Modeling New Product Diffusion in a Competitive Market Using Agent-Based Simulation

The prediction of the results of introducing a new product into the market is one of the vital issues facing the organization's executives before investing in marketing activities. The impact of various factors on the market, as well as the specific characteristics of the market, depending on the region and its product type, has made it difficult to predict market behavior. In Iran, retailers are effective players, especially in the FMCG market. This paper aims to suggest a model for the marketing managers to predict the result of their new product lunch to market considering their special market attributes. Agent-based modeling, as a tool for modeling complicated systems, can be helpful for simulating real-world conditions. In the present paper, agent-based modeling is used to model the market, including retailers and consumers with particular profit functions, and two producers compete with each to maximize their profit. The introduction of a new soft drink in the Iranian market over three years is considered as a case study. The results of policy implementation were evaluated using the decision support system developed in this study. The user interface of this system has been developed with Matlab software, and its model core with SQL Server. The results show that paying attention to the needs of retailers and consumers simultaneously, and changing policies based on long-term profitability, create success in the new product diffusion process. The analysis of a competitive environment, the role of retailers in the market, and the repeat purchase behavior of consumers are instructive. These can provide valuable points for marketing managers to customize the model to their special market and product.