Text-Based Network Industries and Endogenous Product Differentiation
2016/09/01 by Gerard Hoberg, Gordon Phillips, Gordon M. Phillips · 2,150 citations
Business, Management and Accounting · Mathematics · #Business #Competition (biology) #Competitor analysis #Computer science #Corporate Finance and Governance #Digital Platforms and Economics #Economics #Industrial organization #International Business and FDI #Marketing #Mathematics #Microeconomics #Product (mathematics) #Product differentiation #Set (abstract data type) #Similarity (geometry)
paper · doi:10.1086/688176
published in Journal of Political Economy 124(5), 1423-1465 (University of Chicago Press)
openalex publication_date 2016/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
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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