Diaspora Ownership and International Technology Licensing by Emerging Market Firms

Aleksandra Gregorič, Larissa Rabbiosi*, Grazia D. Santangelo

*Corresponding author for this work

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Abstract

The liability of origin makes participation in international technology licensing challenging for emerging market firms. We draw on signaling theory to propose that diaspora ownership – diaspora members’ equity investments in their homeland firms – constitutes a reliable third-party signal of emerging market firms’ trustworthiness, which facilitates the access of these firms to international technology licensing. We further hypothesize that the efficacy of diaspora ownership as a third-party signal varies with the firm’s subnational context. Specifically, the relevance of diaspora ownership signal increases with the degree of homogeneity of the within-industry R&D effort in the firm’s sub-national location. This is because, under these conditions, additional signals are required to differentiate between local firms operating in the same industry. In contrast, the diaspora ownership signal has a smaller effect in dysfunctional institutional contexts due to their prohibitive transaction costs. We test our arguments on a matched sample of 597 Indian firms operating between 2006 and 2015, and find general support for the predicted relationships. Our study advances research on the liability of origin of emerging market firms, the work on subnational dimension of international business, and the literature on the benefits diasporans bring to their homelands and resident countries.
Original languageEnglish
JournalJournal of International Business Studies
Volume52
Issue number4
Pages (from-to)671-691
Number of pages21
ISSN0047-2506
DOIs
Publication statusPublished - Jun 2021

Bibliographical note

Published online: 11 April 2020

Keywords

  • Emerging market firms
  • International technology licensing
  • Diaspora ownership
  • Liability of origin
  • Subnational environments
  • Signaling theory
  • Matched sample
  • Instrumental variables estimation

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