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A Hybrid Method of Analyzing Patents for Sustainable Technology Management in Humanoid Robot Industry

Author

Listed:
  • Jongchan Kim

    (Department of Industrial Management Engineering, Korea University, Seoul 02841, Korea)

  • Joonhyuck Lee

    (Department of Industrial Management Engineering, Korea University, Seoul 02841, Korea)

  • Gabjo Kim

    (Korea Intellectual Property Strategy Agency, Seoul 02841, Korea)

  • Sangsung Park

    (Graduate School of Management of Technology, Korea University, Seoul 02841, Korea)

  • Dongsik Jang

    (Department of Industrial Management Engineering, Korea University, Seoul 02841, Korea)

Abstract

A humanoid, which refers to a robot that resembles a human body, imitates a human’s intelligence, behavior, sense, and interaction in order to provide various types of services to human beings. Humanoids have been studied and developed constantly in order to improve their performance. Humanoids were previously developed for simple repetitive or hard work that required significant human power. However, intelligent service robots have been developed actively these days to provide necessary information and enjoyment; these include robots manufactured for home, entertainment, and personal use. It has become generally known that artificial intelligence humanoid technology will significantly benefit civilization. On the other hand, Successful Research and Development (R & D) on humanoids is possible only if they are developed in a proper direction in accordance with changes in markets and society. Therefore, it is necessary to analyze changes in technology markets and society for developing sustainable Management of Technology (MOT) strategies. In this study, patent data related to humanoids are analyzed by various data mining techniques, including topic modeling, cross-impact analysis, association rule mining, and social network analysis, to suggest sustainable strategies and methodologies for MOT.

Suggested Citation

  • Jongchan Kim & Joonhyuck Lee & Gabjo Kim & Sangsung Park & Dongsik Jang, 2016. "A Hybrid Method of Analyzing Patents for Sustainable Technology Management in Humanoid Robot Industry," Sustainability, MDPI, vol. 8(5), pages 1-14, May.
  • Handle: RePEc:gam:jsusta:v:8:y:2016:i:5:p:474-:d:69917
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Savin, Ivan & Ott, Ingrid & Konop, Chris, 2022. "Tracing the evolution of service robotics: Insights from a topic modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    2. Jongchan Kim & Jaehyun Choi & Sangsung Park & Dongsik Jang, 2018. "Patent Keyword Extraction for Sustainable Technology Management," Sustainability, MDPI, vol. 10(4), pages 1-18, April.
    3. Juan Hao & Xinqin Gao & Yong Liu & Zhoupeng Han, 2023. "Acquisition Method of User Requirements for Complex Products Based on Data Mining," Sustainability, MDPI, vol. 15(9), pages 1-19, May.
    4. Hong-Hua Qiu & Jing Yang, 2018. "An Assessment of Technological Innovation Capabilities of Carbon Capture and Storage Technology Based on Patent Analysis: A Comparative Study between China and the United States," Sustainability, MDPI, vol. 10(3), pages 1-20, March.
    5. Meihui Li & Na Luo & Yi Lu, 2017. "Biomass Energy Technological Paradigm (BETP): Trends in This Sector," Sustainability, MDPI, vol. 9(4), pages 1-28, April.
    6. Jiho Kang & Junseok Lee & Dongsik Jang & Sangsung Park, 2019. "A Methodology of Partner Selection for Sustainable Industry-University Cooperation Based on LDA Topic Model," Sustainability, MDPI, vol. 11(12), pages 1-16, June.
    7. Juhyun Lee & Jiho Kang & Sangsung Park & Dongsik Jang & Junseok Lee, 2020. "A Multi-Class Classification Model for Technology Evaluation," Sustainability, MDPI, vol. 12(15), pages 1-16, July.
    8. Sangsung Park & Sunghae Jun, 2017. "Statistical Technology Analysis for Competitive Sustainability of Three Dimensional Printing," Sustainability, MDPI, vol. 9(7), pages 1-16, June.

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