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Identifying Promising Research Frontiers of Pattern Recognition through Bibliometric Analysis

Author

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  • Inchae Park

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University, 26, Pil-dong 3-ga, Chung-gu, Seoul 100-715, Korea)

  • Byungun Yoon

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University, 26, Pil-dong 3-ga, Chung-gu, Seoul 100-715, Korea)

Abstract

This paper aims at proposing a quantitative methodology to identify promising research frontiers (RFs) based on bibliographic information of scientific papers and patents. To achieve this, core technological documents are identified by suggesting several indices which measure paper impact, research impact, patent novelty, impact, marketability, and the right range to evaluate technological documents and which measure the research capability of research organizations (ROs) such as a RO’s activity, productivity, market competitiveness, and publication impact. The RFs can be identified by clustering core technological documents, and promising indices of each RF which are from the perspectives of growth, impact, marketability, and science-based effect, are calculated to promising RFs. As an illustration, this paper selects the case of pattern recognition technology among various technologies in the information and communication technology sector. To validate the proposed method, emerging technologies on the hype cycle are utilized, allowing analysts to compare the results. Comparing the results derived from scientific papers and patents, the results from scientific papers are proper to suggest themes for research (R) in relatively long-term perspective, whereas the results from patents are appropriate for providing themes for development (D) in terms of relatively short-term view. This approach can assist research organizations and companies in devising a technology strategy for a future direction of research and development.

Suggested Citation

  • Inchae Park & Byungun Yoon, 2018. "Identifying Promising Research Frontiers of Pattern Recognition through Bibliometric Analysis," Sustainability, MDPI, vol. 10(11), pages 1-32, November.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:4055-:d:180746
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    References listed on IDEAS

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    Cited by:

    1. Jinho Choi & Yong Sik Chang, 2020. "Development of a New Methodology to Identity Promising Technology Areas Using M&A Information," Sustainability, MDPI, vol. 12(14), pages 1-25, July.
    2. Lee, Keeeun & Kim, Sunhye & Yoon, Byungun, 2022. "A systematic idea generation approach for developing a new technology: Application of a socio-technical transition system," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    3. Jason Jihoon Ree & Cheolhyun Jeong & Hyunseok Park & Kwangsoo Kim, 2019. "Context–Problem Network and Quantitative Method of Patent Analysis: A Case Study of Wireless Energy Transmission Technology," Sustainability, MDPI, vol. 11(5), pages 1-18, March.
    4. Jinho Choi & Nina Shin & Yong Sik Chang, 2021. "Strategic Investment Decisions for Emerging Technology Fields in the Health Care Sector Based on M&A Analysis," Sustainability, MDPI, vol. 13(7), pages 1-20, March.

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