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A Two-Sided Matching Approach for Partner Selection and Assessing Complementarities in Partners’ Attributes in Inter-Firm Alliances

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  • Mindruta , Denisa
  • Moeen, Mahka

Abstract

Strategic alliances are undertaken to create value through complementarities of resources and capabilities of the partner firms. The authors develop a matching framework to study strategic alliances, taking a market perspective that explicitly incorporates key features of transactions in strategic alliances: two sided decision making in voluntary collaboration; quest for complementarities between indivisible and heterogeneous partner attributes; and competition on each side for partners on the other side. They assess the relative performance of matching models and binary choice models when estimating parameters within simulations based on a known functional relationship. Within the context of research alliances in the bio-pharmaceutical industry, we hypothesize and find support using the matching model framework for complementarity in partner size, and in upstream research capabilities.

Suggested Citation

  • Mindruta , Denisa & Moeen, Mahka, 2014. "A Two-Sided Matching Approach for Partner Selection and Assessing Complementarities in Partners’ Attributes in Inter-Firm Alliances," HEC Research Papers Series 1068, HEC Paris.
  • Handle: RePEc:ebg:heccah:1068
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    Cited by:

    1. Florence Honoré & Martin Ganco, 2016. "Entrepreneurial teams' acquisition of talent: a two-sided approach," Working Papers 16-45, Center for Economic Studies, U.S. Census Bureau.
    2. Chen Shengqun & Shi Hailiu & Li Meijuan & Wang Yingming & Lin Yang, 2016. "Two-Sided Matching Decision-Making with Uncertain Information Under Multiple States," Journal of Systems Science and Information, De Gruyter, vol. 4(2), pages 186-194, April.

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    Keywords

    alliances; two-sided matching; maximum score estimator; bio-pharmaceutical industry; complementarity;
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