making that favour their growth on the other. Full article

Microgrids are increasingly recognized as transformative and crucial constituents within advanced smart grid systems. This study introduces a decentralized energy management approach for interconnected microgrids that leverage renewable energy sources such as wind and solar, alongside distributed energy generators and storage mechanisms. An energy coalition manager (ECM) plays a key role in facilitating each microgrid’s integration to optimize power exchanges, enhance data communication, and reduce costs. The alternate-direction multiplier method is adapted to address optimization challenges, incorporating modifications to develop a censored version that enhances communication efficacy. This refined approach involves the exchange of information among neighboring entities, evaluated against a preset threshold. Through this precise comparison, ECMs strategically reveal their local variables to ensure convergence towards an optimal solution. A detailed case study was conducted to assess the performance, efficiency, and scalability of both methodologies comprehensively. Full article

Background/Objectives: Accurate estimation of healthcare service requirements is essential for planning oncological care pathways, particularly in resource-constrained settings. We developed a combined methodological framework integrating pragmatic rapid literature reviews and population-based cohort analyses to estimate expected and observed utilization of diagnostic imaging and radiotherapy services along the prostate cancer care pathway in the Lazio Region (central Italy). Methods: Observed utilization was assessed using incident prostate cases recorded in the Lazio Region Cancer Registry in 2019 (n = 3047) and provisional cases in 2022 (n = 3254), through linkage with regional health information systems. For each cohort, 16 indicators (magnetic resonance imaging, biopsy, metastatic staging imaging, radiotherapy) were calculated, estimating usage proportions, median delivery times, and stratifying by age class. The expected requirement was estimated through four rapid literature reviews of the Italian literature and applied to incident prostate cancer cases. Results: Sixteen indicators covering diagnostic, staging, and therapeutic services were analyzed. Observed utilization varied across the prostate cancer care pathway, including diagnostic imaging, biopsy, surgery, and radiotherapy. For example, radiotherapy was expected in approximately 33–42% of patients, whereas the observed utilization was 23.00% of cases (95% CI 21.48–24.61) in 2019 and 22.52% of cases (95% CI 21.07–24.03) in 2022. The provision of imaging for metastatic staging—40.85% (95% CI 39.06–42.67) in 2019 and 34.84% (95% CI 33.19–36.53) in 2022—was lower than the expected value of 50%. Differences in utilization patterns by age group and timing of service delivery were observed. Literature-informed expected estimates exceeded observed utilization for several services, including both diagnostic and therapeutic components of the pathway. Conclusions: Overall, variations were identified between observed utilization and literature-informed expected estimates, suggesting the utility of evaluating potential areas for healthcare pathway optimization. This reproducible and adaptable methodology can be applied to other care pathways and healthcare settings, thereby supporting strategic resource allocation and continuous monitoring. Full article

Feeding and Eating Disorders (FED) require integrated, recovery-oriented care models that extend beyond clinical treatment and incorporate supportive environments capable of enhancing psychosocial well-being. Within this perspective, nature-based and socio-agricultural practices represent promising yet underexplored therapeutic resources, particularly when integrated into spatial planning frameworks. This study develops and tests a Geographic Information Systems (GIS)-based Decision Support System (DSS) that matches the specific therapeutic needs of individuals undergoing treatment for FED with the spatial distribution and characteristics of green and agricultural environments. The research is based on a case study involving the FED care center “Il Pellicano” in Perugia, Italy. Supply-side data were collected from 65 facilities, including 58 social farms, 6 community gardens, and the center’s private garden. Demand-side data were obtained through a questionnaire administered to patients by healthcare professionals, while supply-side attributes were collected through structured interviews with facility managers. The spatial matching process was implemented in a GIS environment using a non-compensatory multi-criteria approach that integrated thematic activities, spatial and/or organizational accessibility, confidentiality, spatial capacity, and environmental settings. The results reveal a substantial mismatch between demand and supply, with the current territorial system satisfying only 37.67% of expressed therapeutic needs. Sensitivity analysis indicates that the main constraints relate to the limited availability of medium-sized, low-attendance, and freely accessible environments. Beyond the local case study, the proposed DSS provides a transferable planning-support tool for designing personalized therapeutic pathways and strengthening the integration between green infrastructure, social farming, and healthcare systems. The study highlights the strategic role of spatial planning in promoting health equity, social inclusion, and community well-being. Full article

As lithium-ion batteries are widely deployed, thermal runaway (TR) poses severe safety risks, making early and accurate warning systems critical. While machine learning (ML) has advanced data-driven TR prediction, challenges remain regarding model interpretability, generalization under unseen conditions, and real-time deployment. This review evaluates recent progress in ML-driven TR warning technologies, moving beyond a mere compilation of algorithms to provide an organized synthesis of the field. As a key contribution, we critically analyze the paradigm shift toward physics-informed ML, demonstrating how embedding electrochemical and thermodynamic principles into neural networks reduces prediction errors by 40–60% while enhancing robustness. Furthermore, we synthesize a Battery Digital Twin (BDT) framework integrating Internet of Things (IoT), cloud computing, and on-board master BMS for closed-loop collaboration, effectively balancing low-latency control with high-precision health assessment. Finally, we outline strategic pathways for future breakthroughs: advancing physics-informed cross-scale modeling, optimizing cloud-edge architectures, and establishing open access benchmark databases. By calling for standardized evaluation protocols to break down data silos, this review provides a comprehensive roadmap and actionable insights to accelerate the industrial implementation of next-generation intelligent battery safety management. Full article

Underground space is increasingly positioned in contemporary urban discourse as a strategic resource for sustainable spatial and territorial development, particularly under conditions of limited surface capacity, growing infrastructural demand, and the need for long-term urban resilience. However, its implementation remains constrained by insufficient institutional, planning, and governance integration. Starting from this problem, this paper assesses the institutional readiness of Serbia’s spatial and urban planning system for the integration of underground planning into the territorial development system. The methodological approach is based on the development of an analytical framework for institutional readiness, structured around three key dimensions: regulatory–institutional, spatial–infrastructural, and governance–coordination. This research is conducted through a qualitative analysis of legislative, strategic, planning, and supplementary sources, using stratified criteria—normative, operational, and integrative levels—which enables a structured, document-based diagnostic assessment of the current state of the system. The results indicate that institutional readiness in Serbia is at a low to medium-low level. Although a partially developed normative framework and certain technical-informational capacities exist, underground space is not clearly recognised as a distinct planning category or as an integrated three-dimensional spatial resource. The spatial–infrastructural dimension reveals the existence of relevant cadastral, geospatial, and infrastructural foundations, but without their sufficient integration into a unified 3D planning and governance system. The key limitation is identified in the governance–coordination dimension, where fragmented competences, uneven local capacities, and the absence of dedicated coordination mechanisms hinder the systematic application of underground planning. The paper concludes that the integration of underground planning in Serbia requires gradual institutional transformation toward an integrated, three-dimensional, and long-term-oriented model of spatial governance. Its contribution lies in formulating an initial diagnostic framework that connects debates on planning systems, institutional fragmentation, spatial data integration, and territorial governance, and may serve as a basis for further research and policy development in the field of integrated territorial development. Full article

This study systematically explores the underlying mechanisms of collaborative innovation driving the green transformation of traditional energy enterprises. Existing research primarily focuses on enterprise scale and overall competitiveness, rarely delving into these specific collaborative pathways. Furthermore, studies employing evolutionary game theory to analyze the tripartite relationship among the government, traditional energy, and emerging technology enterprises remain fragmented, failing to fully capture the dynamic mechanisms of multi-stakeholder strategic choices. To bridge these gaps, this paper constructs a tripartite evolutionary game model incorporating coordination costs and the benefit distribution ratio to explore their influence mechanisms. Replicator dynamics equations are employed to identify stable cooperation conditions, overcoming traditional two-party framework constraints. Additionally, MATLAB R2024b numerical simulations validate the theoretical findings. The results reveal two evolutionarily stable equilibrium points. First, higher initial willingness among participants accelerates the system’s evolution toward a stable cooperative state. Second, coordination costs induced by information asymmetry act as a core bottleneck that deters participation and risks collaborative collapse. Third, targeted government incentives and a rational benefit distribution ratio directly determine cooperation willingness; notably, enterprises adopt collaborative strategies only when this ratio falls between 0.27 and 0.69. Fourth, fair and transparent supervision is crucial for mitigating trust deficits and distribution disputes. Ultimately, scientifically designing incentives, optimizing benefit structures, promoting information sharing, and establishing robust supervision effectively facilitate a sustainable tripartite collaborative innovation pattern. Full article

This study examines the relationship between environmental performance, digital integration, information asymmetry, and default risk among European firms. It seeks to understand how sustainability and digitalization jointly enhance corporate financial stability. The sample comprises 1303 non-financial firms from 20 European countries over the period 2016–2023. This study uses a Thomson Reuters sample composed of European publicly listed companies with ESG (environmental, social, and governance) ratings. Europe represents an ideal setting for this analysis due to its dual green and digital transition, supported by some of the most advanced regulatory policies in the world. Methodologically, the analysis employs a dynamic panel model estimated using the two-step system GMM approach, complemented by a robustness check based on 2SLS-IV estimation to address potential endogeneity concerns. The empirical findings reveal that both environmental performance and digital integration significantly reduce default risk whereas information asymmetry increases it. Moreover, sustainability and digital transformation attenuate the adverse effect of information asymmetry on financial stability, confirming their complementary role as resilience-enhancing mechanisms. These results underscore the critical importance of transparency, innovation, and organizational capabilities in mitigating financial risk. Overall, the study makes an original contribution to the literature on sustainable governance by demonstrating that environmental performance and digital integration are not merely regulatory requirements but constitute strategic intangible assets that strengthen financial soundness and reduce default risk within the European context. Full article

Goat production in Peru is primarily carried out under extensive systems shaped by climatic variability, forage seasonality, infrastructure limitations, and persistent sanitary pressure. In this context, Creole goats represent a strategic animal genetic resource due to their capacity to adapt to arid and high-Andean environments. This review integrates the available evidence on production typologies in the main goat-producing regions of the country, the major sanitary and structural bottlenecks, and the state of the art of genomic, multi-omics, and reproductive biotechnology tools applicable to goats. It discusses how the transition from traditional markers to SNP genotyping, together with functional approaches such as microbiome analysis, transcriptomics, and proteomics, can contribute to understanding the biological basis of complex traits related to resilience, feed efficiency, and reproductive performance. Likewise, the potential of precision livestock farming to generate longitudinal phenotypes and strengthen genetic improvement programs in low-input systems is highlighted. Finally, priorities and considerations are outlined to advance the integration of phenotyping, genomics, and reproductive biotechnologies in extensive contexts, with emphasis on the generation of systematic data, interinstitutional coordination, and technology transfer aimed at the sustainability and conservation of goat resources. These insights may also inform genetic improvement strategies in other developing countries facing similar environmental and structural constraints in low-input goat production systems, particularly in arid and semi-arid regions. Full article

Grounded in the MAIN model and multidimensional information-quality frameworks, this research conceptualizes news evaluation through three distinct lenses: credibility, newsworthiness, and readability. Through a 2 (authorship: AI vs. human) × 3 (news domain: finance, weather, sports) mixed experiment (N = 301), participants evaluated identical articles attributed to either an AI system or a human journalist. The results reveal a consistent “credibility penalty” for AI-labeled news across all domains, suggesting that authorship serves as a domain-general source heuristic. However, the effects on newsworthiness and readability were domain-contingent, shifting based on genre-specific expectations and the informational stakes of the topic. These findings demonstrate that audience responses to AI journalism are multidimensional and context-sensitive rather than uniform. This study offers significant implications for communication theory, transparency in disclosure practices, and the strategic adoption of AI in modern newsrooms. Full article

Hydropower-dominated electricity systems are increasingly exposed to hydroclimatic variability, making anticipatory streamflow information essential for energy security, operational resilience, and sustainable planning. This study develops a transparent monthly early-warning framework for the Paute River basin, Ecuador, a strategically important hydrological system for national hydropower generation. Using a 42-year series of observed and compiled monthly streamflow records from 1984 to 2025 (n = 504), the framework derives seasonal low-flow thresholds (P20 warning and P10 critical) and fits a Seasonal Autoregressive Integrated Moving Average model to log-transformed flows. The resulting lognormal predictive distribution provides point forecasts, prediction intervals, and probabilities of low-flow events. Predictive skill was assessed through a 2016–2025 rolling-origin validation with 120 one-step-ahead forecasts and benchmarks against Error–Trend–Seasonal Holt–Winters and seasonal naive models. The SARIMA-log specification achieved the best point accuracy (MAE = 38.80 m³/s, RMSE = 47.62 m³/s, sMAPE = 32.63%) and modest but useful probabilistic skill (CRPSS = 0.069; Brier Skill Score = 0.169 for Q < P20 and 0.274 for Q < P10). A threshold-sensitivity analysis showed that the 0.15 and 0.30 alert thresholds represent a deliberate trade-off between early detection and false-alarm reduction. For 2026, August displayed the highest low-flow probability (P(Q < P20) = 0.303), triggering a moderate Hydropower Low-Flow Risk Traffic-Light category. The contribution is not a new forecasting algorithm but an operationally auditable integration of seasonal thresholds, probabilistic forecasting, verification, and risk communication for hydropower energy-security governance in the tropical Andes. Full article