What is the term for when too many choices results in inability to decide?
A common problem is that when offered too many choices, consumers give up and make no choice. Too many options results in no sale where fewer options might have resulted in more sales. It's like the cognitive load of so many choices makes the decision impossible.
I've heard it called Decision Paralysis or "Analysis Paralysis" but these terms don't seem to have a root in cognitive science. Is there a formal or generally accepted term for this phenomenon?
My guess is that it has something to do with the application of equal weights to all attributes/options, even when some are irrelevant. Whether a digital camera has a huge sensor or a miniscule sensor should be such a big factor that it outweighs whether the camera finish is glossy or matte black, but I think people have a difficult time rationally weighing these things. Likely, heuristically driven decision making probably assigns weights much more efficiently -- hence, the value of going with your gut!
@AndyDeSoto the presumption of equal weight is probably very relevant; related to scanning the ability to filter out irrelevant options is very important. If you can't it may simply seem like all options are valid or that none of them are.
It is "paradox of choice". See these resources:
- The paradox of choice: why more is less By Barry Schwartz (Google Books)
- Excerpts from the above book by Barry Schwartz (
- Positive Psychology in Practice chapter 6 Doing Better but Feeling Worse: The Paradox of Choice by Barry Schwartz and Andrew Ward (
I actually haven't been able to find anything in my search just now, but I remember some claims about a year ago that recent experiments had suggested that the original results were somewhat over-blown.
I was additionally planning to ask a question about the significance of it, but I had to know what to call it first
A TED talk on paradox of choice: http://www.ted.com/talks/barry_schwartz_on_the_paradox_of_choice.html
+1, also known as "choice overload". william is right, though, that the original results may be overblown. see a meta-analysis @ http://www.scheibehenne.de/ScheibehenneGreifenederTodd2010.pdf