The impact of product differentiation on symmetric R&D networks

Mohamad Alghamdi, Stuart McDonald, Bernard Pailthorpe

Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review

1 Citation (Scopus)

Abstract

This paper examines the impact of product differentiation on an R&D network. We find that when firms produce goods that are complements or independent, R&D expenditure, prices, firms? net profits and total welfare are always higher under price competition than under quantity competition. When goods are substitutes, R&D expenditure and profits are higher under quantity competition than under price competition. Also, when goods are substitutes and products are sufficiently differentiated, then total welfare is higher in the Bertrand equilibrium than under the Cournot equilibrium. Beyond this threshold level of product differentiation, Cournot competition is superior in terms of social welfare. The paper finds that the key threshold level of product differentiation, determining the relative superiority of the Cournot and Bertrand equilibrium when goods are substitutes, depends on the cost efficiency of R&D and the number of collaborative partnerships that firms participate in relative to the size of the network. We show that when goods are substitutes, if the network is dense so that the number of partnerships is large relative to the number of firms operating in the market, then the threshold value of the product differentiation parameter can be small.

Original languageEnglish
Title of host publicationAnnals of the International Society of Dynamic Games
PublisherBirkhauser
Pages175-215
Number of pages41
DOIs
Publication statusPublished - 2020

Publication series

NameAnnals of the International Society of Dynamic Games
Volume16
ISSN (Print)2474-0179
ISSN (Electronic)2474-0187

Keywords

  • Cooperative links
  • Oligopoly
  • Product differentiation
  • Research and Development (R&D)
  • Symmetric networks

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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