Although alliance studies have generally favored an ambidextrous approach between exploration and exploitation, they tend to overlook a firm's characteristics, its industry constraints, or the dynamic network in which the firm is embedded. This study examines the ambidexterity hypothesis and its boundary conditions with a unique research method. We not only analyze empirical data from five U.S. industries spanning eight years, but also expand theoretical insights to the network level by building a computer simulation model. Both our empirical and simulation results reveal the contingencies of the ambidexterity hypothesis in alliance formation. Our findings show that although an ambidextrous formation of alliances benefits large firms, a focused formation of either exploratory or exploitative alliances benefits small firms. In an uncertain environment an ambidextrous formation enhances firm performance but so does a focused formation in a stable environment. Finally, the simulation model demonstrates that a firm's centrality and structural hole positions in network relations can moderate the relationships between alliance formation choices and firm performance, and that the ambidexterity hypothesis may be limited to the earlier stage of the network. Our study provides critical evidence into the viability of adopting a dynamic network perspective in understanding the ambidexterity hypothesis and advancing strategic alliance research beyond static and dyadic levels.alliance formation, ambidexterity hypothesis, social networks, empirical analysis, computer simulation

What drives mergers and acquisitions (M&As) in different institutional environments? This article builds on the resource dependence perspective and argues that networks, learning, and institutions represent three building blocks that can enhance our understanding of the drivers behind M&As. Specifically, we consider firms as learning actors embedded in network relations and influenced by institutional development, and compare and contrast firms' acquisition activities across the United States and China. Our findings show that there are indeed important learning and network factors that lead to M&As. More interestingly, the impact of such learning and network factors varies sharply across countries with different market‐based institutions. Copyright © 2009 John Wiley & Sons, Ltd.

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How do small firms manage their alliance strategies with large firms? This study compares the relative impacts of exploration and exploitation alliances with large firms on small firms' valuation. Integrating the literatures on the exploration/exploitation paradigm and alliance governance, we argue that exploitation alliances with large firms will on average generate higher values for small firms than exploration alliances with large firms due to a heightened risk of appropriation in exploration alliances. However, if small firms can manage their alliances with large firms via proper alliance governance, they will increase their valuations from exploration alliances with large firms. Analyses of the U.S. biopharmaceutical industry from 1984 to 2006 largely support our hypotheses. Copyright © 2013 John Wiley & Sons, Ltd.

Acquisition research has traditionally been dominated by economic and atomistic assumptions. This study extends acquisition research by integrating behavioral learning and social network perspectives to examine the acquisitions of alliance partners. Specifically, we examine, at the dyadic level, how firms' alliance learning approaches (exploration versus exploitation) and their joint and relative embeddedness in alliance networks (joint brokerage positions and relative centrality) can interact to drive subsequent acquisitions of alliance partners. Our analyses of the U.S. computer industry support our theoretical framework, highlighting the unique and previously underexplored behavioral and relational drivers of acquisitions.

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