Informational Cascades Prove Tipping Points Exist







Mediapost reported recently on the results of a survey done by research firm Pollara, and Marshall Kirkpatrick over at ReadWriteWeb commented on it in a post titled “There is No Tipping Point”.

A number of thinkers… and now the Pollara study have been arguing that large numbers of people do not make decisions based on the advice of a small number of powerful influencers…

The marketing world was really hoping they could just win over some existing social media power users and have everyone else fall like dominoes. This study says that’s not how it works.

The study says that while 80% of respondents were “very or somewhat more likely to consider buying products recommended by real-world friends and family” only 23% were similarly influenced by “well-known bloggers”. I do not disagree with this data, what I disagree with is the understanding of the mechanisms of social influence. A concept from economics called “Informational Cascades” shows us why the domino-effect/tipping point idea is valid, even in light of this study.

To understand this mechanism an example is helpful. Suppose there are two restaurants and a group of people on the street outside deciding which one to eat at. The most well-informed individuals (those with higher precision in making these types of decisions) will decide first and everyone will see some people start to line up outside of one restaurant. If the others know this person is of higher precision (and even if they don’t) a few people will follow their lead and join the line. Each new person who lines up outside of the restaurant sends a signal to the rest of the group (and in particular their friends and family) that this is the restaurant to pick. The more people who follow the signal, the stronger it gets and you have an Informational Cascade.

The idea is presented in rigorous detail in a paper called “Theory of Fads, Fashion, Custom and Cultural Change as Informational Cascades” written by Sushil Bikhchandani, David Hirshleifer and Ivo Welch and published in 1992. To paraphrase:

An informational cascade occurs when it is optimal for an individual, having observed the actions of those ahead of him to follow the behavior of the preceding individual without regard to his own information…

The prediction that a low-precision individual imitates a higher-precision predecessor is consistent with the evidence of numerous psychological experiments demonstrating that a subject’s previous failure in a task raises the probability that in further trials he will imitate a model performing the task (see Thelen, Dollinger, and Kirkland 1979, p. 146)…

an individual who wishes to bring about a social change, for example, introduce a desirable innovation such as an improved sanitary method in a peasant community, must focus his efforts on persuading early community leaders.

This phenomenon will happen even if the early deciders are not experts (although it is certainly enhanced if they are), or influential people normally, by the act of making a choice before others, they become influential to the rest of the group.

Real-world examples of Informational Cascades can be found everywhere, from the stock market and voting patterns to the fashion industry, but we may ask the question, why do humans put so much stock into choices made by others before them? For an answer to this we look to evolution.

For ancient (and modern) humans, learning by trial and error is energy and time expensive (not to mention dangerous), it is safer and more efficient to let someone else figure out what plants are safe to eat and then just imitate them. A 1980 paper by John Conlisk titled “Costly Optimizers and Cheap Imitators” showed that “imitators may have as high a long-run ‘fitness’ as optimizers“, and in 1992 Peter J. Richerson and Robert Boyd published a report called “Cultural Inheritance and Evolutionary Ecology” where they showed that in many instances social learning (like imitating your peers) is preferred by natural selection.

If we can agree that the choices and actions of others influence our own decisions then the mathematics of Information Cascades prove that as the size of the participating population increases, “Tipping Points” become inevitable.

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{ 13 comments }

Paula April 4, 2008 at 10:49 am

Although I only play with social networking and such for my own amusements, it’s very interesting to see the social science behind how we do the things we do. Thanx for writing such an interesting piece.

Oh yes, and on the 23% of respondents taking the advice of well known bloggers, I’m guessing they didn’t ask too many tech savvy people! :)

laurent April 4, 2008 at 11:03 am

Dan,
Thanks for your analysis and all those great reference. Oh and the beautiful waterfall pictures! You’re probably onto something. How many times have I see friends choosing a restaurant vs another because one was almost full but the other was empty. For most people, the risk of trying something new is always a big consideration in making choices. To fight such a risk, there’s trust. In the restaurant case, as you said, we instinctively trust the others just by the fact that they made a choice before us one way vs the other. Your clarification helps a lot to sort out what’s being said lately about the tipping points, the influencers and so on. I read another posts that said something similar to you and ended up concluding that, when it comes to choosing who to engage with, marketers need to find ‘THEIR’ A-list vs THE A-list. It could be a bunch of people that aren’t part of the cream because they’re passionate about something that doesn’t make everyday’s headlines.

Mark Dykeman April 4, 2008 at 11:55 am

Dan, I’m glad to see that the “influencer” conversation continues forward – it’s been one of my favorite topics in 2008.

Marshall’s article, and the Pollara study, does bring up the interesting point about the influence of bloggers, though, doesn’t it?

lisa C April 4, 2008 at 2:13 pm

This so explains the actions I see on a daily basis, thank you for a well written and easy to understand explanation. I will be doing more reading on this topic for sure.

Ron K Jeffries April 4, 2008 at 4:49 pm

Thought provoking article. Thanks for providing references.

Mark Lancaster April 5, 2008 at 8:17 am

Great article.

I absolutely agree that tipping points exist – it’s how many popular nightclubs become popular, and how those same nightclubs can become unpopular too.

Marketing does play a major role in how people consume the things they do. I mean, look at the idea of “pet rocks” – clearly stupid, yet it was a fad.

Thanks for the article though. Enjoyed it :)

Joan Vinall-Cox April 5, 2008 at 8:59 am

Fascinating! I wonder if it would have been 23% if they’d interviewed Tweeters. I know that the recommendations and links I choose to follow on Twitter are those I see as having “high precision” knowledge, (which is why I’m ‘here’.)

I deliberately set out to change a small detail of behavior of others at my exercise club and it took me, acting twice a week, about a month to effect the change

Rob O. April 5, 2008 at 2:01 pm

Truly thought-provoking stuff. I’ll bet you already have, but you definitely need to read Malcolm Gladwell’s “The Tipping Point” if not. It’s fuel for all sorts of deep thinking and coffeehouse arguments.

Steve Coombes April 13, 2008 at 2:41 pm

Just ran across this post (following in from your Twitter poll). I heard an interview on WBZ newsradio with Boston Market founder George Nadaff. He was discussing how he was impressed by a line of people outside a UFood restaurant (not sure that was name at the time). Long story short, he’s now involved in opening close to 40 of the restaurants out west. Courtesy of the ‘tipping point’ catalyst of a line of people standing outside the restaurant he was driving by.

Bill Canaday September 23, 2008 at 11:51 pm

I usually choose the restaurant that is less crowded. I figure that the place that doesn’t have a table for me almost immediately doesn’t want my business bad enough while the other place is eager to get it and will make certain that I am well cared-for. It’s not bullet-proof logic, but it means that I don’t spend my dinner time standing in line waiting to be given the sardine treatment.

Maybe that’s why nobody likes me.

edward04 August 21, 2009 at 8:31 am

Great post, tad academic.

Question – are there tools out there to identify “influencers” on the web?

Cheers

Edward Appleton

edward04 August 21, 2009 at 3:31 pm

Great post, tad academic.

Question – are there tools out there to identify “influencers” on the web?

Cheers

Edward Appleton

Ivan Walsh January 14, 2010 at 10:11 am

Hi Dan,

Group dynamics is determined by several factors, among which greed, fear, vanity all play a part. Watching how stock markets fluctuate is a good example of this. One ‘hot’ rumor and suddenly everyone wants to get in on the action. Humans are irrational.

The problem for Social Media folks is that it’s very hard to predict how people will behave, i.e. and, by extension, what will trigger an information cascade.

This brings us back to the good ol Chaos theory. (Let’s not go there for now.)

<the math¬e¬mat¬ics of Infor¬ma¬tion Cas¬cades prove that as the size of the par¬tic¬i¬pat¬ing pop¬u¬la¬tion increases, “Tip¬ping Points” become inevitable.

Agreed but how you can forecast — and respond— to this is the real dilemma. The cascade will occur. But what’s going to trigger it?

I think Google are best placed to undo this Gordian knot as they crunch increasing volumes of data, not just from their site but also from Voice and other information streams.

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