Operational Strategies for On-demand Personal Shopper Services

Inspired by several recent startups, we study an on-demand delivery service that lets customers shop online for products from a number of brick and mortar stores. The customer orders are fulfilled by a fleet of personal shoppers who are responsible for both the shopping of orders at the stores and the delivery of these to customer locations. The operation of such a service requires to dynamically manage new requests, coordinate a fleet of shoppers, schedule shopping operations at stores, and execute deliveries to customers on time.

Our work presents three operational strategies, each requiring different levels of shopper flexibility and implementation complexity. We quantify the performance of each strategy in a vast family of computational experiments. Also, the performance of this on-demand shopping service is compared to a setting in which customers travel to stores to shop themselves. Our numerical experiments show that there are significant savings in resources spent in shopping (up to 55.2%) when this activity is outsourced.