Enhancing Strategic Supply Decisions by Estimating Suppliers' Marginal Costs

• Date: 01 October 2013
• Author: Konstantin Kogan,Eyal Eckhaus,Yael Perlman
• Published date: 01 October 2013
• DOI: http://doi.org/10.1111/j.1745-493X.2012.03277.x

ENHANCING STRATEGIC SUPPLY DECISIONS BY

ESTIMATING SUPPLIERS’MARGINAL COSTS

EYAL ECKHAUS, KONSTANTIN KOGAN AND YAEL PERLMAN

Bar-Ilan University

The ability to estimate a supplier’s marginal cost confers a strategic com-

petitive advantage to the buyer, whether in negotiations with suppliers, in

an auction setting, or when an auction is used to initiate the process,

which is then followed up with a traditional negotiation. Focusing on

electronic reverse auctions characterized by a one‐shot, first-price, sealed-

bid format, this article proposes an approach for estimating a supplier’s

marginal cost. Specifically, we suggest a two-stage model: In the first stage,

empirical analysis is used to predict the winning bid. In the second stage,

a game-theory approach is used to refine the outcome of the first stage to

provide an estimate of the supplier’s marginal cost. To assess the model,

we apply it to data from a food and beverages company that carried out

electronic auctions to select suppliers for industrial maintenance services.

We find that our estimates are very close to those made by the suppliers

and compare favorably to the efficient marginal costs determined with the

widely used approach of data envelopment analysis. This also implies that

after selecting a supplier through an auction, the buyer can enhance

follow-up negotiations with the supplier by contrasting our model’s esti-

mates of the marginal costs with the supplier’s inefficiencies detected with

the data envelopment analysis.

Keywords: electronic reverse auctions; supplier management; supplier selection;

negotiation; data envelopment analysis

INTRODUCTION

Electronic reverse auctions (e-RAs), in which com-

peting suppliers place bids through an online plat-

form to win a contract with a purchaser, are being

used with growing popularity. e-RAs have been

adopted as a strategic tool in the purchasing function

and are becoming a standard for many procurement

activities. In particular, this strategy has become preva-

lent in the industrial sector (Rosenthal, Zydiak and

Chaudhry 1995). Over the last decade, nearly every

Fortune 500 company has implemented a plan for

reducing supply chain costs, and e-RAs have been one

of the most common tools in that regard (Pearcy,

Giunipero and Wilson 2007). However, the utility of

e-RAs is complicated by the fact that suppliers who

obtain contracts as a result of low bids might not be

able to deliver on their promises (Garvin and Kagel

1994; Harbour 2000). Therefore, the purchaser must

carefully examine the supplier’s costs to be able to

identify underbidding situations and to ensure that

bid prices are realistic (Emiliani 2000; Mullane, Peters

and Bullington 2001).

Game-theoretic approaches have been proposed for

predicting the bids of an ongoing auction, although

they do not address the bidder’s ability to deliver on

his promise. Research on the game theory of auctions

has focused primarily on two models: the indepen-

dent private value (IPV) model (Vickrey 1961; Tom-

bak and Wang 2005) and the common value (CV)

model (Wilson 1967, 1969). In IPV auctions, an indi-

visible item has a value to each of the participating

bidders that is an independent draw from a known

probability distribution. The bids are submitted simul-

taneously, where each bidder knows only his own val-

uation of the item with certainty. This model

corresponds to the first-price sealed-bid auction we

focus on in this study. In a first-price sealed-bid pro-

curement auction, each supplier independently sub-

mits a single bid without seeing the bids of others.

Usually, each participant is allowed to submit only

one bid (“one shot”). The name “first-price” comes

from the fact that when a single contract is up for

auction, the bidder who submits the lowest price (or

the most economically advantageous bid) wins the

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