Ziyang Liu

This study examines user responses to an AI travel assistant in a cross-border tourism service system. Moving beyond adoption-centered technology acceptance research, it conceptualizes these responses as a staged appraisal process in which social and experiential cues shape performance expectancy and effort expectancy, which then influence attitude and two behavioral outcomes: users’ willingness to accept AI and objections to AI. Cosmopolitanism is introduced as an individual-level boundary condition. Survey data were collected from 499 Chinese tourists holding valid South Korean tourist visas after they evaluated Visit Seoul AI, an official AI-based travel-planning tool. The hypotheses were tested using partial least squares structural equation modeling. The results show that social influence, hedonic motivation, and perceived anthropomorphism significantly affect performance expectancy and effort expectancy, which in turn shape attitude. Attitude increases usersf’ willingness to accept AI and reduces objections to AI, with a stronger effect on users’ willingness to accept AI. Cosmopolitanism strengthens the negative effect of hedonic motivation on effort expectancy. This study extends AIDUA to cross-border AI service systems and shows that users may both accept and object to AI travel assistants.

Fear of Missing Out (FoMO) has become a salient emotion in consumer markets shaped by social media, scarcity appeals, and social display. Yet limited research has examined FoMO as a consumption-specific emotion associated with consumer dispositions, situational cues, and post-purchase intentions. Drawing on Social Comparison Theory, Self-Determination Theory, and the Stimulus–Organism–Response (S-O-R) framework, this study examines the relationships among Materialism, Envy, Scarcity, FoMO, Impulsive Buying (IB), and Repurchase Intention (RI). Survey data from 518 Chinese consumers with prior Pop Mart purchasing experience were analyzed using PLS-SEM. The results show that Materialism, Envy, and Scarcity were positively associated with FoMO, with Scarcity showing the strongest relationship. FoMO was positively associated with IB, and IB was positively associated with RI. The results also supported three serial mediation paths, indicating that FoMO and IB served as sequential mediators between Materialism, Envy, Scarcity, and RI. This study extends FoMO research to cultural and creative product consumption and provides insight into how consumption-related emotions are associated with sustained purchase tendencies.

Purpose: With the rapid development of artificial intelligence, virtual influencers (VIs) have attracted increasing attention as emerging brand endorsers, yet how their multidimensional anthropomorphism shapes brand image remains underexplored. Grounded in Mind Perception Theory and Social Identity Theory, this study examines how virtual influencers' multidimensional anthropomorphism influences brand image through trustworthiness and parasocial interaction, while considering the moderating role of autonomy. Design/methodology/approach: This study surveyed 411 participants who had experience following virtual influencers, and analyzed the proposed relationships using partial least squares structural equation modeling (PLS-SEM) and importance–performance map analysis (IPMA). Findings: Positive anthropomorphism of VIs increases trustworthiness, whereas negative anthropomorphism decreases trustworthiness. Trustworthiness further enhances brand image through parasocial interaction. Autonomy strengthens the positive effect of attractiveness on trustworthiness and amplifies the negative effect of eeriness on trustworthiness, but does not moderate the effect of humanness. Originality/value: This study extends the three-dimensional anthropomorphism framework to the context of VI endorsement, revealing the mechanism through which anthropomorphism shapes brand image by trustworthiness and parasocial interaction, and further clarifying the moderation of autonomy in this process, deepening the understanding of brand image construction by VIs in brand marketing.

In the era of sustainable digital transformation, organizations increasingly rely on artificial intelligence (AI) to enhance efficiency, innovation, and long-term competitiveness. However, employees’ psychological barriers, including technostress and innovation resistance, continue to constrain successful and sustainable AI adoption. Grounded in Social Exchange Theory (SET), Conservation of Resources Theory (COR), Diffusion of Innovation Theory (DOI), and the Technology Acceptance Model (TAM), this study develops an integrated model linking perceived organizational support (POS)—comprising emotional, informational, and instrumental dimensions—to employees’ sustainable AI adoption through the dual mediating roles of technostress and innovation resistance. Based on 426 valid responses collected from multiple industries, a triadic hybrid approach combining Structural Equation Modeling (SEM), Artificial Neural Networks (ANNs), and Necessary Condition Analysis (NCA) was applied to capture both linear and nonlinear mechanisms. The results reveal that Informational Support (IFS) is the most influential factor and constitutes the sole necessary condition for high-level AI adoption, while emotional and instrumental support indirectly promote sustainable adoption by mitigating employees’ stress and resistance. This study contributes to sustainable management and AI adoption research by providing insights into the potential hierarchical and threshold patterns of organizational support systems in digital transformation. It also provides managerial implications for designing transparent, empathetic, and resource-efficient support ecosystems that foster employee-driven intelligent transformation.

In the context of China’s sustainable development goals, this study investigates how market-based environmental regulation, specifically SO₂ emission trading, drives green transformation and upgrading in manufacturing firms. We argue that emission trading can spur firms to optimize their service portfolios and improve their embedded services, thus facilitating a shift toward greener operations—while its effect on a firm’s technological innovation capacity remains ambiguous. Using panel data from Chinese manufacturing firms, our empirical findings show that emission trading significantly promotes service transformation through optimizing embedded services and reducing mixed, noncore services but does not necessarily encourage increased R&D investment or breakthrough innovation. This suggests many enterprises prefer end-of-pipe pollution control measures rather than structural technological upgrading under regulatory pressure. Our results provide insights into refining emission trading mechanisms and designing supportive policies to better channel firm-level transformation toward sustainability.

The authors would like to make the following corrections about the published paper

With the rising urgency of global environmental challenges, understanding the mechanisms behind green consumption has become increasingly vital. This study investigates how green product information disclosure influences consumers’ green consumption intention, focusing on new energy vehicle (NEV) consumers in China. Grounded in the Theory of Planned Behavior (TPB), the study introduces environmental concern as a mediator and brand reputation as a moderator to enhance the explanatory power of the model. A total of 527 valid questionnaires were collected on-site from NEV exhibitions in Beijing. Structural equation modeling and PROCESS macro analysis were employed to test the research hypotheses. The results indicate that environmental information disclosure significantly promotes green consumption intention, both directly and indirectly, through the mediating effects of green consumption attitude, subjective norms, and environmental concern. However, the direct effect of information communication channels was not statistically significant. Moreover, brand reputation positively moderates the relationship between environmental information disclosure and green consumption intention. These findings provide new theoretical insights by extending TPB with contextual and psychological variables and offer practical implications for NEV manufacturers and marketers. Specifically, companies are encouraged to prioritize transparent and credible environmental information disclosure, strengthen brand reputation, and consider consumers’ attitudes and social norms when designing green marketing strategies.

The integration of artificial intelligence (AI), big data analytics, and blockchain technologies within the digital economy presents transformative opportunities for promoting low-carbon urban development. However, a systematic understanding of how these digital innovations influence urban carbon mitigation remains limited. This study addresses this gap by proposing two research questions (RQs): (1) What are the key success factors for artificial intelligence, big data, and blockchain in urban carbon emission reduction? (2) How do these technologies interact and support the transition to low-carbon cities? To answer these questions, the study employs a hybrid methodological framework combining the decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) techniques. The data were collected through structured expert questionnaires, enabling the identification and hierarchical analysis of twelve critical success factors (CSFs). Grounded in sustainability transitions theory and institutional theory, the CSFs are categorized into three dimensions: (1) digital infrastructure and technological applications; (2) digital transformation of industry and economy; (3) sustainable urban governance. The results reveal that e-commerce and sustainable logistics, the adoption of the circular economy, and cross-sector collaboration are the most influential drivers of digital-enabled decarbonization, while foundational elements such as smart energy systems and digital infrastructure act as key enablers. The DEMATEL-ISM approach facilitates a system-level understanding of the causal relationships and strategic priorities among the CSFs, offering actionable insights for urban planners, policymakers, and stakeholders committed to sustainable digital transformation and carbon neutrality.

Based on the Theory of Planned Behavior, this study explores the impact mechanism of green product information disclosure on consumers' green consumption intention, focusing on new energy vehicle consumers. Through the analysis of 527 valid questionnaires collected from new energy vehicle exhibitions in Beijing, it was found that environmental information disclosure has a significant positive impact on green consumption intention, while the direct influence of information communication channels is not significant. The study further reveals the mediating roles of green consumption attitude, subjective norms, and environmental concern between environmental information disclosure and green consumption intention, indicating that personal attitudes, social pressure, and environmental awareness are key factors influencing green consumption decisions. These findings not only enrich the theoretical research on green consumption behavior but also provide practical guidance for companies in formulating green marketing strategies. The study suggests that companies should focus on building a strong ecological brand reputation, adopt a multidimensional information dissemination strategy, and fully consider factors such as consumers' environmental concern, perception of social norms, and personal attitudes when conveying green product information, thereby more effectively promoting the development of green consumption.

With the rise of virtual idols in marketing, especially in collectivist cultures, their impact on consumer behavior warrants further exploration. This study applies social identity theory, flow theory, and the SOR model to examine how collectivism and virtual idol characteristics (external characteristics, content features, and homophily) influence Chinese consumers’ purchase intentions through parasocial interaction (PSI) and flow experience. A survey of 496 respondents, analyzed via structural equation modeling (SEM), shows that collectivism and virtual idol characteristics positively affect PSI, with homophily having the strongest impact. PSI enhances flow experience, and both PSI and flow experience drive purchase intention. PSI and flow experience serve as dual mediators in the model. This study advances research by empirically validating collectivism’s role in PSI, differentiating virtual idol characteristics, and modeling dual mediation. The key contributions of this study are as follows: (1) treating culture as an independent variable to empirically examine its impact on psychological mechanisms, and (2) deconstructing virtual idol characteristics into three dimensions—external, content, and homophily—to reveal their distinct influence on consumer psychology. Findings offer strategic insights for brands, recommending a dual-track approach integrating cultural adaptation and feature design to enhance consumer engagement and purchasing behavior.