A principal–agent model for product specification and production

A principal–agent model for product specification and production

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Article ID: iaor20073807
Country: United States
Volume: 51
Issue: 1
Start Page Number: 106
End Page Number: 119
Publication Date: Jan 2005
Journal: Management Science
Authors: , ,
Keywords: production, inventory
Abstract:

This paper develops and analyzes a principal–agent model for product specification and production motivated by ‘core buying’ decisions at an automobile manufacturer. The model focuses on two important elements of the ‘core’ buyer's responsibility: (1) assessing the supplier's capability, and (2) allocating some or all of a fixed level of some buyer-internal resource to help the supplier. Under the contracting scheme we model, the buyer (principal) delegates the majority of product specification and production activity to the supplier (agent), but retains the flexibility to commit a given, observable amount of an internally available, limited resource (e.g., engineering hours) to help the supplier. The supplier, in turn, allocates his resource (e.g., engineering hours) to produce the finished product. As in the motivating scenario, both the supplier's resource allocation and capability are assumed to be hidden from the buyer. Hence, the principal's problem is to determine a menu of (resource-commitment, transfer-price) contracts to minimize her total expected cost. Our analysis demonstrates that if buyer resource and supplier capability are substitutes, then the buyer's second-best involvement in the supplier's production process will be greater than first-best. The opposite is true if they are complements. Further, when the opportunity cost for the buyer's resource is zero, then in the substitutes case the buyer will commit all of its resource, while in the complements case the buyer may withhold some resources to screen the supplier type. We describe two applications of the model – one in inventory management and one in pharmaceutical drug discovery – to illustrate its applicability and versatility. Finally, we use insights from the model to suggest hypotheses for empirical study.

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