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INFORMS Philadelphia – 2015

466

WD40

40- Room 101, CC

Operations Management/Marketing Interface III

Contributed Session

Chair: Ashkan Negahban, Auburn University, 3301 Shelby Center,

Auburn, AL, 36849, United States of America,

anegahban@auburn.edu

1 - Fulfillment Service in Online Marketplaces

Wenjing Shen, Drexel University, 3220 Market Street,

Philadelphia, PA, 19104, United States of America,

ws84@drexel.edu,

Gangshu Cai, Xiangfeng Chen

Dominant online retailers,such as

Amazon.com

and

Sears.com,

allow small

retailers to sell on their online marketplaces and offer fulfillment service to handle

the order fulfillment activities for small retailers. In exchange, small retailers pay a

fulfillment fee per unit of sales. In this paper,we investigate the benefit of such

fulfillment programs and study the optimal fulfillment fees for the dominant

retailer.

2 - Try Before You Buy Pricing: Should Rental Fees Apply

to Purchases?

Monire Jalili, University of Oregon, 1208 University of Oregon,

Eugene, OR, United States of America,

mjalili@uoregon.edu

,

Michael Pangburn

When a product has uncertain value or is used repeatedly over time, customers

may opt to rent before purchase. Some sellers entice purchase conversions by

offering part of a paid rental price as a subsequent discount. Other sellers offer no

such credit. We analyze the optimal pricing and discount policy for a monopolist

selling to a market of consumers facing uncertain product value, and derive the

conditions under which sellers should optimally apply some of the rental price

towards a purchase.

3 - Responding to Forecasting Errors for New Products:

An Agent-based Simulation Approach

Ashkan Negahban, Auburn University, 3301 Shelby Center,

Auburn, AL, 36849, United States of America,

anegahban@auburn.edu

, Jeffrey S. Smith

Many real-world examples show that even companies with significant experience

in successful product launches have faced huge financial losses due to incorrect

demand forecasts for their new products. We consider the case where the demand

for the new product grows beyond expectations and use agent-based simulation

to evaluate different after-the-fact reactive strategies including capacity

expansion, viral marketing, and sales control to reduce potential losses under

different market dynamics.

WD41

41-Room 102A, CC

Scheduling in Healthcare Operations

Sponsor: Manufacturing & Service Oper

Mgmt/Healthcare Operations

Sponsored Session

Chair: Shrutivandana Sharma, Singapore University of Technology and

Design, 8 Somapah Road, Singapore, 487372, Singapore,

shrutivandana@sutd.edu.sg

Co-Chair: Hossein Abouee Mehrizi, University of Waterloo, 200

University Avenue West, Department of Management Sciences,

waterloo, ON, N2L 3G1, Canada,

haboueemehrizi@uwaterloo.ca

1 - Long Term Surgery Planning and Scheduling

Maya Bam, University of Michigan, 1205 Beal Ave., Ann Arbor,

MI, 48109, United States of America,

mbam@umich.edu

,

Brian Denton, Mark Van Oyen

Scheduling surgeries in a timely manner is a challenge due to competing criteria,

such as patient wait time and the availability and utilization of multiple resources

(i.e., operating room, surgical service block time). Based on collaboration with a

local hospital, we present a mixed integer programming planning model that

strives to achieve high resource utilization and provide timely access.

2 - Data-driven Patient Scheduling in Emergency Departments

Meilin Zhang, PhD Candidate, NUS Business School, BIZ 2

Building, 1 Business Link, Singapore 117592, Singapore, Si,

117592, Singapore,

214101@gmail.com

, Shuangchi He,

Melvyn Sim

We focus on the dynamic scheduling of Emergency Department (ED) patients

aiming to mitigate the ED crowding and consequential delays. We propose a

novel modeling framework for this patient flow control based on robust

optimization approach which is of high fidelity to real ED operations. Our

numerical study is inspired from empirical data and the proposed policy well

retains the computation tractability and yields promising benefits on achieving ED

targets comparing to other common policies.

3 - Combined Advance and Appointment Scheduling

Mehmet Begen, Ivey Business School - Western University,

1255 Western Road, London, ON, N6G0N1, Canada,

mbegen@ivey.uwo.ca,

Jonathan Patrick, Antoine Sauré

Appointment scheduling and advance scheduling have generally been addressed

as two separate problems despite being highly dependent on each other. We

attempt to develop a framework that combines the two problems and present our

findings.

4 - Determining Non-clinical Predictors of Hospital

Ward Length-of-stay

Taylor Corcoran, PhD Student, UCLA Anderson School of

Management, 110 Westwood Plaza, Los Angeles, CA, 90095,

United States of America,

taylor.corcoran.1@anderson.ucla.edu

,

Ira Hofer, Nirav Kamdar, Elisa Long

Post-surgical hospital length-of-stay is influenced by patient acuity and surgery

procedure, and other factors including patient demographics, ward assignment,

surgeon, census levels, discharge day and location. We design an econometric

model to identify non-clinical predictors of length-of-stay using 24 months of data

from the Ronald Reagan UCLA Medical Center, which regularly experiences

occupancy near 100%. Reduced ward length-of-stay could alleviate congestion

and improve on-time surgeries.

WD43

43-Room 103A, CC

Pricing & Revenue Management with New

Ingredients

Sponsor: Revenue Management and Pricing

Sponsored Session

Chair: Xin Geng,

Xin.Geng@sauder.ubc.ca

1 - Threshold Discounts Comparison: Across-the-board or Partial?

Thunyarat Amornpetchkul, Faculty Member, NIDA Business

School, 118 Seri-Thai Road, Bangkapi, Boonchana-Atthakorn

Bldg. 8th Fl., Bangkok, 10240, Thailand,

thunyarat.a@nida.ac.th

An increasingly ubiquitous discount format that is taking over traditional price

cuts is “threshold discount,” under which a price reduction is awarded to a

purchase that meets a minimum quantity or minimum spending requirement. We

consider the use of two popular discount schemes: all-unit and incremental

discount, in a retail setting. Our focus is to investigate when it is more profitable

for the retailer to offer an all-unit discount or an incremental discount.

2 - In Parallel to Ongoing Efforts to Deoptimial Contract Designs for

Carbon Capture and Storage Systems

Wenbo Selina Cai, Assistant Professor, New Jersey Institute of

Technology, Newark, NJ,

cai@njit.edu,

Dashi Singham

In parallel to ongoing efforts to develop improved CCS technology, we model the

decision processes of CCS participants who face uncertainty in both costs and

emissions, and optimize incentives to encourage storage operators to provide the

service of transportation and storage of CO2 from emitters who have

heterogeneous emissions profiles. We also evaluate the impact of the cap-and-

trade carbon policy on CCS participants’ sequestration efforts and storage

operators’ performance.

3 - Consumer Subsidies in Developing Economies: Advance Selling

and Self-control

Qiao-Chu He, PhD Candidate, University of California, Berkeley,

1117 Etcheverry Hall, Berkeley, CA. United States of America,

heqc0425@berkeley.edu,

Zuo-jun Max Shen, Ying-ju Chen

We present an explanation to the product adoption puzzle in developing

economies via consumers’ lack of self-control due to their present-bias. We

explore the roles of advance selling and consumer subsidy in resolving this

puzzle.

4 - Advance Selling to Strategic Consumers: Preorder Contingent

Pricing or Preorder Contingent Production

Mike Wei, Assistant Professor, University at Buffalo, 326C Jacobs

Management Center, Buffalo, 14260, United States of America,

mcwei@buffalo.edu

, Fuqiang Zhang

Motivated by emerging industry practices, this paper studies the effectiveness of

two new advance selling strategies in counteracting strategic consumer behavior:

the preorder contingent production (PCQ) strategy and the preorder contingent

pricing (PCP) strategy, where the seller’s preorder production and price are a

function of the preorder quantities respectively.

WD40