Search Results (299)

Public Fire Emergency Literacy (PFEL) is a critical determinant that fundamentally shapes individual survivability and the efficacy of societal safety governance—particularly amid intensifying fire risks characterized by growing complexity and destructive potential. Traditional single-perspective or linear analytical frameworks fail to capture PFEL’s multi-causal and configurational nature. To address this gap, this study integrates the Emergency Management Life Cycle Theory with the WSR system approach to measure PFEL across 36 major Chinese cities using 3872 survey responses and explores its multidimensional attributes and generative mechanisms via multiple methods (Delphi technique, entropy weighting, GIS spatial analysis, multiple regression, fsQCA). Key findings: (1) PFEL exhibits a pronounced cognition precedes capability gap with marked demographic heterogeneity; (2) PFEL displays a distinct “Central > Northeast > East > West” hierarchical gradient and notable spatial disequilibrium—core cities in the Central region (e.g., Wuhan and Zhengzhou) outperform traditional first-tier metropolises in the East; (3) physical infrastructure, organizational management, and individual cognition jointly shape PFEL with significant regional heterogeneity—participation in emergency training emerges as the most potent driver; (4) configurational path analysis indicates that PFEL is determined by a complex conjunctive causal mechanism formed by the combined effects of physical facilities, organizational management and individual initiative. Policy implications cover strengthened public emergency response capacity, differentiated policies, and multi-factor collaborative governance. The findings offer theoretical references and practical guidance for improving public resilience systems and emergency resource allocation. Full article

Integrated watershed sustainability assessments are still incipient in Ecuador, where scarce and heterogeneous data are limiting factors. This study introduces the Watershed Sustainability Index (WSI) to the Chibunga Basin in Chimborazo, Ecuador, marking its first application in this region. A key aspect of this study is the development of a clear and reproducible method for applying the index, particularly in inter-Andean basins where data are limited. The four dimensions—Hydrology, Environment, Life, and Policy—were assessed through the Pressure–State–Response (PSR) framework by combining secondary statistics, field sampling, GIS land-use analysis, and a two-round Delphi consultation with ten experts to operationalize the institutional (Policy) component. The basin scored 0.38 (low sustainability), with a critical Hydrology dimension (0.08), poor Policy dimension (0.33), moderate–low Life dimension (0.42), and moderate Environment dimension (0.67). The central finding goes beyond these scores: the operationalized PSR framework pinpointed where the management cycle breaks down in practice. Systematically null response scores reveal that unsustainability stems from the failure to translate an existing regulatory framework into formal institutional action, rather than from regulatory absence or physical water scarcity alone, further constrained by unfavorable socioeconomic conditions. The procedure turns the WSI from a scoring tool into a diagnostic one, providing a replicable reference for data-scarce Andean basins. Full article

National and international frameworks provide strategic direction for antimicrobial stewardship (AMS), while their translation into operational practice remains inconsistent. Building on ARCO Step I findings, this study aimed to establish an interregional, multidisciplinary consensus on sustainable AMS implementation strategies across hospital and community settings in Northeastern Italy. A modified Delphi methodology engaged 33 interdisciplinary professionals from Northeastern Italy. Eighteen operational statements across three domains (Governance, Hospital AMS, Community AMS) underwent two quantitative scoring rounds (relevance and feasibility; 1–10 scale) separated by a structured in-person workshop with thematic round-table discussions. Consensus threshold was defined as median score ≥ 8.0; high-priority statements required combined score ≥ 8.5. All 18 statements achieved consensus for relevance, whereas 12 statements achieved consensus for feasibility. Post-discussion median scores feasibility showed a numerically larger increase for feasibility (Δ +0.78) compared to relevance (Δ +0.44), indicating that structured deliberation reduced perceived implementation barriers. Furthermore, 14 statements were classified as high-priority. Qualitative analysis identified key enablers (CEO performance mandates, multidisciplinary teams, standardized indicators) and barriers (digital infrastructure gaps, resource constraints). The participatory approach helped translate strategic policy into a set of practice-oriented recommendations, offering a potentially transferable model for regional health authorities implementing AMR action plans, pending evaluation of actual implementation. Full article

Green smart city development increasingly depends on cooperation between public authorities and enterprises, yet existing research has not adequately explained how government-side enabling conditions and enterprise-side capabilities are structurally connected. This study identifies the key factors affecting green smart city development from the perspective of government–enterprise cooperation and examines their causal relationships, hierarchical structure, driving power, and dependence. A systematic literature review and Delphi consultation with ten experts from government agencies, enterprises, and universities in China were used to establish a framework of ten factors. The enterprise factors include technologies, innovation, responsibilities, management, and talents, while the government factors include databases, platforms, infrastructure, funds, and policy system. An integrated DEMATEL-ISM-MICMAC approach was then applied to analyze the relationships among these factors. The results show that policy system and funds are the fundamental driving factors, infrastructure and talents serve as key transmission factors, and technologies and innovation are highly connected but mainly dependent on upstream conditions. Responsibilities show relatively weak structural connectivity and become more influential when embedded in formal institutional and managerial mechanisms. This study develops a unified analytical framework that links government enabling conditions with enterprise implementation capabilities, clarifies the internal structure of green smart city development, and provides practical guidance for improving policy coordination, financial support, digital foundations, and enterprise capacity in China and other comparable contexts. Full article

Background/Objective: Perioperative nursing care encompasses a diverse patient population with varying needs, anatomical and physiological characteristics, and differing levels of vulnerability, demanding specialized knowledge and skills. This study aims to identify key research priorities in perioperative nursing across the lifespan. Methods: A two-round e-Delphi study was conducted across three Portuguese hospitals, involving expert perioperative nurses (87 in the first round and 69 in the second). Participants rated the importance of various research topics on a 5-point Likert scale about six dimensions: (1) professional development and non-technical skills, (2) person-centered care, (3) organizational aspects and work environment, (4) patient and team safety, (5) digital innovation, and (6) patient outcomes and quality of care. Data were analyzed using mean scores, Content Validity Ratio (CVR) for initial validation, and the Coefficient of Variation (CV) to determine the level of consensus. The reporting of this study followed the DELPHISTAR (Guideline for Reporting Delphi Studies) recommendations. Results: A high degree of consensus was achieved (all CV < 0.20). The experts established a consensus on 48 components. The highest-rated priority was nurse burnout and professional satisfaction (Mean = 4.74). This was closely followed by patient safety (Mean = 4.68), team safety (Mean = 4.65), disaster response (Mean = 4.62), and emergency management (Mean = 4.58). Acute pain control and interdisciplinary communication also emerged as critical areas. Topics such as digital innovation and artificial intelligence, while valued, received lower priority scores. Conclusions: The identified priorities should direct funding toward research, education, quality improvement, and health policies. Future studies should focus on developing interventions to promote a favorable perioperative environment and optimize clinical responses to individuals’ conditions, catastrophes, and life-threatening situations across the lifespan. Full article

Forest-based cultural heritage landscapes associated with traditional potash, tar, resin, and charcoal (PoTaRCh) production constitute valuable socio-ecological systems with considerable potential for sustainable tourism and rural development. However, little is known about how these destinations may evolve under future environmental, social, and governance uncertainties. The objective of this study was to identify the key drivers and critical uncertainties shaping the future development of PoTaRCh-based tourism systems in Europe by 2040 and to develop alternative scenarios to support strategic planning and adaptive governance. The research adopted the Intuitive Logics approach to scenario planning and the Scenario-Based Strategic Planning framework, combining a two-round Delphi study with 42 experts from 15 European countries and qualitative scenario development. Four key drivers were identified: forest ecosystem integrity, destination governance, community participation, and visitor experience and tourism demand. Their interaction resulted in five internally consistent scenarios: Forest Harmony, Guardians’ Forest, Tourist Forest, Forgotten Forest, and Regenerating Forest. The findings demonstrate that the resilience of PoTaRCh-based tourism systems depends on the dynamic interaction between ecological conditions, governance capacity, local stewardship, and tourism demand rather than on any single driver. To facilitate the practical application of the scenarios, the study also proposes a Scenario Monitoring Framework and Scenario Cockpit that translate qualitative scenario narratives into monitoring indicators for early detection of emerging development pathways. The study advances tourism futures research by providing one of the first comprehensive foresight analyses of forest-based cultural heritage tourism systems and offers practical guidance for destination managers and policy-makers seeking to strengthen the long-term sustainability and resilience of heritage landscapes. Full article

Sustainable public procurement (SPP) has emerged as a crucial strategy for advancing environmental management and socioeconomic development. Life Cycle Cost (LCC) is widely regarded as a quantitative measure of long-term economic viability. However, integrating LCC analysis into SPP remains a major challenge. This study addresses this gap by identifying and selecting LCC indicators that align with sustainable procurement. This study develops new indicators for LCC assessment through a mixed-methods approach that combines a systematic literature review, an institutional policy review, and expert stakeholder consensus via a fuzzy Delphi method. A panel of 12 experts evaluated the indicators, and of the 173 potential items generated from the literature review, consensus was reached on 88 indicators, with an average threshold value (d) = 0.182. The findings establish a systematic framework that highlights the cost indicators most critical for guiding public procurement decisions. The findings also suggest indicators that are priorities for LCC in sustainable public procurement. Selecting appropriate LCC indicators in the SPP will help the government achieve several Sustainable Development Goals (SDGs) targets. Full article

The rapid integration of artificial intelligence (AI) tools into academic research and writing has introduced new challenges related to transparency, accountability, and reproducibility. While publishers increasingly permit AI use with disclosure, there is currently no standardized reporting framework guiding how such use should be documented. This study introduces PETMALU-AI (Principles for Ensuring Transparency in Machine-assisted Authorship, Logging, and Use of Artificial Intelligence), a reporting checklist designed to support more consistent disclosure and documentation of AI-assisted research practices. The development of PETMALU-AI followed a multi-phase design framework, including (1) a narrative synthesis of existing AI policies and reporting guidelines, (2) item generation grounded in methodological transparency principles, and (3) modified Delphi-based expert validation involving an interdisciplinary panel. The Delphi process produced a 33-item checklist organized across nine domains: disclosure, human accountability, system transparency, prompting and interaction processes, data provenance, validation, ethics, limitations, and reproducibility. All retained items achieved expert consensus, with item-level content validity indices ranging from 0.85 to 1.00 and final agreement rates ranging from 85% to 100%. Reliability analyses further supported the stability of expert judgments, with Fleiss’ kappa and the intraclass correlation coefficient indicating strong agreement and high consistency. The checklist emphasizes proportional reporting, human accountability, and transparent documentation of AI-assisted research practices. PETMALU-AI offers a framework for documenting AI involvement in ways that are visible, assessable, and accountable, providing a foundation for more transparent research reporting as scholarly writing becomes increasingly shaped by human–AI collaboration. Full article

This study investigates the key drivers and barriers influencing the adoption of electric vehicles (EVs) in urban freight logistics, using Lithuania as a case study. An integrated methodological framework combining Delphi, Fuzzy logic, DEMATEL, and System Dynamics is applied to identify critical factors and analyse their interdependencies. Four main drivers are identified: infrastructure, acquisition costs, technological development, and policy measures. Expert evaluations are transformed into fuzzy values to quantify factor importance, which are then incorporated into a dynamic simulation model to assess EV adoption and CO₂ emission trends. In addition to baseline scenarios, extreme scenario analysis is conducted to evaluate system sensitivity to economic, technological, and policy changes. The results reveal strong nonlinear relationships between factors and highlight the importance of their balanced development. The findings suggest that rapid EV adoption in urban logistics requires a coordinated approach integrating infrastructure expansion, financial incentives, technological progress, and policy support. The study provides practical insights for policymakers and logistics companies aiming to accelerate sustainable urban transport transitions. Full article

Rubble management in Aleppo is a complex recovery planning problem because debris removal is closely linked to transport access, recycling capacity, reconstruction demand, disposal limits, and local acceptance. This study develops a multi-objective reverse-logistics model for managing post-conflict rubble in the city. The proposed network consists of 21 rubble source nodes, 5 collection and sorting sites, 4 recycling facilities, 5 reconstruction-demand nodes, and 2 disposal sites. The model is formulated as a weighted non-preemptive goal programming problem that considers four objectives: total cost, carbon emissions, dust/social acceptance penalty, and operational implementation risk. Because the last two objectives are strongly context-dependent, they were developed through a Delphi process with 13 experts, and the related subcriteria were weighted using fuzzy FUCOM. Four compromise formulations were tested: weighted goal programming (WGP), augmented max–min fuzzy goal programming (AMM-FGP), weighted additive fuzzy goal programming (WA-FGP), and Max–Min optimization. The resulting solutions were ranked using MARCOS and validated using CRADIS. WGP ranked first, with a MARCOS utility score of 0.697919, followed by Max–Min at 0.654658, AMM-FGP at 0.633123, and WA-FGP at 0.629647. The policy analysis also showed that a 30% recycling subsidy produced the largest improvement, reducing the WGP achievement value from 0.192 to 0.046. These results suggest that, for Aleppo, a rubble-management plan cannot be judged only by cost or emissions. Social nuisance, site operability, and policy support also affect whether a technically efficient network can be implemented in practice. Full article

The urban landscape is a constant presence in the daily lives of urban residents, and its quality is closely linked to their overall quality of life. Therefore, it is essential to provide municipalities with effective tools to assess urban landscape quality. The identification of evaluation criteria, validated by an expert panel, contributes to the development of urban landscape assessment policies and supports the construction of a multi-criteria evaluation model. This study acknowledges the multidimensional nature of the urban landscape and is grounded in the definition of “landscape” established by the European Landscape Convention. It proposes a methodology for assessing urban landscape quality through the identification of evaluation criteria using the Delphi method, based on a panel of 24 experts. The process resulted in the identification of five key criteria: Human Dimension, Functional Diversity, Natural Elements, Identity, and Maintenance. Full article

Existing Cyber Resilience Assessment Guidelines, including those of the Bank of Korea (BoK), focus on governance-oriented compliance and lack quantitative criteria for measuring the operational effectiveness of security technologies—a Policy–Technology Gap also common in general enterprise settings. To address this gap, this study proposes D3-CREF, a technology-centric cyber resilience evaluation framework that maps the MITRE D3FEND taxonomy to financial security domains and introduces a Normalized Resilience Index (NRI) aggregating four dimensions—Coverage, Maturity, Automation, and Timeliness—via a closed-form weighted geometric mean with AHP-elicited weights (consistency ratio CR = 0.04). All NRI indicators are anchored to MITRE ATT&CK techniques and exemplar CVE entries, enabling threat-informed measurement. The framework was validated through a three-round Delphi study with 50 experts (Kendall’s W = 0.78, p < 0.001; Cronbach’s α = 0.89; CVR 0.68–0.92) and a Cyber Range-based simulation. For three institutions with identical BoK scores (92/100), NRI yielded discriminative values of 0.83, 0.44, and 0.09 (CV = 0.68 vs. 0.00 for the baseline), confirming a shift from compliance-based to performance-driven assessment. Full article

Background/Objectives: Precision medicine has moved into routine practice, but its evaluation through Health Technology Assessment (HTA) remains ethically underdeveloped. Existing instruments do not address the distinctive ethical demands of genomic profiling, AI-based clinical decision-support, and the equitable distribution of benefits from high-cost targeted therapies. Methods: A modified two-round Delphi study was conducted with a multidisciplinary panel of 18 Greek experts in bioethics, HTA, genomic medicine, nursing, and health policy. In Round 1, 32 candidate ethical statements across seven thematic domains were rated on a three-point scale; retention required a Content Validity Ratio (CVR) ≥ 0.42 and ≥80% agreement. Retained statements were re-evaluated in Round 2 with consensus defined as median ≥ 2.0 and ≥80% agreement. Reporting follows ACCORD guidelines. Results: Fifteen of 32 statements satisfied retention criteria. In Round 2, all 15 achieved consensus with a median of 3.0 and agreement of 94.4–100% (interquartile range, IQR = 0.00). Five domains constituted the final framework: fundamental ethical principles; transparency, stakeholder participation, and institutional accountability; equity and access; digital health and artificial intelligence (AI); and pandemic preparedness and system resilience. Domains addressing environmental sustainability and social acceptability did not meet the threshold. Conclusions: This study presents, to our knowledge, one of the first empirically grounded ethical frameworks for precision medicine HTA developed within an EU Member State through a formal Delphi process. The framework is operationalised through a ready-to-use ethics checklist designed for direct integration into national HTA submission and appraisal processes. Conducted in Greece—a late-aligning EU Member State—the study provides a transferable methodological template for comparable health systems across Europe. Full article

Objective: The professional competence level of pre-service childcare teachers influences the quality of future childcare services. However, due to the lack of necessary assessment tools, this study aims to develop a professional competence scale for pre-service childcare teachers in China. Methods: First, the qualitative data, including domestic and international policy texts, field interviews, and existing research findings, were subjected to three-level coding using Nvivo14 software to construct the dimensions of the perceived professional competence scale for pre-service childcare teachers in China and a preliminarily draft the items. Second, the expert consultation method was employed to test content validity. Two rounds of consultations were conducted with 22 experts using A Delphi 12.0 software to refine the item content. Finally, item analysis, exploratory factor analysis, reliability testing, and convergent validity testing were performed on data from 558 pre-service childcare teachers using SPSS 27.0 software, while confirmatory factor analysis was conducted on data from 534 pre-service childcare teachers using Mplus 8.0 software. Results: The perceived professional competency scale for pre-service childcare teachers in China comprises four dimensions—competence of practice teachers’ morality, responsive caregiving competence, early development support competence, and health management competence—with a total of 48 items. Content validity testing indicated that the scale items are comprehensive, clearly worded, and expressed in accessible language, effectively covering the professional competency requirements of pre-service childcare teachers. Confirmatory factor analysis (CFA) demonstrated good model fit for the scale. The average variance extracted (AVE) for each factor exceeded 0.500, composite reliability (CR) exceeded 0.700, and factor loadings ranged between 0.750 and 0.917. The scale achieved Cronbach’s α of 0.988, and all split-half reliability coefficients were above 0.700, meeting established psychometric standards. Conclusion: The perceived professional competency scale for pre-service childcare teachers in China demonstrates stable psychometric properties and is suitable for use as a measurement tool for assessing the professional competence of pre-service childcare teachers. Full article

Digital literacy (DL) is a cornerstone of sustainable digital transformation in education, yet its systemic cultivation among pre-service teachers in resource-constrained regions remains critically under-theorized. This study develops and validates a contextualized DL measurement framework grounded in the “triple identity” of pre-service teachers as citizens, learners, and future educators. Employing a multiphase mixed-methods design, this systemic framework was refined via Delphi consultation and rigorously validated through exploratory (n = 287) and confirmatory factor analyses (n = 1462) across 24 universities in Southwest China. The newly validated framework, comprising five core dimensions and 41 specific indicators, demonstrates robust psychometric properties and systemic structural validity. Findings reveal a moderately high overall DL (M = 3.44) but highlight a significant “skills-awareness” gap, where operational proficiency exceeds conceptual cognition, particularly in comparison with findings reported in other Chinese regions. Hierarchical regression indicated that structural variables added substantial explanatory power beyond individual demographic characteristics, with institution type emerging as the strongest predictor and urban-rural background making an additional significant contribution. These results underscore the paradox between DL’s inherent malleability and the rigid constraints of structural inequality. The study offers a validated measurement tool and an evidence-informed roadmap for policy interventions aimed at bridging the digital divide in underdeveloped teacher education systems, advocating for a shift from technical training toward systemic equity. Full article