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INFORMS Philadelphia – 2015

360

TD42

42-Room 102B, CC

Patients and Practice: Using the Right Resources to

Deliver Care

Sponsor: Manufacturing & Service Oper

Mgmt/Healthcare Operations

Sponsored Session

Chair: Jonathan Helm, Indiana University Bloomington, 1309 E. Tenth

Street, Bloomington, IN, United States of America,

helmj@indiana.edu

1 - An Empirical Study of The Impact of Physician Assistants During

Critical Care Consultations

Yunchao Xu, New York University, 44W 4th St, 8-152, New York,

NY, 10012, United States of America,

yxu4@stern.nyu.edu

,

Carri Chan, Mor Armony

Trained with a broad set of clinical skills, physician assistants (PAs) can be cost-

effective alternatives to physicians in healthcare systems. However, not much is

known on the impact of PAs on patient delivery in certain settings. Using data

from a major urban hospital system, we utilize a difference-in-differences

approach to explore the effects of introducing PAs into the critical care

consultation process. One key finding is the reduction in boarding times due to

this intervention.

2 - Missed Opportunities in Preventing Hospital Readmissions:

Redesigning Post-discharge Checkup Policie

Xiang Liu, University of Michigan, 1205 Beal Ave, Ann Arbor,

MI, 48109, United States of America,

liuxiang@umich.edu,

Jonathan Helm, Ted Skolarus, Michael Hu, Mariel Lavieri

Hospital readmissions affect hundreds of thousands of patients, placing a

tremendous burden on the healthcare system. Post-discharge checkup can reduce

readmissions through early detection of conditions. Our work develops optimal

checkup plans to monitor patients following hospital discharge using methods

including phone calls and office visits. By analyzing the structure of optimal

policies, we develop checkup schedules that mitigate 32% more readmissions.

3 - Incentive-compatible Prehospital Triage in Emergency

Medical Services

Eric Webb, Graduate Student, Indiana University, 1309 E. 10th

Street, Bloomington, IN, 47405, United States of America,

ermwebb@indiana.edu,

Alex Mills

The Emergency Medical Services (EMS) system is designed to handle life-

threatening emergencies, but a large and growing number of non-emergency

patients seek healthcare through EMS. We evaluate the incentives underlying

prehospital triage, where EMS staff are allowed to identify patients that could be

safely diverted away from the hospital and toward appropriate care. Continued

transition from fee-for-service payments to bundled payments may be necessary

for prehospital triage implementation.

TD43

43-Room 103A, CC

Revenue Management with Consumer

Choice Models

Sponsor: Revenue Management and Pricing

Sponsored Session

Chair: Ruxian Wang, Johns Hopkins University, 100 International Dr,

Baltimore, MD, 21202, United States of America,

ruxian.wang@jhu.edu

1 - Dynamic Pricing for Mobile Apps

Kejia Hu, Kellogg School of Management, Northwestern

University, 2169 Campus Drive, Evanston, IL, United States of

America,

k-hu@kellogg.northwestern.edu

, Chaitanya Bandi,

Srikanth Jagabathula

Mobile apps is special in the following aspects. It has no inventory constraint,

almost zero marginal cost and free version updates. In our research, we will

model these features and show the dynamic pricing for mobile apps.

2 - Product Line Design and Pricing under Logit Model

Anran Li, Columbia University, 345 Mudd, New York, NY, 10027,

United States of America,

al2942@columbia.edu

,

Guillermo Gallego, Jose Beltran

We study a firm who wants to design and price a set of products characterized by

a number of features where each feature has one or multiple levels. We model

consumers’ demand by a feature-level based Logit model and optimize the

assortment on the features space. We find a price independent index of each

feature level that plays a key role. This makes a greedy algorithm, derived from

the K-shortest paths algorithm, able to find an optimal K products’ configuration

in polynomial time.

3 - Optimal Pricing for a Multinomial Logit Choice Model with

Network Effects

Chenhao Du, Student, University of Minnesota, 425 13th Ave SE,

Apt. 1502, Minneapolis, MN, 55414, United States of America,

duxxx181@umn.edu,

William Cooper, Zizhuo Wang

We consider a seller’s problem of determining revenue-maximizing prices for an

assortment of products that exhibit network effects. Customers make purchase

decisions according to a modified MNL choice model. We show that the optimal

strategy is either to maintain a semblance of balanced sales among all product or

to boost the sales of exactly one product. We also show the importance of taking

the network effects into consideration.

4 - Pricing Ancillary Service Subscriptions

Ruxian Wang, Johns Hopkins University, 100 International Dr,

Baltimore, MD, 21202, United States of America,

ruxian.wang@jhu.edu

, Maqbool Dada, Ozge Sahin

We investigate customer choice behavior in the presence of main products,

ancillary services with options of pay-per-use and subscription, as well as the

outside option. Analytical results and numerical experiments show that offering

service subscriptions may result in “win-win-win”“win-win-lose”“lose-lose-win”

and other situations for the firm, competitors and customers in the monopolistic

and competitive scenarios.

TD44

44-Room 103B, CC

Recent Trends in Retailing

Sponsor: Revenue Management and Pricing

Sponsored Session

Chair: Mehmet Sekip Altug, Assistant Professor, George Washington

University, Washington, DC, United States of America,

maltug@gwu.edu

1 - Analyzing Big-Box Retailer in an Emerging Market

Mehmet Gumus, McGill University, 1001 Sherbrooke Street West,

Montreal, Canada,

mehmet.gumus@mcgill.ca

, Aditya Jain,

Saibal Ray

We consider the impact of the entry of a big-box retailer in a market dominated

by small retailers. The small retailers are characterized by local coverage of the

market, whereas the big-box retailer provides services valued by customers. Since

both types of retailers obtain supplies from a common manufacturer, big-box

retailer’s entry affects the supply conditions. Our work thus highlights roles of

direct competition as well as indirect supply side effect on small retailers and

customers.

2 - Dynamic Pricing with Customer Upgrades

Oben Ceryan, Assistant Professor, Drexel University, 3220 Market

St., Philadelphia, PA, United States of America,

oc43@drexel.edu

,

Ozge Sahin, Izak Duenyas

We study the impact of product upgrades on a firm’s pricing and replenishment

policies by considering a multiple period, two-stage model where the firm first

sets prices and replenishment levels, and after observing the demand, it decides

whether to upgrade any customers to a higher quality product. We characterize

the structure of the optimal upgrade, pricing, and replenishment policies and find

that offering upgrades assists in preserving the vertical price differentiation of the

products.

3 - Return Abuse, Countermeasures, and Privacy Concerns

Serkan M. Akturk, PhD Candidate, Texas A&M University, 4217

TAMU Wehner 320 M, College Station, TX, United States of

America,

makturk@mays.tamu.edu

, Michael Ketzenberg

This paper analytically investigates return abuse with respect to both fraudulent

and opportunistic consumer returns and potential countermeasures to deal with

them. The research also shows how those countermeasures impact a retailer’s

profitability, demand structure, and policy parameters with respect to price and

refund. To some extent, our findings contradict common suggestions in the

literature.

4 - Store-clearance or Secondary Markets? Evaluation of Inventory

Clearance Opportunities in Retailing

Mehmet Sekip Altug, Assistant Professor, George Washington

University, Washington, DC, United States of America,

maltug@gwu.edu,

Garrett Van Ryzin

One main assumption in the newsvendor model is that the salvage value is

exogenous and retailers can sell their excess stock at this fixed salvage value.

However, the salvage value of excess stock is mostly determined endogenously.

We compare consolidated secondary markets vs. store clearance with myopic and

strategic customers.

TD42