Probabilistic procurement auctions

Giebe, Thomas; Schweinzer, Paul

doi:10.1007/s10058-014-0161-6

Cited by 6 publications

(4 citation statements)

References 34 publications

(32 reference statements)

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“…Third, I assume throughout that buyers have perfect information about surplus. While this treatment is consistent with the published literature, recent research also examines scoring auctions in which buyers are imperfectly informed (Geibe and Schweinzer, 2014). Finally, the application to the Bazaarvoice/Power Reviews merger gleans information on average prices and costs from accounting reports of Bazaarvoice.…”

Section: Introductionmentioning

confidence: 71%

Modeling the effects of mergers in procurement

Miller¹

2014

International Journal of Industrial Organization

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Section: Introductionmentioning

confidence: 71%

Modeling the effects of mergers in procurement

Miller¹

2014

International Journal of Industrial Organization

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“…In this case too, these punishments are time-limited. 11 See, for instance, Hanazono et al (2013) and Giebe and Schweinzer (2015). between our players, thus investigating relational contracts and the incentives that they create to provide quality.…”

Section: Related Literaturementioning

confidence: 99%

Public procurement with unverifiable quality: The case for discriminatory competitive procedures

Albano

Cesi

Iozzi

2017

Journal of Public Economics

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Unverifiable quality may affect the enforcement of procurement contracts even when the award procedure is able to select the most efficient firm in the market. In this paper, we show that a discriminatory competitive mechanism – which awards the contract on the basis of price and (firms') past performance – yields an efficient allocation of the contract and allows the buyer to implement her desired quality. Quality enforcement arises out of relational contracting whereby the buyer ‘handicaps' a contractor in future competitive tendering processes if it fails to provide the required quality. We study an infinitely repeated procurement model with two firms and one buyer imperfectly informed on the firms' cost, in which, in each period, the buyer runs a discriminatory auction. We restrict our analysis to the case of a buyer committed to her handicapping strategy, a case which captures some of the features of a public buyer. When players use either grim trigger or stick-and-carrot strategies, we find that the buyer can induce the delivery of optimal (unverifiable) quality with a variety of handicap levels and, when applicable, durations of the punishment period; for some values of the handicap and the length of the punishment period, both firms remain active in the market even when punished

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“…Among recent works, Giebe and Schweinzer (2015) and Athey and Nekipelov (2011) present symmetric scoringauction models (for different applications) with quality and cost components in which (exogenous) selection uncertainty arises either from the buyer's inability to assess bidder's quality or from the fact that quality scores vary over time. After accounting for this uncertainty, either a single (Giebe and Schweinzer 2015) or a fixed number of winners (Athey and Nekipelov 2011) is selected. In contrast, we assume that CMS can reliably assess the quality of each proposer's bundle.…”

Section: Literature Reviewmentioning

confidence: 99%

Bundled Payments For Healthcare Services: Proposer Selection and Information Sharing

Gupta

Mehrotra

2015

Operations Research

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The Centers for Medicare and Medicaid Services (CMS) has introduced a "bundled payments for care improvement" (BPCI) initiative. Each bundle pertains to a specific medical condition, a set of linked services, and a length of time referred to as an episode of care. Proposers choose bundles, design service chains, and propose target values of quality metrics and payments per episode. Expert panels evaluate proposals based on CMS-announced relative weights, but there is no limit on the number of proposers that may be selected. Moreover, there is no minimum score that will guarantee selection, which makes selection uncertain for proposers. We develop normative models for the parameter selection problems faced by potential proposers within the CMS' proposal selection process. Proposers have private information about their costs of achieving different quality targets, which determine their equilibrium responses. We show that an optimal strategy for CMS, under its current approach, may be to either announce a fixed threshold or keep the selection process uncertain, depending on market characteristics. We also formulate and solve the proposer selection problem as a constrained mechanism design problem, which reveals that CMS' current approach is not optimal. We present policy guidelines for government agencies pursuing bundled payment innovations.

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Probabilistic procurement auctions

Cited by 6 publications

References 34 publications

Modeling the effects of mergers in procurement

Modeling the effects of mergers in procurement

Public procurement with unverifiable quality: The case for discriminatory competitive procedures

Bundled Payments For Healthcare Services: Proposer Selection and Information Sharing

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