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Analysis of Umbrella Branding with Crowdsourced Data

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  • Timothy J. Richards

Abstract

ABSTRACT We test for umbrella effects among private label products using a new type of data: crowdsourced data, or data contributed by users of an in‐store shopping app for their own, and other users' benefit. We model umbrella effects in our crowdsourced data using a random‐parameter logit model with private‐label preference parameters correlated among product categories. Our results support the existence of umbrella effects in our limited sample data, where umbrella effects are defined as correlated preferences for private labels across categories. [JEL Classifications: D12; D43; L13; L83; M31].

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  • Timothy J. Richards, 2017. "Analysis of Umbrella Branding with Crowdsourced Data," Agribusiness, John Wiley & Sons, Ltd., vol. 33(2), pages 135-150, April.
    • Handle: RePEc:wly:agribz:v:33:y:2017:i:2:p:135-150
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    File URL: http://hdl.handle.net/10.1002/agr.21466
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    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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