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Incomplete incentive contracts in complex task environments: an agent-based simulation with minimal intelligence agents
Journal of Economic Interaction and Coordination ( IF 1.237 ) Pub Date : 2022-06-27 , DOI: 10.1007/s11403-022-00357-6
Friederike Wall

Incentive contracts often do not govern all task elements for which an employee is responsible. Prior research, particularly in the tradition of principal-agent theory, has studied incomplete incentive contracts as multi-task problems focusing on how to motivate the employee to incur effort for a not-contracted task element. Thus, emphasis is on the “vertical” relation between superior and subordinate, where both are modeled as gifted economic actors. This paper takes another perspective focusing on the “horizontal” interferences of—contracted and not-contracted—task elements across various employees in an organization and, hence, on the complexity of an organization’s task environment. In order to disentangle the interactions among tasks from agents’ behavior, the paper pursues a minimal intelligence approach. An agent-based simulation model based on the framework of NK fitness landscapes is employed. In the simulation experiments, artificial organizations search for superior performance, and the experiments control for the complexity of the task environment and the level of contractual incompleteness. The results suggest that the complexity of the task environment in terms of interactions among task elements may considerably shape the effects of incomplete incentive contracts. In particular, the results indicate that moderate incompleteness of incentive contracts may be beneficial with respect to organizational performance when intra-organizational complexity is high. This is caused by stabilization of search resulting from incomplete contracts. Moreover, interactions may induce that the not-contracted task elements could serve as means objectives, i.e., contributing to achieving contracted task elements.



中文翻译:

复杂任务环境中的不完全激励合约:具有最少智能代理的基于代理的模拟

激励合同通常并不管理员工负责的所有任务要素。先前的研究,特别是在委托代理理论的传统中,将不完全激励合同研究为多任务问题,重点关注如何激励员工为非合同任务要素付出努力。因此,重点是上级和下级之间的“垂直”关系,两者都被建模为有天赋的经济参与者。本文采用另一个视角,关注组织中不同员工之间的“水平”干扰——承包和非承包——任务元素,因此,组织任务环境的复杂性。为了将任务之间的交互与智能体的行为分开,本文采用最小智能方法。采用基于 NK 健身景观框架的基于代理的仿真模型。在模拟实验中,人工组织寻求优越的性能,实验控制了任务环境的复杂性和合同不完整性的程度。结果表明,任务环境在任务要素之间相互作用方面的复杂性可能会极大地影响不完全激励合同的影响。特别是,结果表明,当组织内部复杂性很高时,激励合同的适度不完整性可能对组织绩效有益。这是由于不完整的合同导致的搜索稳定造成的。此外,交互可能会导致未签约的任务元素可以作为手段目标,即。

更新日期:2022-06-28
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