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Cited by 2,095

The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.

Text-Based Network Industries and Endogenous Product Differentiation

Hoberg, Gerard, Phillips, Gordon·2016·Journal of Political Economy
DOI 10.1086/688176
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Abstract

We study how firms differ from their competitors using new time-varying measures of product similarity based on text-based analysis of firm 10-K product descriptions. This year-by-year set of product similarity measures allows us to generate a new set of industries in which firms can have their own distinct set of competitors. Our new sets of competitors explain specific discussion of high competition, rivals identified by managers as peer firms, and changes to industry competitors following exogenous industry shocks. We also find evidence that firm R&D and advertising are associated with subsequent differentiation from competitors, consistent with theories of endogenous product differentiation.

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Metadata

Authors
Hoberg, G., & Phillips, G.
Venue
Journal of Political Economy
Publisher
University of Chicago Press
Published
2016-10
Volume
124
Issue
5
Pages
1423-1465
ISSN
  • 0022-3808 (ISSN-L)
  • 1537-534X
DOI
10.1086/688176
OpenAlex
W3123123374
Cited by
2,095
References
29
FWCI
216.67
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Text-Based Network Industries and Endogenous Product Differentiation. https://app.cochat.ai/papers/10.1086/688176
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Hoberg, G., & Phillips, G. (2016). Text-Based Network Industries and Endogenous Product Differentiation. Journal of Political Economy. https://doi.org/10.1086/688176

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.