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 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] 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 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] 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] 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] 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] 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] 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] 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 order to promote the standardization and digital transformation of Hainan sea fishing industry, this paper integrates knowledge management theory and Internet of Things technology to build intelligent management solutions and provide scientific and technological support for the upgrading of recreational fisheries. [Method/Process] Based on the real-time data acquisition and big data analysis technology of HiTo smart bracelet, the "Deshun Haitu" integrated management information service platform was designed and developed. The platform incorporated functional modules such as safety early-warning, resource scheduling, and user behavior analysis. Its efficacy was validated and refined through multiple iterations of case studies, expert evaluations, and simulation tests. [Result/Conclusion] "Desheng Haitu" integrated management information service platform based on HiTo smart bracelet can significantly reduce the rate of sea fishing accidents (down 35%), improve the efficiency of fishery resource allocation (28%), and enhance user activity (up 40%). Through the real-time perception and dynamic analysis of intelligent devices, accurate risk early warning and intelligent resource allocation can be realized, and a replicable technical path and management paradigm can be provided for the digital transformation of recreational fisheries.

Abstract: [Purpose/Significance] Fact-checking is an effective strategy to combat the dissemination of misinformation. Exploring the mechanism of how fact-checking types (crowdsourced and AI fact-checking) influence users' information participation behavior can help social platforms improve and optimize their measures for misinformation governance. [Method/Process] Based on real data from social media platforms, this study used analysis of variance to investigate the impact of fact-checking on users' information participation behavior, while considering the moderating effect of source credibility. [Result/Conclusion] The empirical results show that crowdsourced fact-checking significantly affects users' information engagement behavior, with positive fact-checking promoting information participation behavior and negative fact-checking inhibiting it. AI fact-checking positively influences users' information engagement behavior, and the combination of AI and crowdsourced fact-checking also positively affects users' information engagement behavior. Source credibility positively moderates the relationship between crowdsourced fact-checking and information engagement behavior, as well as the relationship between AI fact-checking and information engagement behavior. This study reveals the impact of different types of fact-checking and their integration on information engagement behavior, providing theoretical support for social media platforms to fully utilize collective intelligence and AI for fact-checking and misinformation governance.

Abstract: [Purpose/Significance] By facilitating the externalization of tacit knowledge, this study aims to drive knowledge innovation within virtual brand communities, ultimately injecting strong momentum into corporate innovation. [Method/Process] Using Xiaomi community members as research subjects, this study conducted coding analysis and relationship mapping of interview data. Grounded in the Stimulus-Organism-Response (SOR) theory, a model was developed to identify the influencing factors and pathways of tacit knowledge externalization among virtual brand community members. Finally, promotion strategies were proposed from three dimensions: individual, community, and brand dimensions. [Result/Conclusion] Community members' risk perception and benefit considerations are direct factors influencing tacit knowledge externalization behavior. Members' self-efficacy and intrinsic motivation, along with community-level factors (including member participation, content dissemination mechanisms, management, and ecosystem), as well as members' emotional identification with the brand and continuous attention to product innovation, indirectly affect tacit knowledge externalization by influencing members' risk perception and benefit considerations.

Abstract: [Purpose/Significance] This study aims to explore the motivation of organized scientific research cooperation among philosophy and social science researchers to effectively promote such cooperation. [Method/Process] Based on the theory of value co-creation, the value co-creation behaviors in organized scientific research cooperation were divided into four stages: value consensus, value sharing, value symbiosis, and value win-win. A consensus-based qualitative research method was adopted, and in-depth interviews were conducted with 20 researchers in the field of philosophy and social sciences to identify the motivation at each stage. [Result/Conclusion] The research finds that in the value consensus stage, the motivation of researchers mainly includes academic drive, policy drive, social value drive, and organizational management drive; in the value sharing stage, the motivation mainly includes reciprocal drive, reputation drive, communication and feedback mechanism drive, and external pressure drive; in the value symbiosis stage, the motivation focuses on collaborative innovation drive, role identity drive, personal development drive, and national demand drive; in the value win-win stage, the motivation emphasizes outcome distribution drive, collaborative win-win drive, and spillover effect drive. Meanwhile, there are significant cross-stage common motivations in each stage. Based on these findings, corresponding suggestions are proposed to promote the active participation of philosophy and social science researchers in organized scientific research cooperation.

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] 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] Focusing on the public opinion dynamics of generative artificial intelligence, especially ChatGPT, we aim to explore the background and significance of this technology and its social impact, analyze the public acceptance and public opinion evolution process, and provide theoretical support for the application of related technologies and social governance. [Method/Process] 221 564 microblog data related to generative AI between January 2023 and September 2024 were analyzed. By using the BERTopic model to extract the core themes and combining with keyword co-occurrence network analysis, we tracked the discussion hotspots and the evolution of public opinion in different time periods. [Result/Conclusion] This study identified eight major themes, including technology industry, education and robotics, and health care, and revealed the evolutionary path of public discussion: the initial phase focused on technological innovation and potential, the mid-term explored scenario applications such as education, health care, and finance, and the later stage turned to data privacy, security, and social ethics. Keyword analysis shows that terms such as "artificial intelligence" and "technology" run through the entire cycle, while high-frequency words such as "privacy" and "security" in the later period reflect the public's concern about the potential risks of technology. This study provides an in-depth understanding of the social effects of generative artificial intelligence technology and theoretical support for technology optimization and policy governance.