Prohibitions should be used sparingly, or not at all. Specifying unnecessary or excessive prohibitions is one of the most common mistakes. The problem usually begins when either the analyst (or the analyst's client) notices that some product combinations displayed during the interview are not realistic, given what currently exists in the market or what the client is considering to offer. Sometimes a product is shown with all the best features at a relatively low price; or two attribute levels that would not naturally occur in the real world are paired together. The inclination is simply to prohibit such combinations. Newcomers to conjoint analysis commonly think that by specifying prohibitions they can concentrate the respondent's effort on the product combinations of most interest to the client, which should in turn improve utility estimation for those most relevant combinations. This unfortunately is not always the case with main-effects utility estimation, which CVA (like most conjoint approaches) employs. Prohibiting certain combinations of levels from occurring often decreases the overall quality of the utility estimates. In other words, by asking respondents to evaluate even those product combinations that the client is unlikely to offer, we often improve the estimates of the product combinations that the client is most likely to consider. We urge you to exercise restraint when considering prohibiting pairs. Please see the discussion of prohibitions in the CVA Tutorial and Example section of the CVA documentation for an example and guidance regarding using limited prohibitions to achieve specific objectives in CVA designs.
Too many prohibitions can lead to imprecise utility estimation. It is better to prompt respondents that they will see combinations during the interview that are not yet available in the market or that seem unlikely. You can urge respondents to answer as if these products were actually available today.
Users commonly ask, "how many prohibitions can I specify without seriously damaging the results of my study?" This cannot be answered without more information. It is not the sheer number of prohibitions but the specific pattern of prohibitions that more directly affects the degree of correlation among the attribute levels in the design matrix, and thus the design efficiency.
Assume that the researcher wants to specify three prohibitions between a two-level attribute and a three-level attribute. There are just six possible combinations that can occur when combining those two attributes. If the researcher prohibits three of those combinations from occurring, this eliminates half of the possible combinations. There would probably be less damage to the efficiency of the design if three total prohibitions were allocated across three separate attribute combinations (one per pair of attributes). The researcher in this instance may decide to specify the three non-prohibited combinations of those two attributes as a single attribute, rather than as two separate (and not independent) attributes. The main drawback of this approach is that after combining these two attributes, the researcher cannot compute the attribute importance or the relative part-worths of each attribute independently.