Framework Agreements in Procurement: An Auction Model and Design Recommendations

69 Pages Posted: 27 Apr 2013 Last revised: 12 Aug 2016

Yonatan Gur

Stanford Graduate School of Business

Lijian Lu

Columbia University - Columbia Business School

Gabriel Y. Weintraub

Stanford Graduate School of Business, Stanford University; Columbia University - Columbia Business School - Decision Risk and Operations

Date Written: August 11, 2016

Abstract

Framework agreements (FAs) are procurement mechanisms commonly used by buying agencies around the world to satisfy demand that arises over a certain time horizon. This paper is one of the first in the literature that provides a formal understanding of FAs, with a particular focus on the cost uncertainty faced by bidders over the FA time horizon. We introduce a model that generalizes standard auction models to include this salient feature of FAs; we analyze this model theoretically and numerically. First, we show that FAs are subject to a sort of winner’s curse that in equilibrium induces higher expected buying prices relative to running first-price auctions as needs arise. Then, our results provide concrete design recommendations that alleviate this issue and decrease buying prices in FAs, highlighting the importance of (i) monitoring the price charged at the open market by the FA winner and using it to bound the buying price; (ii) investing in implementing price indexes for the random part of suppliers’ costs; and (iii) allowing suppliers the flexibility to reduce their prices to compete with the open market throughout the selling period. These prescriptions are already being used by the Chilean government procurement agency that buys US$2 billion worth of contracts every year using FAs.

Keywords: Framework agreement, procurement, Auction, Bayesian Nash Equilibrium, mechanism design

Suggested Citation

Gur, Yonatan and Lu, Lijian and Weintraub, Gabriel Y., Framework Agreements in Procurement: An Auction Model and Design Recommendations (August 11, 2016). Columbia Business School Research Paper No. 13-24. Available at SSRN: https://ssrn.com/abstract=2257073 or http://dx.doi.org/10.2139/ssrn.2257073

Yonatan Gur

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

Lijian Lu

Columbia University - Columbia Business School ( email )

3022 Broadway
New York, NY 10027
United States

Gabriel Y. Weintraub (Contact Author)

Stanford Graduate School of Business, Stanford University ( email )

Stanford, CA 94305
United States

Columbia University - Columbia Business School - Decision Risk and Operations ( email )

New York, NY
United States

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