Demand estimation when there are unobservable substitutions amongst choice alternatives

Lihua Bai, Yuan Ren, Nazrul I Shaikh

Research output: Contribution to journalArticle

Abstract

Product stock-outs and the resultant purchase of substitutes by customer is common in retail. These stock-out lead to censored sales data; the observed demand for products with stock-outs could be lower that the true demand for the same while the observed demand for the substitutes could be inflated. If historical sales data is used to forecast future demand for a product without accounting for stock-outs, it could lead to errors in demand forecasting on account of misspecification. In this paper, we demonstrate the need and the benefits of data unconstraining and develop a data unconstraining method to address the dual issues of estimation of demand and substitution rates when there are unobserved substitutions among choice alternatives. We compare the effectiveness of the proposed technique by comparing it against the popular techniques available in extant literature.

Original languageEnglish (US)
Pages (from-to)51-65
Number of pages15
JournalInternational Journal of Information Systems and Supply Chain Management
Volume12
Issue number1
DOIs
StatePublished - Jan 1 2019

Keywords

  • Censored data
  • Data unconstraining
  • Demand estimation
  • Retail assortment planning
  • Substitution rates

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems

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