Information technology is
an important enabler of efficient supply chain strategies. Indeed, much of
the current interest in supply chain management is motivated by the
possibilities introduced by the abundance of data and the savings inherent
in sophisticated analysis of these data. For example, information
technology has changed the way companies collaborate with suppliers and
customers. These collaborations, which allows companies
to share sensitive demand information with their suppliers in real time,
have achieved huge success in practice in terms of inventory reduction,
service level improvement, and quick response to market changes (Stein
and Sweat (1998) "Killer Supply Chains").
My research in this area
focuses on two questions: (1) how to efficiently utilize the shared information, and (2) what is the impact
of information sharing on supply chain performance.
Zhang, X.L., Y. Zhao
(2010). The Impact of
External Demand Information on Parallel Supply Chains with Interacting
Demand. Production and Operations Management 19(4):
Abstract: This paper considers two
parallel supply chains with interacting demand streams. Each supply chain
consists of one supplier and one retailer. The two demand streams are
jointly described with a vector autoregressive time-series process in which
they interact and their respective innovation errors correlate
contemporaneously. For each supply chain, we develop insights into when and
how much the supplier and the retailer can improve on their forecasting
accuracy if the external demand history of the other supply chain is
utilized. When this external demand history is not available or made
available after a time lag, we develop a partial process and a delayed
process to characterize the demand structure that the retailer can recover
from the available demand histories. Our results show that the external
demand history of the other supply chain always helps the retailer make
better forecasts when demand streams interact; however, the enhanced
information alters the retailerís order process, which may produce larger
forecasting errors for the supplier. Conditions are established for
the supplier to benefit from the external demand history of the other
Simchi-Levi, D., Y. Zhao
(2003). The Value of Information
Sharing in a Two-Stage Supply Chain with Production Capacity Constraint. Naval
Research Logistics 50, 888-916.
Abstract: This paper considers a
class of serial supply chains with a single retailer and a single supplier
constrained by finite production capacity. The supplier, however, can
receive demand information from the retailer in between retailerís
consecutive orders. The paper characterizes the optimal inventory policies
that allow the supplier to best utilize the information over a finite time
horizon. Managerial insights are developed with respect to the impact of
information sharing, its timing and frequency.
Simchi-Levi, D., Y.
Zhao (2004). The Value of
Information Sharing in a Two-stage Supply Chain with Production Capacity
Constraint: The Infinite Horizon Case. Probability in the
Engineering and Informational Sciences 18, 247-274.
Abstract: This paper
extends the analysis of Simchi-Levi and Zhao
(2003) to models in an infinite time horizon under either the total
discounted cost criterion or the average cost criterion. It develops a new
approach to characterize the Markov chain induced by the cyclic order-up-to
policies. It also provides a simple proof for the optimality of the cyclic
order-up-to policy under the average cost criterion.
(2002). The Impact of Information Sharing on
Supply Chain Performance. Ph.D. Thesis. IEMS Dept., Northwestern
University. Evanston, IL.