Preferences and Productivity in Organizational Matching: Theory and Empirics from Internal Labor Markets
Dr. Bo Cowgill
Graduate School of Business
We study the design of managerial practices for matching workers to divisions. Our methods use both sides’ preferences to match with each other, and on the employer’s expectations about resulting productivities. Our model derives boundary conditions for when dictating assignments outperforms delegating matching preferences to worker/division preferences (and vice versa). Our model highlights the tradeoffs between the coordination benefits of dictating versus informational advantages of delegating. We then turn to a large organization’s internal labor market for empirics. We find that optimal matching is highly productive. Using the organization’s preferred metric, the optimal match is 36% more productive than randomly assigned matches within job categories. However, it achieves this through negative assortative matching, and by placing a majority of workers and managers with assignments they did not rank. By contrast, preference-based matches (using deferred acceptance) are much less productive (only 3% better than random), and feature positive assortative matching. Workers and managers are significantly more likely to be assigned to a preferred partner. We show how a novel method — integrating both firm and employees/division preferences — can improve firms’ matchmaking.