Decision Science News

CALL FOR PAPERS: MARKETING SCIENCE SPECIAL ISSUE ON BIG DATA

BIG DATA: INTEGRATING MARKETING, STATISTICS AND COMPUTER SCIENCE

SUBMISSION DEADLINE: December 16, 2013

Digital marketing brings unparalleled data on opinions and behavior. Data include structured data, such as numerical data on consumer purchasing, participation in social media, or exposure to online marketing, and unstructured data, such as text, audio, or even video content freely provided by consumers. Because of scale, these data are often called “Big Data,” with principal characteristics of high volume, high velocity, and high variety. High volume implies the need for models that are scalable; high velocity opens opportunities for real-time, or virtually real-time, marketing decision making that may or may not be automated; and high variety may require integration across disciplines with the corresponding sensitivity to various methods and philosophies of research.

The Special Issue draws on recent advances in computer science and statistics to deepen our understanding of consumer behavior and to improve the practice of marketing in data-rich environments. We encourage new research that spans boundaries to address important marketing science topics. Submitted papers might address marketing problems that could not be resolved prior to the Big Data era. Other papers might combine structured and unstructured data for greater insight. Still other papers might use new methods that scale well to big data. We are open to the use of different research methodologies and we are particularly interested in innovative combinations of methods. We welcome scalable methods that mine large volumes of data, but such papers should address validation, say with out-of-sample testing. Field experiments to test new methods are welcome. We welcome machine learning, dynamic programming, adaptive regression, visualization methods, text processing, and other methods if scale can be demonstrated. We are less interested in existing methods applied to existing problems but with large data sets, conceptual papers on the role of big data, or anecdotes of how big data alone provided managerial insights.

Please submit your manuscript online via ScholarOne Manuscripts at http://mc.manuscriptcentral.com/mksc. When choosing Manuscript Type in Step 1 of the submission process, enter Special Issue – Big Data. All papers will go through the standard review process. Questions should be directed to Frances Moskwa, Managing Editor (frances.moskwa at informs.org).

Special Issue Editors
Pradeep Chintagunta, University of Chicago
Dominique Hanssens, University of California, Los Angeles
John Hauser, Massachusetts Institute of Technology

Special Issue Associate Editors
Sinan Aral, Massachusetts Institute of Technology
Anand Bodapati, University of California, Los Angeles
Eric Bradlow, University of Pennsylvania
Theodoros Evgeniou, INSEAD
David Godes, University of Maryland
Dan Goldstein, Microsoft Research
P.K. Kannan, University of Maryland
Peter Lenk, University of Michigan
Rob McCulloch, University of Chicago
Carl Mela, Duke University
Oded Netzer, Columbia University
Koen Pauwels, Ozyegin
Peter Rossi, University of California, Los Angeles
Olivier Toubia, Columbia University

PROFESSORSHIP IN OPERATIONS AND INFORMATION MANAGEMENT AT THE UNIVERSITY OF PENNSYLVANIA

Department of Operations and Information Management
The Wharton School
UNIVERSITY OF PENNSYLVANIA

The Operations and Information Management Department at the Wharton School is home to faculty with a diverse set of interests in decision-making, information technology, information-based strategy, operations management, and operations research. We are seeking applicants for a full-time, tenure-track faculty position at any level: Assistant, Associate, or Full Professor. Applicants must have a Ph.D. (expected completion by June 2014 is preferred but by June 30, 2015 is acceptable) from an accredited institution and have an outstanding research record or potential in the OPIM Department’s areas of research. Candidates with interests in multiple fields are encouraged to apply. The appointment is expected to begin July 1, 2014 and the rank is open.

More information about the Department is available at: http://opimweb.wharton.upenn.edu/

To apply please visit our secure web site: https://opimweb.wharton.upenn.edu/faculty/faculty-recruiting/

Interested individuals should complete and submit an online application. This includes:

· A curriculum vitae
· At least one sample publication or working paper

Applicants are encouraged to submit additional research publications. Applicants to an Assistant Professor position must ensure that three letters of recommendation are submitted by their references. Associate and Full Professor must provide three names as references.

To ensure full consideration, materials should be received by November 1st, 2013.

Contact:

OPIM Department
The Wharton School
University of Pennsylvania

3730 Walnut Street
500 Jon M. Huntsman Hall
Philadelphia, PA 19104-6340

The University of Pennsylvania values diversity and seeks talented students, faculty and staff from diverse backgrounds. The University of Pennsylvania is an equal opportunity, affirmative action employer. Women, minority candidates, veterans and individuals with disabilities are strongly encouraged to apply.

OBSERVATIONAL STUDIES: “CONVINCING PEOPLE OF THINGS WITHOUT ACTUALLY GENERATING EVIDENCE”

The New York Times had an article on the widespread confusion about whether skipping breakfast causes you to gain or lose weight. It seems there’s no substantial evidence that skipping breakfast has any effect on obesity.

What we found most amusing was this passage with a quote from Dr. David Allison:

Dr. Allison said that the true relationship between eating breakfast and body weight, if there is one, was still an open question. But observational studies that tout an association between the two are churned out “just about every week,” despite doing nothing to actually test or prove the claim.

“At some point, this becomes absurd,” he said. “We’re doing studies that have little or no value. We’re wasting time, intellect and resources, and we’re convincing people of things without actually generating evidence.”

It reminds us of the recent paper in which the authors decided to pick 50 common cookbook ingredients at random and found that 80% of them were claimed to cause or prevent cancer. Little evidence was found for any of the claims.

Here’s an idea: If the reason behind having IRB approval for studies is to prevent their doing any harm, why isn’t there an IRB approval process for publishing (as opposed to conducting) observational health and nutrition studies? They seem to do a lot of harm in making people change their diets and behavior for no good reason, not to mention the needless worry they cause.

Large scale randomized trials would be exempt from this pre-publication IRB process. Wink.

Photo credit:http://www.flickr.com/photos/beautifulcataya/5089823061/

CARPE DIEM: SEIZE THE DAY

Our friend Pete McGraw often says “today is a big day”. When people ask why, he says that every day is a big day. As he writes on his blog, Pete saw his parents die well before their life expectancies, he saw his house, which sits a mile above sea level, suddenly flooded. It reminded him that life is short and can change for the worse very quickly.

Something to keep in mind when deciding about what risks to take and how much weight to put on the distant future.

See Pete’s flooded house on the Boulder news:

Photo credit: http://www.flickr.com/photos/shankargallery/9806276953/

NYCE: NOVEMBER 1, 2013 AT THE SIMONS FOUNDATION IN NEW YORK CITY

Call for Participation:
New York Computer Science and Economics Day (NYCE) will be held on November 1, 2013 at the Simons Foundation in New York City. The goal of NYCE Day is to bring together researchers in New York and surrounding areas who are interested in problems at the intersection of economics and computation. Our invited speakers this year are

• Nicole Immorlica
• Panos Ipeirotis
• Christos Papadimitriou
• Rakesh Vohra.

More details about the program can be found on the website:

https://sites.google.com/site/nycsecon2013/home

Submissions:
The deadline for submissions for short talks and posters is October 8th. Topics of interest to the NYCE community include (but are not limited to) the economics of Internet activity such as search, user-generated content, or social networks; the economics of Internet advertising and marketing; the design and analysis of electronic markets; algorithmic game theory; mechanism design; and other subfields of algorithmic economics. We welcome posters and short talks on theoretical, modeling, algorithmic, and empirical work. You can submit your abstract via our submission form at:

https://sites.google.com/site/nycsecon2013/posters-and-short-presentations

Registration:
If you plan to attend the workshop please register online before October 15, 2013 at

https://sites.google.com/site/nycsecon2013/registration

Please note that the venue for NYCE 2013 has a limited space, and on-site registration may only be available on a (limited) first-come first-served basis.

Organizing Committee

• Jason Hartline (Northwestern University)
• Vahab Mirrokni (Google Research)
• Jenn Wortman Vaughan (Microsoft Research, New York City)

PARTITION EFFECTS IN TIPPING

When you order room service in a hotel, the bill often includes a “delivery charge” of a few dollars plus a “service charge” of close to 20%. When you sign the bill, there is always a blank that says “Additional gratuity”.

From a decision science perspective, it would seem odd if people who generally tip less than 20% on deliveries add something to the “additional gratuity” line simply because the tip has been partitioned into two parts: a required 20% part and an “add what you will” part. This similar to the phenomenon of “partition dependence” in the judgment and decision making literature.

The question we had was whether people add an additional gratuity in this situation.

We are not the only ones who had this question. We quickly found a dozen URLs (see URLs at bottom) of forums in which this issue was discussed.

Looking at the forum posts, a few themes recurred:

• People said that it was never clear if the service charge went to the delivery person (making it the gratuity) or to the hotel or if it was spread around.
• People who did not tip extra tended to be stronger in their opinions than those who did.
• People who did tip extra tended to say they’d add about two dollars, usually in cash.
• Websites varied in their proportion of respondents who tip extra.

To the last point, we combed through the forums and coded as many posts as we could as pro- or con- tipping extra. The results are below, where each row has the syntax:

WEBSITE: #_TIPPING_EXTRA / #_RELEVANT_COMMENTS = %_TIPPING_EXTRA

RESULTS
Fodors: 5 / 23 = 21%
Chowhound: 10 / 23 = 43%
Hotelchatter: 1 / 5 = 20%
Metafilter: 3 / 11 = 27%
Milepoint: 7 / 16 = 44%
Datalounge: 2 / 4 = 50%
Yahoo Answers: 2 / 11 = 18%
Flyertalk: 7 / 19 = 37%

Adding this all together we get:

Grand Total 37 / 112 = 33% tipping extra

Because generosity is socially desirable, those who do tip extra may be more likely to comment than those who don’t. This selection effect would suggest 33% is too high. On the other hand, there may be a sets of people who do add an additional tip for various reasons (e.g. due to misunderstanding, generosity, or being well off) but don’t participate in forums for various reasons. This would suggest that 33% is too low. We’re not comfortable guessing in which direction our estimate is biased.

Suppose that a third of people do tip more when the tip is partitioned than when it’s not. How far this can be pushed? Would it go up if the bill read as follows?

Delivery charge: $5
Base Service charge: 15%
Supplemental Service charge: 10%
Additional Gratuity: ________

NOTES

• When coding the forum posts, we tried to capture what people most always do. We tried to ignore comments that said things like “it depends” or dodged the question. As we got tired, we may have drifted in our coding policy a bit.
• If you want to read something funny about hidden fees, see Ian Frazier’s “From the Bank with Your Money on Its Mind“.
• If you want to read another DSN post on tipping, see: Tipping Heuristics

URLS OF FORUMS DISCUSSING TIPPING EXTRA

• http://www.fodors.com/community/united-states/room-service-tipping-question.cfm
• http://chowhound.chow.com/topics/637417
• http://chowhound.chow.com/topics/673942
• http://chowhound.chow.com/topics/483414
• http://chowhound.chow.com/topics/475569
• http://www.hotelchatter.com/story/2008/8/21/141155/151/hotels/HotelChatter_OpenThread_%3A%3A_Should_We_Tip_Extra_for_Room_Service%3F_
• http://ask.metafilter.com/46319/Should-I-tip-extra-for-room-service
• http://milepoint.com/forums/threads/do-you-tip-for-room-service.3805/
• http://www.datalounge.com/cgi-bin/iowa/ajax.html?t=11525842#page:showThread,11525842
• http://answers.yahoo.com/question/index?qid=20070305164501AAqaVCI
• http://www.flyertalk.com/forum/archive/t-711790.html
• http://www.flyertalk.com/forum/starwood-preferred-guest/175647-room-service-tipping.html

Photo credit:www.flickr.com/photos/merydith/4576874311/

A GLOBAL VIEW

The Guardian newspaper in the UK made this rather amazing interactive infographic (click through to interact) on causes of death, conditioned on age and region, around the world.

They also provide, below, a display of ranked causes of death, and how they’ve changed since 1990.

How do people die? One thing that pops out is how “cardio and circulatory diseases” increase in probability with age and ultimately become the most likely cause.

Also striking is that in a number of regions of the world, most deaths occur before age 5.

REGIONAL AMERICAN ENGLISH

When Decision Science News was in college, we used to volunteer at the Dictionary of American Regional English. We learned things like if you ask folks in the US:

What generic word do you use to describe carbonated soft drinks? (Note that these could be of any brand or type, Coca-Cola, Pepsi, 7-Up, etc. We are concerned with the overall word, not a specific brand.) If you have changed the word you use at some point in your life, please enter the term you first used when you learned English.

… you get data that look like the above. People in the Midwest tend to say “pop”, people in the South tend to say “Coke” (even when they are not referring to a Coke ™), and everybody else tends to say “soda”. That image is from http://www.popvssoda.com. Fine.

Back when Decision Science News as a first year assistant professor at London Business School, we presented this chart to make a point about geographic differences. An American student said “That’s wrong. I’ve been all over and that’s just not true”. This made for an awkward teaching experience.

Years pass, Twitter is invented, and data scientist Edwin Chen decides to analyze Twitter tweets for soft drink terms. The result:

Same deal.

ADDENDUM

Linguist Bert Vaux (a friend of a friend) shared some valuable notes

“The best coke database is indeed Alan McConchie’s…The last time I checked, about 7-8 years ago, Alan already had more than 400,000 data points for coke/pop/soda.

The next best database for that and 121 other variables is my old Harvard survey from 2002-3, for which I collected data from about 50,000 Americans. I’ve mapped those and some of my other surveys using the Google maps engine here:

http://www.tekstlab.uio.no/cambridge_survey

You two have probably also come across Josh Katz’s recent mappings of my old Harvard data:

http://www4.ncsu.edu/~jakatz2/project-dialect.html“

DO NOT LIE ABOUT RISK: PRESENT PROBABILITIES TRUTHFULLY OR NOT AT ALL

On July 7th 2005, four bags containing bombs were left on London public transport. They exploded, killing 52 people. Bombs in two bags at the Boston Marathon this year killed three.

We can imagine the policy-maker’s thinking when they came up with this campaign. “If we had reports of all the suspicious bags, we’d be able to stop some of these bombs from going off. But when people see a left bag, they probably think it’s nothing, and so they don’t report it. So, let’s just lie. That way, they’ll be so scared that they’ll report every bag. We’ll stop some bombs. And that justifies the lying. Here how about this?”:

If it doesn’t feel right, it probably isn’t.

This reminds of of conversations we have had about mortgages. To prevent another meltdown, some policy-makers suggest exaggerating risks of foreclosure to scare people into choosing less expensive houses.

At Decision Science News, we are all for getting people to report suspicious packages, to choose safer mortgages, to exercise and eat well to safeguard their health, but we are dead set against mis-reporting probabilites to scare people into action.

Don’t say something will probably happen when it won’t.

Let’s look at London, in an example from Michael Blastland and David Spiegelhalter’s book The Norm Chronicles: Stories and Numbers About Danger

Since the London attacks, some 250,000 bags have been left on London Transport.

None have turned out to be bombs.

If we define a “present era” as eight years before and after 7/7, the probability of a left bag on London Transport being a bomb is something like 4 in 500,000 or 1 in 125,000. If we consider all the bags left in all the large metropolises of Europe and North America over a decade, we’re talking about microscopic chances.

No trying to be fresh here, but despite what the very well-intentioned New Jersey officials are saying above, which implies a greater than 50% probability of foul play, it’s more the case that:

If it doesn’t feel right, there’s a 0.000008 chance it isn’t.

Again, we’re all for reporting every suspicious bag. Perhaps 7/7 and Boston events could have been prevented. And we’re not saying that “Suspicious bags: Almost certainly safe” is how the poster should read. We’re just saying that there are many ways to bring about desirable behaviors that don’t involve fibbing. For example: Make it easier to report suspicious bags, provide an email address, appeal to reason, remind people of how awful it is when bombs to go off, emphasize how many things could have been prevented if everyone reported everything, and so on.

And we’re not against scaring people. Emotions drive decisions, and getting people to think about possible consequences can improve long-run decision making. But you can present truthful, graphic depictions of outcomes without lying about the probabilities of these outcomes. It’s the product of the probability and the outcome that counts.

To this, you might say “Oh, Decision Science News, don’t you realize that people are irrational, biased, myopic, self-serving, probability-neglecting innumerates who won’t do the right thing unless you make up stories to scare them?”. To this we say “No. First, assembling an ever-expanding list of so-called biases is not science. Science is proposing and testing models of the larger system that predicts when these effects appear, disappear, and invert. Second, the Santa Claus approach of lying to bring about good behavior is not only dishonest but self-defeating. People will quickly learn not to trust you and will ignore all your posters and warnings.”

Improved risk literacy will help people lead happier, healthier and safer lives. But for people to become risk literate, they need accurate risk estimates, not phony probabilities that cry wolf.

ASSOCIATION FOR CONSUMER RESEARCH 2013 CONFERENCE

What: ACR 2013 conference
Where: Hilton Palmer House Hotel, Chicago, IL (map)
When: October 3-6, 2013
Conference Co-chairs:

• Simona Botti, London Business School
• Aparna Labroo, University of Toronto

Registration

ACR 2013: Making a Difference

The theme of this conference is “Making a Difference,” which was inspired by the energy of Chicago, by its ability to change, adapt, and remain cutting edge in creative domains such as architecture, food, arts, and music. We hope that this conference will be an opportunity for consumer researchers from all over the world to discuss ways in which our ideas can make a difference to established theory and practice, as well as advance our understanding of consumers in the lab and in the field.

But Chicago is also a fun city. We want this conference to be a forum in which exciting thoughts, viewpoints, and findings are shared among people who have in common the same passion for rigorous, challenging, and cool consumer research.

Special Events (free with registration)
“Mediation, Contrasts, and LISREL” Workshop
“Design Your Studies with Qualtrics” Workshop
“How to Make a Good Consumer Research Video” Workshop
“New Reviewer Training Session” Workshop
“Advanced Reviewer Training Session” Workshop

Special Events (paid)
Saturday Night Party at House of Blues
Sunday Architectural Boat Tour
Sunday guided tour of the Art Institute of Chicago