Strategic Organization Design unit and Danish Institute for Advanced Study, University of Southern Denmark, Odense, Denmark.
Department of Management, Ca' Foscari University of Venice, Venice, Italy.
Sci Rep. 2018 Oct 25;8(1):15782. doi: 10.1038/s41598-018-34128-w.
Human organizations are commonly characterized by a hierarchical chain of command that facilitates division of labor and integration of effort. Higher-level employees set the strategic frame that constrains lower-level employees who carry out the detailed operations serving to implement the strategy. Typically, strategy and operational decisions are carried out by different individuals that act over different timescales and rely on different kinds of information. We hypothesize that when such decision processes are hierarchically distributed among different individuals, they produce highly heterogeneous and strongly path-dependent joint learning dynamics. To investigate this, we design laboratory experiments of human dyads facing repeated joint tasks, in which one individual is assigned the role of carrying out strategy decisions and the other operational ones. The experimental behavior generates a puzzling bimodal performance distribution-some pairs learn, some fail to learn after a few periods. We also develop a computational model that mirrors the experimental settings and predicts the heterogeneity of performance by human dyads. Comparison of experimental and simulation data suggests that self-reinforcing dynamics arising from initial choices are sufficient to explain the performance heterogeneity observed experimentally.
人类组织通常具有等级指挥链，这有助于分工和努力的整合。高层员工制定战略框架，限制执行旨在实施战略的详细操作的低层员工。通常，战略和运营决策由不同的个体执行，他们在不同的时间范围内行动，并依赖不同类型的信息。我们假设，当这些决策过程在不同的个体之间分层分配时，它们会产生高度异质且强烈依赖路径的联合学习动态。为了研究这一点，我们设计了人类对偶面临重复联合任务的实验室实验，其中一个个体被分配执行战略决策的角色，另一个执行操作决策的角色。实验行为产生了令人费解的双峰表现分布——一些对偶在几个周期后学习，而一些对偶则无法学习。我们还开发了一个计算模型，该模型反映了实验设置，并通过人类对偶预测了性能的异质性。实验数据和模拟数据的比较表明，来自初始选择的自我强化动态足以解释实验中观察到的性能异质性。
