Informs 2015

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INFORMS Philadelphia – 2015
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2 - Managing Sales of a New Product Though Competing Brokers
Rahul Bhaskar, Professor, California State University, Fullerton,
800 north college boulevard, fullerton, ca, 92834, United States of
America, Vahideh Abedi
A new product typically rely on sales efforts of brokers to enhance sales.
Customers make their purchase decision not only based on the word of mouth
they have received from other customers about the product, but also based on the
collective information received from the brokers. Therefore, brokers act
synergistically to generate sales while competing. We develop an analytical
framework for this sales process and show how it can facilitate important
managerial decision making.
3 - Simultaneous vs. Sequential Crowdsourcing Contests
Lu Wang, Rotman School of Management, 105 St. George Street,
Toronto, Canada, , Ming Hu
In a crowdsourcing contest, innovation is outsourced from an open crowd. We
consider two alternative mechanisms for an innovative product involving
multiple attributes. One is to run a simultaneous contest, where the best solution
is selected from the single solution simultaneously submitted by each contestant.
The other is to run multiple sequential sub-contests, with each dedicated to one
attribute. While both mechanisms have their own advantages, either could win
over depending on parameters.
4 - To Tier or Not to Tier: A Comparative Analysis of Different Loyalty
Program Structures
Amir Gandomi, Assistant Professor, Ryerson University,
350 Victoria Street, Toronto, ON, M5B 2K3, Canada,
, Amirhossein Bazargan, Saeed Zolfaghari
This study analyzes the effectiveness of two common loyalty program structures,
namely, linear and multi-tier structures. Using a game theoretic approach, we
formulate the market conditions under which different structures are more
profitable. Market conditions are characterized by the proportion of members
who are active and the degree to which they are forward-looking. The binary
logit model is used to capture the customers’ buying behavior in a multiple-period
setting.
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40- Room 101, CC
Behavioral Operations I
Contributed Session
Chair: Bo Hu, Research Staff, Xerox Corp, 800 Phillips Road, Webster,
NY, 14580, United States of America,
1 - Bidding Decision in Land Auction using Prospect Theory
Xinwang Liu, Professor, Southeast University, Si Pai Lou 2,
Nanjing, 210096, China,
With the background of land auction practice in China, we consider the
preferences of the decision-makers in land bidding decisions with the multi-
attribute additive utility and reference point in cumulative prospect theory. Three
land auction models are proposed based on the appearance time of the land
auctions: the simultaneous model, the time sequential model and the event
sequential model. A case study illustrates the processes and results of our
approaches.
2 - Decision Behavior in Humanitarian Logistics – The Effect of Stress
on Operational Decisions
Maximilian Burkhardt, PhD Candidate, WHU Otto Beisheim
School of Management, Burgplatz 2, Vallendar, Germany,
, Stefan Spinler
We examine the influence of cognitive biases under stress in disaster relief
situations. Although the effect of various biases in operational decisions has been
analyzed, the specific effect of stress on decision behavior has been out of focus.
Time pressure and high-stakes involved serve as relevant stressors in this context.
For the required empirical support we aim at conducting experiments with
different subject groups, such as business students and humanitarian
practitioners.
3 - Apply Behavioral Economics in Designing Services
Bo Hu, Research Staff, Xerox Corp, 800 Phillips Road, Webster,
NY, 14580, United States of America,
Yu An Sun, Julien Bourdaillet
We use data to find biases in choosing voluntary benefit packages. Behavioral
experiments are designed to tests hypothesis in correct those biases.
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41-Room 102A, CC
Joint Session MSOM-Health/HAS/Practice:
Operations Management of Emergency Services II
Sponsor: Manufacturing & Service Oper Mgmt/
Healthcare & HAS Operations
Sponsored Session
Chair: Shane Henderson, Professor, Cornell University, Rhodes Hall,
Ithaca, NY, 14853, United States of America,
1 - The Minimum Expected Penalty Relocation Problem for the
Computation of Ambulance Compliance Tables
Thije Van Barneveld, PhD-student, Centrum Wiskunde en
Informatica, Science Park 123, Amsterdam, Netherlands,
We study the ambulance relocation problem in which one tries to retain the
ability to respond to possible future incidents quickly. For this purpose, we
consider compliance table policies. To compute efficient compliance tables, we
introduce the Minimum Expected Penalty Relocation Problem (MEXPREP), in
which one has the ability to control the number of waiting site relocations.
Moreover, different performance measures related to response times, e.g., survival
probabilities, can be incorporated.
2 - Optimizing Aircraft Configuration for Air-ambulance Service
Provider in Ontario
Pieter Van Den Berg, Delft University of Technology, Mekelweg 4,
Delft, 2628 CD, Netherlands,
Shane Henderson, Karen Aardal
Ornge provides air-ambulance services to patients in the province of Ontario. For
this service, both fixed wing aircraft and helicopters are used. The fixed wing
aircraft have a wider range but are restricted to land on airports. Helicopters, on
the other hand, are more flexible in landing sites. Currently, Ornge operates a
24/7 flat schedule. We apply both simulation and optimization techniques to find
good configurations of the aircraft and helicopters for both day and night.
3 - Optimality of the Closest-idle Policy in Advanced
Ambulance Dispatching
Sandjai Bhulai, VU University Amsterdam, De Boelelaan 1081a,
Amsterdam, 1081 HV, Netherlands, ,
Caroline Jagtenberg, Rob Van Der Mei
In ambulance dispatching it is commonly believed that the ‘closest idle
ambulance’ rule is the best choice. We present two alternatives to this classical
rule and show that significant improvements can be obtained. The first alternative
is based on a Markov decision problem, and the second is a heuristic that can
handle regions with large numbers of ambulances. The heuristic reduces the
fraction of late arrivals by 18% for a large emergency medical services region in
the Netherlands.
4 - An Information-based Bound on the Performance of Ambulance
Redeployment Policies
Kenneth Chong, PhD Student, Cornell University,
257 Rhodes Hall, Ithaca, NY, 14853, United States of America,
Shane Henderson, Mark Lewis,
Huseyin Topaloglu
Ambulance redeployment is the practice of strategically relocating idle
ambulances in real time to improve coverage of future demand. We present an
upper bound on the performance that can be attained by any redeployment
policy. Our approach involves formulating the redeployment problem as a
stochastic dynamic program, considering an information relaxation of this
problem, and penalizing policies that violate nonanticipativity constraints.
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