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The Effect of Unannounced Inspection on Prevention of Drug Fraud

  • Manman ZhangEmail author
  • Juliang Zhang
  • T.C.E. Cheng
  • Guowei Hua
  • Xiaojie Yan
  • Yi Liu
Article
  • 25 Downloads

Abstract

Alarge number of incidents related to fake/inferior-quality drugs have occurred in China in recent years. In order to reduce drug crimes, the China Food and Drug Administration (CFDA) has exploited the new supervision approach, i.e., unannounced inspection (UI), since September 2014. However, the effectiveness of UI in driving drug producers to put more effort into meeting the requirements of Good Manufacturing Practice (GMP) is yet to be ascertained. In this paper we apply game theory to study the effects of UI on the prevention of drug fraud, drug producers’ profits, and social welfare under scenarios of complete and incomplete information. We show that UI is not always an effective way of supervision. Specifically, if the upper bound on the punishment is not very large, UI can drive the firmto make the largest self-supervision effort only when the firm’s technical level is high and the supervision cost is low. Otherwise, UI cannot drive the firm to make the largest self-supervision effort. Under incomplete information, firms with a high technical level would adopt more self-supervision and make more profit than those with a low technical level. Moreover, we design a new mechanism under incomplete information that can incentive drug producers to make greater self-supervision effort to meet the requirements of GMP under certain conditions.

Keywords

Drug supervision healthcare system game theory Nash equilibrium incomplete information mechanism design 

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Notes

Acknowledgements

We thank the anonymous reviewers for their helpful comments on our paper. This work was supported in part by the National Natural Science Foundation of China (grant numbers 71390334 and 71132008) and the Program for New Century Excellent Talents in University (NCET-13-0660).

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Copyright information

© Systems Engineering Society of China and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Manman Zhang
    • 1
    Email author
  • Juliang Zhang
    • 1
  • T.C.E. Cheng
    • 2
  • Guowei Hua
    • 1
  • Xiaojie Yan
    • 3
  • Yi Liu
    • 1
  1. 1.School of Economics and ManagementBeijing Jiaotong UniversityBeijingChina
  2. 2.Department of Logistics and Maritime StudiesThe Hong Kong Polytechnic University, KowloonHong KongChina
  3. 3.Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijingChina

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