This page is based on the work:
Yang, X., Strauss, A.K., Eglese, R, and Currie, C. Choice-Based Demand Management and Vehicle Routing in E-fulfilment.
Download latest version of September 2012.
Attended home delivery services face the challenge of providing narrow delivery time slots to ensure customer satisfaction, whilst keeping the significant delivery cost under control. To that end, the firm can try to influence customers when they are booking their delivery time slot so as to steer them towards choosing slots that are expected to result in cost-effective schedules.
We estimate a multinominal logit customer choice model from historic booking data and demonstrate that this can be calibrated well on a genuine data set from a major e-grocer in the UK. We propose dynamic pricing policies based on this choice model to determine which and how much incentive (discount or charge) to offer for which time slot at the time a customer intends to make a booking. A crucial role in these dynamic pricing problems is played by the also dynamically estimated delivery cost; we show in a simulation study based on real data that anticipating the likely future delivery cost of an additional order in a given location can lead to significantly increased profit of on average 3.8% as compared to typical industry practice, namely using two-tier static delivery prices that only depend on whether or not the order value exceed a certain threshold.
In an industry that operates on very small margins (e.g. Ocado reported operating margins of 0.55% in H1 2012), this profit potential is remarkable.