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Construction of an Evaluation Indicator System for High-Quality Datasets in the Data Element Market Lin Zhenyang 　Wu Jiang　Hu Xin　Wang Jingxuan　Yuan Yiming　Du Le Journal of Information Resources Management    2025, 15 (6): 52-66.   DOI: 10.13365/j.jirm.2025.06.052 Abstract （397）      PDF（pc） （1252KB）（1015）       Knowledge map    Save This study aims to construct a scientific data quality evaluation indicator system as a fundamental basis for promoting the market-oriented allocation of data elements. It provides a quantitative benchmark for the transformation of data resources into assets and capital, thereby supporting the development of a value circulation mechanism in the data element market. Based on grounded theory, this study systematically analyzes policy documents, technical standards, and expert interview materials to build a multi-level evaluation indicator system comprising four main dimensions—compliance characteristics, scale-related attributes, content-specific properties, and value-oriented features—with 12 first-level indicators and 32 second-level indicators. This study further adopts the Analytic Hierarchy Process (AHP) and expert consultation methods to determine indicator weights and develop a practical, operable comprehensive evaluation model. Empirical validation through the selection of high-quality datasets in Hubei Province demonstrates the model’s effectiveness and practical applicability. The findings provide theoretical support and practical references for data asset valuation, improving data circulation efficiency, and optimizing value transformation pathways. Related Articles | Metrics | Comments（0）

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Research on the Intervention Mechanism of Public Opinion Information Dissemination in Deepfake Events Based on AIGC Yang Yangyang Journal of Information Resources Management    2026, 16 (1): 37-49.   DOI: 10.13365/j.jirm.2026.01.037 Abstract （392）      PDF（pc） （1312KB）（462）       Knowledge map    Save Based on trust theory and the characteristics of deepfake event public opinion information generated by artificial intelligence, this paper analyzes the impact mechanism of intervention strategies on system trust, interpersonal trust, emotional trust, and cognitive trust from three types of communication intervention strategies: information strategy, responsibility strategy, and behavior strategy, with the research framework of "intervention strategy-perceived trust-post-intervention trust". The study finds that information strategy indirectly and positively affects post-intervention trust through interpersonal trust and cognitive trust, responsibility strategy indirectly and positively affects post-intervention trust through system trust and emotional trust, and behavioral strategy indirectly and positively affects post-intervention trust through system trust and interpersonal trust, while control variables (gender, age, and education) have no significant impact on post-intervention trust. The influence of intervention strategies on perceived trust does not vary significantly across different gender types. Related Articles | Metrics | Comments（0）

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Bidirectional Influence of Media on the Emergence and Inhibition of Cyberbullying in Group Polarization Effect Ma Xiaoyue　Zhang Liubin Journal of Information Resources Management    2026, 16 (1): 23-36.   DOI: 10.13365/j.jirm.2026.01.023 Abstract （388）      PDF（pc） （2187KB）（670）       Knowledge map    Save The phenomenon of cyberbullying triggered by the group polarisation effect is endless and seriously disrupts social order, but the transformative relationship and internal structure between the group polarisation effect and cyberbullying are vague, and there is a theoretical blind spot. The study employed a combination of social support theory and qualitative comparative analysis to perform configuration analysis, as well as ordered logistic regression for supplementary testing. The study found that the emotional support framework is the trigger for cyberbullying and runs through most paths. The information support framework can induce negative emotions and is a prerequisite for cyberbullying. The tool support framework plays a more auxiliary role in cyberbullying by helping to construct the media environment. Finally, the evaluation support framework has a restraining effect on cyberbullying, though its effectiveness is affected by emotional fluctuations. Official intervention significantly impacts cases involving intense emotional turmoil, while artificial intelligence intervention and official media agenda-setting can suppress cyberbullying by shifting attention and defusing polarized positions. This study clarifies the process from the emergence of group polarisation tendencies to the development of cyberbullying, constructs a mechanism for integrating cyberbullying group dynamics, and provides a theoretical basis for cyberspace governance. Related Articles | Metrics | Comments（0）

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Factors Influencing the Communication Effect of Doctor-Produced Popular Health Science Short Videos Yong Yuhao　Li Xinyue　 Zhao Mengyuan　Ying Jun Journal of Information Resources Management    2026, 16 (2): 69-81.   DOI: 10.13365/j.jirm.2026.02.069 Abstract （376）      PDF（pc） （1536KB）（212）       Knowledge map    Save Focusing on doctors as the core communicators, this study develops a theoretical model based on theories of social presence, cognitive load, and media richness to investigate how multimodal features influence the dissemination effectiveness of health science short videos. Using a dataset of 2,683 health science short videos published by doctors on Douyin, we conducted regression analysis and robustness tests, integrating methods such as audio analysis, text mining, and image recognition. The study examines how video content formats and doctors' self-presentation characteristics affect dissemination effectiveness through mediating factors, including cue multiplicity, interactivity, authenticity, and emotional resonance. Results indicate that the inclusion of case analyses, evidence-based support, and highly cohesive language significantly enhances dissemination effectiveness. In contrast, explicitly prompting user interactions such as comments or likes, as well as emphasizing the doctor's professional identity or clinical setting, significantly reduces it. From the perspective of doctors' professionalism, this study clarifies the multimodal influencing mechanisms underlying the dissemination effectiveness of doctor-led health science short videos. It also enriches research perspectives on science communication via short videos, and offers practical insights for professional institutions and individuals engaged in health science popularization. Related Articles | Metrics | Comments（0）

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Cyberbullying Dissemination in Intelligent Society under Algorithmic Dual-roles: Trends, Motivations and Governance Paths Chen Ye　Xu Hao　Cheng Qingxuan Journal of Information Resources Management    2026, 16 (1): 10-22.   DOI: 10.13365/j.jirm.2026.01.010 Abstract （333）      PDF（pc） （2600KB）（376）       Knowledge map    Save The intelligent society amplifies the risks of cyberbullying dissemination, rendering traditional governance mechanisms ineffective. As a core technological component, algorithms serve dual-roles: both as enablers of cyberbullying and as potential restrainers. This paper investigates this dual-roles through literature review and theoretical analysis, systematically examining the dissemination trends of cyberbullying characterized by algorithmic empowerment and psychological dynamics. We dissect the operational mechanisms through which algorithms exacerbate cyberbullying via content fabrication, emotional manipulation, and conflict amplification, while simultaneously analyzing their counteractive potential through content suppression, environmental purification, and behavioral guidance. Building upon this dual-roles analysis, we propose a collaborative governance framework involving multi-stakeholder participation from governments, platforms, algorithm designers, and users. This paper contributes theoretical innovation and practical guidance for addressing cyberbullying governance challenges in intelligent society, offering insights into the synergistic optimization of technological governance and social regulation mechanisms. Related Articles | Metrics | Comments（0）

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An Exploration of the Core Categories and Knowledge System of Information Resources Management Discipline in China Ma Feicheng　Liu Zhenghao　Chen Shuaipu Journal of Information Resources Management    2026, 16 (3): 5-20.   DOI: 10.13365/j.jirm.2026.03.005 Abstract （333）      PDF（pc） （6209KB）（330）       Knowledge map    Save Since the renaming of Information Resources Management as a first-level discipline, the reconstruction of the core categories and knowledge system of the discipline has become a core issue in discipline development. This study, grounded in the contemporary context of constructing an independent knowledge system for Chinese disciplines, systematically discusses three core questions: the origin of the discipline, the meaning of its content, and the structure of its system. First, it extracts three core characteristics, “sequential annotation, in-depth revelation, and value transformation” from the historical logic of the discipline's evolution, establishing its essential core. Second, through comparative analysis and commonality extraction of the basic categories of the second-level discipline group, it constructs a core category system imbued with the philosophical wisdom of naming Information Resources Management as a discipline. Then, using these three characteristics as a logical starting point, it builds a theoretical framework for the knowledge system based on these core categories, positioning disciplinary knowledge along three dimensions: management object, management process, and management value, and presenting the abstract depth of knowledge through three levels: theory, method, and practice. This framework integrates and deepens the core categories, providing a systematic analytical tool for the construction of the knowledge system, research positioning, and academic evaluation of Information Resources Management. Finally, this article takes the research of Information Resources Management discipline in response to the questions of the people, China, the world, and the times as a clue, and clarifies the value orientation and future direction of the independent knowledge system. Related Articles | Metrics | Comments（0）

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Research on the Value of Data Assets Based on Scenario-Based Dynamic Assessment Xia Wenlei　Wei Zimeng　Yu Hui　Cui Wei Journal of Information Resources Management    2026, 16 (2): 25-39.   DOI: 10.13365/j.jirm.2026.02.025 Abstract （296）      PDF（pc） （5365KB）（268）       Knowledge map    Save This study focuses on the value differences and evolutionary patterns of data assets across distinct application scenarios, proposing a practical framework for scenario-based dynamic pricing. A system dynamics model is developed based on a dual-scenario classification of “self-use” and “transaction-oriented” data applications, structured around development, application, and risk dimensions. Simulation functions are embedded to capture coupling effects and time delays. Using Vensim , multi-scenario simulations and sensitivity analyses are conducted to identify key drivers and feedback loops in the value evolution process. The simulations show that development contributes foundationally to asset growth, application value demonstrates strong amplification effects, and risk control improves system stability. Flow efficiency, value derivation, and data integrity are identified as the most elastic variables influencing value outcomes. The proposed model offers a structured and adaptive approach to valuing data assets under diverse scenarios. Related Articles | Metrics | Comments（0）

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Value Co-creation in the Public Data Authorization and Operation Ecosystem: A System Dynamics Approach Chen Mei　Ding Fangxin Journal of Information Resources Management    2025, 15 (6): 82-95.   DOI: 10.13365/j.jirm.2025.06.082 Abstract （280）      PDF（pc） （6423KB）（213）       Knowledge map    Save This study aims to explore the value co-creation mechanisms within the public data authorization and operation ecosystem. Drawing on information ecosystem theory and value co-creation theory, this study applied grounded theory to analyze 13 public data authorization and operation policies, identifying the key components of the public data authorization and operation ecosystem: data entities, data, and data environment. We then constructed a system dynamics model to simulate the evolution of value co-creation and data outcome application over a 12-month period. The simulation results show that after an initial slow growth phase, both indicators increased significantly after two months. Sensitivity analysis further revealed the positive impact of six key factors on value co-creation: diversity of stakeholders, data governance capabilities, user demand, technological environment, policy environment, and market environment, with the data entity subsystem exerting a particularly significant impact. Related Articles | Metrics | Comments（0）

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From Emotional Fields to Topic Engagement: The Dual Mechanisms of Social Bots in Disseminating Misinformation Zhang Shiying　Ke Qing Journal of Information Resources Management    2026, 16 (1): 50-62.   DOI: 10.13365/j.jirm.2026.01.050 Abstract （277）      PDF（pc） （10577KB）（137）       Knowledge map    Save This study investigates the intrinsic mechanisms of social bots in disseminating misinformation from the dual perspectives of emotional fields and content topics. Drawing on a large-scale dataset of misinformation on Weibo, and employing methods including machine learning, zero-shot sentiment classification, BERTopic, and negative binomial regression, this research explores how social bots participate in misinformation propagation through dual pathways: group emotional fields and topic engagement heat. Key findings include: 1) social bots tend to engage more actively with public issues that have high social influence or are prone to controversy; 2) the involvement of bots significantly increases emotional entropy, thereby enhancing the diversity of collective emotional expression; 3) emotional polarization is more likely to emerge as a natural outcome of human user interaction rather than being directly triggered by bots; 4) both emotional entropy and emotional polarization exhibit dual effects and topic heterogeneity in influencing the virality of misinformation. This study provides a dual-dimensional analytical framework for understanding misinformation dissemination mechanisms in the era of human-bot symbiosis. Related Articles | Metrics | Comments（0）

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Research on the Overall Framework and Implementation Path of Data Circulation and Utilization in China: A Perspective Based on Data Infrastructure Construction Zhao Zheng　An Xiaomi　Guo Mingjun Journal of Information Resources Management    2025, 15 (6): 67-81.   DOI: 10.13365/j.jirm.2025.06.067 Abstract （273）      PDF（pc） （4974KB）（216）       Knowledge map    Save Accelerating the circulation and utilization of data to fully unleash its value relies on robust data infrastructure. This paper integrates domestic and international research foundations and current practices in data circulation and utilization, deeply analyzing the new demands that data elements place on infrastructure. It summarizes the latest trends in global infrastructure development, and based on this, addresses practical challenges such as trustworthy data supply, efficient processing, active circulation, and practical application. This paper proposes a comprehensive framework for data circulation and utilization, consisting of "one computational support base, two types of resource-coordinated scheduling, a three-tier efficient circulation system, and four-dimensional innovative integration demonstrations." It then provides specific recommendations for implementation at different stages, focusing on strengthening foundational support, optimizing circulation systems, and improving application ecosystems. These insights aim to offer valuable references for accelerating data infrastructure development and promoting efficient data circulation and utilization in the new era. Related Articles | Metrics | Comments（0）

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Construction of a Knowledge Graph for "Huoji Dang" Driven by Large Language Models Sui An　Tong Yongsheng　Gao Ning Journal of Information Resources Management    2026, 16 (1): 116-130.   DOI: 10.13365/j.jirm.2026.01.116 Abstract （246）      PDF（pc） （12578KB）（205）       Knowledge map    Save By constructing a knowledge graph of the Qing Yongzheng Imperial Workshop archives, this study systematically organizes the artefact-related information recorded in the Huoji Dang, thereby overcoming the fragmented limitations of traditional research and providing new perspectives and methodological support for the study of imperial artefacts in the Qing dynasty. The research employs large language models (LLMs) and prompt engineering techniques. After iteratively optimizing prompts and incorporating manual verification, the extracted data are stored in a Neo4j graph database, enabling the automatic transformation of unstructured data in the Huoji Dang into a structured knowledge graph. Results demonstrate that DeepSeek-V3 outperforms other LLMs across all evaluation metrics, with clear overall advantages. In sum, this method effectively and accurately extracts entities, attributes, and relationships, and the resulting knowledge graph clearly illustrates the organizational structure, production processes, and imperial aesthetic preferences embedded in the archives. Moreover, the proposed “LLM + prompt engineering” approach demonstrates strong transferability in addressing the automatic extraction of premodern texts, offering a valuable reference for similar studies. It realizes the structuring and visualization of textual information, thereby providing a systematic knowledge-sharing platform for research on Qing imperial artefacts. Related Articles | Metrics | Comments（0）

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Constructing High-Quality Enterprise Data Sets: Connotations, Characteristics, Logical Framework and Future Prospects Zhang Borui　Chen Tao　Hu Jie　Xia Yikun Journal of Information Resources Management    2026, 16 (2): 55-68.   DOI: 10.13365/j.jirm.2026.02.055 Abstract （240）      PDF（pc） （1720KB）（202）       Knowledge map    Save Analyzing the connotation, characteristics and logical framework of enterprise high-quality dataset construction is essential to unlocking data value and enabling firms' digital-intelligent transformation. This paper conceptualises enterprise high-quality datasets, identifies six core attributes, establishes a three-dimensional framework (value, scenario, technology) based on socio-technical systems theory to provide theoretical support for the construction of high-quality corporate datasets under the "AI Plus" background; subsequently, from the analytical perspectives of the data value chain and data life cycle theories, it constructs a five-dimensional model encompassing scenario demand perception, data resource weaving, knowledge resource extraction, data-knowledge integration and refinement, and a digital-intelligence service ecosystem; finally, in response to the practical dilemmas currently faced by enterprises, the study proposes targeted optimization strategies, suggesting that future efforts should focus synergistically on data scenario shaping, data aggregation and governance, data labeling optimization, and data security assurance to overcome the bottlenecks of high-quality dataset construction, enhance the value-enabling efficiency of data elements, and provide robust support for the digital-intelligence transformation and high-quality development of enterprises. Related Articles | Metrics | Comments（0）

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Research on Intelligent Intelligence Service Model for Industrial Technology Innovation: From the Perspective of Context-Driven Innovation Wei Jinyu　Mao Jin　Li Gang　Quan Zhibang Journal of Information Resources Management    2025, 15 (6): 5-19.   DOI: 10.13365/j.jirm.2025.06.005 Abstract （232）      PDF（pc） （9160KB）（579）       Knowledge map    Save From the perspective of context-driven innovation, this paper constructs a new intelligent intelligence service model for Industrial Technological Innovation (ITI) from two aspects: theoretical framework and applied implementation. The service theoretical framework proposes a construction pathway for the intelligence service model based on the 'demand mining-scenario depiction-service response' logical chain. The applied implementation guided by the theoretical framework, focuses on eight task scenarios, such as technology insights, R&D efficiency, and so on. Then we provide a detailed analysis of the implementation path and function of the ITI framework from service content and service methods, and intelligent intelligence service system architecture is proposed. This paper aims to deeply embed intelligent intelligence workflows into ITI scenarios, and promoting intelligence services towards context-based and intelligent approaches. It provides a new theoretical framework and implementation pathway for the development and practical application of science and technology intelligence in the intelligent era. Related Articles | Metrics | Comments（0）

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Adaptation to Local Conditions: Local Differentiated Paths and Configuration Analysis of Public Data Authorization and Operation Song Xinran　Li Ju　Lin Tong Journal of Information Resources Management    2026, 16 (1): 78-88.   DOI: 10.13365/j.jirm.2026.01.078 Abstract （232）      PDF（pc） （1094KB）（170）       Knowledge map    Save Public data authorization operation is a data development and utilization approach with Chinese characteristics. Analyzing the differentiated practical paths in various regions is of great significance for exploring and forming replicable, easily-promoted and sustainable data circulation and utilization operation models. Based on the information ecology theory, this paper conducts a configuration analysis of 25 cities that have carried out public data authorization operations using csQCA. The research finds that data quality and the official information field are necessary conditions for good public data authorization operation effects. Government-led early practice type, government-coordinated data empowerment type and market-driven ecological empowerment type are three paths with good practical effects, while system-to-be-built type and data system shortcoming type are two paths with poor practical effects. Data has dual attributes of private goods and public goods. Market-oriented and centralized systems are needed to guarantee different stages of data operation. Each region should choose an appropriate authorization operation path in line with its local conditions based on the data ecosystem. Related Articles | Metrics | Comments（0）

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Intelligent Innovation Evaluation Engineering： A New Paradigm for Scientific Research Innovation Evaluation in the Digital Intelligence Era Lu Wei　Huang Yong Journal of Information Resources Management    2026, 16 (2): 4-10.   DOI: 10.13365/j.jirm.2026.02.004 Abstract （227）      PDF（pc） （2134KB）（190）       Knowledge map    Save In the context of the digital intelligence era, the core challenge of scientific research innovation evaluation has evolved from partial improvements in metrics and methods to a structural dilemma where evaluation systems fail to operate stably and cannot be embedded in scientific research governance practices. This study proposes a new paradigm termed "Intelligent Innovation Evaluation Engineering", which reconstructs the organizational logic of evaluation activities from a systems engineering perspective. Supported by explainable artificial intelligence, grounded in open sharing as an institutional foundation, and realized through modular engineering integration, this paradigm comprises five synergistic modules: data integration and shared services, dynamic management of evaluation indicators, modeling of scientific research management processes, mapping mechanisms between indicators and processes, and intelligent tool construction. The objective is to upgrade scientific research innovation evaluation from fragmented and closed tool-based research to an integrated, open, and sustainable socio-technical system, thereby enhancing the reproducibility, interpretability, and embeddability of evaluation systems, facilitating deep integration of evaluation into the entire process of scientific research governance, and providing a systematic solution for modernization of scientific research governance in the digital intelligence era. Related Articles | Metrics | Comments（0）

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Drivers and Barriers in Science-to-Technology Transfer: An Empirical Study Based on Exponential Random Graph Model Ma Ming　Mao Jin　Zou Dangyi　Li Gang Journal of Information Resources Management    2025, 15 (6): 20-36.   DOI: 10.13365/j.jirm.2025.06.020 Abstract （222）      PDF（pc） （5208KB）（376）       Knowledge map    Save Investigating the mechanism of knowledge flow from science to technology helps understand how scientific progress drives technological innovation. Thus, this paper first constructed a "science-technology" knowledge transfer network composed of keyword citation. Then, using exponential random graph models, we integrated knowledge attributes with the knowledge transfer process in a modeling approach that simultaneously considered endogenous network structures. Finally, we conducted an empirical analysis based on scientific papers and patent data in the gene editing field from 1990 to 2018. We find that the high economic value of scientific and technological knowledge inhibits knowledge transfer, as rational actors tend to engage in exploitative innovation based on existing high-value knowledge. However, the convergence of economic value facilitates the transfer process by helping to reduce transfer barriers through moderate cognitive distance. The academic value of knowledge contributes to advancing the knowledge transfer process, but this effect is not statistically significant. Under the influence of homogeneity effects, knowledge novelty and geographic proximity have a positive impact on the formation of knowledge transfer relationships from science to technology. Meanwhile, comparison with random networks demonstrates that the citation behavior of technological knowledge toward scientific knowledge may not be influenced by semantic proximity or knowledge potential. These results demonstrate consistency across knowledge network simulation models in different time periods. Related Articles | Metrics | Comments（0）

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Information Behaviors and Influencing Factors in the Public’s Acquisition of Government-Disclosed Information during Public Emergencies Zhang Tairui　Li Yuelin　Zhang Jianwei Journal of Information Resources Management    2025, 15 (6): 96-111.   DOI: 10.13365/j.jirm.2025.06.096 Abstract （220）      PDF（pc） （2744KB）（179）       Knowledge map    Save This study aims to clarify the Public’s Acquisition of Government-Disclosed Information during Public Emergencies, explore the process of public information acquisition and its influencing factors, and corstruct a theoretical framework for information acquisition. The research employed semi-structured in-depth interviews and quqlitative data analysis to reveal the process of public information acquisition, and futher analyzed the characteristics and influcing factors in the process of public information acquisition through questionnaire surveys and logistic regression. The results indicate that three factors motivate the public to acquire information during emergency, such as information tracing, information comparison, and information supplementation, leading to acquisition behaviors migrate from passive information acquisition to active seeking. Additionally, the public’s preferences for information sources, information channels and information forms are influenced by various factors. This study helps the government to understand the process of public information acquisition during emergencies, and lays down a theoretical and practical foundation for improving the quality of information disclosure. Related Articles | Metrics | Comments（0）

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Measurement of Data Element Circulation Level in China: Theoretical Logic, Regional Differences and Dynamic Evolution Zhang Yanhong　Zhou Lexin Journal of Information Resources Management    2026, 16 (2): 40-54.   DOI: 10.13365/j.jirm.2026.02.040 Abstract （215）      PDF（pc） （5070KB）（149）       Knowledge map    Save Data circulation is the key to promote the transformation of data into production factors, and its circulation level is the core index to measure the marketization allocation efficiency of data elements. Based on resource endowment theory and technology potential energy theory, this paper constructs an index system for evaluating the circulation level of data elements, measures the circulation level of data elements in various regions of China from 2019 to 2024, and deeply analyzes the regional differences, structural causes and spatio-temporal dynamic evolution characteristics by using Dagum Gini coefficient, variance decomposition method, kernel density estimation and Moran index. The conclusions indicate that: The circulation level of data elements in China generally presents a right-leaning distribution pattern, with obvious regional gradient characteristics of "eastern leading, central accelerating catch-up, western and northeast lagging"; the overall difference of data elements circulation level in each region is convergent, among which regional difference is the main source of overall difference, and the eastern region contributes the most to regional difference; there is obvious spatial positive aggregation characteristics in the circulation level of data elements in China, and the "low-low" aggregation characteristics in western regions are dominant. The conclusion reveals the regional differences and evolution characteristics of data elements circulation level in China, which has important value for realizing the deep circulation interaction of data elements and the integration of national data market. Related Articles | Metrics | Comments（0）

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A Knowledge Recombination Prediction Framework Based on Heterogeneous Graph Neural Networks Ren Anxing　Yang Guancan　Xing Jiaxin　Zhang Zihe Journal of Information Resources Management    2025, 15 (6): 129-142.   DOI: 10.13365/j.jirm.2025.06.129 Abstract （211）      PDF（pc） （7595KB）（197）       Knowledge map    Save Knowledge recombination is pivotal for fostering innovation and interdisciplinary integration. Existing studies typically rely on homogenous knowledge networks for its early prediction, which fail to capture the intricate relationships between knowledge units and their associated entities, thereby constraining predictive performance. To address this limitation, this paper proposes a knowledge-recombination prediction framework based on heterogeneous graph neural networks. The framework integrates multiple heterogeneous entities and relations closely related to knowledge units, constructs an enriched heterogeneous knowledge network through diverse connection strategies, and employs a relation-aware graph convolutional network to predict potential recombination links. Empirical experiments in the cancer immunotherapy domain demonstrate that the proposed framework markedly outperforms traditional homogenous-network baselines, with the F1 score rising from 0.706 to 0.889. The results also confirm that connection strategies for heterogeneous nodes significantly influence predictive performance, underscoring the importance of heterogenous network design in knowledge-recombination prediction. Related Articles | Metrics | Comments（0）

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Early Identification of Breakthrough Papers from the Perspective of Innovation Scenario: An Application in the Biomedical Field Zhang Shuqian　Huang Shan　Mao Jin　Li Gang Journal of Information Resources Management    2025, 15 (6): 37-51.   DOI: 10.13365/j.jirm.2025.06.037 Abstract （206）      PDF（pc） （6249KB）（215）       Knowledge map    Save The timely and accurate identification of breakthrough scientific literature is of crucial strategic significance for the efficient allocation of scientific research resources, seizing the initiative in technological development, and enhancing national core competitiveness. However, existing identification methods have limitations such as single-dimensional indicators and insufficient recognition efficiency. From the contextual perspective of knowledge innovation, this study constructs a characteristic system that distinguishes breakthrough papers from ordinary papers from three aspects: knowledge foundation, research team, and academic attention, and proposes a machine learning-based early identification method for breakthrough papers. Experiments in the field of biomedicine show that the F1-score of the model in this study reaches 0.838, which verifies the effectiveness of the method. Among the factors, early-stage impact, number of references, and Price Index have the most significant impact on the model's recognition results. This study enriches and expands the theoretical framework and methodological system for breakthrough paper identification from the novel perspective of innovation context. Related Articles | Metrics | Comments（0）

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How Research Team Knowledge Background Composition Affects Knowledge Innovation: A Comparative Interdisciplinary Analysis Li Xinzhe　Lu Xiao Journal of Information Resources Management    2025, 15 (6): 143-156.   DOI: 10.13365/j.jirm.2025.06.143 Abstract （206）      PDF（pc） （9110KB）（242）       Knowledge map    Save This study examines how research team knowledge background composition affects the knowledge innovation across eight major scientific fields by analyzing 32.63 million co-authored papers from the Crossref dataset spanning 1945-2023. Using Monte Carlo simulation and natural language processing, this study developed metrics to characterize team knowledge background composition, including internal knowledge similarity among team members and external knowledge similarity among teams. It was found that (1) Different knowledge background compositions exhibit significant differences in their capacity to generate knowledge innovation, with specific team knowledge background compositions demonstrating markedly superior innovation capabilities compared to others, indicating that team knowledge background composition has a decisive impact on knowledge innovation; (2) Each field has its own optimal team knowledge background composition: physics favors diverse teams with differentiated research directions, while social sciences perform better with specialized team compositions, suggesting that innovation policies should be tailored to specific disciplines; (3) Optimal team knowledge background compositions consistently represent only a minority across all fields, indicating structural misalignment in current research systems; meanwhile, despite exponential growth in publication volume, high-level knowledge innovation output remains constant across fields, revealing a "carrying capacity" phenomenon that highlights the disconnect between research scale expansion and knowledge innovation. These findings have important implications for scientific practice and policy development. Related Articles | Metrics | Comments（0）

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Breakthroughs and Reconstruction: The Theoretical Innovation Path of the Independent Knowledge System of Information Resources Management in China Xia Lixin　Yu Huajuan Journal of Information Resources Management    2026, 16 (3): 30-41.   DOI: 10.13365/j.jirm.2026.03.030 Abstract （204）      PDF（pc） （1708KB）（251）       Knowledge map    Save Theoretical innovation in the independent knowledge system of Information Resources Management(IRM) discipline in China is a new mission and new responsibility entrusted by the new era and the new journey, and an inevitable requirement for distilling, summarizing, and solving problems in IRM. This paper first uses literature analysis and historical research methods to systematically review the evolutionary trajectory of theoretical research in China's IRM discipline, from initial formation, indigenous exploration, and integrated development to independent innovation, and reveals the driving mechanisms behind the discipline's theoretical development. Then, focusing on the three core elements of concepts, principles, and paradigms, it proposes a breakthrough scheme for theoretical innovation that reshapes a system of distinctive identifying concepts, distills basic principles grounded in Chinese practice, and innovates characteristic research paradigms. Finally, from the three dimensions of autonomy, collaboration, and leadership, a theoretical framework is proposed for transitioning from element-level innovation to holistic reconstruction. The theoretical innovation geared toward the independent knowledge system of China's IRM discipline helps give full play to the discipline's theoretical support role in major strategic tasks such as achieving scientific and technological self-reliance and strength, cultural inheritance and innovation, and national security governance. It ultimately forms a theoretical system of IRM with Chinese characteristics that bears China's identifying marks and is capable of participating in global dialogue, thereby enhancing the discipline's capacity to serve national strategies and its international academic discourse power. Related Articles | Metrics | Comments（0）

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International Development of Marine Data Resource Exploitation System and China's Response Mei Ao　Zhang Jiayi Journal of Information Resources Management    2026, 16 (1): 4-9.   DOI: 10.13365/j.jirm.2026.01.004 Abstract （196）      PDF（pc） （683KB）（200）       Knowledge map    Save The development and utilization of marine data resources is an important part of digital economic development. Under the framework of the United Nations Convention on the Law of the Sea, all countries in the world carry out in-depth cooperation and promote the development and utilization of international marine data resources. China's marine data governance has ushered in new strategic opportunities and challenges, and going to deepen marine cooperation among countries under the guidance of the concept of "ocean community of shared future". Through sorting out the current situation of the development and utilization of marine data, there are deficiencies in both the development and utilization phases, and further explanations of the corresponding strategies are made based on the goal of building a marine power, and feasible suggestions for development and utilization of marine data in China and the world are put forward. Related Articles | Metrics | Comments（0）

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Research on Industrial Technology Foresight Based on Patent Value Evaluation and Topic Mining from the Perspective of Fast and Slow Patent Comparisons: Taking Smart Grid as an Example Zhu Mengping　Shi Guoliang　Gao Yimin Journal of Information Resources Management    2026, 16 (1): 101-115.   DOI: 10.13365/j.jirm.2026.01.101 Abstract （196）      PDF（pc） （4370KB）（125）       Knowledge map    Save Firstly, this study constructs a three-dimensional technology foresight framework integrating "technological value, structural relatedness, and examination timeliness" by developing a multi-dimensional patent value evaluation system, employing the entropy-weighted TOPSIS method and multiple linear regression models to derive comprehensive patent value scores and influencing factors. Second, patent datasets are categorized based on examination speed, and BERTopic model are applied to identify the technological themes, enabling a comparative analysis of their thematic distributions. Finally, a three-dimensional technology foresight mapping framework is developed, incorporating theme value, theme relevance, and average examination duration to delineate the technological prospects embedded in fast and slow patents. Taking the smart grid sector as an example, the findings reveal that within the dimension space defined by high thematic relevance and high thematic value, slow patents demonstrate stronger technological prospect potential compared to fast patents. Based on these insights, strategic recommendations are proposed to assist senior R&D managers in effectively advancing innovation. Related Articles | Metrics | Comments（0）

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An Interdisciplinary Perspective on Building an Independent Knowledge System for Information Resources Management in China Huang Cui　Shen Yutian Journal of Information Resources Management    2026, 16 (3): 78-91.   DOI: 10.13365/j.jirm.2026.03.078 Abstract （194）      PDF（pc） （4647KB）（254）       Knowledge map    Save Against the backdrop of major national strategies such as the 15th Five-Year Plan and the Outline for Building China into a Leading Country in Education, interdisciplinarity has become an important practical context and intrinsic requirement for building an independent knowledge system. Taking an interdisciplinary perspective, this paper examines how disciplinary independence can be established, sustained, and expanded in the digital and intelligent era, and systematically analyzes the necessity, practical tensions, framework, and pathways for building an independent knowledge system for Information Resources Management in China. The study argues that disciplinary independence from an interdisciplinary perspective does not imply closure or self-containment. Rather, it requires maintaining disciplinary subjectivity through open interdisciplinary engagement, systematizing knowledge through transformation, and generating sustained knowledge contributions in response to China-specific problems. To this end, the building of such a system should be guided by the balance between preserving disciplinary foundations and pursuing innovation, with the coordinated advancement of the disciplinary system, academic system, and discourse system as its goal. Through the knowledge transformation mechanism of identification, internalization, and expansion, and the subjectivity-sustaining mechanism of foundation-building, interaction, and reinforcement, knowledge gains generated through interdisciplinary innovation can be transformed into accumulable theoretical, methodological, and discursive resources, thereby promoting the coordinated restructuring of the disciplinary system, academic system, and discourse system. This paper provides an explanatory framework for understanding where disciplinary knowledge comes from, why it becomes usable, and how it can be transformed into locally grounded theories and methods. It also offers a mechanism-based practical pathway for enabling Information Resources Management in China to move from knowledge borrowing to knowledge self-reliance and from passive incorporation to active shaping through open and integrative development. Related Articles | Metrics | Comments（0）

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Review Research on Measuring Scientific Contributions of Academic Papers: Identification, Classification, and Intensity Wei Huanan　Ding Jielan1　Liu Xiwen Journal of Information Resources Management    2025, 15 (6): 157-171.   DOI: 10.13365/j.jirm.2025.06.157 Abstract （191）      PDF（pc） （1632KB）（349）       Knowledge map    Save This study systematically reviews research related to the scientific contributions of academic papers in the field of scientometrics, summarizes research methods and the latest progress, and aims to provide reference and guidance for subsequent research. By reviewing relevant domestic and international literature, this study first defines and analyzes the core concepts and connotations of the scientific contributions of academic papers. Subsequently, from a methodological perspective, it provides a detailed description and summary of the identification, classification, and intensity measurement of scientific contributions of academic papers. This study shows that the measurement of scientific contributions of academic papers is an emerging research field that is rapidly developing and requires further development and improvement. In the future, research can deepen the theoretical study of the mechanisms underlying the scientific contributions of papers and refine the measurement methods for fine-grained scientific contributions, such as theoretical contributions, methodological contributions and data contributions, and advance the application research of large language models in measuring the scientific contributions of papers. Related Articles | Metrics | Comments（0）

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Research on the Mechanism and Effect of Data Elements Empowering Urban Community Resilience from a Full Life Cycle Perspective Chen Yingxin　Ge Ran　Ping Shanshan　Ding ding Journal of Information Resources Management    2026, 16 (1): 63-77.   DOI: 10.13365/j.jirm.2026.01.063 Abstract （187）      PDF（pc） （5186KB）（284）       Knowledge map    Save In the context of the development of new quality productive forces, accelerating the digital transformation of communities to enhance community resilience has become the core orientation and fundamental demand of grassroots community governance. Based on the perspective of the whole life cycle of data, the hybrid method of Structural Equation Model (SEM) and BP Neural Network was used to empirically analyze the resilience changes of different types of communities under the influence of data elements, and reveal the mechanism and effect of data-empowered community resilience. The research results are as follows: data production, data integration and data application have different impacts on the physical, social, institutional and cultural resilience of communities, respectively. The community refined consultation governance model promotes data integration and sharing, breaks down departmental barriers and the phenomenon of "digital suspension", and improves the physical and social resilience of communities. Under the basic national conditions of China's population aging, the phenomenon of "silver digital divide" reduces the overall data utilization level of communities, resulting in a decrease in the institution resilience of communities. The dual blessing of community refined consultation governance and the development of community digital technology has made up for the shortcomings of the aging community population, and the overall level of community resilience has been improved. Related Articles | Metrics | Comments（0）

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From Interaction to Collaboration: The Evolution of Human-AI Relations in the Era of Digital Intelligence: A Book Review of Human-AI Interaction and Collaboration Xia Lixin Journal of Information Resources Management    2026, 16 (2): 166-168.   DOI: 10.13365/j.jirm.2026.02.166 Abstract （182）      PDF（pc） （517KB）（110）       Knowledge map    Save How are interaction patterns between users and artificial intelligence systems evolving in the era of digital intelligence? Through the construction of theoretical frameworks, the description of application scenarios, and the identification of potential risks, Human-AI Interaction and Collaboration provides a comprehensive analysis of the underlying logic of human-AI interaction and collaboration. The book posits "human-centered" as the paramount principle for AI systems and offers a detailed examination of how factors such as user perception, system design, and human-AI relations influence the efficacy and outcomes of collaborative synergy. While proposing mitigation strategies for potential risks, this work showcases the vast prospects of human-AI collaboration across multidisciplinary domains, including healthcare, scientific research, and finance. This work provides a theoretical foundation for future research in this field and serves as an ethical compass for AI system designers. Related Articles | Metrics | Comments（0）

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How is Autonomy Possible: The Evolutionary Pathway and Methodology of Constructing an Independent Knowledge System for Information Resources Management in China (1978-2025) Zhang Jiuzhen　Bu Yi　Xia Huichuan　Wang Pianran　Zhou Ya Journal of Information Resources Management    2026, 16 (3): 42-52.   DOI: 10.13365/j.jirm.2026.03.042 Abstract （181）      PDF（pc） （845KB）（245）       Knowledge map    Save This study explores the evolutionary pathway and methodology of constructing an independent knowledge system for the discipline of Information Resources Management in China from 1978 to 2025. It proposes analyzing disciplinary autonomy through four dimensions: the knowledge core, methodology, norms, and discourse. The study reveals that this autonomy has undergone a dialectical developmental process, evolving from "ontological consciousness" to "methodological self-reliance", and finally toward "paradigmatic guidance". The study indicates that the discipline's autonomy is rooted in the dual drivers of national strategic demands and complex local practices, and is realized through specific pathways such as technological absorption and local adaptation, as well as the integration of theoretical reflection and engineering practice, ultimately aiming to serve national development and engage in global academic dialogue. Related Articles | Metrics | Comments（0）

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Discovery and Evolution Prediction of Internet Meme Based on Dynamic Knowledge Graph Hong Liang　Lin Zhiyu Journal of Information Resources Management    2026, 16 (2): 140-153.   DOI: 10.13365/j.jirm.2026.02.140 Abstract （180）      PDF（pc） （10317KB）（112）       Knowledge map    Save To address the limitations of existing methods for detecting internet memes because of their irregular expressions, rapid propagation, and ambiguous semantics, this study proposes a collaborative framework that integrates a dynamic knowledge graph with retrieval-augmented generation. By constructing an adaptively updated knowledge graph and leveraging the contextual understanding capabilities of large language models, the proposed framework enables accurate identification and evolutionary trajectory tracking of internet memes. Experiments conducted on a self-built social media corpus demonstrate that the proposed method effectively overcomes the time-lag limitations of traditional static models and the lack of interpretability inherent in black-box models. It achieves superior performance in memes detection compared to mainstream baseline models. Furthermore, the study provides an in-depth analysis of the advantages and challenges of the graph-based retrieval-augmented strategy in handling noisy and unconventional expressions, and systematically validates the contribution of the proposed framework to overall performance. Finally, a case study of real-world internet memes evolution is presented to verify the effectiveness of the framework, offering support for real-time perception and in-depth analysis of highly noisy and rapidly evolving internet language phenomena. Related Articles | Metrics | Comments（0）

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Structural Morphology and Generative Mechanisms of the Independent Knowledge System in Information Resources Management in China Shi Jing　Wang Jiajie　Chen Guo Journal of Information Resources Management    2026, 16 (3): 132-146.   DOI: 10.13365/j.jirm.2026.03.132 Abstract （179）      PDF（pc） （5386KB）（734）       Knowledge map    Save Constructing an independent knowledge system with Chinese characteristics constitutes a fundamental mission for the discipline of Information Resources Management (IRM) to establish its academic subjectivity and achieve high-quality development. Existing studies have largely focused on macro-level normative discussions, with limited attention to the micro-level logic of knowledge organization and its underlying generative mechanisms. To address this gap, this study treats concepts as the basic units of knowledge systems and introduces an evolutionary framework of domain knowledge growth, proposing a dual-layer analytical framework based on conceptual semantic space and knowledge structural space. Based on the paper data of representative journals in the field of IRM from 2016 to 2025, the abstract notion of a knowledge system is operationalized into measurable network indicators and examined across four levels: knowledge unit, knowledge linkage, knowledge community, and system structure. The findings reveal that: First, at the knowledge unit level, disciplinary concepts exhibit a distribution in semantic space characterized by strong practical orientation and policy-driven dynamics, where highly independent and original concepts function as strategic anchors for knowledge generation. Second, at the knowledge linkage level, policy-led concepts and bridging concepts centered on disciplinary restructuring are increasingly intertwined, breaking down traditional barriers among subfields. Third, at the knowledge community level, multiple functionally differentiated knowledge communities have emerged, including high-level clusters integrating theory and practice. Fourth, at the system structure level, clusters of highly identifiable concepts underpin the development of disciplinary, academic, and discourse systems of IRM with Chinese characteristics. Based on these measurements, this study identifies four core generative modes driving the formation of the independent knowledge system: macro-level strategic and policy discourse-driven mechanisms; institutional restructuring and internal disciplinary reflection; integration of theory and practice with scenario expansion; and the inheritance of historical-cultural traditions alongside the excavation of indigenous experience. This research not only achieves a structural measurement of the autonomy of the “three systems”, but also provides an analytical paradigm and empirical evidence for advancing the construction of independent knowledge systems in philosophy and social sciences. Related Articles | Metrics | Comments（0）

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Research on the Early Identification Method of Breakthrough Achievements from the Perspective of Knowledge Flow Ye Qing　Wang Yezhu　Xie Yundong　Zhang Peng Journal of Information Resources Management    2026, 16 (2): 111-124.   DOI: 10.13365/j.jirm.2026.02.111 Abstract （174）      PDF（pc） （5755KB）（149）       Knowledge map    Save Breakthrough research drives greatly advances in science and technology, and expands the boundaries of human knowledge. The early identification of such achievements is essential for forward-looking basic research planning, the efficient allocation of scientific resources, and the formulation of national innovation strategies. However, existing studies on the identification of breakthrough achievements often focus on a single-dimension rather than an integrated theoretical framework, and few adequately explore the early formation mechanisms of breakthrough achievements. To address these limitations, this study proposes a theoretical framework that grounded in knowledge flow theory, encompassing the process of knowledge input, knowledge production, and knowledge output. Based on this framework, a multi-dimensional early identification index system comprising 15 indicators is constructed by integrating features across the three stages. Multiple machine learning algorithms are then employed to build identification models, from which the most effective model is selected. Finally, SHAP is applied to interpret the model and to quantify the relative importance and contributions of different features in the identification process. The results indicate that: ① the CatBoost model demonstrates the best performance in early identification. ② three key early signals are particularly influential, which are citations within five years, disruption index within five years in the knowledge output stage, and the author's highest academic achievement in the knowledge production stage. ③ the model exhibits strong generalization capability when it verified by APS milestone papers. Overall, this study proposes a novel paradigm that integrates predictive accuracy with interpretability for the early identification of breakthrough research, and provides evidence for understanding its early formation mechanisms. Related Articles | Metrics | Comments（0）

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Identification of Citation Intent in Academic Literature Based on Prompt Learning with Multi-Task Learning Zhang Xiaojuan　Guo Jiarun　Wang Jiahui　Liu Yijun Journal of Information Resources Management    2026, 16 (2): 125-139.   DOI: 10.13365/j.jirm.2026.02.125 Abstract （172）      PDF（pc） （5907KB）（140）       Knowledge map    Save The automatic identification of citation intentions in academic literature contributes to a deeper understanding of academic paper content and facilitates the development of a more equitable framework for scientific research evaluation. To improve the accuracy and generalizability of citation intention recognition in low-resource scenarios, this study proposes a novel framework that integrates prompt learning and multi-task learning, First, the main task of automatic citation intent recognition is jointly trained with two auxiliary tasks: citation value identification and citation section identification. All three tasks are unified within a P-tuning-based prompt learning framework. In this setup, discrete prompt tokens are first transformed into continuous vectors by a multi-layer perceptron. These vectors are then combined with the input text to form the input sequence, effectively converting the classification task into a cloze-style prediction. Furthermore, the label word set is expanded, and a weighted averaging method is applied to select the label with the highest score as the final prediction. Finally, a soft parameter sharing mechanism is employed to achieve collaborative optimization across the three tasks for citation intent recognition. Experimental results on two publicly available datasets, ACL-ARC and SciCite, demonstrate that the proposed model significantly outperforms baseline and other prompt learning models under varying sample sizes. Additionally, the two auxiliary tasks effectively improve the accuracy and generalizability of citation intent recognition. Related Articles | Metrics | Comments（0）

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Measurement of Digital Economic Development Level and Spatiotemporal Evolution Analysis of China's Border Areas Xu Qian　Sha Yongzhong　An Yifang　Niu Chunhua Journal of Information Resources Management    2026, 16 (2): 11-24.   DOI: 10.13365/j.jirm.2026.02.011 Abstract （167）      PDF（pc） （4423KB）（144）       Knowledge map    Save A comprehensive portrayal of the development and changing trends of the digital economy in China's border areas is not only an inherent requirement for the coordinated promotion of Digital China construction across regions, but also a key component in embedding border area development into the overall Chinese path to modernization. This study considers both national orientation and regional characteristics, constructs an indicator system for the development of the digital economy in border areas, systematically measures the level of digital economy development in border areas from 2011 to 2024, and analyzes the characteristics of spatiotemporal evolution. The study found that: ① The digital economy in the nine border provinces and autonomous regions is showing a growth trend, but there are significant regional differences, with a gradient pattern of "northeast > southwest > northwest"; ② The development of the four subsystems of digital infrastructure, digital industrialization, industrial digitalization, and digital governance is uneven; ③ The spatial center of gravity of the digital economy has undergone phased migration with 2017 as a turning point. This study is helpful for re-examining the geopolitical value and economic and social development characteristics of border areas in the new era, and can provide a reference for exploring differentiated development paths of the digital economy in border areas. Related Articles | Metrics | Comments（0）

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Journal of Information Resources Management    2025, 15 (6): 4-4.   Abstract （164）      PDF（pc） （294KB）（224）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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A Framework and Path to the Independent Knowledge System of China's Information Resources Management Discipline from a Global Perspective Li Yuelin　Fan Zhenjia　Liu Tingxiao Journal of Information Resources Management    2026, 16 (3): 92-103.   DOI: 10.13365/j.jirm.2026.03.092 Abstract （164）      PDF（pc） （851KB）（131）       Knowledge map    Save The renaming of Information Resources Management(IRM) as a first-level discipline marks a new stage of theoretical restructuring and independent system building. In recent years, regarding the construction of an independent knowledge system for China's IRM discipline, stage-specific achievements have been made in the systematic integration spanning from the global knowledge ecosystem, the distillation of Chinese wisdom, the transformation of international narratives, and discourse operation mechanisms, to the evaluation of international communication efficacy. This study examines the opportunities and challenges facing the construction of China's independent knowledge system in IRM from the perspective of global knowledge ecology and disciplinary competition. It discusses narrative reconstruction in international dialogue, analyzes the dynamic mechanisms through which the knowledge system moves from internal construction to external communication, and proposes a multidimensional analytical framework for evaluating international promotion effectiveness. On this basis, this study develops an interpretive framework consisting of "global ecological scanning and China's positioning—expression dilemmas and narrative reconstruction—discourse mechanism construction—evaluation of international promotion effectiveness" . The study aims to promote the discipline's shift from accumulated experience to systematic construction and from passive interpretation to active expression. Related Articles | Metrics | Comments（0）

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The Impact of International Mobility on the Early Career Development of Researchers Huang Xiaoyan　Pan Xuelian　Wu Rui　Zhai Yuanyuan Journal of Information Resources Management    2026, 16 (1): 142-154.   DOI: 10.13365/j.jirm.2026.01.142 Abstract （163）      PDF（pc） （1073KB）（117）       Knowledge map    Save Doctoral students in the field of economics and management funded by Chinese Scholarship Council(CSC) are selected as the samples of the experimental group, and the Propensity Score Matching method is used to find the control group of individuals without international mobility experience. Based on this, logistic regression models are developed to systematically evaluate the impact of international mobility on the early career development of researchers, focusing on three dimensions: prestige of initial employing institution, early promotion to senior title, and acquisition of scientific fundings. The study finds that international mobility significantly increases the likelihood of researchers obtaining initial positions at prestigious institutions, accelerates their promotion to senior titles, and speeds up their access to scientific scientific fundings in early career stages. The positive effects are stronger for male researchers, but females also benefit significantly. For graduates from 985 universities, international mobility plays a stronger role in facilitating their initial employment at prestigious institutions and early promotion to senior titles, while for those from non-985 institutions, international mobility is more effective in accelerating the acquisition of national-level scientific fundings in early career stages. Long-term international mobility experiences (over 12 months) are significantly more beneficial for researchers’early career development than short-term mobility. Related Articles | Metrics | Comments（0）

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An Inquiry into the Conceptions of Intelligence, Information and Knowledge in the Context of Representative Axiological Systems of Traditional Chinese Culture Ma Jie 　Gu Yingchi　Dai Yunsong　Hou Yiling Journal of Information Resources Management    2026, 16 (3): 65-77.   DOI: 10.13365/j.jirm.2026.03.065 Abstract （162）      PDF（pc） （6597KB）（376）       Knowledge map    Save The views of intelligence, information, and knowledge serve as the three core concepts within the discipline of Information Resources Management, consistently underpinning its development. Chinese traditional culture boasts a long and profound history, rich in intellectual heritage. Therefore, this study adopts a Chinese philosophical perspective, employing the representative value theories of Confucianism, Mohism, Daoism, and Legalism within Chinese traditional culture as analytical tools to systematically interpret and refine these three views. Through conceptual analysis, the core inquiries of the three views are distilled: the view of intelligence focuses on service orientation, mode of operation, and reliability; the view of information focuses on strategic assets, effectiveness realization, and systemic balance; the view of knowledge focuses on transcendental pathways, cognitive frameworks, and practical orientation. Subsequently, sixteen value dimensions, including people-oriented governance, benefitting the people, institutional framework, holistic perspective, objectivity, and integrity, are extracted from the philosophies of Confucianism, Mohism, Daoism, and Legalism, thereby achieving a coherent alignment between contemporary disciplinary inquiries and traditional intellectual resources. This alignment not only strengthens the cultural foundations of existing disciplinary concepts but also further refines their system of value dimensions. This study elucidates the inherent logic through which traditional Chinese values and resources empower disciplinary development, providing corresponding theoretical grounds and perspectives to facilitate the transition of information resource management research from " functional expansion" toward " value consciousness", thereby contributing to the construction of a disciplinary theoretical framework with distinct Chinese autonomy. Related Articles | Metrics | Comments（0）

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Research on Influencing Factors of Individual Protective Behavior in Public Health Emergencies Based on CAC Paradigm Wang Xiao　Lin Zhonghui　Wang Yuyang　Chen Sijing　Duan Yaoqing Journal of Information Resources Management    2026, 16 (1): 89-100.   DOI: 10.13365/j.jirm.2026.01.089 Abstract （160）      PDF（pc） （2309KB）（139）       Knowledge map    Save Based on the Cognition-Affect-Conation (CAC) paradigm, we constructed a model of the influencing factors of individual protective behaviors in public health emergencies. 379 questionnaires were collected through an online survey, and the Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for empirical analysis to investigate the mechanisms of risk perception, negative emotions, information seeking behaviors, and individual protective behaviors in public health emergencies. The results show that the perceived severity and uncontrollability of risk have a significant positive effect on fear and anxiety, and anxiety has a significant positive effect on individual protective behaviors. Meanwhile, the perceived severity and uncontrollability of risk indirectly affect individual protective behaviors through anxiety. Information seeking behaviors have a significant moderating effect on the mediating effects. This study establishes an analytical framework for the study of individual protective behaviors in public health emergencies from the perspective of the correlation paths of cognition, emotion, and conation, which is conducive to optimizing the risk communication mechanism for emergencies and enhancing the implementation effectiveness of risk governance measures. Related Articles | Metrics | Comments（0）

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Study on Factors Influencing the Enterprises’ Participation Intention in the Construction of the National Smart Elderly Care Data Resource System Sun Shiwei　Ang Enqi　Yan Zhijun Journal of Information Resources Management    2025, 15 (6): 112-128.   DOI: 10.13365/j.jirm.2025.06.112 Abstract （157）      PDF（pc） （1063KB）（131）       Knowledge map    Save To address the current insufficiency in the study of the motives of smart elderly care enterprises to participate in the construction of the national data resource system, this study adopts a combination of grounded theory and empirical analysis. Firstly, it identifies the main factors influencing the participation of smart elderly care enterprises in the construction of the national data resource system through qualitative analysis methods. Secondly, it uses regression analysis to further verify the impact of these factors on the participation motives of enterprises. The research results show that the cognitive level of the data resource system, technical security, support from top management of enterprises, and organizational readiness have a significant positive impact on the participation willingness of enterprises. At the same time, government support and the perception of social transformation have a moderating effect on this process. This paper fills the theoretical gap in the construction of smart elderly care data resource systems based on enterprises as the participating subjects, provides inspiration for future research on smart elderly care data resource systems, and also offers important references for the country to enhance the enthusiasm of enterprises to participate in the construction of the smart elderly care data resource system. Related Articles | Metrics | Comments（0）