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Trouble With Numbers

Posted by on in Rajan Sambandam

A common experience when shopping is to see price discounts expressed in percentage terms. "All items are 25% off". That's easy enough to understand. How about situations where you see signs that say "Take a further 15% off at the register"? This is where complications arise. If an item costs $100 and you see these two signs what do you think is the final discounted price of the item? Multiple percentage changes are often used by stores and for good reason. Recent research shows that consumers are not very good at calculating multiple percentage changes and in fact make predictable mistakes. The researchers show that these mistakes can be rectified in certain ways and that there is a clear economic cost to consumers when such mistakes are made.

 

Beautiful Charts

Posted by on in Rajan Sambandam

How much do you like it when information is visually conveyed in a very pleasing manner? The New York Times Graphics Department is particualrly adept at this. It is a group of about 30 people with various backgrounds who create the visual representations for the Times publications. The group is mainly composed of cartographers, illustrators and programmers. The graphics editor Amanda Cox is unusual in that she is a statistician. You can see her ability to visualize data in the following examples. The Times graphics group dominated the gold medals at the Malofiej Awards, the most important prize for graphic design. Cox won the gold for Individual Portfolio.

Here are some examples of the group's work. Take your time to look at how simply, yet appealingly these are laid out and the amount of information that is packed in with minimal clutter. The designers have been able to stretch their imaginations in the online edition in ways not possible with the paper copy.

 

Circles, Squares and Choice

Posted by on in Rajan Sambandam

Can simple shapes like circles, squares and triangles affect consumer choice? In particular, will exposure to simple shape arrays influence how people buy? Simple shape arrays are of the form OOOOΔOO or the form OOOOOOO. The former is called a uniqueness array as there is one shape that is unique and the latter is called a homogeneity (or uniformity) array as all the shapes are the same. Another type of array called a variety array looks like OΔOOΠΔOΠ. So they are quite innocuous. The question is, are they powerful enough to induce behaviors in consumers that correspond to the shapes, such as variety seeking and uniqueness? This idea was tested by two researchers from Stanford University and produced surprising results.

 

Much as it is with people, there are two ways firms and customers can begin a relationship: one of the two parties can initiate the relationship. With people, who initiates the relationship may have no bearing on the outcome of the relationship (at least none that I know of). With firms and customers it really does make a difference says Paul Dholakia, a researcher at Rice University. It happens at least from the firm's point of view, because of the different behavior exhibited by customers who engage firms on their own, as opposed to being induced to do so.

 

From Script to Hit

Posted by on in Rajan Sambandam

Recently Slumdog Millionaire won the Oscar for best picture. It’s already considerable box office muscle is going to be further enhanced. But this was a movie that nearly did not get made. The money men who read the script did not think it was a likely candidate for success and hence it had to go through its own harrowing twists and turns to hit the screen. That is not at all an atypical scenario in the world of movies. Predicting box-office success is very difficult. It is difficult even when the movie has been made and pre-screening reviews are available. The task is considerably more difficult when only the script is available for prediction. Someone who decides to plunk down money will have to visualize a lot based on words on paper. In this kind of difficult situation is it possible to make good predictions about the success of a script if one were to take an analytical approach? Yes, say three researchers who have demonstrated a method of doing precisely that.

 

License to Thrill

Posted by on in Rajan Sambandam

It is generally accepted that purchasing luxury products (ones that provide more pleasure or thrill than utility) is associated with at least some feelings of guilt. This makes it more difficult for manufacturers of products such as expensive cars and designer jeans to sell them, as consumers may have negative feelings and find it harder to justify the purchase. But is this still the case if purchase context is taken into account? Many real world purchase decisions are not made in isolation. The consumer's mindset, the store environment, the state of the economy and other factors influence what is purchased. However, a lot of purchase decisions are studied by themselves without taking into account these kinds of contextual factors. One such factor is the previous choice made by the consumer. In studying this issue with relation to the purchase of luxury products and prior altruistic intentions, two researchers found interesting conclusions.

 

Books: The Immortal Game

Posted by on in Rajan Sambandam

The Immortal Game: A History of Chess by David Shenk

Chess is not new. Even those who have never played it know enough to recognize the game and its important pieces and terms. But to get a real understanding of its development over time and its influence on all manner of affairs, David Shenk's book is a great place to start. As an excellent science writer and descendent of a legendary chess player he brings great rigorousness and lucid writing to this history of chess. The title is a double entendre that refers to chess itself and a specific game played more than 150 years ago. As Shenk lays out the story of chess in each chapter he also shows, move by move, how that specific game played out, leading to a terrific conclusion.

Precious few of us are completely unbiased. Many of us would like to believe that we are unbiased when it comes to questions of race, gender, appearance etc, and would even say so when asked in surveys. But evidence indicates that at the aggregate level bias is real and prevalent. For instance, research by Marianne Bertrand and Sendhil Mullainathan has shown very clear bias in the selection of candidates for job interviews. They ran an experiment where they sent in resumes to real jobs where nothing was different except for how African-American some of the applicants' names sounded. In spite of equal qualifications, white names received 50% more interview calls. Sadly this was true even for federal jobs where "Equal Opportunity" is explicitly advertised. So, if bias exists but people won't say they are biased, how does one go about measuring it? Cleverly, of course. Here we will discuss two interesting indirect ways of measuring bias: Implicit Association Test (IAT) and Conjoint Analysis (CA).

Sports fans and announcers often talk about hot streaks of particular players - times when a player just can't miss. This phenomenon is supposedly seen in multiple sports and some players are in fact described as "streaky" players. How true is this? Are there hot streaks in sports? Can one objectively test the presence of a streak? Researchers have been looking into this for more than two decades and have found precious little evidence for the presence of hot streaks. At least not anywhere close to the frequency with which the term seems to be used in modern sports. We will take a tour of the pioneering research in this area which used basketball data, as well as some more recent research that spanned other sports. Across the American sports horizon it appears that Joe DiMaggio may have in fact been as special as his legend implies.

 

Lie to Me?

Posted by on in Rajan Sambandam

On the TV show Lie to Me, the lead character confidently declares that on average people lie three times in a ten minute conversation. He is a deception consultant who excels in reading micro expressions on people's faces to determine if they are lying. This character is based on the renowned psychologist Paul Ekman, whose work revolves around the idea that facial emotional expressions are universal and can be analyzed. He is the scientific consultant on the show and in fact deconstructs each episode in his blog, The Truth Behind Lie to Me. But given that it is a dramatic TV show, Lie to Me focuses on people with strong motivation to lie. Would everyday people with no specific motivation still engage in dishonest behavior when given the opportunity? Apparently the answer is yes given the real cost to the economy of low level dishonesty (returning clothes after wearing, taking office supplies, inflated insurance claims etc) which runs into billions of dollars a year. But what explains this behavior? Interesting answers were found by three researchers who ran a series of experiments to investigate this issue.

The Shopping Momentum Effect

Posted by on in Rajan Sambandam

Newton's first law of physics states that there is an inertial quality to bodies: those in motion tend to remain so, while those at rest do so too, unless there are external forces. Is it possible that humans exhibit some version of this? Habits are one example, with bad ones being hard to stop and good ones hard to start (at least for me). Researchers have recently shown that there is a shopping momentum effect too, whereby a consumer can't help buying more once an initial purchase has been made. This does not relate to consolidated buying (saving time by buying many items on one trip) or complementary buying (going in to buy a suit and buying shirts and ties to match). Shopping momentum is when an initial purchase (driver product) triggers additional purchases (target items) that otherwise would not have been made.

Bubble Psychology

Posted by on in Rajan Sambandam

Are market bubbles inevitable? Virginia Postrel has an interesting column in The Atlantic that explores the topic and pretty much arrives at that conclusion. Lab experiments run by the Nobel Prize winning economist Vernon Smith have repeatedly shown the formation of market bubbles. But as traders gain experience the bubbles become less likely and eventually disappear. So it appears that experience can have a modifying effect on bubble formation. However, when market conditions change, even experienced traders stumble and bubbles form.

 

It is no secret that consumers often perceive a price-quality relationship, attributing higher quality to products for which they pay more. A large body of pricing research supports the existence of this phenomenon and it is not hard to find personal examples. But what happens when price is compared to objective quality as measured by say, Consumer Reports? Strangely, the relationship between price and quality almost completely disappears. Why? New research points to a placebo action in marketing whereby self-fulfilling expectations could lead lower priced products to perform worse. In other words the quality you get may be related to what you pay because you (unconsciously, it appears) deem it so.

Baseball fans love to argue. That much we can say with certainty. Where uncertainty begins is in the facts brought forward to support the arguments. Baseball is awash with statistics but a common mistake (the availability error) is to use the easy ones to make one's argument regardless of its relevance. Situationally, a fan can use batting average, home runs, RBI, ERA, saves or other easily available statistics to bolster his case. Alternately, more subjective criteria such as fielding ability, speed, clutch hitting and leadership are also used to contend that certain players are better. Sabermetricians have created many objective measures (OPS, VORP, etc) for player quality which, while sometimes used, have not caught the popular imagination, largely because of a lack of simplicity and comparability. Wouldn't it be nice to have a single, simple number that can accurately summarize a player's complete contribution during a season and that allows players to be easily compared? That is what Bill James the patron saint of sabermetricians has developed. It is called Win Shares. In Part I of this post we will take a non-technical look at this statistic. In Part II we will look at highs and lows over time and why we may be witnessing one of the greatest baseball players of all time.

In Part I of this post the ides of Win Shares was introduced as the creation of the sabermetrician Bill James. It is a single number that encompasses the complete contribution of a baseball player during a season and hence allows measurement and comparison of player values over time. In this part we will look at specific Win Share numbers and players who excelled over time.

Researchers (Randomly) Fight Poverty

Posted by on in Rajan Sambandam

Researchers come in many flavors but tend to have a common aspiration; to do research that is meaningful. The researchers at the Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT are doing exactly that. It is a diverse group of researchers from several institutions from areas such as economics, public policy, development, business and finance that conducts research on developmental issues around the world. What makes them different is that their research often leads to real world solutions that can be applied by governments and NGOs in the service of poverty elimination and related issue. A common technique they apply in this pursuit is the randomized trial.

Of Tightwads and Spendthrifts

Posted by on in Rajan Sambandam

Do you spend money a little too easily or does it hurt to spend at all? Do you wonder if you are the only one or if other people have the same problem too? Does your gender, age or income have anything to do with whether you are a tightwad or a spendthrift? What effect do marketing offers have on your tendency to hand over the cash, or for that matter, your credit card? Recent research shows that tightwads and spendthrifts do exist and are quite different in these behaviors.

The Election: Who Got It Right?

Posted by on in Rajan Sambandam

You can read my previous two election posts here and here. In this post I will take a look at who got the election right and what factors to look for in making that evaluation. Those factors include single polls versus (simple and complex) poll aggregations, use of combination forecasting, the use of cell phone only households in surveys and the astonishing performance of quantitative models that accurately predicted the final results almost a year back. Keep in mind that as of this writing, the final results are still not in both in terms of vote share and in terms of states (Missouri). That said, the results are close enough that we can get a good idea of what went right.

It is election day and you do your civic duty by going to your designated polling place, standing in line, chatting with a couple of nice people, drawing the curtain and pulling the lever. Do you notice where you have voted? Of course, it's at your local school (or church or firehouse). Did that have any iaanfluence on how you voted? Of course not, right? Not so fast. New research (by Jonah Berger, Marc Meredith and Christian Wheeler) indicates that the type of polling place can have a subtle effect on how people vote. The impact is small but it is there in both a controlled lab experiment and in a noisy real-world environment.

Jeopardy! Explains Gender Differences

Posted by on in Rajan Sambandam

OK, so Jeopardy! cannot possibly explain all the differences between the genders, but it helps quite a bit in understanding financial risk taking because of its unique format. Researchers studying gender differences in risk taking have known that men and women are different in several ways. For example, in general men are more willing to take risks, single women allocate less wealth to risky assets compared to single men, women have lower risk tolerance on health and retirement issues, women prefer broader insurance coverage than men, and men are more active in stock trading. But is it just gender or are there other factors mixed in with gender that influence financial risk taking? For example, would competence have an impact and how does that vary by gender? This was the issue studied by three researchers using data from the game show Jeopardy!

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