BoundedRationality_TheAdaptiveToolbox.pdf

132 John W. Payne and James R. Bettman
regress problem but faces the problem of deciding how to decide when faced
with more novel situations.
Our view is that the strategy selection problem is sometimes solved in a
top-down way while at other times it proceeds in a much more bottom-up fashion.
Specifically, we believe that the top-down approach to strategy selection
will be more prevalent when people are faced with complex problems and have
the time to decide how to decide. It is also possible that people may start with a
top-down approach to a decision problem and then constructively adjust their
processing during the course of making the decision as they learn more about the
problem structure. Processing, in other words, can change on the spot to exploit
the task structure in an "opportunistic" fashion (Hayes-Roth and Hayes-Roth
1979). For many other situations, however, we believe that people have simply
learned which rule works best for certain classes of decision problems and will
use that rule when such tasks are recognized. (For more discussion of the processes
of strategy selection, see Chapters 3 and 5 of Payne et al. 1993.)
Anticipated versus Experienced Effort and Accuracy
A third issue concerns the distinction between anticipated and experienced levels
of effort and accuracy. We believe that it is the anticipated effort and accuracy
of different decision strategies in a particular environment that guides strategy
use. However, anticipations of effort and accuracy need not be veridical. That is,
people may be overconfident in the ability of a strategy to produce an accurate
decision or overly sensitive to immediate feedback on the effort involved in implementing
a strategy. This issue is explored in greater detail below, when we
discuss possible sources of failure in adaptive decision making. We now consider
the measurement of strategy effort and accuracy in more detail.
Assessing Cognitive Effort
The concept of cognitive or mental effort has a long and venerable history as a
theoretical construct in psychology (Kahneman 1973; Navon and Gopher
1979). It has also long been assumed that different decision strategies require
different amounts of computational effort (e.g., Simon 1955). However, as mentioned
above, the usefulness of a choice goals framework for strategy selection
is greatly enhanced by the development of more precise metrics for concepts
like cognitive effort.
Based on the work of Newell and Simon (1972), O. Huber (1980) and E.
Johnson (unpublished) suggested that the cognitive effort involved in making a
decision could be measured in terms of the number of elementary information-processing
operations needed to complete a decision task, given a specified
decision strategy. The basic idea was that any decision strategy can be decomposed
into more elementary information processes (EIPs), such as reading an
item of information, comparing two items of information, multiplying or adding