Search Results (860)

Although service firms recognize the significance of frontline employees’ emotional labor in enhancing perceived service quality and sustaining competitive advantage, the theoretical mechanisms underlying this relationship remain insufficiently understood. Drawing on the Emotions as Social Information Model (EASI), this study proposed that frontline employees’ emotional labor influences customer perceived service quality through two distinct pathways: emotional contagion and inferential processing. Moreover, the relative strength of these two pathways is contingent upon customer involvement. Using dyadic data collected from frontline employees and customers in the banking sector, the results indicated the following: frontline employees’ different emotional labor strategies (deep acting and surface acting) exerted significant influence on perceived service quality through different pathways. Specifically, surface acting impacted service quality solely through emotional contagion process (via customers’ positive affect). Whereas deep acting influenced service quality through both emotional contagion (via customers’ positive affect) and inferential processing (via customer participation). Additionally, customer involvement moderated the relationship between deep acting and customer participation (strengthening the positive association), as well as the link between surface acting and customers’ positive affect (attenuating the negative association). Full article

Human behavior is shaped by a pervasive motive to align with others, manifesting across a wide range of tendencies—from motor synchrony and emotional contagion to convergence in beliefs and choices. Existing accounts explain how alignment arises through predictive coding and observation–execution mechanisms, but they do not address how it is regulated in a manner that considers when alignment is adaptive and with whom it should occur. We propose a goal-directed model of social alignment that integrates computational and neural levels of analysis, to enhance our understanding of alignment as a context-sensitive decision process rather than a reflexive social tendency. Computationally, alignment is formalized as a prediction-error minimization process over the gap between self and other, augmented by a meta-learning layer in which the learning rate is adaptively tuned according to the inferred value of aligning versus maintaining independence. Assessments of the traits and mental states of self and other serve as key inputs to this regulatory function. Neurally, higher-order representations of these inputs are carried by the mentalizing network (dmPFC, TPJ), which exerts top-down control through the executive control network (dlPFC, rIFG) to enhance or inhibit alignment tendencies generated by observation–execution (mirror) circuitry. By reframing alignment as a form of social decision-making under uncertainty, the model specifies both the computations and neural circuits that integrate contextual cues to arbitrate when and with whom to align. It yields testable predictions across developmental, comparative, cognitive, and neurophysiological domains, and provides a unified framework for understanding the adaptive functions of social alignment, such as strategic social learning, as well as its maladaptive outcomes, including groupthink and false information cascades. Full article

The urgent need to mitigate climate change has elevated green hydrogen as a sustainable alternative to fossil fuels, while green cryptocurrencies have emerged to address the environmental concerns of traditional cryptocurrency mining. This study investigates the dynamic correlation between the green hydrogen market and selected green cryptocurrencies (Cardano, Stellar, Hedera, Algorand, and Chia) from July 2021 to April 2024, utilizing the Dynamic Conditional Correlation GARCH (DCC-GARCH) model with robustness checks using EGARCH and GJR-GARCH specifications. Our findings reveal significant correlations, with peaks reaching up to 50% in 2022, a period likely influenced by the Russia-Ukraine conflict. Subsequently, a decline in these correlations was observed in 2023. These results underscore the interconnectedness of sustainability-driven markets, suggesting potential contagion effects during periods of global instability. The high persistence of correlation shocks (α + β values approaching unity) indicates that correlation regimes tend to be long- lasting, with important implications for portfolio diversification and risk management strategies. Robustness checks using EGARCH and GJR-GARCH specifications confirmed qualitatively similar patterns, reinforcing the validity of our findings into the evolving landscape of green finance and energy. Full article

This paper investigates how global uncertainty and macro-financial shocks transmitted to BRICS+ equity markets between April 2016 and July 2025. A vector autoregressive (VAR) framework, complemented by Granger-causality tests, variance decompositions, and impulse response functions, is employed to examine four key drivers: U.S. financial market volatility (VIX), geopolitical risk (GPRD), U.S. inflation expectations (T5YIE), and the U.S. term spread (T10Y3M). The findings show that the VIX functions both as a recipient and a transmitter of shocks, amplifying volatility across BRICS+ markets, with India, Brazil, and the Gulf states acting as important nodes in the global contagion network. By contrast, geopolitical risk shocks have only short-lived effects on both U.S. yields and emerging equity markets. Shocks to U.S. inflation expectations and yield-curve dynamics transmit quickly to BRICS+ markets but dissipate within a few days, underscoring efficient market adjustment. Overall, the evidence points to a multipolar structure of global contagion in which BRICS+ markets exert growing influence alongside the United States. These results offer important implications for risk management, portfolio diversification, and policy coordination under heightened uncertainty. Full article

Against the backdrop of policy-driven transformation in construction industrialization, the EPC general contracting model has emerged as a core pathway for the large-scale development of prefabricated buildings. However, the EPC mode integrates the links of design, procurement, production, and transportation, construction, resulting in a complex coupling correlation among the risk factors of prefabricated construction schedule, which is easy to induce the risk contagion effect and increase the difficulty of risk control of project schedule delay. To address this, this study constructs a hybrid model integrating the “Fuzzy Interpretive Structural Model (FISM)-Coupling Degree Model-Bayesian Network (BN)” to systematically analyze risk contagion mechanisms. Taking an EPC prefabricated building project as an example, FISM is used to reveal the hierarchical structure of risk factors, while the coupling degree model quantifies interaction strengths and maps them into the BN to optimize conditional probability parameters. Through comprehensive hazard analysis, seven key causal risk factors and two critical risk propagation paths are identified. Targeted control measures are designed for the key risk factors, and BN-based simulation is applied to locate critical risk nodes and implement break-chain interventions for the risk paths, resulting in a 23% reduction in the probability of schedule delay. Engineering applications demonstrate that this model can effectively achieve the dynamic identification and blocking of risk paths, providing valuable reference for similar projects and offering informed support for managers in formulating scientific response strategies. Full article

The vulnerability of the global financial system to systemic risk-related adverse events has become more evident in recent years, as shown by the 2008 financial crisis and the global pandemic. This study examines systemic risk and its contributing factors using network analysis to understand how contagion occurs. To achieve this, a bibliometric analysis was conducted using a cluster analysis of publications from 2020 to 2025. The bibliometric analysis covered 1642 papers related to systemic risk and financial transmission networks. The CiteSpace software was used to identify seven thematic clusters. The results show the relevance of topological analysis in explaining the connection between institutions and the spread of risk. There is also a clear tradition in the literature of applying the DY spillover index, which captures the temporal dynamics of systemic connectivity. Multilayer networks stand out as a trend in recent studies, as they have the potential to represent different types of relationships simultaneously between nodes. Finally, the literature pays attention to systemic connectivity problems during crises, which can amplify volatility and generate forced asset sales, highlighting the need to use advanced VAR-type models to anticipate risk transmission and guide macroprudential management. Full article

Studies examining emoji applications in digital marketing and advertising are characterized by considerable heterogeneity in their theoretical orientation, methodologies, and contextual factors. A domain-based systematic literature review with the Theory-Context-Characteristics-Methodology (T-C-C-M) framework following PRISMA guidelines was conducted to answer how emojis are researched in marketing, and a bibliometric review was constructed to shed light on important aspects. We found a field growing in volume yet immature, with a diversity of theories and methodologies used to explore the multiple roles of emojis. An analysis of explicit and implicit theories identified that almost a quarter of studies are atheoretical, and the mostly used theories are the Emotions as Social Information Theory (EASI) and the emotional contagion theory. Emojis are mainly researched in social media and in the travel and food industry. The most common methodological categories are experimental designs, with emojis used as independent variables in simple designs. Despite the focus on short-term outcomes (engagement, purchase intention), little attention was given to advertising and to field experiments, constraining ecological validity. Our study reveals the need for a robust theoretical framework that can explain the multiple functions of emojis, and EASI emerged as the leading theory to be tested more extensively. Full article

Multidimensional approaches to understanding the daily lived experiences and well-being among spousal dyads, where one partner has diagnosed mild cognitive impairment (MCI) and the other serves as an informal caregiver, is a relatively unexplored area of research. This study examined contextual day-to-day patterns of spousal dyads’ caregiver burden, depressive affect, stress, relationship mutuality, sleep, and cognition from the perspective of both dyad members. For 14 consecutive nights, 27 dyads (n = 54 individuals) completed online daily diary forms. The forms included self and informant reports about daily caregiver burden, depressive affect, stress, dyadic interactions, memory, and sleep quality. Exploratory multilevel modeling was performed to understand how daily fluctuations among these aspects of everyday living for both dyad members were associated. Mutuality emerged as an important moderator for caregiver burden and depressive affect outcomes, underscoring the significance of the relationship between care recipients with MCI and their caregivers. Sleep debt was also associated with contagion effects among partners’ depressive affect, stress, mutuality, and cognition. The present study demonstrates the value of multifaceted investigations that account for contextually relevant factors using daily repeated measures with both dyad members to better understand the MCI caregiver experience. Larger, more diverse samples are needed for generalizability of findings. Full article

Against the dual backdrop of rapid urban development and the drive to build an ecological civilization, coordinating industrial growth with ecological protection is crucial for the sustainable development of industrial cities. Using Haining—a typical industrial city—as a case study, this paper analyzes land-use and landscape-pattern evolution with five phases of land-use/land-cover data (1980, 1990, 2000, 2010, and 2020) and constructs an ecological security evaluation system. The results indicate that (1) under policy influences, multiple land types in Haining tended to convert into urban–rural residential construction land; (2) over the past forty years, the landscape pattern became more optimized, and ecological security improved, with increased diversity alongside reductions in fragmentation and contagion; and (3) the overall ecological security level rose significantly during the same period. Sustained macro-level policy regulation is needed to maintain long-term ecological security in industrial cities. The study shows that Haining’s ecological security is closely linked to landscape patterns, land-use change, and human disturbance. By tailoring development strategies for different stages, ecological security and sustainable development can be effectively supported, offering guidance for Haining and industrial cities worldwide. Full article

This study examines risk transmission between the United States and China using integrated economic policy uncertainty (EPU) and geopolitical risk (GPR) indices. We employ a dual methodology that combines Vector Autoregressive (VAR) and Granger causality in quantiles tests to analyze interactions during systemic leadership transitions, a dimension that is currently under-explored. Our dataset covers the period from June 2000 to June 2023. Results indicate that China is narrowing the economic influence gap and strengthening its role as a regional anchor. The U.S., however, maintains predominant global leadership. This dynamic reframes bilateral tensions as a “status dilemma” rather than a security conflict. Crucially, we identify asymmetric spillover effects: the U.S. uncertainty shocks spread globally, while China’s volatility remains regional. Our findings contribute to the understanding of financial stability by demonstrating that leadership asymmetries are critical determinants, providing valuable insights for designing systemic risk monitoring tools and contagion mitigation policies during periods of heightened uncertainty. Full article

Background: Tourists returning home and visitors from abroad often carry antimicrobial-resistant (AMR) bacteria. Many of these resistant bacteria are acquired from, or were spread via, the environment (especially water). Understanding the impact from acquiring resistant bacteria via tourism upon global antimicrobial resistance is limited. Methods: Traveller transmission of AMR bacteria can be estimated from combining the numbers of travellers with AMR bacteria rates in different regions and the prevalence of communicable diseases. We used resistance data (WHO and contemporary publications) to measure the prevalence of E.coli resistance to third-generation cephalosporins. The study uses data from 2019, the year with the most complete dataset that also predates disruptions to travel caused by the COVID-19 pandemic. We then used the global burden of disease study and travel data from the World Travel and Tourism to create regional and country level indices measuring the impact of AMR bacteria for 241 countries. Estimates of global travel patterns were obtained using a gravity-style trip distribution model. Findings: Regions with the highest impact of AMR bacteria from returning travellers were Northern Europe and Western Europe. The region with the highest impact of AMR bacteria from visiting travellers was the Caribbean where small island countries receive large numbers of visitors. For countries/administrative regions with populations greater than 5 million, the AMR bacterial travel impacts measured in decreasing risk order from the highest were Hong Kong, Denmark, New Zealand, Hungary, Norway and Sweden. Interpretation: For some countries the incidence of AMR infection among both visitors and returning travellers is much higher than in the domestic population. This impact and how these bacteria are acquired from the environment, must be factored into public health policies for containing global spread of AMR bacteria and as part of a One Health approach. Full article

Background: The COVID-19 pandemic significantly impacted adolescent development, increasing behavioral problems and emotional distress. This study aimed to examine the impact of sensation seeking, empathy, and COVID-19-related stressors on deviant behavior in adolescents. Methods: A cross-sectional study was conducted with 638 Italian adolescents and young adults (M = 18.8 years, SD = 3.51) recruited from schools, universities, and the general population in Tuscany and Emilia-Romagna. Participants completed validated measures assessing sensation seeking, empathy, COVID-19-related stress, and deviant behaviors. Multiple regression analyses examined predictors of deviant behavior, while mediation analyses tested whether empathy mediated the relationship between sensation seeking and deviant behavior. Results: Correlation analyses show a positive association between sensation seeking and deviant behavior and a weaker positive association with COVID-19 isolation. Conversely, affective empathy demonstrated negative correlations with both deviant behavior and sensation seeking. COVID-19 stress demonstrated differentiated effects: social isolation increased deviance, whereas fear of contagion was protective. Mediation analysis revealed that affective empathy partially mediated the relationship between sensation seeking and deviance. Conclusions: This study demonstrates that sensation seeking is a primary risk factor for deviant behavior in adolescents and young adults, while affective empathy acts as a protective mechanism that partially mediates this relationship. Furthermore, COVID-19-related stressors have shown complex effects, with social isolation amplifying the risk of deviance, while fear of contagion promotes more inhibited behavior. These findings underscore the importance of considering both stable personality traits and situational stressors when seeking to understand the pathways leading to adolescent behavioral problems during periods of social crisis. Full article

During the COVID-19 pandemic, migrant workers in Singapore endured one of the longest and most stringent periods of confinement globally. Segregationist policies were intensified as the state imposed strict disciplinary regimes over workers’ mobility and everyday lives, framed as public health interventions but functioning also as labor discipline and social control. This study asks: how did migrant workers experience, narrate, and endure life under such conditions of confinement? Drawing on sixteen in-depth interviews with South Asian male construction workers, conducted in dormitories and makeshift worksites, we adopt a grounded theory approach to elicit contextually grounded accounts of life under lockdown. The analysis highlights three interrelated themes: emotional regulation, migrant masculinity and the gendered politics of endurance, and digital connectivity as an affective infrastructure. These practices enabled workers to carve out agentic spaces within structures designed to render them passive. Our findings reveal that even amid fear, surveillance, overcrowding, and economic precarity, workers combined stoicism, transnational kinship ties, religious routines, and solidarity to sustain resilience. While initially guided by Foucauldian notions of surveillance and biopower, the study advances a counter-Foucauldian insight: that institutional control is never total, and migrant narratives of resilience offer nuanced understandings of agency under constrain. Full article

Controversial events are social incidents that trigger wide discussion and strong emotions, often touching on public interests, moral judgment, or social values. Their diffusion typically involves moral evaluations and affect-laden language. Prior work has mostly examined how the quantity of moral and emotional words shapes diffusion, while largely overlooking blame attribution—that is, whether audiences locate the cause of a controversial event in individual actions or in social structures, across different contexts. Using 189,872 original Weibo posts covering 105 events in three domains— street-level bureaucracy (SLB; individual attribution), education governance (EG; structural attribution), and gender-based violence (GBV; mixed attribution)—we estimate negative binomial models with an interaction between word type and account verification and report incidence rate ratios (IRR). Moral contagion is strongest for SLB (IRR = 1.337) and attenuated for EG (IRR = 1.037). For GBV, moral-emotional language decreases reposts (IRR = 0.844). Unverified accounts amplify the diffusion advantage of moral-emotional wording for both individually and structurally attributed issues, with the largest gains in SLB. When disaggregating by valence and discrete emotions, fear-type moral-emotional words are positively associated with reposts in GBV (IRR = 1.314). Theoretically, we shift the question from whether moral contagion occurs to when it operates, highlighting attribution tendencies and verification status as key moderators. Empirically, we provide cross-issue evidence from large-scale Chinese social media. Methodologically, we offer a replicable workflow that combines length-normalized lexical measures with negative binomial models, including interaction terms. Full article

The global push for electrification and decarbonization has sharply increased demand for critical raw materials—especially lithium and copper—heightening financial and strategic pressures on firms that lead these supply chains. Yet, the systemic financial risks arising from inter-firm interdependencies in this sector remain largely unexplored. This article presents a novel distance-based network framework to analyze systemic risk among the world’s top 15 lithium and copper producers (2020–2024). Firms are represented through standardized vectors of profitability and risk indicators (liquidity–solvency), from which we construct a two-layer similarity network using Euclidean distances. Graph-theoretic tools—including Minimum Spanning Tree, eigenvector centrality, modularity detection, and contagion simulations—reveal the structural properties and transmission pathways of financial shocks. The results show a robust-yet-fragile topology: while stable under minor perturbations, the network is highly vulnerable to failures of central firms. These findings highlight the utility of distance-based network models in uncovering hidden fragilities in critical commodity sectors, offering actionable insights for macroprudential regulators, investors, and corporate risk managers amid growing geopolitical and financial entanglement. Full article