Demand Management in E-Fulfillment

Abstract

Internet retailers are in a unique position to adjust, in real-time, the product and service offering to the customer and to change the corresponding prices. Although this flexibility provides a vast potential for demand management to enhance profitability, standard practices and models to support the decision makers are lacking as of to date. This thesis aims to contribute to closing this gap by systematically investigating demand management approaches in e-fulfillment. We identify relevant novel planning issues through an in-depth case study at a Dutch e-grocer. We focus particularly on attended home delivery, where the Internet retailer applies delivery time slots to coordinate the reception of the purchased goods with the customer. The main levers to manage customer demand in such an environment are the offered time slots and the corresponding delivery fees. The Internet retailer may apply both of these options, slotting and pricing, at different moments in the sales process, either off-line prior to the actual order in-take or real-time as demand unfolds. The thesis presents several decision-support models for time slot management, both forecast-based and in real-time. The computational studies on real-life data demonstrate the viability and the merits of these methods. The results show that a more dynamic and differentiated demand management approach can lead to considerable cost savings and revenue gains.

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