Journal of Economic Psychology 31 (2010) 17–24

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Journal of Economic Psychology

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Children’s adaptive pre-decisional search behavior: Effects of memoryand number of alternatives

Idit Katz a,*, Yoella Bereby-Meyer b, Avi Assor a, Shai Danziger c

a Department of Education, Ben Gurion University of the Negev, Beer Sheva 84105, Israelb Department of Psychology, Ben Gurion University of the Negev, Beer Sheva 84105, Israelc School of Management, Ben Gurion University of the Negev, Beer Sheva 64105, Israel

a r t i c l e i n f o

Article history:Received 1 February 2009Received in revised form 9 September 2009Accepted 15 September 2009Available online 2 October 2009

JEL classification:D12D83

PsycINFO classification:23402800

Keywords:Information searchMemoryChildrenAdaptive behaviorCognitive cost

0167-4870/$ - see front matter � 2009 Elsevier B.Vdoi:10.1016/j.joep.2009.09.003

* Corresponding author. Tel.: +972 8 6461887.E-mail addresses: katzid@bgu.ac.il (I. Katz), yoell

a b s t r a c t

This study examines whether cognitive-processing costs induce adaptive pre-decisionalinformation search in children aged 7–8. Children aged 7–8 and 11–12 asked questionsabout objects kept in sealed boxes for the purpose of subsequent choice. Availability of amemory aid that recorded acquired information and choice set size were manipulatedindependently to create different levels of cognitive-processing cost. Children in bothage groups asked proportionally fewer questions when gathered information had to beremembered relative to when it did not and when the choice set included four alternativesrelative to two alternatives. These findings indicate that children as young as 7 years olddemonstrate adaptive pre-decisional information search.

� 2009 Elsevier B.V. All rights reserved.

1. Introduction

In modern Western society, young children are encouraged to contribute to, and often make, important decisions(Caruana & Vassallo, 2003; Kim & Lee, 1997; McNeal, 1992). Adults inclination to engage children in decisions ranging frommundane to important may be linked to Western beliefs regarding the virtues of autonomy (Ryan & Deci, 2000), and torecent changes in the child’s environment including an increase in available information and in discretionary funds. Sincechildren have become a central player in the household decision-making unit, it is important to understand how they makedecisions. The insights derived from psychological research can be applied to economics and can help us better understand,describe, and analyze economic behavior (Leiser & Azar, 2008).

Unfortunately, this topic has been addressed in only a few studies (for examples, see Bereby-Meyer, Assor, & Katz, 2004;Davidson, 1991a, 1991b; Gregan-Paxton & Roedder, 1995). Patterning themselves after research exploring adult decision-making (Bettman & Jacoby, 1976; Jacoby, 1975; Payne, 1976), these studies have primarily relied on the information-board

. All rights reserved.

a@bgu.ac.il (Y. Bereby-Meyer), assor@bgu.ac.il (A. Assor), shaidanz@som.bgu.ac.il (S. Danziger).

18 I. Katz et al. / Journal of Economic Psychology 31 (2010) 17–24

procedure, in which in order to make choices, participants gather information from a table containing alternatives and theirattributes. A main focus of these studies has been to examine whether children adaptively modify their choice strategies inresponse to situational characteristics of the decision-making context (Gregan-Paxton & Roedder, 1995). Facets of adaptivebehavior include systematic information search, selective attention to relevant dimensions, and a negative relation betweenthe proportion of gathered information and search environment complexity (Davidson, 1991a, 1991b, 1996; Klayman, 1985).The results of the aforementioned studies suggest that 7- and 8-year-olds demonstrate flexible search under some condi-tions while those aged 12 and older demonstrate flexible search unconditionally (Gregan-Paxton & Roedder, 1997; Howse,Best, & Stone, 2003).

This study aims to broaden our knowledge of the situational variables that influence search flexibility in children aged 7–8. We investigate search flexibility in a task that asks children to generate the attributes of the objects among which they areto choose, and to remember their values. Put differently, we examine the effect of memory on pre-decisional search behavior.We presuppose that the request to remember gathered information inflicts a cognitive-processing cost that may trigger flex-ible search in children aged 7–8.

1.1. Adaptive choice behavior in adults and children

Adults flexibly use information acquisition and choice strategies in the choice process (Abelson & Levi, 1985; for a review,see Bettman, Luce, & Payne, 1998). This adaptive behavior is manifested in the ability to adopt simplifying (heuristic) strat-egies that are selective in the collection and use of information (Payne, Bettman, & Johnson, 1990). Past research has foundthat adults shift from resource-demanding compensatory choice strategies (i.e., decision strategies that make tradeoffs) toless cognitively demanding non-compensatory choice strategies (i.e., decision strategies that do not make tradeoffs) withan increase in information load, under time pressure, and when greater cognitive effort is required (Bettman et al., 1998;Edland & Svenson, 1993; Nichols, Kenneth, & Beach, 1990; Olshavsky, 1979; Payne, 1982; Zakay, 1990). Furthermore, an in-crease in task complexity is typically associated with a shift from alternative-based search (interdimentional search) to attri-bute-based search (intradimentional search) (Payne, 1976). This expedient selection of strategies is thought to reflect anadaptive response of a limited-capacity information processor to the demands of complex decision tasks.

Studying information-search and choice-strategy behavior in children, Klayman (1985), asked 12-year-olds to gatherpre-decisional information from an information board before choosing products. He found that 12-year-olds search behav-ior is similar to that of adults. Klayman concluded that basic decision-making skills are developed by early adolescence.Davidson (1991a) used an information-board procedure to study pre-decisional information acquisition and choice in 2ndgraders (7- and 8-year-olds), 5th graders (10- and 11-year-olds), and 8th graders (13- and 14-year-olds). She found 2ndgraders search to be more exhaustive and less efficient than that of older children. Moreover, their search was less alter-native-based (interdimentional) and less systematic than that of the 5th graders’ (Davidson, 1996). However, there wassome evidence that the 2nd graders’ searched flexibly. Specifically, they searched for proportionally less information asmore alternatives and attributes were added to the information board (e.g., Davidson, 1991a). Collecting proportionallyless information as the environment becomes more complex demonstrates flexible and thus adaptive use of choice strat-egies (Payne, Bettman, & Johnson, 1993). In a study that concentrated solely on choice behavior, Bereby-Meyer et al.(2004), found that even children aged 8 can be sensitive to task complexity. In this study, 8–9-year-olds and 12–13-year-olds were asked to choose among multiple attribute alternatives for which the importance of the attributes andthe values for each alternative were given. The authors found that children in both age groups are more likely to use com-pensatory choice strategies when there are two alternatives to choose from than when there are four alternatives tochoose from. Thus, when choosing among options in a larger set, children1 tend to rely on the relatively simple Lexico-graphic choice strategy, i.e., a strategy in which the decision-maker selects the attribute that is most important to themand then chooses the alternative that has the highest value on that attribute, ignoring all other attributes and their values(Payne, Bettman, & Johnson, 1988; Tversky, 1969).

Other studies have looked for factors that moderate search flexibility, search selectivity, and search efficiency in youngerchildren. Davidson (1991b) examined developmental changes in selective attention to choice-relevant information. In thisstudy, 2nd, 5th, and 8th graders made hypothetical product choices for another child. The main finding was that 5th gradersare more likely than 2nd graders to gather relevant information and to select a desired product. Howse et al. (2003) askedwhether 2nd graders’ and 5th graders’ ability to relate to task-relevant information can be improved by ‘‘motivational”means. In particular, they examined search under conditions where children were either paid a penny to eliminate optionsduring search or were explicitly instructed to do so. The main finding was that 2nd graders are more adaptive when moti-vational incentives are given than when they are not. Nevertheless, even under incentive conditions, the 2nd graders ap-peared less adaptive than the 5th graders since they gathered more information.

Gregan-Paxton and Roedder (1997) also examined the effects of motivational incentives on 2nd and 5th graders’ searchbehavior. In a critical motivational ‘‘cost” condition, children paid for information with candy from an endowment while in a

1 Evidence of the adaptive use of cognitive strategies by young children has also been found in other domains of cognition. For example, Siegler (1991, 1996)found children to be adaptive in solving arithmetic problems, in reading and in spelling, and in recalling lists of numbers. In addition, Siegler and Shrager (1984)found that 5-year-olds chose among strategies in ways that yielded desirable speed-accuracy combinations. Such adaptive abilities were also demonstrated in astudy on the development of economic understanding (Thompson & Siegler, 2000).

I. Katz et al. / Journal of Economic Psychology 31 (2010) 17–24 19

control condition, information was provided at no external cost. The main findings were that the proportion of informationsearched for by 2nd graders was equivalent to that sought by 5th graders under the ‘‘cost” condition and larger under the‘‘no-cost” condition. Importantly, children in both age groups searched for proportionally less information as more attributesand alternatives were added to the information board, regardless of the imposition of a search cost.

In sum, studies on pre-decisional information acquisition suggest that the search behavior of young children (aged 7 and8) differs from that of older children (aged 10 and 11) in several ways. First, in the absence of an external motivational incen-tive, younger children gather proportionally more information than older children (Gregan-Paxton & Roedder, 1997; Howseet al., 2003), they are more likely to engage in non-systematic search, as reflected in more shifts between successive infor-mation acquisitions (Davidson, 1991a), and they are more likely to gather irrelevant information (Davidson, 1991b; Howseet al., 2003). Nevertheless, 7- and 8-year-olds gather proportionally less information from larger information boards thanfrom smaller boards suggesting flexible search. Furthermore, younger children search for proportionally less informationwhen information acquisition exerts an external cost than when it does not (Gregan-Paxton & Roedder, 1997; Howseet al., 2003) and under certain circumstances they may gather amounts of information similar to those gathered by olderchildren (Gregan-Paxton & Roedder, 1997).

1.2. The present study

In earlier studies employing the information-board paradigm, gathered information remained visible until choice. Also,the cognitive-processing costs associated with the discovery of information were small, as the participant had only to askto expose the desired information, and not to generate or remember it. In these tasks, memory abilities and memory loadare not expected to influence search behavior. This quality of the information-board paradigm diminishes its ‘‘real-worldvalidity” because memory requirements are part of many everyday choice situations in which information is amassedsequentially and must be remembered for later choice. In a marketing context, for example, choice alternatives may appearon different in-store aisles, on different pages of a catalogue, or on different web pages. To produce a context that resembledthat often encounter in the ‘‘real world”, we asked our participants to remember gathered information.

Within the paradigm that we use each unit of information that must be remembered increases the cognitive load borne inremembering it. We term this extra load an ‘‘internal cost” (see Gray, Sims, Fu, and Schoelles (2006), for a theory on the roleof memory in the cost-benefit tradeoffs between cognitive and perceptual motor resources). Note however that the effects ofthis load on performance are moderated by working memory capacity such that the greater the capacity, the less this cost isexpected to influence performance. In our context this is important since research has documented that working memorycapacity increases with age. This research has used various working memory span tasks in which, as in our task, childrenmust maintain information to be recalled while performing an intervening task (Case, Kurland, & Goldberg, 1982; Hitch,Towse, & Hutton, 2001). An increase in working memory has been suggested by developmental theories to account forage-related improvement in processing complexity (e.g., Case, 1985; Halford, 1993). In line with these findings we expect‘‘having to remember” to exert a greater cost in younger children than in older children since the younger children have lessworking memory capacity to handle the extra load.

Thus, while previous research has focused on the effects of external costs (such as payment for each piece of gatheredinformation) on search behavior of younger children (Gregan-Paxton & Roedder, 1997), we study the effects of an internalcost (having to remember gathered information) on the search behavior of children aged 7–8 and 11–12. While externalcosts are concrete and therefore may be easy to detect and adapt to, internal cost may be difficult to detect and adapt tosince they rely on meta-cognitive processes.

Children played a game in which they asked questions about objects hidden in sealed boxes. In one condition, they used amemory aid that enabled them to keep track of the responses to their questions, while in a second condition, no memory aidwas given. In addition, participants either chose from two or four boxes. We expected both manipulations to influence taskcomplexity.

Based on the results of studies showing that external costs lead to adaptive behavior in young children (Gregan-Paxton &Roedder, 1997) and findings showing that participants who must remember information tend to minimize demands onworking memory (Cary & Carlson, 1999), we predicted that both younger and older children will be sensitive to internal costsproduced by information search. Consequently, we hypothesized that:

H1: Children across ages will ask fewer questions as the cognitive cost produced by search increases. Thus, we expectchildren to ask more questions when a memory aid is available than when it is not.H2: We predict an interaction between age and memory aid on number of questions asked. Specifically, the differencebetween the number of questions asked with and without a memory aid will be larger for younger children than for olderchildren.H3: Children across ages will be sensitive to the number of alternatives in a way that one would expect to find in an adap-tive DM. Thus, we expect the following:H3a: children will ask a lower proportional number of questions when there are four alternatives (more complex task)than when there are two alternatives (less complex task).H3b: children will make proportionally more intradimensional transitions when there are four alternatives than whenthere are two alternatives (Payne, 1976).

Table 1Objects and attribute values.

Object Attributes Alternative 1 Alternative 2 Alternative 3 Alternative 4

Pencil Color Multicolor Red Blue YellowType Regular Changeable-lead Changeable-lead RegularSize Thick Thin Thin ThickEraser Without With Without With

Eraser Color White Pink White MulticolorBrush Without Without Without WithoutSize Big Small Small SmallShape Particular Particular Regular Particular

Pencil Sharpener Color Green Silver Red BlueShape Particular Regular Particular RegularSize Big Small Big SmallCartridge With Without With Without

20 I. Katz et al. / Journal of Economic Psychology 31 (2010) 17–24

2. Method

2.1. Participants

Seventy-nine children were recruited from two schools in a middle-class neighborhood of a large Israeli city. Forty ofthem were aged 7–8; 39 were aged 11–12.

2.2. Experimental stimuli

Forty participants were presented with two identical sealed boxes and 39 were presented with four identical sealedboxes. Each box contained a specific variant of the objects that the participants had been shown in a pretest (the types ofobjects, their attributes, and their specific values are shown in Table 1).

2.3. Procedure

The children were tested individually during school hours in a room adjacent to their classroom. An experimenter com-municated with the children; an assistant summarized the communications. Each child received the following verbalinstructions:

We are going to play a game. In this game you will choose a pencil, the one that you prefer the most, out of the pencils hidden inthese boxes. Since the boxes are sealed and you can’t see the pencils, you can ask me questions about the properties of the pencilin each box so that you can make a good choice. You can ask me up to six questions (for two alternatives/boxes)/12 questions(for four alternatives/boxes about the pencils in the boxes).2 Try not to ask general questions like ‘‘What’s in the boxes?” but ratherquestions that will help you discover the properties of the pencil that is in a particular box. When you feel that you’re ready tochoose, pick one of the boxes. We will play the game three times: once for a pencil, once for an eraser, and once for a pencil sharp-ener. At the end of the game, you will receive the products you chose.

At this point, children who participated in the ‘‘memory-aid condition” were given a table with rubrics resembling theboxes. They received the following instructions:

Here on this sheet, I will write the answers to your questions. First I will tell you the answer and then I will write it down for you.

During the game, the assistant coded information search and choices, including the box about which a question wasasked, the attribute of the product (color, shape, size, and so on), the total number of questions asked, and the choices made.The question phase ended when a child asked the maximum number of questions permitted or when the child indicated thatthey wished to choose. Children received their selections only after the last participant was tested so that they could not tellothers that had yet to participate about the products and/or attributes. Also, after a participant was tested, the objects in theboxes were rearranged so that the next participants would not know which object was hidden in each box.

2.4. Dependent variables

We tested our predictions with measures that characterize pre-decisional information search. To allow for directcomparisons of the amount of information gathered in the two-alternative and four-alternative conditions, we created a

2 Following other studies, we restricted the number of questions that could be asked to encourage children to ask questions based on their relativeimportance (Danziger, Bekerman, & Israely, 2006; Davidson, 1996).

Table 2Mean proportions of questions asked by condition (collapsed over object types).

Two alternatives Four alternatives

With memory aid Without memory aid With memory aid Without memory aid

Second grade 2.5 (0.4) (N = 10) 1.9 (0.4) (N = 10) 1.6 (0.4) (N = 10) 1.7 (0.7) (N = 10)Sixth grade 2.3 (0.34) (N = 9) 1.8 (0.4) (N = 10) 2.1 (0.6) (N=10) 1.7 (0.5) (N = 9)

I. Katz et al. / Journal of Economic Psychology 31 (2010) 17–24 21

proportional measure of questions asked by a child by dividing the number of questions asked by six in the two-alternativecondition and by 12 in the four-alternative condition.3

We characterized search patterns by comparing the proportion of interdimensional transitions (successive questionsrelating to the same alternative), intradimensional transitions (successive questions relating to the same attribute). Gener-ally speaking, interdimensional search is consistent with a compensatory conjunctive decision rule while intradimensionalsearch is consistent with lexicographic and elimination-by-aspects non-compensatory decision rules (Davidson, 1991a; Ja-coby, Jaccard, Kuss, Troutman, & Mazursky, 1987; Jacoby et al., 1994; Payne, 1976). We calculated the number of times suc-cessive questions related to the same alternative (interdimensional search, Type 1 transition) or to the same attribute(intradimensional search, Type 2 transition). Following Payne (1976), we used these values to calculate the proportion ofinterdimensional and intradimensional search by applying the following equation: R = (Type 1 � Type 2)/(Type 1 + Type2). Notice that this measure accepts values ranging from (�1) to (+1), where positive values indicate search that is predom-inantly interdimensional (within the alternative) and negative values indicate search that is predominantly intradimensional(within the attribute).

3. Results

3.1. Proportion searched

The proportion of questions asked were submitted to a 2 (age: 7–8 and 11–12) � 2 (memory aid: with and without) � 2(number of alternatives: two and four) � 3 (object type: pencil, eraser, sharpener) mixed ANOVA. Age, memory aid, andnumber of alternatives were between-subject variables and object type was a within-subject variable.

The means and standard deviations of the proportions of questions asked appear in Table 2.The main effect of the availability of a memory aid was significant, F(1, 70) = 6.78, p = .001, g2 = .09. Consistent with H1,

children that used a memory aid asked proportionally more questions (M = 2.13; SD = .56) than those who did not (M = 1.8,SD = .53).

The main effect of the number of alternatives was also significant, F(1, 70) = 9.90, p = .001, g2 = .12. Consistent with H3a,children faced with 2 alternatives (M = 2.17, SD = .47) asked proportionally more questions than those faced with 4 alterna-tives (M = 1.81, SD = .60).

In contrast to our expectations (H2) the interaction of age and the availability of a memory aid was not significant,F(1, 70) = .64, p = .42.

There was a significant interaction between age and task complexity, F(1, 70) = 3.9, p = .02, g2 = .05. While younger chil-dren asked proportionally fewer questions when four alternatives were available than two (F(1, 70) = 13.5, p < .001, g2 = .16),no significant difference was found for the older children (F(1, 70) = .67, p = .41) (see Fig. 1).

3.2. Pattern of search

Values for the measure R were submitted to a 2 (age: 7–8 and 11–12) � 2 (memory aid: with and without) � 2 (number ofalternatives: two and four) � 3 (object type: pencil, eraser, sharpener) mixed ANOVA. Age, memory aid, and number of alter-natives were between-subject variables and object type was a within-subject variable.

Inline with H3b, a significant effect was found for number of alternatives, F(1, 70) = 9.36, p < .005, g2 = .12, as intradimen-sional search occurred more often when there were four alternatives (M = �.48, SD = .56) than when there were two (M = .9,SD = .59). This suggests that an increase in information load leads to search that is more intradimensional. A significant effectwas also found for age, F(1, 70) = 8.93, p < .004, g2 = .11, as younger children were more likely to use intradimensional search(M = �.48, SD = .56) than older children (M = �.10, SD = .60). Finally, a significant effect was found for object type,F(2, 140) = 5.98, p < .003, g2 = .08, as search became more intradimensional as a child progressed from selecting the firstproduct to the third product (first product M = �.15, SD = .73, second product M = �.30, SD = .73, third product M = �.42,SD = .72).

3 In information-board studies, this proportional measure is calculated by dividing the number of items gathered by the total number of items available(Davidson, 1991b; Gregan-Paxton & Roedder, 1997; Howse et al., 2003).

1.6

1.8

2

2.2

2.4

2 4Number of alternatives

Prop

ortio

n of

que

stio

ns a

sked Age 7-8

Age 11-12

Fig. 1. Proportion of questions asked as a function of age (7–8 and 11–12) and number of alternatives (2 and 4)*.

22 I. Katz et al. / Journal of Economic Psychology 31 (2010) 17–24

3.3. Proportion of generated attributes

Finally, we examined whether age-related differences in information search could be traced to an underlying difference inthe ability to generate attributes. Such a difference may partially account for the age effects that we observed. The fewerattributes a child generates, the more likely he/she is to exhibit an intradimentional search pattern. To test for this possibil-ity, we compared the number of attributes that children in the two age groups generated. We found no age-related differenceon this measure.

The number of alternatives had a main effect, F(1, 70) = 200.4, p < .0001, g2 = .74, as the proportion of attributes generatedwas greater under the two-alternative condition (M = .41, SD = .08) than under the four-alternative condition (M = .2,SD = .04). Memory aid also had a significant main effect, F(1, 70) = 4.5, p < .04, g2 = .06, as the proportion of attributes gen-erated was greater when a memory aid was available (M = .32, SD = .12) than when it was not (M = .29, SD = .11). Further-more, a main effect was found for object type, F(2, 140) = 15.5, p < .0001, g2 = .18, as the proportion of generatedattributes was M = .34, SD = .16 for the first object, M = .29, SD = .11 for the second, and M = .29, SD = .12 for the third. Theinteraction between object type and memory aid was also significant, F(2, 140) = 4.29, p < .02, g2 = .06. For the first objectencountered, participants generated more attributes with a memory aid than without. This pattern was not found for thesecond and third objects encountered. An interaction was also found between object type and number of alternativesF(2, 140) = 3.34, p < .04, g2 = .04. Finally, an interaction was found between object type, age and number of alternatives,F(2, 140) = 3.31, p < .04, g2 = .04.

4. Discussion

Flexible selection of decision strategies in response to a changing environment is a hallmark of adaptive choice behavior(Payne et al., 1990). An extant literature shows that adults alter choice strategies as a function of the amount of informationavailable, time constraints, and motivation. Generally, choice-simplification strategies become more prominent as task com-plexity increases (Bettman et al., 1998; Tversky, 1969). Despite the proliferation of studies exploring adaptive choice inadults, few studies have examined whether and how children alter choice strategies as a function of task complexity. Thepicture arising from these studies is that children aged 10 and above behave similarly to adults and search adaptively, whilethose younger than 10 search adaptively when search entails an external cost (Gregan-Paxton & Roedder, 1997).

The present study extends the aforementioned research by exploring how children make choices when an internal searchcost is imposed, specifically, when children must remember pre-decisional information. This extension is important sincemany situations require decision makers to remember gathered pre-decisional information prior to choice. Our results sug-gest that an internal search cost triggers adaptive search behavior in young children in a manner similar to the triggeringeffects produced by external costs.

Consistent with hypothesis H1, children of all ages asked proportionally more questions when a memory aid was avail-able than when it was not. This finding is consistent with existing research showing adaptive search behavior of young chil-dren when search involves an external cost (Gregan-Paxton & Roedder, 1995).

Contrary to our predictions the interaction between age and memory aid on number of questions asked was not signif-icant (H2). Interestingly, this finding appears inconsistent with research showing that younger children gather more infor-mation than older children; that is, they search less adaptively (Davidson, 1991b; Howse et al., 2003); and it is inconsistentwith Reyna’s fuzzy trace theory (1995), which predicts that younger children approach decisions in a more quantitativemanner than older children and therefore should gather more information.

A possible explanation for this apparent inconsistency may be that in our task, unlike in the information-board paradigm,participants had to generate the attributes of the choice alternatives to engage in search. This task characteristic seems to

I. Katz et al. / Journal of Economic Psychology 31 (2010) 17–24 23

have imposed a cognitive cost that led children to search more frugally and in Reyna’s terms to extract the gist from theavailable information. Consistent with this notion we found that the number of attributes generated was greater when amemory aid was available than when it was not, and was greater when there were two alternatives than four alternativesto choose from.

Further evidence that young children are capable of adaptive search was revealed by the fact that the younger children inour study asked proportionally fewer questions and made greater use of intradimensional search in the four-alternative con-dition than in the two-alternative condition. Both findings are commensurate with adaptive choice behavior. (See also Ber-eby-Meyer et al. (2004), for evidence of adaptive decision making in the context of a different paradigm in children aged 8and 9.)

Another interesting facet of the data is that for the 11- and 12-year-old children, the proportion of questions generateddid not significantly differ in the two and four alternatives conditions. This finding appears to clash with adaptive decision-making. However, it may be explained by assuming that the transition from two to four alternatives did not produce a largeenough change in cognitive load for the older children to ‘‘justify” a reduction in the proportion of questions that they asked.Consistent with the view that older children did exhibit adaptive search, we found that they asked a proportionally greaternumber of questions when a memory aid was available than when it was not (in which case it would be difficult for them toremember acquired information), they generated more attributes when a memory aid was available than when it was not,and they were more likely to use intradimensional search in the four alternatives condition than in the two alternatives con-dition (reflecting another form of flexible behavior in the face of a complex environment). Importantly, the dissociation be-tween performance measures highlights the ability of decision makers to use substitute strategies to deal with taskcomplexity. Moreover, the lack of an effect on a particular measure (for example, the amount of information searched)may merely indicate that the decision maker sees no reason to change strategies in a particular task environment.

In regards to future research, one intriguing direction is to test whether younger children choose ‘‘optimally”. We did nothave an objectively best alternative in the choice set and did not relate choices to the internal preference structure of thechooser. A future study could address choice ‘‘quality” by first eliciting individual preferences for each product attributeand then examine whether choices correspond to the self-reported attribute preference structure, or alternatively, by havingdominant options in the choice set.

Acknowledgment

This paper was supported by Grant Number 2004/20, from the Israel Foundations Trustees (2004–2006).

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