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Decision Models for a Two-Stage Supply Chain Planning under Uncertainty with Time-sensitive Shortages and Real Option Approach
Date
2010-03-23Author
Lee, Hwansik
Type of Degree
dissertationDepartment
Industrial and Systems EngineeringMetadata
Show full item recordAbstract
The primary objective of this research is to develop analytical models for typical supply
chain situations to help inventory decision-makers. We also derive closed form solutions
for each model and reveal several managerial insights from our models through numerical
examples. Additionally, this research gives decision-makers insights on how to implement
demand uncertainty and shortage into a mathematical model in a two-stage supply chain
and shows them what differences these proposed analytical models make as opposed to the
traditional models.
First, we model customer impatience in an inventory problem with stochastic demand
and time-sensitive shortages. This research explores various backorder rate functions in a
single period stochastic inventory problem in an effort to characterize a diversity of customer
responses to shortages. We use concepts from utility theory to formally classify customers
in terms of their willingness to wait for the supplier to replenish shortages. Additionally,
we introduce the notion of expected value of risk profile information (EVRPI), and then
conduct additional sensitivity analyses to determine the most and least opportune conditions
for distinguishing between customer risk-behaviors.
Second, we optimize backorder lead-time (response time) in a two-stage system with
time-dependent partial backlogging and stochastic demand. In this research, backorder cost
is characterized as a function of backorder response time. We also regard backorder rate as
a decreasing function of response time. We develop a representative expected cost function
and closed form optimal solutions for several demand distributions.
Third, we adopt an option approach to improve inventory decisions in a supply chain.
First of all, we apply a real option-pricing framework (e.g., straddle) for determining order quantity under partial backlogging and uncertain demand situation. We establish an optimal condition for the required order quantity when a firm has an desirable fill rate. We
develop a closed form solution for optimal order quantity to minimize the expected total
cost.
Finally, we implement an option contract to hedge the risk of the demand uncertainty.
We show that the option contract leads to an improvement in the overall supply chain prof-
its and product availability in the two-stage supply chain system. This research considers
a standard news-vendor problem with price dependent stochastic demand in a single manufacturer and retailer channel. We derive closed form solutions for the appropriate option
prices set by the manufacturer as an incentive for the retailer to establish optimal pricing
and order quantity decisions for coordinating the channel.
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