Multiproduct retailing and buyer power: The effects of product delisting on consumer shopping behavior

Pre-print, Working paper: This paper empirically examines the effects of product delisting on consumer shopping behavior in a context of grocery retailing by large multiproduct supermarket chains. A product is said to be delisted when a supermarket stops supplying it while it continuous being sold by competing stores. We develop a model of demand in which consumers can purchase multiple products in the same period. Consumers have heterogeneous shopping patterns: some find it optimal to concentrate purchases at a single store while others prefer sourcing several separate supermarkets. We account for this heterogeneity by introducing shopping costs, which are transaction costs of dealing with suppliers. Using scanner data on grocery purchases by French households in 2005, we estimate the parameters of the model and retrieve the distribution of shopping costs. We find a total shopping cost per store sourced of 1.79 € on average. When we simulate the delisting of a product by one supermarket, we find that customers’probability of sourcing that store decreases while the probability of sourcing competing stores increases. The reduction in demand is considerably larger when consumers have strong preferences for the delisted brand. This suggests that retailers may be hurting themselves, and not only manufacturers, when they delist a product. However, when customers have strong preferences for the store such effects are lower, suggesting that inducing store loyalty in customers appears to have an effect on vertical negotiations and, in particular, it enables powerful retailers to impose vertical restraints on manufacturers.

Author(s)

Jorge Florez-Acosta, Daniel Herrera-Araujo

Date of publication
  • 2017
Keywords JEL
D03 D12 L13 L22 L81
Keywords
  • Grocery retailing
  • Supermarket chains
  • Buyer power
  • Vertical
  • Restraints
  • Product delisting
  • Shopping costs
  • One-and multistop shopping
  • Simulated Maximum likelihood
Internal reference
  • PSE Working Papers n°2017-16
Version
  • 1