BoundedRationality_TheAdaptiveToolbox.pdf

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John W. Payne and James R. Bettman
modeled in terms of adaptive behavior in light of the multiple goals that a limited
capacity information processor brings to preferential choice problems.
The rest of this chapter is organized as follows: First, we briefly describe
some of the many decision strategies that have been identified. Second, we identify
some of the important task variables that have been shown to influence when
different strategies are more likely to be used. Third, we present a choice goals
framework for predicting when different strategies will be used. Fourth, evidence
supporting that framework and the idea of adaptive strategy selection is
reviewed. Finally, we raise some issues concerning when adaptivity in strategy
use might fail.
DECISION STRATEGIES
There are many different decision strategies. One classic decision strategy is the
weighted adding strategy (WADD), which embodies the additive composition
notion that the utility of a multiattribute option equals the sum of the utilities of
its components. 2 The additive composition idea implies that the decision maker
is both willing and able to make trade-offs. More specifically, a WADD process
consists of considering one alternative at a time, examining each of the attributes
for that option, determining the subjective value of the attribute values, multiplying
each attribute's subjective value times its importance weight (e.g., multiplying
the subjective value of average reliability in a car times the importance of
a car's reliability), and summing these products across all of the attributes to obtain
an overall value for each option. Then the alternative with the highest value
would be chosen, i.e., the decisionmaker maximizes over the calculated values.
The WADD strategy assumes that the decision maker either knows or can assess
the relative importance of each attribute and can assign a subjective value to
each possible attribute level. More generally, the WADD strategy is characterized
by extensive processing of information, consistent (not selective) processing
across alternatives and attributes, processing that is alternative based (i.e.,
focused on one alternative at a time), and processing that is compensatory in that
a good value on one attribute can compensate for a poor value on another. The
making of trade-offs means that the conflict among objectives is directly
2 Over thirty years ago, Ward Edwards and Amos Tversky (1967) wrote that the idea
that the utility of a multiattribute option equals the sum of the utilities of components
"so dominates the literature on riskless choice that is has no competitors" (p. 255). The
additive composition idea continues to play the major role in studies of multiattribute
choice. For example, Meyer and Kahn (1991), in a review of models of consumer
choice behavior, note that most applications of choice theory assume that the value of
an option A to decision maker i is given by the following linear composition of the
attribute values aih Vt (A) = bt + Zkwk aih where wk is a scaling constant that is often
interpreted as the "weight" given to attribute k, and bt is a constant for the particular
decision maker.