This paper addresses the call center staffing problem. We present a novel prescriptive staffing approach that minimizes the human labor cost and the cost for calls that were abandoned due to excessive waiting times. Our approach is novel in that it determines a prescriptive model based on the...

We investigate the data-driven newsvendor problem when one has n observations of p features related to the demand as well as historical demand data. Rather than a two-step process of first estimating a demand distribution then optimizing for the optimal order quantity, we propose solving the...

We analyze the performance drivers for data-driven inventory management in a Newsvendor setting with nonstationary demand. For this, we study two novel approaches which are based on machine learning techniques (linear quantile regression and tree-based regression, respectively) and which use...

We analyze two fundamentally different concepts to considering data for planning decisions using the example of a newsvendor problem in which observable features drive variations in demand.Our work contributes to the extant literature in two ways. First, we develop a novel joint...

We consider a seller who can dynamically adjust the price of a product at the individual customer level, by utilizing information about customers' characteristics encoded as a d-dimensional feature vector. We assume a personalized demand model, parameters of which depend on s out of the d...

Problem definition: We study the practice-motivated problem of dynamically procuring a new, short life-cycle product under demand uncertainty. The firm does not know the demand for the new product but has data on similar products sold in the past, including demand histories and covariate...

We revisit the classical dynamic inventory management problem of Scarf (1959) from the perspective of a decision-maker who has n historical selling seasons of data and must make ordering decisions for the upcoming season. We develop a nonparametric estimation procedure for the (S, s) policy that...

Based on Alibaba's renowned "green" initiative, the Ant Forest program, we develop a novel measure to reveal an individual investor's nonpecuniary green preference and link it to an individual's investment actions. We present compelling evidence that supports nonfinancial incentives for...