Preferences and Productivity in Organizational Matching: Theory and Empirics from Internal Labor Markets

Bo Cowgill, Jonathan Davis, B. Montagnes, P. Perkowski
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引用次数: 3

Abstract

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.
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组织匹配中的偏好与生产率:来自内部劳动力市场的理论与实证
我们研究将工人与部门相匹配的管理实践设计。我们的方法使用双方的偏好来匹配对方,以及雇主对最终生产力的期望。我们的模型推导出边界条件,说明什么时候指定任务优于将匹配偏好委托给工人/部门偏好(反之亦然)。我们的模型强调了指令的协调效益与委托的信息优势之间的权衡。然后,我们转向一个大型组织的内部劳动力市场的经验。我们发现最优匹配是高效的。使用组织的首选指标,最佳匹配比在工作类别中随机分配匹配的效率高36%。然而,它通过负分类匹配来实现这一目标,并通过将大多数工人和经理分配给他们没有排名的任务。相比之下,基于偏好的匹配(使用延迟接受)的效率要低得多(只比随机匹配好3%),并且具有积极的分类匹配。员工和管理人员更有可能被分配给自己喜欢的伴侣。我们展示了一种新颖的方法——整合公司和员工/部门偏好——如何改善公司的配对。
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