[Purpose/Significance] Constructing the knowledge service value chain model of think tanks is significant for promoting the value-added of think tanks' knowledge service and improving the quality and level of think tanks' knowledge service. [Method/Process] Based on the open innovation paradigm, combining the knowledge value chain model, knowledge spiral theory and open service value chain model, this paper constructed knowledge service value chain model of think tanks on the basis of analysing basic activities and operational characteristics of think tanks' knowledge service value chain, and empirically verified the constructed model. The model and empirical results were applied to propose strategies for accelerating the formation of Chinese think tanks' knowledge service value chain. [Result/Conclusion] The constructed model comprehensively shows three basic activities, four key elements and their interrelationships of think tanks' knowledge service value chain, and profoundly reveals its operation characteristics, which are"based on the open cycle", "producing knowledge based on collaborative innovation"and"aiming at the value-added of knowledge service". Applying the constructed model can provide theoretical references and practical guidance for the knowledge management and value-added of think tanks' knowledge services. It is suggested that Chinese think tanks should accelerate the formation of their knowledge service value chain by strengthening the development of policy analysis tools and methods, promoting internal knowledge flow and sharing, implementing globalisation cooperation mode, enhancing efforts to attract external experts, and broadening dissemination channels of knowledge achievements.

[Purpose/Significance] The complex knowledge objects in scientific and technological literature provide fine-grained and comprehensive knowledge representation of the deep knowledge content in scientific and technological literature, which can effectively support data-driven scientific and knowledge discovery and is an important element of technological innovation. [Method/Process] Firstly, the domain knowledge graph was constructed through steps such as lightweight ontology construction, BRAT knowledge annotation, and Neo4j knowledge storage. Next, the large language model ChatGLM2-6B was locally deployed and fine tuned through LoRA technology. Finally, based on the MOT mechanism, the knowledge in the knowledge graph was injected into the prompts, and complex knowledge objects were extracted from scientific literature through multiple rounds of Q & A with the large language model. [Result/Conclusion] Taking organic solar cells (OSCs)as an example to verify the effectiveness of the method, the results show that the extraction method intergrating knowledge graph and large language model is superior to the extraction method supported by large language model alone, with improvements of 14.1%, 10.3%, and 12.3% in accuracy P, recall R, and F1 score, respectively. Knowledge graph can enhance the ability of large language models to extract complex knowledge objects from scientific literature, and improve the efficiency and accuracy of scientific literature mining in the OSC field.

[Purpose/Significance] Most existing citation recommendation methods adopt meta-path-based network representation learning approaches, which often overlook complex interactions between nodes and heavily rely on domain knowledge. [Method/Process] This paper proposed a heterogeneous graph convolution network-based method to effectively integrate multi-dimensional academic features for improving recommendation accuracy. This proposed method first used pre-trained BERT models to extract semantic features from papers. Then, an attention-aware graph convolutional neural network was designed to automatically learn neighborhood information of nodes in the heterogeneous academic information network. Finally, this method combined the network topology and semantic information to generate paper representations. [Result/Conclusion] Extensive experiments on three datasets demonstrate that the proposed method outperforms baseline models on all evaluation metrics. Case studies further indicate the effectiveness and applicability of the proposed method in the task of citation recommendation.

[Purpose/Significance] This paper aims to explore how to conduct information behavior research to promote the flourishing of individuals in the era of rapid artificial intelligence advancement to lay the foundation for constructing a more inclusive and supportive positive information society. [Method/Process] Through theoretical exploration of positive psychology and positive information science and the discussion of the mutually empowering relationship between information behavior research and positive psychology research, this paper established the scope of research on positively oriented information behavior, which focused on positive factors in information behavior studies and how to approach negative events or phenomena with a positive attitude, extracting positive effects from them. [Results/Conclusion] The paper constructs an I-PERMA framework for information behavior research based on Seligman′s PERMA framework with its five elements (positive emotion, engagement, relationships, meaning, and accomplishment).The paper systematically investigates and examines existing relevant research according to the elements in the I-PERMA framework, including emotion regulation, flow, collaborative information behavior, serious leisure, creativity, and information resilience, and identifies future research directions, including constructing happiness in daily life through flow experiences, promoting positive interpersonal relationships through collaboration, incubating creativity through creative processes, and developing resilience during transitions.The paper proposes new research agendas based on the I-PERMA framework, design principles for information systems oriented toward positive experiences, and new modes for information literacy education that integrate information resilience.

[Purpose/Significance] The study aims to clarify the characteristics of personal digital hoarding behavior and to identify its driving factors in the big data environment.It is conducive to providing valuable references for the study of personal digital hoarding behavior and offering guidance strategies for individuals to reduce or reasonably engage in digital hoarding behavior. [Method/Process] The study based on the meta-ethnography method to construct the index system of personal digital hoarding behavior driving factors under five dimensions of individual factors, emotional factors, cognitive factors, information factors and technology factors, and the index factors were reduced by rough set theory.Then the study analyzed the influence index relationships and weights of the factors at all levels using the combined Grey-DANP method. [Result/Conclusion] Based on the analysis of driving factors such as causality and centrality, guidance strategies for personal digital hoarding behavior are proposed from five dimensions: individual, emotion, cognition, information, and technology.These strategies include cultivating digital storage habits, regularly cleaning digital files, clarifying digital resource needs, and optimizing information quality issues.

[Purpose/Significance] Carrying out the identification of technology evolution paths and analysis of innovation types in target areas can provide realization method support for enterprises to formulate forward-looking technological innovation strategies. [Method/Process] Firstly, the study adopted SAO semantic analysis method to accurately identify the technology nodes, and took the innovation dimensions of multi-dimensional technology innovation map as the navigation to realize the automatic dimension partitioning of technology nodes with the help of naive Bayes classifier.Secondly, the study constructed the panoramic technology innovation map based on the semantic similarity between technology nodes and the innovation laws they involved.Finally, the study used technology proximity index and innovation cycle index to analyze the innovation type of technology evolution path. [Result/Conclusion] By taking the preparation technology of graphite anode material as an example, this study analyzes the technology evolution path and its innovation type, thus verifying the feasibility of the method proposed in this paper.

[Purpose/Significance] Integrated industrial chain development is pivotal for industrial transformation and upgrading, with technology collaboration serving as its core mechanism.Clarifying the current status and multidimensional characteristics of upstream, midstream, and downstream technology collaboration within industrial chains holds significant theoretical and practical value. [Method/Process] This study proposed a super-network construction methodology for technology collaboration in integrated industrial chain development, followed by a multidimensional characteristic analysis to reveal evolutionary trends.First, the study constructed three subnetworks-technological innovation collaboration, technology transfer collaboration, and technology licensing collaboration-using patent data, and integrated them into a technology collaboration super-network through node mapping.Next, the study analyzed the evolutionary dynamics of technology collaboration relationships, core collaborative communities, and collaboration patterns.Finally, an empirical study was conducted on the new display industry to validate the framework. [Result/Conclusion] The proposed analytical framework comprehensively captures multidimensional features of technology collaboration, demonstrating strong alignment with real-world industrial scenarios.It provides a systematic and standardized toolkit for systematically unveiling technology collaboration dynamics in industrial chains, while offering novel theoretical perspectives and methodological tools for future research on industrial chain collaboration.

[Purpose/Significance] This study aims to explore the components and practical strategies of data governance system of Singapore, and further promote development of data governance theories and methods. [Method/Process] With the case study of Singapore, Firstly, construction idea of main contents and characteristics of its data governance system could be identified: the construction idea indicates a developing concept of data empowerment, and data governance environment needed to be systematically built.Secondly, strategic plan was related to the overall national development, and it also needed to deploy systematic plan independently.Thirdly, the rule design highlights personal data protection, and other data practice needed to be expanded.Fourthly, construction of basic data platform was relatively complete, but data space building needed to be taken into consideration.Fifthly, organizational guarantee highlights multi-subject participation and capacity cultivation, and needed to fully deepen the cooperation mechanism. [Result/Conclusion] Therefore, based on the reality of our country, the revelatory strategies are proposed including construction of data governance environment under the guidance of data element view, data strategic plan with both open association and directional design, completion of multi-form rule system led by key management activities, integration construction of platform tool system under the guidance of data space, and comprehensive upgrading of data subject capabilities under the guidance of the State Data Bureau.

[Purpose/Significance] Open science is essential for tackling global challenges and advancing human development.As a global leader in open science, the Netherlands has cultivated a mature and comprehensive approach over several decades, offering valuable insights for China′s own open science initiatives. [Method/Process] This study first investigated the official websites of the Netherlands′ government and various social organizations to identify 19 typical cases of open science practices.Then conducted an in-depth analysis of these cases from three dimensions: open science policy documents, infrastructure, and public participation.Finally, the paper summarized the characteristics of open science practices in the Netherlands. [Result/Conclusion] Open science in the Netherlands adopts a strategic path that seeks international cooperation and builds local partnerships.It emphasizes national-level policy planning, balanced development of specialized and comprehensive infrastructure, and diversified forms of public participation.Based on China′s context, the study suggests that China should not only integrate with international open science initiatives but also strengthen domestic collaboration.Furthermore, China needs to accelerate the establishment of a national-level policy system, improve infrastructure, and emphasize public participation in open science.

[Purpose/Significance] There is a lack of direct evaluation indicators for the academic quality of journals, so it is difficult to evaluate the efficiency of academic exchanges. [Method/Process] In response to the above problems, creatively based on the input-output principle, a new index to measure the academic quality of journals—JQ index was proposed.It measured academic quality based on CNKI management journal and measured its academic communication efficiency. [Result/Conclusion] The research results show that the JQ index is an excellent index to measure the average academic quality of each paper in a journal; the academic communication efficiency of management journals is generally good; a few journals are in the stage of diminishing returns to scale, and their academic quality needs to be improved; measures should be taken in accordance with local conditions.Improve the academic communication efficiency of journals.

[Purpose/Significance] Quantifying the benefits yield from International Research Collaboration (IRC) is central to the national (regional) strategy of participating in IRC for advancement of scientific development. [Method/Process] By considering the total citations of each country's (region's) research articles as a measure for impact, the study, on the one hand, defined the general gain to depict the benefits in impact countries get from IRC, and on the other hand, defined the zero-sum gain to depict the benefits in competitiveness via IRC. [Result/Conclusion] Most countries (regions) are able to gain more impact via IRC, that is, the general gain.However, such general gain is normally less for countries (regions) with advanced domestic efficiency, leading to loss in competitiveness, that is, negative zero-sum gain.Through a cross-lagged multilevel model, the zero-sum gain is revealed to be more influential than general gain to drive countries' future competitiveness development, especially for those already-developed scientific systems.The present study may have taken a non-mainstream zero-sum viewpoint for global scientific research, but the results offer novel insights for academics and policymakers to rethink the research evaluation as well as strategies for IRC.

[Purpose/Significance] This study aims to examine the connotative positioning, dilemmas-obstacles, and operational strategies of organized scientific research, guided by major national strategic needs, with the objective of providing decision-making support for strengthening organized scientific research in China. [Method/Process] Firstly, the principal participants in China's organized scientific research were identified based on the three-helix model and an analysis of the actual operation of organized scientific research. Secondly, through a review of the literature and online research, the definition and principal roles of organized scientific research were established, and the obstacles and difficulties encountered in its implementation were summarized. Finally, recommendations were provided regarding operational strategies to enhance the efficacy of organized scientific research. [Result/Conclusion] This study identified the "five-helix participants in organized scientific research" in China and clarified the role of each participant in organized scientific research. It also found that organized scientific research in China faces problems such as a lack of a mechanism for summarizing scientific problems, an imperfect subject collaboration mechanism, an incomplete management and support system, and an imperfect talent development system. In light of these findings, the study put forth a series of operational strategies.

[Purpose/Significance] Clarifying the real demand of Sci & Tech supporting talents is the key to strengthening Sci & Tech supporting talents power and the focus of cultivating suitable Sci & Tech supporting talents. [Method/Process] Using the shortage talent catalog of Shanghai and the recruitment information of ISTIC as data sources, this paper analyzed and summarized the demand structural characteristics of Sci & Tech supporting talents for achieving self-reliance and self-improvement in Sci & Tech from macro and micro levels respectively, offering insights for talent cultivation of higher education system. [Result/Conclusion] In the process of building a strong country through Sci & Tech innovation, Shanghai and ISTIC require a considerable number of Sci & Tech supporting talents with broad perspectives, specialized knowledge in specific Sci & Tech field, and the ability to learn, research, and standardize problem-solving independently to empower self-reliance and self-improvement in Sci & Tech from the four dimensions of development strategy research, data intelligent management, innovation process service, and innovation quality control.The paper proposed suggestions for improving the adaptability of talent cultivation to social needs with promoting interdisciplinary convergence and real-world integration reforms systematically in graduate education.

[Purpose/Significance] With the complexity of social structure and the diversification of information channels, the response mode of major emergencies relying solely on the government faces many challenges.As an important component of response and governance resources, public online engagement can effectively enhance the effectiveness of emergency management and become an important issue of common concern in disciplines such as library and information science, and communication. [Method/Process] Th study systematically reviewed the research on public online engagement in major emergencies by integrating relevant literature, in order to reveal the research context, theoretical framework, and potential research directions in this field.Specifically, based on the concept tracing, it sorted out the time evolution, theoretical basis, methodology, and event types of public engagement in research.At the same time, the study focused on analyzing the antecedents, processes, and mechanisms of public engagement, and constructed a theoretical framework for public online engagement. [Result/Conclusion] Based on the review and analysis of previous literature, this study explores the potential development direction of AI empowerment and public online engagement in major emergencies in the post pandemic era from a new perspective, in order to enhance academic dialogue for public engagement in major emergencies and provide a new perspective for the management of major emergencies in China.

[Purpose/Significance] The study explores the application and limitations of large models in the open sharing of scientific data, with the aim of leveraging the technological empowerment effect of large models to assist in the digital-intelligent transformation and upgrading of open sharing of scientific data. [Method/Process] Combining data lifecycle theory and stakeholder theory, it outlined the logical path of applying large models to the open sharing of scientific data, analyzed the hidden risks and proposed governance measures. [Result/Conclusion] The study shows that firstly, large models can optimize the full lifecycle form of scientific data from the object dimension, and stimulate stakeholders' open sharing motivation from the subject dimension, thereby effectively driving the improvement of the quality and efficiency of scientific data open sharing; secondly, the application of large models brings data quality risks of dirty data and false data, data security risks of internal threats and external attacks, and data rights protection risks of empowerment and disempowerment; finally, it should be established an agile governance pattern that includes adaptive governance concepts, resilient governance mechanisms, and inclusive governance tools to balance the tension between promoting application and managing risks, and ensure the proper application of large models in the open sharing of scientific data.