Inferring the Economics of Store Density from Closures: The Starbucks Case
Ali Umut Guler ()
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Ali Umut Guler: Koç University, 34450 Sariyer Istanbul, Turkey
Marketing Science, 2018, vol. 37, issue 4, 611-630
Abstract:
This paper proposes a method that makes use of firms’ mass store closures to measure the store network effects of cannibalization and density economies. I calculate each store’s contribution to chain-level profits via one-store perturbations on the set of retained stores, and map these onto the firm’s closure choices. To separate the demand- and supply-side store network effects, I exploit the fact that the business-stealing effect intensifies with local network density, whereas the supply-side disadvantage prevails at sparse regions of the network. I apply the method to study the Starbucks chain. The average rate of cannibalization imposed by a neighbor outlet is 1.2% within one mile and 0.4% within one to three miles. For remote outlets, operation costs increase by 0.3% of revenues for each mile of distance from the network. Counterfactual analyses suggest that income level is a more important determinant of demand than population count at low levels of store penetration, whereas high-population regions can sustain denser store networks because of the softening of the cannibalization effect.
Keywords: store networks; entry models; cannibalization; density economies; Starbucks; great recession (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:37:y:2018:i:4:p:611-630
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