This study investigates the intellectual structure of 3D virtual world language learning (3DVWLL) by using the co-citation approach. Previous studies report the affordance regarding immersive learning experiences, communicative language strategies, and a versatile integration of digital learning materials (Lin & Lan, 2015; Reisoğlu et al., 2017; Avğousti, 2018; Wang et al. 2020). However, a unified account is still required to explain the diverse and incoherent achievements the reviews demonstrate. The objectives of the current study are two-fold. The first one serves to depict the intellectual structure of the core studies in this field. The second one is to provide pedagogical norms for language education as a resource for evaluating teaching plans when practitioners integrate 3DVWs into course designs. The methods of co-citation analysis include (i) document co-citation analysis (DCA) to identify the associations among studies within a discipline and (ii) social network analysis (SNA) to represent the complex relationships among research clusters. The results revealed a well-established intellectual structure of the 3DVWLL research field, comprising highly co-cited pairs and research clusters from 2000 to 2024. Such findings indicate high intellectual cohesion within the field, as evidenced by the cascaded linkage among issues revealed through document co-citation analysis and the primary and isolated components identified through social network analysis. To conclude, the co-citation network reveals 3DVWLL as a sustained process of technological and pedagogical advancement, underpinned by multi-layered and structurally interconnected theoretical linkages that lay the foundation for the field’s disciplinary development.
This study investigates the role of visionary leadership in fostering sustainable innovation amid digital transformation, focusing specifically on the city of Jeddah, Saudi Arabia. As the Kingdom undergoes a profound socio-economic shift under Vision 2030, leadership has emerged as a critical driver in aligning organizational practices with national sustainability and digitalization goals. Employing an exploratory sequential mixed-methods design, the research first conducted qualitative interviews with public and private sector leaders, identifying four major themes: Vision as a Strategic Compass, Culture of Empowerment and Experimentation, Digital Transformation as a Sustainability Enabler, and Barriers Rooted in Institutional and Cultural Structures. A subsequent quantitative phase, involving 175 survey participants, validated these findings through descriptive and inferential statistics, including regression and exploratory path analysis. Results indicated that visionary leadership was significantly and positively associated with sustainable innovation outcomes, both directly and indirectly through empowerment culture and digital technology integration. Conversely, institutional and cultural barriers were shown to inhibit innovation potential. The study proposes a region-specific conceptual model capturing the complex interrelations between leadership, sustainability, and digital capability, moderated by institutional context. This research contributes theoretically by contextualizing global leadership frameworks within the Arab Gulf and practically by offering actionable insights for leaders, policymakers, and digital transformation strategists. It highlights the need for adaptive leadership strategies that are both technologically progressive and culturally sensitive in driving sustainable futures.
This study investigates the role of academically experienced independent directors (AIDs) in shaping firms’ climate risk consciousness in Chinese listed companies. Using a panel dataset from 2008 to 2023 and fixed effects regression models, we find that a higher proportion of AIDs significantly enhances firms’ climate risk consciousness. The effect operates through two mechanisms: improving the quality of corporate information disclosure and shaping executives’ environmental cognition. The influence of AIDs is stronger in firms with low managerial ownership, weaker internal ESG performance, higher analyst coverage, and in regions with stricter environmental regulations. The study contributes to the literature by examining the previously underexplored impact of AIDs on corporate environmental awareness, identifying key moderating factors, and highlighting the role of China’s Confucian cultural context in shaping board effectiveness. These findings provide practical implications for policymakers and corporate practitioners regarding board composition and the integration of academic expertise to promote corporate sustainability.
Historically, within Western frameworks, the burden of labor has been contextualized through a theological narrative: labor as a form of ontological toil rooted in the biblical curse of Genesis 3:17. This paradigm established work as a divinely ordained existential endurance demanding moral submission. However, successive scientific revolutions disrupted this narrative, giving rise to modern technology as an ideological means of seeking mastery over nature. This paper analyzes the dialectical tension between the existential parameters of biblical labor and the mechanistic assertions of contemporary technological systems—a phenomenon Neil Postman conceptualizes as Technopoly. I argue that contemporary technological systems have transcended mere utility, operating as a surrogate technical deity that renders the biblical curse of labor obsolete. By offering a secularized salvation predicated on efficiency and automation, Technopoly repositions itself as the ultimate agent of material redemption. This promise culminates in the vision of the “End of Work,” reframing liberation not as a deferred spiritual afterlife, but as an immanent technological reality—the realization of a modern, earthly heaven. Engaging critically with thinkers from John Paul II and Bulgakov to Postman, Francis, and Stiegler, this paper maps the positive virtues of this post-work heaven, its existential boundaries, and the enduring ontological question of whether an automated paradise can truly satisfy humanity’s historic longing for the Transcendent or render it entirely obsolete.
Sustainable innovation serves as an inexhaustible driving force for enterprise development, yet few studies have explored the impact of ambidextrous leadership on an enterprise’s sustainable innovation capability. This study adopts ambidextrous leadership as its starting point, introducing organizational innovation climate and employee innovation behavior as two mediating variables. It constructs a chained mediation model to examine the relationship mechanism of ambidextrous leadership on enterprise sustainable innovation capability, thereby enriching research on the factors affecting sustainable innovation capability. Empirical analysis was conducted on 311 valid questionnaire responses using SPSS 27.0 and PROCESS, employing multiple regression and the Bootstrap method to test the proposed research hypotheses. The results show that: ambidextrous leadership is positively associated with enterprise sustainable innovation capability, and ambidextrous leadership style shows a stronger positive association with enterprise sustainable innovation capability is better than that of a single leadership style, organizational innovation climate and employee innovative behavior play a partial mediating role in the above relationships, and the mediation chain formed by both of them plays a chain mediating role. The research findings not only reveal the “black box” mechanism through which ambidextrous leadership influences sustainable innovation capability but also provide new insights for enterprises seeking to improve their sustainable innovation capability.
As two critical dimensions of regional responses to structural crises, population shrinkage and economic resilience are intrinsically interconnected in their theoretical foundations. However, the complex network mechanisms underlying their interconnection remain inadequately explored. This study investigates the networked linkage mechanisms between regional population shrinkage and economic resilience, using Northeast China as a representative case. It employs a comprehensive methodology, including the resilience proxy approach, gravity model, vector autoregression (VAR) model, Granger causality tests, and social network analysis (SNA), to systematically construct regional population shrinkage and economic resilience networks. Furthermore, Quadratic Assignment Procedure (QAP) regression analysis is employed to examine the correlation patterns between these two dimensions at both network and node levels. The main findings are as follows: (1) Northeast China exhibits a widespread trend of population shrinkage, with Heilongjiang and Jilin provinces being the most significantly affected. As the central city of Jilin, Changchun demonstrates a pronounced siphoning effect, intensifying population loss in surrounding regions. The economic resilience index across the region displays an overall decline yet exhibits considerable spatial heterogeneity: Heilongjiang shows marked internal disparities, whereas Jilin and Liaoning provinces demonstrate convergent downward trajectories. (2) The spatial linkage structures of the population shrinkage network and the economic resilience network demonstrate substantial dissimilarities. In the population shrinkage network, provincial capitals and regional hub cities function as core nodes, exhibiting high network centrality. Conversely, the economic resilience network is predominantly sustained by resource-based cities as pivotal nodes. Owing to industrial path dependence, these cities have developed distinctive regional mutual-support mechanisms, which contribute to maintaining high network centrality. (3) The relationship between the population shrinkage network and the economic resilience network exhibits a clear spatial scale effect. QAP analysis at the full-network level reveals a weak and statistically insignificant correlation, indicating that the two networks have evolved through relatively independent pathways. However, at the node level, nine cities display statistically significant correlations, five exhibiting positive associations and four demonstrating negative relationships, reflecting differentiated urban resilience mechanisms in responding to population shrinkage. The policy implications indicate that enhancing economic resilience and mitigating population shrinkage necessitate regionally differentiated strategies. Core cities should reinforce coordinated development mechanisms to harness agglomeration advantages, while resource-based cities must overcome path dependency and foster new drivers of resilience through industrial diversification and innovation. This study offers a novel analytical framework and a robust decision-making foundation for deciphering the complex interactions within population-economy systems and advancing sustainable regional development.
Facing volatile oil prices, strict ecological regulations and complex geological conditions, traditional multi-attribute decision-making (MADM) methods for oilfield investment overemphasize economic benefits while ignoring non-economic indicators and attribute uncertainty. To solve these deficiencies, this paper proposes an improved MADM framework for oil and gas development investment decision-making. Firstly, a five-dimensional evaluation index system covering economic, technological, geological, ecological and social attributes is established. Secondly, interval-valued fuzzy numbers (IVFNs) and interval fuzzy analytic hierarchy process (IF-AHP) are adopted to quantify index weights and address decision uncertainty. Furthermore, grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to rank development schemes. A case study of six oilfield blocks in China verifies the reliability of the proposed framework. The results indicate that this method can effectively reduce decision bias and comprehensively characterize multidimensional attributes. This study provides a systematic decision-making tool for oilfield investment optimization and offers references for the sustainable development of oil and gas resources.
This study introduces the novel concept of ECON-ESG to investigate, for the first time, the impact of economic, environmental, social, and governance factors on energy poverty in South Asian countries during 2000–2021. Using advanced econometric techniques—including Pooled Mean Group (PMG)/Autoregressive Distributed Lag (ARDL) models, Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Granger causality tests—the study examines both long-term and short-term dynamics. The results reveal significant long-term relationships between energy poverty and individual ESG dimensions. Environmental improvements reduce energy poverty over the long term but present short-term challenges due to high transition costs. Social investments, especially in education, healthcare, and gender equity, are crucial for alleviating energy poverty, fostering inclusive development, and enhancing access to energy. Governance, characterized by transparency, accountability, and efficient policy implementation, ensures equitable energy distribution. The composite ECON-ESG factor highlights both opportunities and challenges, emphasizing the complexity of integrating ESG strategies with economic realities. Bidirectional causality tests further indicate interdependence between energy poverty and ESG factors, with governance, social, and environmental dimensions showing significant causal effects. The findings underscore the importance of context-specific, adaptive frameworks in South Asia, harmonizing ESG objectives with economic growth. Policymakers are encouraged to adopt balanced strategies addressing short-term trade-offs and long-term sustainability, ultimately promoting social equity, reducing energy poverty, and advancing the region’s sustainable development goals (SDGs).
Although the Chinese government has launched a series of capital account liberalization schemes to promote the systemic importance of the mainland China stock market, the mainland China market still remains relatively marginal within global stock markets. That is, China’s capital account liberalization does not seem to have worked as expected. In this study, the systemic importance of the mainland China stock market is measured on the basis of high-dimensional dynamic return, risk, and extreme risk spillover networks, and the heterogeneous effects of China’s capital account liberalization on it are further analysed. The empirical results show that capital account liberalization indeed contributes to improving the systemic importance of the mainland China stock market. However, the positive effects are manifested in the return and risk spillovers among global stock markets and are more obvious after the implementation of the RMB Qualified Foreign Institutional Investor, Shanghai–Hong Kong Stock Connect and Shenzhen–Hong Kong Stock Connect schemes. In addition, gross domestic product, economic policy uncertainty, and investor sentiment significantly affect the systemic importance of the mainland China stock market in different directions and magnitudes.
This study investigates the causal impact of educational attainment on individuals’ pro-environmental behaviors in China’s public and private domains. Despite China’s significant educational progress and environmental commitment, the non-monetary benefits of education in fostering sustainable behavior remain understudied. Employing the Compulsory Education Law as an instrumental variable and drawing on Value-Belief-Norm theory, we analyze how education influences pro-environmental behaviors. Instrumental variable estimates reveal that each additional year of schooling increases public-sphere pro-environmental behaviors by 8.0% and private-sphere behaviors by 9.3%. These effects remain robust across alternative specifications, including different instrumental variables, age range, and geographical fixed effects. We identify both direct mechanisms (environmental knowledge, cognition, and awareness) and indirect mechanisms (information via media utilization and economic capacity through income) for education’s influence on environmental stewardship. Heterogeneity analysis reveals that educational impacts on public-sphere PEBs are substantially stronger among rural residents, low-income groups, and populations in environmentally challenged regions, while private-sphere effects remain relatively consistent across demographic and regional contexts. Our findings contribute to the current understanding of education’s non-monetary returns in environmental protection and provide actionable implications for context-specific educational policies promoting sustainable development.
Data fairness is increasingly emerging as a new and critical social issue, following long-standing concerns over income, education, and healthcare fairness. In digital healthcare, platforms increasingly rely on large-scale patient data and algorithmic systems to deliver services, raising pressing social and ethical questions regarding the fairness of health data practices. While existing research has largely examined data fairness from technical or regulatory perspectives, comparatively little attention has been paid to how patients subjectively perceive data fairness and how such perceptions are formed through psychological and governance-related mechanisms. Drawing on fairness theory, trust theory, and perceived risk theory, this study develops an integrated analytical framework to examine how data transparency, algorithmic fairness, and data control shape patients’ perceived data fairness on healthcare platforms. Using survey data collected from 1116 users of healthcare platforms in China, the proposed model is empirically tested through partial least squares structural equation modeling, complemented by multi-group analyses across demographic and health-status groups. The findings indicate that data transparency enhances perceived data fairness primarily by fostering patient trust, while algorithmic fairness exerts a direct and independent influence on fairness perceptions, with stronger effects observed among older users. In addition, greater patient control over personal data reduces perceived risk, which in turn strengthens perceived data fairness, particularly among individuals in sub-healthy conditions. These results demonstrate that patients’ judgments of data fairness emerge from a combined process of trust formation, algorithmic evaluation, and risk mitigation rather than from isolated technical features. By foregrounding patients’ subjective experiences, this study contributes to social science debates on digital health governance and highlights the importance of patient-centered data practices for building ethical, trustworthy, and socially sustainable health data ecosystems.
In manufacturing specifically, small and medium-sized enterprises (SMEs) play a pivotal role in China’s industrial transformation, yet often face constraints that hinder innovation and performance. This study investigates how management control systems (MCSs), specifically belief systems (Bs) and interactive control systems (ICs), foster innovation capability (IC) and, through it, stimulate multiple types of innovations: product (PRDI), process (PROI), organizational (OI), and marketing (MI), and ultimately enhance innovation performance (IP). Drawing on the dynamic capability theory (DCT), MCSs are conceptualized as enabling mechanisms that help SMEs to transform limited resources into innovation outcomes. Leveraging survey data obtained from 505 employees in Chinese equipment manufacturing (SMEs) and analyzing with partial least squares structural equation modeling (PLS-SEM), the results reveal that both Bs and ICs significantly strengthen IC, with ICs exerting the stronger effect. IC most strongly drives OI and PROI, while OI contributes most to IP. The results reveal the role of MCS-enabled IC as a strategic pathway for enhancing adaptability and competitiveness among Chinese manufacturing SMEs.
During the development of transportation infrastructure in China, the high-speed rail (HSR) network has been rapidly expanded, exerting a substantial impact on regional economic growth. While most existing studies on the HSR-economy relationship have focused on developed regions in eastern China, this study selects two major urban agglomerations in the relatively less-developed western region—the Guanzhong Plain Urban Agglomeration (GPUA) and the Chengdu-Chongqing Urban Agglomeration (CCUA)—as its study subjects. This study constructs a multi-layer network framework based on complex network theory and the gravity model, incorporating physical and operational HSR networks along with an economic network. By employing Social Network Analysis (SNA), the Mantel test, and the Time Exponential Random Graph Model (TERGM), we systematically examine the spatiotemporal evolution of the HSR network structure, its correlation with the regional economic network, and the associated mechanisms and effects. The results indicate that from 2014 to 2024, the density of the HSR network increased in both the GPUA and the CCUA. The GPUA maintained a single-core structure centered on Xi’an, while the CCUA exhibited a dual-core structure with Chengdu and Chongqing as hubs. The Mantel test confirms a significant positive correlation between the HSR operational network and the economic network. This correlation is stronger in the more economically developed and administratively concentrated CCUA—spanning just one province and one municipality—than in the cross-provincial GPUA. Further analysis by TERGM demonstrates the independent role of HSR in the development of economic networks and its transmission path. Correlation analysis further reveals that enhanced HSR connectivity and strengthened economic ties are not fully synchronized.
This study explores how Augmented Reality User Experience Features (ARUEF) in AR-enabled virtual fitting applications influence user engagement and continuance tendency. Despite the increasing adoption of augmented reality technologies in retail environments, limited research has examined how AR user experience features jointly shape user perceptions, engagement, and continued usage in virtual fitting contexts. To address this gap, this study conceptualizes ARUEF as a multidimensional construct composed of nine key user experience attributes. Based on the Technology Acceptance Model (TAM), a research model is developed to examine the mechanisms through which ARUEF influence user responses. A quantitative survey was conducted among 465 augmented reality users in China, and the proposed model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that ARUEF are positively associated with Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Emotional Engagement, and Cognitive Engagement. In addition, the results support the traditional TAM relationship in which Perceived Ease of Use positively influences Perceived Usefulness. These factors are in turn associated with users’ continuance tendency toward AR-enabled virtual fitting applications. The findings highlight the importance of AR user experience features in shaping user perceptions and engagement in immersive retail environments. By conceptualizing ARUEF as a multidimensional experience framework and integrating emotional and cognitive engagement into TAM, this study extends existing research on AR-enabled retail technologies and provides a more comprehensive understanding of user responses in virtual fitting environments. Moreover, it provides practical insights for designing more interactive and user-centered AR virtual fitting applications.
As a key initiative toward achieving China’s “dual carbon” objectives, the programs for low-carbon cities and new energy demonstration cities have significantly contributed to enhancing urban carbon emission efficiency(UCEE). Existing research has identified the separate impacts of the two environmental regulation policies, yet tends to emphasize a single dimension, neglecting their complementary roles and the synergistic emission-reduction benefits arising from joint implementation. Using panel data for 252 Chinese cities covering 2008–2021, this study regards the dual-pilot initiative for low-carbon and new energy demonstration cities as a quasi-natural experiment and applies a spatial DID (SDM-DID) model to evaluate its influence and spillover effects on UCEE. The findings indicate: (1) The dual-pilot policy positively contributes to improving UCEE but exerts certain negative spillover effects on neighboring cities. The findings are supported by multiple robustness verification methods. (2) The dual-pilot policy affects UCEE through mediating mechanisms such as promoting population size (PS) and service-sector development (SSD). (3) The policy effect of the dual-pilot policy is more pronounced than that of single-pilot policies. (4) Heterogeneity analysis shows that the dual-pilot policy has stronger effects in sparse-population areas, while its influence is relatively weaker in densely populated areas; furthermore, the policy effect is more evident in non-capital cities compared to provincial capital cities.
In the digital era, personal data privacy protection has become a key element of sustainable development. However, most existing literature examines technical, legal, and behavioural aspects in isolation, overlooking the nonlinear propagation mechanisms across different levels. This study integrates a literature review and expert interviews to comprehensively survey existing works and identifies thirteen determinants involving data subjects, data collectors, and regulatory agencies. Building on this foundation, we innovatively integrate a three-stage hybrid methodology—DEMATEL-ISM-MICMAC—to systematically map causal dependencies, hierarchical structures, and attribute robustness among factors. The results reveal that the completeness of legal frameworks and enforcement intensity function as core drivers, whereas trust constitutes a highly dependent yet fragile node. Critical transmission paths encompass the longest chain of “institution–enforcement–cognition–trust” and the shortest chain of “legal provisions→processing transparency”. On this basis, we propose a five-dimensional policy package that (i) reinforces regulatory drivers, (ii) institutionalises trust-repair mechanisms, (iii) leverages trauma-induced learning effects, (iv) optimises transmission pathways, and (v) implements full-cycle collaborative governance, thereby offering a systemic intervention framework to resolve the dilemma of fragmented governance.
The promotion of national pride is an important topic for all countries. Research has shown that national scientific and technological achievements can promote citizens’ national pride. However, there is a lack of academic research on the influencing factors and mechanisms involved, calling for an exploratory investigation to generate a substantive theory from empirical data. Therefore, this study adopts a grounded theory approach, using Chinese university students as research participants, to explore the influencing mechanism of the internet dissemination of scientific and technological achievements on national pride based on the case of the C919 commercial flight. The study reveals that internet access, information features, and thinking dispositions are core factors influencing national pride perception. The internet allows university students to easily access information about the C919 commercial flight, and the information content evokes empathy, group belonging, and rational evaluation, which in turn inspires a sense of national pride among the students. This study deepens our understanding of the influence of the dissemination of scientific and technological achievements on national pride, expands the research on the factors influencing national pride, and provides a new case for the study of national pride.
Artificial Intelligence Painting Tools (AIPT) have emerged as human-AI co-creative systems that enable professional artists to collaborate with generative algorithms throughout the creative process. However, the mechanisms underlying the adoption and sustained use of these interactive tools among professional artists remain insufficiently understood, particularly from the user experience (UX) and usability perspectives. To address this gap, this study proposes an Extended Technology Acceptance Model (ETAM) that integrates core Technology Acceptance Model (TAM) constructs with UX factors to explain art professionals’ adoption behaviour toward AI-assisted technologies. Survey data collected from 465 art professionals in Nanchang were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Results indicate that creativity (CRE), hedonic motivation (HM), and AI literacy (AIL) significantly enhance both perceived usefulness (PU) and perceived ease of use (PEOU); while social influence (SI) primarily affects PU, and self-efficacy (SE) mainly affects PEOU. PEOU positively influences PU, and both contribute to behavioural intention (BI), which subsequently predicts use behaviour (UB). Several conventional TAM/UTAUT relationships, including the effects of facilitating conditions and selected direct pathways, were not supported. In addition, perceived trust (PT) significantly moderates the relationship between BI and UB. The findings demonstrate that intrinsic experiential and creative factors play a more influential role than the external environmental determinants in shaping AI painting tool adoption among professional artists. Theoretically, the study extends TAM by integrating creativity, AI literacy and trust moderation within a professional artistic context, identifying trust as a critical boundary condition and highlighting the importance of experiential factors in AI-assisted creative adoption. Practically, it provides insights for the user-centred design and sustainable deployment of AIPT.
The integration of artificial intelligence (AI) into administrative, judicial, and regulatory processes is reshaping how legal rules are implemented and experienced in contemporary China. The study examines whether established legitimacy mechanisms continue to structure acceptance of AI-mediated legal duties. Drawing on procedural justice theory and responsibility-gap debates, the study develops a legitimacy-centered model in which perceived procedural fairness, perceived AI accountability, and trust in state institutions influence public and professional stakeholders’ acceptance of AI-embedded legal duties through perceived legitimacy of the AI-enabled state. AI literacy is incorporated as a moderating factor. Using a mixed-methods design that combines survey data (N = 642) and semi-structured interviews (n = 41) across the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Greater Bay Area, the study employs partial least squares structural equation modeling (PLS-SEM) to test direct, indirect, and moderated relationships. Results indicate that procedural fairness and AI accountability significantly enhance perceived legitimacy, which in turn strongly predicts acceptance of AI-mediated legal obligations such as algorithmically enforced traffic regulation and administrative decision-making. Trust in state institutions operates primarily through legitimacy rather than independently. Qualitative findings reveal conditional support: respondents acknowledge efficiency and consistency benefits but express concerns regarding opacity, data misuse, and reduced human oversight. The study demonstrates that algorithmic governance remains normatively dependent on legitimacy judgments and provides empirically grounded insight into AI-enabled authority within China’s centralized governance framework.
Natural disasters create disproportionate risks for individuals with Autism Spectrum Disorder (ASD) because emergency environments often involve sudden changes, sensory overload, disrupted routines, and communication demands. This qualitative study examined the experiences of search and rescue (SAR) personnel who interacted with individuals with ASD during and after earthquake-related rescue operations in Türkiye. A phenomenological design was used to explore the shared meanings of these experiences. Data were collected through a single online focus group conducted in two sessions with six SAR personnel selected through criterion-based purposive sampling. All participants had direct experience of interacting with individuals with ASD during disaster response. The data were analysed using inductive content analysis. Five main themes were identified: interaction with individuals with ASD during the disaster process; SAR experiences; challenges encountered in SAR operations; support requirements in SAR operations; and recommendations. The findings show that communication breakdowns, sensory and emotional distress, uncertainty about appropriate interaction strategies, limited family-professional coordination, andin sufficient ASD-related training shaped SAR personnel’s experiences. The study highlights the need to integrate autism-specific communication strategies, family-informed planning, inter-agency coordination, and disability-inclusive training into disaster preparedness and response systems. Although exploratory and context-specific, the findings offer practical implications for developing more inclusive emergency response practices in Türkiye and comparable disaster-prone contexts.
