[Purpose/Significance] The library is currently in a critical period of development for the "15th Five-Year Plan", and the intelligent strategy is one of the key areas of the library's "15th Five-Year Plan". The large-scale modeling technologies represented by DeepSeek, ZhipuAI, ChatGPT, etc. are reshaping the boundaries and forms of knowledge services through the deep integration of new-generation artificial intelligence technologies and knowledge service systems, providing important theoretical and technical support for the development of library intelligence strategies during the 15th Five-Year Plan period. Therefore, exploring how DeepSeek enhances library knowledge services has become one of the most cutting-edge issues worth paying attention to in the library and information science (LIS) field. [Method/Process] On the basis of a brief review of the current state of research on the integration of DeepSeek and library knowledge service theory, this article designs and proposes a theoretical model for DeepSeek to enhance library knowledge services. It explores the innovative model of DeepSeek that empowers library knowledge services from five aspects: knowledge discovery, knowledge acquisition, knowledge analysis, knowledge recombination, and knowledge utilization and thoroughly analyzes the four core dimensions of technology empowerment, business empowerment, user empowerment, and ecological empowerment. It also elaborates on the security issues of large models caused by the open source strategy, the intellectual property risks caused by technological innovation, the knowledge illusion problems caused by data traps and defects, and the information cocoon problems caused by technological applications. This study aims to provide some reference and inspiration for the research of related issues. [Results/Conclusions] The library is currently in a critical period of development for the "15th Five-Year Plan". DeepSeek's inherent technological advantages such as low cost, high performance, and open source ecosystem not only enable the library knowledge service system in multiple dimensions, reshape the boundaries and forms of knowledge services, comprehensively enhance users' knowledge service experience, but also provide stronger impetus for library construction, management, and service in the "15th Five-Year Plan" period. The theoretical model of DeepSeek empowerment of library knowledge services mainly includes four core dimensions: technology empowerment, business empowerment, user empowerment, and ecological empowerment. It has an impact on library service innovation in five aspects: knowledge discovery, knowledge acquisition, knowledge analysis, knowledge recombination, and knowledge utilization. At the same time, it can bring many problems, such as model security, intellectual property risks, knowledge illusions, and information cocoons. From the existing public information, DeepSeek can provide important technical support and core driving force for library knowledge service innovation in the era of artificial intelligence from four aspects: technical algorithms, training cost, open source ecology, and local lightweight deployment. Since the gradual formation of the DeepSeek open source ecosystem, more and more enterprises, communities, research institutions, teams, and developers have actively participated in and built the industry ecosystem, showing a strong magnetic field effect. Libraries should adhere to the principle of "join if you can't win", actively integrate into the DeepSeek open source ecosystem, and build an ecosystem of knowledge service ecosystems with library industry characteristics and disciplinary features.
[Purpose/Significance] With the rapid development of generative artificial intelligence (AI) and large language models (LLMs), the role of "prompt librarians" has emerged. This study constructs a theoretical framework for prompt librarians and explores the rationality, feasibility, and significance of the transition of librarians to this role from the perspective of new quality productive forces. Driven by the new quality productive forces represented by AI, transforming librarians into prompt librarians can not only optimize application scenarios and user experience, but also improve work efficiency and effectively promote the intelligent transformation of libraries. There is currently no research on this topic in the existing literature. This study, for the first time, proposes a theoretical framework for prompt librarians and the implementation path for the transition of librarians, filling the research gap in this area. [Method/Process] Through a review of relevant national and international literature, this study examines the impact of AI on the role and positioning of librarians within the library industry. Taking the new quality productive forces as the theoretical foundation and driving factor, the study explains the necessity of the transition of public librarians to prompt librarians, and analyzes the rationality, feasibility, and significance of this transition. Furthermore, a theoretical framework for prompt librarians is constructed, encompassing concepts, scope of functions, work processes, and core competencies. Additionally, through the method of literature review and online surveys, the study examines the current status of information and knowledge services in public libraries, focusing on the top thirty libraries ranked by online influence in China. It identifies the major challenges faced by librarians in the transition. Based on the theoretical framework of prompt librarians and real-world challenges, the study explores the implementation path for the transition of librarians to prompt librarians, ensuring the scientific, logical, and innovative nature of the research. [Results/Conclusions] As an emerging role that combines the library industry with AI technology, prompt librarians, driven by user needs, explore the unique resources of their collections in depth, revitalizing literature, diverse information resources, and other materials through AI pathways. They act as guides and translators between knowledge and AI, effectively driving the intelligent transformation of libraries. However, the transition of librarians faces many challenges. To facilitate a smooth transition, this study proposes implementation pathways, such as the establishment of dedicated prompt librarian positions, a "three-step leap" training model for librarians, robust top-level planning, the construction of multi-modal resource service platforms, AI ethics considerations, and interdisciplinary collaboration. Through these explorations, the study aims to provide innovative ideas and practical guidance for the transition of librarians in the AI era, enrich research on the application scenarios of new quality productive forces, and enhance the service quality and competitiveness of libraries.
[Purpose/Significance] Satisfaction is the patient's evaluation and emotional feedback on the entire mobile healthcare experience. Not only does it directly affect the patient's experience, but it also significantly influences user adoption and retention. Therefore, this study aims to explore the influencing factors, hierarchical relationships, and associated pathways of user satisfaction with mobile health applications, and provide scientific evidence and practical recommendations for the healthy development of mobile health applications, thereby promoting the construction of a healthy China and intelligent healthcare. By clarifying the key drivers of user satisfaction and their interactions, the study provides theoretical support for enhancing user experience, optimizing service quality, and increasing user retention. [Method/Process] This study first crawled, cleaned, and filtered negative user review data from mobile health applications, resulting in 539 valid data points after processing. Using the grounded theory, the study extracted factors influencing user satisfaction with mobile health applications by coding the review data. Subsequently, based on the interpretive structural model (ISM), the internal logic and associated pathways between these influencing factors were explored. Finally, the cross-impact matrix multiplication (MICMAC) method was used to examine the dependencies and driving forces among the influencing factors, and to identify the key factors affecting user satisfaction with mobile health applications. [Results/Conclusions] The study found that user satisfaction with mobile health applications is influenced by 23 factors across eight dimensions, including physician service quality, management service quality, system quality, information quality, transaction quality, perceived value, perceived risk, and perceived cost. Perceived cost and perceived risk are key drivers that directly affect user satisfaction. The middle-level factors transmit the effects of the bottom-level factors to the top level, acting as "mediators," and consist of factors from the dimensions of system quality, information quality, perceived value, transaction quality, and perceived risk. The bottom-level factors are the primary driving forces, including the quality of medical service, management service quality, system quality, and information quality. Based on the analysis results, this study proposes the following practical recommendations: strictly review the qualifications of doctors and establish a service quality evaluation mechanism; provide communication training for doctors and simplify medical terminology; add artificial intelligence and human services, and regularly train management service staff; design a simple interface and offer personalized customization; ensure information security and privacy, follow the principle of minimal data collection, and allow users to view and delete their personal information. Subsequent research, based on the expansion of the types of mobile health applications, will use a combination of qualitative and quantitative research methods to explore more deeply the relationships among the various factors that influence user satisfaction.
[Purpose/Significance] With the rapid development of artificial intelligence generated content (AIGC) technology and the deepening of social impact, it is an important responsibility and historical mission of university libraries to cultivate and enhance students' critical information literacy (IL) in the application of AIGC. The research aims to explore the content and pedagogical strategies of critical IL education in university libraries for AIGC applications, promote the ability of college students to critically recognize and apply AIGC in the AI era, and also provide reference for the development of critical IL education in university libraries. [Method/Process] By reviewing the relevant literature at home and abroad, this paper summarizes the research status of critical IL education for AIGC applications. Based on the requirements of the "Higher Education Information Literacy Framework" for the cultivation of critical thinking ability, the current situation of critical IL education in university libraries, and the relevant policies and guidelines for the development of AI literacy education at home and abroad are reviewed. The content of critical IL education in university libraries for AIGC applications can be categorized into three aspects: AIGC application knowledge, AIGC application skills, and AIGC application ethics. At the same time, based on the requirements of IFLA library's Strategic Response to Artificial Intelligence' and the lack of IL education system in university libraries, it is proposed that the critical IL education of university libraries from the perspective of AIGC application should be ensured and implemented from the aspects of educational content integration, educational team building, educational mode development and educational system optimization. [Results/Conclusions] The research on critical IL education for AIGC application has a critical role in promoting the cultivation and improvement of students' critical thinking ability for AIGC. University libraries should be aware of their responsibilities, actively respond to the new requirements of critical IL education for AIGC applications, innovate and expand the content and form of IL education, and help students acquire the new IL skills needed for AIGC applications. At the same time, university libraries should also continuously update the content of critical IL education from the perspective of AIGC application, and have the courage to explore new teaching methods and strategies, so as to better cultivate and improve students' IL of AIGC application, help students use AIGC scientifically, correctly and normatively, and realize lifelong learning.
[Purpose/Significance] Public access policy plays a crucial role in raising the awareness of openness, promoting scientific progress and innovation development. Studying the current situation of scientific data sharing in international countries can provide a reference for the practice and development of scientific data sharing activities in China. [Method/Process] Over the past 15 years, an increasing number of funding agencies in the United States have responded to national policy calls to require funded projects to share the research results in order to improve the effectiveness of the grant implementation and to promote scientific development. To this end, many academic institutions have established and provided a variety of data support facilities and services, but these facilities and services are often scattered across different administrative departments. Data management and sharing activities under this model suffer from organizational deficiencies, fragmented activities, overlapping services, inaccessibility, and others that reduce the efficiency of public access to scientific data. In order to understand the reality of scientific data sharing, ARL conducted a fact-based study named the RADS initiative on the scientific data sharing model, with survey respondents coming from six research-intensive universities in the United States, who are involved in scientific data management and sharing, resulting in a relatively comprehensive survey. The article adopts the network research method and literature analysis method, through the interpretation of the first phase of ARL's RADS Initiative series of reports and materials, to comprehensively understand the composition of the entire life cycle of scientific data management and sharing activities, service content and implementation costs of the U.S. academic institutions under the public access policy. We also analyze the behavioral characteristics of the two main actors of the U.S. colleges and universities involved in the practice of scientific data sharing, the characteristics of the activities and support services, and summarize the real problems of scientific data management. The practical problems of scientific data sharing include inter-departmental coordination and linkage, gaps in supply and demand between disciplines, boundaries between disciplines, inadequate cost-benefit evaluation, and the availability of shared data to the public. [Results/Conclusions] On the basis of summarizing the successful experiences and shortcomings of the RADS Initiative, and taking into account the current situation of scientific data sharing in China, this paper puts forward the construction ideas and quality enhancement suggestions to promote the implementation of scientific data sharing activities in China at each level with an emphasis on public participation, We propose to integrate the coordinated development and optimize cost-effectiveness, foster the data literacy and emphasize user feedback, focus on the public access, and construct the core clusters.
[Purpose/Significance] Information literacy (IL) training for farmers has become one of the main contents for farmers in the new era. However, the current implementation of rural revitalization still does not pay enough attention to farmers. At the same time, farmers' IL ability is an important embodiment of farmers' integration into the digital countryside, which can give a strong boost to the modernization of agriculture and rural areas. Therefore, it is of great practical significance for the rural revitalization strategy in the new era to make full use of multiple social subjects and improve farmers' IL. [Method/Process] This paper reviews the concept and definition of IL, and analyzes the research on farmers' IL in recent years. The results show that most of the current research on the cultivation of farmers' IL focuses on a specific topic and lacks holistic research. Therefore, it is necessary to systematically understand the cultivation process of farmers' IL, and guide the cultivation behavior of IL by the all-round cultivation concept. [Results/Conclusions] At present, although the local governments have initially built an IL training model of the new era, with schools and social organizations as participants in the model, farmers still lack information knowledge, information awareness, and IL skills. Several proposals are put forward here to address the above issue. First of all,it is necessary to strengthen the construction of IL education system and improve farmers' information knowledge. The government should give full play to the local government agencies in resource integration, schools and scientific research institutions in professional advantages, and social organizations in providing information services, so as to provide farmers with more systematic IL training. Second, efforts should be made to jointly build IL education space to raise farmers' information awareness: the government should build farmers' IL training base, the schools should promote the transformation of the education model, and social organizations continue to carry out IL training project. The three parties join hands to build a three-dimensional integrated IL education space of "material space, spiritual space and social space", and a new way of the cultivating farmers' information awareness. Finally, IL teachers should be trained to improve farmers' information literacy. The government will attract and retain information talent in rural areas through positive talent polices. Schools will play an educational role in developing farmers' information literacy skills.
[Purpose/Significance] Public emergencies frequently trigger online public opinion, exacerbating public panic and threatening social stability. The intrinsic linkage between public emergencies and online discourse amplifies the dissemination of public emotions, attitudes, and perspectives across online platforms, creating a feedback loop that influences event dynamics. Investigating the generation mechanism of public opinion on hot topics in such contexts provides critical theoretical foundations for mitigating cyber discourse risks, while enhancing the accuracy and efficiency of governmental mangement over online public opinion. [Method/Process] From an information ecology perspective, this study employs fuzzy-set qualitative comparative analysis to examine the online public opinion heat of 50 public emergencies between 2020 and 2022. We analyze eight conditional variables across four dimensions - information, information person, information technology, and information environment - including peak propagation speed, peak event popularity, netizen attention, opinion leaders' communication power, important media participation, central media coverage, the proportion of the overall public opinion field, and event duration. Single-factor necessity detection and configuration analysis were performed, and robustness was tested by adjusting calibration points and consistency thresholds. Finally, based on empirical findings, we interpreted case studies and proposed a mechanism for the generation of online public opinion heat in public emergencies. [Results/Conclusions] The results reveal that information and information people are the primary drivers and key causes of hot public opinion. Although information environment and information technology are not necessary conditions, they still contribute to the process. In public emergencies, multiple factors jointly influence online public opinion, and no single factor alone determines its intensity. Rather, the complementarity of multiple factors can, to some extent, substitute for seemingly necessary conditions. The key findings reveal that the event's peak plays a dominant role in driving high online public opinion intensity, and directly triggers its rapid outbreak, while the absence of major media participation and short event duration - core conditions for non-hot events - significantly reduce public engagement due to limited coverage and transient attention. Additionally, opinion leaders' communication power exhibits a strong positive correlation with public opinion on hot topics, as their amplified expressions attract more attention from netizens and further amplify the momentum of the discourse. These findings will provide valuable insights for effectively managing and controlling online public opinion during emergencies. Future research should examine the impact of emotional shifts, such as positive, negative, and neutral emotions, on the virality of online public opinion during emergencies, while also exploring the underlying mechanisms of such emotional shifts. Additionally, future studies should differentiate between policy stages in emergency development and examine how policy interventions shape the dynamics of public opinion. Finally, network analysis techniques (e.g., forwarding relationship networks, key evolutionary network structures) should be employed to uncover the mechanisms that drive public opinion heat in emergency-related discourse.
[Purpose/Significance] Scientific literature contains rich domain knowledge and scientific data, which can provide high-quality data support for AI-driven scientific research (AI4S). This paper systematically reviews the methods, tools, and applications of arge language models (LLMs) in scientific literature data mining, and discusses their research directions and development trends. It addresses critical shortcomings in interdisciplinary knowledge extraction and provides practical insights to enhance AI4S workflows, thereby aligning AI capabilities with domain-specific scientific needs. [Method/Process] This study employs a systematic literature review and case analysis to formulate a tripartite framework: 1) Methodological dimension: Textual knowledge mining uses dynamic prompts, few-shot learning, and domain-adaptive pre-training (such as MagBERT and MatSciBERT) to improve entity recognition. Scientific data extraction uses chain-of-thought prompting and knowledge graphs (such as ChatExtract and SynAsk) to parse experimental datasets. Chart decoding uses neural networks to extract numerical values and semantic patterns from visual elements. 2) Tool dimension: This explores the core functionalities of notable AI tools, including data mining platforms (such as LitU, SciAIEngine) and knowledge generation systems (such as Agent Laboratory, VirSci), with a focus on multimodal processing and automation. 3) Application dimension: LLMs produce high-quality datasets to tackle the issue of data scarcity. They facilitate tasks such as predicting material properties and diagnosing medical conditions. The scientific credibility of these datasets is ensured through a process of "LLMs + expert validation". [Results/Conclusions] The findings indicate that LLMs significantly improve the automation of scientific literature mining. Methodologically, this research introduces dynamic prompt learning frameworks and domain adaptation fine-tuning technologies to address the shortcomings of traditional rule-driven approaches. In terms of tools, cross-modal parsing tools and interactive analysis platforms have been developed to facilitate end-to-end data mining and knowledge generation. In terms of applications, the study has accelerated the transition of scientific literature from single-modal to multimodal formats, thereby supporting the creation of high-quality scientific datasets, vertical domain-specific models, and knowledge service platforms. However, significant challenges remain, including insufficient depth of domain knowledge embedding, the low efficiency of multimodal data collaboration, and a lack of model interpretability. Future research should focus on developing interpretable LLMs with knowledge graph integration, improving cross-modal alignment techniques, and integrating "human-in-the-loop" systems to enhance reliability. It is also imperative to establish standardized data governance and intellectual property frameworks to promote the ethical utilization of scientific literature data. Such advances will facilitate a shift from efficiency optimization to knowledge generation in AI4S.
[Purpose/Significance] Digital literacy education has become the new educational mission of university libraries. Clarifying the user's perception and utilization mechanism of digital literacy knowledge and optimizing the representation of digital literacy knowledge can promote university libraries to achieve satisfying results in digital literacy education. Based on the frontier of representation theory, this study innovatively puts forward the concept of "sensory digital literacy education", constructs a three-dimensional knowledge perception model including action, image and symbolic representation, and reveals the mechanism of digital literacy knowledge representation and user perception behavior through empirical research. It provides a theoretical anchor for the paradigm shift in library education from tool skills training to cognitive skills training. The "cognition-practice-innovation" teaching system and the "three-in-one" resource construction framework proposed in the study effectively connect the knowledge representation theory with the educational practice scene, and provide a viable way for the three-dimensional implementation of digital literacy education in colleges and universities. [Method/Process] Based on the theories of SOR, TAM and self-efficacy, the theoretical hypothesis model of users' perception and utilization of digital literacy knowledge from the perspective of representation was constructed, and was empirically verified by questionnaire and empirical study. [Results/Conclusions] Action representation, reflexive representation and symbolic representation of digital literacy knowledge all positively affect users' perceived ease of use and perceived usefulness of digital literacy knowledge; perceived ease of use has a positive impact on perceived usefulness; self-efficacy plays a positive moderating role between perceived ease of use, perceived usefulness, and user intention and behavior. Due to the limitations of space and personal energy, the shortcomings of this paper are as follows. First, the methodological level is mainly based on quantitative analysis, and the mining of qualitative dimensions such as details of teacher-student interaction and informal learning scenarios in digital literacy education is insufficient. Secondly, the research object focuses on the groups of teachers and students in colleges and universities, and the issues such as the intergenerational differences of the public's digital literacy and the professional digital literacy needs of professionals have not been covered, and the comparative study of multiple subjects can be expanded in the future. In the future, more research can be done on research methods and research objects. Through the deep coupling of representation theory and educational practice, it is expected to provide a new theoretical mirror for the cultivation of cognitive ability in the digital age, and help to build a three-dimensional educational ecology of "technology empowerment-cognitive development-literacy transfer".
[Purpose/Significance] The rapid advancement of artificial intelligence (AI) technology is transforming various sectors, particularly in higher education. The LLaMA (Large Language Model Meta AI) represents a significant innovation in this arena, making its application within university future learning centers increasingly important. As institutions of higher education strive to create environments conducive to learning and growth, understanding the construction requirements of future learning centers becomes paramount. This study delves into the integration of LLaMA core technologies in these learning spaces and emphasizes the importance of evolving libraries into intelligent learning support systems. [Method/Process] The methodology employed in this research combines technical deconstruction and scenes for validation, allowing for a comprehensive analysis of the legal risks associated with embedding advanced technologies in educational frameworks. By systematically examining these potential risks, the study aims to establish a well-rounded perspective on the implications of AI deployment in educational settings. [Results/Conclusions] The study identifies three principal challenges encountered in the application of the LLaMA within university learning centers. The first challenge arises from reliability risks linked to content generated by the AI, which may be affected by biases present in the training data. Such biases can lead to the dissemination of inaccurate or misleading information, undermining the trustworthiness of educational resources. Secondly, there are privacy leakage risks, particularly associated with the retention of user behavioral data. As AI systems analyze user interactions, there is a potential for sensitive information to be exposed or misused, raising concerns about student privacy and data security. The third challenge involves ownership determination dilemmas regarding the content generated through AI-driven creative processes. These dilemmas are intricately tied to existing copyright law frameworks, which may not adequately address the complexities introduced by human-machine collaboration in content creation. In response to these challenges, the study proposes several pathways for governance aimed at effectively navigating the landscape of AI in education. It suggests the implementation of dynamic data cleansing mechanisms to address reliability risks and inaccuracies. Additionally, establishing tiered privacy protection systems can help safeguard against user data breaches. Legal frameworks also need refinement to ensure clear ownership distribution for outputs of human-machine collaboration. Ultimately, optimizing the application of the LLaMA model in university future learning centers necessitates a careful balance between technological innovation and legal regulation. By focusing on technical refinement, risk control, and relevant regulatory measures, the development and application of AI can be advanced, facilitating a more integrated evolution of artificial intelligence and educational practices.
[Purpose/Significance] Under the background of digital government construction, as a new type of service subject of human-machine collaborative governance, the influence mechanism of the social role positioning of government digital humans on public adoption behavior urgently needs theoretical exploration. Most existing studies have focused on the technical level. This study, based on the perspective of social role theory, explores the influencing mechanism of different role positioning of government digital humans in government service scenarios on public adoption behavior, which is of great significance for optimizing government services and improving the intelligent level of government services. [Method/Process] An experimental research method was adopted to construct a two-factor inter-group experimental design of "social role-business type", and a simulation experiment of government service scenarios was carried out through random grouping. Based on previous studies, we defined the role positioning of "advisors" and "decision-makers" for government digital humans, and constructed experimental scenarios by combining two service scenarios of consultation and approval. The subjects were randomly grouped to complete the role cognition test and human-computer interaction tasks. Data were collected by using the research path combining situation simulation and questionnaire survey. The psychological mechanism and decision-making logic of the public's adoption behavior were analyzed through the data analysis results. [Results/Conclusions] The research findings are as follows: 1) There is a significant interaction effect between the social roles and business types of government digital humans. In approval service scenarios, the decision-maker role is more capable of promoting public adoption behavior than the advisor role; 2) Human-computer trust perception plays a crucial mediating role in the influence path of social roles on the public's adoption behavior, revealing the core value of the trust mechanism in human-computer interaction; 3) The synergy effect between role authority and task fit constitutes an important mechanism influencing public cognition. This study expands the explanatory boundary of the social role theory in the field of intelligent government services and provides theoretical support for the construction of smart government services. However, there are still certain limitations. The service scenario simulation in the experimental design is difficult to fully restore the complexity of real government services. Future research can extend the multi-dimensional role classification system and deepen the mechanism exploration by combining the mixed research method. We have verified the applicability of the theoretical model in real government service scenarios and expand the existing conclusions. In addition, exploration on the dynamic impact of long-term interaction between government digital humans and the public on behavioral evolution is also a potential research direction.
[Purpose/Significance] The ongoing digital transformation has led to significant changes in public cultural services, particularly in content generation, communication channels, and modes of public participation. "Accessibility," a key indicator of the extent to which citizens' cultural rights are realized, is typically assessed along four dimensions: availability, acceptability, accessibility, and adaptability. Previous research has focused primarily on the supply side of accessibility, examining how factors such as the distribution of cultural resources, infrastructure development, and policy support affect user engagement. However, with the widespread adoption of digital technologies, individuals' ability and willingness to access information, utilize services, and provide feedback - collectively referred to as "digital literacy" - has become an increasingly important variable influencing cultural participation. Consequently, this study seeks to explore the relationship between users' digital literacy and the accessibility of public cultural services from a demand-side perspective. It aims to provide a more systematic theoretical framework and practical approach to optimizing the effectiveness of public cultural services. [Methods/Process] This study assesses users' digital literacy by examining their level of digital access, Internet usage, and service availability based on data collected from the Beijing-Tianjin-Hebei region. A structured questionnaire yielded 892 valid responses. To analyze the relationship between users' digital literacy and the accessibility of public cultural services, the study applies a generalized ordered logit model. A generalized ordered logit model is employed to analyze the substitution and overlap effects between users' digital literacy and the various dimensions of service accessibility. [Results/Conclusions] There is currently a digital divide exists between different demographic groups. A significant substitution effect is observed between traditional public cultural accessibility and users' digital literacy, with limited overlap between the two. Digitization has driven the modernization of public cultural resources and services, particularly in terms of technology and service delivery. However, there remains a time lag between the users' digital literacy of users and the digital transformation of the public cultural supply side. This lag suggests that the digital needs of users and the availability of digital cultural services are not fully aligned, which negatively impacts the effectiveness of public cultural services. Therefore, enhancing users' digital literacy, especially improving their ability to adapt to digital cultural resources, is a crucial factor in transitioning public cultural services from "accessibility" to "enjoyment". In promoting the digital upgrading of public cultural services, greater emphasis should be placed on developing users' capabilities and anticipating their needs.
[Purpose/Significance] With the globalization of knowledge sharing and the vigorous development of preprint at home and abroad, the role of preprint platform in academic exchange has been recognized and appreciated by academic community. This paper introduces the evolutionary simulation method for the first time from the previous research on government and enterprises to the research on preprint platform, and takes the three main stakeholders in the construction of preprint platform, that is government, researcher and the public as the main players of the game. Different from the existing research, this paper uses system dynamics theory and software to fill the gap in quantitative analysis of SD model, and combines qualitative and quantitative research to further enrich the research content of the preprint platform through game model construction and simulation analysis. This research aims to guide stakeholders to actively participate in the construction of preprint platform, improve the utilization rate of domestic preprint platform by users, and promote the construction of preprint platform in China. [Method/Process] This study established a tripartite evolutionary game model of "government, researcher, and the public" to analyze the strategic stability of the three stakeholders. Vensim PLE software was used to simulate and analyze the the SD model, focusing on the influence of mixed strategies and external sensitivity variables on stakeholders' decision behavior. [Results/Conclusions] In the construction of preprint platform, the willingness of government supervision is mainly influenced by the supervision cost and credibility Within a reasonable range, the higher the scientific research funding for researchers or the more severe the penalty for their passive participation, the greater the willingness of researchers to participate actively. The public's willingness to cooperate is influenced by the costs of participation and the social dividends. In the future, the construction of the preprint platform can be continuously promoted from three perspectives: formulating the framework of the underlying reward and penalty mechanism of the preprint platform, establishing the reputation evaluation mechanism of researchers, and accelerating the construction of the government's open scientific innovation service. However, due to the limitation of the author's professional ability, the cognition of the preprint platform and the consideration of the relevant policy establishment process are relatively limited. There are many stakeholders involved in the construction of preprint platform, and there are also many factors that can affect the decision-making behavior in the external environment and system. In this study, three stakeholders from three main aspects are selected to model and study the external influence. In the future, we can select stakeholders from different angles and increase the influencing factors to expand the research on preprint platform.
[Purpose/Significance] Promoting the digital transformation of agricultural product circulation through e-commerce has become a crucial way for rural revitalization in China. For three consecutive years, China's No. 1 Central Document has listed the high-quality development of agricultural e-commerce as a priority for upgrading the level of rural industrial development. However, persistent disparities in information literacy and imbalance in risk-benefit perceptions among farmer groups constrain the effective popularization of e-commerce platforms for agricultural products. To address this issue, this study integrates the Theory of Planned Behavior (TPB) and the perceived benefit-risk theory to construct a conceptual framework. It explores the relationship pathways among information literacy, perceived risks, perceived benefits, government support, and farmers' willingness to participate in e-commerce, aiming to provide theoretical insights for governments and enterprises to deepen the high-quality development of agricultural e-commerce business and rural revitalization. [Method/Process] Based on the above background, this paper integrates and proposes a conceptual model that includes the relationship of five potential variables: information literacy, perceived benefits, perceived risks, government support and engagement intention, based on the theory of planned behaviour and the theory of perceived benefits-perceived risks. In order to ensure the appropriateness of the sample distribution as well as the convenience, authenticity and reliability of the data collection, this study used a combination of online (WeChat group of village committees) and offline (recruiting home-based university students for field survey) to collect questionnaires from farmers across the country, and a total of 730 valid farmers' sample data were collected. Finally, based on the above data, the direct paths of perceived benefits, perceived risks and farmers' information literacy on farmers' willingness to participate in agricultural e-commerce were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). We focus our analysis on verifying the mediating roles of perceived benefits and perceived risks, as well as the moderating role of government support, in enhancing farmers' willingness to participate in agricultural e-commerce. [Results/Conclusions] The findings reveal that increased information literacy strengthens farmers' willingness to engage in agricultural e-commerce. Most farmers prefer participation scenarios with high perceived benefits and low perceived risks, where government support plays a key role in endorsing and leading trust. In this regard, local governments should establish tiered training systems and risk-hedging mechanisms (e.g., agricultural insurance, logistics subsidies) to address age-specific demand for information literacy improvement in rural areas and mitigate operational risks. We suggest actively publicizing national high-quality rural e-commerce demonstration cases and improving the perception of benefits to motivate farmers to participate, so as to achieve the high-quality development of agricultural e-commerce in a multi-initiative way. In addition, future research should pay more attention to the breadth of the sample coverage and the depth of the sample research process, and consider using all offline field research to further examine the impact of regional differences and the differences in the digital characteristics of the new farmers (Generation Z) on their willingness to participate in e-commerce. This will provide empirical evidence and guidance for rural revitalization and high-quality development of agricultural e-commerce.
