Search Results (597)

Background: Despite advances in monitoring and forecasting systems, natural disasters continue to cause significant human losses. During the response phase, fast decisions are required to allocate limited resources, particularly rescue helicopters, which play a key role in reaching inaccessible areas. However, helicopter allocation involves trade-offs between efficiency and operational safety under uncertain conditions. Methods: This study proposes a decision-support methodology based on Multi-Criteria Decision Analysis (MCDA) for allocating rescue helicopters during disaster response. The approach integrates Value-Focused Thinking (VFT) and Multi-Attribute Value Theory (MAVT) to structure objectives, assign weights, and evaluate alternatives using criteria related to mission safety, response time, and expected number of rescued victims. The method is illustrated through a simulated flood response scenario in a Brazilian regional context. Results: The results show that the model allows decision-makers to compare allocation scenarios and to make explicit the trade-offs between operational efficiency and safety. The application indicates that small reductions in efficiency may lead to relevant gains in operational safety, particularly under adverse weather conditions. Conclusions: The proposed approach provides a transparent and traceable structure for supporting helicopter allocation decisions during disaster response. It contributes to more consistent decision-making in critical operations, especially in contexts characterized by uncertainty and time pressure. Full article

The Tourism Area Life Cycle shaped tourism research for decades, but its concepts Product Life Cycle and Carrying Capacity remain problematic. We apply a Path Dependence frame under an Urban Growth Machine Theory lens to explore the effects of growth pressure and resource undersupply on the decline and rejuvenation of Japan’s former premier hot spring resort Atami. We conduct structured data collection utilizing sampling and coding methods to collect quantitative and qualitative data from primary and secondary sources, reconstructing Atami’s development paths. Findings suggest that growth pressure conflicted with local supply such as land, water, labor and created negative externalities, most notably high prices. Decision makers’ uncompromising focus on growth aggravated displacement of key actors, disrupting local communities and undermining the human agency needed for small-scale product innovation; empowered associations obstructing promotion and diversification efforts; encouraged extreme specialization depriving Atami of new independent businesses; and drove local opposition to major new projects, thereby stalling product renewal. The framework helped recontextualize Atami’s recovery and demonstrated the value of directly incorporating factors of capacity into analysis. Results link displacement to long-term sustainability risks affecting ‘replaceable’ resorts reliant on innovation. Unencumbered access to local resources for residents (housing, training) is proposed as mitigation. Full article

This study examines Lean 4.0, defined as the integration of Lean soft practices (LSPs) and Industry 4.0 technologies (I4Ts), from a socio-technical systems perspective. While prior research has mainly linked Lean and I4Ts to operational and cost-based performance indicators, far less is known about how their human and technological elements interact as one socio-technical system during digital transformation. We investigate how LSPs and I4Ts combine to form social and technical subsystems, how their interaction reshapes work systems, and how these configurations relate to organisational performance. An inductive qualitative design was used. Fifteen managers and professionals with direct experience in continuous improvement and digital transformation completed an open-ended online questionnaire. Data were analysed using Braun and Clarke thematic analysis, guided by socio-technical systems theory and complemented by a cross-case synthesis. The findings identify four interrelated subsystems, social, technical, work, and outcomes, that co-evolve in Lean 4.0 initiatives. LSPs such as training, empowerment, and stakeholder involvement constitute a social system that enables the adoption and effective use of I4Ts in the technical system. When both subsystems are strong, their combined operation drives more extensive digital transformation of operational processes and customer facing activities, and in some cases business models, and is associated with broader improvements in efficiency, quality, customer satisfaction, employee engagement, and financial performance than medium or unbalanced configurations. The analysis also highlights recurrent integration challenges, including skill gaps, legacy system constraints, resistance to change, and data security concerns. Overall, the study conceptualises Lean 4.0 as an integrated socio-technical configuration and extends socio-technical systems theory by showing how LSPs mediate and amplify the value created by I4Ts, providing an empirically grounded framework and configuration-based insights for future testing. Full article

Under the context of non-dyadic human–machine interaction in intelligent coal mines, this study investigates the impact of different dyadic collaboration modes on Team Situation Awareness (TSA). Based on a simulated coal mine monitoring task, the experiment compares four working modes—Individual Operation, Supervised Operation, Cooperative Operation, and Divided-task Operation—across tasks of varying complexity. TSA was assessed using both objective (SAGAT) and subjective (SART) measures, alongside parallel evaluations of task performance and workload (NASA-TLX). The results demonstrate that, compared to Individual or Supervised Operation, both Cooperative and Divided-task Operation significantly enhance TSA and task performance. Cooperative Operation improves information integration and comprehension, while Divided-task Operation enhances response efficiency by enabling focused attention on role-specific demands. Moreover, dyadic collaboration reduces cognitive workload, with the task-sharing mode showing the lowest cognitive and temporal demands. The findings indicate that clear task structuring and real-time information exchange can alleviate cognitive bottlenecks and promote accurate environmental perception. Theoretically, this study extends the application of non-dyadic interaction theory to intelligent coal mine scenarios and empirically validates a “Collaboration Mode–TSA–Performance” model. Practically, it provides design implications for adaptive collaboration frameworks in high-risk, high-complexity industrial systems, highlighting the value of dynamic role allocation in optimizing cognitive resource utilization and enhancing operational safety. Full article

Insects constitute a vital component of terrestrial ecosystems, yet their ongoing global decline underscores the urgency of identifying the factors that facilitate or hinder public engagement in their conservation. This study identifies the key psychological drivers of insect-related conservation behavior within a Romanian context, an understudied geographical and sociocultural setting. Using data collected from 346 adult respondents via an online questionnaire, the predictive performance of the Value–Belief–Norm (VBN) theory, the Theory of Planned Behavior (TPB), and an integrated VBN–TPB framework was examined through Partial Least Squares Structural Equation Modeling (PLS-SEM). The VBN model exhibited superior explanatory power relative to TPB, with biospheric values, ecological worldviews, and personal moral norms emerging as the most influential determinants of behavioral intention and self-reported action. Although participants demonstrated moderate levels of general entomological knowledge, awareness of specific insect-friendly practices was notably limited and frequently characterized by misconceptions. Perceived barriers, particularly informational deficits, time constraints, and financial considerations, exerted significant inhibitory effects on conservation engagement. The findings indicate that effective interventions must extend beyond knowledge transmission, incorporating strategies that activate moral norms, strengthen affective and identity-based motivations, and reduce structural barriers to action. Full article

There is a growing demand for digital innovation to facilitate authentic communication during the learning experience at Australian Universities. Student’s communication is considered ‘authentic’ in various ways, from using discipline-specific professional language to expressing personal values through honest self-reflection. Enhancing authentic rational decision-making during social learning online is one priority area now available for students developing clinical reasoning skills. Using a Design-based Research (DBR) methodological framework, 34 students, 26 educators, and 5 learning designers from Torrens University Australia provided iterative feedback on the development and implementation of a simple digital decision wheel tool, aimed at supporting independent and collaborative decision-making. Three DBR phases were implemented, encompassing an initial pilot and development stage with 3 subjects, and two subsequent phases with an additional 17 subjects that were incorporated using a decision wheel tool for independent and problem-based learning. Data were generated through 44 semi-structured interviews and 20 focus groups across twenty undergraduate subjects delivered in various learning modes across five 12-week DBR action cycles. Reflexive thematic analysis and bounded rationality theory guided analysis. Outputs reveal that a simple digital tool contributed positively to making authentic learning moments visible and promoted inclusive and formative dialogue. Benefits included development of psychological authenticity when preparing to make authentic industry decisions. The initiative aligns with broader educational goals for resourcing and developing tools to scaffold a ‘critical pause’ before articulating authentic thinking when engaging with humans and machines. Full article

At the intersection of the circular economy and artificial intelligence (AI), high-value secondhand trading faces a “triple decision dilemma” of cognitive overload, trust risk, and emotional attachment. To address the limits of traditional human-centered theories, this study develops and empirically tests a novel framework of Algorithmic Empowerment. Drawing on data from 1396 users of Chinese secondhand luxury platforms and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings reveal that users’ empowerment perception arises from three dimensions—Algorithmic Connectivity (AC), Human–Agent Symbiotic Trust (HAST), and Algorithmic Value Alignment (AVA). This perceived empowerment affects participation willingness through two parallel pathways: the social pathway, where algorithmic curation shapes social norms and recognition, and the cognitive pathway, where AI enhances decision fluency and reduces cognitive friction. The results confirm the dual mediating effects of these mechanisms. This study advances understanding of human–AI collaboration in sustainable consumption by conceptualizing empowerment as the bridge linking algorithmic functions to user engagement, and provides actionable implications for designing AI systems that both enhance efficiency and foster user trust and identification. Full article

The rapid emergence of generative AI is transforming how employees engage with technology to perform tasks, make decisions, and create value. Despite its transformative potential, empirical findings on AI adoption remain inconsistent, particularly regarding how job characteristics shape employees’ confidence and readiness to use generative AI. Grounded in the Task–Technology Fit framework and self-efficacy theory, this research examines the curvilinear relationship between job complexity and AI self-efficacy and its subsequent effects on AI adoption readiness and behavior. We conducted two survey studies to test the proposed hypotheses using structural equation modeling. Results reveal that employees in both low- and high-complexity roles exhibit a low level of AI self-efficacy and a subsequent lower level of AI adoption behaviors compared to those in moderately complex roles. These findings challenge the assumption that highly skilled roles typically lead AI integration and instead highlight the importance of aligning task structure with AI capabilities. This study advances theory by introducing a non-linear boundary condition to technology adoption and offers practical guidance for organizations to design jobs and training programs that cultivate confidence and foster sustainable human–AI collaboration. Full article

Classical game theory provides powerful tools for modeling strategic interaction, but often overlooks the social, cultural, and institutional dimensions of human behavior. To address this gap, Tom Burns and collaborators developed generalized game theory (GGT) and later sociological game theory (SGT). These frameworks extend classical game theory by embedding rules, norms, values, beliefs, roles, and institutional structures into formal models of interaction. This review synthesizes thirty key contributions to this research program, organizing the literature into eight thematic areas and providing an integrated overview of the field. The originality of this work lies in its comprehensive approach, which advances conceptual and formal foundations while exploring practical applications and outlining directions for future research. GGT/SGT develops rule-based modeling, the analysis of norms and values, multiple modalities of action determination, and various equilibrium types, offering a rigorous framework for understanding strategic behavior in complex social contexts. In application, these approaches provide insights into organizational processes, negotiation, legitimacy, distributive justice, and institutionalized procedures, while integrating interactionist and group-theoretical perspectives. By linking formal modeling with normative and institutional analysis, GGT/SGT offers innovative socio-economic decision models that capture uncertainty, fairness, legitimacy, and institutional transformation. It extends classical game theory by bridging mathematics, economics, and sociology, providing a versatile theoretical tool for understanding complex socio-economic systems and improving strategic decision-making in contemporary society. Full article

Ecocentrism has emerged as a significant theoretical paradigm for addressing ecological crises and promoting sustainable development. However, while influencing the evolution of ecological governance systems, it faces fundamental criticisms including accusations of being “eco-authoritarianism”, “anti-human”, and “utopian”. This study develops a theoretical defense of ecocentrism through Daoism’s three-dimensional framework encompassing ontology, value theory, and practice theory. First, the Daoist holistic concept of living together (bingsheng 並生)—grounded in the principle of “Dao as one”—deconstructs the ontological foundations of anthropocentrism while addressing ecocentrism’s alleged “dictatorial “tendencies. Second, the Daoist value paradigm of valuing life (guisheng 貴生) challenges anthropocentrism’s value hegemony while establishing ethical justification for ecocentrism. Third, Daoist practical philosophy—particularly the concept of nurturing life (yangsheng 養生)—demonstrates how the harmonious coexistence of heaven, earth, and humanity can be achieved through balanced integration of instrumental and value rationality in ecological governance, thereby resolving accusations of “utopianism”. The findings affirm that Daoist philosophy provides not only a robust theoretical defense for ecocentrism but also insightful practical wisdom for global environmental governance and the pursuit of sustainable development. Full article

E-commerce virtual anchors’ live-streaming sales represent a critical intersection of virtual human technology and artificial intelligence (AI), paving the way for new developments in digital marketing. Recent advancements in AI have significantly enhanced the intelligence of virtual anchors, driving increased consumer acceptance. As intelligence is a key determinant of user adoption, this study employs a mixed-methods approach combining grounded theory and quantitative analysis to conceptualize, structure, and measure virtual anchor intelligence. The grounded theory results reveal that virtual anchor intelligence encompasses multiple capabilities—manifested in guidance, recognition, analysis, and feedback during human–computer interaction, which enable effective hosting and sales performance. Four core dimensions of intelligence are identified: guidance intelligence, recognition intelligence, analysis intelligence, and feedback intelligence. Following established protocols for scale development, we constructed and validated an 18-item measurement scale, demonstrating strong reliability and validity. Empirical findings indicate that while guidance intelligence exerts an adverse effect on consumer participation, the remaining dimensions have positive effects, mediated by perceived shopping value. This study provides a comprehensive framework for understanding and measuring virtual anchor intelligence, elucidating its underlying mechanisms. The findings lay a theoretical foundation for future research on e-commerce virtual anchors but also offer practical implications for optimizing live-streaming strategies and advancing the design of virtual humans. Full article

This study develops and validates the concept of Regulatory Cultural Stewardship (RCS) as a dynamic capability that enables small and medium-sized enterprises (SMEs) to achieve sustainable AI-enabled digital transformation (AIEDT) in a volatile emerging economy. RCS empowers SMEs to harmonize regulatory compliance with cultural legitimacy, a critical nexus for fostering sustainable business practices and long-term resilience (economic viability and social legitimacy), in line with the global sustainable objectives. Using survey data from 391 Pakistani SMEs and Partial Least Squares Structural Equation Modeling (PLS-SEM), we find that four key AIEDT drivers explain 65.1% of the variance in AI innovation, with Technological Infrastructure and Policy and Ecosystem Support as dominant enablers. AI innovation fully mediates the relationship between AIEDT drivers and sustainable business performance. RCS not only enhances SME performance directly but also strengthens the AI innovation–business performance linkage as a significant moderator. Sectoral analysis reveals that services benefit most from Socio-Cultural Readiness, while manufacturing and primary sectors depend more on policy infrastructure and RCS. Significantly, RCS is validated as a distinct construct, integrating compliance and cultural alignment, rather than a subset of existing factors like policy support or cultural readiness. The study emphasizes the importance of scalable AI infrastructure, workforce upskilling, and internal cultural adaptation, while urging policymakers to stabilize AI governance frameworks to ensure a sustainable and equitable digital transition. The findings advance theory by conceptualizing RCS as a meta-capability bridging institutional voids and socio-cultural dynamics and offer practical insights for policymakers and managers seeking to implement ethically aligned and sustainable AIEDT strategies in emerging markets. At a conceptual level, RCS is ethically grounded in global AI principles, including fairness, accountability, and transparency, ensuring that cultural alignment never overrides human-centered values. Full article

The increasing occurrence of extreme rainfall events often leads to flash floods, infrastructure damage, loss of human life, and significant economic impacts. There is a pressing need for data-driven assessments and the application of robust analytical approaches to better understand these changes. Analyzing ground-level daily rainfall data from 1985 to 2023 from 26 monitoring stations, this study first employs the Mann–Kendall test using robust statistics including minimum, median, various quartiles, and maximum rainfall values for detecting long-term trends across Saudi Arabia. Next, the k-means clustering technique is applied to characterize the annual rainfall cycles across different regions of the country. Finally, the Peaks Over Threshold (POT) approach within Extreme Value Theory (EVT) is employed to identify site-specific thresholds for extreme rainfall using the Generalized Pareto Distribution (GPD). This automated, data-driven method offers a more objective alternative to the commonly used ad hoc percentile-based threshold selection, thereby enhancing the rigour and reproducibility of extreme rainfall analysis. Local specific thresholds were computed ranging from about 16 to 47 mm from Arar and Jazan, respectively. These thresholds were then used to calculate the frequency and intensity of extreme rainfall events. The fitted GPD parameters were further used to estimate return levels (RLs) for different return periods (2-, 5-, 10-, 20-, 50-, and 100-year) into the future. The results underscore considerable spatial variability in extreme rainfall behaviour across Saudi Arabia, with a higher likelihood of intense and infrequent precipitation events in the coming decades. Full article

Contemporary architecture is undergoing a transformation from the modernist techno-functional paradigm towards practices that integrate technology with humanistic, cultural, and environmental values. Biophilia—understood as the innate human need for contact with nature—is becoming an important design category that supports health, well-being, and ecological awareness, yet it can also convey additional narratives. In this context, immersion plays a significant role: it is a process of deep engagement of the user with space, involving the senses, emotions, and imagination, while simultaneously fostering relationships between humans and their surroundings. The concept of immersiveness, originating in art theory and digital media studies, is now applied in architecture as a tool for creating spatial narratives and cultural experiences. Biophilic architecture employs immersive strategies to transform buildings into environments that support sensory, behavioural, and social practices. This article analyses selected examples of such projects (including the Rooftop Garden—Warsaw University Library, Musée du quai Branly, and apartment buildings Bosco Verticale) and proposes a Multi-criteria Method for Assessing Architectural Immersiveness (MMAAI). The findings indicate that the integration of nature, technology, and spatial narrative enables architecture to act as a mediator between humans and the environment, generating new qualities of spatial experience in the Anthropocene epoch. Full article

Background/Objectives: Sustainable nutrition is essential for human and planetary health. The Transtheoretical Model-based Sustainable Nutrition Behavior Scale (TTM-SNBS) was developed to assess sustainable nutrition behaviors and the dynamic processes of behavior change in adolescents. Methods: The item pool was generated through literature review and expert consultation using the Delphi technique (10 experts, three rounds). Construct validity was assessed using exploratory and confirmatory factor analyses. Reliability was evaluated through Cronbach’s alpha and test–retest methods. External validity was examined through correlations with the Sustainable and Healthy Eating Behaviors Scale (SHEBS), following COSMIN standards. The study included 512 adolescents aged 14–18 years (54% female) from public high schools in Ankara, Türkiye. Results: Initially, 75 items were developed through expert evaluation. After preliminary testing, two items with low and negative correlations were removed; 73 were retained for validation. Factor analyses and refinement produced a 45-item final validated scale comprising one stage of change item and five subscales: cognitive processes (14 items), behavioral processes (18 items), decisional balance—pros (4 items), decisional balance—cons (4 items), and self-efficacy (4 items). Items showed good discrimination (>0.27). Cronbach’s alpha values ranged from 0.67 to 0.93, and fit indices were acceptable (χ²/df = 2.8–4.2; RMSEA = 0.045–0.065). External validity was supported by significant positive correlations with the SHEBS. Conclusions: The TTM-SNBS is the first psychometrically validated, theory-based instrument to assess sustainable nutrition behaviors in adolescents. It offers a reliable and valid instrument to support future research and interventions promoting sustainable dietary practices. Full article