with expertise in a task domain (Chi et al., 1988). This is true even .... consumer may always buy the cheapest brand. Sometimes the LEX strategy includes the ...
The adaptivedecision maker John W. Payne FuquaSchoolof Business Duke Uniuersity
JamesR. Bettman Fuqua Schoolof Business Duke Uniuersity
Eric J. Johnson The Wharton School Uniaersityof Pennsylaania
l$LHCaNrsRrDGE qP UNTVERSITY PRESS
2 in decisionmaking Contingencies
Introduction By now, our basicpremiseis apparent:Irrdividualsdisplay-agreat deal of flexibility in making decisions.In their highly influential decisiontheory,Einhorn and Hogarth (1981) reviewof behavi,oral notedthat "themostimportantemPiricalresultsin theperiodunder review have shown the sensitivityof judgment and choice to seeminglyminor changesin tasks"(p. 61).More than a decadeof ,.s.ur.h iinceEinhornind Hogarth'sreviewhasstronglyreafftrmed in decisionmaking,asin other areasol that informationprocessing cognition,is highiycontingenton the demandsof the task.The same individual will use many differentkinds of strategiesin making a decision,contingentufon such factors as how information is displayed,the nature of the response,and the complexityof the prout.*. This chapterhas two purposes.First, we briefly dehnea numberof decisionstrategiesthat have beenproposedto describe judgmentand choice.second,we reviewthe researchshowingthe i*p-u.t of differenttask and contextvariableson the useof decision bY an individualstrategies Beforewe reviewtheliterature,severalaspectsof our point of view needto be madeexplicit.First, in order to keep the scopeof the we focus on preferentialdecisions;inferences chaptermanageable, for.."sts receivemuch more limited attention. Preferential "nd decisionprobiemsare typically describedusing three basic components:(t) ti,. alternaiivesavailable to the decisionmaker; (2) that relateactionsto outcomes,as well as eventsor contingencies the associatedprobabilities of those events;and (3) the values associatedwith the outcomes.Values are often basedon multiple objectives,such as maximizingsafetyand minimizing cost.These alongwith a goalstatement(suchas"choose iniormationalelements,
in decisionmaking Contingencies
2l
thepreferred alternative"), represent thetaskenvironment presented to a decision maker.Outsidethelaboratory, decision problems often are not presented in a completedform. For example,alternatives (Keller& Ho, 1988; may not be givenbut may haveto be generated Pliske, Gettys, Manning,& Casey,1987).Nevertheless, it remains usefulto definedecisionproblemsin terms of thesethree basic components of alternatives, uncertainties, and values. The decisionmaker'sinternalrepresentation of the taskenviron(or problem mentis the individual's space setof knowledgestates) (Newell& Simon,1972). A typicalexampleof a decisionproblemis theseiection of an automobile. Eachcaris characterized by different mileage,attractiveness, capacity,and so safetyrecord,passenger forth. The valuesof someof theseattributesmay be known with reasonable certainty(e.g.,a specificcar'senginesize).However,the value of other attributesis uncertain,such as the reiiability or durability of a newly introducedcar. Of course,the individual's will generailybe selective representation and wili not includeall features of thecar.Anotherexampleis thechoiceamongtwo simple lotteriesor gambles.Each lottery is dehnedby a probabilityof winningor losingand a specifiedamountto be won or lost. Whenpresented to subjects, suchpreferential choiceproblemsare "weil usually structured"(Langley,Simon,Bradshaw,& Zytkow, 1987). That is,subjectsaretypicallygivena specified setof alternativesand a setof attributevaluesto be usedin solvingtheproblem. It is importantto note,however,that preferential problemsoften haveelements that maketheir solutiondifficult.For example,conflictis typicallypresent, in thesensethat no oneoptionis beston all attributesof value,andconflicthasiongbeenrecognized asa major sourceof decisiondifhculty(Shepard,1964).The task alsomay be unfamiliarin the sensethat a rule for resolvingthe conflictcannot readilybe drawn from memory.Thus,solvingdecisionproblems oftenis not the kind of "recognizeand calculate"processassociated with expertise in a task domain(Chi et al., 1988).This is true even for the simplestlaboratorydecisiontasks.Rather,decisionmaking is oftencharacterizedby tentatiueness, search,and the useof relatiuely "weak"methods (heuristics) that aremorerepresentative of novicelike problemsolving(Langleyet al.,1987). A secondaspectof our viewpointconcernsthe terms taskeffects and context effects,which have often been usedinterchangeably in the literature.For the DurDoses of this book. we distineuish
22
The adaptiuedecisionmaker
with betweenthetwo.Taskeffectsdescribethosefactorsassociated the generalstructuralcharacteristics of the decisionproblem,includnumberof outcomesor mode,numberof alternatives, ing response attributes,time pressure, informationdisplaymode,and agenda constraints. Contexteffectsreferto thosefactorsassociated with the particularvaluesof the objectsin the specilicdecisionset under consideration, includingsimilarityand the overallattractiveness of alternatives. In general,the valuesof context factorsare more thanthevaluesof taskfactors. dependent on individualperceptions Finally,weviewdecisionmakingasconsisting of suchinterrelated evaluationof information, subprocesses asinformationacquisition, and the expressionof a decision.The literature reviewfocuseson that resultin (1) a changein the thosetask and contextinfluences salienceand useof informationin the environment,andlor (2) a changein the processes usedto combineinformationinto a judgment or choice.lFor example,a changein responsemode may resultin the sameevaluation(combination)strategybeing used but with attentionfocusedon differentinformation.Alternatively, the changein response mode may resultin the useof a different evaluationprocess. contingentdecisions Thus,observed may result from the effectof a task or context variableon the acquisition (salience)of theinformationusedor on thestrategyusedto combine the informationor both. Mellers,Ord6frez,and Birnbaum(1992) haverecentlyemphasized a similardistinctionbetweentheencoding (salience) of informationand theintegration(evaluation) of multiple (see itemsof informationin their examinationof preference reversals the sectionon responsemode effectsin this chapter). Decisionstrategies Beforeconsideringhow individualsflexiblyusevariousstrategies in responseto differentdecisiontasks,we outline someof the more t Goldsteinand Busemeyer (1992)havesuggested that ratherthan affectingeither the encodingor combinationof attributeinformation,task and contextfactors impactthe criterionusedby a decisionmakerto decidewhetherthe evidencein favorofonealternativeor anotheris suflicientto warrantan expressed preference. Although we do not doubt that the useof a criterion for decidingis sometimes part of the decision-making process,we feelthat the evidencepresentedhereis overwhelmingly supportiveof the useof multipledecisionstrategiesratherthan useofa singlecriterion-dependent strategy.Further discussion ofthis point can be found in chaDter3.
in dectsion nmking Contingencies
23
commonstrategies used.A varietyof suchdecision-making strategies hasbeenidentified, and descriptions of someof thesestrategies and theirpropertiesaregivenhere.Eachstrategycan be thoughtof as a method(a sequence of operations)lor searchingthrough the decisionproblemspace.That searchmay reflectinformationabout suchaspects as the relativeimportanceof an attribute- weightor (e.g.,safetyis more importantthat comfort);cutoifvalues salience specifyinga minimal acceptable level for attributes(e.g.,the gas mileagecannorbe lessthan 20 milesper gallon);and differential preferences across attributelevels (e.g., a lossoi$10hurtsworsethan thepleasure of a gainof $10).Searchis oftenserective, and different strategies limit the amount or type of informationprocessed in variousways. Beforeexaminingthe specihcstrategies, however,somegeneral aspects of decisionprocesses needto be addressed. First,as noted earlier,decisionproblemsoften involve conflict among values, because no oneoptionbestmeetsall of our objectives. Someof the decisionstrategies used by peoplecan be thought of as conflict confrontingandothersasconflicravoiding(Hogarth,19g7). That is, somedecision processes confrontand resoiveconfljctby considering the extentto which one is willing to trade off more of one valued attribute(e.g.,economy)for lessof anothervaluedattribute(e.g., safety).other strategies do not as explicitlyconfrontand resolve tradeoffsamongvaluedattributes.Second,particularevaluation strategies can eitherbe usedalone or in combinationwith other strategies.some typical combinationsare discussedafter the individualstrategies havebeenpresented. Third, strategies can be eitherconstructed on thespotor their usecouldbe planneda priori (seechapter5 for furtherdetails). For example, Bettman(1979, p. 33) has suggested that "choiceheuristicsmay not be storedin their entiretyin memory,but may exist only as fragments - subparts which are put togetherconstructivelyat the time of making a decision."Fourth, strategies differ in both how effortfulthey are to useand how accuratethey are likely to be (seechapter3). For example, a heuristicthat only considered informationon oneattribute(e.g.,thelexicographic heuristic)mightbe lesserfortfuland less accurate for sometypesof decisions than a heuristicthat examined a largerproportionof the availableinformation.
24
The adaptiuedecisionmaker of choiceProcesses Descriptions
The weightedadditiue(WADD) rule,The weightedadditiverule on all therelevantattributes thevaluesof eachalternative considers or weightsof theattributes a//therelativeimportances andconsiders amongvaluesis assumed the conflict Further, maker. decision the to to be confrontedand resolvedby explicitlyconsideringthe extent to which one is willing to tradeoff attributevalues,as reflectedby the relativeimportancesor weights.A rule like WADD involves substantialcomputationalprocessingof the information.The WADD rule deveiopsan overallevaluationof an alternativeby multiplyingthe weighttimesthe attributevaluefor eachattribute and summingtheseweightedattrifute valuesover all attributes.It is assumedthat the alternativewith the highestoverallevaluation all of the is chosen.Giventhat the weightedadditiverule processes conflictingvaluesexplicitly relevantprobieminformationand resolves the WADD rule (or somevariantof it) is tradeoffs, by considering oftenviewedasa normativeprocedurefor dealingwith preferential decisionproblemsof the type consideredin this book (see,e.g., Keeney& Raiffa,1916). Exactlyhow peoplethink of "weights"within the contextof the Thereis someevidence WADD rule is the subjectof investigation. in that therelative interpretation, localin that weightsaresometimes weightsreflectthe rangesof attributevaluesacrossthe alternatives in the choice set- that is, the greater the range,the greaterthe importanceof the attribute(Goldstein,1990).At other times,the more by subjects to beinterpreted weightgivento an attributeseems viewed as much more globally,for example,safetymight alwaysbe of local ranges importantthan costs,without much consideration of values(Beattie& Baron,1991).Anotherissuerelatedto weights reflectsan is whetherthe influenceof the weights on preferences weights the model, process. an averaging In addingor averaging are constrainedto sum to one; that is, they are normalized(see of adding & Naylor, 1990,for a discussion Busemeyer, Stevenson, vs.averagingmodels). Two strategiesrelatedto the WADD rule may be usedin making decisionsunderrisk, the expectedvalueand expectedutility rules. The expectedvaluerule involvesmultiplyingthe value(i.e.,monetary amount)of eachpossibieoutcomeof a lotteryby its probability Theseproductsof the valuesand probabilitiesare of occurrence.
Contingencies in decision making
Zs
thensummedover the outcomesto arriveat the expectedvalueof thelottery.Thismultiplyin-e andsummingprocess is assumed to be repeatedlor aii the lotteriesin a choiceset.It is further assumed that thelotteryor gambiewith the highestEV will be chosen.The expected utility rule differsfrom rhe EV rule in that the utility of eachoutcomeis substitutedfor its monetaryvalue.This valuation (utility assessmenr) aspectof the EU rule expandsthe domain to which tbe EU rule appliesbeyondmonetarygambles;it may also requireaddjtionalprocessing effort.However,the generalprocessing assumptions of both modeisareverysimilar. The EV rule, and especialiythe EU role, are also viewedas normativerulesfor choice.Thus,in the literatureone can seethe EV and EU rules used as both proposeddescriptionsof actual behaviorand as normativepr.r.riptions for behavior.However, while peoplesometimesmake decisionsin ways consistentwith procedures like the WADD, EV, and EU rules,more oftenpeoole appearto makedecisions usin,e simplerchoiceprocesses (heuristics). some oi the more commonchoiceheuristicsare describedin this chapter.Eachheurisricrepresents a differentmethodior simplifying searchthroughthe decisionproblemspaceby limiting the amount of informationprocessed and/ormakinghow informationis processed easler. The equalweight( EQW) heuristic.This processingstrategyex_ aminesall the alternativesand all the attribute valuesfoi each alternative. However,the equalweightstrategysimplifiesdecision makingby ignoringinformationabout the relativeimportanceor probabiiityof eachatrdbute.An overallvaluefor eachalternative is obtajnedby simplysummingthevaruesfor eachattributefor that alternative. This assumes that the attributevaiuesareexpressed, or canbe expressed, on a commonscaleof value.Hencethis heuristic is a specialcaseof the weightedadditiverule. The equalweight rule hasbeenadvocatedas a highly accuratesimplificationof the decision-making process (Dawes,1979;Einhorn& Hogarth,1975). A variationof this rule that has beenadvocatedfor usein risky choiceis the equiprobableprocedure,in which probability informationis ignoredand the alternativewith the highestaverage payoffselected (Thorngate, 1980). o. Huber(1999)references empiiical work documentingthe use of an equal weight heuristicin . riskychoice.
26
The adaptiuedecisionmaker
(SAT) heuristic.Satisficingis one of the oldest The satisJicing heuristics identifiedin thedecision-making literature(Simon,1955). With this strategy,alternatives are considered one at a time;in the ordertheyoccurin theset.This heuristiccomparesthevalueof each attributeof an alternative to a predelined cutofflevel,oftenthought of as an aspirationlevel.If any attdbutevalueis belowthe cutoff, thenthat alternativeis rejected. The hrst alternativethat hasvalues that meetthe cutoffsfor all attributesis chosen.If no alternatives passall the cutoffs,the cutoffscan be relaxedand the processrepeated,or an alternativecan be randomlyselected. An implication of the satisficingheuristicis that choicewill be a functionof the order in which a decisionmaker evaluatesalternatives. That is, if alternativeA and alternativeB both passthe cutoffs,thenwhether A or B is chosenwill dependon whetherA or B is evaluatedfirst. Therewill be no comparisonof the relativemerit of arternative A as comparedwith alternativeB. A variationof this procedureis the conjunctivemodeiproposedby Coombs(1964),Dawes(1964),and Einhorn(1970). ( LEX ) heuristic.The lexicographicprocedure The lexicographic determinesthe most important attribute and then examinesthe valuesof all alternatives on that attribute.The alternativewith the bestvalueon the most importantattributeis selected. If two alternativeshave tied values,the secondmost important attributeis considered,and so on, until the tie is broken. For example,a consumer may alwaysbuy the cheapest brand.Sometimes the LEX strategyincludesthe notion of a just-noticeable (JND).If difference severalalternatives are within a JND of the bestalternativeon the mostimportantattribute(or any attributesconsidered subsequently), they are considered to be tied (Tversky,1969).This versionof the LEX ruleis sometimes calledlexicographic-semiorder (LEXSEMI). A consequence of usinga lexicographic-semiorder decisionrure is that a personmay exhibitintransitivities in preferences in which X > Y, Y > Z, andZ > X. The followingexampledecisionproblem, adaptedfrom Fishburn(1991),illustratesthat potential.professor P is aboutto changejobs.Sheknowsthat if two offersarefar apart on salary(e.g.,more than $ 10,000apart),then salarywill be the determiningfactor in her choice.otherwise,the prestigeof the universitywill be dominant.She eventuallyreceivesthree offers, described in part asfollows:
in decisionntaking Contingencies Salary X Y Z
27
Prestige
$65,000 Low $ 50,000 High $58,000 Medium
SheprefersX to Y on thebasisoi the bettersalaryof X. Because I and Z arelessthan $ 10,000 apartin salary,sheprefersY to Z on the basisof thegreaterprestige. ShealsoprefersZ to X on thebasis of prestige. Thus,X > Y, Y > Z, andZ > X, an intransitivepattern of preferences. The generalassumption is that rationalityin choice transitivityin preferences, requires althoughFishburn( 1991)presents why it may be reasonable somearguments for peopleto sometimes violatetransitivity. (EBA) heuristic.First describedby The elimination-by-aspects Tversky(1.972), an EBA choicestrategybeginswith determination of the mostimportantattribute(Tverskyactuallyassumed that the attributeis selected probabiiisticaily, with the probabilitythat an attributeis selected beinga functionof its weightor importance). Then, the cutoff vaiue for that attribute is retrieved,and all alternativeswith valuesfor that attribute below the cutoff are elimjnated. Onecaninterpretthisprocess asrejectingor eliminating alternatives that do not possess an "aspect";the "aspect"is dehned as havinga valueon the seiected attributethat is greaterthan or equalto thecutofflevel.The EBA process continues with thesecond most important attribute,then the third, and so on, until one alternativeremains.Note that while an EBA processviolatesthe idea that one should use all relevantinformationin making a decision, it doesreflectrationalityin theordereduseof theattributes. This "partial" rationalityin processing characterizes most choice heuristics. (MCD) heuristtc.Described The majorityof conJirming dimensions by RussoandDosher(1983), theMCD heuristicinvoivesprocessing pairsof alternatives. The valuesfor eachof the two alternatives are comparedon eachattribute,and the alternativewith a majorityof winning(better)attributevaluesis retained. Theretainedalternative is then comparedwith the next alternativeamong the set of alternatives. The processof pairwisecomparisonrepeatsuntil all alternatives havebeenevaluatedand the hnal winningalternative hasbeenidentified.
28
The adaptiuedecisionmaker
The MCD heuristicis a simplifiedversionof a more general model of choicecalled the additive difference(ADDIF) model (Tversky,1969).In that processingstrategy,the alternativesare between .otnpu.LOdirectlyon eachdimension,and the difference is dimension that on alternatives two the of the subjectiu.u"iu"s difference each to applied is determined.Then a weightingfunction and the resultsaresummedover all dimensionsto obtain an overall relativeevaluationof the two alternatives.Under Someconditions,the additivedifferencerule and the WADD rule will produce orderings,althoughthe two rulesdifferin some identicalpreference aspectsoi processing(seeTversky, 1969,for a further discussion of how th; ADDIF and WADD modelsare related).The MCD heuristicsimplifresthe additivedifferencemodel both by ignoring in a binary attributeweigntsand by codingthe attlibute differences not its but fashion,so that only the direction of the difference, magnitude,is considered. A variation on the additive differenceprocess,proposed by (1986),is to Bockenholt,Albert, and Schmalhofer Aschenbrenner, the accumulating processthe attribute differencessequentially, until the summedadvantageof one option over summeddifferences somecriterionvalue.Bockenholt,Albert,Aschenanotherexceeds that thecriterionvaluemay (1991)suggest brenner,andSchmalhofer reflectthe balancethe decisionmaker desiresbetweenthe effort and thequalityof thechoiceprocess. invoivedin a decisionprocess Thefrequencyof good and badfeatures( FRQ) heuristic.Alba and Marmoistein(1987)suggestthat decisionmakersmay evaluateor basedsimply upon countsof the good or bad choosealternatives To implementthis heuristic,a featuresthe alternativespossess. p".ron would needto devilop cutoffsfor specifyinggood and bad Then the decision-aker would countthe numberof such ieatures. features.Dependingupon whetherthe decisionmaker focusedon goodfeatures,bad fiatures,or both,differentvariantsof the heuristic iould arise. Note that this heuristic could be viewed as the applicationof a voting rule to multiattributechoice,wherethe attributescan be viewedas the voters. Individualssometimesuse combinationsof Combinedstrategies. Typicaliy,combineddecisionstrategieshave an initial strategies. are eliminated,and then a second phase,wheri poor-alternatives
in decisionntaking Conttngencies
29
phaseexamining the remainingalternatives in moredetail(payne, 1976).One suchcombinedheuristicthat is frequentlyobservedin decision behavioris an elimination-by-aspects plusweighted additive strategy. EBA is usedto reducethe numberof alternatives to some smallnumber(e.g., two or three),and thena weightedadditiverule is usedto seiectamongthoseremainingalternatives. other heurisrics. Severaleven simpler heuristicsalso have been proposed.A frequentstrategyfor choiceo[ this sort is the habitual heuristic:choose what one choselast time. A relatedheuristic, mentionedin chapter1 and suggested by P. Wright (1975), is alfect referral.An individuaisimpiyelicitsa previouslyformedevaruation for each alternativefrom memory and selectsthe most highiy evaluatedalternative. No detailedattributeinformationis considered. Note that both of theseheuristicsare only relevantfor repeated choices. Generalproperties of chotcestrategtes The strategies we havediscussed arejust someof thoseproposedto describe choicebehavior.Thesestrategies havecomefroma nurnber of discipiines and havebeendescribed usingverydifferentkinds of formaiisms. As a result,in orderto compareand contraststrategies for choice,researchers haveoftendescribed themusingfairlybroad and -elobalcharacteristics. Severalof thesecharacteristics are considerednext. Contpensatory Dersus noncompensatory. A centraldistinctionamong strategiesis the extent to which they make tradeoffsamong attributes. Decisionstrategies (suchasweightedadditive)that make tradeoffsare called compensatorystrategies, whereasstrategies (suchas lexicographic) that do not maketradeoffsare callednoncompensatory. The key to this distinctionis the ability of a good valueon oneattributeto makeup for badvalueson otherattributes. A lexicographic strategyis noncompensatory because a bad value on the most important attdbute will ensurethat an aiternative would neverbe chosen,no matterhow good it is on anotherattribute.A weightedadditivemodel is compensatorybecausegood valueson one attributecan offsetbad vaiueson another.Finally. somerules,Iike the majorityof conhrmingdimensions (MCD) rule,
30
The adaptiuedecisionmaker
in that the total numberof advantages arepartiallycompensatory doesmatter,but therelativesizesof theadvantages for anaiternative do not. This distinctionbetweencompensatoryand noncompensatory rulesis relatedto how a strategydealswith conflict.Compensatory rules avoid it. rules confront conflict,whereasnoncompensatory explicit making peopie hnd (1987) that suggested has Hogarth makers may Thus, decision tradeoffsemotionallyuncomfortable. not only becausethey are avoid strategiesthat are compensatory (cognitive also becausethey require effort) but execute to difijcult (conflicts)2. value tradeoffs the explicitresolutionof diffrcult A related aspectof choice Consistentnersusselectiueprocessing. which amount of processingis to the degree the is strategies That is,is the or attributes. alternatives across or selective consistent sameamountof informationexaminedfor eachalternativeor attrithat bute,or doesthe amountvary?In general,it hasbeenassumed acrossalternativesis indicativeof a more moreconsistentprocessing compensatorydecisionstrategy(Payne, 1976).Consistentprocessingsometimesinvoivesexaminationof all informationfor every alternativeand attribute. A more variable (selective)processing pattern,on the other hand,indicatesa strategyof eliminatingalternativesor attributesusing only part of the information available, whetheradditionalinformationmight change without considering the decision. A third generalprocessingcharacteristicis Amountof processing, processing. A key distinctionamongdecision the total amount of rulesis whetherthey explicitlyignore potentiallyrelevantinformation in solvinga decisionprobiem,and thus reducethe amountof or attemptto processall relevantinformainformationprocessed, processing is consistentor not, the total amountof Whether tion. information examinedcan vary, from quite cursory to exhaustive. such as EBA, lexicographic,and satisficing, For somestrategies, is contingentupon the the total amount of informationprocessed and cutoffs. particularvaluesof the alternatives 2 As an exampleof this avoidanceof tradeoffs,Gregory,Kunreuther,Easterling, ofpeopleto considertradingoff and Richards(1991)notethat the unwillingness is onereasonwhy in environmentalrisksfor money(economicbenehts) increases the siting of hazardouswastedisposalfacilitiesis so controversial.
Contingencies in decision ntaking
3l
A lternatiue-hased uersusattribute-b asedprocessing. A fourth aspecr of processing concernswhetherthe searchand processing of alternativesproceedsacrossor within attributesor dimensions. The formeris often calledholisticor alternative-based and the latter dimensional or attribute-based processing. In alternative-based processing, multiple attributesof a singlealternativeare considered beforeinformationabout a secondalternativeis processed. In contrast,in attrjbute-based processing, the valuesof severalalternativeson a singleattributeareprocessed beforeinformationabout a secondattributeis processed. Russoand Dosher(1983)suggest that attribute-based processing is cognitivelyeasier. Formationof eualuations. The strategies differin termsof whether or not an overallevaluationfor eachaiternative is explicitlyformed. In the equal weightor weightedadditiverules,for example,each alternative is givena scorethat represents its overallevaluation. on the otherhand,rulessuchas lexicographic or EBA eliminatesome alternatives and selectotherswithout directlyforming an overall evaluation. t)ersus qualitatiue reasoning. Finally,the strategies Quantitatiue also differ in terms of the degreeof quantitativeversusqualitative reasoningused. Some strategiesinclude quantitativereasoning operations.For exampie,the equal weight method involves a summingof values,and thefrequency heuristicrequirescounts.The weightedaddingruleincludestheevenmorequantitativeoperation of multipiyingtwo values.In contrast,the reasoningcontainedin the other strategiesdescribedpreviouslyis more qualitativein nature.That is, most of the operationsfor a strategysuchas EBA involvesimplecomparisons of values.Tverskyet al. (1988)makea similar distinctionbetweenqualitativeand quantitativethinking. Hegarty,Just, and Morrison (1988)also have recentlyexplored strategydifferences that involvea distinctionbetweenqualitative and quantitativereasoningin makinginferences aboutmechanical systems. The various decisionstrategiesor rules we have describedrepresentdifferentcombinations of thesegeneralproperties. Table2.1 characterizes eachof the major strategies in termsof five of these properties.Consistentwith our conceptionof strategiesas particularsequences of mentaland elfectoroperations(seechapter1),
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