Estimating the Stockout-Based Demand Spillover Effect in a Fashion Retail Setting

43 Pages Posted: 6 Nov 2020 Last revised: 15 Aug 2022

See all articles by Songtao Li

Songtao Li

Tsinghua University; Alibaba Group

Lauren Xiaoyuan Lu

Dartmouth College - Tuck School of Business

Susan F. Lu

Purdue University - Krannert School of Management

Simin Huang

Tsinghua University

Date Written: May 31, 2022

Abstract

Problem definition: In brick-and-mortar fashion retail stores, inventory stockouts are frequent. When a specific size of a fashion product is out of stock, the unmet demand might not be completely lost due to spillovers to adjacent sizes of the same style or to other styles. Little research has been done to study consumer response to stockouts of fashion products because researchers had limited access to proprietary data of fashion retailers and because it is challenging to estimate stockout-based demand spillover patterns using existing approaches due to the enormous number of stock keeping units (SKUs) and frequent stockouts in fashion retail stores. To fill this void in the literature, we empirically estimate the stockout-based demand spillover effect in a fashion retail setting.
Methodology/Results: We obtain a large-scale data set from a fashion retail chain selling world-renowned sportswear brands. The retail stores in the sample are dedicated to products of a single brand. Employing around 1.5 million granular and real-time sales and inventory records of 217 stores, 503 men’s footwear products, and 4,024 SKUs over a two-year period, we develop a difference-in-differences framework to estimate the stockout-based cross-size demand spillover effect. We demonstrate the validity of this framework by conducting a pre-trend test and a placebo test. We find that roughly 51.7% of the unmet demand of an out-of-stock SKU spills over to adjacent sizes of the same style when they are in stock: 25.1% to the adjacent-larger size and a 26.6% to the adjacent-smaller size. The cross-size demand spillover effect is larger in regular stores than in flagship stores, larger for casual sports shoes than for specialized sports shoes, and larger for low-price products than for high-price products. Adapting an existing attribute-based demand model to our setting, we estimate that roughly 20.2% of the unmet demand of an out-of-stock SKU spills over to different styles when they are in stock. Taken together, these estimations suggest that about 28.1% of the unmet demand of an out-of-stock SKU becomes lost sales. We further find that when stockouts are widespread among SKUs, stockout-based demand spillovers are significantly reduced, resulting in much increased lost sales.
Managerial implications: First, we empirically quantify the stockout-based cross-size demand spillover effect and its impact on lost sales in a brick-and-mortar fashion retail setting. Second, our simulation analysis shows that incorporating the cross-size demand spillover effect into the sportswear retail chain’s proactive transshipment decision can substantially reduce its transshipment cost and improve its profitability.

Keywords: retail operations; inventory stockouts; demand spillover; lost sales; difference-in-differences; proactive transshipment

Suggested Citation

Li, Songtao and Li, Songtao and Lu, Lauren Xiaoyuan and Lu, Susan Feng and Huang, Simin, Estimating the Stockout-Based Demand Spillover Effect in a Fashion Retail Setting (May 31, 2022). Tuck School of Business Working Paper No. 3696682, Available at SSRN: https://ssrn.com/abstract=3696682 or http://dx.doi.org/10.2139/ssrn.3696682

Songtao Li

Alibaba Group ( email )

Tsinghua University ( email )

Beijing, 100084
China

Lauren Xiaoyuan Lu (Contact Author)

Dartmouth College - Tuck School of Business ( email )

Hanover, NH 03755
United States

Susan Feng Lu

Purdue University - Krannert School of Management ( email )

1310 Krannert Building
West Lafayette, IN 47907-1310
United States

HOME PAGE: http://https://sites.google.com/site/susanluhome/home

Simin Huang

Tsinghua University ( email )

Beijing, 100084
China

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