Informs 2015

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INFORMS Philadelphia – 2015
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3 - The Impact of Digital Natives on B2B Purchasing Decisions
Haris Krijestorac, PhD Student, Information Systems, University
of Texas at Austin, 3106 Speedway, Apt. B203, Austin, Tx, 78705,
United States of America,
Our study seeks to better understand how businesses buys from businesses in a
marketplace with increasingly digitally oriented decision makers. We analyze how
‘Digital Natives’ and ‘Digital Immigrants’ differ when influencing purchasing
decisions in a business-to-business (B2B) context. To this end, we are surveying
purchase decision makers at B2B companies. The results of our survey can help
B2B companies better understand their target market, and refine their approach
to marketing and sales.
4 - Improving The Persuasive Effectiveness of Anti-piracy
Educational Campaign Messages
Bong Keun Jeong, Assistant Professor, Metropolitan State
University of Denver, Campus Box 45, P.O. Box 173362, Denver,
CO, 80217, United States of America, ,
Tom Yoon
Prior literature suggests that anti-piracy educational campaign is an effective way
to dissuade users from downloading illegal contents. However, most comments
and opinions on public campaigns are against what they seek to achieve. The
objective of this study is to explore ways to improve the effectiveness of anti-
piracy campaigns. We examine the impact of message frame, issue involvement,
risk perception, and message evidence on the persuasive effectiveness of anti-
piracy campaign messages.
5 - Collective Innovation in 3D Printing: Novelty, Reuse and
Their Interplay
Harris Kyriakou, Stevens Institute of Technology, 1 Castle Point
on Hudson, School of Business 642, Hoboken, NJ, 07030, United
States of America, , Jeffrey V. Nickerson
We present an empirical fitness landscape of open hardware designs and examine
how (i) digital artifact reuse, (ii) novelty and (iii) their interaction affect the
success of open innovation endeavors. We use mixed research methods to draw
insights about how members of open innovation communities build upon
preexisting work and collaborate to create something new. A theory of search in
the design space is used to explain how these seemingly contradicting forces affect
innovation.
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31-Room 408, Marriott
Data-driven Operations Management of
Energy Systems
Sponsor: Data Mining
Sponsored Session
Chair: Adrian Albert, Senior Data Scientist, C3 Energy, 1300 Seaport
Blvd, Suite 500, Redwood City, CA, 94063, United States of America,
1 - Data-Driven Structural Health Monitoring of Large-Scale
Power Grids
Adrian Albert, Senior Data Scientist, C3 Energy, 1
300 Seaport Blvd, Suite 500, Redwood City, CA, 94063,
United States of America,
Physical asset failure on power grids leads to costly loss-of-service. In the past,
energy utilities have only performed maintenance retroactively. Yet new sensing
and data processing allow for a near real-time picture of network state. However
in practice the sensors used to detect faults often malfunction. Here we describe a
system for predicting faults on certain asset types. We also develop a model for
optimizing sensor replacement as to ensure desired operation profiles.
2 - Simulating Annual Variation in Load, Wind, and Solar by
Representative Hour Selection
John Bistline, Technical Lead And Project Manager, Electric
Power Research Institute, 3420 Hillview Avenue, Palo Alto, CA,
94305, United States of America,
The spatial and temporal variability of renewables have important economic
implications for investment and system operation. This talk describes a method
for selecting representative hours to preserve key distributional requirements for
regional load, wind, and solar time series with a two orders of magnitude
reduction in dimensionality. We discuss the implementation of this procedure in
the US-REGEN model and compare impacts on energy system decisions with
more common approaches.
3 - C3 Cyberphysix: An Operating System for the Smart Grid
Mehdi Massoumy, Senior Data Scientist, C3 Energy,
1300 Seaport Blvd, Suite 500, Redwood City, CA, 94063,
United States of America,
We propose an operating system that aggregates data from disparate data sources
across the smart grid value chain, applies analytics on the data, and makes
optimal decisions for the operation of the system. The proposed operating system
in real-time analyzes the requirements of the supply side, and requirements of
the demand and performs optimal operation of the system while taking into
account the constraints of all the components of the grid.
4 - Data-Driven Management of Large, Distributed Energy Systems –
The Case of Residential Solar Networks
Amir Kavousian, Data Scientist, Sunrun Inc., 747 Anderson St,
San Francisco, CA, 94110, United States of America,
This talk presents the data-driven operation of one of the largest residential solar
fleets in the US. I demonstrate how advanced statistical methods are deployed to
proactively identify operational issues and their root causes. The data-driven
insights are fed back into operations, customer relations management, sales,
marketing, product, and design teams. In particular, I explain a novel method to
estimate the long-term, gradual decrease in solar systems productivity, known as
degradation.
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32-Room 409, Marriott
Data Mining Methodology
Contributed Session
Chair: Xuelei Ni, Associate Professor, Kennesaw State University,
365 Cobb Ave, Suite 209, MD# 1601, Kennesaw, GA, 30144,
United States of America,
1 - Multivariate Statistical Analysis in NPD: Customization of a
Sustainable Product
Istefani Paula, Professor, UFRGS, Osvaldo Aranha street 99,
Porto Alegre, 90035190, Brazil,
Manoel Silveira, Angela Marx, Ana Facchini,
Márcia Elisa Echeveste
The aim of this poster is to present an approach to identify clusters of consumers
using Chi squared Automatic Interaction Detector. Based on the clusters formed it
is possible to find different segments and to associate requirements demanded by
them what allows the customization by means of product derivation. The method
contributes to the Requirements Management area illustrated in the development
of an eco friendly household cleaning product.
2 - Change Detection using Local Amplitude and Phase
Synchronization in Complex Dynamical Systems
Ashif Sikandar Iquebal, Texas A and M University, 4501 College
Main St, Apt. 1002, Bryan, TX, 77801, United States of America,
, Satish Bukkapatnam
We propose a novel technique to detect changes in dynamical systems using local
phase and amplitude synchronization among its constituent signals, generated
using a non-parametric time scale decomposition method. We identify a set of
components that is likely to capture the information about dynamical changes of
interest using a maximum mutual agreement concept. Finally, a statistic is defined
that can be employed to detect changes in complex systems where other methods
fail.
3 - Between-Participants’ Discourse Bias in Comments
Classification: Adjusting Tf-idf
Inbal Yahav, Lecturer, Bar Ilan Business School, Bar Ilan
University, Ramat Gan, Is, 52900, Israel, ,
David Schwartz
Text mining has gained great momentum in recent years. A leading research
branch in this regard is the field of comment classification. An essential pre-step
in comment classification is words processing, commonly achieved by using the
tf-idf formula. This work reveals, analyses and correct the bias introduced by
between-participants’ discourse to tf-idf. We show that ignoring this bias can
manifest in a non-robust method at best, and can lead to an entirely wrong
conclusion at worst.
4 - High-Dimensional Semi-Supervised Learning via a
Fusion-Refinement Procedure
Xuelei Ni, Associate Professor, Kennesaw State University,
365 Cobb Ave, Suite 209, MD# 1601, Kennesaw, GA, 30144,
United States of America, , Xiaoming Huo,
Zhikun Lei, Renfu Li
This paper develops a sufficient dimension reduction (SDR) approach for the
high-dimensional semi-supervised learning (SSL) problem. We first modify the
fusion-refinement procedure, an SDR technique, to extract the essential features
for a lower-dimensional representation, then apply an SSL algorithm in the
lower-dimensional feature space to tackle the SSL problem. Numerical
experiments demonstrated the effectiveness of the new technique.
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