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A Review of Research on Elderly-oriented Digital Products: Demand Mining, Obstacle Analysis and Optimal Design Lin Yuqin　Zhao Yang　Liu Wanting　Wang Lin Journal of Information Resources Management    2024, 14 (4): 146-160.   DOI: 10.13365/j.jirm.2024.04.146 Abstract （1445）      PDF（pc） （4159KB）（17819）       Knowledge map    Save The "digital divide" exacerbated by the simultaneous development of population aging and social digitization has become increasingly severe, prompting a focus on the research and design of elderly-oriented digital products within both industry and academia. Using a systematic review approach, this study analyzes 348 research articles on elderly-oriented digital product design indexed in CNKI and Web of Science from 2014 to 2023. It explores the research progress and developing trend of the demand mining, usage obstacles, and optimal design of digital products for elderly users. The findings reveal that research on elderly users' needs mainly focuses on the three levels of material, emotional and spiritual needs, with significant focus on sensory barriers, cognitive barriers, behavior barriers and psychological barriers in product usage. The study investigates elderly-oriented design through various lenses, including design standards, optimization countermeasures, and usability testing. Future research should further consider the evolving nature of digital products and demographic trends by enhancing the methods for sample collection, innovating research methodologies, and expanding the content of studies. The findings of this study provide valuable references for identifying research priorities in elderly-oriented digital product adaptation, spotlighting emerging areas, advancing theoretical frameworks, and also offer practical insights for the proactive development of an age-friendly digital society. Related Articles | Metrics | Comments（0）

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Trends and Future Prospects in Sentiment Analysis of Financial Reviews Texts Wu Jiang　Duan Yiqi Journal of Information Resources Management    2025, 15 (1): 86-101.   DOI: 10.13365/j.jirm.2025.01.086 Abstract （1291）      PDF（pc） （5622KB）（4141）       Knowledge map    Save This study surveys recent advancements in sentiment analysis of financial review texts, both domestically and internationally, to delineate the field’s developmental trajectory. Adopting dual perspectives of technology-driven and content-driven approaches, it scrutinizes prevailing research trends. Technologically, the evolution from lexicon-based methods, through traditional machine learning, to deep learning paradigms is summarized. Content-wise, BERTopic and LLaMA3 are employed for document clustering based on scholarly viewpoints, with dynamic topic modeling elucidating domain progress. Findings indicate a domestic transition from sentiment analysis methods to investigations of emotional impacts on financial market prediction. Meanwhile, international research continues progressing deep learning applications while revealing emerging interests in financial sentiment modeling. By integrating these observations, the paper proposes future directions including: (1)constructing high-quality datasets, (2)conducting granular sentiment analysis of financial discourse, and (3)improving the interpretability of analytical outcomes. These recommendations aim to establish methodological foundations for subsequent studies in this field. Related Articles | Metrics | Comments（0）

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An Exploration of the Data Assetization Paths for the Three Major Types of Data Ma Feicheng　Sun Yujiao　Xiong Siyue　Wang Wenhui Journal of Information Resources Management    2024, 14 (5): 4-13.   DOI: 10.13365/j.jirm.2024.05.004 Abstract （1242）      PDF（pc） （6613KB）（1886）       Knowledge map    Save Data assetization is a key stage in grasping digital opportunities, realizing the value of data, and promoting the digital transformation of the economy and society. This paper argues that public data, enterprise data and personal data are the major subjects of data elements. However, current research on the realization path of data assetization for the three major types of data is insufficient, hindering the release of the value of data elements. In this paper, we systematically review the relevant concepts of data assets, and delve into the path of data assetization from the three major data subjects: public, enterprise and individual. The results shown that public data can serve internal government needs or be supplied to the society, generating social benefits or economic benefits through sharing and opening, and authorized operation, thus forming public data assets. Enterprises, depending on whether they hold data ownership, can carry out different degrees of processing and handling of data, so as to complete the deep excavation of data value and redistribution of data benefits, forming inventory, intangible assets and other types of data assets. The practice related to personal data assetization is limited, mainly relying on two paths: direct transaction between suppliers and demanders or entrusted transaction by data intermediaries to complete market circulation and form personal data assets. Through in-depth exploration of this topic, this study aims to provide theoretical guidance and practical reference for the value realization of data elements and the effective allocation of data resources. Related Articles | Metrics | Comments（0）

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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 （1212）      PDF（pc） （5120KB）（231）       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）

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Research on New Quality Productive Forces Driving High-Quality Development of Digital Economy Ma Feicheng　Sun Yujiao　Xiong Siyue Journal of Information Resources Management    2025, 15 (1): 4-12.   DOI: 10.13365/j.jirm.2025.01.004 Abstract （1174）      PDF（pc） （1353KB）（935）       Knowledge map    Save New quality productive forces, emerging from a new wave of scientific and technological revolution and industrial transformation, align with China's domestic strategic blueprint and the practical needs arising from international competitive dynamics. With digital economy becoming a pivotal force in global economic and social transformation, promoting its high-quality development has become a strategic imperative for China's economic development in the new era. This research investigates how new quality productive forces drive the high-quality development of digital economy, which holds significant implications for advancing productivity theory, understanding digital era development patterns, and facilitating economic transformation. The study first explored the evolutionary context of new quality productive forces, systematically examined its theoretical underpinnings from three dimensions of "newness," dual implications of "quality," and intrinsic characteristics of "productive forces," and analyzed its practical features. Building upon this foundation, the research revealed from a theoretical perspective how new quality productive forces drive the high-quality development of digital economy, identifying three inherent mechanisms: new technology stimulated new growth drivers, new elements reshaped production relations, and new industries reconstructed competitive landscape. Finally, the research proposed five implementation paths: improving institutional supply, strengthening talent cultivation, unleashing element value, promoting coordinated regional development, and deepening opening up. This study aims to provide theoretical guidance and practical insights for promoting the high-quality development of digital economy. Related Articles | Metrics | Comments（0）

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Deepfake Information in AIGC: Generation Mechanisms and Governance Strategies: An Analytical Framework Based on Actor-Network Theory Ran Lian　Zhang Wei Journal of Information Resources Management    2025, 15 (2): 137-150.   DOI: 10.13365/j.jirm.2025.02.137 Abstract （1067）      PDF（pc） （2326KB）（1521）       Knowledge map    Save Exploring the complex logical mechanisms behind AIGC-driven deepfake information generation has significant practical value for constructing a cognitive framework for understanding deepfake information and formulating targeted governance strategies in cyberspace. Drawing on the actor-network theory, this study constructs a theoretical framework for analyzing AIGC deepfake information generation, focusing on four aspects: problem presentation, allocation of benefits, mobilization, and exclusion of dissent. It further interprets the dynamic process of deepfake information generation in terms of network formation, alliance-building, and stabilization. The findings indicate that the continuous output of AIGC-generated deepfake information is likely to intensify adverse social effects, such as technological domination, truth decay, and moral dissolution. The production and dissemination of deepfake information involve AIGC technologies translating heterogeneous actors through interest-driven strategies, driving the deepfake interest network from formation to stabilization while engaging in a competitive dynamic with opposing organizations. Based on these findings, this study proposes targeted governance strategies for AIGC deepfake information across four dimensions: moral governance, rule of law, technological governance, and crowd-based governance. Related Articles | Metrics | Comments（0）

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A Multinational Comparative Study of Regulatory Policies for Generative AI from the Perspective of “Tools-Structure” Deng Shengli　Ding Weiwei　Wang Fan　Wang Haowei Journal of Information Resources Management    2025, 15 (1): 54-68.   DOI: 10.13365/j.jirm.2025.01.054 Abstract （1065）      PDF（pc） （4448KB）（2981）       Knowledge map    Save Based on the dual perspective of policy tools and structural characteristics, this study takes the regulatory policies of generative AI in different countries as the research object, aiming to explore the structural characteristics and internal connections of the policy elements of generative AI, in order to promote the healthy development of generative AI. A total of 14 effective policy texts were collected, and 327 relevant text units were coded and interpreted using bibliometrics, content analysis, and BERTopic. The structural characteristics were analyzed from three dimensions: policy issuance time, policy issuance subject, and policy theme characteristics. The role paths were discussed by dividing into three types of policy tools: environmental, demand-driven, and supply-driven. The findings show that the regulation of generative AI is still in its infancy, and there are significant differences in the overall characteristics of policies among different countries, with significant differences in the regulatory level. Overall, the role path of policy tools is mainly dominated by the indirect role of environmental policy tools, showing a structural imbalance and bias in the role path. Further comparison of the similarities and differences in regulatory policies among different countries is conducted, and corresponding countermeasures and suggestions are put forward to optimize the policy tool structure, balance the role path of policy tools, assessing the effectiveness of policy implementation, and promote the coordinated development of the generative AI regulatory system. Related Articles | Metrics | Comments（0）

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Generation AI in Human-AI Interaction: Origins, Characteristics and Future Prospects Xu Hao　Cheng Qingxuan　Dong Jing　Wu Dan　Tian Li Journal of Information Resources Management    2025, 15 (1): 13-20.   DOI: 10.13365/j.jirm.2025.01.013 Abstract （963）      PDF（pc） （2333KB）（3168）       Knowledge map    Save The rapid development of artificial intelligence is driving society toward a new era of human-AI interaction (HAII) and reshaping a new generation of minors growing up with AI—Generation AI. This paper reviews the origins and evolution of human-computer interaction (HCI), examining the shift from HCI to HAII, and focuses on the unique traits of Generation AI in this context. By analyzing the interaction modes and characteristics of Generation AI, the study reveals their distinctive attributes in HAII scenarios, including intelligent perception, social contention, and digital embedding across all settings, timeframes, and environments. Finally, the paper envisions the future of human-AI synergy for Generation AI from three perspectives: human-centered design, multimodal interaction, and augmented collaboration, providing a theoretical foundation for building a smart and human-centered society. Related Articles | Metrics | Comments（0）

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Research and Design of General Knowledge Model of Ancient Books Chen Tao　Zhao Xiaofei　Yang Xin　Lin Lixin Journal of Information Resources Management    2025, 15 (1): 139-153.   DOI: 10.13365/j.jirm.2025.01.13 Abstract （952）      PDF（pc） （8021KB）（194）       Knowledge map    Save China boasts a vast collection of ancient books. While the traditional organization and management mode of ancient books has facilitated the transformation of ancient book resources from "collection" to "use", the "raw resources" are increasingly unable to meet the needs of ancient book utilization in the digital era. This paper investigates and analyzes the reusable ontology model for ancient book knowledge organization, reviews the perspectives and approaches to knowledge modeling of ancient books, and proposes a five-layer framework for a general knowledge model of ancient books based on the two dimensions of form and content characteristics. To verify the usability of the model, this paper takes the "Hu Zi Book" of the Yongle Encyclopedia as an example, constructs an associated dataset, explores the knowledge graph of ancient books by integrating associated data, and realizes the combination of knowledge association and data aggregation.This paper constructs a general knowledge organization model for ancient books, providing an alternative approach for the association and aggregation, inference and calculation, dissemination and sharing, and intelligent application of ancient book knowledge. Related Articles | Metrics | Comments（0）

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Research on Multilateral Platform for Data Element Transactions: Current Status, Approaches, and Framework Wu Jiang　Yuan Yiming　He Chaocheng　Qian Long　Du Le　Miao Jiarui Journal of Information Resources Management    2024, 14 (3): 4-20.   DOI: 10.13365/j.jirm.2024.03.004 Abstract （927）      PDF（pc） （4171KB）（1685）       Knowledge map    Save In response to the national policies aiming to establish a unified and comprehensive market for the circulation and transaction of data elements, it is imperative to systematically analyze the current processes involved in the circulation and transaction of data elements. Such analysis is crucial for the construction of data element platforms and holds strategic importance in advancing the market-driven distribution of data elements and fostering the growth of the digital economy within China. Through case studies and literature reviews, this study examines the entities within the multilateral data trading market and their interrelationships. It also identifies the primary challenges within the current market and proposes breakthrough pathways and a research framework for the development of a multilateral data element trading platform. This framework is grounded in value chain theory and socio-technical system theory, aiming to serve as a guide for the construction of a market conducive to the circulation and transaction of data elements. Related Articles | Metrics | Comments（0）

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Research on Large Language Model Evaluation for the Generation Task of Natural Language Processing in Classical Chinese Zhu Danhao　Zhao Zhixiao　Zhang Yiping　Sun GuangYao　Liu Chang　Hu Die　Wang Dongbo Journal of Information Resources Management    2024, 14 (5): 45-58.   DOI: 10.13365/j.jirm.2024.05.045 Abstract （922）      PDF（pc） （3124KB）（4105）       Knowledge map    Save The rapid development of large language models (LLMs) presents both opportunities and challenges for their evaluation. While evaluation systems for general-domain LLMs are becoming more refined, assessments in specialized fields remain in the early stages. This study evaluates LLMs in the domain of classical Chinese, designing a series of tasks based on two key dimensions: language and knowledge. Thirteen leading general-domain LLMs were selected for evaluation using major benchmarks. The results show that ERNIE-Bot excels in domain-specific knowledge, while GPT-4 demonstrates the strongest language capabilities. Among open-source models, the ChatGLM series exhibits the best overall performance. By developing tailored evaluation tasks and datasets, this study provides a set of standards for evaluating LLMs in the classical Chinese domain, offering valuable reference points for future assessments. The findings also provide a foundation for selecting base models in future domain-specific LLM training. Related Articles | Metrics | Comments（0）

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Reflections on Construction of Information Resources in University Libraries Serving National Strategies in the Era of Open Science Huang Ruhua　Shi Leyi Journal of Information Resources Management    2024, 14 (4): 16-28.   DOI: 10.13365/j.jirm.2024.04.016 Abstract （919）      PDF（pc） （907KB）（2410）       Knowledge map    Save The arrival of the open science era has changed the information environment and scholarly communication system, and has also brought new opportunities and challenges to the construction of information resources in university libraries. Based on the national strategies of becoming a leading country in education, science and technology, talent, culture and so on, construction of information resources in Chinese university libraries urgently needs to achieve high-quality development on the basis of serving multiple national strategies. This article proposes countermeasures in four aspects, including: constructing information resources that are consistent with a holistic approach to national security, constructing information resources system needed for the digitalization of Chinese higher education, consolidating the information resource foundation for great self-reliance and strength in science and technology, and strengthening information resource support needed for construction of philosophy and social sciences with Chinese characteristics. Related Articles | Metrics | Comments（0）

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A Qualitative Study on the Impact Mechanisms of User Satisfaction of Comprehensive Government Service APPs Based on User Reviews Zhao Ying　Deng Huili　Li Guangyao　Chen Cheng Journal of Information Resources Management    2024, 14 (3): 121-135.   DOI: 10.13365/j.jirm.2024.03.121 Abstract （899）      PDF（pc） （1873KB）（689）       Knowledge map    Save Comprehensive Government Service Apps are critical for delivering "one-stop" solutions for high-frequency government transactions and are essential for the development of efficient, collaborative digital governance. This study explores the determinants of user satisfaction and their mechanisms to inform targeted enhancements in app functionality and service processes, ultimately aiming to improve digital governance standards. Utilizing the Service Encounter Triad and the Service Encounter Satisfaction Model as theoretical frameworks, this study analyzed user reviews from 29 apps through Grounded Theory, identifying seven key factors within product quality and usage contexts. This study developed a triadic subject model and a process model to describe these dynamics and revealed that higher product quality and usage scenarios aligned with user needs lead to greater satisfaction. Institutional pressures in app promotion negatively influence satisfaction prior to use, whereas during usage, product quality positively impacts user satisfaction. After use, perceived empathy within the usage context enhances satisfaction. Additionally, institutional pressures negatively moderate the positive relationship between product quality and satisfaction. This study not only elucidates the complex mechanisms affecting user satisfaction but also enriches the management information systems literature by extending the applicability of established theories. The insights provided offer a theoretical basis for further quantitative studies on satisfaction dimensions and the regulatory effects of institutional pressures. Recommendations derived from this study could optimize digital governance services, promoting high-quality development and advancing digital transformation in China. Related Articles | Metrics | Comments（0）

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The Impact of Work Unpredictability on Work-family Conflict in a Remote Work Context——A Moderated Mediation Model Xie Xinzhou　Jin Guangyao Journal of Information Resources Management    2024, 14 (3): 136-148.   DOI: 10.13365/j.jirm.2024.03.136 Abstract （897）      PDF（pc） （1230KB）（1447）       Knowledge map    Save Remote work has become the norm in digital work practices, and the study of the negative effects associated with work and family life in the use of digital technologies is receiving increasing scholarly attention in the field of information systems. Using a theoretical model of work-home resources, this paper explores the new types of work stress perceived by employees in the process of adapting to digital technologies in a remote work context and experiencing a shift in the form and manner of work, and explains the specific paths by which this stress undermines employees' prosperity in the family sphere. The results indicate that the work unpredictability in the context of intensive use of digital technologies leads to a reduction in coping resources for employees' psychological resilience, resulting in work-family conflict. Self-esteem, on the other hand, can be effective in helping employees relieve work stress and restore personal resources. The empirical results provide new insights and implications for how telecommuting affects employees' work experiences and work-home relationships. Related Articles | Metrics | Comments（0）

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Experts in Information Resource Management Discipline Discussing "The 2024-2035 Master Plan on Building China into a Leading Country in Education"(Part 1): Talent Cultivation and Digital Literacy Education Sun Jiangjun Wu Dan Sun Xin Zhang Jiuzhen Huang Ruhua Li Yanke Journal of Information Resources Management    2025, 15 (2): 4-12.   DOI: 10.13365/j.jirm.2025.02.004 Abstract （894）      PDF（pc） （790KB）（5238）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Research on Algorithm Embedding and Visibility Mechanism：A Platform Affordance Perspective Du Yan　Xie Xinzhou Journal of Information Resources Management    2024, 14 (5): 91-103.   DOI: 10.13365/j.jirm.2024.05.091 Abstract （890）      PDF（pc） （4260KB）（1426）       Knowledge map    Save Given the increasing relevance of algorithms, how to implement the main responsibility of platforms has become a focal issue. Based on the perspective of affordance theory, the study analyzes the relationship between algorithms, the platform environment, and user perception through mixed research methods to clarify the role of platforms in the process and the problems that arise. The research results show that the algorithm reshapes the platform environment through specific encoding programs, multi-objective optimization, and billions of feature vector combinations. For ordinary users, the algorithm is invisible, uneditable and inaccessible. The platform initially constructs the visibility mechanism of the algorithm through interface cues, but the effect is limited. The research, combined with the embedding logic of the algorithm, provides policy recommendations to promote user algorithmic knowledge, which has certain theoretical and practical significance. Related Articles | Metrics | Comments（0）

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The Inherent Attributes of Artificial Intelligence Generated Content(AIGC) and Its Impact on the Discipline of Information Resources Management Zhu Yu　Chen Guanze　Ye Jiyuan Journal of Information Resources Management    2024, 14 (6): 60-72.   DOI: 10.13365/j.jirm.2024.06.060 Abstract （876）      PDF（pc） （1088KB）（1241）       Knowledge map    Save The inherent attributes of the concept of Artificial Intelligence Generated Content(AIGC) remains a matter of contention within the field of library and information science/ information resources management(IRM). As the issue is closely related to the core research content of IRM research, delving into this problem is significant to understand the key research areas of the discipline, with a focus on AIGC research and a moderate expansion of the disciplinary scope. This study utilized both conceptual and comparative analysis methods to investigate the inherent attributes of AIGC and its related concepts, analyzing the information resources characteristics of AIGC from three perspectives, namely, knowledge philosophy, practical needs, and disciplinary construction, thus proving the necessity of incorporating AIGC into IRM research. Moreover, this study demonstrated the rationality through an analysis of AIGC’s source technology and an examination of the information chain, leading to a renewed understanding within the framework of IRM. Notably, this study clearly identified the inherent attribute of AIGC as the value of information resources, which is one of the core research content of IRM discipline. Additionally, it presented 6 pressing research topics on AIGC for the field of IRM to address. Related Articles | Metrics | Comments（0）

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Scientific Paper Recommendations with User Dynamic Preferences: A Knowledge Graph Approach Based on Attention Embeddings Liu Ya　Mao Qian’ang　Yan Jiaqi　Chen Xi Journal of Information Resources Management    2025, 15 (1): 113-125.   DOI: 10.13365/j.jirm.2025.01.113 Abstract （843）      PDF（pc） （2167KB）（937）       Knowledge map    Save Scientific paper recommendation systems serve as an effective solution to the problem of information overload in academic databases. This study proposes a knowledge-graph-based method employing attention embeddings for the task of scientific paper recommendation to enhance the effectiveness of recommendations. This method initially constructs a collaborative knowledge graph to integrate user behavior with paper attribute information and optimizes node vector representations using the TransR approach. Subsequently, it introduces an attention sequence module that employs an attention propagation mechanism to learn node features and utilizes a sequence attention mechanism to capture the temporal preferences of users from their reading sequences. Finally, the model calculates match scores between researchers and candidate papers to generate personalized recommendation lists. Experiments conducted on a dataset provided by the "Blockchain Laboratory" have validated the effectiveness of the model. Experimental results indicate that the proposed model significantly improves recommendation recall rates, capturing the dynamic interests of researchers more accurately. This study not only enhances the performance of scientific paper recommendation systems but also provides new perspectives and tools for understanding and predicting the evolution of researcher interests. Related Articles | Metrics | Comments（0）

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Construction and Application of Semantic Interoperability Concept System from the Perspective of Standardization: Taking Development of Smart Cities International Standards as an Example Huang Jie　An Xiaomi　Kuang Miaomiao　Wu Jing Journal of Information Resources Management    2024, 14 (3): 56-68，135.   DOI: 10.13365/j.jirm.2024.03.056 Abstract （811）      PDF（pc） （3928KB）（2736）       Knowledge map    Save This paper adopts ISO 704:2022 terminology work—principles and methods, regards the definitions of “semantic interoperability” in international standards as the research objects, and then identifies the core concepts, characteristic and their relationships of “semantic interoperability”. It constructs a concept system of “semantic interoperability” based on international standards, which reveals the capability characteristics and functional requirements of “semantic interoperability”. Then, this paper uses case analysis method to map the “semantic interoperability” characteristics of relevant international standards in the field of smart cities, to analyse gaps in the development of semantic interoperability standards and to provide guidance for selection and development of semantic interoperability standards in smart cities, which helps verify the practicality of this concept system. The research has shown that this system has significance for improving efficiency of data, information, and knowledge sharing and exchange in artificial intelligence scenarios, for promoting data, information, and knowledge association, fusion, and interpretability, and for promoting standardization collaboration on multi-dimensional, multi-scenario, and multi-dimensional semantic interoperability. Related Articles | Metrics | Comments（0）

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International Standardization Consensus Building and Application on Concepts of “Smart” in Digital Domain from System of Systems Perspective An Xiaomi　Zhang Hongwei　Wei Wei　Huang Jie　Zhang Hui Journal of Information Resources Management    2024, 14 (3): 31-41.   DOI: 10.13365/j.jirm.2024.03.031 Abstract （796）      PDF（pc） （1506KB）（761）       Knowledge map    Save In the digital age, with the fast development and widespread application of big data and artificial intelligence technologies, “smart” designations are increasingly emerging. However, there is lack of research on international standardization consensus on “smart” concepts. This paper identifies the core concepts and essential characteristics of “smart” from definitions of relevant international standards in digital domain from system of systems perspective and employs principles and methods for concept building in ISO 704:2022. Based on cross-domain international standards experts virtual meetings and surveys conducted, cross-domain standardization consensus on generic concepts of “smart” is achieved. These concepts of “smart” have been used to map and guide the development of a Chinese national standard in smart city domain. The study has important strategic significance for promoting the compatibility between national and international standards. Related Articles | Metrics | Comments（0）

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The Concepts of "Transparency" in AI Scenarios:A Content Analysis of Definitions from International Standards Organizations An Xiaomi　Xu Mingyue Journal of Information Resources Management    2024, 14 (3): 42-55.   DOI: 10.13365/j.jirm.2024.03.042 Abstract （794）      PDF（pc） （3492KB）（2190）       Knowledge map    Save This paper aims to clarify the intension and extension of the concepts of “transparency” in the AI scenario and build consensus on the concept within the AI field. It analyzes 11 definitions of transparency from international standards organizations including ISO, IEC and ITU-T, identifying core concepts and their relationships. In combination with analysis of relevant international standards of AI, a concept system model of transparency in AI scenarios is proposed. Through the analysis of definitions in different SDOs, this paper proposes implications to artificial intelligence information governance from three aspects in terms of objects, stakeholders and characteristics. This paper offers new insights into standardization collaboration on information governance and information technology governance for AI from a transparent perspective, which has both theoretical value and practical value. Related Articles | Metrics | Comments（0）

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Exploring a Multi-factor Model of Privacy Disclosure in User-Generative AI Interaction Sun Guoye　Wu Dan　Liu Jing　Deng Yuyang Journal of Information Resources Management    2025, 15 (2): 108-122.   DOI: 10.13365/j.jirm.2025.02.108 Abstract （786）      PDF（pc） （5021KB）（1165）       Knowledge map    Save The widespread application of generative artificial intelligence (Generative AI) has brought unique privacy challenges to human-computer interaction. This study focuses on privacy disclosure in the interaction between users and Generative AI, combining large language models with manual coding to identify common types of privacy disclosed in the interaction between users and Generative AI. Based on contextual integrity theory, this study employs user annotation and semi-structured interviews to explore the mechanisms influencing user privacy disclosure. The findings reveal that user privacy disclosure is jointly affected by the user's privacy attitude, technology trust, and privacy risk perception, and the system's data management transparency indirectly affects privacy disclosure by affecting technology trust. Based on the research results, this study constructs a multi-factor influence model of privacy disclosure in the interaction between users and Generative AI, providing a theoretical reference for the development of more privacy-friendly Generative AI. Related Articles | Metrics | Comments（0）

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Research on Online Public Opinion Guidance and Control of Major Emergencies from the Perspective of Actor Network：Analysis Based on the Hybrid Method of SD and fsQCA Li Ming　Hou Tiantian Journal of Information Resources Management    2024, 14 (5): 104-115.   DOI: 10.13365/j.jirm.2024.05.104 Abstract （779）      PDF（pc） （5326KB）（2279）       Knowledge map    Save The occurrence of major emergencies often leads to a surge in online public opinion, making the effective guidance and control of such opinions a significant challenge in current public opinion management. From the perspective of actor-network theory, this study constructs an analysis framework for guiding and controlling online public opinion, which includes actors such as events, media, netizens, and government. A system dynamics model is employed to simulate the mechanism of online public opinion guidance and control for major emergencies. Through sensitivity analysis, the key influencing factors are identified. Based on this, the fuzzy set qualitative comparative analysis (fsQCA) method is applied to analyze the conditions configuration to explore effective pathways for online public opinion guidance and control in major emergencies. This study reveals that the severity of the event, the intensity of media coverage, the emotional intensity of netizens, and the level of government attention play crucial roles in guiding public opinion. It is essential to further strengthen the ability to analyze complex influencing factors, emphasize the roles of media and netizen actors, and enhance the organic linkage and effective collaboration between government attention and various actors to ultimately achieve effective guidance and control of online public opinion in major emergencies. Related Articles | Metrics | Comments（0）

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The Realization of Data Value in the Collaborative Development of Digital Industrialization and Industrial Digitization Ma Feicheng　Wang Wenhui　Sun Yujiao　Xiong Siyue Journal of Information Resources Management    2024, 14 (4): 4-15.   DOI: 10.13365/j.jirm.2024.04.004 Abstract （778）      PDF（pc） （1513KB）（1132）       Knowledge map    Save The collaborative development of digital industrialization and industrial digitization is crucial for driving economic transformation and upgrading. However, existing research lacks in-depth exploration of the collaborative relationship between digital industrialization and industrial digitization. This study, based on the data value chain, elucidates four forms of data value: data resources, data assets, data commodities, and data capital. It further reveals the relevance of digital industrialization and industrial digitization for the two types of data, industrial data and government data. Additionally, it analyzes the evolution process of data element value and the value realization stages in the collaborative development of digital industrialization and industrial digitization. The study demonstrates that the collaborative development of the digital economy consists two value realization processes: the leap from data assets to data commodities and the evolution from data commodities to data capital. To promote the collaborative development of the digital economy, it is necessary to reshape and upgrade both digital and traditional industries by combining the transformation of data element value. Through in-depth analysis of the collaborative development of digital industrialization and industrial digitization, this study enhances the understanding of data element value realization and comprehension of the laws governing digital economic development, providing valuable insights for research in this field. Related Articles | Metrics | Comments（0）

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Research on the Copyright Dilemma and Solution Path of Generative Artificial Intelligence Using Previous Works Liu Zubing Journal of Information Resources Management    2024, 14 (5): 147-158.   DOI: 10.13365/j.jirm.2024.05.147 Abstract （770）      PDF（pc） （859KB）（1158）       Knowledge map    Save The rapidly development and embedded applications of generative artificial intelligence pose challenges to the existing copyright system. Generative artificial intelligence normalizes the crawling of massive amounts of prior work data, inducing infringement risks. Long distance text semantic understanding ability is intended to cover up infringement traces, and open cross domain generalization reasoning ability provides technical convenience for infringement. In terms of data feeding in works, generative artificial intelligence may cross the boundaries of fair use systems or lead to the extreme of unprotected or overprotected rights in previous works; In terms of copyright-ability of generated content, generative artificial intelligence decouples copyright subjectivity with its high-quality and massive generation ability, meeting the "minimum creative standards" and originality requirements. Propose to establish an endorsement system for the use of prior works to address the problem of rational use of algorithms; Promote the horizontal transition from "author centrism" to "work centrism", and shift the author's rights law starting from personality rights to copyright law starting from property rights; Establish an interpretable generative artificial intelligence originality evaluation mechanism and reinterpret originality standards. Related Articles | Metrics | Comments（0）

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Research on Core Concepts of Regulation and Their Relationships in the Context of Artificial Intelligence: From Perspectives of Standardization and Multidisciplinary Integration Kuang Miaomiao　An Xiaomi　Huang Jie Journal of Information Resources Management    2024, 14 (3): 69-79.   DOI: 10.13365/j.jirm.2024.03.069 Abstract （766）      PDF（pc） （3873KB）（1497）       Knowledge map    Save In order to understand the concept of regulation in the context of artificial intelligence, this study investigates and analyzes the regulatory definitions in the standard documents published by the three major international standardization organizations, ISO, IEC, and ITU, and deconstructs and reconstructs core concepts and the relationships in these definitions. Using the concept system “entity-tool-management scenario-activity-object-feature” identified from the regulatory definitions in international standards as an analytical framework, this study analyzes the representative literature related to regulation in the context of artificial intelligence using content analysis. From a multidisciplinary perspective, this study proposes the core concepts of regulation and their relationships in the context of artificial intelligence. This study provides reference for establishing a consensus on the regulatory concepts in the context of artificial intelligence and the standardized collaborative implementation path for general regulatory concepts in the context of artificial intelligence. Related Articles | Metrics | Comments（0）

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Exploring the Cognitive Factors of Healthcare Professionals’ Health Misinformation Correcting Intention on Social Media——Using SEM and fsQCA Yu Mei　Yu Shiya　Liu Rui Journal of Information Resources Management    2024, 14 (3): 104-120.   DOI: 10.13365/j.jirm.2024.03.104 Abstract （736）      PDF（pc） （1527KB）（1180）       Knowledge map    Save This paper aimed to explore the factors of healthcare professionals’ health misinformation correcting intention on social media. The results of this study can be useful to reduce the spread of health misinformation. Based on Third-Person Effects (TPE), Protective Motivation Theory (PMT) and Heuristic System Model (HSM), this paper employed Structural Equation Model(SEM) and Fuzzy-Set Qualitative Comparative Analysis(fsQCA) to explore the influencing factors of healthcare professionals’ health misinformation correcting intention and its configurations. The path analyses showed that third-person effect, social media trust, self-efficacy, response efficacy and professional identity can positively affect health misinformation correcting intention; Information processing affected social media trust and the third-person effect; Social media trust positively affected self-efficacy and response efficacy, and these two variables had mediating effects between social media trust and health misinformation correcting intention. The fsQCA found that there were three configurations leading to health misinformation correcting intention. Third-person effect, self-efficacy, response efficacy, and professional identity were important antecedents. This study can call for and encourage more healthcare professionals to participate in the correction of health misinformation on social media, thus reducing the adverse effects of misinformation and safeguarding public health. Related Articles | Metrics | Comments（0）

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Construction of the Whole Process Field of Data Element Circulation for the High-quality Development of Digital Economy Ma Haiqun　Liu Xinrui Journal of Information Resources Management    2024, 14 (4): 29-35.   DOI: 10.13365/j.jirm.2024.04.029 Abstract （725）      PDF（pc） （2351KB）（1219）       Knowledge map    Save Based on the major strategic needs of the deepening development of the national digital economy, the construction of a full-process field for the circulation of data elements will help improve the overall efficiency of the release of the value of data elements and their transaction circulation, and accelerate the standardization of China's data element market. Related Articles | Metrics | Comments（0）

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Evolutionary Characteristics of the Interdisciplinary Research in Scientific Breakthrough Topics Yang Junhao　Xu Haiyun　Wang Chao　Liu Chunjiang　Zhang Huiling　Tan Xiao Journal of Information Resources Management    2024, 14 (4): 70-85.   DOI: 10.13365/j.jirm.2024.04.070 Abstract （706）      PDF（pc） （12975KB）（171）       Knowledge map    Save The paper explores the impact of interdisciplinary collaboration on scientific breakthroughs at the granularity of research topics, advancing our understanding of the driving mechanisms behind scientific breakthroughs. By analyzing the dynamic characteristics of temporal data, it unveils the breakthrough potential of emerging research topics and their interdisciplinary features. Specifically this paper initially identifies scientific breakthrough topics based on emerging research topics and examines their interdisciplinary characteristics. Furthermore, the consistency in the increase and decrease evolutionary trends in the number of citations and the number of cross-disciplinary documents on scientific breakthrough topics and their knowledge base documents is analyzed. Finally, it measures the predictive causal relationship between the citation count of scientific breakthrough topics and their interdisciplinary quantity time series, thus investigating the association between the emergence of scientific breakthroughs and interdisciplinarity. Using stem cells research as a case study, this empirical research categorizes the interdisciplinary characteristics of scientific breakthrough topics into three categories. Results show that there is a great consistency between the scientific breakthrough topics and the knowledge base in the increase and decrease evolutionary trends in the number of citations and interdisciplinary quantity. However, the predictive causal relationship between the citation time series of most scientific breakthrough topics and the time series of interdisciplinary is not significant. Therefore, relying solely on the interdisciplinary quantity metric may not effectively identify or predict scientific breakthrough topics. The paper provides valuable insights to better understand the characteristics of scientific breakthrough research. Related Articles | Metrics | Comments（0）

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How does the Quality of Online Health Information Trigger Cyberchondria? Multiple Mediating Roles of Perceived Uncertainty and Health Anxiety Jin Yan　Zhang Xiaohan　Sun Zhuo　Bi Chongwu Journal of Information Resources Management    2024, 14 (6): 156-169.   DOI: 10.13365/j.jirm.2024.06.156 Abstract （691）      PDF（pc） （1601KB）（435）       Knowledge map    Save In the era of "digital health", there has been a significant increase in the public's behavior of "Internet self-diagnosis" based on online health information. The uncertainty in the quality of online health information has heightened health anxiety and led to the emergence of cyberchondria. Understanding the impact of online health information quality on cyberchondria can offer valuable insights for improving online health information governance. This study investigates the mechanisms through which argument quality and source credibility affect cyberchondria from the perspective of online health information quality. We collected 386 valid responses through a questionnaire survey and performed data analysis and model testing with SmartPLS software. The results indicate that both the argument quality and source credibility significantly enhance users' perceived uncertainty and health anxiety, which are common factors contributing to the cyberchondria. Additionally, perceived uncertainty and health anxiety mediate the relationship between argument quality, source reliability, and cyberchondria. Furthermore, health anxiety serves as a mediator in the relationship between perceived uncertainty and cyberchondria. Related Articles | Metrics | Comments（0）

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Identifying Technology Opportunities from High-Value Patents in Universities: The Case of Generative Artificial Intelligence Ran Congjing　Li Wang　Huang Wenjun Journal of Information Resources Management    2024, 14 (4): 103-116.   DOI: 10.13365/j.jirm.2024.04.103 Abstract （689）      PDF（pc） （2703KB）（4590）       Knowledge map    Save This study proposes a method for identifying technological opportunities of high-value patents in colleges and universities, using theme modeling, mutation level method, machine learning and outlier detection algorithms to further identify technological themes and patented technologies with potential technological opportunities on the basis of evaluating high-value patents in colleges and universities. Taking the field of "Generative Artificial Intelligence" as an example for empirical evidence, the results show that the potential technology themes in the field of "Generative Artificial Intelligence" are centered on cutting-edge areas such as deep learning, neural networks and machine learning, and AI imaging and AI diagnosis and treatment are potential technological opportunities in this field, and the above technologies are vigorously supported by relevant national policies. This method can break through the core problems such as poor targeting of the identification results of a single technology opportunity identification method, low value of the identified patents, and a single form of the identification results, and the relevant identification results can provide decision-making support for the technology transfer, technology research and development, and technological innovation of universities. Related Articles | Metrics | Comments（0）

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Multidisciplinary Intersection and Multi-Scenario Embedding:Review of Domestic and International Research on Data Ethics Zhang Chuhui　Li Zhuozhuo　Pei Lei Journal of Information Resources Management    2025, 15 (2): 91-107.   DOI: 10.13365/j.jirm.2025.02.091 Abstract （687）      PDF（pc） （1589KB）（1843）       Knowledge map    Save In the age of digital intelligence, conflicts in data ethics arising from the exploitation and utilization of data have become increasingly pronounced, challenging societal governance structures and value systems. Research on data ethics has thus emerged as a shared concern across multiple disciplines. This paper adopts a systematic review method to analyze relevant literature, synthesizing data ethics theories and summarizing the core issues in data ethics research. Current studies demonstrate a clear trend toward interdisciplinary integration, with data ethics governance practices embedded across diverse digital contexts. Both theoretical and practical dimensions exhibit characteristics of multidisciplinarity and multi-contextuality. However, there remains significant scope to enhance the systematic, comprehensive, collaborative, and normative aspects of data ethics research. Future studies could explore three key directions: effectively linking empirical and normative research on data ethics, advancing interdisciplinary integration in data ethics studies, and transitioning from context-specific applications to holistic research addressing broader data governance ecosystems. Related Articles | Metrics | Comments（0）

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Research on the Organization and Management of Anticipatory Intelligence Work Li Guojun　Wang Yanfei　Xu Yang Journal of Information Resources Management    2024, 14 (3): 80-89.   DOI: 10.13365/j.jirm.2024.03.080 Abstract （684）      PDF（pc） （1312KB）（746）       Knowledge map    Save The purpose of this paper is to explore the practical experience of U.S. intelligence agencies in carrying out anticipatory intelligence work, and to provide reference and inspiration for China's intelligence agencies. Taking the four anticipatory intelligence projects initiated by the U.S. Intelligence Advanced Research Projects Agency (IARPA) as cases, it analyzes their mission scenarios, organized scientific research mode, implementation process and influence. This paper organizes the practical process of anticipatory intelligence work from four aspects, including the connotation of mission scenarios, the sources of clues, the indicators for judging, and the construction of teams. This paper summarizes the characteristics and revelations of anticipatory intelligence work from five aspects, including cross-domain synergy, quantitative assessment, win-win situation of science and commerce, diversified team, and impact assessment. Finally, the paper puts forward some suggestions for China's intelligence agencies to carry out anticipatory intelligence work. Related Articles | Metrics | Comments（0）

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Multi-level Functional Structure Recognition of Scientific Literature Liu Haotan　Liu Jiawei　Zhang Fan　Lu Wei Journal of Information Resources Management    2024, 14 (3): 90-103.   DOI: 10.13365/j.jirm.2024.03.090 Abstract （676）      PDF（pc） （3730KB）（777）       Knowledge map    Save The automatic recognition of structure function helps improve the efficiency of tasks such as fine-grained information retrieval, keyword extraction, and citation analysis. In response to the current challenges faced by structure function recognition research, including weak expression of internal textual dependencies and insufficient model generalization and transferability, this paper utilizes graph convolution neural networks to capture inherent dependency information and topological structures among word nodes, enhancing the modeling and representation capabilities of scientific publications. Additionally, adversarial learning is introduced to improve the generalization ability of the structure-function recognition model. The ScienceDirect dataset is selected to examine the recognition effectiveness of various model approaches for structure function at three different granularities: Header, Section, and Paragraph. Furthermore, we tested the transferability of multiple models across domains on PubMED-20k, a medical abstract structure function recognition dataset. Experimental results demonstrate that BERT+GCN get the best performance at the Header level, with an value of 88%, which is a 3% improvement over baseline models. At the Section level, the combination of BERT and GAN achieves the best performance, which is also a 3% improvement over baseline models. At the section paragraph level, the score reaches 68%. BERT+GCN exhibits superior cross-domain transferability compared to other models, achieving an score of 90% on cross-domain data. Related Articles | Metrics | Comments（0）

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A Study on the Correlation Factors of Psychological Resilience and Impact on AIGC Users’ Dropout Behavior Based on ISM-MICMAC Xie Jing　Zhang Hai　Shi Qin Journal of Information Resources Management    2025, 15 (1): 126-138.   DOI: 10.13365/j.jirm.2025.01.126 Abstract （675）      PDF（pc） （2456KB）（3040）       Knowledge map    Save In order to clarify the influencing factors of user dropout behavior in the context of AIGC, improve the user experience and willingness to continue using AIGC, and promote the high-quality development of domestic AIGC application platforms, this study drew on the grounded theory research paradigm and extracted causal factors of AIGC user dropout behavior through coding analysis of interview sample data. Based on the interpretative structural model, the intrinsic logic and correlation paths of causal factors of AIGC user dropout behavior were explored. Furthermore, the dependencies and driving forces between individual factors were studied using the cross-impact matrix multiplication method in order to identify the key factors influencing the dropout behavior of AIGC users.The research results show that psychological resilience, technological factors, perceived risk factors，and environmental factors are important factors affecting the dropout behavior of AIGC users. At the same time, it was found that psychological resilience can effectively alleviate the negative factors such as technological burden, technological risk, and information overload, and has important theoretical and practical significance for improving the sustained use behavior of AIGC users. At last, effective measures and suggestions have been proposed to resolve the dropout behavior of AIGC users and promote their continued use. Related Articles | Metrics | Comments（0）

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Identification of Potential R&BD Opportunities by Generative Topogrophic Mapping from a Dynamic Perspective Feng Lijie　Li Pengyue　Wang Jinfeng　Zhang Ke　Lin Kuoyi Journal of Information Resources Management    2024, 14 (3): 149-160.   DOI: 10.13365/j.jirm.2024.03.149 Abstract （673）      PDF（pc） （9019KB）（455）       Knowledge map    Save In the face of an increasingly competitive market environment, it is important for enterprises to objectively and accurately identify potential Research, Business and Development (R&BD) opportunities to reduce the risks of blind innovation and seize market advantages. From a dynamic perspective, this paper proposes a method for identifying potential R&BD opportunities by generative topogrophic mapping using trademark and patent texts. Through the mapping and inverse mapping of trademark blank, combined with the text similarity calculation of trademark blank and patent and theme evolution analysis results of trademark blank, the potential R&BD opportunities are accurately identified for enterprises. Finally, the effectiveness of the proposed method is verified by taking the smart home system as an example. The research results show that the gradual filling or replacement of business gaps in the selected target areas can reveal different paths of its evolution, thus identifying the technical opportunities with potential R&BD value, and then providing targeted reference ideas for enterprises to efficiently carry out technological innovation. Related Articles | Metrics | Comments（0）

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The Theoretical Logic and Implementation Path of Digital Industrialization Ma Feicheng　Wang Chunyang Journal of Information Resources Management    2024, 14 (6): 4-16.   DOI: 10.13365/j.jirm.2024.06.004 Abstract （671）      PDF（pc） （1268KB）（1274）       Knowledge map    Save Digital industrialization is the core foundation of the digital economy, exerting profound impacts on both the economy and society. This paper first reviews the concepts and measurement methods of digital industrialization and explores its logical development path. Technological innovation and application have transformed the structure and distribution of data, information, and knowledge, leading to the creation of distinctive products and services, which in turn foster the formation of digital industrial chains and clusters. Moreover, digital industrialization integrates with traditional industries, driving their transformation and upgrading. The emergence of new quality productive forces presents significant opportunities for the qualitative transformation of digital industrialization. Building on this foundation, the paper proposes implementation paths for advancing digital industrialization: leading the development of digital infrastructure through "new infrastructure" initiatives, strengthening core technology research and development through original and disruptive technologies, unlocking the potential of data resources through market-oriented reforms in data elements, ensuring a steady supply of digital talent through an improved talent cultivation and recruitment system, fostering digital industrial clusters led by strategic emerging industries, promoting the deep integration of digital industrialization with the real economy through the digital transformation of traditional industries, and unleashing new momentum for digital industrialization by constructing a comprehensive digital industrial ecosystem. This study offers insights into deepening the understanding of digital industrialization and advancing reforms in this critical field. Related Articles | Metrics | Comments（0）

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Personal Information Protection Misconducts in the Era of Digital Intelligence: An AIGC-Assisted Grounded Theory Analysis Zhao Haiping　Liu Zhixin　Sun Yanchao　Jiang Na Journal of Information Resources Management    2024, 14 (4): 59-69.   DOI: 10.13365/j.jirm.2024.04.059 Abstract （671）      PDF（pc） （1491KB）（1692）       Knowledge map    Save The extensive collection and deep utilization of personal information in the era of data intelligence highlight the significance of identifying misconducts in personal information protection. This study, guided by the current personal information protection laws and regulations, qualitatively analyzed 2100 cases of violations of laws. It aimed to identify common prevailing misconducts in safeguarding personal information during data processing activities. AIGC technology was introduced in the analytical process of Grounded Theory to categorize the identified misconducts. As a result, we identified eleven major categories and fifty-five subcategories of personal information protection conducts. We then particularly discussed key issues in personal information protection in the age of data intelligence. The findings of this study can not only offer a theoretical framework for future research in the field of personal information protection but also provide decision support for various organizations and government regulatory authorities. Related Articles | Metrics | Comments（0）

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Measuring the Academic Value of Scientific Papers by Integrating Innovation and Recognition—A Case Study in the Field of Artificial Intelligence Wu Jiachun　Dong Ke　Chen Xingyuan　Chen Lifang　Sun Jiaming Journal of Information Resources Management    2024, 14 (6): 17-30.   DOI: 10.13365/j.jirm.2024.06.017 Abstract （654）      PDF（pc） （2994KB）（2793）       Knowledge map    Save The full text of papers and their citation relationships convey a significant amount of academic information, which helps characterize the connotation of academic value and improve the precision of value assessment. This study builds a new evaluation index of academic value based on the epistemology of value, integrating the factual knowledge based on the papers themselves with the contingent knowledge based on external citations, and selecting papers in the field of artificial intelligence from the Web of Science database from 1990 to 2021 as the experimental data. Compared with traditional metrics, the academic value measurement proposed in this study comprehensively considers the value of internal innovation(represented by innovativeness), external recognition value(based on citation sentiment, citation intensity, and citation similarity). The results showed that:(1) value of internal innovation was not correlated with either the number of citations or the number of mentions;(2) value of external recognition was positively correlated with the number of mentions but not significantly correlated with the number of citations;(3) and academic value was positively correlated with the number of mentions, value of internal innovation, and value of external recognition, although value of external recognition was not significantly correlated with value of internal innovation. The results revealed that the impact indicator based on the number of citations has a lag and is insufficient to reflect the paper’s innovation. Compared to citation counts, the number of mentions, incorporating citation preference, shows slight improvement in measuring value of external recognition. The academic value measure proposed in this study has certain advantages in integrating the internal and external values of the paper and reflecting comprehensive academic value. Related Articles | Metrics | Comments（0）

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Government Data Openness Level Measurement, Regional Difference Decomposition and Dynamic Evolution：Evidence from 21 Provinces Gao Fan　Xu Sijia　Li Yiheng Journal of Information Resources Management    2024, 14 (5): 59-74,90.   DOI: 10.13365/j.jirm.2024.05.059 Abstract （650）      PDF（pc） （5908KB）（594）       Knowledge map    Save This study delves into the overall differences, regional differences, and dynamic evolution trends of interprovincial government data openness in China, with the aim of narrowing these differences, promoting balanced development in government data openness, and accelerating the digital transformation of government. Based on the Chinese Government Data Openness Evaluation Reports, the study employs the panel entropy method to calculate the comprehensive index of government data openness and four sub-dimensional indices across 21 provinces. Additionally, the study utilizes the Dagum Gini coefficient and Kernel Density Estimation to analyze the regional differences and evolution trends of government data openness across different regions. The findings reveal that the level of government data openness in China is on the rise, with significant and gradually widening regional differences. The differences across the four sub-dimensions vary, and except for the western region, the absolute differences between the eastern and central regions are expanding. This study innovatively applies the Gini coefficient to the theme of government data openness and equilibrium and integrates the entropy method, Dagum Gini coefficient, and Kernel density estimation to provide a progressive and comprehensive analysis of the overall differences, regional disparities, and future evolution dynamics of government data openness. Related Articles | Metrics | Comments（0）