The number of instant delivery and transportation services grows rapidly with many competing companies such as Amazon Now, GrubHub, Doordash, GoPuff, MOIA, or Uber.

The service-providers respond in real time to customer demand and promise a successful service fulfillment only a short time later. To keep customers happy and to grow the customer base, reliable and punctual service is essential. This is challenging because the companies experience high uncertainty in demand. Furthermore, many of the business models partially rely on gig-economy drivers and thus experience uncertainty in the available workforce resources as well. Thus, many customers receive late services, either because demand is high or because the level of available resources is low.

In this talk, we discuss means to control both demand and resources in a way that provides punctual and cost-efficient services to many customers. For demand control, we propose sizing the service area dynamically with respect to observed and future demand. For the uncertainty in resources, we complement the gig-economy fleet with scheduled company drivers when needed. We show that our policies work and analyze the managerial implications for service providers.

Marlin Ulmer is Professor of Prescriptive Analytics at the Business Department of the Technische Universität Braunschweig in Braunschweig, Germany. He studied Mathematics in Göttingen and Swansea. His PhD thesis at TU Braunschweig focused on the interface between Management Science, Mathematics, and Computer Science. It was awarded, amongst others, by the INFORMS TSL Society and the German Operations Research Society. Marlin’s teaching and research interests comprise applications from the entire field of Urban Mobility and Logistics, Operations Research, Stochastic Optimization, Dynamic Decision Making, Approximate Dynamic Programming, and Machine Learning. He works with leading experts of these fields all over the world.

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