Modeling managerial search behavior based on Simon’s concept of satisficing

Abstract Computational models of managerial search often build on backward-looking based hill-climbing algorithms. Regardless its prevalence, there is some evidence that this family algorithms does not universally represent managers’ behavior. Against background, the paper proposes an alternative algorithm captures key elements Simon’s concept satisficing which received considerable support in behavioral experiments. The contrasts satisficing-based to two variants agent-based model a simple decision-making organization. builds framework NK fitness landscapes allows controlling for complexity decision problem be solved. results suggest model’s behavior may remarkably differ depending whether or serves as algorithmic representation decision-makers’ search. Moreover, with algorithm, indicate oscillating aspiration levels, even negative, and intense—and potentially destabilizing—search activities when intra-organizational increases. Findings shed new light prior computational organizations point avenues future research.