2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - Is The FDA Too Conservative Or Too Aggressive?:
A Bayesian Decision Analysis Of Clinical Trial Design
Andrew W Lo, Charles E. and Susan T. Harris Professor, MIT, 100
Main Street, E62-618, Cambridge, MA, 02142, United States,
Andrew W Lo, Charles E. and Susan T. Harris
Professor, MIT, 32 Vassar Street, Cambridge, MA, 02139, United
States, Leah Isakov, Vahid Montazerhodjat
We explore the application of Bayesian decision analysis (BDA) to minimize the
expected cost of drug approval, where the relative costs of Type I and Type II
errors are calibrated using burden of disease data. For terminal illnesses with no
existing therapies such as pancreatic cancer, the standard Type I error threshold of
2.5% is substantially more conservative than the BDA-optimal threshold of
23.9% to 27.8%. We compute BDA-optimal sizes for 25 of the most lethal
diseases and show how a BDA-informed approval process can incorporate all
stakeholders’ views in a systematic, transparent, internally consistent, and
repeatable manner.
4 - A Comparison Between The Robust Risk-aware And Risk-seeking
Managers In R&D Portfolio Management
Aurelie Thiele, Associate Professor, Southern Methodist University,
Dallas, TX, United States,
Shuyi Wang
We analyze via simulation two mathematical modeling frameworks that reflect
different managerial attitudes toward upside risk in R&D portfolio selection. The
manager seeks to allocate a development budget between low-risk, low-reward
projects, called incremental projects, and high-risk, high-reward projects, called
innovational projects. We study the differences in strategy and portfolio’s risk
profile that arise between a risk-aware manager, who takes upside risk because he
has to for the long-term competitive advantage of his company, and a risk-seeking
manager, who will take as big a bet as allowed by the model.
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205A-MCC
Frontiers of Supply Chain Research
Sponsored: Manufacturing & Service Oper Mgmt, Supply Chain
Sponsored Session
Chair: Karen Zheng, MIT Sloan School of Management, Cambridge,
MA, 02142,
1 - Dual Co-product Technologies: Implications For Process
Development And Adoption
Brian Tomlin, Tuck School of Business,
, Ying-Ju Chen, Yimin Wang
Many industries operate technologies in which multiple outputs (co-products) are
jointly produced. Three important attributes of a co-product technology are its
production cost, its overall yield, and its co-product split. Process development
often wrestles with an inherent trade-off: improvement in one attribute comes at
the expense of another. In this talk, we first explore production and pricing
decisions for a firm with two technologies and then use this foundation to
examine implications for process development and process adoption.
2 - Impact Of Grocery Store Density And Market Structure On
Food Waste
Elena Belavina, University of Chicago Booth School of Business,
Food waste is one of the major contributors of greenhouse gas emissions. If food
waste was a country, it would be third largest polluter shortly after US and China.
About $1 trillion dollars of food is wasted every year, which is equivalent to 1%
of GDP globally. This study explores the impact of store density and market
structure on consumer food waste.
3 - Self-policing In A Supply Chain Under Threat Of Public Disclosure
Sang-Hyun Kim, Associate Professor, Yale University, New Haven,
CT, United States, Saed Alizamir
We study incentive dynamics among supply chain members and an external
stakeholder (e.g., NGO) that impact environmental performance. A buyer inspects
a supplier’s production in its supply chain to detect and correct environmental
compliance violations. The buyer’s primary motive is to deter the NGO from
discovering the violation first and publicize it, from which the buyer incurs a
reputational penalty. The buyer and the NGO engage in a game to competitively
set their inspection intensities, which influence the supplier’s decision to restore
compliance. Together, the actions made by all parties determine the
environmental outcome and and social welfare.
4 - Increasing Retail Sales Via Improved Store Staffing:
An Empirical Study With Implemented Results
Santiago Gallino, Dartmouth College,
, Marshall L Fisher,
Serguei Netessine
We analyzed 30 months of a retailer’s history on store-month sales and potential
sales drivers to measure the impact of store selling staff level on revenue. We
identified a third of the stores where our analysis indicated that increasing staffing
would increase sales. The retailer confirmed this finding via a 16 store test which
showed that a 10% increase in sales staff resulted in a 9.9% sales increase, and
was highly profitable. The retailer is now implementing our finding in other
stores.
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205B-MCC
Information and Risk in Supply Chain Networks
General Session
Chair: Kostas Bimpikis, Stanford Graduate School of Business,
650 Knight Way, Stanford, CA, 94305, United States,
1 - Inventory Management With Censored Demand Data:
The Adversarial Case
Michail Markakis, Universitat Pompeu Fabra,
We consider a repeated newsvendor problem where the demand distribution is
unknown ex ante and has to be learned from sales/censored data. To shed light to
scenarios where the demand may be non-stationary, e.g., exhibiting trends or
seasonalities, we model the problem as a game between the inventory manager
and an oblivious opponent, who prior to the game decides a sequence of demands
for the different periods arbitrarily. We propose randomized inventory
management policies that perform well with respect to the regret criterion, i.e.,
the difference between a policy’s cumulative cost and the cumulative cost of the
best fixed action/ordering decision in hindsight, for any given demand sequence.
2 - Optimizing Local Content Requirements Under Technology Gaps
Shiliang Cui, Georgetown University,
, Lauren Xiaoyuan Lu
We study the optimal Local Content Requirements (LCR) and innovation policies
of a developing economy in which a foreign Original Equipment Manufacturer
(OEM) produces and sells a final product. We find that as the domestic
component supply base becomes more cost efficient, surprisingly, the OEM’s
profit could decrease.
3 - Take-rate Crowdsourcing Contracts
Yun Zhou, University of Toronto, Toronto, ON, Canada,
Ming Hu
Motivated by the surge pricing strategy by the ridesharing platforms, we consider
the pricing problem in a two-sided market. The total amount of supply is an
increasing function of the wage and the amount of demand depends on the price.
We model supply and demand uncertainty by a number of different scenarios,
and show that the take-rate price contract is optimal for maximizing the
platform’s profit or the total utility of the platform and the supply side when only
the market size is scenario dependent. In more general cases, we derive
performance bounds for the take-rate contract.
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205C-MCC
Revenue Management, Assortments and
Choice Models
Sponsored: Manufacturing & Service Oper Mgmt, Supply Chain
Sponsored Session
Chair: Ozge Sahin, Johns Hopkins University, Brooklyn, NY,
United States,
1 - Consumer Choice Under Rational Inattention And Implications
For Assortment Planning
Tamer Boyaci, ESMT Berlin, Berlin, 10178, Germany,
Frank Huettner, Yalcin Akcay
We study the choice behavior of rationally inattentive customers who optimally
acquire information about available options with ex-ante uncertain values
through potentially different channels with different costs. Customers trade-off
the benefits of better information obtained by asking questions with the
associated cost. We quantify acquired information and its cost through a novel
function based on conditional mutual information. We solve the consumer’s
choice problem and analytically characterize the resulting optimal choice
behavior. We illustrate some properties of the choice behavior and discuss
implications for assortment planning.
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