Decision modeling

Decision modeling attempts to replicate a decision-making process. Decision matrixes are often used in such analyses. To illustrate, consider its use in consumer research. In such an application the analyst might be interested in understanding what attributes of their product are important to consumers. A decision matrix might be constructed, as explained earlier, with competing products on the rows and attributes in the columns. The model would assume that the scores have a relationship to the market shares that the products would derive in direct market competition. Research has shown that the relationship may not be linear, however, but rather s-shaped. In other words a good product at the top of the heap has to get a lot better to capture much more market share. With such a model the analyst could study how improving or emphasizing one attribute might change market share. In another application, the process can be reversed: decisions are analyzed to infer the criteria that must have been at work in order for that decision to have been made. Here, decision modeling attempts to develop a model of the decision process applied by decision-makers, including consumers. This approach assumes that decision-makers consider a number of different factors explicitly or implicitly when comparing various alternatives and that some of these factors are more important than others. Although a decision maker may not actually list these decision factors or consciously weigh them, they are implied by the decision taken. Decision modeling and analysis is widely used in market research and strategic planning.