The role of stimuli in a virtual shopping environment: A test of predictions derived from...

The role of stimuli in a virtual shoppingenvironment: A test of predictions derivedfrom conditioning models of marketing firms

Phil Reed *, John McCarthy, Nermen Latif, Julie DeJongh

Department of Psychology, University of College of London, Gower Street, London WC1E 6BT, UK

Received 7 November 1999; received in revised form 10 May 2001; accepted 20 February 2002

Abstract

Two experiments examined the function served by cues presented to subjects shopping in a

virtual supermarket. The aim was to explore whether such cues possessed the properties of

conditioned stimuli (CS), which can attract consumers to the product with which the cues were

associated, or whether the cues served as discriminative stimuli (Sd), signalling that a purchasewould receive reinforcement. To tease apart these functions, a blocking design was employed.

A contingency was arranged so as to embue a stimulus with a particular function (CS or Sd) ina first stage of the study. In the second stage, that stimulus was presented in compound with a

second stimulus, and the compound served as a CS. As with experiments on associative learn-

ing, stimuli which served as CSs blocked the acquisition of CS properties by other stimuli, but

Sds did not block the acquisition of CS properties (Experiment 1). Likewise, stimuli whichserved as Sds blocked the acquisition of Sd properties in other stimuli, but CSs did not blockthe acquisition of Sd properties (Experiment 2). This demonstrated that cues in a virtual super-market can acquire either of these associative properties. It also implies that marketing firms

should concentrate upon different aspects of the relationship between the environment and

product when attracting costumers to an area (classical conditioning), and encouraging pur-

chase (instrumental conditioning). � 2002 Elsevier Science B.V. All rights reserved.

PsycINFO classification: 2343; 2420; 3940

JEL classification: C92; D12; M30; M31; M37

Keywords: Marketing; Learning; Discriminative stimuli; Pavlovian conditioning; Blocking

Journal of Economic Psychology 23 (2002) 449–467

www.elsevier.com/locate/joep

*Corresponding author. Fax: +44-171-4364276.

E-mail address: [email protected] (P. Reed).

0167-4870/02/$ - see front matter � 2002 Elsevier Science B.V. All rights reserved.

PII: S0167-4870 (02 )00096-X

mail to: [email protected]

1. Introduction

The influence of learning theory on marketing has long been made explicit; start-ing with the work of J.B. Watson, who attempted to endow products with particularproperties by pairing them with emotionally charged images (see Malone, 1990). Al-though the use of conditioning principles by marketing forms was then, and remainstoday, largely crude, the use of conditioning principles to understand the processesof marketing has become rather more sophisticated (e.g., Foxall, 1999). In particu-lar, the use of principles derived from the study of conditioning and associativelearning have begun to illuminate the manner in which a marketing firm may forgean influence over consumer behaviour.Foxall (1999) produced a model of the manner in which a marketing firm operates

to influence consumer behaviour. This model draws on concepts derived from theanalysis of instrumental conditioning. In this model, marketing firms were viewedas capitalising upon the instrumental nature of the consumer’s behaviour. The keyidea in Foxall’s (1999) analysis of the role of the marketing firm, is the way in whichthe firm manipulates the discriminative stimuli (Sds) that are present during a con-suming episode. If a response is made in the presence of a stimulus, and that responsereceives reinforcement, then that stimulus may become a discriminative stimulus forthat response. A discriminative stimulus can be described as setting the occasionupon which a response will be reinforced (Skinner, 1938); that is, an Sd is a stimuluswhich serves to increase the likelihood that similar responses will be emitted in itspresence in the future. Foxall (1999) argued that marketing firms manipulate thestimuli present when consumers are in a shopping environment in order to increasethe probability that a consummatory response will be emitted. Any stimulus that hasbeen associated with a rewarded purchasing response in the past will, when subse-quently presented to the consumer, make it more likely that a similar purchasing re-sponse will be emitted by the consumer. Manipulation of the cues present during aconsuming episode by a marketing firm will alter the likelihood of a purchasing re-sponse, due to those cues setting the occasion for such responses. The left-hand panelof Fig. 1 presents this relationship schematically.Of course, it is also possible that consumer behaviour can be conceived of in a

somewhat different manner, and this would alter the analysis of the marketing firm’sbehaviour. For example, Reed (1999) suggested that the behaviour emitted during ashopping episode could be classically conditioned, rather than instrumentally condi-tioned. When such a classical conditioning view is applied to consumer behaviour,the stimuli associated with the retail environment are viewed as conditioned stimuli(CS), the item or the service can be viewed as the unconditioned stimulus (US), andthe act of buying is the resulting conditioned response (CR). This model owes moreto the earlier conceptual work of Watson (1936), than to Skinner (1938). Within aclassical conditioning framework, buying an item would result from the establish-ment of an association between the retail environment and the benefits that accruefrom that item, rather than being dependent upon the reinforcement that item wouldprovide for the buying response. If this classical conditioning model of consumer be-haviour is accurate, then the marketing firm can be seen as setting up a powerful US,

450 P. Reed et al. / Journal of Economic Psychology 23 (2002) 449–467

a salient CS, and manipulating the contingencies which relate the CS to the US inways that will produce a maximal CR (see right panel of Fig. 1 for a schematic rep-resentation).To summarise the different views: the instrumental conditioning model (Foxall,

1999) suggests that the stimuli associated with the retail environment serve as occa-sion setting cues for a response; in contrast, the classical conditioning model sug-gests that these stimuli serve as a CS for a consummatory CR. Each of thesemodels leads to a different conception of the role of the marketing firm. Of course,these two models are not mutually exclusive, and under various circumstances eitherinstrumental or classical conditioning may dominate a consumer’s behaviour. Beforeattempting to tease apart these two models as accounts of the role of the marketingfirm, it is important to establish in the first instance, that cues in a retail environmentcould play the role in consumer behaviour that is suggested by conditioning models.Foxall (1999) notes that other types of relationship, such as informational cues, maywell serve to generate much human behaviour. If this were the case, then it would beexpected that learning about these cues would be influenced by factors known to af-fect the course of conditioning. The first aim of the present report is to documentthat manipulations of the stimulus functions noted to control nonhuman behaviourin the conditioning laboratory, can also be seen to control the behaviour of consum-ers in a retail environment.It should be noted that it is very difficult to distinguish between the two stimulus

functions noted above (i.e. Sd or CS). In all of the situations in which a stimuluscould serve as an Sd, there are embedded classical conditioning contingencies be-tween that stimulus and the US. That is the discriminative stimulus for the delivery

Fig. 1. Schematic representation of two conceptions of the relationship between stimuli in a consuming

episode. Left panel: instrumental conditioning view (Foxall, 1999); Right panel: classical conditioning view

(Reed, 1999).

P. Reed et al. / Journal of Economic Psychology 23 (2002) 449–467 451

of a reinforcer upon the emission of an instrumental response, also itself predicts theoccurrence of the US. The existence of this stimulus–reinforcer relationship meansthat stimuli could serve to promote behaviour by virtue of classical conditioning.To investigate the role that a stimulus is playing in any given situation, subtle exper-imental designs are needed. Such experiments have been performed within a learningtheory framework in order to separate these two possible stimulus functions (e.g.,Bonardi, 1988; Holman & Mackintosh, 1981). It is to these designs that any inves-tigation into the manner in which consumers’ behaviour is controlled must turn.The principle of blocking, in the context of learning theory, concerns the effect on

the course of conditioning to one element of a compound stimulus, of prior experi-ence with the other stimuli constituting that compound. Prior independent establish-ment of one element of a compound stimulus as a CS for a particular US, interfereswith (or blocks) subsequent conditioning to the other elements of the compound(Kamin, 1968). For example, if a rat learns that a tone predicts food, and is subse-quently exposed to a compound stimulus comprising a tone and light which is fol-lowed by food, the rat will not learn much about the light, compared to rats thatonly experience the compound stimulus followed by food. The prior training withthe tone is said to block acquisition of a light-food association.Holman and Mackintosh (1981) carried out two experiments using a blocking de-

sign in order to dissociate the functions of CS and occasion setting cues. In Exper-iment 1, they found that if a rat were exposed to a clicker–light compound,conditioning to the light would be blocked if the clicker had previously served asa classical conditioned signal for food. Such learning about the light, in a clicker–light compound, was not blocked if the clicker previously had been established asa discriminative stimulus for an instrumental food-reinforced leverpress. In Experi-ment 2, reported by Holman and Mackintosh (1981), a clicker–light compoundserved as a discriminative stimulus for food-reinforced lever pressing. Control overthe response by the light was blocked, if the clicker had previously been establishedas a discriminative stimulus in an earlier phase of the experiment. However, if theclicker had previously been established as a classically conditioned signal for food,it did not block learning about the occasion setting properties of the light (whenthe clicker and light were presented in compound, as an occasion setter, in a subse-quent phase of the study). Thus, an Sd for an instrumental response will not blockthe acquisition of the CS properties of a cue, and a CS will not block acquisitionof Sd properties of a stimulus.Such a design could be applied to determine the function of stimuli in a retail en-

vironment. The outcome of such a study could show if stimuli present in a retail en-vironment have associative properties, and which functions these stimuli serve undervarious conditions. When the situation that prevails during a purchasing episode isanalysed, it is apparent that a number of stimuli and events occur: a particular stim-ulus array confronts the shopper; a purchase is made (in the presence of this array),and some benefit accrues (presumably) to the purchaser. One possibility is that thestimuli could become directly associated with the benefits accruing from the product;that is, classical conditioning could occur. If this were the case, then the stimuli pre-sent during the episode would come to serve as CSs, eliciting the purchasing response


(see Reed, 1999). Alternatively, the purchase response may become associatedwith the benefits accruing from the product; that is, instrumental conditioningcould occur, and the stimuli could come to serve as discriminative cues for that re-sponse.Given the first of the above possibilities, a subject can be presented with a stim-

ulus that is associated with a product. Subsequently, this stimulus could be presentedin compound with a second stimulus, and the compound could be associated withthe product. In the absence of the shopper making a purchasing response (or ifthe response does not enter into the associative structure concerning the situation),then the expected result would be blocking of learning about the added stimulus inthe compound. A classically conditioned stimulus will serve to block the acquisitionof CS properties by another CS compounded with it (Kamin, 1968). In contrast,such a CS should not block the acquisition of Sd functions of a second cue, whenboth cues are presented in compound, and signal that a purchasing response willbe reinforced (Holman & Mackintosh, 1981).If the subject made a purchasing response in the presence of the product (or that

response is encoded into the associative structure produced by the situation), then itis possible that the cue would serve as a discriminative stimulus for the purchasingresponse, as suggested by Foxall (1999). If this were the case, then such a cue, servingas an Sd, should block acquisition of learning about additional Sds, when those cuesare presented in compound with the first stimulus and when both stimuli signal thata purchasing response will be reinforced. In contrast, such an Sd should not blockacquisition of knowledge about a second cue presented in compound with it, whenthose cues are associated with a product, but where no response is required.The second aim of this report is to assess whether these predictions are borne out,

and to illustrate the conditions under which stimuli may serve as CSs and Sds in theretail environment (as these stimulus functions are not mutually incompatible). Inorder to determine how stimuli guide behaviour in a retail environment, a computergame was used, which served as a virtual shopping environment. In this environ-ment, the subject was required to navigate around a supermarket, and sometimeswas also required to make particular acquisitions. This allowed investigation ofthe stimulus functions of the retail environment cues when purchases were, and werenot, made. The functions of the stimuli associated with those purchases were as-sessed with a blocking design. Such a virtual environment has the advantage of al-lowing precise control to be obtained over the relationship of the stimuli,purchasing response, and product.

2. Experiment 1

As noted above, the role of the cues associated with a product was investigatedusing a virtual supermarket. To simulate the act of buying a product, a subject wasrequired to locate the product within a supermarket, and ‘pick up’ that product fromthe supermarket shelf. If the cues associated with the product guided this performancethrough their discriminative nature, then training in this environment should mean


that the cues associated with the purchase, would not block acquisition of knowledgeabout other cues when they, along with the former stimulus, were placed in a purelyPavlovian relationship to an outcome (i.e. one in which no response was required). Incontrast, if cues present when a purchase was made only served a Pavlovian function,then blocking should occur just as when the cues had been trained initially in a purelyPavlovian procedure. These cues would serve to block the acquisition of knowledgeabout subsequently added Pavlovian cues in the environment.To test the above hypotheses, subjects were required to explore a virtual super-

market, and to locate, and (for some subjects) to purchase some coffee. The coffeewas placed in an aisle (on which some of the jars were labelled ‘‘coffee’’), and the taskwas to locate this aisle as quickly and efficiently as possible. To simulate a purchase,the subject had to make a response by picking up a coffee pod. Cues were associatedwith aisle containing the coffee, and the subjects could use these cues to locate thisproduct. It was hypothesised that if these cues were associated with the product ina condition where the subject had to make a purchasing response, and the subjectlearned a relationship between the response and the benefit from that product (in thisvirtual context the benefit was to ‘win’ or complete the game), then those cues be-come discriminative cues for that response. In this case, getting to the aisle wouldbe controlled by Sds. The stronger the learning about these cues, the greater theircontrol over behaviour, and the faster they should allow location of the aisle andpurchase of the product. Consequently, these stimuli would not subsequently inter-fere with learning about other cues, presented along with the former stimuli, and as-sociated with the product when no response was required. In this latter case,performance is assumed to be controlled by Pavlovian mechanisms (the CS for a par-ticular product eliciting approach behaviour). The greater the degree of classical con-ditioning, the greater the approach behaviour (CR), and the faster the product willbe located. However, if no response were initially required (i.e. the subjects only hadto locate the coffee, but not purchase it), then these cues would interfere with subse-quent learning about other cues signalling the coffee’s location.

2.1. Method

2.1.1. SubjectsThirty subjects were used in the present experiment. They were drawn from the

student population at University College London, and all were volunteers. Therewere 11 males and 19 females (mean age ¼ 21:7 years, age range ¼ 19–28 years).

2.1.2. ApparatusAmodified version of the computer game ‘‘Duke Nukem’’ was run on two PCs. On

PC1, the game was run for the subject to play. On PC2, the experimenter viewed thesubject’s movements through the virtual environment. The environment consisted ofa virtual supermarket, containing a number of aisles. Fig. 2 shows the plan of the en-vironment, with the entrance and position of the coffee marked.


On the ends of each aisle were squares of a particular colour, and the produce wasfound marked on the selves. The subjects moved themselves through the environ-ment by the use of four assigned keys: ‘‘a’’, ‘‘z’’, ‘‘<’’ and ‘‘>’’.

2.1.3. ProcedureThe subjects were divided into three equal sized groups ðn ¼ 10Þ. All of the sub-

jects had first to perform in a training environment, to accustom them to moving inthe 3-D display. This training phase involved using the assigned keys to movethrough a slalom course. All the subjects had three attempts at the training course.Prior to performing in this part of the experiment, the subjects were given the follow-ing printed instructions to read:

This experiment requires you to move in between the red and the bluepoles in this training room. The keys which help you to move are: a: for-ward; z: back; <: right; and >: left. There will be three trials in this train-ing room. A large circular sign on the wall signals the end of the trial.Move towards this and press the space bar when you reach it to endthe trial. When you have completed all three trials, wait for the experi-menter to give you further instruction.

Following this pretraining, the subjects were transferred to the virtual supermar-ket. Written instructions were given to the subjects as below:

Fig. 2. Outline of the supermarket-maze environment used in Experiments 1 and 2, showing the entrance,

and location of the coffee product.


This part of the experiment consists of a set of mazes, set in a computer sim-ulated 3-D supermarket. Your task is to find the coffee in the supermarket.

The task is divided into blocks, of which there will be five trials in each block. [Inblock one, you must pick up the pod by the coffee to exit the maze.] When you havesuccessfully completed a trial, the screen will return to the start of the next trial,which you may begin when you feel ready. The experimenter will come and seeyou between blocks.Thank you for taking part in this experiment.Each group performed three phases of the experiment (with the exception of the

control group, who performed only in Phases 2 and 3). There were five trials in eachphase. The subjects were told that their task was to find the coffee in the supermarket.Depending upon which phase and group they were in, different coloured signs, locatedat the end of each aisle, signalled the aisle in which the coffee was placed. The stimulusat the end of the target aisle was either a blue, or a grey, or both a blue and a grey,coloured square. All of the other aisles also had displayed other coloured markers.In the first phase of training, for one group (Group Discrim), the cues were ar-

ranged so that they had the potential to serve as discriminative stimuli for an instru-mental response. In this group, the subjects had to navigate to the appropriate aisle,marked with a particular coloured sign (blue or grey), and make the response ofpicking up a coffee pod in that aisle. Once the experimenter had seen that the subjecthad made the correct response, the trial was terminated, and the time taken to com-plete the trial (as well as the number of aisles entered in total) was recorded. For asecond group (Group Class), the subjects only had to navigate to the location of thecoffee, but did not have to make a response. That is, there was no instrumental re-sponse required; the cues served only a classical function. All other components ofthe trial were as for Group Discrim. The third group (Group Control) did not par-ticipate in this phase of the study.In Phase 2, all three groups performed the navigation part of the task again (with

no group having to make a response in this phase of the study). Once the subject hadlocated the coffee in the appropriate aisle, the experimenter terminated the trial.However, during the five trials of this phase of the experiment, the aisle was markedwith both a blue and grey square.Finally, in the test phase of the experiment, the subjects had to navigate to the ap-

propriate aisle, as in Phase 2 (i.e. no response was involved). The aisle was markedwith the coloured square that had not been used in Phase 1 (for Group Control, halfthe subjects navigated to the blue square aisle, and half to a grey square markedaisle). Once the subjects had located the coffee, the experimenter terminated the trial.The top panel of Table 1 schematically displays the design of the experiment.

2.2. Results

2.2.1. TimeThe time taken to find the product by all groups in the first two phases of the

study is shown in Table 2. Inspection of the data from Phase 1, reveals that Group


Discrim was initially faster than Group Class, but that both groups took successivelyless time to locate the product over the course of training. An analysis of variance(ANOVA) was performed on these data, with group as a between-subject factor,and trial as a within-subject factor. A rejection criterion of p < 0:05 was adoptedfor this, and all subsequent studies. This analysis revealed a statistically significantmain effect of group, F ð1; 18Þ ¼ 20:86, a significant main effect of trial, F ð4; 72Þ ¼11:77, and a significant interaction between these two factors, F ð4; 72Þ ¼ 4:64. Sim-ple main effect analysis of group on Trial Five (i.e. the end of training) revealed nostatistical difference between the two groups, F < 1.During Phase 2, there was very little difference between the groups, and all groups

came to navigate through the maze, and locate the coffee, much faster on the lasttrial, than they had on the first trial. An ANOVA (group � trial) revealed no signif-icant main effect of group, F < 1, a significant main effect of trail, F ð4; 108Þ ¼ 59:58,but no significant interaction between the two factors, F < 1.Fig. 3 displays the mean time taken to find the target product by the three groups

during the test phase of the study. Inspection of these data reveals that Group Classinitially took longer than either of the other two groups to locate the product,and that all groups finally took very little time to find the target. An ANOVA(group� trial) revealed no main effect of group, p > 0:20, but a significant main ef-fect of trial, F ð4; 108Þ ¼ 82:13, and a significant interaction between group and trial,

Table 2

Time taken (s) to complete task for all groups during Phases 1 and 2 of Experiment 1

Group Trial 1 Trial 2 Trial 3 Trial 4 Trial 5

Phase 1

Discrim 44.80 25.10 23.40 17.90 15.80

Class 117.20 82.60 24.20 18.80 20.80

Phase 2

Discrim 139.50 97.10 42.70 26.30 22.70

Class 149.20 68.50 28.10 21.60 20.40

Control 129.50 84.20 32.40 25.10 21.30

Table 1

Schematic representation of the experimental designs

Group Phase 1 Phase 2 Phase 3

Experiment 1

Discrim Sd1 CS1 þ CS2 CS2Class CS1 CS1 þ CS2 C2Control – S1 þ CS2 CS2

Experiment 2

Discrim Sd1 Sd1 þ Sd2 Sd2Class CS1 Sd1 þ Sd2 Sd2


F ð8; 108Þ ¼ 3:04. Simple effect analysis of group on Trial One, revealed a significantdifference between the groups, F ð2; 265Þ ¼ 5:01. Tukey’s honestly significant differ-ence (HSD) tests conducted on this trial, revealed that Group Class took longer thaneach of the other two groups to locate the coffee. The other two groups did not differfrom one another.

2.2.2. ErrorsThe errors made, that is entries into an incorrect aisle, by all groups in the first

two phases of the study are shown in Table 3. Inspection of the data for Phase 1,reveals that Group Class made more errors than Group Discrim, and that bothgroups made successively fewer errors over the course of training. An ANOVA(group � trial) revealed a statistically significant main effect of trial, F ð4; 68Þ ¼10:02, no significant main effect of group, F < 1, but a significant interaction be-tween these two factors, F ð4; 68Þ ¼ 5:06. Simple main effect analysis of group onTrail Five revealed no statistical difference between the groups.During Phase 2, Group Class made fewer errors than the other two groups, and

all groups came to locate the product with fewer errors on the last trial than they hadmade on the first trial. An ANOVA (group � trial) revealed a significant main effectof group, F ð2; 26Þ ¼ 3:64, a significant effect of trail, F ð4; 108Þ ¼ 71:55, but no sig-nificant interaction between the two factors, p > 0:10.Fig. 4 displays the mean number of errors made by three groups during the test

phase of the study. Inspection of these data reveals that Group Class initially mademore errors than the other two groups when locating the aisle, and that all groupsmade very few errors on the last trial of training. An ANOVA (group� trial) revealedno main effect of group, p > 0:10, but a main effect of trial, F ð4; 104Þ ¼ 82:80,

Fig. 3. Experiment 1. Mean time taken to locate the coffee product during Phase 3 of Experiment 1. Dis-

crim: group with training of Sd in Phase 1 then exposure to CSs; Class: group with training of CS in Phase1, then exposure to CSs; Control: group with no training in Phase 1, then exposure to CSs.


and a significant interaction between group and trial, F ð8; 104Þ ¼ 2:35. However,simple effect analysis of group failed to revealed any significant differences on thetrials. Tukey’s HSD tests conducted on these trials revealed that Group Classmade more errors than each of the other two groups, which did not differ from oneanother.

2.3. Discussion

These results demonstrate that, in the context of the present experiment, block-ing of learning about an added element occurred in human subjects when theyused those cues to find a particular location. That Group Class responded more

Table 3

Errors made (incorrect aisle entries) when completing task for all groups during Phases 1 and 2 of Exper-

iment 1


Phase 1

Discrim 6.33 3.00 8.00 0.67 0.22

Class 12.60 7.40 0.10 0 0

Phase 2

Discrim 20.33 10.44 5.11 2.44 1.89

Class 13.90 5.00 1.00 0.40 0.30

Control 14.00 10.00 3.70 2.30 1.70

Fig. 4. Experiment 1. Mean number of errors made when locating the coffee product during Phase 3 of

Experiment 1. Discrim: group with training of Sd in Phase 1 then exposure to CSs; Class: group with train-ing of CS in Phase 1, then exposure to CSs; Control: group with no training in Phase 1, then exposure to

CSs.


slowly than Group Control, is consistent with the occurrence of a blockingeffect. Prior training with a stimulus associated with a particular product and lo-cation, blocked learning about an added element in a subsequent phase of the ex-periment. However, no such blocking effect occurred when the subjects wererequired to make a response in the presence of the cue in the first phase of the train-ing. That is, when the subject made a response in the presence of the product, learn-ing about the cue did not serve to block leaning about the cues in a second phasewhere no response was required. This result is consist with that reported by Holmanand Mackintosh (1981) for nonhumans, who similarly showed no blocking of a sub-sequent classical relationship by a stimulus previously established as instrumentaloccasion setter. This suggests that if the consumer makes a purchase in the presenceof the cues associated with product, and this purchase is rewarded, then the cuesassociated with that purchase do not appear to be serving as a classically CS. Tothis extent, the model of consumer behaviour suggested by Foxall (1999) is vali-dated.

3. Experiment 2

The results from the first experiment demonstrate that a stimulus that accompa-nies a response will not serve to block learning about a stimulus subsequently pre-sented in compound with it, that does not signal the occasion for a response. Tofurther demonstrate a failure of blocking between stimuli established as a CS andas an Sd, the second experiment investigated whether a classically conditioned stim-ulus would block subsequent learning about an instrumental occasion setting stim-ulus. If the purchase was encoded as part of the associative structure of the event,then the cues present at the time the purchase was made could serve as Sds. If thiswere the case, then performance in locating and purchasing the product would beunder their control, and would be proportional to the strength of learning aboutthe Sds. Subsequent learning about other Sd would be blocked by such stimuli (lead-ing to longer search times for the product and purchase). A stimulus presented alongwith a cue when no purchasing response was required should, on the other hand, ac-quire classically conditioned properties, and should not block the subsequent learn-ing about the Sd properties of additional added stimuli when a purchase is required.However, if the purchase does not enter into the association, then cues in bothgroups should acquire Pavlovian properties, and the time taken to learn about thelocation of the product should be similar in both groups across all phases of the ex-periment.

3.1. Method

3.1.1. Subjects and apparatusSixteen subjects were used in the present experiment. They were drawn from the

student population at University College London, and were volunteers. There were


six males and 10 females (mean age ¼ 20:5 years, age range ¼ 18–32 years). The ap-paratus was as described in Experiment 1.

3.1.2. ProcedureThe subjects were divided into two equal sized groups ðn ¼ 8Þ. All the subjects

had first to perform in a training environment, as described in Experiment 1, in orderto accustom them to moving in the 3-D supermarket display. The subjects were thentransferred to the virtual supermarket. Written instructions were given to the sub-jects as described in Experiment 1.Each group performed in three phases of the experiment. There were five trials in

each phase. The subjects were told that their task was to find the coffee in the super-market. Depending upon which phase and group they were in, different signs sig-nalled the aisle in which the coffee was placed. As in Experiment 1, the stimuluslocated on the target aisle comprised a blue square, or a grey square, or both squaresof both colours. Other aisles had different coloured squares associated with them.The instrumental condition required that the subject made the response of pickingup a coffee pod in the aisle which contained the coffee. The classical component re-quired no such response.For Group Class, Phase 1 involved the subjects having to find coffee located in the

aisle with the blue (or grey) sign on the end of it (a classical stimulus). Phase 2 in-volved the subjects locating the aisle with a blue and a grey stimulus on it, and pick-ing up a coffee pod from that aisle. Phase 3 was the test, involving locating the aislewith the grey (or blue) stimulus on it, and picking up a pod. For the second group(Group Discrim), the stimuli and tasks were identical, except a response of pickingup the pod was required during Phase 1. The design for this experiment is shown inthe bottom panel of Table 1.

3.2. Results

3.2.1. TimeThe time taken to find the product by both groups, in the first two phases of

the study, is shown in Table 4. Inspection of the Phase 1 data, reveals that bothgroups took successively less time to locate the product over the course of training.An ANOVA (group � trial) revealed a statistically significant main effect of trial,F ð4; 56Þ ¼ 18:81, no significant main effect of group, and no significant interaction,p’s > 0:10.During Phase 2, both groups came to navigate the maze much faster on the last

trial than they had on the first trial. An ANOVA ðgroup� trialÞ revealed no signif-icant main effect of group, F < 1, a significant effect of trial, F ð4; 56Þ ¼ 36:04, but nosignificant interaction between the two factors, F < 1.Fig. 5 displays the mean time taken to find the target by the groups during the test

phase of the study. Inspection of these data reveals that Group Discrim initially tookmuch longer than Group Class to locate the aisle, and that by the end of training,both groups took very little time to find the target. An ANOVA ðgroup� trialÞ re-vealed no significant main effect of group, p > 0:08, a significant effect of trial,


F ð4; 56Þ ¼ 25:10, and a significant interaction between the two factors, F ð4; 56Þ ¼5:50. There was a significant simple main effect of group on Trial One, F ð1; 65Þ ¼24:13.

3.2.2. ErrorsThe mean errors made, entering an incorrect aisle, by both groups in the first two

phases of the study are shown in Table 5. Inspection of the data for Phase 1, revealsthat both groups made successively fewer errors over the course of training. An AN-OVA ðgroup� trialÞ revealed no main effect of group, p > 0:06, but a main effect oftrial, F ð4; 56Þ ¼ 20:48, and a significant interaction between group and trial,F ð4; 56Þ ¼ 2:69. Simple effect analysis of group on Trial One revealed a significantdifference between the groups, F < 1.

Fig. 5. Experiment 2. Mean time taken to locate the coffee product during Phase 3 of Experiment 2. Dis-

crim: group with training of Sd in Phase 1 then exposure to Sds; Class: group with training of CS in Phase1, then exposure to Sds.

Table 4

Time taken (s) to complete task for all groups during Phases 1 and 2 of Experiment 2


Phase 1

Discrim 173.50 101.87 43.88 33.13 20.88

Class 110.13 88.88 39.88 50.00 24.75

Phase 2

Discrim 147.25 67.50 44.25 30.00 21.13

Class 173.75 58.25 34.63 34.25 29.25


During Phase 2, all groups came to navigate the maze with fewer errors on the lasttrail than they had on the first trial. An ANOVA ðgroup� trialÞ revealed no signif-icant main effect of group, p > 0:10, a significant main effect of trial, F ð4; 56Þ ¼24:13, but no significant interaction between the two factors, F < 1.Fig. 6 displays the mean number of errors made by groups during the test phase of

the study. Inspection of these data reveals that Group Discrim initially made moreerrors than Group Class when locating the aisle, and that both groups finally madevery few errors. An ANOVA (group � trial) revealed a significant main effect ofgroup, F ð1; 14Þ ¼ 6:82, a significant main effect of trial, F ð4; 56Þ ¼ 11:03, and a sig-nificant interaction between group and trial, F ð4; 56Þ ¼ 5:08. Simple effect analysis ofgroup on Trial One revealed a significant difference between the groups, F ð1; 67Þ ¼26:76.

Fig. 6. Experiment 2. Mean number of error made when locating the coffee product during Phase 3 of

Experiment 2. Discrim: group with training of Sd in Phase 1 then exposure to Sds. Class: group with train-ing of CS in Phase 1, then exposure to Sds.

Table 5

Errors made (incorrect aisles entered) when completing maze for all groups during Phases 1 and 2 of Ex-

periment 2


Phase 1

Discrim 23.50 11.38 3.75 1.63 1.00

Class 11.63 7.38 2.63 2.63 0.13

Phase 2

Discrim 15.13 6.63 3.50 1.88 0.88

Class 10.63 3.50 1.00 1.00 0.88


3.3. Discussion

That Group Class displayed fewer errors, and a faster time in navigating the mazeduring the test trials suggests that blocking of the occasion setting function of thecues had not occurred by the stimulus that functioned as a classically conditionedstimulus during Phase 1. This contrasts with the longer time and greater numberof errors in the group in which the cues always served as an occasion setter. Theseresults mirror those reported in Experiment 1, and show that a stimulus initially serv-ing as a CS will not serve to block the acquisition of Sd properties in other cues.Thus, if the stimuli are serving to control behaviour through their discriminativeproperties, due to their association with a rewarded response, then the ability to nav-igate the maze will depend on the strength of this stimulus function. The blockedstimuli in Phase 2 will not acquire much strength as Sds, and maze navigation willbe poor on the basis of these cues when presented alone. In contrast, if the cue ac-quired a role as a CS in Phase 1 (since no response to the product was reinforced),this stimulus function would not effect the acquisition of Sd properties subsequently.

4. General discussion

The present report investigated whether the cues present at the time when a pur-chasing response was made in a virtual environment, controlled performancethrough their classically conditioned properties, or via their function as a discrimina-tive stimulus. The results demonstrated that, depending upon the situation, bothstimulus functions could be served by the cues present in the environment. Whenthe subject was required to make a response in the presence of the cues, these cuesappeared to act as discriminative cues, as suggested by the model outlined by Foxall(1999). However, when the subject was required only to locate a particular item, andnot to make a response, the cues appeared to control behaviour though classicallyconditioned properties.These conclusions were arrived at by the demonstration that a cue which was set

up as a discriminative stimulus, would not block the subsequent acquisition of learn-ing about cues that served as CSs (Experiment 1). Similarly, a stimulus that served asclassically conditioned stimulus (one that would elicit approach behaviour by virtueof its being paired with the desired outcome) would not serve to block learning abouta second stimulus, with which it was presented in compound, when the compoundserved to signal that a response would be reinforced (Experiment 2). However, anestablished occasion setter would block learning about the occasion setting proper-ties of a second stimulus when the two were presented in compound, and an estab-lished CS would block learning about a second CS. To this extent, it can beconcluded that the function of occasion setting and classical cues are separable inthe virtual shopping environment. This demonstration that stimuli in a retail envi-ronment could acquire associative properties, and be influenced by manipulationsthat also influence the course of conditioning, was the main purpose of the presentexperiment.


As both stimulus functions are demonstrable, it becomes a point of contentionabout which of the functions are serving to control the consumer’s behaviour. How-ever, on no other grounds than face validity of the shopping experience, it appears asif the cues most important to controlling a purchases may well be discriminativecues, as suggested by Foxall (1999). That is, when a response is involved which in-cludes the item to be purchased, the cues present appear to serve as occasion setters,since they will block the acquisition of knowledge about future occasion setters forthat response, but not will not block acquisition of learning about classically CS.However, if the purpose of the cues is to generate approach behaviour only (i.e.no purchase response is required or reinforced), then the cues appear to work as clas-sically CS. They will block further learning about new CSs, but not about occasionsetters.In practical terms, the results do have some implications about the types of

manipulations that marketing firms should conduct with respect to stimuli andproducts. Currently, research concerning the role of extrinsic cues in retail environ-ments has focused mainly on their general arousal properties (e.g., Spangenberg,Crowley, & Henderson, 1996), or on their influence over product evaluation (Rich-ardson, Dick, & Jain, 1994). The present report suggests that a more subtle analysisis possible. If the intention is to attract customers to particular locations, then themarketing firms should focus on manipulating the Pavlovian relationships betweencues and the products they signal. However, if a specific purchase is the aim, thenthe manipulation should be aimed at maximizing the discriminative function of aparticular set of stimuli associated with a product. In both these scenarios, the termstimuli is used to refer to any cue that is consistently associated with a product, andcould include the cues in the retail environment, the brand cues for that product, orthe cues associated with the product through advertising.Of course, clarification of the functioning of the cues in a retail environment also

can aid consumers to avoid exploitation by those manipulations made by the mar-keting firm. As Foxall (1999) has noted, the relationship between the marketing firmand the consumer is a reciprocal one. The behaviour of the consumer forms the Sd

that controls the marketing firm’s behaviour. Thus, to the extent that purchase iscontrolled by instrumental discriminative stimuli, the consumer can exert on influ-ence on the retail environment through their impact on the marketing firm’s behav-iour. This will result from the consumer being able to perform a careful functionalanalysis of the cues which appear to be associated with products during the pur-chase. A similar awareness of the classical cues involved also can allow consumersto control their behaviour within the retail environment. It has been established thatsubjects can withhold a CR (in this case approach), when they become aware of thecontingency (e.g., Swensen & Hill, 1970). One obvious example of where such aware-ness could be used by the consumer to protect themselves from marketing ploys is inthe ambush advert. Here the product is paired with a major event to endow the prod-uct with positive affective properties (see McDaniel & Kinney, 1998). Awareness ofthis could substantially reduce the impact of this ploy. The implications of recencyand gender effects in consumer response to ambush marketing. It should be noted,however, that such a functional analysis of the controlling cues may be quite


complex within a real life shopping environment, and it is often difficult to obtainconscious awareness of the controlling cues.As outlined in the General Introduction to this report, it is very difficult to isolate

the classically conditioned properties of any cue from its occasion setting functions.This is a point that has been made in the context of studies of animal conditioning,and the task is made doubly difficult in a complex situation such as the study of con-sumer behaviour. The adoption of an experimental analogue of the shopping envi-ronment allows some of the difficulties to be overcome, and the properties of thecues present at any one time to be manifest. Of course, it could be argued that theuse of a virtual shopping experience necessitates a loss in validity of the findings.It could be that the organisation of the present virtual environment contributed tothe present pattern of results. However, it is not clear how this would have occurred,and it is believed that the potential loss of validity may be counteracted by an in-crease in the reliability of the findings.There is reasonably good evidence that experience in virtual environments can

transfer to behaviour emitted in their equivalent real environments. For example,Wilson, Foreman, and Tlanker (1997) have demonstrated significant transfer of spa-tial information between virtual and real environment, and many simulations run ina virtual framework have proved effective in imparting skills to be exercised later in areal situation (Wilson, Foreman, & Stanton, 1993). Thus, there is no reason, on thebasis of these data, that the results obtained from the use of virtual environmentsshould not transfer to real shopping experiences. Of course, in a real shopping envi-ronment, there will always be great difficulty in accurately specifying the cues whichare controlling the consumers’ behaviour at any given point.Although there may be reason for some optimism regarding the generality of the

results of the present experiment, it should be remembered that there are advances invirtual shopping technology almost every week. Given this rapidly changing situa-tion, more convincing virtual shopping simulations could be developed as the tech-nology improves. These simulations using more recent technology may well havegreater validity for the shopping task simulated. Having acknowledged this problem,it should also be mentioned that the laws of learning employed in designing this taskand explaining the results survived transition from the conditioning chamber withrat subjects to the computer screen with humans. Given this successful transi-tion, it seems a plausible suggestion that whatever the task, the results should be sim-ilar.It should also be noted that the present results are not only of potential interest to

those involved in the study of marketing. There are very few demonstrations of thepresent phenomena in the nonhuman conditioning literature (see Holman & Mack-intosh, 1981); and these results represent an important corroboration that classicallyconditioned cues will not block instrumental occasion setting cues, nor vice versa.Indeed, there are very few examples of blocking in the human literature (see Shanks,1985). The fact that both of these phenomena have been demonstrated in the presentcontext suggests that the conditioning model derived from the animal laboratorymay have some potential in explaining human economic behaviour, whether the con-ditioning model of marketing and consumer behaviour proposed by Foxall (1999) or


the alternative presented by Reed (1999) ultimately comes to explain most of thevariance in the data.

Acknowledgements

Thanks are due to Lisa A. Osborne for initiating discussion of these ideas. Re-quests for reprints should be addressed to: Phil Reed, Department of Psychology,University College London, Gower Street, London WC1E 6BT, UK (e-mail:[email protected]).

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