Estimating the buyer's willingness to pay using Bayesian belief distribution with IFR

Brusset, Xavier and Cattan-Jallet, Roxane (2009): Estimating the buyer's willingness to pay using Bayesian belief distribution with IFR.

Abstract

In supply chain management, information about the downstream party's willingness to pay (wtp) for a service or a good sold by an upstream party may not be known to the latter. The seller has to make an educated guess for the price at which to offer a good or service. If the buyer refuses to buy, the seller can still turn to a third party and sell at a lower price or hold onto the good. We show that the seller has one interior profit maximizing price if his Bayesian belief about the buyer's wtp follows a distribution which has an increasing failure rate (IFR) in the sense of Barlow and Proschan (1965). We prove that the precision of information available to the supplier influences the rent distribution and how the downstream party might opportunistically mis-inform the upstream partner. We propose another reading of the single-price newsvendor problem in Lariviere and Porteus (2001), Ziya et al. (2004a,b), Paul (2006) or Lariviere (2006). Our approach applies to all types of mechanism design problems where a profit-maximizing party has to rely on Bayesian belief to palliate information asymmetry and has alternative sources of income or cost.

• Item Type: MPRA Paper
• Language: English
• Keywords: supply chain optimization; Bayesian belief; mechanism design; increasing failure rate
• Subjects: D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D84 - Expectations ; Speculations; C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C44 - Operations Research ; Statistical Decision Theory; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D82 - Asymmetric and Private Information ; Mechanism Design; C - Mathematical and Quantitative Methods > C7 - Game Theory and Bargaining Theory > C72 - Noncooperative Games

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