IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v59y2021i6p1860-1874.html
   My bibliography  Save this article

Incentive contracts for green building production with asymmetric information

Author

Listed:
  • Weidong Chen
  • Liming Li

Abstract

When creating a product, a supplier faces the problem of designing the optimal contract to screen the manufacturer's private information. In this paper, we consider a manufacturer with private information about the cost type of production (N types defined in this paper) and its unobservable effort. Aiming to eliminate the negative effects on the green building market development caused by these two kinds of private information, we build a principal-agent model with asymmetric information. The optimal subsidy of the model is obtained by introducing the ‘spot check mechanism’. The results show that manufacturers with reasonable subsidies will not defraud the public about the actual quality of green buildings. Moreover, we discuss the impact of the probability of spot checks and subsidies on the optimal solution. Finally, a numerical example is given to show the effectiveness of the obtained results.

Suggested Citation

  • Weidong Chen & Liming Li, 2021. "Incentive contracts for green building production with asymmetric information," International Journal of Production Research, Taylor & Francis Journals, vol. 59(6), pages 1860-1874, March.
  • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:6:p:1860-1874
    DOI: 10.1080/00207543.2020.1727047
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2020.1727047
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2020.1727047?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Yan Wang & Lifan Yang & Enzo Russo & Domenico Graziano, 2021. "The Incentive Mechanism of Knowledge Sharing in Cross-Border Business Models Based on Digital Technologies," Sustainability, MDPI, vol. 13(22), pages 1-33, November.
    2. Tianjian Yang & Chunmei Li & Xiongping Yue & Beibei Zhang, 2022. "Decisions for Blockchain Adoption and Information Sharing in a Low Carbon Supply Chain," Mathematics, MDPI, vol. 10(13), pages 1-23, June.

    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:taf:tprsxx:v:59:y:2021:i:6:p:1860-1874. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.