Incentive rate determination in viral marketing

In viral marketing campaigns, incentivized consumers can act as sales agents by sharing information. In this study, we investigate the problem of incentive rate determination over a network of consumers to maximize the profit of a single good by a monopolist. For this purpose, we develop an epidemic spreading model to explore the dynamics of a viral marketing campaign under network externalities and incentivized individuals. We will examine two cases of homogeneous and heterogeneous incentive rates. In each case, we derive an N-intertwined dynamics model and obtain the existence and stability conditions of a trade-free or an endemic equilibrium. By treating the incentive as a control parameter, we investigate the problem of maximizing the monopolist’s profit by formulating two nonlinear programming models. In the case of homogeneous incentive rates, results show that the optimal incentive is determined by devising a balance between the consumers’ states in the Markov process. In the heterogeneous case, it is observed that despite the existence of a strong correlation with different centrality measures, the optimal incentive allocation cannot be solely determined by centrality measures.