Informs 2015

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INFORMS Philadelphia – 2015
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3 - Optimizing The Online Sellers’ Shipping Strategy and Return
Service Charge Jointly
Huijun Hou, University of Science and Technology of China,
No.96, JinZhai Road, Hefei, 230026, China,
Xiangyu Meng
Our work develops a theoretical model to optimize the sellers’ shipping strategy
of free shipping or not and return service charge jointly when no-reason return
are admitted. The results imply that the sellers should adjust their shipping
strategy and return service charge according to the market environment. Data
experiments show that the joint optimal decisions could improve the sellers’
profit and keep it more stable with the change of the price effectively.
4 - Optimal Routing for Multi-channel Call Centers with Idling Times
during the Service Process
Oualid Jouini, Associate Professor, Ecole Centrale Paris, LGI,
Grande Voie des Vignes, Chatenay-Malabry, 92290, France,
, Ger Koole, Benjamin Legros
We consider a call center with inbound and outbound jobs. The inbound service is
characterized by three successive stages where the second one is a break (idle
time for the agent). This leads to a new opportunity to efficiently split the agent
time between inbounds and outbounds. We focus on the optimization of the
outbound job routing to agents. We prove for the optimal policy that all the time
there is at least a systematic treatment of outbounds, either during the break, or
between two calls.
5 - Lodging Capacity Analytics for the Qatar 2022 Fifa World Cup
Ahmed Ghoniem, Isenberg School of Management, UMass
Amherst, 121 Presidents Dr., Amherst, MA, 01002, United States
of America, , Agha Iqbal Ali
Capacity analytics is important for small countries, such as Qatar, that host the
FIFA World Cup. We develop an Analytics-Optimization framework that assesses
the lodging preparedness of the host country under an array of likely scenarios.
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64-Room 113A, CC
Strategic Decision Making
Sponsor: Decision Analysis
Sponsored Session
Chair: Wenxin Xu, Illinois University, United Sates of America,
Co-Chair: Youngsoo Kim, University of Illinois at Urbana-Champaign,
1 - Strategic Decisions for Bringing Innovation to Market in Presence
of Spillover Risks
Yunke Mai, Duke University, Duke University, Durham, NC,
United States of America, Sasa Pekec
We study optimal sourcing strategies of a technology innovator facing a
manufacturer who is also a competitor in the product end market. The competing
manufacturer has its own inferior product which could be improved through
technology spillover, should a contract with the innovator be secured. We
characterize the equilibria and analyze comparative statics in several variants of
this supply chain/innovation management game.
2 - Decision Analysis using Holistic Component as Opposed to
Conventional Attribute Driven Methodology
Subhabrata Bapi Sen, Adjunct Faculty, Sillberman College of
Business, 32 Rolling Hill Dr, Chatham, NJ, 07928,
United States of America,
The holistic approach - 5 stage skill acquisition model that differentiate “knowing
how” from “knowing that” is better than multi-attribute decision analysis (MDA)
supported by AI which uses decomposition. This truly reflect the decision making
as an inscrutable business, a mysterious blending of careful analysis, intuition,
and the wisdom and judgement distilled from experience that takes us away from
limited rationality to a-rational domain which limit unmindful use of MDA in
social policy.
3 - The Impact of Spillover in R and D Competition
Wenxin Xu, Illinois University, United States of
America Jovan Grahovac, Dharma Kwon
Why are some firms willing to disclose their intellectual properties to their
competitors while others are not? To answer this, we investigate a game theoretic
duopoly model to examine the impact of spillover on R&D investment strategies
when the R&D completion times are uncertain. We find that spillover may or may
not hurt the more efficient firm. We identify the conditions under which the
more efficient firm benefits from spillover.
4 - Investment in Shared Supplier under Spillover, Uncertainty,
and Competition
Youngsoo Kim, University of Illinois at Urbana-Champaign,
Urbana, IL, United States of America,
Anupam Agrawal, Dharma Kwon, Suresh Muthulingam
We consider two competing buyers who can invest into their common supplier
under spillover and uncertainty. One firm’s investment could be spilled to the
other through the shared supplier. Moreover, return on investment is unknown
to the buyers though it can be learned based on the supplier’s performance.
Modeling as real option game, we find two equilibria, one of which has been
rarely studied in literature, and we characterize the conditions under which the
investment is hastened or delayed.
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65-Room 113B, CC
Intelligent Transportation Systems
Contributed Session
Chair: Xiaoyun Zhao, PhD Student, Dalarna University, Sweden,
Hˆgskolan Dalarna, 79188 Falun, Falun, 79188, Sweden,
1 - Nonparametric, Heterogeneous Demand for Autonomous
Electric Vehicles
Ricardo Daziano, Assistant Professor, Cornell University,
305 Hollister Hall, Ithaca, NY, 14853, United States of America,
In this paper we use data about vehicle preferences, and automation awareness
and attitudes. A sample of 1,260 respondents answered a discrete choice
experiment especially designed for this study. Several models were estimated,
including a semi-parametric random parameter logit (with assumption-free
heterogeneity distributions that are a mixture of normals). Estimation of the
Gaussian mixture model was implemented in R using the maximum simulated
likelihood estimator with analytical gradients.
2 - Deployment and Utilization of Plug-in Electric Vehicles in
Round-trip Carsharing Systems
Stephen Zoepf, MIT, 1039 Massachusetts Ave., #302, Cambridge,
MA, 02138, United States of America,
Alexandre Jacquillat
Plug-in Electric Vehicles (PEVs) can reduce gasoline consumption but are also
constrained by range limitations and recharging requirements. We address the
problem of PEV utilization in a round-trip carsharing system by optimizing and
simulating the assignment of trips to vehicles. We use these results to inform the
deployment of PEVs in the carsharing fleet. We find that PEV deployment and
utilization can reduce gasoline consumption significantly and improve carsharing
operators’ profitability.
3 - Connected Vehicle V2i(vehicle-to-infrastructure) Based
Microscopic Dynamic Merge Coordination System
Xiaowen Jiang, Ph.d Fellow, Rutgers, The State University of New
Jersey, #736 CORE Building Busch Campus, 96 Frelinghuysen
Rd, Piscataway, NJ, 08854, United States of America,
Peter J. Jin
This paper proposes a connected vehicle V2I(Vehicle-to-Infrastructure) based
dynamic merge coordination system. The system assumes DSRC Road-side Unit
(RSU) can obtain full vehicle trajectories through radar sensors and will
coordinate all DSRC-equipped thru and ramp vehicles. Each ramp vehicle is
paired and synchronized with a targeted gap on the through lane. The putative
following (PF) vehicle of the gap will be advised to yield and maintain enough
gap to allow smooth merging.
4 - Framework for Standalone Application Development for Traffic
Management in Ad Hoc Networks
Sayyid Vaqar, KFUPM, P.O. Box 983, Dhahran, 312600,
Saudi Arabia,
Road traffic condition awareness is an important tool in traffic management in
intelligent transportation systems. We propose a framework to develop
standalone application to be run on participating node in the network that can
process information collected from neighboring nodes to predict driving condition
down the road. The nodes can communicate with each other for gathering data
but processing and decision making is done individually.
5 - On Processing and Evaluating GPS Based Traffic Data
Xiaoyun Zhao, PhD Student, Dalarna University, Sweden,
Hügskolan Dalarna, 79188 Falun, Falun, 79188, Sweden,
, Kenneth Carling, Johan HÂkansson
This paper aims to evaluate the reliability of GPS based traffic data to reveal the
neglected but susceptible measurement error. We assess the reliability of the data
on geographical positioning, speed and altitude for three types of vehicles: bike,
car and bus with a randomized experiment. We outline a general procedure for
data processing considering no standard software packages or procedures are
available in former studies.
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