ANALYSIS OF ORGANIZATIONAL DECISION-MAKING FROM COST-TIME PERFORMANCE PERSPECTIVES: DEVELOPMENT OF AN ACTIVE GARBAGE CAN MODEL USING MULTI-AGENT SIMULATION

Abstract

This study extends the Garbage Can Model, a model of organizational decision-making, into a multi-agent simulation to analyze organizational performance from both decision-making tendencies and cost/time perspectives, ultimately deriving practical implications. The Garbage Can Model posits that organizational decisions result from the random convergence of participants, problems, solutions, and choice opportunities, often leading to outcomes such as oversight or flight rather than direct problem resolution. However, previous criticisms argue that the model's simulation results are questionable and do not adequately represent real-world organizational decision-making. Building on previous research, this study develops a refined version of the model by addressing these criticisms and adapting it for multi-agent simulation. Simulation results using the newly developed Active Garbage Can Model reveal key insights into organizational performance under varying conditions of organizational size, managerial range of decision-maker, and organizational structure. The results indicate that in small organizations, structure enhances efficiency, while a narrower managerial range of decision-maker leads to greater efficiency. Whereas, expanding managerial range of decision-maker significantly reduces efficiency. Moreover, in large organizations where both size and managerial range of the decision-maker are expanded, structural factors further reduce efficiency.