  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 to understand 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, standard and noise reduction
modes, and the spread of customers' word of mouth. To validate and evaluate our
model, we introduce new performance measure specific to retail operations. We
show that by varying different parameters in our model we can simulate a range
of customer experiences leading to significant differences in performance
measures. Ultimately, we are interested in better understanding the impact of
changes in staff behavior due to changes in store management practices. 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 organizational capabilities in the future.
