Abstract
Facing such issues as demand uncertainty and in- and cross-channel competition, managers of today's retail chains are keen to find optimal strategies that help their firms to adapt to the increasingly competitive business environment. To help retail managers to address their challenges, we propose in this paper an agent-based retail model (ARM), grounded in complex adaptive systems, which comprises three types of agents, namely suppliers, retailers, and consumers. We derive the agents' optimal behaviours in response to competition by evaluating the evolutionary behaviour of the ARM using optimisation methods and genetic algorithm. We find that consumers' ability to collect pricing information has a significant effect on the degree of competition in retail chains. In addition, we find that the everyday low price (EDLP) strategy emerges from the evolutionary behaviour of the ARM as the dominant pricing strategy in multi-product retail chains.
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