Complex Strategic Choices: A New Approach and Application to Foreign Firm Agglomeration. (17th July 2017) - Wu, Zheying; Salomon, Robert; Martin, Xavier
Abstract : Research summary: In this study, we introduce a new statistical technique to the field of strategy that accounts for complex interrelated decisions. The technique is meant for situations in which one strategic decision depends critically upon another—e.g., where companies must commit to one decision before making another. We demonstrate the value of the technique in the context of companies choosing countries in which to invest, followed by areas within those countries in which to locate their facilities. We then describe the generic benefits of the statistical technique, offer guidance for how to use it, and provide the programming code so that others can implement it. We explain how the technique is particularly well suited to problems in which companies must decide between multiple options and the sample size is small relative to the number of initial options. Managerial summary: Research in strategy and international business has increasingly adopted two‐stage models to account for endogeneity. Established approaches, however, deal most effectively with problems characterized by binary first‐stage models. We introduce an alternative that allows for multiple choices in the first stage. We use the technique to examine the agglomeration patterns of foreign firms, while accounting for country selection. We find that, conditional on country selection, foreign firms tend to agglomerate in host countries characterized by collectivist cultures, political uncertainty, and economic uncertainty. The results imply that host country characteristics exert a strong influence on the agglomeration preferences of foreign firms. We provide guidance on when to use the empirical estimation technique and furnish details of the estimation procedure so that others can apply the technique to a broader class of selection problems. Copyright © 2017 Strategic Management Society.