Agents offer a new and exciting way of understanding the world of work. In this paper we describe the development of agent-based simulation models, designed to help toudunderstand the relationship between people management practices and retail performance. We report on the current development of our simulation models which includes new features concerning the evolution of customers over time. To test the features we have conducted a series of experiments dealing with customer pool sizes,udstandard and noise reduction modes, and the spread of customers’ word of mouth. To validate and evaluate our model, we introduce new performance measure specific toudretail operations. We show that by varying different parameters in our model we can simulate a range of customer experiences leading to significant differences inudperformance measures. Ultimately, we are interested in better understanding the impact of changes in staff behavior due to changes in store management practices.udOur multi-disciplinary research team draws upon expertise from work psychologists and computer scientists. Despite the fact we are working within a relatively novel andudcomplex domain, it is clear that intelligent agents offer potential for fostering sustainable organizational capabilities in the future.
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