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Visualizing asymmetric competition among more than 1,000 products using big search data

Ringel, Daniel M. and Skiera, Bernd 2016, Visualizing asymmetric competition among more than 1,000 products using big search data, Marketing science, vol. 35, no. 3, pp. 511-534, doi: 10.1287/mksc.2015.0950.

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Title Visualizing asymmetric competition among more than 1,000 products using big search data
Author(s) Ringel, Daniel M.
Skiera, Bernd
Journal name Marketing science
Volume number 35
Issue number 3
Start page 511
End page 534
Total pages 24
Publisher Institute for Operations Research and the Management Sciences
Place of publication Catonsville, Md.
Publication date 2016-05
ISSN 0732-2399
Keyword(s) big data
competitive market mapping
asymmetric competition
online search
product- and price-comparison sites
Summary In large markets comprising hundreds of products, comprehensive visualization of competitive market structures can be cumbersome and complex. Yet, as we show empirically, reduction of the analysis to smaller representative product sets can obscure important information. Herein we use big search data from a product- and price-comparison site to derive consideration sets of consumers that reflect competition between products. We integrate these data into a new modeling and two-dimensional mapping approach that enables the user to visualize asymmetric competition in large markets (>1,000 products) and to identify distinct submarkets. An empirical application to the LED-TV market, comprising 1,124 products and 56 brands, leads to valid and useful insights and shows that our method outperforms traditional models such as multidimensional scaling. Likewise, we demonstrate that big search data from product- and price-comparison sites provide higher external validity than search data from Google and Amazon.
Language eng
DOI 10.1287/mksc.2015.0950
Field of Research 150505 Marketing Research Methodology
150503 Marketing Management (incl Strategy and Customer Relations)
150501 Consumer-Oriented Product Or Service Development
080704 Information Retrieval and Web Search
1505 Marketing
Socio Economic Objective 910403 Marketing
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, INFORMS
Persistent URL http://hdl.handle.net/10536/DRO/DU:30091168

Document type: Journal Article
Collections: Open Access Checking
Department of Marketing
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