Estimating Demand for Substitutable Products when Inventory Records are Unreliable
Name
2016_Steeneck_DemandInventoryUncertainty copy.pdf
Size
24.53 MB
Format
Adobe PDF
Checksum (MD5)
64a3c139d621e6803a3f3573cefb1b5a
Author(s)
Steeneck, Daniel
Eng-Larsson, Fredrik
Jauffred, Francisco
Date Issued
October 21, 2016
Series/Report no.
SCALE Working Paper Series;16-06
Abstract
We present a procedure for estimating demand for substitutable products when the inventory record is unreliable and only validated infrequently and irregularly. The procedure uses a structural model of demand and inventory progression, which is estimated using a modified version of the Expectation Maximization-method. The procedure leads to asymptotically unbiased estimates without any restrictive assumptions about substitution patterns or that inventory records are periodically known with certainty. The procedure converges quickly also for large product categories, which makes it suitable for implementation at retailers or manufacturers that need to run the analysis for hundreds of categories or stores at the same time. We use the procedure to highlight the importance of considering inventory reliability problems when estimating demand, first through simulation and then by applying the procedure to a data set from a major US retailer. The results show that for the product category in consideration, ignoring inventory reliability problems leads to demand estimates that on average underestimate demand by 5%. It also results in total lost sales estimates that account for only a fraction of actual lost sales.
Subjects
demand estimation
inventory uncertainty
choice behavior
multinomial logit model
EM method
MIT Department
Massachusetts Institute of Technology. Center for Transportation & Logistics
Terms of Use
Attribution 3.0 United States
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