Search Results (2,701)

This study aims to identify and synthesize the major global trends that shaped 2025 by applying the DeflyCompass methodology to a curated corpus of strategic foresight reports. The study synthesizes insights from 23 strategic reports published by leading international organizations, including the World Economic Forum, Accenture, Euromonitor, and major technology firms. Methodologically, DeflyCompass operationalizes a structured hybrid human–AI pipeline comprising the deployment of multi-agent AI systems, automated knowledge graph construction, semantic clustering, and hybrid human–AI validation processes, reducing an initial set of 816 preliminary signals to a validated catalog of 50 high-priority trends across six PESTEL domains: Political, Economic, Social, Technological, Environmental, and Legal/Governance. Key findings indicate that artificial intelligence functions as a systemic enabling technology across all domains, climate and sustainability imperatives permeate multiple domains, geopolitical fragmentation introduces systemic tension, and trust deficits emerge as a critical vulnerability. The study contributes a replicable and scalable framework for global-level strategic foresight that operationalizes human–AI integration within a rigorous expert-driven validation process, complementing existing hybrid analytical approaches in the literature. Implications extend to decision-making in technology governance, sustainability strategy, social adaptation, and scenario planning, highlighting the necessity of integrating AI augmentation with human expertise for effective future-oriented planning. Full article

Influencer marketing research has shown that source-related evaluations matter, yet less is known about how specific influencer cues are translated into consumer responses through differentiated internal psychological states. Drawing on the Stimulus–Organism–Response (S-O-R) framework, this study examines how influencer attractiveness and expertise shape consumer responses through parasocial interaction and trust. Attractiveness is conceptualized as a social-affective cue, whereas expertise is conceptualized as a competence-based cue. Parasocial interaction is modeled as a relational organismic state, and trust is modeled as a reliance-oriented organismic state. Survey data were collected from 532 Taiwanese social media users with prior experience following influencers and analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that attractiveness positively predicts parasocial interaction, expertise positively predicts trust, and parasocial interaction further contributes to trust. Trust, in turn, positively influences loyalty, purchase intention, and recommendation intention, with the strongest effect observed for recommendation intention. These findings suggest that influencer effectiveness is better understood as a differentiated cue–mechanism–response process rather than as a generalized source-evaluation effect. By distinguishing attractiveness from expertise and by modeling parasocial interaction and trust as conceptually distinct but sequentially connected organismic states, this study provides a more precise S-O-R account of how influencer evaluations are translated into relational, transactional, and advocacy-oriented consumer responses. Full article

Peru’s recent national mental health (MH) reforms aim to decentralise care and expand access to MH services for rural populations by integrating services into primary healthcare through the expansion of Community Mental Health Centres (CMHCs). Evidence on the implementation of these reforms at the local level remains limited. This qualitative study aimed to (i) describe the structure and implementation framework of MH services, (ii) analyse local understandings of MH; and (iii) examine pathways to care and identify barriers and facilitators to MH service implementation from both the supply (service providers) and demand (users and community members) perspectives. MH services were mapped across three provinces of northern Peru using a review of national MH policies, 2 focus group discussions, and 31 semi-structured interviews. Data were analysed thematically to explore local understandings of MH, pathways to care, and health system barriers. Local understandings of MH are shaped by cultural beliefs, social norms, and economic conditions, with many individuals experiencing distress initially relying on family networks or traditional healers. Stigma and expectations of a quick recovery hinder engagement with formal services. While the expansion of CMHCs has improved geographical access to specialised care in rural areas through proximity and being patient-centred, the implementation of respectful provider interactions remains uneven. Weak referral pathways and limited coordination between primary care centres and CMHCs frequently shift the responsibility for navigating care onto users and their families. Family involvement and culturally sensitive practices foster trust and support continued engagement. Persistent challenges include the limited capacity of service providers, high staff turnover, and the follow-up mechanisms, stigma, and tensions between cultural and biomedical understandings of MH. Peru’s expansion of CMHCs represents a significant health system reform to improve equitable access for rural populations. To sustain these gains, it will be necessary to strengthen workforce stability, clarify referral processes, and integrate culturally responsive approaches within primary care systems, offering lessons for similar resource-constrained contexts. Full article

Based on Weibo big data, BERTopic, and dual-channel sentiment analysis model, a dynamic analysis framework of public perception and emotion evolution is constructed from the perspective of disaster chain and public response. The results show that (1) Due to the trust of information sources by the public, the efficiency of early warning information reaching the public and attracting attention is relatively high. Social media activity on related topics peaked several times in response to reports of major hazards, such as railway suspensions, passengers trapped in trains, and severe flooding in Miyun District, Beijing. (2) The evolution of topics of public attention strongly corresponds to the disaster process: From early warning and emergency risk avoidance, gradually move to disaster report and rescue coordination, and finally focus on the criticism of infrastructure vulnerability. (3) The emotional response presents phased characteristics. At the initial stage of the rainstorm red warning issued by the meteorological department, anxiety is dominant; after the release of rescue information, emotion rises briefly, and reflection and attribution tendencies generally appear after the disaster. (4) Elderly populations and those in remote areas exhibit characteristics of vulnerability, information isolation, and high dependency in response to disasters. Full article

The rapid advancements in large language models (LLMs) have transformed natural language processing, enabling their application in diverse domains such as conversational agents and decision-support systems in sensitive areas like healthcare, finance, and eldercare. However, as LLMs are increasingly integrated into real-world contexts, concerns about their adherence to ethical principles, privacy norms, and contextual expectations have become critical. Privacy preservation is particularly pressing in interactions involving personal or sensitive data, where ensuring that LLMs align with societal norms while mitigating risks of information leakage is essential to fostering trust and ensuring responsible deployment. Contextual integrity (CI) provides a robust framework to address these challenges, emphasizing that information flows should adhere to context-specific social norms. This principle is especially vital in sensitive applications, where LLMs must evaluate roles, information attributes, and transmission principles to maintain ethical behavior. Despite their linguistic proficiency, LLMs often fail to recognize and adapt to nuanced contextual norms, a limitation exacerbated by their probabilistic nature and the biases in their training data, which can lead to inappropriate or harmful outputs. Addressing these shortcomings requires rigorous evaluation methodologies and fine-tuning strategies that embed societal and contextual norms into the models. Full article

In August 2022, the Pearl River flooded portions of Jackson, Mississippi and temporarily closed the city’s water treatment plant, leaving most citizens without access to safe drinking and potable water for more than a month. This event punctuated an ongoing water crisis that had lingered for decades in this predominately African American city. We employ a social production of disaster approach to reveal aspects of slow violence perpetrated against disadvantaged peoples that increased their collective vulnerability to flood risks and limited their access to safe water. Using survey data collected one year after the flood, we examine event-related psychosocial stress as measured by the Impact of Event Scale and associated risk factors related to Conservation of Resources Theory. Multivariate analysis indicates that resource losses from the flood, health concerns about water quality, and trust in government were significantly related to elevated levels of psychosocial stress. Although the 2022 Pearl River flood can be treated as a discrete event, a social production of disaster perspective situates the flood in terms of its cascading effects and cumulative impacts on the city’s water infrastructure and citizens who depend on it. Full article

Social resilience has become a central concept in urban and sustainability research, yet its institutional and spatial determinants remain insufficiently specified in contexts marked by persistent urban–rural asymmetries. The objective of this article is to explain how spatial differences in institutional trust shape divergent resilience trajectories across territories in Central and Eastern Europe. This study develops a conceptual, mechanism-based framework and employs a qualitative comparative illustration based on institutional indicators of trust, service accessibility, and governance effectiveness. The analysis shows that territorialized institutional trust—structured by institutional presence, procedural consistency, and institutional legibility—systematically conditions access to resources, stabilizes expectations, and shapes adaptive behavior, with dense and predictable institutional environments supporting longer-term resilience while thin and uneven ones entrench short-term coping. The findings suggest that social resilience should be understood as an institutional outcome shaped by the spatial organization of governance rather than as a territorially neutral attribute of communities. The broader significance of the study lies in providing a territorially sensitive and institutionally grounded framework for urban sustainability and resilience planning, highlighting how built environment and governance arrangements jointly structure the adaptive capacities of urban and rural territories. Full article

With the rapid integration of distributed energy resources, achieving a balance between economic efficiency and environmental sustainability in multi-microgrid (MMG) systems is critical. However, existing studies typically treat microgrid operators as fully compliant entities. They often neglect the “trust-risk” dimension along with potential default behaviors in decentralized markets. This paper proposes a novel co-optimized scheduling model for urban MMG systems, centered on a unified “Social–Economic–Physical” coupling framework. To ensure transaction integrity, a robust reputation evaluation framework is developed using Root Mean Square Error (RMSE), mean absolute error (MAE), plus Dynamic Time Warping (DTW). This framework effectively identifies fraudulent data or contractual breaches. Furthermore, to enhance fairness while promoting decarbonization, the model integrates a dynamic network pricing strategy based on the Shapley value. It works alongside a reputation-weighted reward–penalty step-type carbon trading scheme. The proposed model is formulated as a mixed-integer linear programming (MILP) problem and solved using MATLAB R2025b with CPLEX 12.10. Simulation results demonstrate that the integrated approach significantly optimizes system performance. Total carbon emissions are reduced by 49.6 tons. Meanwhile, revenues for the MMG Alliance, individual microgrids, and shared energy storage operators increase by 4.08% to 33.00%. The proposed framework provides a practical governance solution for Smart City multi-microgrid systems, effectively addressing the “trust-risk” challenge in decentralized urban energy markets. The findings validate that the proposed mechanism effectively fosters a trustworthy trading environment, achieving a “win-win” outcome for economic profitability and urban energy resilience. Full article

The phase-out of carbon-intensive power generation systems has posed a multifaceted governance challenge for carbon-reliant regions in Europe. Despite highlighting the significance of fair and inclusive distribution and decision-making within the framework of the Just Transition Development Plan, empirical evidence is rather limited as regards the affected workers’ evaluative perceptions of the relevant transition management in impacted regions. The present research investigates the determinants shaping workers’ perceptions of Just Transition management in Western Macedonia, a major post-lignite region in Greece. Using original survey data collected from 189 workers, the analysis develops four composite indices, which capture perceptions of institutional readiness, expectations about economic transition outcomes, views on environmental and health implications, as well as levels of awareness, participation, and trust in the Just Transition Development Plan (SDAM, in Greek). The analysis employs a baseline cross-sectional Ordinary Least Squares (OLS) regression, combined with an interaction model designed to assess whether the impact of participatory governance varies with economic expectations. The results demonstrate that awareness, participation, and perceived credibility of the transition plan have a strong and statistically significant positive impact on workers’ perceptions of transition management, whereas institutional readiness, workers’ perceptions of broader regional economic prospects during the transition, and environmental or health implications do not significantly contribute to shaping respondents’ evaluations. The research provides micro-level empirical evidence, based on individual workers’ perceptions, while the economic expectations captured refer to broader regional economic trajectories during the transition. From a sustainability perspective, the findings suggest that workers’ evaluations of transition management are more strongly associated with participatory governance, transparency, and stakeholder engagement than with the specific regional economic expectations captured in the survey. Consequently, sustainable transition management must encompass not only environmental objectives but also inclusive and credible governance processes that foster social acceptance and regional resilience. Full article

In the current context of ESG practices, sustainability reporting becomes very important in strengthening consumer perception about a company’s ESG performance. This study has employed the P-ESG scale to investigate how consumers relate to companies in the oil and gas industry in relation to their corporate social responsibility and sustainability activities. Specifically, this study investigates how consumers perceive the impact of ESG-related communication—particularly disclosures about community involvement—on organizational attributes such as corporate culture, internal communication, and employee engagement. Online quantitative marketing research was carried out on a sample of 400 respondents. The results show that ESG factors have a strong association with consumer perceptions on organizational transparency, effective communication and organizational culture. A negative direct relationship of ESG with the consumer perceptions regarding employee engagement is noticed, and a strong correlation between consumer perceived organizational culture and the consumer perception about employee engagement. This study contributes to defining the role of ESG reporting on the consumers perception about the company, and how ESG can be used to increase consumer trust. Full article

The institutional drive to deploy digital assistive technologies—from IoT monitoring to AI companions—as a solution to the aging care crisis functions as an ethical double-edged sword. This article argues that beyond isolated risks, these technologies introduce a systemic tension where gains in safety and efficiency often come at the cost of autonomy, human connection, and equity. We propose a critical framework that diagnoses four interconnected dimensions of this tension: (1) the erosion of privacy and autonomy through pervasive surveillance; (2) the risk of dehumanization in high-tech, low-touch interactions; (3) the “digital grey divide” as a social determinant of health; and (4) the perpetuation of “coded ageism” through algorithmic bias. To bridge the gap between ethical principle and practice, the framework translates this diagnosis into a practical roadmap for “Dignity-by-Design.” It operationalizes person-centered care through three actionable shifts: moving from compliance to commitment, replacing static consent with dynamic engagement, and establishing the lived experience of older adults and caregivers as a core design standard via participatory action research. Ultimately, this work provides a critical tool for researchers, developers, and policymakers to guide the ethically aligned implementation of technologies that truly enhance autonomy, foster trust, and uphold dignity in geriatric care. Full article

Electronic word of mouth (eWOM) and traditional word of mouth (WOM-T) are key information channels in consumer decisions, but there are still gaps in integrative models that analyze both channels simultaneously in emerging contexts. This exploratory, theory-informed study proposes a conceptual model that articulates five antecedents—satisfaction, trust, emotional bond, openness to novelty, and perceived social influence—two mediators—consumer engagement and recommendation intention—and two outcome behaviors—eWOM and traditional WOM—to examine how these variables are associated with the generation of recommendations among young/internet-connected consumers of SME services in the Lambayeque Region, Peru. Using PLS-SEM with 380 participants, 25 structural hypotheses were evaluated, including direct effects and simple and sequential mediations. In this non-probability sample, the hypothesized associations were statistically supported: antecedents were positively associated with engagement, which was positively associated with recommendation intention, which in turn predicted both online and offline WOM behaviors. Emotional bond and trust showed particularly strong effects. The model explained between 49% and 64% of the variance in endogenous variables. The findings contribute to understanding word-of-mouth dynamics in emerging markets for the studied segment of digitally connected consumers, with implications for relational marketing strategies and SDGs 8 and 12. Importantly, the contribution to SDG 12 is conditional: word-of-mouth can also amplify unsustainable consumption when recommendations are not linked to responsible practices; this caveat should be considered when interpreting the sustainability implications of these findings. Full article

Climate change poses a significant threat to the livelihoods of smallholder farmers in South Africa, particularly in rural areas where dependence on rain-fed agriculture and limited institutional support heighten vulnerability. This study investigates how different forms of social capital (bonding, bridging, and linking) influence climate change adaptation strategies among smallholder farmers in Bergville, KwaZulu-Natal. A mixed-methods design was employed, combining a household survey (n = 150), focus group discussions, and key informant interviews. Households engaged in smallholder farming were purposively identified and randomly selected within the study ward. To accommodate varying literacy levels, structured questionnaires were administered through interviewer-led surveys. Quantitative data were analysed using descriptive statistics, chi-square tests, and a probit regression model, while qualitative data were thematically analysed to contextualise adaptation decisions and social dynamics. The findings show that trust in peer information, farmer group membership, collective action, and access to extension services significantly increase the likelihood of adopting climate adaptation practices (p < 0.05). While bonding social capital supports short-term coping, limited bridging and linking social capital constrain access to institutional resources and climate information. By explicitly operationalising and empirically distinguishing these dimensions of social capital, the study provides context-specific evidence on how uneven social networks shape adaptation outcomes. Strengthening inclusive institutional linkages and extension services is essential for promoting long-term climate resilience among smallholder farmers in rural South Africa. This study contributes to the international literature by providing empirical evidence on the differentiated roles of social capital dimensions in shaping adaptation outcomes in resource-constrained rural contexts. The findings highlight the need for policy interventions that strengthen institutional linkages, improve extension service delivery, and promote inclusive access to adaptation resources to enhance long-term climate resilience. Full article

Logistics platforms (LPs) increasingly use multidimensional data to provide supply chain financing (SCF) to small and micro logistics enterprises (SMLEs). However, platform-centered data control can weaken financial institutions’ (FIs’) trust in platform data, thereby reducing the effectiveness of data-driven credit enhancement. To address this issue, this study integrates the social–ecological systems framework with evolutionary game theory and develops a tripartite evolutionary game involving FIs, LPs, and SMLEs. By comparing scenarios with and without regulatory governance, the study examines how regulatory governance affects the strategic evolution of data-driven credit enhancement in SCF for SMLEs. The results show that regulatory governance improves system performance through cost reduction, trust enhancement, and incentive alignment, thereby relaxing the conditions required for the system to evolve toward the Pareto-optimal state of credit granting, strict supervision, and non-default. The strategic choices of the three actors are mainly influenced by data acquisition costs, incentive intensity, and penalties. Numerical simulations further show that government incentives must exceed certain thresholds to promote cooperation, while penalty mechanisms play a critical role in constraining opportunistic behavior and accelerating convergence to the desirable equilibrium. These findings provide theoretical support and practical insights for improving data-driven credit enhancement in SCF for SMLEs. Full article

Gender-based and sexual violence are major public health concerns, and norms about consent are central to their prevention. This study examines how attitudes toward sexual consent relate to digital sexual consent and to the occasional feeling of distrust in public consent campaigns and institutions. We conducted a cross-sectional online survey embedded in the evaluation of a municipal consent campaign in Zaragoza (Spain). Adults (N = 404; 56.7% women) completed a 14-item short version of the Sexual Consent Scale–Revised, two items on digital sexual consent, and three items on institutional reluctance (perceived “sermonizing” tone, distrust in effectiveness, and lack of personal identification with the message). Correlation and multiple regression models with robust standard errors were estimated, controlling for gender, age, education, income, relationship status, and social media use. Attitudes toward sexual consent were strongly and positively associated with digital sexual consent. Gender was the most consistent sociodemographic correlate: men showed less egalitarian attitudes than women across all consent measurements. Institutional reluctance was systematically related to less supportive consent attitudes: perceiving institutional messages as exaggerated or personally irrelevant predicted lower support for sexual and digital consent norms, whereas trust in the campaign’s effectiveness was associated with more egalitarian attitudes. The findings support the continuity between sexual and digital consent and highlight gender and institutional trust as key determinants for the prevention of gender-based and sexual violence. Public health and social policies should integrate digital consent into consent education and co-design campaigns that minimize defensive reactions and rebuild trust in institutions. Full article