Agent-based Simulation for Convenient Store’s Promotion Strategy Selection

Nowadays, convenience store becomes more important to urban life. It is also a competitive industry for retailers who would like to gain attention from customers and grow their profit. To achieve their goals, doing promotion is a way to go. However, promotion has two sides where the gain is also coming with the possibility of loss, so a thoughtful decision is concerned when doing the promotion. This study aims to develop agent-based simulation, an approach to deal with complex and high-dimension problems, to find how each strategy works on different price elasticities for strategic insights for the company’s future planning. The agent-based simulation is able to reach many possibilities of combinations between strategy and price elasticity instead of testing or gathering data in the real world. To achieve our purpose, we vary strategies while fixing the price elasticity and see how customers react in each situation. The customer’s decision is initially based two factors (advertisement effectiveness, and word of mouth), and then it is based on price reduction rate when they come to the store. The strategy is designed on two dimensions, percentage of price reduction and frequency of the promotion. The result shows that different strategies work on different price elasticity values where high price reduction rate strategy works well on high price elasticity, and vice versa. This study provides an insight about promotional strategy selection and future vision for a new method to approach complex problems.