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"With or Without Forecast Sharing: Competition and Credibility under Information Asymmetry," Production and Operations Management

Published: 20 November 2013

Author: Mehmet Gumus

Publication: Production and Operations Management

Abstract:

Forecast sharing among trading partners lies at the heart of many collaborative and contractual SCM eorts. Even though it has been praised in both academic and practitioner circles for its critical role in increasing demand visibility, some concerns remain: The rst one is related to the credibility of forecast sharing, and the second is the fear that it may turn into a competitive disadvantage and induce suppliers to increase their price oerings. In this paper, we explore the validity of these concerns under a supply chain with a competitive upstream structure, focusing specically on (i) when and how a credible forecast sharing can be sustainable, and (ii) how it impacts the intensity of price competition. To address these issues, we develop a supply chain model with a buyer facing a demand risk and two heterogeneous suppliers competing for order allocation from the buyer. The extent of the demand risk is known only to the buyer. The buyer submits a buying request to the suppliers via a commonly used procurement mechanism called request for quotation (RFQ). We consider two variants of RFQ. In the rst type, the buyer simply shares the estimated order quantity with no further specications. In the second one, in addition to this, the buyer also species minimum and/or maximum order quantities. We fully characterize equilibrium decisions and prots associated with them under symmetric and asymmetric information scenarios. Our main ndings are that the buyer can use a RFQ with quantity restrictions as a credible signal for forecast sharing as long as the degree of demand information asymmetry is not too high, and that, contrary to above concerns, the equilibrium prices that emerge between competing suppliers under asymmetric information may indeed increase if the buyer can not share forecast information credibly with its upstream partners.

Read full paper: Production and Operations Management

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