Informs 2015

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WC42INFORMS Charlotte – 2011
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2 - Comprehensive Analysis of the U.S. Army’s Global
Assessment Tool
Cardy Moten, Maj, TRADOC Analysis Center-Monterey, 700 Dyer
Road, Room 183, Monterey, CA, 93943, United States of
America,
The focus of this research is to investigate new interpretations of the Global
Assessment Tool in order to provide more informed feedback to the Soldier and
improve prediction of Soldier outcomes. We used factor analysis, cluster analysis,
and data visualization techniques to evaluate similarities and differences between
the services and provide a more comprehensive picture of the component data
that is more readily understood by Soldiers.
WA30
30-Room 407, Marriott
Information Systems for E-Business/Commerce
Contributed Session
Chair: Anwesha Bhattacharjee, Student, University of Texas, Dallas,
2200 Waterview Pkwy, #1836, Richardson, TX, 75080, United States of
America,
1 - Investigating the Effect of Social Connections on Usefulness of
Online Reviews
Pouya Khansaryan, University of Connecticut, 101 South
Eagleville, Apt. 18B, Storrs, CT, 06268, United States of America,
Online reviews are a form of eWOM which are nowadays available to prospective
customers. In this study, we try to answer the question: “what are the key factors
that contribute to the consumer’s perception of the usefulness of online
reviews?”. The data from Yelp in different time spots show that star ratings, total
votes, review length, average writer’s star rating, number of fans and elapsed time
are the most significant measures for the perceived usefulness.
2 - Online Activities in Virtual World and Money Spending in
Real World
Gwangjae Jung, Korea Information Society Development
Institute, 18, Jeongtong-ro, Deoksan-myeon, Jincheon, Korea,
Republic of, Youngsoo Kim
We examine the relationship between online activities virtual world and money
spending in real world. We collected users’ log data in an online game from Feb.
to Aug. 2010. Our analyses show that virtual money spending complements real
money spending in playing an online game. Another finding is that group play in
an online game facilitates real money spending on avatar decorations, but not on
gaming efficiency. Real money spending also decreases as users advance to the
latter stage of game.
3 - Differences in Hedonic and Utilitarian Apps through Consumer
Addiction, Frustration and Evaluation
Bidyut Hazarika, University of Colorado Denver,
1475 Lawrence St, Denver, CO, 80202, United States of America,
Madhavan Parthasarathy,
Jahangir Karimi, Jiban Khuntia
Hedonic and utilitarian apps differ in addiction, frustration and subsequent
evaluation scores. This study analyzes scores on these factors for more than 18136
apps data to establish this differentiation values using interaction models and
econometric analyses.
4 - How Could We Cope with Malicious Rater? A New Detection
Method for Trustworthy Reputation Systems
Yuanfeng Cai, CUNY—-Baruch College, 55 Lexington Ave,
New York, NY, United States of America,
, Dan Zhu
Reputation systems are vulnerable to rating fraud. To address it, we use data from
Tripadvisor, Expedia and Amazon to empirically exploit the rating time series
features of malicious rater. Then we propose the two-phase method for detection.
First, it examines the rating series associated with each entity and filters out those
under attack. Second, the clustering method is applied to discriminate malicious
raters. Experimental studies have demonstrated the effectiveness of the proposed
method.
5 - Searching the Global Distribution System: A Double-edged Sabre
Anwesha Bhattacharjee, Student, University of Texas, Dallas,
2200 Waterview Pkwy, #1836, Richardson, TX, 75080, United
States of America, Vijay Mookerjee,
Mehmet Ayvaci, Radha Mookerjee
As the demand for travel grows, so does the need for travel agencies. Travel
agencies, in turn, use a global distribution system to find the appropriate service
for their clients. In this paper, we look at one such travel service market segment:
hotel shopping. We identify search behaviors among agencies and we identify the
tradeoff for the global distribution system itself which invest millions on setting
up the search want to increase the number of bookings with the minimum
number of searches.
WA31
31-Room 408, Marriott
Data Mining for Environmental and Natural
Hazard Applications
Sponsor: Data Mining
Sponsored Session
Chair: Seth Guikema, Associate Professor, Johns Hopkins University,
3400 N Charles Street, Ames Hall 313, Baltimore, MD, 21218, United
States of America,
1 - Data Mining Approaches to Characterize Non-uniform Wind Farm
Power Production
Andrea Staid, PhD Candidate, Johns Hopkins University, 3400 N.
Charles St., 313 Ames Hall, Baltimore, MD, 21218, United States
of America, Claire Verhulst, Seth Guikema
Power production of wind farms with non-uniform layouts is more difficult to
analyze using traditional wake-decay models. We present some of the
discrepancies that arise when modeling these types of farms and highlight the
sources of error. We then present new methods to characterize farm production
based on data mining instead of wake modeling, and we show the benefits of
using these methods in conjunction with more traditional means.
2 - Analysis of Low Probability Streamflow Outcomes in the
Mid-atlantic Region
Gina Tonn, PhD Candidate, Johns Hopkins University,
115 Broadbent Road, Wilmington, DE, 19810,
United States of America, , Seth Guikema
Standard flood frequency analysis methods are widely used, but involve much
uncertainty and low probability outcomes can occur. In this study, statistical
analysis is used to identify watershed characteristics that are correlated with low
probability streamflow outcomes. Methods include a Random Forest model and
clustering analysis.
3 - Data Mining for Understanding Tsunami Death Rates in Japan
Seth Guikema, Associate Professor, Johns Hopkins University,
3400 N Charles Street, Ames Hall 313, Baltimore, MD, 21218,
United States of America, , Roshanak Nateghi
Then 2011 Tsunami in Japan caused widespread destruction and led to a large
number of deaths. It was the most recent in a strong of tsunamis in the Tohoku
region of Japan. We use data from the 1896, 1933, 1960, and 2011 tsunamis
together with modern data mining methods to better understand the factors
affecting death rates during these events.
4 - Prediction of Mean Harvest Weight of Royal Gala Apples
Tom Logan, PhD Student, University of Michigan, 3700 N Charles
Street, Baltimore, MD, 21218, United States of America,
Seth Guikema, Stella Mcleod
Early prediction of the mean harvest size of apples is useful for decision makers in
the apple and horticultural industry. Decisions including logistics and marketing
are made prior to harvest and are generally based on estimates of the crop. A
random forest model was developed using data for the apple variety Royal Gala
from orchards within the Hawkes Bay Region of New Zealand. For the eight years
of data available it has been shown to have a mean predictive error of 2.4%.
WA32
32-Room 409, Marriott
Data Mining with Marketing Applications
Contributed Session
Chair: Elham Khabiri, IBM, 1101 Kitchawan Rd, Yorktown Heights, NY,
United States of America,
1 - Evaluating Database Marketing Models: More than Meets the Eye
Sam Koslowsky, Senior Analytic Consultant Modeling Solutions
and Delivery, Harte Hanks, 2118 Avenue T, Brooklyn, NY, 11229,
United States of America,
Managers are most pleased with using the gains table to assess their predictive
models. Identifying more ‘HAVES’ at the top, and fewer on the bottom is most
desirable. But, more needs to be examined. Some use standard statistical criteria.
This may be fine. But, some common sense features are frequently ignored as it
relates to model evaluation and the gains table. These include variations in lift,
unevenness in decile performance, the stability of predictions and the
interpretations of results.
WA32