Visualizing Asymmetric Competition Among More Than 1,000 Products Using Big Search Data

Daniel M. Ringel () and Bernd Skiera
Additional contact information
Daniel M. Ringel: Department of Marketing, Faculty of Business and Economics, Goethe-Universität Frankfurt, 60629 Frankfurt am Main, Germany

Marketing Science, 2016, vol. 35, issue 3, 511-534

Abstract: 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.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mksc.2015.0950 .

Keywords: big data; competitive market mapping; asymmetric competition; online search; product- and price-comparison sites (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (28)

Downloads: (external link)
http://dx.doi.org/10.1287/mksc.2015.0950 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:35:y:2016:i:3:p:511-534

Access Statistics for this article

More articles in Marketing Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().