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Empirical prediction of patent pledge financing of pharmaceutical enterprises—A case study in Jiangsu China

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  • Xiaojuan Zhao
  • Yunhua Liu

Abstract

Financing by patent pledge is an important way for small- and medium-sized pharmaceutical enterprises to address financing problems. In this study, eight indexes are analyzed considering both the pledge patent value and pledger credit value. And a prediction model for the patent pledge financing amount for pharmaceutical enterprises is constructed for the first time using the analytic hierarchy process and the fuzzy comprehensive evaluation method. Three levels of financing amount are concluded through the prediction model and prediction results corresponding with the financing amount are displayed. This model was designed to help small- and medium-sized pharmaceutical enterprises get access to financing through patent pledge to relieve their financial stress. At the same time, it provides guides for pledgees and policymakers to improve the efficiency and quality of patent pledge. This work is reliable and valid in that it constructs this prediction model based on systematical data from official data sources.

Suggested Citation

  • Xiaojuan Zhao & Yunhua Liu, 2020. "Empirical prediction of patent pledge financing of pharmaceutical enterprises—A case study in Jiangsu China," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-13, June.
  • Handle: RePEc:plo:pone00:0233601
    DOI: 10.1371/journal.pone.0233601
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    References listed on IDEAS

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    1. Sudheer Chava & Vikram Nanda & Steven Chong Xiao, 2017. "Lending to Innovative Firms," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 6(2), pages 234-289.
    2. Mann, William, 2018. "Creditor rights and innovation: Evidence from patent collateral," Journal of Financial Economics, Elsevier, vol. 130(1), pages 25-47.
    3. Jonas Fabian Ehrnsperger & Frank Tietze, 2019. "Patent pledges, open IP, or patent pools? Developing taxonomies in the thicket of terminologies," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-18, August.
    4. Ho, William & Ma, Xin, 2018. "The state-of-the-art integrations and applications of the analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 267(2), pages 399-414.
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