Understanding Retail Productivity by Simulating Management Practise

TL;DR

This paper develops an agent-based simulation to explore how human resource management practices influence retail productivity, incorporating realistic customer behavior and footfall patterns based on case study data.

Contribution

It introduces a novel retail simulation model with enhanced features for realistic customer and footfall data, enabling analysis of management practices' impact.

Findings

Simulation incorporates detailed customer behavior

Realistic footfall and customer evolution data included

Supports analysis of management practices effects

Abstract

Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. Our research so far has led us to conduct case study work with a top ten UK retailer, collecting data in four departments in two stores. Based on our case study data we have built and tested a first version of a department store simulator. In this paper we will report on the current development of our simulator which includes new features concerning more realistic data on the pattern of footfall during the day and the week, a more differentiated view of customers, and the evolution of customers over time. This allows us to investigate more complex scenarios and to analyze the impact of various management practices.