Decision Science News

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

BEHAVIORAL DECISION RESEARCH IN MANAGEMENT 2014

BDRM 2014 Website

Our LBS colleagues and Yuval write:

The Behavioral Decision Research in Management (BDRM) Conference will be held on July 17-19, 2014 at London Business School. Please watch your email for more information about the conference and the submission deadline after the summer. In the meantime, save the date and spread the word!

Also announcing “The Greater Good” pre-conference in partnership with the Journal of Marketing Research, which will focus on behavioral decision research that can contribute to understanding and fixing pressing social needs. The pre-conference will take place at London Business School on July 17, 2014. For questions about the pre-conference, contact Deborah Small (deborahs@wharton.upenn.edu) or Cynthia Cryder (cryder@wustl.edu).

Have a nice summer and hope to see you next year in London.

Simona Botti (Term Associate Professor of Marketing, London Business School)
David Faro (Associate Professor of Marketing, London Business School)
Yuval Rottenstreich (Professor of Management, Rady School of Management, U.C. San Diego)

Visit the BDRM 2014 Conference Website.

AU YEAH: GOLDEN NUDGE

One of our colleagues at London Business School was speaking to a doctor from Dubai about the growing obesity problem in the UAE. The doctor felt his patients had a hard time noticing they were gaining weight because their long, loose-fitting traditional garments don’t give much feedback when weight is gained. No tightening waistline to clue you in.

Whatever the cause, there seems to be a weight problem in Dubai and now the government has come up with a clever incentive: lose a kilogram of weight, get a gram of gold.

That’s about 20 bucks a pound (at current rates, for you American readers (13 quid for you Brits)), but what we like best about this nudge is that they’re not giving people 20 bucks. They’re giving gold, which is likely generating much more buzz.

Photo credit: http://www.flickr.com/photos/teflon/147695972/

A BEHAVIORAL INSIGHTS TEAM FOR THE STATES

We’ve posted before about the UK’s Behavioural Insights Team. Some recent good news is that a similar team has been approved for the United States government. What’s more: they’re hiring! The team is led by the impressive Maya U. Shankar, Senior Policy Advisor , who is a Ph.D. psychologist and Rhodes Scholar. We just chatted with Maya and feel that this team is poised to do great things.

With out further ado, the call:

Research to Results:
Strengthening Federal Capacity for Behavioral Insights

Overview:

A growing body of evidence suggests that insights from the social and behavioral sciences can be used to help design public policies that work better, cost less, and help people to achieve their goals. The practice of using behavioral insights to inform policy has seen success overseas. In 2010, UK Prime Minister David Cameron commissioned the Behavioural Insights Team (BIT, https://www.gov.uk/government/organisations/behavioural-insights-team), which through a process of rapid, iterative experimentation (“Test, Learn, Adapt”), has successfully identified and tested interventions that will further advance priorities of the British government, while saving the government at least £1 billion within the next five years (see previous Annual Reports 2010-11 and 2011-12). The federal government is currently creating a new team that will help build federal capacity to experiment with these approaches, and to scale behavioral interventions that have been rigorously evaluated, using, where possible, randomized controlled trials. The team will be staffed by 4-5 experts in behavioral science and experimental design and evaluation. It is likely that selected individuals will serve on a temporary detail under the Intergovernmental Personnel Act before returning to their home organization, which can be a university, non-profit, or state and local government. Our preference is for individuals who are willing to serve full time but we will also consider people who are only in a position to serve part-time. Moreover, several agencies are looking to recruit expert academics to sit directly within their agencies and to help inspire, design, and execute on specific policy projects, and so it is possible to serve in this capacity as well.

If you are aware of individuals with strong analytic skills, experience designing, testing, and evaluating rigorous randomized control trials, and a strong research background in fields such as social psychology, cognitive psychology, or behavioral economics, please encourage them send a CV and contact information to mshankar2@ostp.eop.gov, which will be sent to the relevant parties for consideration.

Job Responsibilities for Central Team:

* Build Capacity: Work with a broad range of federal agencies to identify new program areas that could benefit from the application of behavioral insights. Help to design, implement, and test the relevant interventions using rigorous experimental methods.

* Enhance Capacity: Provide conceptual and technical support to agencies with specific behavioral insights efforts already underway.

* Convene: Lead a multi-agency “community of practice” to identify and share promising practices and common challenges.

* Create and Provide Resources: Generate tutorials and other “how to” documents to help accelerate these efforts within agencies. Manage online library of relevant documents and media.

* Help inspire new ideas: Work with external partners to identify research findings that can inform policy and practice.

We are already working with over a dozen federal departments and agencies on newly-designed behavioral insights projects, including the Department of Labor, Department of Health and Human Services, Department of Education, Veterans Administration, Department of Treasury, Social Security Administration, Department of Housing and Urban Development, and the United States Department of Agriculture.

Below are some examples of U.S. and international policy initiatives that have benefited from the implementation of behavioral insights:

* Increasing college enrollment and retention: Providing streamlined personal assistance on the FAFSA form (e.g., pre-populating forms using tax return data and following up with a personal call) to low or moderate income individuals resulted in a 29% greater likelihood of their attending college for two consecutive years.

* Getting people back to work: Asking unemployed individuals to create a concrete plan for immediate implementation regarding how, when, and where they would pursue reemployment efforts led to a 15-20% decrease in their likelihood of claiming unemployment benefits just 13 weeks later.

* Improving academic performance: Students taught to view their intelligence as a “muscle” that can grow with hard work and perseverance (as compared to a “fixed trait”, such as eye-color) experienced academic boosts of a letter grade, with the largest effects often seen for low-performing students, students of color, or females in STEM-related courses.

* Increasing retirement savings: The Save More Tomorrow program 1) invites employees to pledge now to increase their savings rate later, since self-control is easier to exert for future events; 2) links planned increases in the savings rate to pay raises, in order to diminish loss aversion; and 3) leverages the power of inertia by keeping members enrolled until they reach a preset limit or elect to opt. Adoption of these auto-escalation plans has boosted annual savings by an estimated $7.4 billion.

* Increasing adoption of energy efficient measures: Offering an attic-clearance service (at full cost) to people led to a five-fold increase in their subsequent adoption of attic-insulation. Interestingly, providing additional government subsidies on attic insulation services had no such effect.

* Increasing tax compliance: Sending letters to late taxpayers that indicated a social norm –i.e., that “9 out of 10 people in Britain paid their taxes on time” – resulted in a 15 percentage point increase in response rates over a three-month period, rolling out to £30 million of extra annual revenue.

ONE CRAZY NUMBER

We at DSN thought it would be worth memorizing some reciprocals because we have a system for remembering numbers and because it might come in handy. So, we started writing out 1/x

1/2 = .5
1/3 = .3
1/4 = .25
1/5 = .2
1/6 = .16
1/7 = .142857
1/8 = .125
1/9 = .1
1/10 = .1

Everything seems plain, predictable, ordinary, but what’s that going on at 1/7? .142857 repeating. That’s weird. Everywhere else it’s the first or second digit right of the decimal that repeats, but then at 1/7 you get 6 unique numbers that repeat as a weird group.

Are the multiples of this number weird? They’re even weirder.

1/7 = .142857
2/7 = .285714
3/7 = .428571
4/7 = .571428
5/7 = .714285
6/7 = .857142
See what’s going on there? They’re all just rotations of the same digits, 142857. Just pop digits off the left and stick them on the right to get any of the above.

Or as this blog shows it:

If we keep going, we run across
22/7 = 3.142857, which is of course, very nearly (within .0013 of) pi. Weird.

100/7 = 14.2857142857, which is handy b/c it comes up a lot.

Now, we were hooked. A bit of search engine magic showed us that 142857 is kind of famous. It has its own Wikipedia page.

And it has other kooky propreties:
142+857=999 and
.142+.857 = 1

What’s more, 142857 is a Harshad number, which means it is divisible by the sum of its digits:
142857/(1+4+2+8+5+7) = 5291

What’s surely not the last oddity, if you write the numbers 1 … 9 around a circle, put a triangle connecting 3, 6, and 9 and then connect 1, 4, 2, 8, 5 and 7, you get the New-Agey enneagram pictured above.

Photo credit: Wikipedia.