We build an agent-based computational model to study how the changing number of active product variants in a two-dimensional product space affects the performance of different firm types (i.e. large-scale and small-scale enterprises). We use an alternative approach to measure product space dimensionality, considering that dimensions may be a fraction of the Euclidean measure. The results confirm that high dimensionality gives advantage to small-scale firms. Additionally, we find that large-scale firms may also benefit from initial increasing dimensionality, since it allows a small degree of product differentiation and price discrimination.