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Structural Estimation of the Effect of Out-of-Stocks
Open accessAbstract
We develop a structural demand model that captures the effect of out-of-stocks on customer choice. Our estimation method uses store-level data on sales and partial information on product availability. Our model allows for flexible substitution patterns which are based on utility maximization principles and can accommodate categorical and continuous product characteristics. The methodology can be applied to data from multiple markets and in categories with a relatively large number of alternatives, slow moving products and frequent out-of-stocks. We estimate our model using sales data from multiple stores for twenty four items in the shampoo product category. In addition, we illustrate how the model can be used to assist the decisions of a retailer in two ways. First, we show how to quantify the lost sales induced by out-of-stock products. Second, we provide insights on the financial consequences of out-of-stocks and suggest simple policies that can be used to help mitigate the negative economic impact of out-of-stocks.
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Recent literature methods for estimating primary demand for substitutable products under stock-outs are more suitable for in-season promotions rather than markdown sales.
“Though there exists recent literature on how to estimate primary demand for substitutable products under the presence of stock-outs (e.g., Vulcano et al. 2009 and Musalem et al. 2010), the data and computational requirements make them more suitable for in-season promotions rather than markdown sales.”
From Clearance Pricing Optimization for a Fast-Fashion Retailer (2012) · cites this paper as Musalem et al. 2010
The Literature Review (pp. 6, 9) describes a method for estimating demand and substitution under stock-outs and says it uses inventory and sales data and is computationally intensive. The Conclusions (p. 32) identify temporary price promotions as an application. Our copy does not compare the method’s suitability for in-season promotions versus markdown sales; that comparison is the citing authors’ own conclusion. (LLM, conf=0.84)
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References 46 · Cited by 196
Research works printed but not linked: 39
- 10.1287/mksc.22.3.304.17739 · DOI
- 10.1287/mnsc.1060.0577 · DOI
- 10.1177/002224379503200105 · DOI
- 10.1287/mksc.17.4.406 · DOI
- 10.2307/2555829 · DOI
- 10.2307/2171802 · DOI
- 10.1287/mnsc.49.9.1121.16565 · DOI
- 10.1287/mksc.1080.0366 · DOI
- 10.1287/mnsc.1090.1095 · DOI
- Cachon G. P., 2005, Matching Supply with Demand
- 10.1016/S0022-4359(00)00026-9 · DOI
- 10.1016/S0167-8116(03)00037-5 · DOI
- 10.1509/jmkr.44.4.613 · DOI
- 10.1509/jmkr.2005.42.3.368 · DOI
- 10.1177/002224379102800404 · DOI
- Conlon C., Mortimer J. H. Demand estimation under incomplete product availability. (2009) . Working paper, Harvard University, Cambridge, MA · DOI
- 10.1287/mnsc.1070.0789 · DOI
- 10.1177/002224379603300406 · DOI
- 10.1086/314323 · DOI · Paper page
- Gruen T. W., 2002, Retail Out-of-Stocks: A Worldwide Examination of Extent, Causes and Consumer Responses
- 10.1086/209225 · DOI
- 10.1016/j.jeconom.2008.12.010 · DOI
- 10.1287/mksc.1070.0270 · DOI
- 10.1080/01621459.1995.10476572 · DOI · Paper page
- 10.1287/mksc.21.3.229.143 · DOI
- 10.1287/opre.1070.0409 · DOI
- 10.1509/jmkr.41.4.467.47005 · DOI
- 10.1509/jmkr.45.6.715 · DOI
- 10.1002/jae.1060 · DOI
- O'Connell V., 2008, Wall Street Journal, B1
- 10.1515/9781503619883 · DOI
- 10.1177/002224379102800405 · DOI
- 10.1287/mksc.15.4.321 · DOI · Paper page
- 10.1287/opre.48.1.50.12443 · DOI
- 10.1509/jmkr.39.3.304.19106 · DOI
- 10.1017/CBO9780511753930 · DOI
- 10.1287/mnsc.45.10.1324 · DOI
- 10.1023/B:QMEC.0000003327.55605.26 · DOI
- Zipkin P., 2000, Foundations of Inventory Management
Metadata
- Authors
- Musalem, A., Olivares, M., Bradlow, E. T., Terwiesch, C., & Corsten, D.
- Affiliations
- Duke University (US)
- Columbia University (US)
- University of Pennsylvania (US)
- Operations and Technology Management, IE Business School, 28006 Madrid, Spain
- Venue
- Management Science
- Published
- 2010-07
- Volume
- 56
- Issue
- 7
- Pages
- 1180-1197
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2136554921
- Cited by
- 196
- References
- 46
- Citations by year
- 2026: 8 · 2025: 10 · 2024: 15 · 2023: 10 · 2022: 19 · 2021: 15 · 2020: 8 · 2019: 15 · 2018: 16 · 2017: 11 · 2016: 14 · 2015: 15 · 2014: 11 · 2013: 5 · 2012: 9
- FWCI
- 15.20
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Management Science (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, other-oa)
- ScholarlyCommons (University of Pennsylvania) (submittedVersion)
- Americanae (AECID Library) (submittedVersion, other-oa)
- DukeSpace (Duke University) (submittedVersion, cc-by-nc-nd)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Supply Chain and Inventory Management
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Keywords
- stockouts, structural demand model, consumer choice, product availability, substitution patterns, utility maximization, lost sales, slow-moving products
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