Product Variety, Across-Market Demand Heterogeneity, and the Value of Online Retail
Author(s) -
Thomas Quan,
Kevin Williams
Publication year - 2017
Publication title -
ssrn electronic journal
Language(s) - English
Resource type - Journals
ISSN - 1556-5068
DOI - 10.2139/ssrn.2993236
Subject(s) - variety (cybernetics) , business , product (mathematics) , value (mathematics) , marketing , retail market , industrial organization , commerce , computer science , geometry , mathematics , machine learning , artificial intelligence
Online retail gives consumers access to an astonishing variety of products. However, the additional value created by this variety depends on the extent to which local retailers already satisfy local demand. To quantify the gains and account for local demand, we use detailed data from an online retailer and propose methodology to address a common issue in such data - sparsity of local sales due to sampling and a significant number of local zeros. Our estimates indicate products face substantial demand heterogeneity across markets; as a result, we find gains from online variety that are 30% lower than previous studies.
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