2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - Price Discrimination In a Regulated Healthcare Market:
Role Of Government Subsidy And Price Cap
Jianpei Wen, Peking University, Founder Building, No.298
ChengFu Rd, HaiDian District., Beijing, 100871, China,
Frank Y Chen, Jie Song
The long waiting times in the public health sector in many countries has
motivated the government to shift health authority waiting lists to the private
sector, by setting a price cap and subsidizing switching patients in private services.
We propose a novel queuing model incorporating choice behavior of
heterogeneous time-sensitive customers. The optimal pricing policy with price
discrimination to maximize the private sectors’ revenue will exam the effect of
subsidy and price cap in a government regulated market.
4 - A Reservation Policy For Medical Diagnostic Resource Allocation
Weifen Zhuang, Xiamen University,
We study the problem of the resource allocation of medical diagnostic facilities,
accessed by three types of patients. Both inpatients and outpatients have to make
appointments in advance, and emergency patients walk in directly. We formulate
a dynamic programming model of the resource allocation problem and study the
structural properties, based on which we fully characterize the optimal
reservation policy. An upper bound and a lower bound to the DP value are
created and proved to be asymptotically optimal. Numerical studies show that the
performance of bounds works very well, and our heuristic policy outperforms the
hospital’s target policy significantly.
WB36
205B-MCC
Supply Chain Analytics
Sponsored: Manufacturing & Service Oper Mgmt, Supply Chain
Sponsored Session
Chair: A Serdar Simsek, University of Texas-Dallas,
800 W. Campbell Rd, SM 30, Richardson, TX, 75080, United States,
1 - Dynamic Selling Mechanisms For Exploring Markets With
Customer- And Time-heterogeneity
Meng Li, University of Massachusetts, Dartmouth, MA,
United States, N. Bora Keskin
Consumers are often heterogeneous in their preferences for product quality, and
firms usually face uncertainty about consumer preferences when they sell
vertically differentiated products to such heterogeneous consumers. We study this
problem in a setting where a firm can dynamically optimize its prices.
2 - Consumer Choice Models With Endogenous Network Effects
Ruxian Wang, Johns Hopkins Carey Business School, Baltimore,
MD, 21202, United States, , Zizhuo Wang
Network externality arises when the utility of a product depends not only on its
attributes, but also on the number of consumers who purchase the same product.
We first characterize the choice probabilities under such models and conduct
studies on comparative statics. Then, we show that a new class of assortments,
called quasi-revenue-ordered assortments, which consist of a revenue-ordered
assortment plus at most one additional item, are optimal under mild conditions.
An empirical study on a mobile game dataset shows that our proposed model can
provide better fits for the data, increase the prediction accuracy for consumer
choices and potentially increase revenue.
3 - Two Echelon Distribution Systems With Random Demands And
Storage Constraints The Multi-product Case
Awi Federgruen, Columbia University, ,
Daniel Guetta, Garud N Iyengar
We address a general model for a two-echelon system with arbitrarily many
retailers and products, joint storage constraints and joint order costs.. We develop
an approach to compute a tractable lower bound dynamic program (DP) for the
optimal system-wide costs, along with a novel order, withdrawal and allocation
policy that is derived from the strategy which is optimal in the lower bound DP.
The lower bounds are based on a combination of relaxation methods, Lagrangian
and others. Based on an extensive numerical study, the lower bound is found to
be very accurate, and the proposed system-wide policy is close to optimal. We also
show how the model can be used to make strategic, e.g., assortment decisions.
4 - An Expectation-maximization Algorithm To Estimate The
Parameters Of The Markov Chain Choice Model
A Serdar Simsek, The University of Texas at Dallas, Naveen Jindal
School of Management, 800 W Campbell Road, Richardson, TX,
75080, United States, ,
Huseyin Topaloglu
We develop an expectation-maximization algorithm to estimate the parameters of
the Markov chain choice model. The parameters of the Markov chain choice
model are the probability that the customer arrives into the system to purchase
each one of the products and the probability that she transitions from the current
product to another one for each pair of products. We give computational
experiments on multiple data sets, one of which uses real hotel data from the
literature. Markov chain choice model, coupled with our expectation-
maximization algorithm, yields better predictions of customer choice behavior
when compared with other commonly used alternatives.
WB37
205C-MCC
Supply Chain Structure and Sustainability
Sponsored: Manufacturing & Service Oper Mgmt, Sustainable
Operations
Sponsored Session
Chair: Greys Sosic, University of Southern California, Los Angeles, CA,
United States,
Co-Chair: Hailong Cui, Marshall School of Business, University of
Southern California, CA, United States,
1 - Ensuring Corporate Social And Environmental Responsibility
Through Vertical Integration And Horizontal Sourcing
Adem Orsdemir, University of California Riverside,
Bin Hu, Vinayak V Deshpande
Inspired by Taylor Guitars’ vertical integration with its supplier to ensure
corporate social and environmental responsibility (CSER), we investigate vertical
integration as an alternative strategy for ensuring CSER in a competitive setting.
We find that demand externality due to violation exposures and the possibility of
supplying the competitor may fundamentally change firms’ behaviors and CSER
outcome. Furthermore, we find that high probability of violation exposure may
discourage responsible sourcing under strongly negative demand externalities.
Our findings suggest guidelines for firms interested in ensuring CSER, and for
NGOs’ violation scrutiny and reporting policies.
2 - Peer-to-peer Product Sharing: Implications For Ownership,
Usage, And Social Welfare
Guangwen Kong, University of Minnesota, 111 Church Street,
Minneapolis, MN, 55455, United States,
Saif Benjaafar, Xiang Li
We consider a two-sided market consisting of product owners and renters,
mediated by an online platform. Individuals decide on whether to be owners or
renters. Owners are able to generate income from renting their products to non-
owners while non-owners are able to access these products through renting on as
needed basis. The platform decides on rental prices, commission rates, and
membership fees. We characterize equilibrium outcome and compare product
ownership and product usage with and without sharing.
3 - Capacity Allocation For A Green Farm
Dong Li, Singapore University of Technology and Design,
Singapore, Singapore, , Saif Benjaafar,
Niyazi Taneri
Much of the farmland in the United States is leased to farmers by landlords
through a crop-sharing agreements. Consumers are willing to pay a premium for
green produce and some even more for locally sourced green produce. However,
yields for green farming are typically lower than conventional farming. We model
the strategic interaction between a farmer and a landlord, the capacity allocation
decision of the farm across conventional and green produce, and the decision of
the farm to allocate its green produce across a global market and a local market
under a crop-sharing agreement.
4 - Design Of Public Warning System
Saed Alizamir, Yale University, ,
Francis E De Vericourt, Shouqiang Wang
We study the design of public warning systems in a multi-period model. In each
period, the sender (she) receives an imperfect signal about the true state of the
world (dangerous or safe), and has to decide whether to warn the receiver to act.
Depending on the true realization of the random event, the receiver updates his
belief about sender’s credibility. The sender, therefore, has to dynamically manage
her reputation over time, while also incentivizing the receiver to act on her
warnings. We characterize the optimal warning policy, and gain insights into why
it may sometimes be optimal for the sender to distort her signal.
WB37