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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 （1314）      PDF（pc） （4159KB）（15598）       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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Criteria of Structural Equation Modeling: Comparisons and Enlightenments of CB-SEM and PLS-SEM Yuan Ye　Shiau Wenlung　Yu Yuan　Wang Kanliang　Li Yiran Journal of Information Resources Management    2023, 13 (3): 6-22.   DOI: 10.13365/j.jirm.2023.03.006 Abstract （4857）      PDF（pc） （2464KB）（8573）       Knowledge map    Save Structural Equation Modeling (SEM) is used to analyze the complex relationships between observed variables and latent variables. Covariance-based structural equation modeling (CB-SEM) and partial least squares structural equation modeling (PLS-SEM) are the two types of SEM. SEM has been widely used in social science such as organizational management, information systems, marketing management and other disciplines. In recent years the number of research papers using PLS-SEM method has increased. Since CB-SEM and PLS-SEM are different in algorithm and requirements, the application of unsuitable methods may lead to inaccurate results. Therefore, it is necessary to understand the differences between the two methods and report guidelines. This paper reviews the conditions and application criteria of CB-SEM and PLS-SEM, and takes the use of fintech by wealth management enterprises as an example to compare the analysis process and results of the two methods, emphasizing the importance and necessity of choosing appropriate methods. This paper provides a valuable reference for researchers to use SEM for accurate data analysis. Related Articles | Metrics | Comments（0）

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Research on the Formation Mechanism of Social Media Group Polarization under Hot Events Peng Guochao　Cheng Xiao Journal of Information Resources Management    2023, 13 (2): 42-52.   DOI: 10.13365/j.jirm.2023.02.042 Abstract （1908）      PDF（pc） （1084KB）（8501）       Knowledge map    Save By exploring the mechanism of generating social media group polarization, this study aims to provide a reference for guiding and avoiding social media group polarization. Based on the social burning theory, this study uses existing literature and selected cases to refine six explanations, including interest oppeals, news narrative framework, opinion leaders, initial media, issue types, and communication forms, and uses the clear-set qualitative comparative analysis to explore the generative path of social media group polarization. The study found that news narrative framework is a necessary condition for social media group polarization, and opinion leaders are the core condition for social media group polarization, which act as "accelerators" to jointly promote the generation of group polarization; As the "ignition temperature", the issule type has a moderating effect on the generation of social media group polarization; Hot events in the form of pictures and texts are more likely to cause group polarization on social media. Related Articles | Metrics | Comments（0）

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Research on the Path to Realize the Value of Data Elements Ma Feicheng　Wu Yishu　Lu Huizhi Journal of Information Resources Management    2023, 13 (2): 4-11.   DOI: 10.13365/j.jirm.2023.02.004 Abstract （2148）      PDF（pc） （1011KB）（5025）       Knowledge map    Save Identifying the path to realize the value of data elements is of great significance to accelerate the deep integration of digital economy and real economy. In order to explore the mechanism and path of realizing the value of data elements, this study combs the existing ways and attributes of data elements, clarifies the mechanism of realizing the value of data elements on this basis, and constructs the value realization path including basic activities, auxiliary activities and value development based on the value chain theory. The research shows that the value realization mechanism of data elements includes subject participation mechanism, marketization realization mechanism, ownership definition and transfer mechanism. Data collection, data organization, data circulation and data utilization are the basic paths to realize the value of data elements, while the three auxiliary activities of data security protection, data technical support and data talent guarantee ensure the realization of value. 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 （854）      PDF（pc） （790KB）（5024）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Value Creation of Data Elements: Review and Research Prospects Zhao Caijing Journal of Information Resources Management    2024, 14 (2): 41-53.   DOI: 10.13365/j.jirm.2024.02.041 Abstract （1792）      PDF（pc） （985KB）（5010）       Knowledge map    Save Data has become a key production factor in China’s economic and societal development, with the circulation and value realization of data elements progressively becoming a crucial means for the high-quality development of the digital economy. This paper reviews the literatures and practices concerning the value creation of data elements, examining aspects such as the connotation, mechanisms, driving factors, obstacles and development paths. Based on this, this paper identifies gaps in the existing literatures on the value creation of data elements, advocating for a future research agenda that emphasizes interdisciplinary integration. It also proposes to explore future research directions and methodologies from perspectives including the conceptualization and measurement of data element value, determinants, and mechanisms of influence. Related Articles | Metrics | Comments（0）

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The Academic Dialogue Journey in Case Study Research: Insights from the Information Systems Field Li Liang　Wang Mingxu Journal of Information Resources Management    2023, 13 (3): 112-123.   DOI: 10.13365/j.jirm.2023.03.112 Abstract （656）      PDF（pc） （2125KB）（4982）       Knowledge map    Save In recent years, the case study method has been attached great importance and widely used in the domestic management academia. However, the development of domestic case studies was hindered by a number of typical problems that led to weak theoretical contributions. In order to address these problems, this paper argues that the researcher should carry on in-depth dialogues with literature, theory, phenomenon, methodology and self in conducting case study research. We analyze exemplary case studies from leading journals in the field of information systems and refine the aforementioned five aspects into nine specific academic dialogues. The “best practices” highlighted in these exemplary case studies provide researchers with rich and referential examples. Finally, we make some suggestions on how to improve the quality of domestic case studies. Related Articles | Metrics | Comments（0）

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The Evolution and Contemporary Perspectives on the Empowerment of Intelligence by Artificial Intelligence Technology Li Guangjian　Pan Jiali Journal of Information Resources Management    2024, 14 (2): 4-20.   DOI: 10.13365/j.jirm.2024.02.004 Abstract （1682）      PDF（pc） （1976KB）（4953）       Knowledge map    Save This paper systematically explores the evolution and application of artificial intelligence (AI) technology in intelligence work, revealing its new developments in ideology, characteristics, technical methods, and practical scenarios. Transitioning from a rule-based paradigm to the era of foundation model approaches, AI presents significant opportunities for the intelligence field’ s enhancement in intelligence processing. However, it also introduces novel challenges related to ethics, legal considerations, and privacy concerns. The paper identifies issues and challenges that should be addressed by the intelligence community in the new era of intelligence. Furthermore, the paper proposes forward-thinking strategies to address these issues and challenges, providing valuable insights for the stable development of intelligence field. Related Articles | Metrics | Comments（0）

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A Review of Secondary Analysis in Information Management and Information Systems Research in China: Research Methods,Topics, and Theory Applications Chen Liping　Ren Fei Journal of Information Resources Management    2023, 13 (3): 61-78.   DOI: 10.13365/j.jirm.2023.03.061 Abstract （1216）      PDF（pc） （1792KB）（4660）       Knowledge map    Save This study conducts a content analysis of 282 Chinese research papers published from 2012 to 2022 that use secondary analysis in the area of information management and information systems (IM&IS), aiming to reveal the distribution and trend of research methods, topics, and theory applications. The results show that the advantages of secondary analysis in data acquisition and causality identification are increasingly prominent, as reflected in the gradual diversity of data sources, rigorous empirical analysis on causality testing, richer mechanism analyses, and the emergence of mixed-method research. Four research topic trends have been identified, including macro digital development, enterprise digital transformation, information interaction between enterprise and market, and user online behavior. However, IM&IS theory development and the application of Chinese theories require further improvement. This study is novel in that it combines bibliometric analysis with machine learning methods (LDA and DTM) to reveal a multi-dimensional overview of the secondary analysis in IM&IS in China. The findings provide evidence and guidelines for further strengthening research norms, grasping research topic trends, developing and applying theories, as well as suggestions for disciplinary development and strategic research planning. 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 （658）      PDF（pc） （2703KB）（4401）       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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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 （894）      PDF（pc） （3124KB）（4037）       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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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 （1237）      PDF（pc） （5622KB）（4020）       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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Online Brand Community Users’ Interaction Behavior Transformation Mechanism for Value Co-creation：Based on Grounded Theory Le Chengyi　Zhu Xinya Journal of Information Resources Management    2023, 13 (3): 124-139.   DOI: 10.13365/j.jirm.2023.03.124 Abstract （1125）      PDF（pc） （2271KB）（3976）       Knowledge map    Save Companies use online brand communities to facilitate user interaction behaviors as a major path to value co-creation. Through in-depth interviews with 19 active community members, data were collected and programmatically coded using a grounded theory approach to construct a theoretical model of the transformation process and drivers of user interaction behavior. According to the extent of user participation in value co-creation in the community, user interaction behavior can be classified as human-machine interaction, human-human interaction and human-enterprise interaction. The transition from human-machine interaction to human-human interaction is mainly influenced by information quality, social experience and self-realization, while the transition from human-human interaction to human-enterprise interaction is mainly influenced by community incentive, social enhancement and symbiotic co-creation. And the driving factors of users’ behavioral transitions can be categorized into visceral layer, behavioral layer and reflective layer, with information quality and community incentives in the visceral layer playing a greater role in the early stages of each behavioral transition, while self-realization and symbiotic co-creation in the reflective layer having the most effective and longest driving role. The results provide a theoretical reference for an indepth understanding of the transformation mechanism of user interaction behaviors in online brand communities, as well as suggestions for enterprises to target the promotion of user interaction behaviors and value co-creation at different stages. Related Articles | Metrics | Comments（0）

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Influencing Factors of Online Health Information Searching Behavior Based on DEMATEL-ISM：From a Meta-analysis of Empirical Studies at Home and Abroad Zhao Wenjun　Meng Kai　Ma Jinhui　Ni Zhifei Journal of Information Resources Management    2023, 13 (2): 53-66.   DOI: 10.13365/j.jirm.2023.02.053 Abstract （1036）      PDF（pc） （3687KB）（3660）       Knowledge map    Save Systematic analysis of the influencing factors of online health information search behavior and its hierarchical logical relationship, this paper provided theoretical guidance for deepening academic research on online health information search behavior and optimizing online health information services. To synthesize and analyze the empirical studies on the influencing factors of online health information-seeking behavior at home and abroad based on the meta-analysis method, the overall effect of these influencing factors on online health information-seeking behavior and their significance were assessed, and 16 influencing factors of online health information-seeking behavior were extracted accordingly. Then DEMATEL-ISM was introduced to analyze the hierarchical logical structure and action path among the influencing factors. The results showed that health anxiety, health literacy, self-efficacy, health status, trust, and income were located at the top of the hierarchical model and directly influenced users’online health information-seeking behavior, categorized as neighborhood influencing factors. Nine influencing factors, such as perceived risk, perceived value, social support, and information quality, were located in the progressive hierarchy model’s middle level and categorized as transitional influencing factors. Internet access was located at the bottom of the recursive hierarchy model, and was classified as a fundamental influencing factor. Related Articles | Metrics | Comments（0）

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Research on the Model of Public Data Entering the Data Element Market Fan Jiajia Journal of Information Resources Management    2024, 14 (2): 68-81.   DOI: 10.13365/j.jirm.2024.02.068 Abstract （724）      PDF（pc） （1208KB）（3520）       Knowledge map    Save Public data is an important component of the data marketplace, yet its modes of entry and participation categories have received limited attention in the current literature. This paper investigates the modes of public data participation in the data element market, both domestically and internationally, through sorting and comparative analysis. We identified two main categories and five modes for public data to enter the data element market, including: 1) the primary market (authorized operation) + secondary market (trading in the data exchange) mode, 2) the public data development and utilization + trading outside the data exchange mode, 3) the construction of a public data circulation market mode based on data platforms, 4) the trading mode using data brokers and data intermediaries, and 5) the participation in the data market mode through (public) data trusts. Building upon this categorization, the paper proposes an ideal mode for public data entry into the data element market, outlined in three phases: data acquisition, data product production, and data product trading. This paper offers insights for strategic selection regarding the entry of public data into the data element market in China. Related Articles | Metrics | Comments（0）

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Exploring the Generation Mechanism of Affective Responses of User Danmaku Commenting Behavior in Reaction Videos Ye Xujie　Zhao Yuxiang　Zhang Yan　Li Jinhao　Preben Hansen Journal of Information Resources Management    2024, 14 (2): 104-120.   DOI: 10.13365/j.jirm.2024.02.104 Abstract （988）      PDF（pc） （3042KB）（3393）       Knowledge map    Save Investigating the generation mechanism of affective response of danmaku commenting behavior in reaction videos can provide valuable insights into the reasons for affective generations and the process of affective change. This paper takes reaction videos of the Bilibili video website as examples. We conduct coding using the directed content analysis method by selecting the danmaku resources, video content, and reactor responses of 11 popular videos in different camps as samples. Based on the Affective Response Model (ARM), this paper builds a theoretical framework of the generation mechanism of affective responses of user danmaku commenting behavior in reaction videos. The results suggest that affective responses of user danmaku commenting behavior in reaction videos generally follows the path of "information cues-affective response", that is, information cues can arouse emotions or particular affective responses autonomously, and they can also affect the generation of emotions or learned affective responses by arousing particular affective responses. The proposed framework helps to improve the contextualized exploration of ARM theory in computer-mediated communication and will also provide practical implications for optimizing user-information interaction in social media. Related Articles | Metrics | Comments（0）

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Intelligent and Smart Service of Multi-model Cultural Heritage Resources: From Available to Evidential and Experiential Xia Cuijuan Journal of Information Resources Management    2023, 13 (5): 44-55.   DOI: 10.13365/j.jirm.2023.05.044 Abstract （1011）      PDF（pc） （2030KB）（3243）       Knowledge map    Save The development of data and intelligence technologies is promoting the transformation from "digital GLAMs" to "smart GLAMs". In the transformation from digitalization to datafication and then to intelligence, the cultural heritage resources of GLAMs show the multi-model characteristics of multimedia, multi-format and multi-granularity. Aiming at the problem of how GLAMs provide intelligent services based on multmodel cultural heritage resources, this paper summarizes the transformation path of cultural heritage resources from digital, data to intelligent services based on case analysis and literature research. According to the low to high degree of resource intelligence, inteligent services can be summarized into three modes: available, evidential and experiential, which correspond to three different demand scenarios: resource-centered services, digital intelligence evidence-based services, and interactive experience-centered services. It is concluded that the intelligent services of multi-model cultural heritage resources are to predict in advance and automatically adapting to users' needs for different modes of cultural heritage resources in different demand scenarios. 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 （928）      PDF（pc） （2333KB）（3098）       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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Construction of Chinese Classical-Modern Translation Model Based on Pre-trained Language Model Wu Mengcheng　Liu Chang　Meng Kai　Wang Dongbo Journal of Information Resources Management    2024, 14 (6): 143-155.   DOI: 10.13365/j.jirm.2024.06.143 Abstract （531）      PDF（pc） （1784KB）（3030）       Knowledge map    Save This study aims to construct and validate a Chinese ancient-modern translation model based on pre-trained language models, providing strong technical support for the research of ancient Chinese and the inheritance and dissemination of cultural heritage. The study selected a total of 300,000 pairs of meticulously processed parallel corpora from the "Twenty-Four Histories" as the experimental dataset and developed a new translation model—Siku-Trans. This model innovatively combines Siku-RoBERTa(as the encoder) and Siku-GPT(as the decoder), designed specifically for translating ancient Chinese, to build an efficient encoder-decoder architecture. To comprehensively evaluate the performance of the Siku-Trans model, the study introduced three models as control groups: OpenNMT, SikuGPT, and SikuBERT_UNILM. Through comparative analysis of the performance of each model in ancient Chinese translation tasks, we found that Siku-Trans exhibits significant advantages in terms of translation accuracy and fluency. These results not only highlight the effectiveness of combining Siku-RoBERTa with Siku-GPT as a training strategy but also provide important references and insights for in-depth research and practical applications in the field of ancient Chinese translation. Related Articles | Metrics | Comments（0）

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The Developing Directions of Information Resources Management Discipline in the Era of Artificial General Intelligence Yan Hui Journal of Information Resources Management    2024, 14 (2): 21-28,53.   DOI: 10.13365/j.jirm.2024.02.021 Abstract （950）      PDF（pc） （765KB）（2989）       Knowledge map    Save This paper reviews the seventy-year developing history of Artificial Intelligence and Artificial General Intelligence(AGI), reflects on the fifty-year history of information resources management, analyzes the profound and multifaceted impacts of AGI on the knowledge system, education system, and career system of information resources management, and proposes three suggestions for the developing direction of information resources management discipline in the AGI era. 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 （648）      PDF（pc） （2456KB）（2988）       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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Institute of Information Science, Shanghai Academy of Social Sciences, Shanghai, 200235 Zhang Zhun Journal of Information Resources Management    2024, 14 (2): 54-67.   DOI: 10.13365/j.jirm.2024.02.054 Abstract （858）      PDF（pc） （1104KB）（2983）       Knowledge map    Save The guideline, which includes twenty key measures to build basic systems for data released in December 2022 (referred to as the "Twenty Data Measures"), proposes a structural separation system for data property rights, with "incentivizing data circulation" as its core focus. The rational allocation of the right to hold data resources affects the initial distribution of data benefits, serving as the foundation for achieving the strategic goal of "common use and shared benefits" of data. Under the traditional exclusive property rights mindset, the allocation patterns of the right to hold data resources may exacerbate conflicts of interest among data co-producers. This article suggests allocating the right to hold data resources among data co-producers in a "1+N" model, which means "prior hold data right for a specific data producer + access rights for N other data producers". With the support of tools such as technical governance and transparency governance, it explores a new, fair, and efficient data property rights system that aligns with the developing laws of the data economy. Related Articles | Metrics | Comments（0）

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The Construction of Cultural Heritage Smart Data for the Inheritance and Activation Wang Xiaoguang　Hou Xilong Journal of Information Resources Management    2023, 13 (5): 5-14，43.   DOI: 10.13365/j.jirm.2023.05.005 Abstract （933）      PDF（pc） （2842KB）（2919）       Knowledge map    Save Smart data is becoming a new development trend of information resource construction in the age of data and intelligence. It is an advanced form of data resources organization and more suitable for the new demands and requirements on the data and service in the new environment. Firstly, this article systematically reviews the historical evolution and development trend of smart data, and analyzes the scientific meaning and critical features of smart data. Secondly, facing the problems of cultural heritage inheritance and activation, this article explains the internal logic of smart data empowering cultural heritage activation. Finally, the article puts forward the construction measures and path of cultural heritage smart data, including the construction mechanism, smart data standards and specifications, cultural gene deconstruction, quality control system. The research of smart data not only improves the quality and efficiency of big data resources, but also contributes to the theoretical reform of information resources management and knowledge management in the empowerment of data and intelligence. The construction of cultural heritage smart data resources will effectively promote the process of cultural heritage protection, inheritance and activation. Related Articles | Metrics | Comments（0）

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A Triple Helix Coupling Model of China’s Open Government Data Resource System Chen Ling　Jiang Guoyin Journal of Information Resources Management    2024, 14 (2): 121-135.   DOI: 10.13365/j.jirm.2024.02.121 Abstract （629）      PDF（pc） （4882KB）（2863）       Knowledge map    Save This study delves into the intricate dynamics of open government data, examining its coupling and coordinated evolution from a systemic lens, which is pivotal for advancing the openness of government data, enhancing data value empowerment, and promoting the development of both the data industry and digital economy. This study establishes an isomorphic mapping between the theoretical model and the empirical system and constructs a triple helix model and functional equation for the open government data system, with a focus on data openness, data utilization and data value. Employing a hierarchical analytical framework that dissects the relationships among ‘element-subsystem-system’, the study provides an empirical evaluation of the data coupling intensity among the data resources available on China’s government open platforms. From the perspective of resource-based theory, this study proposes the coordination and optimization path of government data resources, which provides a new theoretical perspective and methodological support for future research of open government data. 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 （1023）      PDF（pc） （4448KB）（2819）       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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The Path and Empirical Study of Intelligence Support for Emergencies by Fusing Eventic Graph and Network Opinion Analysis——Taking Hazardous Chemical Accidents as an Example Zhang Shiying　Li Yang Journal of Information Resources Management    2023, 13 (4): 60-71.   DOI: 10.13365/j.jirm.2023.04.060 Abstract （1061）      PDF（pc） （4153KB）（2818）       Knowledge map    Save Existing emergency intelligence support has some deficiencies, such as static knowledge, fuzzy reasoning, and spatial homogeneity. The paper proposes a path of emergency intelligence support that integrates eventic graph and network opinion analysis, aiming to improve the situational awareness and predictive response capability of emergencies in complex situations, and support emergency intelligence paradigm innovation in the era of digital intelligence empowerment. The paper constructs a framework for emergency intelligence support from the integrated perspective of reasoning and knowledge fusion, business and network fusion, and carries out empirical research using hazardous chemical accidents as an illustration. The work includes building a database of relevant emergencies, portraying the development logic of emergencies using an eventic graph, and describing the impact of emergencies in cyberspace using online opinion analysis techniques. This provides intelligence support for emergency management and decision making for new emergencies. The intelligence support path proposed in this paper can take into account the characteristics of multi-source spatial data as well as the integration of event logic and knowledge, allowing for a more systematic "past-future" intelligence prediction of emergencies. The empirical study and validation of hazardous chemical accidents also show good knowledge presentation and intelligence reasoning. Related Articles | Metrics | Comments（0）

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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 （557）      PDF（pc） （3045KB）（2776）       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）

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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 （585）      PDF（pc） （2994KB）（2718）       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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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 （787）      PDF（pc） （3928KB）（2690）       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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A Study on Automatic Categorization of the Siku Quanshu Based on a Large Language Model Zuo Liang　Zhao Zhixiao　Wang Dongbo Journal of Information Resources Management    2024, 14 (5): 23-35.   DOI: 10.13365/j.jirm.2024.05.023 Abstract （575）      PDF（pc） （2258KB）（2604）       Knowledge map    Save The craze of ancient book research and the contemporary requirement of ancient book revitalisation have raised higher requirements for automatic classification of ancient books. This study explores the classification effect of Xunzi large language series models on the automatic classification of ancient books by combining the large language model along the current preface with the 25 categories of corpus from the history and scripture sections of the Siku Quanshu as the input corpus.Through the comparison experiments with its base model, the results show that Xunzi large language models for ancient books have obvious advantages in the automatic classification task of ancient books, among which the Xunzi-Baichuan2-7B large language model has the most significant advantage in the automatic classification task of ancient books, and the overall classification F1 value reaches 96.90%. In addition, the experiments of adjusting the training data size show that the Xunzi-Baichuan2-7B large language model is able to achieve comparable classification results with the base model with only a small amount of data. Therefore, the automatic classification model for ancient books based on Xunzi large language models for ancient books proposed in this study can achieve efficient fine-grained classification of ancient books and opens up a new way for the classification of ancient books in resource-constrained contexts. Related Articles | Metrics | Comments（0）