Agent-Based Simulation of Customer Satisfaction : A Systematic Review

Abstract

Mathematical modelling of customer satisfaction has attracted strong academic interest over the centuries. Traditional satisfaction models have aimed at empirical generalizations and hence describe the customers’ behaviour parsimoniously at the market level. More recently, agent-based modelling and simulation has increasingly been adopted since it operates on the individual level and, thus, can capture complex emergent phenomena highly relevant in satisfaction research. Agent-based methods have been applied in this context both as intuition aids that facilitate theory-building and as tools to analyse real-world scenarios, support management decisions and obtain policy recommendations. This review addresses both streams of research. The research critically examine the strengths and limitations of agent-based modelling in the context of customer satisfaction. The target audience of the paper includes both researchers in marketing interested in new findings from the agent-based modelling literature and researchers who intend to implement agent-based models for their own research endeavours. Accordingly, cover pivotal modelling aspects in depth (concerning, consumer behavior) and outline existing models in sufficient detail to provide a proper entry point for researchers new to the field.