Automotive Procurement Under Opaque Prices: Theory with Evidence from the BMW Supply Chain

• 成果类型: Article; Early Access
• 署名作者: Turcic, Danko; Markou, Panos; Kouvelis, Panos; Corsten, Daniel
• 署名单位: University of California System; University of California Riverside; University of Virginia; Washington University (WUSTL); IE University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2023.4880
• 发表日期: 2023
• 关键词: Asymmetric information; risk management; supply chain; automotive; empirical

摘要

Several features of automotive procurement distinguish it from the prototypical supply chain in the academic literature: pass-through pricing that reimburses suppliers for raw material costs, market frictions that prohibit cost transparency and imbue suppliers with pricing power, and contractual commitments that span multiple production periods. In this context, we formalize a procurement model by considering an automaker that buys components from an upstream supplier to assemble cars over several production periods in an environment where period demands and raw material costs are both stochastic. Our paper clarifies how information asymmetry and market factors that amplify or weaken this asymmetry affect the firms' procurement protocol preferences. 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 do so. Our analysis also reveals that existing contracting protocols in this context are not optimal for procurement under asymmetric information, and so we propose an alternative contracting method. We calibrate our model and estimate an automaker's performance improvement from this optimal contract over the status quo.