Beteiligte: | |
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In: | Marketing Science, 37, 2018, 4, S. 611-630 |
veröffentlicht: |
Institute for Operations Research and the Management Sciences (INFORMS)
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Medientyp: | Artikel, E-Artikel |
Umfang: | 611-630 |
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ISSN: |
0732-2399
1526-548X |
DOI: | 10.1287/mksc.2017.1078 |
veröffentlicht in: | Marketing Science |
Sprache: | Englisch |
Schlagwörter: | |
Kollektion: | Institute for Operations Research and the Management Sciences (INFORMS) (CrossRef) |
<jats:p> 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. </jats:p><jats:p> Data are available at https://doi.org/10.1287/mksc.2017.1078 . </jats:p> |