2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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SB27
201A-MCC
Diagnosis Under Uncertainty
Sponsored: Manufacturing & Service Oper Mgmt
Sponsored Session
Chair: Sarang Deo, Indian School of Business, Hyderabad, India,
Co-Chair: Tinglong Dai, Johns Hopkins University, Baltimore, MD,
United States,
1 - False Diagnosis And Overtreatment In Services
Senthil Veeraraghavan, University of Pennsylvania,
In many services, consumers must rely on experts to identify the type of service
they need. In such service, diagnosis is a crucial step in which the expert identifies
the problem and provides the corresponding treatment. The information
asymmetry leads to inefficiencies in the form of overtreatment. Overtreatments
are expensive but also require more service capacity and time, and thus result in
longer delays and higher waiting costs for services. However, we find that such
delays act as a natural “fraud cost” and mitigates expert cheating and induce
honesty. Experts high capacity utilization are less prone to overtreat.
2 - Conspicuous By Its Absence: Diagnostic Expert Testing
Under Uncertainty
Tinglong Dai, Assistant Professor, Johns Hopkins University,
100 International Drive, Baltimore, MD, 21202, United States,
, Shubhranshu Singh
Diagnostic experts, such as medical doctors, are crucial for evaluating the state of
the world. All diagnostic experts are not equally competent, and even the best
experts are imperfect. We model the decision-making process of a diagnostic
expert, who is altruistic but concerned about reputation. Our paper presents
interesting insights about the expert’s test-ordering behavior primarily driven by
reputation concerns.
3 - Incentizing Less-than-Fully-Qualified Providers For Early
Diagnosis Of Tuberculosis In India
Sarang Deo, Indian School of Business,
Milind Sohoni, Neha Jha
A major driver of TB epidemic in India is delay in diagnosis by less-than-fully-
qualified providers (LTFQs), who are typically the first point of contact for
patients. This work is motivated by pilots funded by international donors to
provide monetary incentives to LTFQs to induce earlier referral and diagnosis.
Using a game-theoretic model, we show that the optimal structure of the
incentive referral contract (whether to pay for all referrals or only for confirmed
referrals) depends on the quality of diagnosis of the provider. We calibrate our
model results using realistic parameter estimates obtained from primary and
secondary data sources.
4 - Medical Guideline Making When Litigation Is A Concern:
The Role Of Ubiquitous Health Information
Mehmet U Ayvaci, University of Texas-Dallas,
800 W. Campbell Rd. SM33, Richardson, TX, 75080, United States,
, Yeong In Kim,
Srinivasan Raghunathan, Turgay Ayer
We examine the optimal formulation of guidelines in a generic health screening
with consideration for the physician’s increased liability risk under ubiquitous
health information and information technologies. We find that under the
litigation concern, the social planner strategically provides imprecise guidelines
with vague recommendations regarding which patients should undergo the test
while providing precise guidelines regarding the physician’s decisions based on
test results. Strategic vagueness in guidelines balances the trade-off between the
reduction of defensive medicine and supply of the health service.
SB28
201B-MCC
MSOM Student Paper Competition Finalists – II
Sponsored: Manufacturing & Service Oper Mgmt
Sponsored Session
Chair: Sameer Hasija, Insead, 1 Ayer Rajah Avenue, Singapore, 138676,
Singapore,
Co-Chair: Tolga Tezcan, London Business School, Regent’s Park,
London, NW1 4SA, United Kingdom,
Co-Chair: Nicos Savva, London Business School, Regent’s Park,
London, NW1 4SA, United Kingdom,
- Economies of Scale and Scope in Hospitals
Michael Freeman, University of Cambridge, Cambridge, United
Kingdom.
Abstract to come
3 - Online Decision-Making with High-Dimensional Covariates
Hamsa Bastani, Stanford University, Stanford, CA,
Big data has enabled decision-makers to tailor decisions at the individual-level in
a variety of domains such as personalized medicine and online advertising. This
involves learning a model of decision rewards conditional on individual-specific
covariates. In many practical settings, these covariates are high-dimensional;
typically only a small subset of the observed features are predictive of a decision’s
success. We formulate this problem as a multi-armed bandit with high-
dimensional covariates, and present a new efficient bandit algorithm based on the
LASSO estimator. Our regret analysis establishes that our algorithm achieves
near-optimal performance in comparison to an oracle that knows all the problem
parameters. The key step in our analysis is proving a new oracle inequality that
guarantees the convergence of the LASSO estimator despite the non-i.i.d. data
induced by the bandit policy. Furthermore, we illustrate the practical relevance of
our algorithm by evaluating it on a real-world clinical problem of warfarin dosing.
4 - Real-time Optimization of Personalized Assortments
Negin Golrezaei, USC Marshall School of Business, Los Angeles,
CA,
Abstract to come
SB29
202A-MCC
Innovations in the Operations-Marketing Interface
Sponsored: Manufacturing & Service Oper Mgmt
Sponsored Session
Chair: Jose A Guajardo, University of California-Berkeley, Berkeley,
CA, United States,
1 - Does Online Learning Work In Retail?
Serguei Netessine, INSEAD,
Marshall L Fisher, Santiago Gallino
We partnered with Experticity, a firm that provides online training modules for
retail Store Associates, and Dillard’s, a leading department store chain whose
more than 50,000 Store Associates had access to the Experticity product training
modules. We found that as Store Associates engaged in training over time, their
sales rate increased by 1.8 percent for every module taken. We also found that
willingness to engage in voluntary training was an indicator of raw talent; those
Store Associates who engaged in training were 20 percent more productive prior
to any training, and 46 percent more productive after training, than those who
took no training.
2 - Business Models In The Sharing Economy: Manufacturing
Durable Goods In The Presence Of Peer-to-peer Rental Markets
Zhe Zhang, Carnegie Mellon University, 4800 Forbes Avenue,
Pittsburgh, PA, 15213, United States,
Vibhanshu Abhishek, Jose A Guajardo
Business models focusing on providing access to assets rather than on transferring
ownership of goods have become an important recent industry trend. Motivated
by this trend, this research analyzes the interaction between a manufacturer of
durable goods and a peer-to-peer marketplace, characterizing market outcomes
under alternative market structures.
SB27
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