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Research summary: Strategic alliances are undertaken to create value through complementarities of resources and capabilities of the partner firms. This paper uses a recently developed estimator of matching games, i.e., the maximum score estimator, to advance strategic management research on partner selection in strategic alliances, with a focus on the formation of research alliances in the biopharmaceutical industry. We contribute to the literature in three ways. First, we develop a matching framework to study strategic alliances, taking a market perspective that explicitly incorporates key features of alliance formation: two-sided decision making; quest for complementarities between indivisible and heterogeneous partner attributes; and competition on each side of the market for partners on the other side of the market. Second, we assess the relative performance of the maximum score and standard discrete choice estimators by performing simulations based on known functional relationships in various matching scenarios. Third, within the context of biopharmaceutical research alliances, we hypothesize and find support using the maximum score estimator for complementarity in partner size and in upstream research capabilities.
Managerial summary: A critical question facing managers who seek to benefit from strategic alliances is “whom to ally with”. Typically, each party seeks a partner whose attributes reinforce their own. This paper explains that the interaction of these preferences leads to a market-wide sorting of alliance partners. Since the value created by an alliance is driven by attributes of all alliance partners, firms cannot successfully bid financial resources to get access to their most preferred partner. Instead, managers need to understand the market-wide competition and invest in the “right” mixture of attributes to make their firm more attractive in the market for alliance partners. Using this framework, we highlight firms' sizes and research capabilities as two drivers of partner selection and sorting in bio-pharmaceutical research alliances.
