2016 INFORMS Annual Meeting Program

465 / 561

INFORMS Nashville – 2016
465
4 - Discretionary Service Line Design With
Heterogeneous Customers
Cuihong Li, University of Connecticut, ,
Laurens G Debo
We study discretionary service line design facing heterogeneous customers. For
discretionary services, the longer the service time, the higher is the quality of the
service. In the presence of variability, longer service times also create more
congestion. Hence, a service firm needs to trade off congestion costs with value
creation. We find that self-selection of heterogeneous customer might lead to
distortion of the high-quality service, contrary to the classic product line design
result of Moorthy (1984).
WD31
202C-MCC
Services in the Sharing Economy
Sponsored: Manufacturing & Service Oper Mgmt, Service
Operations
Sponsored Session
Chair: Laurens Debo, Dartmouth College, Tuck School of Business,
Hanover, NH, 03755, United States,
Co-Chair: Luyi Yang, University of Chicago, Booth School of Business,
Chicago, IL, 60637, United States,
1 - When Is Capacity Trading Among Consumers A Win-win To
Consumers And Service Providers?
Behrooz Pourghannad, University of Minnesota, Minneapolis, MN,
United States, , Saif Benjaafar, Jian-Ya Ding
We study a setting where consumers can trade among themselves unused
capacity they purchased from a service provider (e.g., excess data on a mobile
data plan). We examine implications for service provider profits and consumer
surplus.
2 - Allocating Capacity In Bikeshare Systems
Daniel Freund, Cornell University, Ithaca, NY, 14850, United
States, , Shane Henderson, David B Shmoys
A Bikeshare system (BSS) allows users to rent and return a bike at any station
within the system. The amount of usage data BSSs collect has increased greatly in
the last decade, allowing us to develop data-driven methods to support their
operations. In this talk we extend a continuous-time Markov chain model to
allocate docks within a BSS so as to minimize the expected number of out-of-
stock (OOS) events. We compute that quantity & efficiently find the allocations of
bikes and docks that minimize it both over a finite horizon & at steady-state. Our
work is used by NYC Bikeshare to redistribute bikes & (re-)allocate docks.
3 - Skill Screening In Large-scale Service Marketplaces
Eren Basar Cil, University of Oregon, ,
Gad Allon, Achal Bassamboo
We consider a large-scale service marketplace where the moderating firm can run
two skills tests on agents to assess if their skills are above certain thresholds. Our
main objective is to evaluate the effectiveness of skill screening as a revenue
maximization tool. We find that skill screening leads to negligible revenue
improvements in marketplaces where agent skills are highly compatible. As the
compatibility of agent skills weakens, we show that the firm starts to experience
as much as 25% improvement in revenue from skill screening. Apparently, the
firm can reap the most of these substantial benefits when it runs only one test.
WD32
203A-MCC
Risk Analysis
Contributed Session
Chair: David S Kim, Professor, Oregon State University, 204 Rogers
Hall, School of Mech., Industrial and Mfg Eng., Corvallis, OR, 97331-
2407, United States,
1 - Uncertainty, Entropy, And Ambiguity As Risk Measures In
Decision Modeling For Portfolio Optimization
David F. Rogers, University of Cincinnati, Department of
Operations, Business Analytics, and Information Systems,
Carl H. Lindner College of Business, 2925 Campus Green Drive,
Cincinnati, OH, 45221-0130, United States, ,
George G Polak
For a portfolio optimization setting, the risk from uncertain outcomes is typically
considered. Other risk measures, including the choice of how to best employ the
state-space probabilities and how to consider alternative probability functions are
also important. Information entropy is incorporated for measuring the risk
associated with the stratification of state-space probabilities resulting in convex
integer optimization models with entropy employed as either the objective to
minimize or as a constraint with a maximum return objective.
2 - Quantifying The Contribution Of Seawalls To Mitigating
Tsunami Damage
Tom M Logan, PhD Pre-Candidate, University of Michigan,
1205 Beal Avenue, Ann Arbor, MI, 48109, United States,
Jeremy D Bricker, Seth Guikema
Seawalls are commonly used to defend against tsunamis, making it is essential we
understand whether they truly mitigate damage. The north-east of Japan has
been stuck by four tsunamis in the past 110 years. A model combining a cellular
automaton and hydrodynamic models simulates how land development
hypothetically changes with time and under different seawall height options. The
insights will indicate which scenarios they provide physical protections and which
scenarios require alternative action.
3 - Sample Sut Of Sample Inference Based On Wasserstein Distance
Yang Kang, PhD Candidate, Columbia University, 1255th
Amsterdam Ave SSW, RM901, New York, NY, 10027, United
States, , Jose Blanchet
We present a novel inference approach which we call Sample Out-of-Sample (or
SOS) inference. Our motivation is to propose a method which is well suited for
data-driven stress testing, in which emphasis is placed on measuring the impact of
(plausible) out-of-sample scenarios on a given performance measure of interest
(such as a financial loss). The methodology is inspired by Empirical Likelihood
(EL), but we optimize the empirical Wasserstein distance (instead of the empirical
likelihood) induced by observations. From a methodological standpoint, our
analysis of the asymptotic behavior of the induced Wasserstein-distance profile
function shows dramatic qualitative differences relative to EL.
4 - Destructive Testing Gauge Capability Analysis
David S Kim, Professor, Oregon State University, 204 Rogers Hall,
School of Mech., Industrial and Mfg Eng., Corvallis, OR, 97331-
2407, United States, , Xinyu Luo
This research examines the current state-of-the-art in gauge capability analysis for
destructive testing. Results are then presented that extend the specific destructive
testing situations where gauge repeatability can be estimated.
WD35
205A-MCC
Retail Analytics & Optimization
Sponsored: Manufacturing & Service Oper Mgmt, Service
Operations
Sponsored Session
Chair: Tulay Flamand, University of Massachusetts Amherst, Isenberg
School of Management, Amherst, MA, 01003, United States,
1 - Store-wide Shelf Space Analytics To Optimize Impulse Buying
Tulay Flamand, University of Massachusetts Amherst, Amherst,
MA, United States, , Ahmed Ghoniem,
Bacel Maddah
We address a store-wide retail shelf space allocation problem with the objective of
promoting impulse buying. Basket data analysis is conducted using real data in
order to calibrate a predictive model of in-store traffic. This predictive model is
then embedded in a non-linear mixed-integer model in order to prescribe shelf
space solutions that maximize impulse buying.
2 - Pricing And Inventory Decisions Of an Assortment Under Equal
Profit Margins
Bacel Maddah, American University of Beirut, Bliss Street,
Beirut, Lebanon, , Hussein Tarhini,
Melanie Jabbour
We consider the interdependent decisions on inventory and pricing of
substitutable products in an assortment. Within a newsvendor-type supply
setting, we analyze the joint pricing and inventory decision problem of the
retailer under the assumption that all products have equal profit margins. We
derive several concavity and monotinicity results under two common consumer
choice models, the logit and the nested-logit. We also present an extensive
numerical study testifying to the near-optimlity of equal-margin pricing.
WD35