Interactive bundle pricing strategy for online pharmacies

Online retail pharmacies usually price their products differently from traditional drugstores. Based on real-time consumer behaviors, this paper proposes a dynamic bundle pricing strategy to maximize the pharmacy's profit. Given free shipping thresholds and consumer budgets, we propose a mixed-integer nonlinear programming model and a heuristic to sequentially price customized bundles. We further conduct a numerical study using the data from a leading e-pharmacy in China. Our computational results indicate that the proposed model not only improves the e-pharmacy's profit by attracting more customers but noticeably contributes to consumer surplus. Through sensitivity analysis, our model is proved to be robust under various scenarios.