Reconciling Gladwell’s Tipping Point with Information Cascades
The theory underlying an information cascade assumes that individuals have two broad sources of information. Private information, which is information gathered by a particular person, and information implied from the crowd. If all information is of equal weight, then two pieces of information assumed from the crowd can outweigh one piece of private information. That is, if there are two restaurants, and I see two people sitting in the second restaurant and none in the first, I would, as a rational actor, dine at the second restaurant even if I had seen a Yelp review indicating that the first restaurant is actually better. In this simple scenario, I am assuming that each of the two people sitting at the restaurant, by their actions, are conveying that they knew this restaurant was better. This information implied from the crowd, is contrasted with the Yelp review, the private information. This scenario assumes that I place equal value on the indication of quality implied by the Yelp review, and the indication implied by each seated customer. But in reality, a Yelp review is composed of the opinions of multiple people, and so it would be reasonable to give this piece of private information greater weight than the information implied from each of the first two diners. Many situations in real life, similarly, are more complicated, with different pieces of private information and crowd implied information bearing different weights, and each vying for influence against the other. Malcolm Gladwell’s book, “The Tipping Point” provides an interesting story for how these different pieces of information can compete. (It is important to note that in crafting the title, Gladwell borrows from the study of epidemiology, and the term is somewhat different from the term “tipping point” used in the context of describing direct benefit network effects, that is situations in which an increase in network participants raises the payoff for each participant.)
Gladwell describes three types of characters – connectors, mavericks and salesman. Connectors have a large number of weak ties, providing a connector access to a varied set of social groups. Mavericks are the information specialists. They are typically very knowledgeable and critical, and their opinions are therefore highly valued. Salesmen are, as the name implies, skilled promoters. A maverick’s review of a particular restaurant then can be viewed as a strong piece of private information. A connector on the other hand, perhaps has weaker information, but his information can penetrate a larger group of people. Assuming rational actors, a salesmen’s influence might be limited as the strength of their message is a result of their character not the value of the message itself. A connector’s opinion then when compared to a mavericks opinion, is more likely to be offset by the effects of an information cascade, where the information implied by the crowd, after a certain point, will constantly outweigh the private information suggested by a connector’s opinion. Situations in which the private information derives from a maverick, using the same logic, would be less susceptible to such a phenomena, as the private information would carry greater weight. If the cumulative information summed up in a Yelp review, where treated as the equivalent of the information implied by a maverick, it is very possible to imagine a scenario where private information outweighs the information implied from the crowd, leading to a break down of the information cascade.
This makes sense. Let’s assume that the result of a strong word-of-mouth phenomena (the components of which Gladwell attempts to describe) is to change the currently dominant behavior; for example, to induce customers to buy one product over another. If this dominant behavior is caused by an information cascade, where, say, consumers buy the product because they see other people with the same product, then mavericks, along with connectors and salesmen, could effectively reverse such a trend by shifting the balance of power towards private information and away from the information implied by crowds. Such a scenario could even be the start of a new information cascade. In this way, we can see how the characters in Gladwell’s book can, broadly speaking, make sense in the context of information cascades and network theory.
Sources:
Gladwell, Malcolm. The Tipping Point: How Little Things Can Make a Big Difference. Boston: Little, Brown, 2000.
http://www.gladwell.com/tippingpoint/index.html