Search strategies in decision making: the success of “success”

Abstract

Examination of search strategies has tended to focus on choices determined by decision makers' personal preferences among relevant cues, and not on learning cue-criterion relationships. We present an empirical and rational analysis of cue search for environments with objective criteria. In such environments, cues can be evaluated on the basis of three properties: validity (the probability that a cue identifies the correct choice if cue values differ between alternatives); discrimination rate (the proportion of occasions on which a cue has differing values); and success (the expected proportion of correct choices when only that cue can be used). Our experiments show that though there is a high degree of individual variability, success is a key determinant of search. Furthermore, a rational analysis demonstrates why success-directed search is the most adaptive strategy in many circumstances. Copyright # 2004 John Wiley & Sons, Ltd. key words search strategies; heuristics; cue hierarchies, adaptive behaviors When faced with a decision it is often impossible to consider all of the options, their attributes and their potential consequences simultaneously, so we must do so sequentially. The order that we adopt to dictate this sequential search may have profound effects on our decisions and the consequences of those decisions (Hastie & Dawes, 2001). In this paper we present a new conceptualization of search in decision making in which search is dictated by the ''success'' of information in predicting the correct outcomes of decisions. Success is a function of the likelihood that a piece of information is usable and its accuracy in leading to a correct inference. We report empirical evidence showing that people's search patterns are allied to those determined by success, and a rational analysis that demonstrates the variety of circumstances in which success-directed search achieves the best outcomes.Decision making can be considered to have three component processes: information acquisition; evaluation/action; and feedback/learning (Einhorn & Hogarth, 1981;Payne, 1982). Arguably, information acquisition has received the least attention of these three aspects. Indeed, Anderson (1990) notes that the literature

The limited use of the fluency heuristic: Converging evidence across different procedures

“…Still another possibility is that FH use actually declines due to the repeated object presentations: With a reduced number of fluency-heterogeneous pairs, the discrimination rate of fluency (i.e., the proportion of pairs in which fluency distinguishes between alternatives) also drops. In turn, the success rate of fluency (i.e., the proportion of correct decisions when using fluency as the only cue throughout the task) also declines, when seen across the whole set of pairs (Martignon & Hoffrage, 1999;Newell, Rakow, Weston, & Shanks, 2004). In sum, if truly fluencyheterogeneous pairs decline across the task, the effort of strategy switching increases, which may motivate decision makers to discard the FH and rely on some other strategy that is more often applicable, and thus entails fewer switching costs (see, e.g., Bröder & Schiffer, 2006).…”

A Response-Time Approach to Comparing Generalized Rational and Take-the-Best Models of Decision Making

“…A combination of process tracing and outcome approaches has been used (Rieskamp & Hoffrage, 1999;Rieskamp & Otto, 2006). In a typical processtracing experiment, a person must actively uncover each cue to see its value, so the experimenter can observe the order, extent, and time course of information search (e.g., Broder, 2000;Johnson, Payne, Schkade, & Bettman, 1991;Newell, Rakow, Weston, & Shanks, 2004;Rieskamp & Hoffrage, 1999;Rieskamp & Otto, 2006). In contrast, in an outcome-oriented experiment, certain decisions are predicted by certain models, so researchers can infer which strategy was used from the final decision made (Juslin, Jones, Olsson, & Winman, 2003;Lee & Cummins, 2004;Rieskamp & Hoffrage, 1999).…”

On the Role of Recognition in Decision Making.

“…The discrimination rate is the proportion of occasions on which a cue has different values for each alternative. Newell et al (2004) demonstrated that a function of validity and discrimination rate termed success (cf. Martignon & Hoffrage, 1999) drove participants' search patterns in an environment similar to the one used here.…”

“…In spite of their popularity and emphasis on plausibility, however, evidence that people use the specific search, stopping, and decision rules that comprise the heuristics has been equivocal (Bröder, 2000(Bröder, , 2003Bröder & Schiffer, 2003;Chater, Oaksford, Nakisa, & Redington, 2003;Juslin, Jones, Olsson & Winman, 2003;Newell, Rakow, Weston, & Shanks, 2004;Newell, Weston, & Shanks, 2003;Oppenheimer, 2003).…”