Analysis of Umbrella Branding with Crowdsourced Data

Timothy Richards

doi:10.1002/agr.21466

Analysis of Umbrella Branding with Crowdsourced Data

Research output: Contribution to journal › Article › peer-review

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].

Original language	English (US)
Pages (from-to)	135-150
Number of pages	16
Journal	Agribusiness
Volume	33
Issue number	2
DOIs	https://doi.org/10.1002/agr.21466
State	Published - Mar 1 2017

ASJC Scopus subject areas

Food Science
Geography, Planning and Development
Animal Science and Zoology
Agronomy and Crop Science
Economics and Econometrics

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10.1002/agr.21466

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title = "Analysis of Umbrella Branding with Crowdsourced Data",

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].",

author = "Timothy Richards",

note = "Funding Information: The author gratefully acknowledges funding from the Agriculture and Food Research Initiative of the National Institute for Food and Agriculture, USDA. Publisher Copyright: {\textcopyright} 2016 Wiley Periodicals, Inc.",

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N2 - 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].

AB - 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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Analysis of Umbrella Branding with Crowdsourced Data

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