Motivated by the real-world problem of a logistics company, this paper proposes a novel distribution-free prescriptive analytics approach – termed kernelized ERM – to solve a complex two-stage capacity planning problem with multivariate demand and vector-valued capacity decisions and...

Motivated by the work with a leading maintenance service provider in the aviationindustry, this paper examines novel data-driven approaches to solving a certaintype of capacity-sizing problem—the multi-shift staffing problem—with uncertain,time varying arrival rates and patient "customers"...

Motivated by the overwhelming success of gradient boosting approaches in machine learning and driven by the need for explainable prescriptive analytics approaches in operations management (OM), we propose an explainable prescriptive analytics approach to solving complex OM problems: subgradient...

We study the risk attitudes of an important segment of the economy: managers. We conduct artefactual field experiments with 130 managers from 12 industrial companies. Our analysis is particularly careful to evaluate alternative models of decision-making under risk. In general, we find that the...

Purpose – The purpose of this paper is to investigate the potential of a new convenience‐enhancing service at the interface between retailers and consumers: time‐based delivery of parcels. The service allows consumers to choose a preferred time slot for a parcel to be delivered. This...