The Impact of Supply Quality and Supplier Development on Contract Design

Abstract: In this talk, we examine two key issues in supply management: supply quality and supplier development. To this end, we consider a supplier-buyer pair and develop analytical models for designing optimal buyer-initiated supply contracts with lot sizing, supply quality, and supplier development considerations while modeling private information and individual incentives explicitly. We study two distinct contractual settings. First, we concentrate on the case where there is no supplier development, and, hence, no supply quality improvement effort. In this case, we show that the contractual lot size is larger than the channel optimum when the buyer has incomplete information about the supplier's quality level. For the special case where the buyer's prior distribution of supplier's quality level is uniform, we prove that immediate contracting is in fact more efficient for the channel than not having a contract in the long run as long as the buyer's prior expected quality level is sufficiently high, i.e., more than 75%, or the buyer's estimation of the quality level is unbiased. However, for general prior distributions of the supplier's quality level, immediate contracting may not be effective for the channel depending on the characteristics of the hazard rate function of the prior distribution. Since the efficiency of the contract depends on the buyer's prior distribution of the supplier's quality level, we also present a dynamic programming model for the buyer to determine when to offer a contract to the supplier under information updating. Next, we concentrate on the case where the buyer seeks a quality improvement initiative under a supplier development program but she has incomplete information about the supplier's quality investment sensitivity. We show that the buyer will request a lower level of quality improvement than in the full information case. Also, in this case, we demonstrate that buyer-initiated contracting under asymmetric information is always worthwhile; however, contracting may not lead to quality improvement. In particular, depending on the characteristics of the reverse hazard rate function of the buyer's estimation of the supplier's investment sensitivity, investment decision may not be made. As a result, information asymmetry may ruin the buyer's interest in initiating a supplier development program in practice.

Bio:  Sila Çetinkaya is Professor of Industrial and Systems Engineering at Texas A&M. She joined Texas A&M faculty in 1997 after obtaining her Ph.D. in Management Science from McMaster University in Canada. She also holds M.S. and B.S. degrees, both in Industrial Engineering, from Bilkent University and Istanbul Technical University in Turkey, respectively. Her research interests include supply chain management, inventory theory, and applied probability. Çetinkaya’s publications appeared in Management Science, Operations Research, IIE Transactions, Naval Research Logistics, Production and Operations Management, and Interfaces among other refereed journals. Her research and education activities have been supported by the U.S. National Science Foundation, U.S. Department of Education, Texas Engineering Education Coordination Board, and Frito-Lay, Pepsi-Co, and Nokia among other companies. In 2001, she received the National Science Foundation CAREER Award. She was named the Outstanding Young Industrial Engineer by IIE in 2003, Texas Engineering Experiment Station Fellow in 2006, and Texas A&M Dwight Look College of Engineering Faculty Fellow in 2003, 2006, and 2011. She was also awarded the BP Faculty Award for Teaching Excellence in 2004, E.D. Brockett Professorship in 2006, and Dwight Look College Dean’s Merit Award in 2010. Çetinkaya was a finalist for INFORMS Wagner Prize in 2008 and a co-author of IIE Transactions Best Paper award in 2011. She has been a department editor for IIE Transactions, an associate editor for Naval Research Logistics, and a member of the editorial boards of International Journal of Inventory Research and Manufacturing and Service Operations Management.