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What is the difference between ACA and CBC?

What is the difference between ACA and CBC in the term of accuracy? I’ve read the manual and noticed that each had totally different features. But the problem is that I didn’t get the exact point of them. When studying my research, I’m going to put 4 or 5 attributes and each attribute has approximately 4 levels. When doing a pilot test, there will be about 100 respondents. In this case, what conjoint analysis do I have to use in order to get a precise result, ACA or CBC? (2) Is it possible to run the software through many computers at a time? During the web survey, it is more efficient to make 100 respondents use 10 separate computers, that is, 10 respondents on each computer at a time, than to make 100 respondents use only one computer.

You can read about some of the advantages and disadvantages of the different methods of conjoint analysis in our paper: Which Conjoint Method Should I Use? (2013)

ACA and CBC are both perfectly capable of getting accurate estimates of respondents’ part-worth utilities. They are simply different methods of getting people’s preferences. ACA is an adaptive, ratings-based approach that will show people partial profile cards for ratings based tradeoffs. CBC is a full profile choice based method that will ask people to select their favorite concept in a set of concepts.

If pricing research is a big part of your studies then I would definitely favor CBC over ACA. With only five attributes you should be able to do a CBC study, even with only 100 respondents. If you are concerned about sample size then ACBC does better with small samples then CBC.

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