Agent-based simulation of pricing strategy for agri-products considering customer preference

Agri-products typically have short life cycles and are perishable. The price of perishable goods is influenced by many factors. Customers in a market have different preferences with regard to price, the quality of the product and the brand. Though studies on pricing strategies that consider customer preference are rare, this paper addresses the problem of optimal pricing strategy for retailers considering customer preferences. Traditional mathematical methods cannot adequately describe the complexities of customer preference. Due to these complexities, this paper proposes an agent-based simulation model composed of six retailers and hundreds of customers, each with personal preferences. The different retailers set prices according to freshness, inventory, cost and other factors. Due to the perishable nature of the products considered, this paper proposes a new categorising price strategy that sets prices according to different degrees of treatments. By comparing the final profit of all retailers at the end of a simulation, the categorising price strategy is demonstrated to be the optimal strategy if customers with different preferences are randomly distributed. Furthermore, based on the model, the paper studies how optimal strategies are influenced by the proportion of customers with different preferences.