2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
464
WD26
110B-MCC
Information Systems III
Contributed Session
Chair: Benjamin Schooley, Assistant Professor, University of South
Carolina, 1301 Gervais Street, Columbia, SC, 29201, United States,
1 - Digital Ecosystem Competition, To Open Or To Close?
Chao Ding, Assistant Professor, KK Leung 807,
The University of Hong Kong, Pok Fu Lam, Hong Kong,
IT firms are currently striving to build their own digital empire of ecosystem that
profit from sales of both hardware/system and content/service. This study sets
under the context of duopoly ecosystems and examines their content/service
offering strategies and pricing strategies.
2 - A Quasi Experiment Using Social Network Approach To Effects Of
Trust Building In Sharing Economy
Shivom Aggarwal, Instututo de Empresa S.L., Instututo de
Empresa S.L., IE Business School, Calle de Maria de Molina, 12
Bajo, Madrid, 28006, Spain, , Gautam Ray
Trust is inherent in the success of Sharing economy business models, but how
building trust affects such success poses a crucial issue for firms competing with
sharing economy business models. We analysed a longitudinal data of bike
sharing systems across several cities using a social network approach. We found
that trust helped in increasing the overall revenues of a given station, but the
average revenue per bike decreased significantly. The study discusses the
implications and remedial possibilities based on the results.
3 - The Effect Of Ambidextrous Developers On Open Source
Project Success
Orcun Temizkan, Ozyegin University, Istanbul, Turkey,
Ram Kumar
Open Source Software (OSS) development is an important, yet poorly understood
type of software development with high project failure rates. We analyze a sample
of real OSS projects to better understand project success. We argue that there are
different types of developers and study their effects on success. We argue that
developers can be classified into non-ambidextrous and different types of
ambidextrous developers. Our results illustrate direct and interaction effects that
ambidextrous developers have on project success and the importance of having
multiple types of ambidextrous developers in projects.
4 - Effects Of Health Information Exchange On The Process Of Care,
Patient Care Delivery, Administrative Productivity, And Population
Health Outcomes
Benjamin Schooley, Assistant Professor, University of South
Carolina, 1301 Gervais Street, Columbia, SC, 29201, United States,
, Sue Feldman, Neset Hikmet
Health information exchange (HIE) is expected to transform the U.S. healthcare
system through access to patient data from electronic health records across
organizational boundaries - for the purpose of supporting care provision to
improve care quality and population health. However, relatively few of the more
than 100 operational U.S. HIE’s have been the subject of published evaluations.
We surveyed Virginia healthcare providers to assess perceived value of HIE,
including impacts on the process of care, patient care delivery, information
quality, and population health outcomes. Perspectives differ based on
organizational, medical specialty, and prior experience characteristics.
WD27
201A-MCC
Empirical Healthcare Operations
Sponsored: Manufacturing & Service Oper Mgmt
Sponsored Session
Chair: Diwas S KC, Emory University, Atlanta, GA, United States,
1 - The Effects Of Discrete Workshifts On Non-terminating Queues
Robert Batt, University of Wisconsin, ,
Diwas S KC, Bradley R Staats, Brian W Patterson
While an emergency department is a non-terminating queue, it is staffed by care
providers working discrete workshifts. We examine how productivity changes
over the workshift. Further, because care providers work fixed-duration shifts,
they sometimes must hand off care of in-process patients to another provider. We
examine the impact these handoffs have on treatment time and revisit rate. Using
simulation, we show that policies that prohibit starting new patients near the end
of the shift can lead to improved system throughput.
2 - A Near-term Mortality Indicator For Terminal Cancer Patients
Using High Frequency Medical Data
Donald Lee, Yale University, New Haven, CT, United States,
Edieal J Pinker
Although end of life cancer care accounts for a significant portion of the costs of
all cancer care, it often fails to improve quality or quantity of life. Yet, oncologists
consistently overestimate the chances of survival, leading to suboptimal delays in
the transition to hospice care. To more accurately assess mortality risk, we
develop a bedside statistical tool that utilizes high frequency EMR data to predict
near term mortality. Projected savings from averting excessive curative
interventions suggest significant inefficiencies in current practice. Joint work with
the Smilow Cancer Centre.
3 - A Machine Learning Approach For Personalized Health Care
Outcome Analysis
Guihua Wang, Ross School of Business, University of Michigan,
Ann Arbor, MI, United States, , Jun Li,
Wallace J Hopp
Using a patient-level data set across 35 hospitals for cardiovascular surgeries in
New York, we first provide empirical evidence that the quality gaps between
hospitals are heterogeneous for subgroups of patients. We then use a machine
learning approach to identify subgroups of patients that have large or small
quality gaps. After that, we estimate the quality gaps between a hospital and the
state average for each subgroup of patients to derive patient-centric information.
Lastly, we show that providing patient-centric information not only helps patients
choose providers but also helps hospitals identify areas for improvement and
payers design cost-effective payment programs.
4 - Are Patients Patient? The Effect Of Universal Healthcare On
Emergency Department Visits
Diwas KC, Emory University,
We study a natural policy experiment to examine the impact of universal
healthcare on emergency departments. We find that the policy has differential
effects on hospitals. Compared to EDs with high pre-policy workloads, we observe
a relative increase in volume at EDs with lower levels of pre-policy workload.
WD28
201B-MCC
Product Strategies and Channel Structure in Supply
Chain Management
Sponsored: Manufacturing & Service Oper Mgmt
Sponsored Session
Chair: Laurens G Debo, Dartmouth College, Hanover, NH,
United States,
Co-Chair: Cuihong Li, University of Connecticut, Storrs, CT, United
States,
1 - Salesforce Incentives For Managing Product Returns
Rashmi Sharma, Pennsylvania State University, University Park,
PA, 16802, United States, ,
Aydin Alptekinoglu
We study a setting where product sales and returns are effort-dependent and the
selling activity is conducted by a salesforce. We investigate the effect of salesforce
behavior on net sales and compare different incentive schemes to identify optimal
incentive strategies.
2 - Returns Policies For Overstock And Consumer Returns In
Distribution Channels
Meng Li, University of Massachusetts, Amherst, MA,
United States, Yunchuan Liu
This paper studies the interactions between an upstream manufacturer and
competing downstream retailers on offering returns policies to retailers and end-
consumers respectively. The effects of channel structure, demand uncertainty, and
retail competition are studied in a unified model covering both overstock returns
and consumer returns.
3 - Retail Market Power: A Supplier-side Perspective
Shuya Yin, University of California at Irvine, Irvine, CA,
United States, , Yuhong He, Saibal Ray
Does a supplier prefer that its downstream retailers are more balanced in terms of
their market power or that one of them is dominant, especially when the market
power might be correlated to their bargaining powers? In this paper we address
this issue and establish the supplier’s preference for a monopoly value chain as
well as when there is value chain competition.
WD26