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Inventor profile mining approach for prospective human resource scouting

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  • Chung, Jaemin
  • Ko, Namuk
  • Kim, Hyeonsu
  • Yoon, Janghyeok

Abstract

Scouting young and talented human resources with firm-specific domain knowledge has a great impact on performance and sustainable growth among technology-based firms. Previous studies have proposed key researcher identification and recommendation approaches, but few studies have focused on identifying prospective human resources—young and talented people suitable for a firm’s technology strategy. Thus, this study proposes an inventor profile mining approach for identifying such human resources. The proposed approach is as follows: 1) collecting patent data related to a target firm and preprocessing candidate inventors’ patents; 2) identifying the inventors’ technology fields and measuring their invention performance and career; 3) generating performance-career portfolio maps for invention fields to identify prospective inventors aligned with the target firm’s technology development directions. We show that this approach can identify prospective inventors through a case study and statistical validation. This approach is expected to be used as a human resources management tool by technology-based firms to help them identify and scout young and talented human resources the most suitable for technology strategies.

Suggested Citation

  • Chung, Jaemin & Ko, Namuk & Kim, Hyeonsu & Yoon, Janghyeok, 2021. "Inventor profile mining approach for prospective human resource scouting," Journal of Informetrics, Elsevier, vol. 15(1).
    • Handle: RePEc:eee:infome:v:15:y:2021:i:1:s175115772030328x
    DOI: 10.1016/j.joi.2020.101103
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    Cited by:

    1. Chung, Jaemin & Ko, Namuk & Yoon, Janghyeok, 2021. "Inventor group identification approach for selecting university-industry collaboration partners," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    2. Choi, Jaewoong & Lee, Changyong & Yoon, Janghyeok, 2023. "Exploring a technology ecology for technology opportunity discovery: A link prediction approach using heterogeneous knowledge graphs," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).

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