Die abstrakte Grafik zum ADABOX-Tool AHP für den Analytic Hyrarchy Process zeigt ein dreidimensionales Diagramm mit blauen, grünen und gelben Quadraten.

AHP

ANALYTIC HIERARCHY PROCESS

THE PRODUCT

AHP (Analytic Hierarchy Process) is a compositional approach to the measurement of preferences, with hierarchical arrangement of features and levels.

FEATURES IN BRIEF

  • Permits convenient hierarchy definition with an unlimited number of levels
  • Determines individual utility values, even with very small samples
  • Offers multiple aggregation options
  • Runs consistency checks based on various criteria at case level

OBJECTIVE

AHP was originally an instrument to support decision-making, in which a ranking of alternative options is determined on the basis of items that are structured in a hierarchy.

To measure preferences, attributes and their levels are arranged in a hierarchy. The simplest hierarchical structure consists of the individual best concept on the top step, the attributes on the second step and the levels of each attribute on the third step (see illustration). In principle, this structure corresponds to the structure of a conjoint design.

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PRACTICAL IMPLEMENTATION

But in contrast to the holistic rating of concepts in conjoint approaches, in AHP the individual levels of an attribute as well as the attributes themselves are presented as alternatives in paired comparisons. Thus, in the example, 5 times 6 paired comparisons for the attribute levels as well as 10 paired comparisons for the attributes are to be done by each respondent. For each one, the respondents must indicate how much they prefer one attribute level against the other or how far one attribute is more important than the other.

Thus the creation of a survey design to determine which complete concepts are to be presented, as in conjoint, is superfluous. In consequence the survey is further removed from reality, but the individual tasks are easier for respondents to handle. However, when there are large numbers of features or many levels of a feature, the number of paired comparisons increases considerably.

As with conjoint, the results of AHP are the individual utility values of the attribute levels and the importance of the attributes, calculated individually for each respondent. Thus simulations of scenarios are possible as well.

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