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

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 （661）      PDF（pc） （790KB）（4847）       Knowledge map    Save Related Articles | Metrics | Comments（0）

Select

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 （1090）      PDF（pc） （5622KB）（3623）       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）

Select

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 （790）      PDF（pc） （2333KB）（2824）       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）

Select

The Development Pattern, Dilemmas, and Countermeasures of Government-Led Data Trading Platforms：An Analysis Based on Classical Grounded Theory Hua Meifang　Zhang Yong Journal of Information Resources Management    2025, 15 (2): 73-90.   DOI: 10.13365/j.jirm.2025.02.073 Abstract （470）      PDF（pc） （3045KB）（2747）       Knowledge map    Save Government-led data trading platforms are spearheading the robust development of China's data factor market. This study focuses on five bench mark platforms, employing the classical grounded theory framework to analyze their development patterns and challenges. The findings reveal that their developmental models can be summarized into five key elements: policy guidance, developmental strategies, standardization construction, platform services, and the cultivation of a digital business ecosystem. However, these platforms face several challenges, including a lack of core competitiveness, insufficient interconnectivity, pronounced data silos, and limited transaction scales. To address these challenges, platforms need to expand their market influence through differentiated positioning, joint construction of a standardized interconnected ecosystem, collaborative development of digital business alliances, and active expansion of bilateral user groups. Meanwhile, the National Data Administration should undertake overall planning for platform deplayment, strengthen integrated security supervision, and establish a robust safety framework to ensure the healthy development of the market. Related Articles | Metrics | Comments（0）

Select

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 （536）      PDF（pc） （2456KB）（2619）       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）

Select

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 （844）      PDF（pc） （4448KB）（2522）       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）

Select

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 （415）      PDF（pc） （1589KB）（1754）       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）

Select

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 （699）      PDF（pc） （2326KB）（1445）       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）

Select

Exploring Factors Affecting Individual’s Social Loafing Propensity in Human-AI Collaborative Creative Task Wang Siran　Yan Qiang Journal of Information Resources Management    2025, 15 (2): 123-136.   DOI: 10.13365/j.jirm.2025.02.123 Abstract （289）      PDF（pc） （1035KB）（1377）       Knowledge map    Save Drawn on motivation theory and social cognitive theory, this study investigates the potential factors that affect individual social loafing tendency in these tasks. The findings reveal that task visibility, perceived others’ loafing tendency, and distributive justice significantly affect individuals’ social loafing tendencies when collaborating with AI. Additionally, creative self-efficacy indirectly affects social loafing tendencies through personal outcome expectation and negatively moderates the relationship between perceived others’ loafing tendency and individual social loafing tendency. These results enhance the understanding of how an individual’s social loafing tendency is affected in human-AI collaborative creative tasks and offer practical suggestions for practitioners to improve human-AI collaboration. Related Articles | Metrics | Comments（0）

Select

Thirty Years of the Internet in China: Formation and Development of Internet with Chinese Characteristics Xie Xinzhou　Zhang Jingyi Journal of Information Resources Management    2025, 15 (1): 21-29.   DOI: 10.13365/j.jirm.2025.01.021 Abstract （414）      PDF（pc） （741KB）（1290）       Knowledge map    Save This article systematically reviews the evolution of the Internet in China over the past 30 years, elucidating the exploration, formation, and development of the Internet development path with Chinese characteristics. China has adhered to an inclusive and symbiotic Internet development philosophy, forming a diverse and balanced Internet system and embarking on a uniquely Chinese way of Internet governance. Key characteristics of the Chinese Internet, such as technology-driven initiatives and industrial innovation, have become significant manifestations of this unique path. The paper summarizes the achievements and contributions of the Chinese Internet while also pointing out the major challenges China faces in the future. It aims to provide beneficial references for the high-quality development and innovative of the Chinese Internet. Related Articles | Metrics | Comments（0）

Select

Policy Changes in Digital Service Regulation: The EU’s Approach and The China’s Mirror Li Guihua　He Peipei　Huang Lin Journal of Information Resources Management    2025, 15 (2): 59-72.   DOI: 10.13365/j.jirm.2025.02.059 Abstract （255）      PDF（pc） （1951KB）（1244）       Knowledge map    Save The negative externalities of digital services on Internet platforms has attracted extensive regulatory attention. The study of the global typical EU digital service regulation policy changes can provide a mirror for China's Internet platform regulation and digital service policy. Based on the policy feedback theory, this paper constructs an analytical framework, standardizes the content and reform practice of the EU digital service regulation policy, and combs the evolution of the EU digital service regulation policy of "lenient responsibility-balanced responsibility-diligence responsibility". In this process, the regulation activities of policy change are influenced by the first order feedforward resource effect and the interpretation effect. The formation of new public policy is shaped by the evolution effect of second-order feedback and the learning effect. Based on this logic, the EU has created a policy reform approach for digital service regulation, which covers three major strategies: policy consolidation, policy learning and policy adaptation. To sum up the experience of EU digital service regulation policy is of great significance for our country to learn from EU approach scientifically and rationally. Related Articles | Metrics | Comments（0）

Select

Analysis on the Differences in the Diffusion Speed of Scientific Papers and Its Influencing Factors from the Perspective of Social Media Users Hou Jianhua　Yang Siyu　Wang Yuanyuan　Zhang Yang Journal of Information Resources Management    2025, 15 (2): 151-162,封3.   DOI: 10.13365/j.jirm.2025.02.151 Abstract （282）      PDF（pc） （5238KB）（1082）       Knowledge map    Save This study aimed to develop a metric for measuring the diffusion speed of scientific knowledge on social media platforms, using Twitter as an example, and to investigate the differences between short-term and long-term diffusion speeds of scientific papers, as well as their influencing factors. Articles published in Volumes 66-68 of CA: A Cancer Journal for Clinicians were selected as the research sample. The entropy weight method was used to construct a metric for diffusion speed. SPSS was used to analyze the differences between short-term and long-term diffusion speeds, while Eviews was employed to conduct Granger causality analysis to identify the factors influencing these differences. The analysis revealed that the number of keywords and the number of authors significantly influenced the diffusion speed of scientific knowledge on social media. In the short term, the diffusion speed was Granger-caused by the citation count of the first author, whereas in the long term, it was influenced not only by citation counts but also by the first author’s academic impact, as measured by their h-index. These findings suggested that the diffusion speed of scientific knowledge on social media is affected by multiple factors. Specifically, the number of keywords and the number of authors played a significant role in both short-term and long-term diffusion. Moreover, in the short term, the citation count of the first author was a key driver, while in the long term, both citation counts and the first author’s academic impact contribute to sustained dissemination. Therefore, scholars with higher academic influence were more likely to facilitate the long-term diffusion of their scientific papers on social media, primarily through the endorsement of their academic reputation. Related Articles | Metrics | Comments（0）

Select

Experts in Information Resource Management Discipline Discussing "The 2024-2035 Master Plan on Building China into a Leading Country in Education"(Part 2): Opportunities and Challenges for the Discipline Wang Xiaoguang Liu Yuenan Zhang Yang Journal of Information Resources Management    2025, 15 (3): 4-10.   DOI: 10.13365/j.jirm.2025.03.004 Abstract （237）      PDF（pc） （629KB）（1059）       Knowledge map    Save Related Articles | Metrics | Comments（0）

Select

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 （475）      PDF（pc） （5021KB）（921）       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）

Select

Analysis on the Construction and Characteristics of Data Governance and Policy Curriculum in iSchools iCaucus Abroad Liang Shuang　Zhou Qingshan Journal of Information Resources Management    2025, 15 (1): 30-41.   DOI: 10.13365/j.jirm.2025.01.030 Abstract （393）      PDF（pc） （1437KB）（919）       Knowledge map    Save This study investigates and analyzes data governance and policy curriculum in iSchools iCaucus abroad, and summarizes the teaching contents and characteristics, so as to provide reference for the construction of related courses and talent cultivation models in China. By conducting online research, the course information and syllabuses are obtained. The study summarizes the teaching contents and constructs a framework for course classification by using content analysis, and then analyzes the teaching conditions. The findings reveal that data governance and policy courses abroad are mainly divided into five categories: management and governance, ethics and morality, policy and law, security and assurance, and comprehensive category. These courses exhibit systematic and diverse characteristics in terms of teaching objectives, prerequisites, course materials, teaching and assessment methods. Finally, this paper puts forward some suggestions on the improvement of related courses and the optimization of the teaching models in China from the aspects of curriculum system, course content and course teaching. Related Articles | Metrics | Comments（0）

Select

Exploration of the Five-stage Theoretical Model of Data Elementization of Cultural Heritage Sun Jing　Zhang Tong　Wang Jiandong Journal of Information Resources Management    2025, 15 (3): 37-48.   DOI: 10.13365/j.jirm.2025.03.037 Abstract （265）      PDF（pc） （1461KB）（891）       Knowledge map    Save The elementization of cultural heritage data demonstrates a positive role in stimulating the value of such data and promoting the development of the cultural industry. However, challenges such as difficulties in data rights confirmation, lack of standards, an underdeveloped market system, and inconsistent pricing logic persist throughout the elementization process. This article innovatively proposes a five-stage theoretical model for the elementization of cultural heritage data, offering insights into activating its value and facilitating the transformation and upgrading of the cultural industry. At different stages of the elementization process, it is necessary to address these challenges and promote development by building a national platform for the registration and verification of cultural heritage data property rights, formulating standards and guidelines for data product development, optimizing valuation frameworks for data assets, improving trading mechanisms, and enhancing the regulatory system for financial innovation related to cultural heritage data. Related Articles | Metrics | Comments（0）

Select

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 （937）      PDF（pc） （1353KB）（839）       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）

Select

Evaluation of Prompt Fine-Tuning Data Efficacy in Large Language Models： A Focus on Data Quality Liu Xiaohui　Ran Congjing　Liu Xingshen　Li Wang Journal of Information Resources Management    2025, 15 (3): 108-121.   DOI: 10.13365/j.jirm.2025.03.108 Abstract （396）      PDF（pc） （5454KB）（737）       Knowledge map    Save Breakthroughs in generative artificial intelligence have led to the emergence of phenomenon-level large language models (LLMs), such as ChatGPT, posing unprecedented challenges to traditional data utility assessment methods. In response, this study focuses on evaluating the utility of instruction-tuning data for LLMs by establishing a multi-dimensional assessment framework that integrates three key dimensions—complexity, usability, and diversity—and accordingly proposes a novel data utility evaluation function. Experiments on multiple publicly available instruction-tuning datasets demonstrate that the proposed approach provides a reasonable and effective means of measuring data quality, while the reasoning loss observed in LLMs fine-tuned on different datasets exhibits a high degree of consistency with the proposed evaluation metrics. This work is the first to directly employ reasoning loss as a measure of the quality of LLM instruction-tuning data, further introducing the three dimensions—complexity, usability, and diversity—to characterize “high-quality data”. By proposing new quantitative metrics, this study offers important theoretical and practical guidance for future improvements in the quality of instruction-tuning data for large language models and related research applications. Related Articles | Metrics | Comments（0）

Select

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 （690）      PDF（pc） （2167KB）（734）       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）

Select

Digital Interaction: A New Dimension for Analyzing Digital Inequality Zhang Yuhao　Yan Hui Journal of Information Resources Management    2025, 15 (2): 36-45.   DOI: 10.13365/j.jirm.2025.02.036 Abstract （319）      PDF（pc） （745KB）（669）       Knowledge map    Save With the rapid development of Information and Communication Technology, accelerating digital development and building Digital China is one of our country’s important development goals. Narrowing the digital divide and reducing digital poverty are key measures to achieve this goal. This study aims to develop the concept of digital interaction, thereby enriching the connotations and scope of digital inequality and advancing theoretical research on digital inequality. Based on the theoretical framework related to social support and social interaction, this study utilizes a combination of semi-structured interview methods and diary methods. Data was collected from 43 interviewees and 18 recorders through various means such as audio recordings, text, and images. The aim was to explore and analyze the manifestations of digital interaction across different age groups. The study constructed a three-dimensional theoretical framework to describe digital interaction, identifying three main categories: interaction types, ties between interaction participants, and interaction content. The interaction types encompass ten subcategories: receiving help, offering help, digital sharing, digital competition, digital cooperation, digital restriction, digital conflict, digital compliance, digital imitation, and digital exchange. The relationships between interaction participants include two subcategories: strong ties and weak ties. The interaction content comprises five subcategories: devices, networks, applications, functions, and information. This research provides a theoretical foundation for the development of subsequent measurement frameworks and explores how digital interaction influences digital inequality. The findings offer valuable insights for policymakers, researchers, and social workers in designing more effective interventions to bridge the digital divide and promote social equity. Related Articles | Metrics | Comments（0）

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 （97）      PDF（pc） （2257KB）（609）       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 Measurement Model for Industrial Technology Involution Index：Empirical Evidence from Strategic Emerging Industries in Shandong Province Guo Rui　Dong Kun　Tian Changwei　Chen Kexin Journal of Information Resources Management    2025, 15 (1): 102-112.   DOI: 10.13365/j.jirm.2025.01.102 Abstract （413）      PDF（pc） （2713KB）（584）       Knowledge map    Save With the continuous intensification of industrial technology competition, some industries show obvious trends of repeated innovation and technological convergence, the leading and breakthrough of technological innovation are weakened, and industrial technological progress is slowed down. In order to actively cope with this trend of "involution", it is urgent to make a scientific evaluation of the current degree of industrial technology involution. Firstly, this study clarified the connotation and characteristics of industrial technology involution. Then, we constructed a measurement model based on five dimensions of technological growth, technological difference, technological leadership, technological breakthrough and technological expansiveness to measure the degree of industrial technology involution. Finally, we selected the strategic emerging industries in Shandong Province for empirical study, measuring their technological involution index and analysing the reasons. The model can effectively measure the degree of industrial technology involution and provide a quantitative and process method model for the measurement of industrial technology involution. Related Articles | Metrics | Comments（0）

Select

App Walkthrough Method: A New Approach for Human Information Behavior and Interaction Design in the Era of Digital Intelligence Zhao Yuxiang　Ye Xujie　Li Jinhao Journal of Information Resources Management    2025, 15 (3): 60-75.   DOI: 10.13365/j.jirm.2025.03.060 Abstract （332）      PDF（pc） （3839KB）（496）       Knowledge map    Save In the era of digital intelligence, the proliferation of mobile applications has profoundly altered the way individuals interact with information and technology, posing challenges to the study of human information behavior and spurring the need for innovative research methods. The App Walkthrough Method, an emerging research approach, offers new opportunities and powerful tools for the investigation of human information behavior and human-computer interaction. This paper provides a systematic review of the App Walkthrough Method, sorting out the relevant research, examining in detail the evolution of the method's origin and its theoretical basis, elaborating the specific implementation steps, and analyzing in depth the research object and research theme. Furthermore, this paper proposes key areas for future research, aiming to bridge the gap between theoretical conceptualization and practical applications, and to offer a new research perspective and framework for the fields of human information behavior and user experience design. 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 （191）      PDF（pc） （3297KB）（493）       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

The Identification and Application of Theories in Inter-organizational Information Sharing Research Zhou Lihong　Hu Jiangfeng Journal of Information Resources Management    2025, 15 (1): 42-53.   DOI: 10.13365/j.jirm.2025.01.042 Abstract （434）      PDF（pc） （3220KB）（451）       Knowledge map    Save Inter-organizational information sharing(IIS) research is becoming a topic of great interest to organizations and researchers around the world. The introduction of different theoretical perspectives is crucial to exploring the problems that exists in IIS. Based on a survey of the research literature closely related to IIS, this paper has identified 19 specific theories appearing in the literature which can be categorized into four perspectives in terms of game, information resource, relationship, and tension respectively. Additionally, this paper further summarizes the thematic distribution characteristics of the theories used in this research field, which are roughly focusing on four aspects: barriers, influencing factors, realization paths, and mechanisms of action. Besides, the research team constructs a system of IIS research topics and theoretical application. Finally, according to the current status of IIS theory application, future research directions are proposed. The findings of this research provide reference and guidance for systematically grasping the theoretical system composition of IIS research and the hot topics in the field. Related Articles | Metrics | Comments（0）

Select

Theoretical Framework on Synergistic Mechanism and Extraction Strategy of Scientific and Technological Knowledge Driven by Data-Intelligence Xiang Bo　Yan Zhaoping　Pan Zhuoya　Yu Dejian　Shi Jin Journal of Information Resources Management    2025, 15 (3): 122-134.   DOI: 10.13365/j.jirm.2025.03.122 Abstract （252）      PDF（pc） （3716KB）（439）       Knowledge map    Save It is the important issue to promote the value realization of data elements through clarifying the multiple stakeholders and multi-source heterogeneous data of scientific and technological knowledge, and their synergistic mechanism, as well as delineating the knowledge extraction paths empowered with big data and intelligent technology. Based on the process of data-to-wisdom derivation in the DIKW chain, this study constructed a synergistic framework of scientific and technological knowledge involving multiple stakeholders, such as universities, research institutes, enterprises, government and the public, covering multi-source data such as papers, patents, products, policies and user-generated content. Furthermore, this study expanded the front-end and back-end structures of scientific and technological knowledge extraction paths, and explored the knowledge extraction outcomes and their diverse service scenarios under intelligent strategy combination patterns. Driven by digital intelligence, scientific and technological knowledge has formed a bi-directional and multi-dimensional intertwined synergy pattern under the direction of multi-stakeholders to facilitate the interaction and matching of knowledge supply and demand. Related Articles | Metrics | Comments（0）

Select

The Configurational Approach to Innovation in Technology-based Small and Medium-sized Enterprises Based on the Synergistic Framework of “Capabilities-Motivation-Policy” Wang Liuhong　Wang Hongqinling　Ba Zhichao　Wang Qi Journal of Information Resources Management    2025, 15 (3): 135-151.   DOI: 10.13365/j.jirm.2025.03.135 Abstract （265）      PDF（pc） （2605KB）（413）       Knowledge map    Save Technology-based small and medium-sized enterprises (SMEs) serve as a pivotal force in bolstering independent innovation and facilitating research transformation. Understanding how technology, market forces, and policy mix interact to influence their innovation is crucial for fostering sustainable and high-quality growth among technology-based SMEs. Given the current dearth of comprehensive discussions on multifaceted conditions and mechanisms underlying local technology-based SME innovation, this study draws the Fogg behavior model (FBM) to conceptualize the innovation process of these enterprises as a collective driving behavior jointly shaped by capabilities, motivations, and policy interventions. It introduces an integrated analytical framework to explore the innovation landscape of local technology-based SMEs and employs a dynamic fsQCA method to conduct a configuration analysis of 283 cases from urban technology-based SMEs across China between 2015 and 2022. This analysis incorporates both inter-group and intra-group comparisons to reveal the spatiotemporal distribution disparities in configuration coverage. Our results indicate that: 1)the innovation of technology-based SMEs within a city is jointly propelled by its fundamental capabilities, innovation motivations, and a combination of policy interventions; 2)the synergistic interaction of “capabilities-motivations-policy” forms five distinct configuration paths that facilitate high-level innovation among local technology-based SMEs, exhibiting notable spatiotemporal heterogeneity; 3)under conditions of strong innovation motivation, capabilities and policy intervention combinations enhance the innovation level of local technology-based SMEs through equivalent substitution, achieving similar outcomes through diverse approaches. Related Articles | Metrics | Comments（0）

Select

Unlocking the Value of Local Chronicle Data Elements: From Formation to Realization Ding Qiujing　Zeng Jianxun Journal of Information Resources Management    2025, 15 (3): 49-59.   DOI: 10.13365/j.jirm.2025.03.049 Abstract （235）      PDF（pc） （1325KB）（356）       Knowledge map    Save Against the backdrop of China's systematic layout of the data infrastructure system, the formation and realization paths of the value of local chronicle data elements are further clarified. Based on the relevant research findings related to the development and utilization of local chronicles and the realization of data element value, this paper first articulates the connotation and characteristics of local chronicle data elements, pointing out that local chronicle data elements have the following characteristics: non-excludability of public culture, synergism of data aggregation, derivativeness of knowledge recombination, and complexity of property rights management. Secondly, it constructs a local chronicle data element value chain that covers the entire process from data collection and aggregation to data service utilization. Finally, it proposes strategies for the realization of the value of local chronicle data elements from four aspects, including top-level design, unified registration mechanism, product system construction, and the construction of a trustworthy data space. The research findings are conducive to promoting the expansion of China's local chronicle work from compilation to data production and application. They also help to stimulate the innovative vitality of local chronicles and enable them to play a greater role in the construction of Digital China, especially in the strategy of cultural digitalization. Related Articles | Metrics | Comments（0）

Select

Constructing a New Ecology of Information Resources Management Discipline Development Empowered by New Quality Productivity Forces Chu Jingli　Liu Jingyi　Li Nan Journal of Information Resources Management    2025, 15 (2): 13-19.   DOI: 10.13365/j.jirm.2025.02.013 Abstract （308）      PDF（pc） （654KB）（264）       Knowledge map    Save Constructing the new ecology of the development of information resources management discipline empowered by new quality productivity forces is of great significance for the high-quality development of the discipline. It is the core key to discipline construction and development. This article first analyzes 9 aspects for the information resources management discipline to understand new quality productive forces, such as new thinking, new technologies, and new methods, and advocates integrating information resources into the development of disciplines. Then, the fundamental of discipline construction is proposed, and the traditional ecology and new ecology of the discipline are discussed. Finally, it proposes the new ecological construction paths of information resources management discipline, which includes strengthening the top-level design of the discipline, adhering to the right path and innovation, striving to build a second-level discipline system, highlighting the characteristics of new liberal arts and talent training, strengthening research capabilities and scientific research and teaching output, and narrowing the gap between academia and industry. Related Articles | Metrics | Comments（0）

Select

Journal of Information Resources Management    2025, 15 (1): 154-160.   DOI: 10.13365/j.jirm.2025.01.154 Abstract （397）      PDF（pc） （688KB）（182）       Knowledge map    Save Related Articles | Metrics | Comments（0）