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A Cross-Citation-Based Model for Technological Advancement Assessment: Methodology and Application

Author

Listed:
  • Shengxuan Tang

    (Guangdong Provincial Key Laboratory of Intelligent Transportation System, School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518000, China)

  • Ming Cai

    (Guangdong Provincial Key Laboratory of Intelligent Transportation System, School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518000, China)

  • Yao Xiao

    (Guangdong Provincial Key Laboratory of Intelligent Transportation System, School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518000, China)

Abstract

Assessing technological advancements is crucial for the formulation of science and technology policies and making well-informed investments in the ever-evolving technology market. However, current assessment methods are predominantly geared towards mature technologies, limiting our capacity for a systematic and quantitative evaluation of emerging technologies. Overcoming this challenge is crucial for accurate technology evaluation across various fields and generations. To address this challenge, we present a novel approach that leverages bibliometrics, specifically paper citation networks, to gauge shifts in the flow of knowledge throughout the technological evolution. This method is capable of discerning a wide array of trends in technology development and serves as a highly effective tool for evaluating technological progress. In this paper, we showcase the accuracy and applicability of this approach by applying it to the realm of mobile communication technology. Furthermore, we provide a comparative analysis of its quantitative results with other conventional assessment methods. The practical significance of our model lies in providing a nuanced understanding of emerging technologies within a specific domain, enabling informed decisions, and fostering strategic planning in technology-oriented fields. In terms of originality and value, this model serves as a comprehensive tool for assessing technological progress, quantifying emerging technologies, facilitating the evaluation of diverse technological trajectories, and efficiently informing technology policy-making processes.

Suggested Citation

  • Shengxuan Tang & Ming Cai & Yao Xiao, 2024. "A Cross-Citation-Based Model for Technological Advancement Assessment: Methodology and Application," Sustainability, MDPI, vol. 16(1), pages 1-20, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:1:p:435-:d:1312810
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    References listed on IDEAS

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    Cited by:

    1. Liming Zhang & Ming Cai & Yingxin Zhang & Shuai Wang & Yao Xiao, 2024. "Two-layer network evolutionary game model applied to complex systems," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(11), pages 1-17, November.
    2. Yassine Sekaki & Hamza Ziane & Abdelhafid Khazzar, 2025. "Artificial Intelligence in Management Studies (2021-2025): A Bibliometric Mapping of Themes, Trends, and Global Contributions," Post-Print hal-05236423, HAL.

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