Information Asymmetry, Rents, and Cost Risk Allocation: Theory with Evidence from BMW

52 Pages Posted: 15 Oct 2019 Last revised: 12 May 2022

See all articles by Danko Turcic

Danko Turcic

University of California, Riverside (UCR) - A. Gary Anderson Graduate School of Management

Panos Markou

University of Virginia - Darden School of Business

Panos Kouvelis

Washington University in St. Louis

Daniel Corsten

FundaciĆ³n Instituto de Empresa, S.L.

Date Written: April 1, 2022

Abstract

Several features of automotive procurement distinguish it from the prototypical supply chain in the academic literature: pass-through pricing that reimburses auto part suppliers for raw material costs; informational asymmetries that imbue suppliers with pricing power; and contractual commitments that span multiple production periods. We formalize a model of automotive procurement by considering an automaker that procures components from an upstream supplier to assemble cars over several production periods, and where period demands and raw material costs are both stochastic. Our model identifies four key market factors that drive protocol preference: asymmetric information in raw material costs, the price elasticity of consumer demand, supplier R&D and tooling costs, and raw material price variability. Then, using proprietary contract and supplier data from BMW, we empirically validate this model and show that it reflects BMW's reality: the factors that should theoretically go into automotive procurement decisions in fact do so. Our analysis also reveals that existing contracting protocols in this context are not optimal for procurement under asymmetric information. We therefore propose an alternative procurement protocol that achieves a second-best outcome, which is the best the automaker can do under asymmetric information. We calibrate our model and estimate an automaker's performance improvement from this optimal contract over the status quo.

Keywords: asymmetric information, risk management, commodity, automotive, empirical

Suggested Citation

Turcic, Danko and Markou, Panos and Kouvelis, Panos and Corsten, Daniel, Information Asymmetry, Rents, and Cost Risk Allocation: Theory with Evidence from BMW (April 1, 2022). Darden Business School Working Paper No. 3464595, Available at SSRN: https://ssrn.com/abstract=3464595 or http://dx.doi.org/10.2139/ssrn.3464595

Danko Turcic (Contact Author)

University of California, Riverside (UCR) - A. Gary Anderson Graduate School of Management ( email )

Riverside, CA 92521
United States

Panos Markou

University of Virginia - Darden School of Business ( email )

P.O. Box 6550
Charlottesville, VA 22906-6550
United States

Panos Kouvelis

Washington University in St. Louis ( email )

One Brookings Drive
Campus Box 1156
St. Louis, MO 63130-4899
United States

HOME PAGE: http://www.panoskouvelis.info

Daniel Corsten

FundaciĆ³n Instituto de Empresa, S.L. ( email )

Serrano 99
Madrid, 28006
Spain

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