2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - Data Analytics Approaches For Winning Service Contracts:
Development And Impacts on Practice
Aly Megahed, IBM Research - Almaden, San Jose, CA, 95123,
United States, , Taiga Nakamura,
Kugamoorthy Gajananan, Mark Smith, Gregory Heim
Service providers in B2B often must prepare bids to win service outsourcing
contracts. For high-value IT service outsourcing deals, the solution design and
deal pricing process can be a complicated, expensive gamble. We present an
approach based in data analytics to automate and customize the often manual
practices used to configure such contract proposals. We propose a base model and
model enhancements, demonstrating their performance using historical contract
data and third-party vendor market data. The actionable methods demonstrate
how data analytics tools can enable more effective manager decisions regarding
contract proposal solution design and pricing.
4 - Welfare Implications Of Congestion Pricing: Evidence from
SFpark
Hsin-Tien Tsai, University of California, Berkeley,
1822 Francisco St., Apt 4, Berkeley, CA, 94703, United States,
, Pnina Feldman, Jun Li
SFpark is a congestion pricing program for street parking implemented in San
Francisco. We investigate whether consumers benefit from congestion pricing
using data from this program. We build a structural model of consumer search
and quantify the change in consumer welfare.
5 - On a Variation Of Two-part Tari Pricing Of Services:
A Data Driven Approach
Charles Thraves, Massachusetts Institute of Technology,
Cambridge, MA, United States, , Georgia Perakis
We present a pricing optimization problem for the data plans of a big satellite
firm. First we address the problem of missing data (as reservation prices are not
directly observed especially for those who are not current customers). We
formulate the price optimization problem as a MIP and develop properties and
heuristics in order to solve realistic instances providing analytical lower bounds of
their performance. We conclude that with our method the company can increase
its profits by more than 10% and outperform the current plans’ prices even under
misspecifications of the assumptions.
TC55
Music Row 3- Omni
Inventory Management V
Contributed Session
Chair: Hueon Lee, PhD Candidate, University of Arkansas, 4207 Bell
Engineering Center, 1 University of Arkansas, Fayetteville, AR, 72701,
United States,
1 - Long Term Outsourcing Under Stochastic Learning And
Information Asymmetry
Ting Luo, UT Dallas, 7208 Fair Valley Way, Plano, TX, 75024,
United States,
We study a firm’s procurement and selling decisions in a multiclass demand and
multisupplier inventory system. We show that optimal procurement is driven by
multisourcing and intertemporal substitution, while optimal selling is driven by
customer segmentation and intertemporal rationing.
2 - Selling Luxury Fashion Online With Social Influences
Bin Shen, Donghua University, Xuri Building, 1882 Yanan Road,,
Donghua University, Shanghai, China,
In the luxury fashion retailing industry, consumers can be categorized into the
groups of fashion leader and fashion follower. These two groups influence one
another and create social influences in the market. In this paper, we construct an
analytical model to examine the effects of demand changes on a luxury fashion
supply chain with social influences. We consider the case when the supply chain
consists of one supplier and one online retailer providing differentiated services to
different groups of consumers.
3 - A Multi-product Dynamic Block Stacking Problem With
Deterministic Demand
Hueon Lee, PhD Candidate, University of Arkansas, 4207 Bell
Engineering Center, 1 University of Arkansas, Fayetteville, AR,
72701, United States, Kelly Sullivan,
John A White
Block stacking is a commonly used storage method for palletized loads where unit
loads are stacked on top of each other and stacks are aligned in storage rows
having different depths. In a multi-product storage system each product is
assigned to storage rows having a specific depth. As the inventory level changes
for a product, it can be relocated to storage rows having a different depth if
relocation minimizes the cost of relocation and the cost of storage space. In our
formulation, we require all inventory of a product to be stored in rows having the
same depth. With the assumption of a given layout and known inventory cycles,
we formulate the problem as a variation of the multicommodity flow problem.
TC56
Music Row 4- Omni
Managing Sales in On-demand Economy
Sponsored: EBusiness
Sponsored Session
Chair: Michelle Wu, Washington State University, WA, United States,
1 - We Are On The Way: Analysis Of On- Demand Booking Systems
Guiyun Feng, Student, University of Minnesota, 1006 27th
Avenue SE, Apt E, Minneapolis, MN, 55414, United States,
, Guangwen (Crystal) Kong, Zizhuo Wang
On-demand platforms such as Uber allow passengers with smartphones to submit
trip requests and match them to drivers based on their locations and drivers’
availability. We build a model to analyze the efficiency of such on-demand
systems and compare it to systems where people hail taxis on streets. We simulate
customers’ waiting time in the two different systems and find that customers’
waiting time with on-demand system can be higher than street hailing. We
provide a cap policy that takes advantages of both on-demand system and street
hailing in order to minimize customers’ waiting time.
2 - Conform Or To Be Cast Out: Quantifying The Effect Of Platform
Endorsement And Consumer Generated Reputation In Online
Service Marketplace Demand System
Yong Tan, University of Washington, ,
Jinyang Zheng, Youwei Wang
We estimate demands for online service to understand heterogeneous sensitivity
to platform endorsement and consumer generated reputation, and to investigate
“conform or to be cast out” policy which is applied to force sellers to improve
platform endorsement. Our finding shows individuals exhibiting consistent
sensitivity to consumer generated reputation, but perceiving platform
endorsement differently. With regard to the policy, we find that even though
casting out reduce variety of sellers, the negative effect is offset by conforming
sellers’ improvement. Furthermore, we find sellers’ further quality escalation in
the establishment of new equilibrium, benefiting consumer welfare.
3 - Measuring Consumer Surplus In The On Demand Economy The
Case Of Ride Sharing
Meng Liu, MIT Sloan, Cambridge, MA, United States,
Uber and Lyft, two pioneer ride-sharing platforms have seen dramatic growth
over the last few years. To understand their roles and impacts on the economy,
we estimate the consumer welfare of these platforms in a structural demand
model for rides. In our model, consumers choose their rides based on price,
convenience, brand, and unobserved characteristics. Our identification leverage
on the taxi/Uber/Lyft trip records from the New York City, and Uber/Lyft surge
price and waiting time at granular location-time levels. We contribute to the
understanding of the On-Demand Economy by providing evidence of an increase
in consumer welfare due to the fast-growing satisfied instantaneous demand.
4 - Mobility Analytics For Parking Support
Michelle Wu, Washington State University,
Zachary Owen, David Simchi-Levi
Ford is developing smart mobility business model as part of the company’s
strategic plan to deliver the next level of connectivity, mobility, and customer
experience. We develop analytics for dynamic pricing strategies that enable
efficient matching of supply with demand.
TC56