IDEAS home Printed from https://ideas.repec.org/a/bla/randje/v49y2018i3p619-655.html
   My bibliography  Save this article

Pairing provision price and default remedy: optimal two‐stage procurement with private R&D efficiency

Author

Listed:
  • Bin Liu
  • Jingfeng Lu

Abstract

This article studies cost‐minimizing two‐stage procurement with Research and Development (R&D). The principal wishes to procure a product from an agent. At the first stage, the agent can conduct R&D to discover a more cost‐efficient production technology. First‐stage R&D efficiency and effort and the realized second‐stage production cost are the agent's private information. The optimal two‐stage mechanism is implemented by a menu of single‐stage contracts, each specifying a fixed provision price and remedy paid by a defaulting agent. A higher delivery price is paired with a higher default remedy, and a more efficient type opts for a higher price and higher remedy.

Suggested Citation

  • Bin Liu & Jingfeng Lu, 2018. "Pairing provision price and default remedy: optimal two‐stage procurement with private R&D efficiency," RAND Journal of Economics, RAND Corporation, vol. 49(3), pages 619-655, September.
    • Handle: RePEc:bla:randje:v:49:y:2018:i:3:p:619-655
    DOI: 10.1111/1756-2171.12247
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1756-2171.12247
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1756-2171.12247?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vivek Bhattacharya, 2021. "An Empirical Model of R&D Procurement Contests: An Analysis of the DOD SBIR Program," Econometrica, Econometric Society, vol. 89(5), pages 2189-2224, September.
    2. Lee, Jun Gon & Park, Min Jae, 2020. "Evaluation of technological competence and operations efficiency in the defense industry: The strategic planning of South Korea," Evaluation and Program Planning, Elsevier, vol. 79(C).
    3. Huiyi Guo & Wei He & Bin Liu, 2022. "Learning by Consuming: Optimal Pricing with Endogenous Information Provision," Papers 2209.01453, arXiv.org.
    4. Lu, Jingfeng & Wang, Zijia, 2021. "Optimal selling mechanisms with buyer price search," Journal of Economic Theory, Elsevier, vol. 196(C).
    5. Meng, Dawen & Sun, Lei & Tian, Guoqiang, 2022. "Dynamic mechanism design on social networks," Games and Economic Behavior, Elsevier, vol. 131(C), pages 84-120.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:randje:v:49:y:2018:i:3:p:619-655. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/randdus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.