Strategies for sales Using Agent-Based Simulation of Behavioral Consumers.
The aim of this project simulate sales based on the utility function assigned to each agent. An agents purchase decision of a product is determined by several factors such as innovation, price etc and by the influnce of adjacent agents. Each factors are assigned weights unique to each agent which when summed up are equal to 1. Multiple products are assigned values to each factors (the highest value is 1 with the rest normalized by dividing with the highest value). A social network is created using an adjacency matrix. The degree for each nodes are assigned using a power law distribution. Based on the degree assigned the agents are further divided into Innovators, early adopters, Early majority, Late majority and Laggards. The simulation begins by introducing agents who are ready for adoption in the social network. Different sales startegies are siimulated to forecast the mastket share by the end of simulation.