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A patent portfolio-based approach for assessing potential R&D partners: An application of the Shapley value

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  • Song, Bomi
  • Seol, Hyeonju
  • Park, Yongtae

Abstract

We propose a patent portfolio-based approach for assessing potential R&D partners that can consider the inter-partner resource fit in the assessment process. The concept of an integrated patent portfolio is suggested and its value is designed to reflect the resource fit between potential R&D partners. The Shapley value is applied to assess the contribution of each potential partner to the value of the integrated patent portfolio. A case study of a lighting control system is presented to show the feasibility and advantages of our method. Overcoming the weakness of individual capability-focused evaluation of potential R&D partners, our method can better inform decision makers and experts in the partner selection process by enabling more comprehensive assessment of potential R&D partners.

Suggested Citation

  • Song, Bomi & Seol, Hyeonju & Park, Yongtae, 2016. "A patent portfolio-based approach for assessing potential R&D partners: An application of the Shapley value," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 156-165.
  • Handle: RePEc:eee:tefoso:v:103:y:2016:i:c:p:156-165
    DOI: 10.1016/j.techfore.2015.10.010
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    Cited by:

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    3. Kaifeng Zhao & Seyed Hanif Mahboobi & Saeed R. Bagheri, 2018. "Shapley Value Methods for Attribution Modeling in Online Advertising," Papers 1804.05327, arXiv.org.
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    5. Park, Youngjin & Yoon, Janghyeok, 2017. "Application technology opportunity discovery from technology portfolios: Use of patent classification and collaborative filtering," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 170-183.
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    7. Yanhua Du & Jun Fang & Yongjian Ke & Simon P Philbin & Jingxiao Zhang, 2019. "Developing a Revenue Sharing Method for an Operational Transfer-Operate-Transfer Project," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    8. Fred Phillips, 2017. "A perspective on ‘Big Data’," Science and Public Policy, Oxford University Press, vol. 44(5), pages 730-737.
    9. Song, Kisik & Kim, Kyuwoong & Lee, Sungjoo, 2018. "Identifying promising technologies using patents: A retrospective feature analysis and a prospective needs analysis on outlier patents," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 118-132.
    10. Wei Chen & Hui Qu & Kuo Chi, 2021. "Partner Selection in China Interorganizational Patent Cooperation Network Based on Link Prediction Approaches," Sustainability, MDPI, vol. 13(2), pages 1-16, January.

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