01 October 2026, Volume 22 Issue 5

    

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  A Preliminary Discussion on One-Person Research

  CHEN Chao

  Competitive Intelligence. 2026, 22(5): 1-1.

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  An Intelligence Support Framework for Decision-Making on Organizational Mechanisms of China’s Major Science and Technology Missions: The Case of NASA’s Commercial Space Programs

  SHI Yingjie

  Competitive Intelligence. 2026, 22(5): 2-12.

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  Editor’s Note: Competition in major science and technology missions is increasingly becoming a comprehensive contest of technological, industrial, and organizational capabilities. In 2026, the White House released “Science: A New Golden Age”, identifying reforms to the organization of scientific research and funding mechanisms as important issues in federal science and technology policy; the Third Plenary Session of the 20th Central Committee of the Communist Party of China likewise called for efforts to “optimize the organizational mechanisms for major scientific and technology innovation.” However, existing science and technology intelligence work tends to focus more on technology pathways, innovation entities, and industry dynamics, while paying insufficient attention to organizational issues such as who should undertake a mission, how responsibilities should be divided, what organizational instruments should be employed, and when mechanisms should be adjusted. Against this backdrop, this journal invited the author to examine NASA’s commercial space programs as a case study, analyze the underlying logic of the selection and transition of their organizational mechanisms, and, on this basis, propose an intelligence support framework for decision-making on the organizational mechanisms of China’s major science and technology missions. This article aims to broaden the boundaies of intelligence analysis for major science and technology missions, extend the focus beyond technology and industry themselves to organizational dimensions such as mission conditions, the allocation of rights and responsibilities, competition structures, and mechanism transitions, and to carry this analysis throughout the entire process of mission appraisal, organization implementation, and dynamic adjustment, thereby providing more targeted intelligence support for the design, selection, course correction, and with drawal of organizational mechanisms for major science and technology missions.
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  The Impact of Competitive Intelligence Process on Product Innovation Performance in High-Tech Enterprises

  ZHI Fengwen, XU Yangjiao, PAN Yunhan

  Competitive Intelligence. 2026, 22(5): 13-25.

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  Analyzing the impact of competitive intelligence processes on product innovation performance from the perspective of strategy formulation, this study introduces two moderating variables—intelligence personnel’s experiential knowledge and entrepreneurial spirit—to construct a theoretical model framework of “competitive intelligence processes→strategy formulation→product innovation performance.” Primary data were collected through questionnaire surveys, and regression analysis was conducted based on sample data from high-tech enterprises. The findings indicate that both competitive intelligence processes and strategy formulation positively affect product innovation performance. Strategy formulation plays a partial mediating role in the relationship between competitive intelligence processes and product innovation performance. Furthermore, this mediating effect is moderated by intelligence personnel’s experiential knowledge and entrepreneurial spirit, with the moderating effect of experiential knowledge being stronger than that of entrepreneurial spirit. Product innovation performance reaches its highest level when both moderating variables are at high levels. The results contribute to revealing the relationship between competitive intelligence processes and product innovation performance from the perspective of strategy formulation and offer important insights for high-tech enterprises seeking to enhance product innovation performance.
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  An Investigation into the Citation Analysis of Non-Source Literature in High-Level Papers Indexed in Web of Science

  CHEN Yuecong, YANG Siqi, ZHAO Dongmei

  Competitive Intelligence. 2026, 22(5): 26-37.

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  This study uses inclusion in the five Web of Science (WoS) sub-database—SCI, SSCI, CPCI-S, CPCI-SSH, and A&HCI—as the criterion to distinguish between source and non-source literature, taking high-quality papers from the Web of Science (WoS) platform as research subjects. It analyzes the citation status of non-source literature within the WoS platform and explores their role in their respective fields. The results show significant variation in the proportion of non-source literature across disciplines, ranging from 13.23% in life sciences to 44.25% in arts and humanities. In the interdisciplinary field of library and information science, this proportion reaches 39.35%, approaching that of arts and humanities. Among the samples, journals constitute the largest category, and both journals and books exhibit very high and closely similar values in the Category Normalized Citation Impact index (CNCI), significantly exceeding those of source literature.
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  Study on Asian Experiences in Building Science and Technology Innovation Centers

  JIANG Fen, LI Wanqiu, WEI Jianliang, DENG Danqing

  Competitive Intelligence. 2026, 22(5): 38-48.

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  Drawing upon the core practices of the three science and technology innovation centers in Singapore, Tokyo, and Tel Aviv, this study investigates the deve- lopmental experiences of representative technology and innovation hubs in Asia. By establishing an analytical framework centered on “institutional mechanisms—resource allocation—innovation ecosystem,” the research comparatively analyzes three distinct paradigms—government-led, internal-external collaborative, and venture enclave—to elucidate their unique characteristics. The findings indicate that while these centers—Singapore, Tokyo and Tel Aviv—share commonalities such as prominent government governance, high-density aggregation of innovation elements, and robust global connectivity, their further improvement will be driven by systemic synergy, global resource integration, the “research + capital” dual-drive mechanism, and the cultivation of top-tier international talents.
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  Research on Think Tank Evidence-Based Decision-Making Model Based on Multimodal Knowledge Graph and Retrieval-Augmented Generation Technology

  YE Nanjun

  Competitive Intelligence. 2026, 22(5): 49-58.

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  Faced with an increasingly complex data environment, traditional think tanks encounter bottlenecks in evidence-based decision-making, including data polymorphism, information overload, and delayed knowledge updates, which severely constrain the scientific rigor and timeliness of decision support. To address these challenges, this study proposes a novel evidence-based decision-making framework for think tanks by integrating multimodal knowledge graph (MMKG) and retrieval-augmented generation (RAG). The theoretical contribution of this study lies in providing a systematic technical integration pathway to address core challenges faced by think tanks in the digital era. It offers a theoretically feasible and clearly defined roadmap for constructing next-generation high-end think tanks with superior decision-support capabilities. The framework establishes a four-tier integrated theoretical architecture encompassing data, knowledge, models, and applications, where MMKG serves as a structured multidimensional evidence foundation, and RAG functions as an intelligent decision-making engine. The framework employs mechanisms such as semantic + structural hybrid retrieval and a generation-verification dual reasoning chain to achieve deep knowledge mining and trustworthy content generation. Research demonstrates that this framework effectively integrates multi-source heterogeneous evidence, transforming fragmented data into interconnected knowledge networks. The RAG engine generates logically rigorous, traceable decision analyses based on dynamically updated knowledge graphs, significantly enhancing the comprehensiveness, timeliness, and interpretability of decision support.
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  Global Low-Altitude Economy: Current Development Status and Future Trends

  WANG Yifeng

  Competitive Intelligence. 2026, 22(5): 59-68.

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  The global low-altitude economy is developing rapidly, with strong expectations for industrial scale and accelerating progress in the certification of new types of aircraft and the construction of vertiports. However, manufacturers in the low-altitude aviation sector have yet to establish proven and sustainable profit models, and most leading companies remain highly dependent on external financing. From a regional perspective, the United States is leveraging its mature general aviation system and the eVTOL Integration Pilot Program (eIPP) to accelerate the development of emerging low-altitude aviation services. China is shifting from a case-by-case certification approach toward standardized certification procedures while expanding into international markets such as the Middle East and Southeast Asia. Europe places greater emphasis on establishing regulatory frameworks and certification foundations in advance. The Middle East, represented by the United Arab Emirates and Saudi Arabia, is actively positioning itself as an early testing ground for commercial operations, while other regions focus more on international regulatory coordination and localized commercial demonstrations. In terms of technology, new low-altitude aircraft are evolving from pure multirotor configurations toward integrated designs combining vertical takeoff and landing with fixed-wing cruise. Propulsion systems are transitioning from conventional fuels toward battery-electric and hybrid new-energy solutions, while operational control is evolving from manual piloting toward AI-enabled autonomous operation and remote supervision. Looking ahead, the development of the global low-altitude industry will be increasingly influenced by geopolitical factors; testing and validation will place greater emphasis on system-level verification; certification standards will move toward greater coordination and mutual recognition; and industry consolidation is expected to accelerate further.