Abstract: [Purpose/Significance] Addressing the issue of "big data price discrimination" in the digital economy, which severely undermines consumer rights and market fairness, this study focuses on two key governance strategies: information transparency and consumer education. It explores their synergistic efficacy in countering this phenomenon to foster a fair digital market with multi-stakeholder participation. [Method/Process] Based on information asymmetry theory, equity theory, and information processing theory, the research had employed two 2×2 scenario-based experiments (food package ordering and hotel booking) to examine the interactive effect of information transparency and consumer education on perceived price discrimination, and had analyzed the mediating effect of perceived price fairness. [Result/Conclusion] The results indicate that the interaction between information transparency and consumer education significantly enhances consumers' perception of price discrimination. While enhancing either strategy individually improves recognition ability, their combined effect yields more pronounced results. Perceived price fairness partially mediates this interactive influence: improvements in information transparency and consumer education enhance consumers' understanding of pricing procedures, thereby increasing their perception of fairness and indirectly mitigating their ultimately negative judgments.

Abstract: [Purpose/Significance] Against the background of the increasingly prominent reproducibility issues in digital humanities research, this paper systematically analyzes the challenges posed by data complexity, methodological heterogeneity, and the multimodal nature of research outputs to research verifiability, and explores the critical role of academic journals in institutional regulation and technical governance. [Method/Process] From the three dimensions of data, methods, and research outputs, the paper examined the dilemmas of reproducibility and, on this basis, introduced an analytical framework of “boundary-keeping, boundary-breaking, and their dynamic balance”. By integrating data publishing, platform-based collaboration, intelligent empowerment, and human-machine collaboration mechanisms, it constructed practical pathways through which journals can enhance reproducibility. [Result/Conclusion] It is argued that journals should achieve transparent and traceable management of the entire research process through standardized data collection and metadata specifications, centralized platform management, intelligent quality control, and human–machine collaborative peer review. The study concludes that academic journals need to maintain a dynamic balance between safeguarding academic norms and promoting publishing innovation, gradually forming an integrated “data–methods–publishing” ecosystem, so as to enhance the credibility, reproducibility, and academic impact of digital humanities research, and to provide institutional support for building an open, transparent, and sustainable scholarly publishing system.

Abstract: [Purpose/Significance] Against the backdrop of the widespread application of Generative Artificial Intelligence (AIGC) and the interdisciplinary convergence of new medical science, this study analyzed medical students' actual needs for library information resource services and put forward targeted suggestions for the innovation of library information resource services. It aimed to provide countermeasures and suggestions for medical university libraries to carry out demand-oriented, AIGC-based optimization and innovation of interdisciplinary medical information resource services. [Method/Process] By designing a questionnaire, this study surveyed and analyzed the demands of 813 medical students for medical information resource services provided by medical university libraries, as well as their practices and competencies in accessing and utilizing medical information resources. [Result/Conclusion] Analysis of the survey results found that in the context of AIGC and the interdisciplinary convergence of modern medical science, medical students across different academic years have increasingly diversified demands for medical information resource services, with an urgent need for integrated interdisciplinary resources and intelligent services. However, existing interdisciplinary information resources in medical university libraries are scattered, and intelligent services are insufficient. Simultaneously, medical students' abilities in accessing and utilizing information resources—including retrieving, reading, and managing them—are relatively weak. Furthermore, while their demand for the application of emerging technologies like AIGC is high, their understanding of these technologies is inadequate. Based on the above needs and problems, this study proposes utilizing AIGC to optimize and innovate interdisciplinary medical information resource services in medical university libraries, and conducting multi-tiered information literacy training and education based on AIGC to enhance the abilities and efficiency of medical students in accessing and utilizing interdisciplinary information resources.

Abstract: [Purpose/Significance] Exploring young people's attitudes towards the digital modeling of traditional culture plays a significant role in the communication of cultural heritage. [Method/Process] Based on CAPS theory, this study had employed methods such as word frequency analysis, topic identification, and sentiment analysis to investigate the young people's attitudes towards the digital modeling of traditional culture, having used the danmaku and comments from videos showcasing traditional culture on Bilibili as the research subjects. The study had collected and cleaned a total of 22,961 danmaku and comment texts from high-play-volume videos related to the construction of traditional Chinese architecture using the sandbox game Minecraft on Bilibili. [Result/Conclusion] Results show that the younger generation maintains a certain level of interest and awareness in traditional architecture and culture, especially regarding the use of new forms like Minecraft to inherit traditional architectural culture; the younger generation appreciates and recognizes the aesthetic and cultural value of traditional architecture and shows a certain interest in the design and creative skills of traditional construction; nearly 60% of the younger generation hold a positive attitude towards using Minecraft to inherit traditional architectural culture, demonstrating a fondness for historical civilization and pride in traditional culture. It is evident that inheriting traditional architectural culture through game formats is feasible, capable of attracting the attention and participation of the younger generation, and providing new ideas for the protection, inheritance, and promotion of traditional architecture.

Abstract: [Purpose/Significance] Technology forecasting is a field of research related to future technology development trends and technological innovation. This paper aims to identify the current research hotspots and frontiers in the field of technology forecasting, to provide guidance for the technological innovation of enterprises and organizations, helping them seize opportunities and avoid risks. [Method/Process] Technology forecasting literature from WoS and CNKI (2001—2024) was analyzed using VOSviewer and CiteSpace to identify literature characteristics, hotspots, and frontiers. [Result/Conclusion] The result shows that: ①The volume of articles published in the field of technology forecasting has grown steadily at domestic and international, and the core journals are distributed in the fields of information science, management and other disciplines. ②A stable core authors group has formed in the field of technology forecasting at home and abroad. In China, collaboration remains predominantly intra-institutional, and there are cross-institutional, with cross-institutional ties often stemming from mentor-apprentice relationships. Internationally, cross-institutional collaboration is more prevalent, frequently facilitated by jointly-trained scholars and visiting academics who serve as bridges for research partnerships. Notably, Chinese scholars have emerged as key contributors to international technology forecasting research. ③Regarding research hotspots, domestic research focuses on the research of emerging and disruptive technologies, technology opportunities, and technology forecasting methods. Foreign countries focus on technology development trend research, emerging technology assessment and forecasting research, technology convergence and technology intelligence research, technology opportunity discovery and analysis research. ④In terms of research frontiers, identification and prediction of disruptive and emerging technologies, research on technology convergence and technological innovation, and optimization of technology opportunity identification and discovery methods are the research frontiers in the field of domestic technology forecasting. The research frontiers in the field of foreign technology forecasting mainly focus on the improvement of technology forecasting methods and the discovery and analysis of technology opportunities.

Abstract: [Purpose/Significance] Addressing issues such as single point of failure, privacy leakage, and insufficient ability of traditional digital resource preservation methods, an integrated model based on blockchain and distributed storage is proposed to solve the core challenges such as easy data tampering, inefficient permission management and a lack of trust in cross-institutional collaboration. [Method/Process] This study designed a hierarchical architecture model that integrates blockchain depositary metadata and IPFS chunked storage files. And smart contracts were utilized to automate processes including resource upload, permission control and data recovery. Data privacy was safeguarded through AES encryption. The model's reliability was rigorously verified based on a hash collision probability calculation (4.26×10^-27) and a quantified disaster tolerance capacity quantification (annual file recoverability rate of 99.99%). [Result/Conclusion] The model significantly outperforms other methods in data immutability, privacy protection (it takes 3.68×10⁵¹ years to crack AES-256) and disaster tolerance capacity. And it is suitable for high-security scenarios such as digital archives and medical data management. The study also proposes strategies such as hierarchical storage, data deduplication and compression to optimize system performance and reduce cost. A modular design reduces development complexity, while the integration of managed services enhances deployment efficiency. This research shows that the collaborative mechanism of blockchain and IPFS provides a reliable path for digital resources preservation. In the future, it is necessary to further balance performance and cost to support large-scale applications.

Abstract: [Purpose/Significance] This study employs the BERTopic model to analyze the core themes, evolutionary pathways, and frontier dynamics of data element valorization in China, providing a macro perspective and objective foundation for advancing theoretical exploration and guiding practical applications. [Method/Process] Having used 1735 articles published in CNKI from 2019 to the present as the dataset, this research had applied the BERTopic topic modeling approach. First, a semantic embedding space had been constructed using a pre-trained language model, and UMAP had been applied for dimensionality reduction, combined with HDBSCAN for density-based clustering, to have initially generated the incorporation of a temporal analysis method to trace the dynamic evolution of research topics. [Result/Conclusion] The findings reveal that: ① Current research themes focus on five key areas: "Enterprise Innovation and Data Element Market Cultivation", "Data Infrastructure Systems and Industrial Digital Transformation", "Element Marketization Allocation and Institutional Reform", "Data Transaction Systems and Market Competition Mechanisms", and "Data Empowerment for Productivity Improvement and Regulatory Balance". ② Data element valorization exhibits multidimensional collaborative characteristics and forms a dynamic evolutionary mechanism.

Abstract: [Purpose/Significance] As AI technologies become deeply embedded in social life, AI literacy has emerged as a fundamental competency for the public in the intelligent era. This study aims to systematically review the progress of empirical research on AI literacy assessment worldwide, providing reference and insights for future studies. [Method/Process] Following the principles of systematic review, this study selected 69 empirical studies on AI literacy assessment as the analytical sample. Through a comprehensive examination of the included literature, descriptive characteristics were summarized, and key elements of AI literacy assessment—including assessment targets, assessment dimensions, development and validation of assessment tools, influencing factors, and research limitations—were systematically analyzed. [Result/Conclusion] Existing research shows that AI literacy assessments primarily target the general public, students, and educators. Core assessment dimensions commonly include cognition, application, evaluation, and ethics. The assessment process generally involves sample selection and the development and validation of assessment tools. Empirical findings indicate that AI literacy levels are influenced by variables such as gender, age, nationality, and educational background. Current studies still exhibit limitations regarding assessment tools, sample characteristics, and assessment methods, suggesting the need for further refinement in future research.

Abstract: [Purpose/Significance] This study aims to reveal the current research status of library smart education services, clarify their irreplaceable role and value realization path in smart education, and provide reference for libraries to accurately meet educational needs and build adaptive service scenarios. [Method/Process] Selecting relevant Chinese and English literature from CNKI, Wanfang, and Web of Science databases, using bibliometrics, scientific knowledge graph, and other methods, and utilizing software such as CiteSpace and VOSviewer, visual analysis was conducted from the dimensions of literature temporal distribution, institutional regional distribution, keyword clustering, thematic performance, and domestic and international differences, with a focus on sorting out the role dimensions and practical characteristics of libraries. [Result/Conclusion] The study finds that the differences in research between Chinese and English reflect the essential differences in core driving mechanisms, technological applications, and value orientation between domestic and foreign countries; University libraries are the core battlefield, and public libraries and professional libraries can play a unique role in lifelong learning, vocational education, and other scenarios, forming a diversified supply system. The study clarifies the four-dimensional value positioning of libraries as "resource centers, spatial carriers, literacy platforms, and ecological hubs", and proposes that in the future, the focus should be on the core goals of "resource intelligence connection space intelligence integration service intelligence reach ecological intelligence governance". Through optimizing collaboration mechanisms, deepening technological integration, expanding practical scenarios, and improving evaluation systems, the four paths will promote the iterative upgrading of library smart education services, and help promote the high-quality construction of smart education ecology and the rapid development of library smart transformation.

Abstract: [Purpose/Significance] Under the background of AI, it is of great significance to study the digital transformation of digital governance, the ideas for solving the problems of digital governance, and the cultivation of intelligent talents from a knowledge-based perspective. [Method/Process] Based on the ideas of governance and complex systems, this paper analyzed the process of knowledge-based and knowledge deepening in AI, digital transformation, and digital governance; revealed the dual subject dual intelligence of humans and AI, the spillover symbiotic characteristics of AI's digital intelligence, as well as the elements, characteristics, advantages, and challenges of digital governance. In response to the problem of human cultivation ability, which is attributed to the attitude of "upright, serious, and pragmatic", the cultivation of "humanistic literacy, learning experience, insight, and cognitive ability of thinking logic", this paper analyzed the process of knowledge-based sublimation of knowledge, intelligence, spirituality, cognition, and wisdom, and proposed the idea of smart education to solve governance problems and cultivate intelligent talents. [Result/Conclusion] Digital transformation and governance require intelligent talents with a "correct, serious, and pragmatic" attitude and a profound humanistic background. Through universities, enterprises, urban governance, and personal cultivation, to cultivate the intelligent talents urgently needed for digital transformation and digital governance under AI, and make due contributions to supporting the implementation, expansion, optimization, and strengthening of the digital economy.

Abstract: [Purpose/Significance] This study proposes a methodology and process for knowledge discovery in technology fields based on the integration perspective. By constructing a knowledge map of multi-energy technology and focusing on analyzing the integration features (e.g., synergistic energy utilization and system integration), this study aims to provide a new methodological tool for identifying the potential of technology integration. [Method/Process] By integrating different patent technology classification systems, this study innovatively constructed a multi-energy integration patent knowledge graph. It established a domain knowledge organization framework based on multi-technology classification fusion. The conceptual model was constructed by combining the "top-down" and "bottom-up" methods, with the low-carbon energy technology field using as the empirical research object to systematically analyze the multi-energy fusion trend, fusion signal, and multi-energy fusion potential of low-carbon energy. [Result/Conclusion] Empirical study shows that combination of knowledge map, and bibliometrics can help analyze the development trends of low-carbon energy convergence, reveal the characteristics of technology integration of multiple low-carbon energy sources, and focus on specific domains to explore the potential and technological evolution path, to provide a decision-making basis for the development and application of low-carbon multi-energy integration technology.

Abstract: [Purpose/Significance] By constructing a model of online application behavior among fine arts undergraduates, this study aims to provide a basis for art universities to understand and grasp students' online behaviors, thereby monitoring their digital activities and exploring innovative online ideological and political education models in higher education. [Method/Process] Based on grounded theory and using the qualitative data analysis tool NVivo 12, interview texts were subjected to open coding, axial coding, selective coding, and theoretical saturation testing to develop a model of online application behavior for fine arts undergraduates. [Result/Conclusion] The model reveals that under different online and real-world contexts, influenced by personal traits and realistic constraints, fine arts undergraduates' online behaviors exhibit similar group characteristics while differing in behavioral purposes and patterns. The model summarizes six core categories (representation layer, environment layer, goal layer, behavior layer, extension layer, and constraint layer), as well as 18 main categories. Based on these core categories, the study further proposes that art universities should enhance the effectiveness of online ideological and political education by focusing on three aspects: environmental governance, goal guidance, and behavior correction, thereby providing a foundation for properly guiding students' online behaviors.

Abstract: [Purpose/Significance] This paper aims to comprehensively grasp the theoretical and practical frontiers of data governance in the field of library and information science, construct a systematic cognitive framework, and provide a strong reference for relevant policy formulation, institutional design, and strategic planning implementation. [Method/Process] With the help of CiteSpace and VOSviewer visualization tools, the data source of this paper was CNKI. Through the analysis of the topic information, this paper built the research framework of the field, extracted the frontier hotspots of the field, and explored the development and evolution of the field. [Result/Conclusion] The research literature on data governance in the field of Library and Information Science in China shows an exponential growth trend and can be divided into two stages (2015-2019 and 2020 to now). Through topic clustering, five topics are summarized, including governance theory system, governance technology system, governance business model, governance practice plan, governance policies and laws, and regulations. Further prospects for the research on data governance in China are put forward, which provide theoretical and practical reference for better playing the role of "data element ×" and promoting the modernization of the national governance system.

Abstract: [Purpose/Significance] Many scholars are using qualitative comparative analysis and structural equation modeling to conduct empirical analysis in the field of library and information, but few relevant studies are comparing the two methods. This study can provide a useful reference for selecting appropriate methods to explore the problems in the field of library and information, which is of great benefit to improving the overall research level of this discipline. [Method/Process] The principle, operation procedure, and application of QCA and SEM are elaborated and compared, and then QCA and SEM are respectively used to conduct an empirical study on the willingness of online knowledge paying users to continue using. [Result/Conclusion] The results showed that there were differences between the two methods. In terms of theoretical basis, QCA theory is based on set theory and Boolean algebra, while SEM theory is based on analysis of variance. In terms of causal analysis, QCA emphasizes equivalence and asymmetry, which is suitable for analyzing complex and interrelated problems with multiple antecedents, and SEM emphasizes linearity and symmetry, which is suitable for analyzing the relationship between two variables. In terms of research objectives, QCA is mainly to construct new theories and extend existing theories, while SEM is mainly to verify and improve existing theories. In terms of logic analysis, QCA is mostly an exploratory analysis method in logic analysis, while SEM is mostly a verification analysis method. In empirical studies, the multiple pathways resulting from QCA can complement the univariate conclusions of SEM.

Abstract: [Purpose/Significance] This study investigates the underlying mechanism through which library smart knowledge services empower the development of AI literacy among faculty in borderland universities. It aims to provide a regional perspective and practical insights for addressing challenges in teachers' digital-intelligent transformation and for expanding the functional role of academic libraries. [Method/Process] Utilizing a grounded theory approach, in-depth interviews were conducted with 30 faculty members from universities in the Guangxi border region. Data analysis involved a three-level coding process to construct a "Symbiotic Mechanism Model of Library Smart Knowledge Services". [Result/Conclusion] The research reveals an empowerment model characterized by "Preconditions — Multi-dimensional Empowerment — Collaborative Evolution". Faculty's AI literacy challenges and mismatches in library services constitute the preconditions. Libraries then engage in multi-dimensional intervention through four interconnected empowerment pathways: skills, cognition & ethics, culture & localization, and outcomes & governance. This ultimately drives the librarian-faculty relationship towards collaborative evolution, externally manifested in the behavioral progression of "anxiety → trust → integration → co-creation", and internally representing a fundamental shift from one-way support to two-way collaboration. This study enriches the regional theoretical perspective on smart libraries and faculty development, offering concrete implications for the localized and collaborative practices of academic libraries.

Abstract: [Purpose/Significance] Focusing on sudden incidents at tourist attractions within the short-video public opinion environment, this study aims to explore the most effective recovery strategies (apology, rectification, compensation) to restore public trust and enhance post-recovery satisfaction. [Method/Process] Using an online experiment, a 4 (recovery strategy: apology, rectification, compensation, no remedy) × 2 (involvement: high, low) between-subjects design was implemented. Short videos of service failures at tourist attractions served as stimulus materials to examine the effects of different strategies on public negative emotions and satisfaction under varying levels of involvement. [Result/Conclusion] The results indicate that among the recovery strategies, compensation is the most effective, followed by rectification, and then apology. Effective recovery enhances satisfaction by mitigating the public’s negative emotions. Public involvement plays a key moderating role: under high involvement, compensation is the optimal strategy for emotional remediation; under low involvement, rectification and compensation are equally effective in alleviating negative emotions.

Abstract: [Purpose/Significance] In response to the practical demand for high-quality data support and trustworthy operation of domain large models in specialized and high-risk application scenarios, this study systematically examines the basic connotation, key characteristics, and systematic construction path of the domain large model data foundation. It aims to provide a theoretical framework and methodological support for the practical deployment of trustworthy artificial intelligence, and to offer systematic references for the standardized construction and governance practice of the domain large model data foundation. [Method/Process] Based on a systematic review of the relevant literature, this study clarified the conceptual connotation, major characteristics, and constituent elements of the domain large model data foundation. It introduced the theory of layered modular architecture to construct a layered framework for the domain large model data foundation, mainly covering the data resource layer, knowledge organization layer, knowledge storage and semantic indexing layer, model layer, algorithm layer, application layer, and governance and operational support layer, so as to characterize the overall mechanism of the coordinated operation of data, knowledge, and models. Finally, a desk research method based on public evidence and a cross-case comparison approach were employed to demonstrate the contextual applicability of the framework. [Result/Conclusion] Cross-domain comparisons show that the proposed framework can explain the common mechanisms underlying external knowledge memory access, evidence-constrained generation, and compliance-audit output chains in reference systems across different domains. On this basis, the study further distills reusable methodological elements such as data contracts, index configuration, and evaluation baselines, thereby validating the applicability and transferability of the framework across domains.