Incorporating Neuroscience Data into Agent-Based Simulation Models of Buyer Behavior

Abstract

Purpose: The article aims to analyze the possibility of using various cognitive neuroscience techniques when building the agent model of buyer behavior and propose an experimental procedure for obtaining qualitative data based on the triangulation of methods. Design/Methodology/Approach: The proposed approach combines agent-based simulation with cognitive neuroscience techniques at the stage of designing the characteristics and behavior rules of agents-consumers. Findings: The consumer’s purchasing behavior is determined by the compilation of the influence of environmental factors and marketing stimuli as well as by his personality traits. Due to the necessity to consider all these elements when mapping the consumer-agent characteristics and decision rules, traditional methods of data collection may not be sufficient. In such a situation, cognitive neuroscience techniques can become a source of additional information, allowing to take into account the influence of emotions or cognitive abilities on one’s decisions. To make it possible, it is necessary to conduct experiments with the use of neuroscience research tools (e.g., EEG, GSR, HR etc.) aimed at detecting emotional and cognitive states during exposure to an advertisement of a specific product. The neurophysiological data collected during the experiments allow for a more accurate estimation of the qualitative parameters describing consumer behavior rules. Practical Implications: The proposed concept allows for a more accurate representation of agents-consumers’ features and decision rules. Consequently, the agent-based model more reliably reflects reality, and thus the results obtained during model simulation are more valuable and can be the basis for formulating marketing plans. Originality/Value: The proposed approach enriches the methodology of data collection and estimation of qualitative parameters in building agent models of buyer behavior.