Most Downloaded

Published in last 1 year| In last 2 years| In last 3 years| All| Most Downloaded in Recent Month | Most Downloaded in Recent Year|

Published in last 1 year

Please wait a minute...


For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails

Select

Research on Innovative Evaluation of Academic Papers Based on Reorganized Content of Knowledge Units Chang Xia　Wei Xuqiu　Zhang Yidi　Li Zehan Journal of Information Resources Management    2025, 15 (4): 144-156.   DOI: 10.13365/j.jirm.2025.04.144 Abstract （222）      PDF（pc） （2257KB）（1160）       Knowledge map    Save As one of the scientific and technological innovation achievements, an accurate evaluation of the innovation of academic papers is helpful to stimulate the innovation vitality of researchers, guide the direction of scientific research correctly, and improve the quality of scientific research achievements. Innovative knowledge units are the basis for evaluating the innovation of academic papers. Based on the perspective of breakthrough reorganization and progressive reorganization of knowledge units, this study divides the combination of knowledge units into three types: “new knowledge unit-new knowledge unit”, “new knowledge unit-old knowledge unit” and “old knowledge unit-old knowledge unit”. Secondly, based on three types of knowledge unit combination and four aspects of knowledge unit combination emergence, the innovative evaluation model of academic papers is constructed. Taking the field of digital humanities as an example, the empirical research shows that the method can effectively identify the novel knowledge unit combination; the academic papers selected from the perspective of knowledge unit reorganization are highly innovative in terms of research methods and research content. Related Articles | Metrics | Comments（0）

Select

A Comparative Study on User Behavior and Learning Effect Between Conversational Search in AIGC Environment and Traditional Search Zhao Yiming　Yu Xinjie　Chen Yijin　Zhang Xin　Yang Yunhe Journal of Information Resources Management    2025, 15 (4): 56-71.   DOI: 10.13365/j.jirm.2025.04.056 Abstract （350）      PDF（pc） （3297KB）（888）       Knowledge map    Save This study compares the differences between generated AI supported conversational search and traditional web search in user information search behavior and learning outcomes. Combined with the cognitive load theory, this study explores the information acquisition efficiency, learning outcomes and user experience of users using the two systems in various learning search situations, aiming to deeply understand the characteristics of user information search behavior and help improve the information search and learning outcomes. The experimental method was used to collect the index data, the experimental subjects were divided into a conversational search and a traditional web search group, and the user's learning information search behavior was divided into information seek behavior, information selection behavior and information utilization behavior. The learning search outcomes were divided into five dimensions, and a linear regression model was used to compare the differences in information search behavior and learning effect between the two groups of users. Results show that users' use of conversational search system can improve the learning outcome by reducing the cognitive load, and also make part of the user's information search behavior more complex. This study provides theoretical support for revealing the cognitive mechanism behind users' information search behavior and learning outcome differences, broadens the research vision of "search as learning", and provides practical enlightenment for improving the interactive design of the functions of conservational search and traditional web search system and providing learning information service functions. Related Articles | Metrics | Comments（0）

Select

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 （182）      PDF（pc） （1252KB）（685）       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）

Select

Influencing Factors of Discontinuous Usage Behavior of Mobile Short-Form Video Users: A Systematic Literature Review Dai Bao　Zheng Yiqing　Yang Liying Journal of Information Resources Management    2025, 15 (5): 131-146.   DOI: 10.13365/j.jirm.2025.05.131 Abstract （265）      PDF（pc） （1486KB）（488）       Knowledge map    Save This paper aims to explore the factors influencing the discontinuous usage behavior of mobile short-form video users, with the purpose of providing theoretical guidance for operators to develop effective user retention strategies and offering insights for deepening related studies. Based on the “Theory-Context-Methodology” (TCM) framework, the paper first systematically reviewed the research status of mobile short-form video users' discontinuous usage behavior, examining theoretical foundations, research contexts, and methodological approaches both domestically and internationally. Subsequently, it synthesized the influencing factors and mechanisms underlying this behavior by integrating the dual-factor (enabling-inhibiting) perspective, the information ecology perspective, and the S-O-R model.The present study reveals that the discontinuous usage behavior of mobile short-form video users is significantly influenced by enabling factors such as privacy concerns, information overload, system feature overload, and upward social comparison, as well as inhibiting factors including switching costs, information timeliness, platform usefulness, and social influence. Related Articles | Metrics | Comments（0）

Select

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 （164）      PDF（pc） （9160KB）（344）       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）

Select

Topic Mining and Spatial Effect of China’s Digital Economy Policy Texts Xu Huichao　Zhao Yanyun Journal of Information Resources Management    2025, 15 (5): 51-65.   DOI: 10.13365/j.jirm.2025.05.051 Abstract （225）      PDF（pc） （4583KB）（315）       Knowledge map    Save The digital economy policy is one of the manifestations of the government's support for the development of the digital economy, and the analysis of policy characteristics is helpful to clarify the implementation effect of the policy. Based on the characteristics of the digital economy and from the perspective of the digital economy industry chain, this study uses 468 comprehensive digital economy policies in China from 2017 to 2022, combined with text analysis methods, network analysis methods and spatial econometric models. The results show that China's digital economy policies are divided into eight categories: talent training, enterprise and park development, service platform, technology development, industrial integration development, declaration and evaluation, management and planning, and rewards and subsidies. Overall, the digital economy policies have significantly promoted the development of the digital economy in both the region and neighboring regions. Policies related to talent training and technology development have shown significant positive externalities, and policies on enterprise and park development, service platforms, technology development, incentives and subsidies, and management and planning all show obvious digital economy promotion effects. The number of digital economy policies has a long-term impact on the development of the digital economy, while the intensity of digital economy policies has a significant effect in the short term. Related Articles | Metrics | Comments（0）

Select

Logic and Framework of the Nationwide Integrated and Multifunctional Data Registration System Wang Jingxuan　Sun Zhan　Liu Qi　Yang Qianqian　Wu Jiang Journal of Information Resources Management    2025, 15 (4): 72-79.   DOI: 10.13365/j.jirm.2025.04.072 Abstract （219）      PDF（pc） （967KB）（300）       Knowledge map    Save Data registration is a foundational element in building a robust data governance system and plays a central role in regulating the emerging data element market. While local pilot initiatives for data registration are gaining momentum across China, significant differences remain in core aspects such as registration functions, target entities, validity frameworks, and institutional objectives. This paper reviews the current landscape of data registration practices and analyzes the practical demands of various stakeholders from both governmental and market perspectives. Based on this analysis, it proposes a integrated, multifunctional national data registration framework aimed at supporting data circulation and utilization, unlocking data value, and facilitating the establishment of an integrated national data market. Related Articles | Metrics | Comments（0）

Select

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 （120）      PDF（pc） （1632KB）（280）       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）

Select

A Review of the Behavioral Research on Conversational Search: Defining the Paradigm, Constructing Models, and Characterizing Behaviors Meng Gaohui　Liu Chang Journal of Information Resources Management    2025, 15 (4): 24-41.   DOI: 10.13365/j.jirm.2025.04.024 Abstract （505）      PDF（pc） （1862KB）（269）       Knowledge map    Save At the developmental turning point brought by the generative artificial intelligence (GenAI) wave, this paper provides a comprehensive review of research on conversational search behavior. It examines how the new paradigm transforms traditional perceptions of search behavior, summarizes the current state and limitations of this field, and offers valuable research directions for future studies. By reviewing the research progress in defining the overall characteristics of human-computer interaction, modeling the behavior categories and development processes of users and agents, and characterizing the behavior features and related factors of users or agents in conversational search, it argues that the main limitations of previous studies are that research objects seldom cover the cognitive and emotional activities that drive objective dialogue actions, research scenarios are mostly limited to simulated human-human dialogue scenarios, and research topics rarely involve the evaluation of user behavior performance and the enhancement of user capabilities. Future research should inherit and develop the cognitive research paradigm in the field of interactive information retrieval, expand the research scenarios to real human-computer dialogues under the GenAI scenario, and focus on evaluating and discovering better user behavior patterns. Related Articles | Metrics | Comments（0）

Select

Integration of Data and Traditional Production Factors: Mechanisms, Paths, and Guarantees Wu Jiang　Yuan Yiming　Miao Jiarui　Zhang Dongying　Lin Zhenyang　Du Le Journal of Information Resources Management    2025, 15 (5): 4-13.   DOI: 10.13365/j.jirm.2025.05.004 Abstract （464）      PDF（pc） （1340KB）（253）       Knowledge map    Save With the accelerated development of the digital economy, the deep integration of data elements with traditional production factors has become a key driver of industrial upgrading, as data elements ultimately realize their value in practical application scenarios. Through literature review and theoretical analysis, this study summarizes the mechanisms by which data elements interact with traditional production factors, including the multiplier effect, the entropy reduction effect of information, and the data network effect. It further explores four synergistic pathways toward all-factor integration, identified from practical application scenarios of such integration. Based on these findings, this study proposes safeguard strategies to promote the coordinated development of data elements and multiple production factors across four application dimensions: land data governance, labor skill transformation, capital allocation, and technological innovation. This study provides theoretical support for unlocking data value and constructing a modernized system of production factors. Related Articles | Metrics | Comments（0）

Select

Identification, Evolution, and Prospects of Global Information Literacy Education Research Themes in 1974—2024 Huang Ruhua　Wu Yingqiang　Shi Leyi Journal of Information Resources Management    2025, 15 (4): 4-22.   DOI: 10.13365/j.jirm.2025.04.004 Abstract （1266）      PDF（pc） （5120KB）（249）       Knowledge map    Save The year 2024 marks the 50th anniversary of the introduction of the term information literacy on a global scale. This study applies the BERTopic topic modeling method to identify 44 major research topics in global information literacy education over the past five decades. These topics are categorized into five thematic clusters: (1) pedagogical practices in information literacy education, (2) information literacy education driven by digital and intelligent technologies, (3) information literacy education targeting specific populations, (4) disciplinary applications of information literacy education, and (5) social and ethical issues in information literacy education. Five key topics are highlighted: librarian-faculty collaboration in higher education, nurses’ information literacy, health information literacy, teachers’ ICT competence and skill development, and information literacy in the context of artificial intelligence. By tracking topic-specific keywords, this study outlines five stages in the evolution of research: the conceptual dissemination stage, the technological impact stage, the connotation expansion stage, the convergence of multiple literacies stage, and the stage influenced by major societal events. Over the past 50 years, three prominent characteristics have shaped the development of global information literacy education research: (1) consistent focus on higher education and academic libraries across all stages; (2) a distinct phase-based impact of technology on information literacy education; and (3) the influence of changing educational environments on the content and form of information literacy instruction. Finally, six future directions are proposed for global research and practice in information literacy education: strengthening theoretical study of information literacy education, emphasizing the development of standards and assessment systems, diversifying the contexts for information use, enhancing the roles of both the academic library community and the information industry, fostering nationwide collaboration, and boosting China’s international influence in the field. Related Articles | Metrics | Comments（0）

Select

Research on the Influence of Initiative in Conversational Search Systems on Human-AI Collaboration Fu Shiting　Jiang Tingting　Song Defeng Journal of Information Resources Management    2025, 15 (4): 42-55.   DOI: 10.13365/j.jirm.2025.04.042 Abstract （319）      PDF（pc） （3789KB）（245）       Knowledge map    Save This study examines the role of proactivity in conversational search systems (CSS), identifying three key proactive interaction strategies, i.e., clarification, suggestion and disclosure.A mixed-initiative CSS was developed based on these strategies and compared with a user-initiative CSS. Experimental results showed that proactive CSS significantly improved the intrinsic, contextual, and representation quality of search results, enhanced system usability and social presence, and increased user trust and task attraction. Team consensus consistently mediated these effects. The findings offer both theoretical and practical insights for designing proactive CSS. Related Articles | Metrics | Comments（0）

Select

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 （150）      PDF（pc） （5208KB）（224）       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）

Select

Research on the Data Governance Framework for Artificial Intelligence: Construction and Prospects Based on Policy Texts Zhou Wenhong　Xiong Xiaofang　Ye Yahan Journal of Information Resources Management    2025, 15 (4): 87-98.   DOI: 10.13365/j.jirm.2025.04.087 Abstract （585）      PDF（pc） （1302KB）（221）       Knowledge map    Save To explore a data governance framework for artificial intelligence (AI), this paper aims to clarify the layout and progress of data governance actions within current global AI strategies, thereby promoting the optimization of AI policy systems in the context of digital intelligence transformation. This paper conducts a statistical analysis of AI policies released by government departments in various countries and regions, extracting policy provisions related to data governance. Using content analysis, this paper outlines a data governance framework for AI and proposes directions for optimization based on the existing framework. It is found that the current policy framework for AI-oriented data governance includes four key points: data subjects, data objects, data lifecycle management, and data security. While showing reference points, it also reflects the optimization construction direction of the data governance framework for artificial intelligence from strengthening the participation of data management institutions, highlighting the orientation of professional resource construction, supplementing key links, and optimizing phased focus configuration. Related Articles | Metrics | Comments（0）

Select

Journal of Information Resources Management    2025, 15 (4): 23-23.   Abstract （150）      PDF（pc） （286KB）（217）       Knowledge map    Save Related Articles | Metrics | Comments（0）

Select

Exploring the Influence Mechanism of Social Media Users’ Algorithm Awareness on Privacy Risk Coping Behaviors: A Perspective from Algorithm Abuse Meng Xi　Li Qingshuang　Guo Yajun Journal of Information Resources Management    2025, 15 (5): 99-115.   DOI: 10.13365/j.jirm.2025.05.099 Abstract （214）      PDF（pc） （2169KB）（217）       Knowledge map    Save Based on the APCO (Antecedents-Privacy Concerns-Outcomes) model framework, this study adopts a mixed-method approach combining qualitative and quantitative research to examine the impact of users’ algorithm awareness and privacy concerns on their privacy risk coping behaviors, from the perspective of algorithm abuse. In the qualitative study, in-depth interviews with 24 social media users were conducted and analyzed with grounded theory, aiming to identify key dimensions of privacy concerns under the lens of algorithm abuse. In the quantitative study, survey data from 513 users were empirically analyzed using structural equation modeling to examine the direct effect of algorithm awareness on privacy risk coping behaviors and to further explore the mediating roles of five identified privacy concern factors. Results from the qualitative analysis reveal five key privacy concern dimensions: perceived privacy intrusion, perceived algorithm surveillance, perceived algorithm bias, perceived algorithmic decision-making risk, and perceived data permanence risk. Empirical results show that algorithm awareness has a significant positive impact on privacy risk coping behaviors. Moreover, perceived privacy intrusion, algorithm bias, algorithmic decision-making risk, and data permanence risk partially mediate this relationship, while the mediating role of perceived algorithm surveillance is not significant. These findings provide practical evidence to support the governance of algorithm abuse risks and the management of user privacy risks in China. Related Articles | Metrics | Comments（0）

Select

Exploring the System and Mechanism of National Data Infrastructure for Promoting the Value Release of Data Elements Zhao Yiming　Li Linxin　Luo Lin　Wang Zizhao　Huang Dandi Journal of Information Resources Management    2025, 15 (5): 21-33.   DOI: 10.13365/j.jirm.2025.05.021 Abstract （290）      PDF（pc） （1211KB）（213）       Knowledge map    Save The national data infrastructure serves as the key carrier for the circulation and utilization of data elements throughout their entire life cycle. It plays a strategic role in promoting the aggregation, sharing, security, and efficient use of data resources. From the perspective of value release of data elements, this paper systematically analyzes the functional and institutional requirements for the national data infrastructure. It is proposed that the national data infrastructure should provide support in all stages of data elements value realization, including "creation of use value—mining of application value—release of multiple values". Furthermore, this paper constructs a three-dimensional organizational system of "region—industry—enterprise" and an operational mechanism that includes "one core, two pillars, and two safeguards." This builds a comprehensive system for the construction and operation of national data infrastructure, covering the entire data element chain across platforms and hierarchical levels. Additionally, safeguard measures for the innovation of the construction and operation system mechanism are proposed from the dimensions of technological innovation, institutional construction, and ecological collaboration. This study provides theoretical basis and practical reference for promoting the high-quality development of national data infrastructure in China and accelerating the release of data element value. Related Articles | Metrics | Comments（0）

Select

A Study on User’ Information Screening Ability in Interaction with Generative Artificial Intelligence: Influence Mechanisms and Cultivation Strategies Wu Dan　Guo Qingyue Journal of Information Resources Management    2025, 15 (4): 80-86.   DOI: 10.13365/j.jirm.2025.04.080 Abstract （388）      PDF（pc） （1565KB）（209）       Knowledge map    Save Against the backdrop of the rapid development of generative artificial intelligence, helping users to improve their information screening ability and construct cognitive subjectivity in interaction is essential for promoting the development of an intelligent society. From the perspectives of generative technology, cognitive subject and information system, this study identifies the challenges that users face in screening information in interaction. It then analyses both the positive and negative influence mechanism of users' information screening ability. Based on this, this study proposes strategies to cultivate AI systems, enhance users' AI literacy and optimise the interaction mechanism from a socio-technical point of view. These strategis aim to activate users' deep processing mechanisms and inhibit tendency towards processing inertia. This study provides a theoretical explanation of the influence mechanism of information screening ability in the context of human-AI interaction, supporting the formulation of strategies to cultivate users' information screening ability. Related Articles | Metrics | Comments（0）

Select

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 （130）      PDF（pc） （2187KB）（202）       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）

Select

How Digital Government Empowers Social Governance: A Quasi-Natural Experimental Study Based on the “National Pilot Project of Information Benefiting the People” Policy Li Junrong　Liu Zhiyong　Fan Ruguo　Lu Jianfeng Journal of Information Resources Management    2025, 15 (4): 99-113.   DOI: 10.13365/j.jirm.2025.04.099 Abstract （280）      PDF（pc） （1548KB）（199）       Knowledge map    Save The construction of digital government is an important lever for promoting the modernization of governance system and governance capacity. The “National Pilot Project of Information Benefiting the People” policy is adopted as an exogenous policy shock for digital government construction, and the empirical analysis of the mechanism of digital government empowering social governance is conducted using methods such as double difference-in-differences (DID) and regression discontinuity (RD). The study found that after the implementation of the “National Pilot Project of Information Benefiting the People” policy, the level of social governance in the pilot areas has been significantly improved. The construction of digital government will promote the participation of social subjects in public affairs decision-making by improving the use of the Internet, improve the efficiency of social governance, reduce the perception of uncertainty, and amplify the social governance effect of “National Pilot Project of Information Benefiting the People”. At the same time, the impact of digital government on social governance will be restricted by factors such as policy lag effect and show significant heterogeneity. In order to continuously and efficiently empower social governance, in the future, China should promote and improve the construction of a digital government by ensuring comprehensive digital governance coverage, strengthening digital empowerment, motivating officials to take proactive actions, and enhancing public participation. Related Articles | Metrics | Comments（0）

Select

Journal of Information Resources Management    2025, 15 (6): 4-4.   Abstract （126）      PDF（pc） （294KB）（166）       Knowledge map    Save Related Articles | Metrics | Comments（0）

Select

Beyond Text-Centrism: The Transformation of Chinese Digital Humanities Driven by Multimodal Technologies Liu Wei　Shan Rongrong　Jin Jiaqin Journal of Information Resources Management    2025, 15 (5): 14-20.   DOI: 10.13365/j.jirm.2025.05.014 Abstract （350）      PDF（pc） （677KB）（160）       Knowledge map    Save Digital humanities research has traditionally centered on textual analysis, yet this "text-centrism" paradigm reveals significant limitations within the Chinese context, including insufficient character set coverage, low OCR accuracy, and the loss of non-textual cultural information, all of which hinder a comprehensive study of China's rich material cultural heritage. The emergence of multimodal technologies offers a transformative pathway for Chinese digital humanities. This paper investigates the predicaments of text-centrism, analyzes solutions enabled by multimodal fusion technologies, and uses DeepSeek’s Janus Pro model as a case study to illustrate the potential of unified multimodal large-scale models in ancient text digitization, intelligent agent development, and cultural heritage preservation. The results show that multimodal technology can reconstruct cultural memory through cross-modal synergy, enhance the public's cultural identity, and provide technical and methodological support for the transformation of Chinese digital humanities. Related Articles | Metrics | Comments（0）

Select

“Objectives-Instruments-Subjects” Triangular Framework: A Quantitative Analysis of China’s Data Asset Management Policies Zhang Wei　Ye Shiqi Journal of Information Resources Management    2025, 15 (5): 66-81.   DOI: 10.13365/j.jirm.2025.05.066 Abstract （269）      PDF（pc） （4955KB）（156）       Knowledge map    Save The policy text on data assets plays a crucial role in the forward-looking, guiding, and coordinated management of data assets. It is crucial to scientifically recognize its value orientation, specific measures, and subject layout to promote the establishment and improvement of the data asset policy system. This study has built a three-dimensional analytical framework of “policy objectives-policy instruments-policy subjects” and conducted multi-dimensional quantitative analysis on 36 policy texts based on this framework. It has sorted out that mechanism innovation, risk prevention and control, value exploitation, ecological cultivation are the four major pathways of the current policy system. The three major real problems in the current data asset policy system are imbalanced policy objectives, imbalanced policy instrument structures, and insufficient motivation of policy subjects. In the future, it is necessary to break through the development dilemma by strengthening policy goal coordination, optimizing policy instrument structures, and giving full play to the role of policy subjects. This will promote the comprehensive management and compliance, standardization, and value-added management of data assets. Related Articles | Metrics | Comments（0）

Select

A Typical Action Integrating Intelligence and Data: Data Sensemaking in User-Generated Intelligent Search Engine Interactions Peng Siyuan　Wu Siying　Ling Shang　Li Qiao　Wang Ping Journal of Information Resources Management    2025, 15 (5): 34-50.   DOI: 10.13365/j.jirm.2025.05.034 Abstract （212）      PDF（pc） （3569KB）（152）       Knowledge map    Save Generative intelligent search engines, which integrate generative artificial intelligence technology and retrieval techniques, have the potential to support researchers in overcoming challenges during data sensemaking, but they also come with certain risks. Drawing upon sense-making theory, information behavior model, information search process model, and information search behavior model, this study preliminarily proposes the Data Search As Data sensemaking(DS-DSM) theoretical model. To explore this model, this study conducts a user experiment on the Bing Copilot platform to understand how researchers construct the meaning of data through interaction with generative intelligent search engines. The findings indicate that in the interaction scenario of generative intelligent search engines, the essence of researchers’ data search is data sensemaking. This study also identifies the stages of this process and reveals how, at each stage, researchers cognitively, affectively, and behaviorally engage with generative intelligent search engines as a bridge to overcome gaps in the data sensemaking process to complete data-centered tasks. In data-related task situations, researchers’ sensemaking begins at the formulation stage. In contrast, in research-related task situations, some researchers first go through initiation, selection, and exploration stages without clear goals. In the formulation stage, the types of gaps researchers face and the bridges they use are the most diverse, showing the most complex behavioral, cognitive, and affective responses. Based on these findings, this study proposes practical strategies for optimizing the design of generative intelligent search engines and conducting user literacy education. Related Articles | Metrics | Comments（0）

Select

Technology Opportunities Identification and Evaluation Based on Policy-Technology Topic Association：A Case Study of the New Energy Vehicle Industry Zhang Zihan　Li Yang　Wu Keye Journal of Information Resources Management    2025, 15 (5): 82-98.   DOI: 10.13365/j.jirm.2025.05.082 Abstract （240）      PDF（pc） （7117KB）（151）       Knowledge map    Save Previous studies on technology opportunity identification are mostly limited to the perspective of technology itself, pay insufficient attention to policy documents that directly reflect the major strategic demands of a country. In view of this, this paper proposes a technology opportunity identification method based on policy-technology topic association, aiming to explore the potential gaps between policy demands and technological development. Specifically, this paper uses policy documents to represent policy demands and patent technologies to represent the degree of technological development. The identification of technology opportunities is divided into three modules: topic extraction of policies and technologies, topic association, and identification and evaluation of policy-technology integration opportunities. Firstly, this paper identifies policy and technology topics by constructing a LDA topic model. Then, word embedding and hierarchical clustering methods are used to establish the mapping relationship between policy and technology. This paper locates technology opportunity by constructing identification quadrant according to the identification rules. Finally, This study takes the field of new energy vehicles as an example to verify the effectiveness of research framework, which provides information support for country and research institutions to accelerate the layout in this field. Related Articles | Metrics | Comments（0）

Select

Identifying Knowledge Heuristic Intervention and Enhancement Patterns for Algorithmic Literacy in Personalized Recommendation Contexts Liu Jing　Bai Fangrui　Wu Dan Journal of Information Resources Management    2025, 15 (5): 116-130.   DOI: 10.13365/j.jirm.2025.05.116 Abstract （207）      PDF（pc） （9235KB）（145）       Knowledge map    Save Personalized recommendations significantly influence daily life and represent a key shift in information control toward algorithms. This change necessitates new skills for individuals to perceive, understand, and utilize these algorithms effectively, highlighting an urgent need for research on algorithmic literacy within the context of personalized recommendations. This study concentrated on personalized recommendation contexts, developing a knowledge heuristic intervention to enhance algorithmic literacy. A 4-week longitudinal user experiment involving 30 participants was conducted, with statistical comparisons and analyses of changes in algorithmic literacy, as well as the identification of enhancement patterns through cluster analysis. Before and after the experiment, users showed significant improvements in different dimensions of algorithmic literacy, confirming the effectiveness of the knowledge heuristic intervention. Cluster analysis identified three enhancement patterns of algorithmic literacy: gradual improvement with weak foundations pattern, Knowledge-Skill enhancement with weak motivation pattern, and awareness enhancement with strong motivation pattern. This study further analyzed user characteristics associated with each pattern and proposed tailored knowledge heuristic strategies for enhancing algorithmic literacy based on these characteristics. Related Articles | Metrics | Comments（0）

Select

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 （173）      PDF（pc） （4974KB）（134）       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）

Select

Aggregating Data into Knowledge: Unlocking New Horizons——A Book Review of Research on Multi-dimensional Aggregation of Internet Resource and Knowledge Discovery Sun Jianjun Journal of Information Resources Management    2025, 15 (4): 157-160.   DOI: 10.13365/j.jirm.2025.04.157 Abstract （206）      PDF（pc） （569KB）（133）       Knowledge map    Save In the context of big data, how can Internet resource aggregation be leveraged to enable effective knowledge discovery? This review examines Professor Xia Lixin’s book Research on Multi-dimensional Aggregation of Internet Resource and Knowledge Discovery around this central question. Grounded in cutting-edge research and disciplinary concerns, this review distils the core content and research characteristics of the book from dimensions including disciplinary perspective, theoretical foundation, structural design, research methodology and conclusions. Through critical reading and comparative analysis, this review argues that the book precisely focuses on the cutting-edge trends and practical demands of information resource management in the evolution of the Internet ecosystem. Its academic concerns align closely with the core issues in China's library and information science field. The research findings demonstrate significant theoretical value and practical significance, providing a systematic framework to address phenomena such as ‘information overflow’ and ‘information disorientation’, while offering theoretical support and practical references for future related research in the field of information resource management. Related Articles | Metrics | Comments（0）

Select

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 （141）      PDF（pc） （6423KB）（131）       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）

Select

Research on the Development of Information Resources Management Discipline from the Perspective of NSFC Funding Hu Jiming　Yang Yun Journal of Information Resources Management    2025, 15 (5): 147-161.   DOI: 10.13365/j.jirm.2025.05.147 Abstract （219）      PDF（pc） （12506KB）（128）       Knowledge map    Save From the perspective of National Natural Science Foundation projects, this study delves into the theme and direction synthesis of research in the field of Information Resources Management, aiming to grasp the trends in this discipline as it undergoes transformation. A framework for analysing the developmental trends of the discipline has been constructed, integrating theme mining and deep learning models. Based on the NSFC's G0414 project data from the past five years, this study conducts visual analyses of project theme identification, differences between application and funding themes, thematic association structures, and their evolution over time.The funding ratio for the Information Resource Management discipline remains stable and at a high level, primarily concentrated among a few top-ranking universities. A limited number of thematic areas have received final funding, including information demand, multimodal computing, knowledge discovery, intelligent empowerment, large models, and risk management. These themes exhibit varying degrees of interconnection and influence, characterized by ongoing evolutionary traits. In the realm of natural science research, the overall development of the Information Resource Management discipline is promising, with stable funding levels focusing on specific research directions. However, there is a significant discrepancy between project applications and funding outcomes. Related Articles | Metrics | Comments（0）