2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - Price Formation And Efficiency In Ride Sharing Services
Yi Xu, University of Maryland, , Liu Ming,
Tunay Tunca, Weiming Zhu
Using data obtained from a leading company, we construct a structural model to
estimate price formation in ride-sharing services based on operational
characteristics such as the number of consumers and the utilization of drivers.
Further, we conduct counterfactual analysis to examine efficiency and welfare
implications.
4 - When Do Financial Firms Relocate? A Stochastic View
Michael Pinedo, New York University Stern School of Business,
44 West 4th St. KMC8-152, New York, NY, United States,
, Yuqian Xu, Lingjiong Zhu
We consider a financial firm makes the relocation decision based on two
perspectives: i) higher expected utility in relocation, and ii) higher probability in
achieving certain utility. In this paper, we use the hiring lead time which is a
random variable to capture the difficulty in hiring, and thus how this factor
impact the relocation decision. At the same time, we integrate in our model the
uncertainty and variation in employee capability as well as the uncertainty in
their willingness to relocate.
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Music Row 4- Omni
Crowdsourcing and Sharing Economy
Sponsored: EBusiness
Sponsored Session
Chair: Wei Chen, University of Arizona, 1130 East Helen Street
McClelland Hall 430, Tucson, AZ, 85721-0001, United States,
1 - Do Ride Sharing Services Affect Traffic Congestion?
An Empirical Study Of Uber Entry
Yili Hong, Arizona State University, Tempe, AZ, United States,
Ziru Li, Zhongju Zhang
Sharing economy, which leverages information technology to re distribute
unused or underutilized assets to people who are willing to pay for the services,
has received tremendous attention in recent years. Its creative business model has
disrupted many traditional industries by fundamentally changing the mechanism
to facilitate the matching of demand with supply. In this research, we investigate
how Uber affects traffic congestion in the urban areas of the United States.
Findings from this research provide evidence on the potential effect of ride
sharing services in the transportation industry, contributing to the understanding
of the sharing economy and government policy decisions.
2 - Room Sharing Economy And Destination Tourism
Wei Chen, University of Arizona, 3750 E Via Palomita, Apt 23103,
Tucson, AZ, 85718, United States, ,
Lijia Xie
While significant debate has surrounded the entry of room-sharing services,
limited empirical work uncovers the impact of such services to traveler activity,
particularly, tourism flow and satisfaction at local destinations. We exploit a set of
natural experiments, the entry of two major room-sharing services, and
, into markets of China between 2011 and 2015. The study
underscores the connection of peer-to-peer accommodation availability to
relocation of traveler spending, extended stays and improved experience which
are critical to the local tourism industry gains. Important implications of theory,
practice, and policy making will be provided.
3 - The Role Of Syndication In Democratizing Capital Flow In Online
Equity-crowdfunding
Qiang Gao, City University of New York, New York, NY, 85719,
United States, , Mingfeng Lin
Equity crowdfunding provides opportunities for startups to raise funds from large
number of online potential investors. However, the issue of information
asymmetry not only remains as the major barrier for financing these early stage
companies but is actually exacerbated by the “virtual” nature of these
marketplaces. This paper examines whether syndication, a group of investors who
collaborate to pool resources and share risks, in online equity crowdfunding, can
alleviate this issue and democratize the access to capital and investment
opportunities. We further investigate the drivers for the formation of such
syndicates.
4 - “Release Early, Release Often”? The Impact Of Release
Frequency In Open-source Software Co-creation
Wei Chen, University of Arizona,
Vish Krishnan, Kevin Zhu
A central virtue of OSS is the contributions from the communities, yet our
knowledge of how to coordinate and maximize the benefit of such contributions
for market success is limited. In this paper, we uniquely formalize, analyze, and
validate the impact of product release frequency as a coordinating mechanism in
the adoption of open-source products. We build a dynamic structural model to
characterize the optimal release strategy from the project owner’s perspective. The
theoretical and empirical results have important implications for managing
technology-enabled collaboration in open-source communities and for research
on open-source software, open innovation, and software adoption.
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Music Row 5- Omni
Consumer Behavior and Pricing Optimization
Sponsored: Behavioral Operations Management
Sponsored Session
Chair: Nikolay Osadchiy, Emory University, Atlanta, GA, United States,
1 - Pricing Under Anticipation
Javad Nasiry, Hong Kong University of Science and Technology-
HKUST, Ioana Popescu
We model the purchase behavior of consumers by accounting for anticipatory
feelings triggered by the prospect of buying at a discount, as well as for the
disappointment when anticipated outcomes fail to materialize. We show that sales
policies can outperform uniform pricing when a monopolist sells to anticipating
customers.
2 - Mental Accounting, Reference Price Adaptation, And The Pricing
Of Flat-rate Contracts
Manel Baucells, University of Virginia, 100 Darden Blvd,
Charlottesville, VA, 22903, United States,
Woonam Hwang
We propose a model where consumers possess a mental account that stores the
worth of items purchased and yet to be consumed. Reference prices act as the
book values of these items, and are determined by a psychological process of
adaptation to the price evoked by the trade. The model is integrative, in that it
explains a wide array of observed anomalies such as sunk-cost effects, payment
depreciation, reluctance to trade, preference for pre-payment, and the flat-rate
bias. We explore the pricing implications of the model when it comes to flat-rate
pricing.
3 - Tell Me What I Want: A Study Of Personalized Assortment
Planning For Learning Consumers
Yulia Vorotyntseva, University of Texas at Dallas, Richardson, TX,
7508, United States,
Dorothee Honhon, Canan Ulu
We model retailer’s and consumer’s simultaneous learning about the consumer’s
idiosyncratic preferences. In each period the retailer chooses an assortment of
products to offer the consumer and learns about her preferences by observing the
choice. The consumer picks one product, gets a noisy signal about its utility and
updates her beliefs in Bayesian fashion. We use this model to study structural
properties of the firm’s optimal assortment policy and to quantify the value of
information about the consumer’s experience, such as feedback surveys.
4 - Optimal Dynamic Upgrade
Xiao Zhang, PhD Candidate, The University of Texas at Dallas, 800
West Campbell Rd, Richardson, TX, 75080, United States,
, Metin Cakanyildirim, Ozalp Ozer
Upgrade, a strategy used in travel industry to balance supply-demand mismatches
among products of different quality levels, is usually implemented either at the
booking time or at the consumption time. We study a revenue management
problem of a firm which sells two products and offers upgrade option anytime
when necessary. The optimal policy specifies the timing of the upgrade option and
how many customers should be offered this option.
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