Working Paper No. 1247

Inventory Behavior, Demand, and Productivity in Retail

Published: November 8, 2018Pages: 45Keywords: Productivity; Inventory performance; Supply chain management; Product varietyJEL-codes: L11; L13; L25; L81; M21

Inventory Behavior, Demand, and Productivity in Retail Florin Maican and Matilda Orth


This paper studies the factors underlying the heterogeneity in inventory behavior and performance across retail stores. We use a dynamic model of multi-product retailers and local competition to estimate store productivity and consumers’ perceived quality of the shopping experience, and we analyze their relationship with inventory behavior and product variety.

Using novel and detailed data on Swedish stores and their products, we find that stores learn from demand to improve future productivity. Store productivity is the main primitive that increases inventory turnover and product variety, and this increase is larger for stores with already high inventory turnover. Stores in small markets with intense competition from rivals have higher inventory turnover. Consumers in large markets and markets with large investments in technology benefit from a broader product variety. Counterfactual experiments show that the increase in inventory turnover due to innovations in productivity is three times greater when uncertainty in demand is reduced by 30 percent.

Our analysis highlights important trade-offs between productivity and demand that allow retailers to reach high levels of inventory turnover and offer a broad product variety to consumers.

Matilda Orth

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Ph: +46 8 665 45 31
Mob: +46 73 642 3824
matilda.orth@ifn.se

Florin Maican

Contact

Ph: +46 31 786 4866
Mob: +46 76 235 3039
florin.maican@ifn.se

Global index of the sharing economy

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2018 Bergh Funcke Wernberg - Timbro Sharing Economy Index-1fHemsidan.jpg

Andreas Bergh, IFN and Lund University, is one of the authors of this book. The Timbro Sharing Economy Index is the first global index of the sharing economy. The index has been compiled using traffic volume data and scraped data, and provides a unique insight into the driving factors behind the peer-to-peer economy.

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