2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - Selling To Socially Connected Customers
Ruslan Momot, INSEAD, Fontainebleau, France,
Elena Belavina, Karan Girotra
We study the value of different kinds of social network information and illustrate
its use. We build a model of a social network of strategically interacting customers
who value exclusive ownership of the product and are heterogeneous in the
number of friends (degree) and proclivity for social comparisons (conspicuity).
We find that high-conspicuity customers within intermediate-degree segments are
the firm’s best targets. Our analysis reveals how they should be selectively
targeted by the firms with information on either (or both) of the customer traits.
We find that information about degree is more valuable than information about
conspicuity and that the two are substitutes.
4 - Subscription Box Business Models: Pricing And Quality Decisions
Basak Kalkanci, Georgia Institute of Technology,
Necati Tereyagoglu
We model the value of online subscription box business model for a consumer
who chooses the replenishment frequency (or timing) of a frequently used
durable good. We explore the seller’s pricing and quality decisions under the
online subscription box business model, and evaluate the performance of such a
model in comparison to selling through an offline retail channel.
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201B-MCC
Sequential Sampling and Optimization
Sponsored: Applied Probability
Sponsored Session
Chair: Raghu Pasupathy, Purdue University, West Lafayette, IN,
United States,
1 - Sequential Stopping Rules For Simulation Problems Where
Variance Estimation Is Difficult
Jing Dong, Northwestern University, ,
Peter W Glynn
We solve the sequential stopping problem for a class of simulation problems in
which variance estimation is difficult. In particular, we establish the asymptotic
validity of sequential stopping procedures for estimators constructed using various
cancellation methods. We characterize the limiting distribution of the estimators
at stopping times as the error size (the absolute error or the relative error) goes to
0, which is different from the limiting distribution of the estimator constructed
based on a fixed size of samples as the sample size goes to infinity.
2 - Probabilistic Bisection Converges Almost As Quickly As
Stochastic Approximation
Shane Henderson, Professor, Cornell University, 230 Rhodes Hall,
Ithaca, NY, 14853, United States, , Peter Frazier,
Rolf Waeber
The probabilistic bisection algorithm (PBA) can be applied to stochastic root
finding problems in one dimension. The PBA successively updates a Bayesian
prior on the location of the root after using a power-one test at the median of the
posterior to estimate the direction of the root from the median. The power-one
test has a variable sample size. The PBA has features that we believe make it
attractive relative to stochastic approximation for such problems. I will discuss the
algorithm and sketch a proof that it converges at a rate arbitrarily close to the
canonical “square root” rate of stochastic approximation.
3 - Fixed-Step, Line Search, And Trust-Region Adaptive Sampling
Recursions for Simulation Optimization
Raghu Pasupathy, Purdue University,
We present a sequential sampling framework for recursively solving stochastic
optimization problems. The framework consists of embedding a globally conver-
gent numerical optimization search routine, e.g., line search, trust region, with
Monte Carlo sampled estimators of the objective function and gradient. Global
convergence to a stationary point depends crucially on a result characterizing the
sample size at each iteration. We will outline the conditions that guarantee the
attainment of the Monte Carlo canonical rate.
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202A-MCC
Managing Capacity in Energy Markets Through
Demand and Supply-side Interventions
Sponsored: Manufacturing & Service Oper Mgmt, Sustainable
Operations
Sponsored Session
Chair: Charles J Corbett, University of California - Los Angeles,
Los Angeles, CA, United States,
1 - Energy Efficiency Contracting In Supply Chains Under
Asymmetric Bargaining Power
Ali Shantia, HEC Paris, 1 rue de la Liberation, Jouy-en-Josas,
78350, France, Sam Aflaki, Andrea Masini
Evidence shows that suppliers refrain from investing in energy efficiency (EE)
measures because they fear that a buyer with greater bargaining power will use
the EE-related cost reductions to push prices down, in the purchase bargaining
process, and thereby further reduce the supplier’s profit margin. In a supply chain
consisting of a buyer and a supplier, this study analyses the effect of relative
bargaining power and technology uncertainty on the supplier’s decision to invest
in energy efficiency measures. We analyse price commitment and shared
investment contracts as potential coordination mechanisms and compare them in
their ability to boost EE investment by the supplier.
2 - An Analysis Of Time-based Pricing In Electricity Supply Chains
Asligul Serasu Duran, Kellogg School of Management, 2001
Sheridan Road, 5th floor, Evanston, IL, 60208, United States,
, Baris Ata, Ozge Islegen
This study builds a framework for the retail electricity market to empirically
evaluate the impact of time-based tariffs on the electricity supply chain. We find
that optimal time-based tariffs reduce peak demand, but do not change
consumers’ electricity bills significantly. Time-of-use tariffs with predetermined
rates can capture most of the benefits of real-time prices. The environmental
impact of time-based tariffs depends on the characteristics of the electricity
market under study.
3 - Investments In Renewable And Conventional Energy:
The Role Of Operational Flexibility
Kevin Shang, Duke University, Durham, NC, United States,
, Gurhan Kok, Safak Yucel
We study capacity investments of a utility firm in renewable and conventional
energy sources with different levels of operational flexibility, i.e., the ability to
quickly ramp up or down the output of a generator. We consider supply
characteristics of conventional and renewable sources and derive the optimal
capacity investment portfolio. We find that inflexible sources (e.g., nuclear
energy) and renewables are substitutes; flexible sources (e.g., natural gas) and
renewables are complements.
4 - Explaining The Variation In Progress In The Us Nuclear Industry
Christian Blanco, University of California - Los Angeles,
Los Angeles, CA, United States, ,
Felipe Caro, Charles J Corbett
We examine the factors that influenced the US nuclear power production
efficiency and safety over time.
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202B-MCC
Studies in Service Operations
Sponsored: Manufacturing & Service Oper Mgmt
Sponsored Session
Chair: Robert Batt, Wisconsin School of Business, UW - Madison,
Madison, WI, United States,
1 - Heart Failure transitions: Staffing Follow-up Clinics To
Reduce Readmissions
Itai Gurvich, Kellogg School of Management, i-
Benjamin Grant,
Jan A Van Mieghem, Kannan Mutharasan
Heart failure (HF) readmissions are a major driver of cost and health care
utilization. Timely follow-up of patients post-discharge represents an evidence-
based intervention proven to reduce readmission rates. Patients discharged after
HF hospitalization are scheduled to meet a cardiologist in the outpatient clinic.
Meeting targets for timely follow-up requires appropriate capacity planning for
these clinics that takes into account the inpatient-discharge variability. An
intervention based on simple safety capacity rules and more aggressive utilization
of existing capacity resulted in more than doubling the fraction of patients seen
within one week of discharge.
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