Self-organizing behavior in collective choice models: laboratory experiments

Abstract

Purpose – The purpose of this paper is to consider queuing systems where captive repeat customers select a service facility each period. Are people in such a distributed system, with limited information diffusion, able to approach optimal system performance? How are queues formed? How do people decide which queue to join based on past experience? The authors explore these questions, investigating the effect of information availability, as well as the effect of heterogeneous facility sizes, at the macro (system) and micro (individual performance) levels. Design/methodology/approach – Experimental economics, using a queuing experiment. Findings – The authors find little behavioural difference at the aggregate level, but observe significant variations at the individual level. This leads the authors to the conclusion that it is not sufficient to evaluate system performance by observing average customer allocation and sojourn times at the different facilities; one also needs to consider the individuals’ performance to understand how well the chosen design works. The authors also observe that better information diffusion does not necessarily improve system performance. Practical/implications – Evaluating system performance based on aggregate behaviour can be misleading; however, this is how many systems are evaluated in practice, when only aggregate performance measures are available. This can lead to suboptimal system designs. Originality/value – There has been little theoretical or empirical work on queuing systems with captive repeat customers. This study contributes to the understanding of decision making in such systems, using laboratory experiments based on the cellular automata approach, but with all agents replaced by humans.