Dimensions and Patterns in Decision-making Models and the Controlled/Automatic Distinction in Human Information Processing

Dimensional and compound pattern decision models are examined, and their respective compatibility with analytical and holistic approaches is indicated. It is shown that dimensional models depict strategies that depend on analysis and evaluation of the dimensions of choice alternatives, followed by either using complex combinatory and comparison operations, or some short-cut rules that rely on processing partial information. Compound pattern models, in contrast, underscore processes of matching whole patterns. It is argued here that the type of processes emphasised by models that assume dimensional analysis can be classified as directed/attentional processes, whereas matching of whole patterns depends more on automatic processes. Current approaches to the automatic/controlled distinction in various domains are then presented, and their relevance to decision-making models is discussed.