Emergent task allocation and incentives: an agent-based model

Abstract

In recent times, organizations have increasingly adopted structures in which decision making is distributed rather than centralized. This approach often leads to task allocation emerging from the bottom up, moving away from strict top-down control. This shift raises a key question: How can we guide this emergent task allocation to form an effective organizational structure? To address this question, this paper introduces a model of an organization where task assignment is influenced by agents acting based on either long-term or short-term motivations, facilitating a bottom-up approach. The model incorporates an incentive mechanism designed to steer the emergent task allocation process, offering rewards that range from group-based to individual-focused. The analysis reveals that when task allocation is driven by short-term objectives and aligned with specific incentive systems, it leads to improved organizational performance compared to traditional, top-down organizational designs. Furthermore, the findings suggest that the presence of group-based rewards reduces the necessity of mirroring, i.e., for a precise matching of the organizational structure to task characteristics.