People are often confronted with problems whose complexity exceeds their cognitive capacities. To deal with this complexity, individuals and managers can break complex problems down into a series of subgoals. Which subgoals are most effective depends on people's cognitive constraints and the cognitive mechanisms of goal pursuit. This creates an untapped opportunity to derive practical recommendations for which subgoals managers and individuals should set from cognitive models of bounded rationality. To seize this opportunity, we apply the principle of resource-rationality to formulate a mathematically precise normative theory of (self-)management by goal-setting. We leverage this theory to computationally derive optimal subgoals from a resource-rational model of human goal pursuit. Finally, we show that the resulting subgoals improve the problem-solving performance of bounded agents and human participants. This constitutes a first step towards grounding prescriptive theories of management and practical recommendations for goal-setting in computational models of the relevant psychological processes and cognitive limitations.
翻译:处理这种复杂问题,个人和管理人员可以将复杂的问题分为一系列次级目标,哪些次级目标最有效取决于人们的认知限制和追求目标的认知机制,这为次级目标管理人员和个人提供了一个尚未利用的机会,以提出切实可行的建议,次级目标管理人员和个人应当根据界限合理性的认知模式提出这些建议。为了抓住这一机会,我们运用资源合理性原则,以制定数学精确的(自我)管理规范理论,通过目标设定。我们利用这一理论从追求人类目标的资源合理模式中计算出最佳次级目标。最后,我们表明,由此产生的次级目标改善了受约束的代理人和人类参与者解决问题的绩效。这是朝着在相关心理过程和认知限制的计算模型中确定目标的规范性管理理论和实践建议迈出的第一步。