An Agent-Based Simulation of In-Store Customer Experiences

TL;DR

This paper presents an agent-based simulation model to analyze how human resource practices influence retail productivity, incorporating evolving customer behaviors and communication effects, with initial experimental insights.

Contribution

It introduces a novel agent-based model with features on customer evolution and communication, advancing understanding of retail dynamics.

Findings

Customer pool size impacts retail performance

Noise reduction modes influence customer behavior

Word of mouth affects customer evolution

Abstract

Agent-based modelling and simulation offers a new and exciting way of understanding the world of work. In this paper we describe the development of an agent-based simulation model, designed to help to understand the relationship between human resource management practices and retail productivity. We report on the current development of our simulation model which includes new features concerning the evolution of customers over time. To test some of these features we have conducted a series of experiments dealing with customer pool sizes, standard and noise reduction modes, and the spread of the word of mouth. Our multi-disciplinary research team draws upon expertise from work psychologists and computer scientists. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents offer potential for fostering sustainable organisational capabilities in the future.