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Improving mariculture insurance premium rate calculation using an information diffusion model.

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اقرأ على الانترنت اقرأ أكثر حفظ في قائمتي
  • المؤلفون: Zhang Q;Zhang Q
  • المصدر:
    PloS one [PLoS One] 2021 Dec 23; Vol. 16 (12), pp. e0261323. Date of Electronic Publication: 2021 Dec 23 (Print Publication: 2021).
  • نوع النشر :
    Journal Article
  • اللغة:
    English
  • معلومة اضافية
    • المصدر:
      Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
    • بيانات النشر:
      Original Publication: San Francisco, CA : Public Library of Science
    • الموضوع:
      Aquaculture/*economics ; Insurance/*economics ; Risk Assessment/*methods; Aquaculture/methods ; Humans ; Insurance/trends ; Models, Theoretical
    • نبذة مختصرة :
      Mariculture is a well-known high-risk industry. However, mariculture insurance, which is an important risk management tool, is facing serious market failure. An important reason for this market failure lies in the unsound premium rate and pricing method. Due to a lack of long-term yield data, empirical rates are often adopted, but this adoption can lead to a high loss ratio. This paper provides an improved method for premium computation of mariculture insurance using an information diffusion model (IDM). An example of oyster insurance in China shows that, compared with the traditional pricing approach, the IDM can greatly improve the accuracy and stability of premium rate calculations, especially in cases of small samples.
      Competing Interests: The authors have declared that no competing interests exist.
    • References:
      Sci Total Environ. 2014 Jun 1;482-483:318-24. (PMID: 24657580)
      J Alzheimers Dis. 2016 Apr 5;52(4):1335-42. (PMID: 27060960)
      PLoS One. 2020 Mar 5;15(3):e0224347. (PMID: 32134926)
    • الموضوع:
      Date Created: 20211223 Date Completed: 20220110 Latest Revision: 20220110
    • الموضوع:
      20231215
    • الرقم المعرف:
      PMC8700043
    • الرقم المعرف:
      10.1371/journal.pone.0261323
    • الرقم المعرف:
      34941908