Jing Liu

Purpose: Artificial intelligence (AI)-assisted tools have become widely used to improve reading efficiency. This study aims to systematically investigate how AIGC-generated summaries modulate cognitive load and reading performance across varying levels of text difficulty, conceptualizing such summaries as digital nudges grounded in cognitive load theory and nudge theory. Design/methodology/approach: This study used a 2 × 2 within-subjects design in which participants completed reading comprehension tasks under four conditions: easy versus difficult texts and the presence versus absence of AIGC-generated summaries. During the tasks, electroencephalography (EEG) signals, behavioral measures and questionnaire data were simultaneously collected. Findings: Findings revealed that AIGC-generated summaries reduced theta/alpha ratio (TAR), shortened reading time, improved comprehension accuracy and alleviated subjective cognitive load across both levels of text difficulty. Interaction analyses further demonstrated that these load-reducing effects were more pronounced under high-difficulty conditions. Originality/value: To the best of the authors’ knowledge, this study provides the first neurophysiological evidence for the cognitive benefits of AIGC-generated summaries in alleviating cognitive load during reading, thereby addressing limitations in prior behavior-based research. The findings not only offer practical guidance for the design of AI-assisted intelligent reading systems but also provide empirical evidence to support personalized summary delivery in libraries and digital reading platforms.

This study focuses on UTAUT and integrates the D&M, SDT, and SET models to explore the factors influencing continuous usage intention in the context of gamified online public welfare. By applying structural equation modeling and fuzzy-set qualitative comparative analysis to 389 valid survey samples, this study identifies that public value, leisure and entertainment, and self-payment significantly influence users’ continuous usage intention. Furthermore, game design and tool convenience, along with subjective norms, are key drivers of these three factors. In contrast, gaming convenience and social factors have limited impact on user engagement. The findings reveal three enhancing configurations—functionality-driven, comprehensive support, and pure public value paths—and four inhibiting configurations—complete disengagement, social impact without incentives, convenience without enjoyment, and engagement without enjoyment paths. The crucial role of subjective norms is found to be consistently significant in both the SEM and fsQCA results, making it a key factor in promoting user engagement in gamified public welfare activities. This research contributes to the theoretical understanding of user participation in game-based charity activities and provides insights for improving user retention. Its originality lies in the integration of SDT and SET models alongside D&M and UTAUT, as well as the use of mixed methodologies to examine the multifaceted drivers of continuous usage intention.

Background: With the rapid advancement of artificial intelligence technologies, AI-generated content (AIGC) was increasingly applied in the health information sector, becoming a vital tool to enhance the efficiency and quality of health information exchange.Purpose: This research investigated the motivations behind users’ adoption with AIGC during health information searches, aiming to advance public health management and technological innovation in health information.Methods: The study employed a model constructed from the UTAUT and the Health Belief Model. Comprehensive analysis of survey data was conducted using Structural Equation Modeling (SEM) and Fuzzy-Set Qualitative Comparative Analysis (fsQCA). Data handling and model verification were performed using SPSS 27, SmartPLS 4, and fsQCA 4.1 software tools.Results: The SEM results reveal that performance expectancy, effort expectancy, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and self-efficacy significantly positively influence adoption intentions, while facilitating conditions showed no significant effect. Fuzzy-Set Qualitative Comparative Analysis identifies two pathways that trigger adoption intention: Comprehensive Support and Health-Dominated.Conclusion: The study integrates the UTAUT and HBM in the context of health information technology adoption intention and employs a hybrid approach to deepen understanding of user behavior in the health information environment. Further exploration of emerging theories suitable for the rapidly evolving field of health information technology is still needed.

This study examines the potential heterogeneous effects of domestic value chains (DVCs) on two different paths of export expansion, namely the intensive margin and the extensive margin. Using panel data of 195 prefecture-level cities in China spanning from 2000 to 2013, this paper explores the association between DVCs and export binary margin. The results indicate that DVCs exhibit a significant positive U-shaped relationship with the export intensive margin, while it has a linear positive effect on the export extensive margin. Additionally, market integration and market competition emerge as important mechanisms through which DVCs influence the city’s export binary margin. In addition, the study suggests that central and western regions' integration into DVCs more strongly promotes local export expansion compared to eastern regions. Overall, the empirical evidence presented in this paper contributes to enhancing the understanding of the development pattern of DVCs in China from the perspective of trade competitiveness.

Background: Short videos play a key role in the process of tourism destination promotion, and attractive short videos can bring tourist flow and economic income growth to tourist attractions. Many tourist attractions in China have achieved remarkable success through short video promotion.Purpose: The purpose of this study was to investigate the behavioral characteristics of short video users browsing short tourism videos and explore what factors of short video affected users’ tourism intention. This study also compared which factors were most important in triggering users’ tourism intention in marketing communication via short tourism videos in order to shed light on tourism destination strategy and facilitate adaptation to market development trends.Methods: This study developed a conceptual model by extending the stimulus-organism-response (SOR) model with technology acceptance factors (perceived usefulness, perceived ease of use) and short video factors (perceived enjoyment, perceived professionalism, perceived interactivity) to examine users’ tourism intention. A convenience random sampling technique was used to distribute the questionnaire in Chinese city of Nanjing. Four hundred twenty-one respondents participated in the questionnaire, with 395 providing valid data.Results: The results of the SEM analysis show that all posed hypotheses (Perceived professionalism - > Telepresence, Perceived interactivity - > Telepresence, Perceived enjoyment - > Telepresence, Perceived ease of use - > Telepresence, Perceived enjoyment - > Flow experience, Perceived ease of use - > Flow experience, Telepresence - > Flow experience, Telepresence - > Tourism intention, Flow experience - > Tourism intention) are confirmed except for (Perceived usefulness - > Tourism intention), which is not confirmed.Conclusion: The findings of this study will help fill the gap in previous research on the relationship between short video influencing factors and users’ tourism intention, thus contributing to the academic research on emerging short videos and the endorsement of destinations promoted by technological innovation.

Background: Affected by the COVID-19, many colleges have adopted online teaching. Meanwhile, the digital transformation of academic journals has shifted readers’ reading habits from traditional paper media to digital media. Digital academic reading has become the main reading method of college students during the COVID-19 pandemic.Purpose: The purpose of this study was to investigate the behavioral characteristics of college students’ digital academic reading and explore the internal factors and external environmental factors affecting the Intention and Use behavior of digital academic reading. At the same time this study provide recommendations to address these influencing factors in terms of the individual, the environment and library resources.Methods: Based on UTAUT2 model and digital academic reading theories, this paper constructs a digital academic reading information behavior (DARB) model of college students to examine college students’ digital academic reading behavior and intention. College students with digital academic reading behavior were recruited as research participants. A multi-stage sampling technique was used to collect representative samples from universities in Nanjing. 239 respondents participated in the questionnaire, with 189 providing valid data. Results: Effort expectancy (EE), social influence (SI), price value (PV), perceived risk (PR) and habit (BH) have a significant impact on behavioral intention (BI), and behavioral intention (BI) and habit (BH) have a significant impact on use behavior (B). However, performance expectancy (PE) and facilitating conditions (FC) have no significant influence on behavioral intention (BI).Originality/value: The findings of this study will help fill the gap in previous research on the relationship between the influencing factors of digital academic reading and college students’ reading intentions and behaviors, so as to provide a basis for improving the academic reading literacy program in colleges and optimizing the current digital academic reading environment.

The purpose of this paper is to summarize the research hotspots and frontiers in the field of public health emergencies (PHE) between 1994–2020 through the scientometric analysis method. In total, 2247 literature works retrieved from the Web of Science core database were analyzed by CiteSpace software, and the results were displayed in knowledge mapping. The overall characteristics analysis showed that the number of publications and authors in the field of PHE kept an upward trend during the past decades, and the United States was in the leading position, followed by China and England. Switzerland has the highest central value and plays an important intermediary role in promoting the integration and exchange of international PHE research achievements. The keyword co-occurrence analysis indicated that COVID-19 was the most high-frequency keyword in this field, and there had been no new keywords for a long time until the outbreak of COVID-19 in 2019. The burst detection analysis showed that the top five burst keywords in terms of burst intensity were zika virus, Ebola, United States, emergency preparedness and microcephaly. The results indicated that the research theme of PHE is closely related to the major infectious diseases in a specific period. It will continue to develop with more attention paid to public health. The conclusions can provide help and reference for the PHE potential researchers.

Many scholars have conducted extensive research on the adoption behavior of mobile readers, and there are obvious differences in the degree and direction of conclusions drawn from different individual studies. In this study, a meta-analysis method was used to comprehensively analyze a total of 74,964 independent samples of 31 relevant empirical research documents at home and abroad. The results show that the main influencing factors of mobile reading are perceived usefulness, perceived ease of use, perceived mobility, perceived entertainment, social influence, cognitive adjustment, perceived value, usage attitude, interface design, etc. Cognitive adjustment and usage attitude have the greatest impact on intention to use, followed by perceived usefulness, perceived mobility, subjective norms, perceived ease of use; perceived ease of use has a significant positive impact on perceived usefulness; interface design has a significant positive effect on perceived ease of use; behavioral intention has a significant positive effect on actual behavior; and perceived usefulness and perceived ease of use have a significant positive effect on usage attitude.

The long-term development of mobile banking (m-banking) relies on users’ continued usage. Motivated by the need to better understand the motivations and barriers of users’ continuance intention towards m-banking, this study develops a research model based on the incorporation of the technology acceptance model (TAM): task-technology fit model (TTF) and perceived risk into the expectance-confirmation model (ECM). Empirical data from 434 users who had prior experience with m-banking were tested against the proposed research model by using structural equation modeling (SEM). The results indicate that satisfaction, perceived usefulness, perceived task-technology fit, and perceived risk are the main predictors of continuance intention, satisfaction, in turn, is determined by confirmation, perceived usefulness, and perceived risk. Perceived usefulness is affected by confirmation, perceived ease of use, and perceived task-technology fit. However, the direct effect of perceived ease of use to continuance intention is not significant. The results also show that gender significantly moderates the effect of perceived risk to continuance intention. Implications of the findings and future research directions are discussed.