01 April 2025, Volume 21 Issue 2

    

• Select all
  |

• Select
  Evaluation of the U.S. “Small Yard, High Fence” Strategy: China-U.S. Competition and Prospects in Artificial Intelligence Field

  Competitive Intelligence. 2025, 21(2): 2-12.

  Abstract ( ) Download PDF ( ) Knowledge map Save

  With the rapid iteration of artificial intelligence (AI) technology and the continuous expansion of its application scenarios, the competition between China and the United States in technological research and development, industrial deployment, and policy formulation has become increasingly intense. This rivalry not only shapes the future direction of global AI development but also profoundly influences the evolution of the world’s economy, politics, and even social structures. The trajectory of China-U.S. AI competition will be determined by the interplay and balance of multiple factors in the future. Its impact has long transcended technology itself, becoming a crucial microcosm of great power rivalry in the 21st century. Understanding the logic behind the the U.S. administration’s “small yard, high fence” strategy over the past four years and comprehensively assessing its effectiveness can help Chinese competitive intelligence professionals establish strategic coordinates in several key areas-dynamically tracking U.S. technology restrictions, analyzing China’s technological breakthroughs, forecasting risks and opportunities, and formulating competitive strategies that integrate both offensive and defensive approaches.
  
• Select
  Technical Information Analysis Process Design and Case Study of “AI Assistance-Librarian Analysis-User Decision”

  Competitive Intelligence. 2025, 21(2): 13-21.

  Abstract ( ) Download PDF ( ) Knowledge map Save

  Technical information analysis is the key to discover technological innovation pounts. The development of artificial intelligence (AI) technology and the demand for more accurate information are promoting the reform and innovation of information service in university libraries. How to make reasonable use of AI tools to improve the technical information analysis paradigm and give play to the wisdom of librarians is an important issue for promoting innovation and development. The study analyzes the current situation of technical information analysis and the application of AI tools, explores the selection mechanism of technical information analysis tools, and constructs a cooperation technical intelligence analysis process involving the collaboration of AI technology, librarian teams, and expert users by considering the cooperation and parallel tasks of people, data, and AI tools. Through case practice, this study analyzed the application of this process, and realized the technical information research products with granularity from coarse to fine, which met the needs of the information service objects. Therefore, the results showed that the new technical information analysis process had three advantages: firstly, AI tools can help bring out the wisdom of librarians. Secondly, the active interaction of the three parties can ensure the efficient and accurate information. Thirdly, the economical and practical performance promotes the replication of the information analysis process.
  
• Select
  Enterprise Product-Level Competitor Identification Research Based on Online Reviews

  Competitive Intelligence. 2025, 21(2): 22-28.

  Abstract ( ) Download PDF ( ) Knowledge map Save

  In view of the limitations of traditional competitor identification methods in the context of the Internet, this paper proposes a product-level competitor identification method based on user reviews as the data source, aiming to provide a strong basis for enterprises to optimize product design and formulate competitive strategies. Firstly, the candidate competitive products are defined based on the user’s selection preference, and the online reviews of the company’s products and the candidate competitive products are collected by using Python crawling technology. Secondly, the Python word segmentation technology is used to combine frequency statistics and manual screening to construct the product feature set and the sentiment word set. Thirdly, relying on the sentiment feature weight algorithm, the advantages and disadvantages of the company’s products are analyzed, the feature strengths and weaknesses are formed, the product vector space model is constructed and the similarity is calculated. Finally, the main and secondary competitors are identified to provide data support for market strategy optimization. In this study, “Colgate” is selected as an empirical analysis case. The study finds that the main competitors of “Colgate” are “Crest” “Liangmianzhen” and “Lengsuanling”, with similar advantages comparable and disadvantages; “Dental Doctor” and “DARLIE” are listed as secondary competitors because they have similar advantages and do not reach a considerable level in disadvantage characteristics.
  
• Select
  Text Analysis of China’s Provincial Data Element Policy under the “ Tool-Goal ” Framework

  Competitive Intelligence. 2025, 21(2): 29-38.

  Abstract ( ) Download PDF ( ) Knowledge map Save

  Under the background of promoting digital transformation and fostering new quality productive forces, data elements have become the hot topic and key direction for China’s economic and social development. This paper takes 31 provincial data element policy texts in China as the research object, uses NVivo12 plus to code, and constructs the analysis framework of “policy tool-policy goal” to analyze content, structure, feature and trend of the policy texts. It is found that there are some problems in the policy texts, such as the imbalance in policy tools and their internal structure, the uneven distribution of policy goals, and the weak matching between policy tools and policy goals. It is expected to provide some theoretical and practical reference for the subsequent adjustment and optimization of data element policy and the construction of a scientific and reasonable policy system.
  
• Select
  Research on Construction of Civil Aviation Emergency Management Mechanism Based on Blockchain Technology

  Competitive Intelligence. 2025, 21(2): 39-47.

  Abstract ( ) Download PDF ( ) Knowledge map Save

  With the modern society transitioning into the VUCA era, civil aviation emergencies have become increasingly frequent. To enhance the current civil aviation emergency management mechanism, it is imperative to evaluate the existing framework of China’s civil aviation emergency management and propose a new mechanism based on blockchain technology tailored to the specific needs of civil aviation emergency operations. This study examines the proposed mechanism from three dimensions: platform architecture, organizational structure, and technical infrastructure, systematically detailing the components within this framework. The operational process is elaborated through the system operation mechanism, encompassing the warning and support stage, the emergency response stage, and the post-incident recovery stage, referred to as “1 system+3 stages”. Additionally, the practical application of this mechanism is explored. Blockchain technology will provide comprehensive, full-cycle emergency support for civil aviation emergency management during crises, addressing the shortcomings of the current system and advancing its modernization.
  
• Select
  Analyzing and Forecasting the Associative Characteristics of Empowering Networks Composed by Ontology and Artificial Intelligence: Taking Rare Disease Research as an Example

  Competitive Intelligence. 2025, 21(2): 48-58.

  Abstract ( ) Download PDF ( ) Knowledge map Save

  Taking rare disease research as an example, this study conducts recognition and relation extraction of ontology, artificial intelligence (AI) , and rare disease named entity from rare disease research literature in the Web of Science Core Collection and MEDLINE databases. It constructs coupling and co-occurrence networks among entities, analyzes the characteristics of ontology, AI, and rare disease association networks, and explores the application patterns of ontologies and AI in rare disease research. Additionally, it predicts potential future applications of these technologies in the field. The results show that 30% to 40% of rare diseases have applied ontologies or AI technologies in research; the network structure of rare diseases formed based on the coupling relationship between ontologies and AI is clear and can be divided into distinct rare disease clusters. The collaborative application of ontologies and AI technologies in rare disease research presents 5 basic patterns, and ontologies such as gene ontology, epilepsy ontology, as well as AI technologies such as machine learning and pattern recognition, have great potential for application in the field of rare disease research.
  
  
• Select
  Long-Term Preservation Practice of Russian Digital Resources: An Exploratory Study

  Competitive Intelligence. 2025, 21(2): 59-66.

  Abstract ( ) Download PDF ( ) Knowledge map Save

  Since the 21st century, long-term preservation of Russian digital resources has shaped a three-step development path of theoretical research, practical exploration and technological innoration. From three perspectives of “National Committees UNESCO IFAP” “The National Electronic Library (NEL) ” “Russian Science Citation Index” as the research objects, this article focuses on three dimensions: strategy, practice and innovation. All this comes to a panorama of Russian efforts in the information preservation. However, in the context of the Russia-Ukraine conflict and Western technological sanctions, the long-term preservation of digital resources in Russia inevitably shifts towards a development path that strengthens technological sovereignty.