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Rajan Sambandam

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.

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