a current overview of consumer neurosciencephd.meghan-smith.com/wp-content/uploads/2015/09/co… ·...

Journal of Consumer BehaviourJ. Consumer Behav. 7: 272–292 (2008)Published online in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/cb.251
A current overview of consumerneuroscienceMirja Hubert*,y and Peter Kenningy

Zeppelin University, Am Seemooser Horn 20, 88045 Friedrichshafen, Germany

� T

*CorAm SE-mayCha

Cop

he emerging discipline of neuroeconomics employs methods originally used in brain

research for investigating economic problems, and furthers the advance of integrating

neuroscientific findings into the economic sciences. Neuromarketing or consumer neuro-

science is a sub-area of neuroeconomics that addresses marketing relevant problems with

methods and insights from brain research. With the help of advanced techniques of

neurology, which are applied in the field of consumer neuroscience, a more direct view

into the ‘‘black box’’ of the organism should be feasible. Consumer neuroscience, still in its

infancy, should not be seen as a challenge to traditional consumer research, but constitutes a

complementing advancement for further investigation of specific decision-making behavior.

� T
he key contribution of this paper is to suggest a distinct definition of consumer
neuroscience as the scientific proceeding, and neuromarketing as the application of

these findings within the scope of managerial practice. Furthermore, we aim to develop a

foundational understanding of the field, moving away from the derisory assumption that

consumer neuroscience is about locating the ‘‘buy button’’ in the brain. Against this

background the goal of this paper is to present specific results of selected studies from this

emerging discipline, classified according to traditional marketing-mix instruments such

as product, price, communication, and distribution policies, as well as brand research.

The paper is completed by an overview of the most prominent brain structures relevant

for consumer neuroscience, and a discussion of possible implications of these insights for

economic theory and practice.

Copyright # 2008 John Wiley & Sons, Ltd.

Introduction

In recent years, interest in applying neuro-scientific findings and methodologies to otherdisciplines has been increasing. The innovativeapproach of neuroeconomics demonstratesthat this development has been incorporatedinto economic research (Braeutigam, 2005;

respondence to: Mirja Hubert, Zeppelin University,eemooser Horn 20, 88045 Friedrichshafen, Germany.il: [email protected] of Marketing.

yright # 2008 John Wiley & Sons, Ltd. Jour

Camerer et al., 2005; Kenning and Plassmann,2005; Singer and Fehr, 2005). Neuroeco-nomics employs methods originally used inbrain research to investigate economic pro-blems, and further advances the integration ofneuroscientific findings into the economicsciences. Although both economists andneurologists attempt to understand and pre-dict human behavior, they have used quitedifferent methods in the past. Whereas eco-nomic research has tried to explain behaviorthrough observational data and theoretical

nal of Consumer Behaviour, July–October 2008

DOI: 10.1002/cb

A current overview of consumer neuroscience 273

constructs such as utility or preferences,neurology contemplates the physiologicalelements and somatic variables that influencebehavior. Neuroeconomics, which evolvedfrom the combination of both disciplines,proposes an interdisciplinary approach andspecifically examines the neural correlates ofdecision-making (Sanfey et al., 2006). Market-ing research has discovered neuroscience aswell. Neuromarketing or consumer neuro-science is a sub-area of neuroeconomics thataddresses marketing relevant problems withmethods and insights from brain research(Fugate, 2007; Lee et al., 2007).Classical consumer research has seen the

human organism figuratively as a ‘‘black box,’’into which investigators could not gain directinsights. Instead, they had to use theoreticalconstructs in order to explain human behavior.In this sense, the stimulus–organism–responsemodel, which originated in neo-behaviorism,explains the initiation of behavior by acontrolled stimulus (e.g., price) or an uncon-trolled stimulus (e.g., weather). The stillunobservable processing of this stimulus insidethe organism is then related to the resultingobservable reaction (e.g., purchase) (Howardand Sheth, 1969). Examinations of the pro-cesses inside the human organism are based onestablished indirect methods such as electro-dermal response (EDR) measurement, pupillo-graphy, and, most common, self-assessmentmethods (Bagozzi, 1991; Groeppel-Klein,2005). A more direct view into the blackbox of the organism should be feasible with thehelp of advanced techniques and methods ofbrain research that are now applied in the fieldof consumer neuroscience (Kenning et al.,2007a). Even though the application ofneurobiological methods such as electroence-phalography (EEG) is not new in marketingresearch, the direct observation of the reac-tions within the brain that is now availablethrough the use of steadily improving methodsof imaging techniques, for example, positronemission tomography (PET) or functionalmagnetic resonance imaging (fMRI), is provid-ing a completely different perspective (Plas-smann et al., 2007a).

Copyright # 2008 John Wiley & Sons, Ltd. Jour

The determination of cortical areas that arestimulated during consumer decision proces-sing is important for various reasons. First, theapproach of consumer neuroscience enablesthe researcher to reassess existing theories thattheoretically assume different brain mechan-isms (e.g., hemisphere theory) by investigatingthe actual brain activations. Beyond this, theobservation of the total brain has the potentialto yield new, unpredictable results, andenhances the explorative character of con-sumer neuroscience. This contrasts measuringthe brain activity by recording only one signal,as it is used, for example, in EDR or eyetracking, which can be compared to an effortto capture the musical sounds of an orchestraby measuring only the noise level (Kenninget al., 2007a). Third, concerning the empiricaldata ascertainment, the observation of brainactivity can offer another, and more objective,perspective: self-assessment methods that relytotally on the ability of the respondent todescribe and reconstruct feelings and thoughtsare very subjective. Many effects in the humanorganism that influence behavior are notperceived consciously; hence, the cognitivefilter of the test taker may bias the results. Forexample, a person who has a temperature maydetermine that his body feels cold, eventhough the objective measurement of a clinicalthermometer indicates that it is not. Fourth,strategic behavior and social desirability,which can confound findings of self-assess-ment methods, can be eliminated, given thatthe participating subjects have little to noinfluence on the measurement of their brainactivity (Camerer et al., 2005). A last, but veryimportant, advantage of determining thecortical stimulation is the simultaneousnessof measurement and experiment. Some pro-cesses might not be stable over time, making itvery difficult for researcher and participant toreconstruct them ex-post (Lee et al., 2007).As a consequence of these advantages, the

crossing of the own disciplinary boundariesand the consideration of all aspects thatdetermine decision-making can help consumerresearchers and social scientists to more fullyunderstand human behavior (Zaltman, 2000).


DOI: 10.1002/cb

274 Mirja Hubert and Peter Kenning

With better comprehension and steadilyimproving methods, it may be possible toderive new theories for marketing researchand to arrive at a higher level of explainedvariance (Knutson et al., 2007). This may inturn help to improve companies’ actions, forexample, marketing responses that are basedon a better satisfaction of unconscious emo-tional consumer needs. However, consumerneuroscience is still in its infancy and shouldnot be seen as a challenge to traditionalconsumer research. Rather, it constitutes acomplementing advancement for further investi-gation of specific decision-making behavior.The increasing relevance of this area of

research is indicated by the growing interest ofscience and practice (Fugate, 2007; Lee et al.,2007; Plassmann et al., 2007a). For example,numerous conferences, calls for papers fromprominent scientific journals, and calls forresearch by institutes such as the MarketingScience Institute, the Institute for the Study ofBusiness Markets (Lee et al., 2007), and theWorld Advertising Research Centre focus onthis subject. The Association of ConsumerResearch even implemented a new content

Figure 1. Development of google hits on neuromarketing


area code for neuroscience. Furthermore,‘‘googling’’ the term ‘‘neuromarketing’’ cur-rently yields more than 800 000 hits, whichestablishes the field’s move into the main-stream of research (Figure 1).

Against the background of the embryonicnature of the field, a key contribution of thispaper is to suggest a distinct definition ofneuromarketing and consumer neuroscience.The term ‘‘consumer neuroscience’’ com-prises the scientific proceeding of this researchapproach, and ‘‘neuromarketing’’ designatesthe application of the findings from consumerneuroscience within the scope of managerialpractice. Because of the way the terms areapplied in the existing literature, and toprevent misunderstandings, both terms arestill used synonymously in the following.Furthermore, we aim to develop a definitivefoundation, moving away from the derisoryassumption that consumer neuroscience isused for locating the ‘‘buy button’’ in the brain(Blakeslee, 2004). In order to achieve our goal,this paper discusses a wide scope of marketing-mix instruments and addresses the questionof the extent to which the application of

2003–2007.


DOI: 10.1002/cb


neuroscientific methods can help to identifythe cortical areas that drive consumer be-havior. We attempt to connect consumerresearch and neuroscience in order to providea better understanding of current proceedingsin neuromarketing.

Neurally reconstructing themarketing mix — overview ofselected studies

In order to show the close alliance betweenconsumer neuroscience and established mar-ket research, we present here specific resultsand implications of selected exemplary studiesfrom this recent field of research. The selectiontakes into account whether or not the studywas related to marketing issues. Regardingcontent, the overview is structured accordingto traditional marketing-mix instruments suchas product, price, communication, and distri-bution policies, as well as brand research,because they represent predominant andessential elements of marketing theory andoperational marketing management (Winer,1986; Constantinides, 2006). In this connec-tion, neural activation patterns evoked bystimuli of each mix instrument and brandingresearch are identified. Additionally, Table 1offers a graphical overview of selected studiesin consumer neuroscience.

Product policy

Product policy is also called the ‘‘heart ofmarketing,’’ as it includes all decisions that acompany makes regarding the market-drivencomposition of its offered services (Kotler andKeller, 2006). It is an essential element ofsuccessful corporate policy, because a productrange that satisfies the needs, demands, andproblems of the customer can be the key forsustainable corporate success (Cooper, 1979;Selnes, 1993; Anderson et al., 1994; Bailettiand Litva, 1995). However, the application ofconventional market research methods such asself-reports often does not yield the desiredinformation about consumers’ real opinion of a


product. For example, self-reports are fre-quently in contrast to the actual inner states ofthe subjects, because people are generally notable to reconstruct and interpret theirthoughts and feelings retrospectively (Bagozzi,1991). In this area, consumer neurosciencecan yield a more complete and objectiveunderstanding of consumer’s desires, andmay consequently assist companies to adjusttheir strategies.One important aspect of product policy is

the optimal design of a product according tothe preferences of the customer (Bloch, 1995).The investigations by Erk et al. (2002)provided the first central insights into howthe brain processes differently designed goods(e.g., sports cars, limousines, and small cars).Their fMRI results showed that reward-relatedbrain areas are activated by objects that havegained a reputation as status symbols throughcultural conditioning signaling wealth andsocial dominance. In relation to the perceivedattractiveness of the products, pictures of thecars in their study led to activation in the leftanterior cingulate, the left orbitofrontal, andbilateral prefrontal cortex, as well as in theright ventral striatum. According to the presentstandard of knowledge, these regions areassociated with motivation, the encoding ofrewarding stimuli, the prediction of rewards,and decision-making (Bechara et al., 2000;O’Doherty, 2004). A very interesting findingfor the optimal design of a product is themeasured activation in the ventral striatum inwhich the nucleus accumbens is located: Themore attractive the subject perceived a car tobe, the stronger the detected activation.Hence, the most intense average activationsignal was measured when the subjects lookedat sports cars, followed by limousines, andthen small cars. Erk et al. (2002) reasoned thatthe relative activation in the ventral striatumcan be seen as an indicator for how attractive avisual stimulus (i.e., product design or shape)is evaluated to be. Assuming that there is arelation between product design and purchasedecision, we can hypothesize that activitychanges in the reward system of the braininduced by an attractive product design can


DOI: 10.1002/cb

Table

1.Overview

ofselectedstudiesin

alphabetical

order

Study

Subject

Problem

Method

Experimentalset-up

NResults

Ambleretal.,

2000

Communication

policy

What

impactdoesaffective

advertisementhaveon

theneuralactivityin

comparisonwithcognitive

advertisement?

MEG

Thesubjects

watched

differentcommercials

witheitheraffective

orcognitivecontent

n¼3

-Cognitivepictures:stronger

activationin

posterior

parietalareas

andin

the

superiorprefrontal

cortex!

strongeruse

ofworkingmemory

-Affectivepictures:activation

intheareas

ofthe

ventromedialprefrontal

cortex(VMPFC),the

amygdalaan

dthebrain

stem

!processingof

emotional

stim

uli

Deppeetal.,

2005a

Distribution

policy

Isitpossible

tofindthe

‘‘fram

ingeffect’’on

aneuralbasis?

fMRI

Evaluationofthe

credibilityoffictive

headlinesthat

are

combinedwith

differentnewspap

er

logos

n¼21

-Ifthenewspap

erbrandhad

astrongim

pactonthe

judgmentoftheperson,

astrongactivationin

the

VMPFCwas

measured!

integrationofim

plicit

fram

inginform

ationin

thedecision-m

aking

process

Deppeetal.,

2005b

Brandresearch

What

aretheneuralcorrelates

ofbrandchoice?

fMRI

Binarydecisionsbetw

een

‘‘target’’brandan

ddiversebrand

n¼22

Only

thefavorite

brandisable

toemotionalizethedecision

makingprocess.First

choice

brandslead

toadeactivation

inareas

that

areassociated

withan

alytical

processes

andto

activationin

areas

that

areassociatedwith

integratingemotionsin

the

decision-m

akingprocess


Copyright # 2008 John Wiley & Sons, Ltd. Journal of Consumer Behaviour, July–October 2008

DOI: 10.1002/cb

Table

1.Overview

ofselectedstudiesin

alphabetical

order

Study

Subject

Problem

Method

Experimentalset-up

NResults

Deppeetal.,

2007

Distribution

policy

What

influencedoesthe

‘‘fram

ingeffect’’haveon

neuralactivationin

caseof

intuitivedecisions?

fMRI

Evaluationofthe

attractiveness

of

printadsthat

are

combinedwith

differentnewspap

er

logos

n¼21

Ifthenewspap

erbrandhad

astrongim

pactonthejudgment

oftheperson,astrong

activationin

thean

terior

cingulate

cortexwas

measured!

evaluationofthe

relevan

ceofthefram

ingstim

ulus

Erk

etal.,

2002

Productpolicy

Isthere

aneuralrepresentation

ofproductattractiveness?

fMRI

Ran

kingofattractiveness

ofsportscars,limousines,

andsm

allcarswith

scan

neran

dquestionnaire

n¼12

Products

that

symbolize

wealth

andprestigelead

toahigher

activationin

areas

that

are

associatedwiththeperception

ofrewards

Kenningetal.,

2007b

Communication

policy

Can

theperceivedattractiveness

ofan

advertisementbe

associatedwithspecific

neuralactivations?

fMRI

Thesubjects

had

toevaluate

differentadvertisements

bytheirattractiveness

whiletheirbrain

activitywas

measured

n¼22

Attractiveadslead

toastronger

activationin

-TheVMPFC!

integration

ofemotionsin

the

decision-m

akingprocess

-Nucleusaccumbens!

attractiveadscan

work

asrewardstim

ulus

Knutsonetal.,

2007

Pricepolicy

Whichim

pactdoestheprice

haveonproduct

preferencesan

dneuralactivity?

fMRI

Whilemeasuringtheirbrain

activity,

products

with

correspondingprice

inform

ationwere

presentedto

thesubject.

Intheendtheyhad

tomakeabuyingdecision

n¼26

-Activationin

thenucleus

accumbenscorrelates

withproductpreferences

-Theactivationoftheinsula

cortexisevokedby

highprices

-Themedialprefrontalcortex

(MPFC)reacts

toreduced

prices!

pricescan

be

perceiveddifferentlyan

dcan

evokedifferent

neuralreactions.

(Continues)


DOI: 10.1002/cb


Table

1.(Continued)

Study

Subject

Problem

Method

Experimentalset-up

NResults

Koenigsan

dTranel,

2007

Brandresearch

Isitpossible

toreceivethe

sameresultsas

McClure

etal.2004a,

throughthe

observationofpeople

with

lesionsin

theMPFC?

Lesion-study

Inorderto

test

the

‘‘Pepsi-paradox’’(people

preferPepsiin

blindtests,

butCocaCola

ifthey

know

thebrand),three

groupswere

form

edan

dthetastetest

from

McClure

etal.2004awas

repeated,

thistimewithoutthefM

RI

Scan

ner:

1.Healthysubjects

2.Su

bjects

withlesions

notincludingthe

VMPFC

3.Su

bjects

withlesion

intheVMPFC

Groups

1.n¼16

2.n¼16

3.n¼12

Theresultsfrom

McClure

etal.

2004acould

bevalidated:

-Only

personswithlesions

intheVMPFCdid

notshow

preferencebiaswhen

exposedto

brandinform

ation

-Theothergroupswere

susceptible

tobrand

inform

ation

-Theresultsshow

that

the

VMPFCseem

toplayakey

role

indevelopingbrand

preferences

McClure

etal.,

2004a

Brandresearch

What

effectdoesbrand

inform

ationhaveonthe

sensory

perceptionof

similar

products

(CocaCola/Pepsi)?

fMRI

Anonym

ousan

dsemi-

anonym

oustastetestsof

CocaCola

andPepsiinside

andoutsidethescan

ner

n¼67

-TheVMPFCevaluates

sensory

inform

ation

-Throughthecooperationwith

thedorsolateralprefrontal

cortexan

dthehippocam

pus,

memoriesan

dcultural

inform

ation(e.g.,brand

knowledge)areintegrated

inthedecision-m

akingprocess

Plassman

netal.,2005

Brandresearch

What


ofbrandchoiceunderrisk?

fMRI

Subjects

participatedin

abrandchoicetask

where

theyhad

tochoose

betw

een16travelbrands

toariskyan

daless

riskydestination

n¼15

-‘‘First

brandeffect’’was

confirm

ed

-More

prominentactivationof

theMPFCwhenthesubject

facedriskydecisions.

-Integrationofemotionsin

the

decision-m

akingprocess

of

particularim

portan

cein

risky

decision-m

aking



DOI: 10.1002/cb

Table

1.(Continued)

Study

Subject

Problem

Method

Experimentalset-up

NResults

Plassman

netal.,2007b

Distribution

policy

What


ofbrandloyalty?

fMRI

Thesubjects

had

todecide

from

whichretailbrandthey

would

preferto

buyacertain

garment.In

additionto

measuringtheirbrain

activity,

dataabouttheir

buyingbehaviorwere

collected

n¼22

-Loyalcustomers

probably

integrate

emotionsmore

intensively

inthe

decision-m

akingprocess

-Forloyalcustomers

the

favorite

brandcan

bea

rewardingstim

ulus

Plassman

netal.,2007d

Pricepolicy

Isthere

aneuralcorrelate

for

theindividual

willingness

topay?

fMRI

Theypresentedhungry

subjects

food,while

measuringtheirbrain

activity.

Theparticipan

tshad

toevaluatetheir

individual

willingness

topay

n¼19

-Themedialorbitofrontal

cortexplays

probably

akeyrole

forcomputingthe

individual

willingness

topay

-TheDLPFCencodesthe

final

decisionan

dis

responsible

forthemotor

signal

(keypress)

Plassman

netal.,2007e

Pricepolicy

Isahighpriceable

tochan

ge

theexperiencedutility

and

thecorrespondingneural

activity?

fMRI

Thesubjects

tasteddifferent

kindsofwinewiththe

explicitpriceinform

ation,

whiletheirbrain

activity

was

measured

n¼20

Ahighpriceledto

abetter

evaluationofthetastean

dto

achan

gein

theneuralactivity

intheMPFCan

din

therostral

anteriorcingulate

cortex

Rossiteran

dSilberstein,2001

Communication

policy

Isitpossible

toderivehow

welladsareremembered

from

neuralactivation

pattern?

EEG

Thesubjects

watcheddifferent

commercialsan

dwere

asked

whichsingle

scenesthey

remembered

n¼35

Scenesthat

evokedafast

response

intheleft

hemisphere

were

better

remembered

(Continues)



DOI: 10.1002/cb

Table

1.(Continued)

Study

Subject

Problem

Method

Experimentalset-up

NResults

Schaefer

etal.,2006

Brandresearch

What


ofbrandknowledge?

fMRI

Theresearchers

presented

subjects

culturalfamiliaran

dculturalunfamiliarlogosof

car

man

ufacturesan

dasked

them

toim

aginethemselves

drivingthecar

n¼13

-Significan

tactivationsin

the

MPFCwere

found,whenthe

subjects

were

exposedto

familiarbrandinform

ation

!confirm

ationofthe

importan

ceofthisbrain

regionfortheprocessing

ofculturallybasedbrands

-Brandsmightfunctionas

subconsciouspresentiments

that

influencethedecision-

makingprocess,before

the

participan

tsevenstarted

thinkingaboutadvan

tages

anddisadvan

tagesof

thecars

Yoonetal.,

2006

Brandresearch

Dopersonsbuildupa

connectionto

abrandthat

resemblesasocial

relationship?

fMRI

Participan

tswere

scan

nedwhile

makingjudgments

about

whetheratraitadjective

describedatargetcue

(products

andpersons)

n¼25

Characterizationofpersonsleads

toastrongeractivationin

theMPFCin

comparisonto

thecharacterizationofbrands

Fortheevaluationofproduct

attributesastrongeractivation

inobjectrelatedbrain

areas

was

measured!

theconcept

of‘‘brandpersonality’’has

toberevisedbecause

itis

notpossible

totran

sfer

human

likeattributesto

brandsin

anunlimitedway



DOI: 10.1002/cb


partly be applied in order to predict purchas-ing behavior. Knutson et al. (2007) supportedthese findings: results from their study pro-vided evidence that activation of the nucleusaccumbens correlates with individual productpreferences and that activation in this areaduring product presentation may at least partlypredict subsequent purchasing decision.

Price policy

Price policy is a central concept in marketingbecause it constitutes a basic influencing factorof the company’s sales result and profits (Rao,1984; Pasternack, 1985; Gabor and Granger,1979; Lichtenstein et al., 1993). Particularly insaturated markets, this marketing-mix instru-ment has gained greater importance. A veryinteresting phenomenon often observed inprice policy is that a similar price level can beperceived by the buyer in two different ways,depending on diverse product categories. Onthe one hand, high prices can deter customersfrom buying a product because those pricesare perceived as a loss. On the other hand, highprices can be seen as an indicator for highquality, and can enhance the product value andthe probability that the customers will buy thegoods (Lichtenstein et al., 1993; Volckner,2007). This holds particularly true whencustomers have uncertainty about buying aproduct, because they are not familiar with it,yet. However, asking consumers about pricingissues can sometimes be ineffective. Forinstance, consumers are often not able torecall prices (Vanhuele and Dreze, 2002;Evanschitzky et al., 2004), and it is verydifficult for them to specify abstract economicconcepts like the ‘‘willingness to pay’’ orexperienced utility. In addition, they mightrespond strategically when asked about con-structs like price fairness.Against this background, Knutson et al.

(2007) examined the neural correlates of thenegative price effect. While lying in the fMRIscanner, subjects had to solve an exercise inwhich they first saw a product, and then sawthe same paper with its corresponding price


information. In the end they had to decidewhether or not to buy the product. The resultsresembled those of studies examining theneural correlates of anticipation and thereceipt of gains (Breiter et al., 2001; Knutsonand Peterson, 2005) and losses (Sanfey et al.,2003). Hence, the activation of the nucleusaccumbens (activation through the anticip-ation of gains) correlates with product pre-ferences, the activation of the insula (acti-vation through the anticipation of losses) withhigh prices, and the activation of the medialprefrontal cortex (activation through theprocessing of gains and losses) with reducedprices. This result supports the speculationthat activity changes in the insula might reflectthe perception of a loss and, thus, the neuralrepresentation of a negative price effect. In thefuture this information can be important, forexample, in the identification of price limits.A more recent study from Plassmann et al.

(2008) examined the opposite positive skew-ing impact of price setting on the evaluation ofa specific product. In their fMRI experiment,subjects consumed wine that was presentedwith explicit price information. The resultsshowed, among other things, that the personsnot only evaluated the more expensive wine asbeing better, but also that the neural activation— in the medial prefrontal cortex and in therostral anterior cingulate cortex — indicatedsignificant activation differences in relation tohigher price information. Based on theseresults, Plassmann et al. (2008) assumed thatthe experienced utility of a product is not onlydependent on intrinsic aspects such as thecomposition of the wine or thirst, but it is alsoimpacted by other adjustable factors within theframe of marketing-mix instruments such asprice setting.Another important issue in price policy is

the high degree of wasted opportunities forcustomization. It can be very profitable forfirms with heterogeneous customer segmentsto charge individual prices according to thevalue that different customers place on aproduct. For the adjustment of prices at theright level, it is necessary to know how peoplecompute their individual ‘‘willingness to pay’’


DOI: 10.1002/cb


— themaximumprice that a buyer is willing topay for a specific object (Simon and Dolan,1998). As mentioned above, the determinationof this abstract concept is very difficult withexisting research methods. Recently, in anfMRI study from Plassmann et al. (2007d),hungry subjects were scanned while differentedibles were presented. The task was topropose a specific amount of money thatsuited the subject’s personal ‘‘willingness topay.’’ The data showed that the medialprefrontal cortex is likely to play an activerole in computing the maximal acceptableprice. The dorsolateral prefrontal cortex codesthe final decision and seems to be essential forthe motor signal (e.g., the push of a button, orbuying).

Communication policy

Besides products and prices, communicationplays an increasingly decisive role in market-ing. In the future, one important challenge forthis marketing-mix instrument is the psycho-logical differentiation of brands (Milgrom andRoberts, 1986; Meenaghan, 1995). We assumethat, especially within communication policy,consumer neuroscience can help to bridge theexisting lack of theory (Pitt et al., 2005). Thequestion of how the brain processes and storesadvertising stimuli may have essential import-ance.Regarding the short-term processing of

advertisements, two studies by Kenninget al. (2007b) and Plassmann et al. (2007c)dealt with the neural correlates of attractiveadvertisements. Brain activity of subjects wasmeasured by an fMRI scanner while they rateddifferent advertisements according to theirattractiveness. The data showed that anadvertisement that was rated as attractive ledto activation in brain areas associated with theintegration of emotions in the decision-makingprocess (ventromedial prefrontal cortex) andthe perception of rewards (ventral striatum/nucleus accumbens). Kenning et al. (2007b)concluded from these results that attractive adscan act as a rewarding stimulus. In addition,


the studies revealed that positive facialexpressions are an essential component ofattractive advertisements. A possible expla-nation for this is provided by Aharon et al.(2001), who showed that beautiful femalefaces led to the activation of reward-relatedareas in the brains of heterosexual males.Future studies may provide further informationabout the effect of typical ad stimuli such as theschemes of childlike characteristics or pup-pies.

Referring to the long-term memorization ofbrand information, two exploratory exper-iments conducted by Ambler and Burne (1999)and Ambler et al. (2000) showed that anadvertisement is remembered better if it isconnected with emotional images, in compari-son to use of exclusively rational arguments. Ina preliminary pharmacological study (Amblerand Burne, 1999), b-blockers (propranolol)and placebos were randomly dispensed to theparticipants, who were than asked to watchbrand advertising. b-blockers are defined as aclass of drugs that block specific receptorsand hence inhibit the effect of certain stresshormones (www.texasheartinstitute.org, 4.3.2008). Ambler and Burne (1999) used this classof medication because it is noted to reduceaffective responses to stimuli, which wouldenhance their goal of examining the effect ofemotions on the recall and recognition ofadvertising. Results showed that the suppres-sion of emotions due to the pharmacologicaltreatment had an effect on recall and recog-nition of ads. The placebo and control groupthat did not receive b-blockers showed ahigher recall and recognition rate of affectiveads, in comparison to cognitive ads. Incontrast, subjects from the b-blocker groupdid not show similar effects. The participantstreated pharmacologically, in fact, remem-bered the cognitive ads better than theemotional ads. Within the main experiment,Ambler et al. (2000) applied magnetoence-phalography (MEG) to prove that cognitivepictures cause a stronger activation inposterior parietal areas and in the superiorprefrontal cortex, which may be traced to amore intense use of working memory. After


DOI: 10.1002/cb


presenting the more affective images, asignificant activation was observable in theareas of ventromedial prefrontal and orbito-frontal cortex, as well as in the amygdala andthe brain stem.

Distribution policy

The distribution policy comprises all decisionsconcerning the optimal distribution of goodsbetween manufacturer and retailer. Theoptimal distribution of products can have aprominent influence on the buying decisionsof customers (Ailawadi and Keller, 2004;Kotler and Keller, 2006). Therefore, a centralaspect of this important marketing-mix instru-ment is the choice of product- and brand-adequate marketing channels, in order todefine the optimal frame for the presentationof a brand (Pasternack, 1985; Eliashberg andSteinberg, 1987; Choi, 1991; Lee and Staelin,1997). In two similarly constructed studies,Deppe et al. (2005a, 2007) examined theneural correlates of this ‘‘framing effect.’’ Amain finding of their investigations was thatthe medial prefrontal cortex and the anteriorcingulate cortex, in particular, play a centralrole for the integration of implicit framinginformation, for example, the importance ofemotions and unconscious memories in thedecision-making process.In a similar vein, Plassmann et al. (2007b)

identified the neural correlates of retail brandloyalty. In their fMRI study, subjects had tochoose between retail brands from which theywould prefer to buy an identical garment. Withthe help of previously collected informationabout the buying behavior of the subjects, theresearchers were able to identify the favoriteretail brand of the participants. Furthermore, adivision into two groups was possible, and wasmade according to the previous average buyingbehavior of the subjects. Group A spent aminimum of 250s on five or more shoppingdays per month at a certain retailer (so-called‘‘loyal customers’’), Group C spent amaximumof 50s and had only one shopping day permonth at the same retailer (so-called ‘‘disloyal


customers’’). The analysis of the data showedthat loyal customers integrate emotions intothe decision-making process in a more intenseway (activation in the ventromedial prefrontalcortex), and that the favorite brand can act as abehaviorally relevant rewarding stimulus. Incontrast, this activation was not measurable fordisloyal participants. Plassmann et al. (2007b)concluded from their results that the use ofemotional reinforcers in marketing can con-stitute the base for long-term customer reten-tion. Through a learning process, positiveexperiences are combined with the retailbrand, then stored in the memory of thecustomer and recalled for buying decisions.

Brand research

The field of brand research is concerned withexamining the important influence of brandinformation on decision-making (Ailawadi andKeller, 2004). One central topic of brandresearch is whether or not consumer decisionsare influenced by brand information. Deppeet al. (2005b) addressed this question in astudy designed to determine which neuralprocesses are involved in the brain during theprocessing of brand information. In their fMRIstudy, subjects had to make fictitious buyingdecisions between two very similar productsthat were differentiated only by brand infor-mation. In one part of the study, subjects hadto choose between the brand with the greatestmarket share — which had been declared asthe target (‘‘T’’) brand in the preliminaryphase — and diverse (‘‘D’’) brands (TDdecisions). In the next part of the study, theyhad to decide between two diverse brands (DDdecisions). The data analysis showed a signifi-cant difference in brain activity between TDand DD decisions, if the subjects had declaredthe target brand as their preferred brand (firstchoice brand, FCB group) in the pretest phase.A closer look into the brain activities of the FCBgroup showed a reduced activity in thedorsolateral prefrontal cortex, left premotorarea, posterior parietal, and occipital cortices— areas that are generally associated with


DOI: 10.1002/cb


working memory, planning, and logic de-cisions. Deppe et al. (2005b) assumed thatfor decisions comprising the favorite brand ofthe consumer, strategic processes are nolonger as relevant. The responsible brainregion is deactivated and a ‘‘cortical release’’occurs (Kenning et al., 2002). In contrast, anincreased activity was measured in the ventro-medial prefrontal cortex, the inferior precu-neus, and the posterior cingulate cortex. Theseareas operate as association cortices and haveimportant functions in combining incominginformation with background knowledge, therecall of episodicmemories, and self-reflection.The increased activation in the ventromedialprefrontal cortex during decisions in the FCBgroup could be interpreted as integration ofemotions into the decision-making process(Bechara and Damasio, 2005). Thus, the resultsrevealed a so-called ‘‘winner-take-all’’ effect:only the favorite brand of the subject is able toemotionalize the decision-making process.This finding is crucial for marketing researchbecause it is contrary to the well-establishedconsideration-set concept. Whereas the con-sideration-set theory assumes that there is setof goal-satisfying alternatives (Shocker et al.,1991), the results of Deppe et al. (2005b)provide evidence that only the favorite brand isable to trigger significant cortical activationpattern. Intriguingly, a lesion study conductedby Koenigs and Tranel (2007) confirmed thesuggestions of Deppe et al. (2005b). Personswith damage within the ventromedial prefrontalcortex that exhibit irregularities in emotionalprocessing did not show the normal preferencebiases when exposed to brand information.Plassmann et al. (2005) provided additional

support for the investigated ‘‘first choice brandeffect.’’ Their study aimed to explain theinfluence of brand information within uncer-tain situations, by investigating the role of theprefrontal cortex during decision-makingunder risk. The subjects participated in abrand choice task where they had to choosebetween sixteen travel brands, for travel to arisky and a less risky destination. In addition tothe ‘‘first choice brand effect,’’ the dataanalysis exhibited a more prominent activation


of the medial prefrontal cortex when thesubject faced risky decisions. Plassmann et al.(2005) reasoned that the integration ofemotions in the decision-making process, asopposed to analytical decision strategies, is ofparticular importance in risky decision-mak-ing. One potential reason for this might be thatemotions could provide additional consciousor unconscious information.

Analogous to the studies mentioned, Schae-fer et al. (2006) confirmed the reportedimportance of the medial prefrontal cortexfor decision-making influenced by brand infor-mation (Plassmann et al., 2005; Deppe et al.,2005b). Schaefer et al. (2006) presented theirsubjects with culturally familiar and unfamiliarlogos of automobile manufacturers, and askedthem to imagine themselves driving the car. Ifthey did not know the car manufacturer,participants were instructed to imagine ageneric car. Interestingly, Schaefer et al.(2006) found significant activity changes inthe medial prefrontal cortex when the subjectswere exposed to familiar brand information, aresult that confirms the importance of thisbrain region for the processing of culturallybased brands. Because the medial prefrontalcortex is often associated with self-reflectionand self-relevant information processing,Schaefer et al. (2006) concluded that theimagination of driving a familiar car led to self-relevant thoughts. Furthermore, the resultssuggested that brands might function assubconscious presentiments that influencedthe decision-making process even before theparticipants began thinking about advantagesand disadvantages of the cars. This suggestionis supported, to some degreed, by Deppe et al.(2007) and their investigations of the neuralprocessing of magazine brands.

Another abstract and implemented conceptwithin the framework of brand research is‘‘brand personality’’ (Aaker, 1997). Advertisingoften applies this construct by using productdescriptions that correspond to humanliketraits (e.g., Henkel: ‘‘a brand like a friend’’). Forexample, it is possible to describe both a friendand a car as ‘‘reliable.’’ Yoon et al. (2006)examined the concept of ‘‘brand personality’’


DOI: 10.1002/cb


by addressing the question of whether thebrain processes semantic judgments aboutobjects and persons in different ways. Theirdata analysis revealed that the characterizationof persons leads to a stronger activation in themedial prefrontal cortex, compared to thecharacterization of brands. For the evaluationof product attributes, a stronger activation inobject-related brain areas, such as the leftinferior prefrontal cortex, was measured.These results might be crucial for marketingresearch and brand management, as theysupport a conclusion that it is not possibleto transfer human-like attributes to brands inan unlimited way. This observation is alsosupported by the phenomenon that subjectsreveal higher rates of missing values when the‘‘brand personality’’ scales are applied tounfamiliar brands.

Prominent brain structures forconsumer neuroscience

The discussed studies show that consumerneuroscience has already localized importantbrain structures associated with the processingof products, prices, advertisements, and(retail) brands. However, it is crucial to usecaution for the interpretation of neuralactivation patterns, because the activation ofa specific area can mean different thingsdepending on the context (Sanfey, 2007).Accordingly, one aim of this paper is to enableconsumer researchers to better understand thefunctionality of the brain. To achieve this goal,the following summary of the discussed brainstructures is organized as follows. First, theconstruct of interest is described. Next, thedelineation of marketing stimuli that can affectthis variable is detailed, followed by a briefdepiction of the brain structures associatedwith the construct of interest.

Reward

The encoding of rewards as stimuli thatpositively reinforce behavior is dependent


on learned expectations, context, time dimen-sions, and reward amplitude (McClure et al.,2004b). Brain structures that are involved inprocessing rewards are often summarized bythe term ‘‘reward system.’’ This complexnetwork of different brain areas plays animportant role for the understanding ofconsumer behavior. By evaluating the stimulusvalue and by predicting when a certain stimuliwill occur, the reward system seems to beconcerned with seeking out rewards andevading punishments (O’Doherty, 2004). Ingeneral, the reward system is seen as acomplex evaluation system that drives particu-larly goal-directed behavior and corresponds toa closely linked network of different brainstructures with various functions such as theventral striatum/nucleus accumbens, the orbi-tofrontal cortex, and the amygdala (McClureet al., 2004b; Sanfey, 2007). Recent findingsshow that the reward system can be activatednot only by primary rewards such as food,water, and sexual stimuli, but also throughattractive advertisement (Kenning et al.,2007b), price reductions (Knutson et al.,2007), beautiful faces (Aharon et al., 2001),or status symbols such as sports cars (Erk et al.,2002). The reward system also seems to beinvolved in the development of productpreferences and brand loyalty (Plassmannet al., 2007b).The nucleus accumbens, a component of

the ventral striatum, belongs to themesolimbicdopamine system that is often associated withthe pursuit of pleasure. Erk et al. (2002) andKnutson et al. (2007) point out that thenucleus accumbens is involved in the for-mation of product preferences, because itsactivity scales with the evaluation of a stimulus.Therefore, recent findings often connect thenucleus accumbens with the anticipation andprediction of rewards (McClure et al., 2004b;Sanfey, 2007; Plassmann et al., 2007b).The evaluation of the rewarding aspects of

incoming stimuli is primarily assigned to theorbitofrontal cortex (O’Doherty, 2004). Thestudies conducted by Erk et al. (2002) andAmbler et al. (2000) demonstrate the import-ance of the orbitofrontal cortex for the


DOI: 10.1002/cb


evaluation of incoming stimuli such as attrac-tive cars or emotional ads. Due to its closeconnection with numerous brain structuresand its capability tomemorize the reward valueof sensory stimuli, the orbitofrontal cortexmight play an important role for the processingof rewards and the emergence of behavior(O’Doherty, 2004; McClure et al., 2004b).Another important structure of the reward

system might be the amygdala. In contrast tothe orbitofrontal cortex, which seems toencode for the valence of a stimulus, theactivation of the amygdala may indicate theperceived strength of arousal of an incomingstimulus (McClure et al., 2004b).

Punishment

An additional issue of interest is the encodingof punishment in the human brain. Punishingstimuli are defined as incentives that lead toavoidance behavior, in the sense that peopleexpend energy in order to evade them(Seymore et al., 2007). Primary stimuli thatinduce punishment are, for example, physicalpain, aversive odors/tastes, or disgust.Recent studies from consumer neuroscience

and neuroeconomics discovered that theseneural mechanisms can also be activated byrelevant economic stimuli such as the percep-tion of unfair offers, monetary losses, and highprices (Sanfey et al., 2003; Knutson et al.,2007).Brain structures involved in the processing

of punishment are, among others, the orbito-frontal cortex, the amygdala, and the insulacortex. Although their functions are not fullyunderstood, these areas seem to correspond tothe reward system, and it is not possible toaccurately delineate the reward and thepunishment system. For example, the orbito-frontal cortex not only encodes the rewardingvalue but also the negative value of anincoming stimulus. Another example for anarea that seems to be involved in both systemsis the amygdala, because aversive stimuli canlead to activation in this area as well. In fact,earlier studies predominantly associated the


amygdala with the perception of fear ornegative emotions (McClure et al., 2004b).Today, it is assumed that both rewarding andaversive stimuli can lead to an activation of theamygdala, depending on the strength ofarousal and the intensity of a stimulus(O’Doherty, 2004; McClure et al., 2004b).

A structure that is primarily associated withthe processing of aversive stimuli is the insulacortex. Again, its functions are to a large extentstill unexplored, but the insula cortex seems tobe involved in the anticipation of losses (e.g.,processing of high prices; Knutson et al.,2007) and the perception of unfair offers(Sanfey et al., 2003).

Decision-making

Decision-making can be described as theevaluation of a situation and the choice of anappropriate action. For consumer research, theunderstanding of this decision-making processis very important, because consumers have tomake specific decisions, for example, for abrand, in almost every shopping situation.Even though a strict distinction of the differentmechanisms behind the decision-making pro-cess is not possible, there are three crucialaspects for a certain choice: the evaluation ofan incoming stimulus, rational consideration,and the emotional component (Bechara andDamasio, 2005).

The prefrontal cortex is a very importantbrain structure linked to decision-making(Ridderinkhof et al., 2004). In addition to itsinteraction with emotional structures in therewarding/punishment system, this brain areaplays a key role in consumer decision-making(Wood and Grafman, 2003; Bechara andDamasio, 2005). The prefrontal cortex canbe divided into three parts that appear to fulfilldifferent functions: the orbitofrontal cortex,the ventromedial cortex, and the dorsolateralcortex.

As already mentioned above, the orbitofron-tal cortex is closely connected to the reward/punishment system and is often associatedwith the evaluation of an incoming stimulus.


DOI: 10.1002/cb


The dorsolateral part of the prefrontal cortex isprimarily involved in cognitive actions. Inter-estingly, its activation can be reduced ifconsumers have to make decisions thatcomprise their favorite brand (Deppe et al.,2005b). On the other hand, the dorsolateralprefrontal cortex is very important for rationaldecision-making such as estimating the ‘‘will-ingness to pay’’ (Plassmann et al., 2007d). Theventromedial part of the prefrontal cortexmight be crucial for the integration of emotionsin the decision-making process, due to its closeconnection to the amygdala and the hippo-campus (Wood and Grafman, 2003). Thestudies of Ambler et al. (2000), Deppe et al.(Deppe et al., 2005a,b), Kenning et al.(2007b), and Plassmann et al. (2007b) indicatethat the ventromedial prefrontal cortex is notonly associated with the processing of attrac-tive and affective images, but that it is alsorelevant for building up product preferencesand brand loyalty. Furthermore, activation inthe ventromedial prefrontal cortex can be anindicator of how easily people are influencedby brand information, and thus can beinterpreted as the individual ‘‘framing effect.’’Interestingly, brain damage in this area leads toless susceptibility to brands (Koenigs andTranel, 2007).

Conclusion

By giving a general overview of the currentstate of consumer neuroscience, the aim of thispaper was to show that a wide spectrum of thetraditional marketing-mix components andbrand research is already being investigatedin this new research area. Key contributionswere to make a first move toward definingneuromarketing as an applied science, and tohighlight the importance of consumer neuro-science as a more objective measure ofindividual responses to marketing stimuli.The application of methods from brain

research to marketing relevant problems hasalready yielded several theoretical implica-tions. First, as discussed in the introduction,the neuroscientific measurement approachcan lead to more objective results, and the


researchers hope to gain specific new insightsinto unconscious and automatic processes thatinfluence human behavior. Second, neuroeco-nomics and consumer neuroscience emergedfrom the consolidation of economics andneuroscience. This transdisciplinary approachmay assist both disciplines to gain innovativeperspectives and to generate new ideas. Fromthis, it follows that consumer neuroscience canconfirm, reconfigure, or improve conventionaltheories of marketing theory (Fugate, 2007). Inthis regard, one important contribution ofconsumer neuroscience is the emphasis onemotions and their influence on consumerdecision-making. Consumers are no longerconsidered as completely rational, becauseemotions, unconscious and automatic pro-cesses, play a central role in generatingbehavior (Bechara and Damasio, 2005;Camerer et al., 2005). The strict distinctionbetweenmarketing-mix instruments is anotherexample that can be derived from the studiespresented. The studies on ‘‘framing effect’’(Deppe et al., 2005a, 2007) yield importantinsights not only for distribution policy, butalso for communication policy. In fact, there isa strong interaction between the classicalmarketing-mix instruments because the con-sumer perceives all elements simultaneously(Plassmann et al., 2008). Therefore, a possibleimplication could be a new conceptualizationof this approach.However, consumer neuroscience is still in

the fledgling stages, and current investigationshave been mostly targeted to basic research.For that reason, to date, the direct practicalrecommendations must be derived from thenew findings very carefully (Plassmann et al.,2007a). Nevertheless, in the next years aconcrete deduction of practical implicationswill be very likely. In order to achieve short-term operative optimization goals, consumerneuroscience could, for example, examinewhether a variation of the brand is reasonable,or how the communication between consu-mer and company can be improved. Withregard to long-term product strategy, consu-mer neuroscience could be used to determinewhich consumer segments are reached by


DOI: 10.1002/cb


advertisement strategies, or whether a futurepurchase of the brand is probable. Anotherpossible field of application is the determi-nation of the market potential for a newproduct or for discontinued products. Thenew techniques offered by the emerging fieldcould address the questions associated withthe potential profitability of revitalization of adiscontinued brand (Kenning et al., 2002;Braeutigam, 2005). With respect to currentregulatory policies such as competition law,the findings of consumer neuroscience canhelp to improve existing practices, whichwere previously based on erroneous theoreti-cal assumptions, such as the consumer makinga buying decision on a rational basis (Chorvatet al., 2004).As the ultimate buying decision-makers,

consumers can profit from the findings ofconsumer neuroscience as well, by beingpresented with products that they actuallydesire. Moreover, consumers will learn tobetter understand their own behaviors. Froman ethical point of view, neuromarketing isoften associated with the abuse of neuroscien-tific methodologies, as a means to ‘‘read’’consumers’ minds and to manipulate theirthoughts and behaviors. At present, suchconcerns are arbitrary, because the technol-ogies are still very imprecise and investigatingthe brain activations does not necessarily yieldan understanding of how the brain works(Fugate, 2007). Another way that consumerneuroscience can benefit the consumer is forexample, to investigate the neural correlates ofshopping addiction. It could be hypothesizedthat people suffering from shopping addictionshow irregularities in executive regions (e.g.,prefrontal cortex) or in areas associated withthe perception of losses (e.g., insula; Knutsonet al., 2007). Thus, they might experience onlythe rewarding feeling and are not able tocontrol themselves. Even though investi-gations by Bijou et al. (2004) that explorethe connection of prefrontal dysfunction andcredit card use do not support this assumption,further investigations may help people controltheir buying habits, andmay help consumers ingeneral to protect themselves from their own


emotions in the buying process. In order toprevent the risk that neuromarketing inter-venes in personal privacy to an unacceptabledegree (The Lancet, 2004), institutions andneuroethic conferences are already discussingthe need for the responsible use of the newtechniques and the associated findings.

As with any new approach, consumerneuroscience must face the challenge of somelimitations. For example, the studies are verycost and time intensive, and are associatedwith legal and moral considerations. Asmentioned above, the outcome of experimentsto date needs to be further validated andexpanded, because of the complex dataanalysis required, the relatively small numberof existing studies, and the relatively simpleexperimental setting that is necessary forconducting brain imaging studies (Plassmannet al., 2007a). Even though the technicalmethods are steadily improving, they still onlyoffer a relatively indirect measurement ofcortical activity changes, due to limitationsin temporal and spatial resolution. Beyond this,all results provided by consumer neurosciencerely on the assumption that the measuredactivation is not the result of only noise orsystematic errors, that a correct spatial andtemporal assignment of measured quantities ispossible, and that the supposition abouttypical functions of certain brain areas is validin the actual case as well. Furthermore, it ispresumed that the stimulus under investi-gation and no confounder leads to the corticalresponse of the participating subject (Kenningand Plassmann, 2005).

Another limitation could be the validity ofthe studies, which is often called into question.Due to high costs, the number of the participat-ing subjects is usually very low and a smallsample size may include the possibility of falsepositives and a higher probability of committinga type II error (Tversky and Kahneman, 1971).However, an argument for the validity of theresults could be that several researchers ofdifferent nationalities, applying various exper-imental settings to investigate marketingrelevant questions with the help of brainresearch methods, have arrived at very similar


DOI: 10.1002/cb


results concerning the specific brain activation(Ambler et al., 2000; McClure et al., 2004a;Koenigs and Tranel, 2007; Kenning et al.,2007b; Plassmann et al., 2007a). On the otherhand, the described robustness of the neuroe-conomic findings may also constitute a counter-argument for the validity. For example, weknow that there are both semantic andphenomenological variations between differentbrands, but the brain seems to process them in avery similar way, as can be deduced byobserving the specific activation pattern withfMRI. Thus, it could be possible that the researchmethod is still too inaccurate to measure smallvariations in brain activation.With this paper we hope to rectify the

sometimes over-simplified assumption thatconsumer neuroscience is focused on a searchfor the ‘‘holy grail’’ of marketing, the ‘‘buybutton’’ in the brain. Our evidence shows thatthere is no possibility of such a result.Furthermore, though the application of neuro-logical methods in the area of marketingresearch has already yielded relevant findingsin both theory and practice (Plassmann et al.,2007a), because of the complex data analysisrequired and the relatively small number ofexisting studies, the outcome of experimentsto date needs to be further validated andexpanded (Cacioppo et al., 2003; Kenning andPlassmann, 2005). Nevertheless, by observingthe brain — the organ of (buying) decisions –one of the most fascinating objects of researchis now spotlighted by marketing research.

Biographical notes

Mirja Hubert completed undergraduate stu-dies in business at Humboldt-University, Ber-lin, majoring in Marketing and InternationalManagement. Since September 2007, she is aResearch Assistant to Professor Peter Kenningat Zeppelin University, Friedrichshafen,Germany.Peter H. Kenning is a Professor of Marketing

at Zeppelin University, Germany. His primaryresearch interests are consumer behavior, con-sumer neuroscience, neuroeconomics, andmarketing management. His work has been


widely published, for example, in Inter-

national Journal of Advertising, Manage-

ment Decisions, Journal of Product and

Brand Management, Advances in Consumer

Research, Journal of Neuroimaging, Neu-

roReport, and Brain Research Bulletin. Hehas presented papers at numerous conferencesincluding AMA-Conference EMAC, and ACR.For his work he received several best paperawards and grants.

References

Aaker JL. 1997. Dimensions of brand personality.

Journal of Marketing Research 34(3): 347–356.

Aharon I, Etcoff N, Ariely D, Chabris C, O’Connor E,

Breiter H. 2001. Beautiful faces have variable

reward value-fMRI and behavioral evidence.

Neuron 32(3): 537–551.

Ailawadi KL, Keller KL. 2004. Understanding retail

branding: conceptual insights and research

priorities. Journal of Retailing 80(4): 331–342.

Ambler T, Burne T. 1999. The impact of affect on

memory of advertising. Journal of Advertising

Research 39(2): 25–34.

Ambler T, Ioannides A, Rose S. 2000. Brands on the

brain: neuro-images of advertising. Business

Strategy Review 11(3): 17–30.

Anderson EW, Fornell C, Lehmann DR. 1994. Cus-

tomer satisfaction, market share, and profitabil-

ity: findings from Sweden. Journal of Marketing

58(3): 53–66.

Bagozzi RP. 1991. The role of psychophysiology in

consumer research. In Handbook of Consumer

Behavior, Robertson TS, Kassarjian HH (eds).

Prentice-Hall: Englewood Cliffs, NY; 124–161.

Bailetti AJ, Litva PF. 1995. Integrating customer

requirements into product designs. Journal of

Product Innovation Management 12(1): 3–15.

Bechara A, Damasio AR. 2005. The somatic marker

hypothesis: a neural theory of economic

decision. Games and Economic Behavior 52:

336–372.

Bechara A, Damasio H, Damasio AR. 2000. Emotion,

decision making and the orbitofrontal cortex.

Cerebral Cortex 10: 295–307.

Bijou Y, Spinella M, Lester D. 2004. Credit card use

and prefrontal cortex dysfunction: a study in

neuroeconomics. Psychological Reports 94(3):

1267–1268.


DOI: 10.1002/cb


Blakeslee S. 2004. If you have a ‘‘Buy Button’’ in your

brain, what pushes it? New York Times 154: 5.

Bloch PH. 1995. Seeking the ideal form: product

design and consumer response. Journal of Mar-

keting 59(3): 16–29.

Braeutigam S. 2005. Neuroeconomics—from

neural systems to economic behavior. Brain

Research Bulletin 67: 355–360.

Breiter H, Aharon I, Kahneman D, Dale A, Shizgal P.

2001. Functional imaging of neural responses to

expectancy and experience of monetary gains

and losses. Neuron 30: 619–639.

Cacioppo JT, Berntson GG, Lorig TS, Norris CJ,

Rickett E, Nusbaum H. 2003. Just because you’re

imaging the brain doesn’t mean you can stop

using your head: a primer and set of first prin-

ciples. Journal of Personality and Social Psy-

chology 85(4): 650–661.

Camerer C, Loewenstein G, Prelec D. 2005. Neu-

roeconomics: how neuroscience can inform eco-

nomics. Journal of Economic Literature 43: 9–64.

Choi SC. 1991. Price competition in a channel

structure with a common retailer. Marketing

Science 10(4): 271–296.

Chorvat TR, McCabe K, Smith V. 2004. Law and

neuroeconomics, George Mason Law and Eco-

nomics Research Paper.

Constantinides E. 2006. The marketing mix

revisted: towards the 21st century marketing.

Journal ofMarketingManagement 22: 407–438.

Cooper RG. 1979. The dimensions of industrial new

product success and failure. Journal of Market-

ing 43(3): 93–103.Deppe M, Schwindt W, Kramer J, Kugel H, Plas-

smann H, Kenning P, Ringelstein EB. 2005a.

Evidence for a neural correlate of a framing

effect: bias–specific activity in the ventromedial

prefrontal cortex during credibility judgments.

Brain Research Bulletin 67: 413–421.Deppe M, Schwindt W, Kugel H, Plassmann H,

Kenning P. 2005b. Nonlinear responses within

the medial prefrontal cortex reveal when specific

implicit information influences economic

decision-making. Journal of Neuroimaging 15:

171–182.

Deppe M, Schwindt W, Pieper A, Kugel H, Plas-

smann H, Kenning P, Deppe K, Ringelstein EB.

2007. Anterior cingulate reflects susceptibility to

framing during attractiveness evaluation. Neu-

roReport 18(11): 1119–11123.


Eliashberg J, Steinberg R. 1987. Marketing-pro-

duction decisions in an industrial channel of

distribution. Management Science 33(8): 981–

1000.

Erk S, Spitzer M,Wunderlich AP, Galley L, Walter H.

2002. Cultural objects modulate reward circui-

try. NeuroReport 13(18): 2499–2503.

Evanschitzky H, Kenning P, Vogel V. 2004. Con-

sumer price knowledge in the German retail

market. Journal of Product and Brand Manage-

ment 13(6): 390–405.

Fugate DL. 2007. Neuromarketing: a layman’s look

at neuroscience and its potential application to

marketing practice. Journal of Consumer Mar-

keting 24(7): 385–394.

Gabor A, Granger CWJ. 1979. Price sensitivity of the

consumer. Management Decisions 17(8): 569–

575.

Groeppel-Klein A. 2005. Arousal and consumer in-

store behavior. Brain Research Bulletin 67:

428–437.

Howard JA, Sheth JN. 1969. The Theory of Buyer

Behavior. John Wiley & Sons: New York.

Kenning P, Plassmann H. 2005. NeuroEconomics:

an overview from an economic perspective.

Brain Research Bulletin 67: 343–354.

Kenning P, Plassmann H, Ahlert D. 2007a. Appli-

cations of functional magnetic resonance ima-

ging for market research. Qualitative Market

Research: An International Journal 10(2):

1352–2752.

Kenning P, Plassmann H, Deppe M, Kugel H,

Schwindt W. 2002. The discovery of cortical

relief. Field of Research: Neuromarketing 1: 1–

26.

Kenning P, Plassmann H, Kugel H, Schwindt W,

Pieper A, Deppe M. 2007b. Neural correlates of

attractive ads, FOCUS-Jahrbuch 2007, Schwer-

punkt: Neurookonomie, Neuromarketing, Neu-

romarktforschung, Koschnick WJ (ed.). FOCUS

Magazin Verlag: Munich; 287–298.Knutson B, Peterson R. 2005. Neurally reconstruct-

ing expected utility. Games and Economic

Behavior 52: 305–315.

Knutson B, Rick S, Wimmer GE, Prelec D, Loewen-

stein G. 2007. Neural predictors of purchase.

Neuron 53(1): 147–156.

Koenigs M, Tranel D. 2007. Prefrontal cortex

damage abolishes brand-cued changes in cola

preference. Social Cognitive and Affective


DOI: 10.1002/cb


Neuroscience Advance Access (published online

on 18 September 2007): 1–6.

Kotler P, Keller KL. 2006.MarketingManagement.

Prentice-Hall International: New Jersey.

Lee E, Staelin R. 1997. Vertical strategy interaction:

implications for channel pricing strategy. Mar-

keting Science 16(3): 185–207.

Lee N, Broderick AJ, Chamberlain L. 2007. What is

‘‘neuromarketing’’? A discussion and agenda for

future research. International Journal of Psy-

chophysiology 63: 199–204.

Lichtenstein DR, Ridgway NM, Netemeyer RG.

1993. Price perceptions and consumer shopping

behavior: a field study. Journal of Marketing

Research 30(2): 234–245.

McClure SM, Li J, Tomlin D, Cypert KS, Montague

LM, Montague PR. 2004a. Neural correlates of

behavioral preference for culturally familiar

drinks. Neuron 44: 379–387.

McClure SM, York MK, Montague PR. 2004b. The

neural substrates of reward processing in

humans: the modern role of fMRI. The Neuros-

cientist 10(3): 260–268.

Meenaghan T. 1995. The role of advertising in

brand image development. Journal of Product

and Brand Management 4(4): 23–34.

Milgrom P, Roberts J. 1986. Price advertising signals

of product quality. The Journal of Political

Economy 94(4): 796–821.

O’Doherty JP. 2004. Reward representations and

reward-related learning in the human brain:

insights from neuroimaging. Current Opinion

in Neurobiology 14: 769–776.

Pasternack PA. 1985. Optimal pricing and return

policies for perishable commodities. Marketing

Science 4(2): 166–176.

Pitt LF, Berthon P, Caruana A, Berthon J-P. 2005.

The state of theory premier, advertising journals:

a research note. International Journal of Adver-

tising 24(2): 241–291.

Plassmann H, Ambler T, Sven B, Kenning P. 2007a.

What can advertisers learn from neuroscience?

International Journal of Advertising 26(2):

151–175.

Plassmann H, Kenning P, Ahlert D. 2007b. Why

companies should make their customers happy:

the neural correlates of costumer loyalty.

Advances in Consumer Research 34: 1–5.

Plassmann H, Kenning P, Pieper A, Schwindt W,

Kugel H, DeppeM. 2007c. Neural correlates of ad


liking. Proceedings of the Society for Consumer

Psychology Conference, Las Vegas.

Plassmann H, Kenning P, Schwindt W, Kugel H,

Deppe M. 2005. The role of the medial prefrontal

cortex in risk modulated processing of brand

information. Poster presented on the OHBM-

Annual Meeting 2005, Toronto.

Plassmann H, O’Doherty J, Rangel A. 2007d. Orbi-

tofrontal cortex encodes willingness to pay in

everyday economic transactions. The Journal of

Neuroscience 27(37): 9984–9988.

Plassmann H, O’Doherty J, Shiv B, Rangel A. 2008.

Marketing actions can modulate neural repres-

entations of experienced pleasantness. Proceed-

ings of National Academy of Sciences of the

United State of America 105(3): 1050–1054.

Rao VR. 1984. Pricing research in marketing: the

state of the art. The Journal of Business 57(1):

39–60.

Ridderinkhof KR, Illsperger M, Crone EA, Niewen-

huis S. 2004. The role of the medial frontal cortex

in cognitive control. Science 306: 443–447.

Rossiter JR, Silberstein RB. 2001. Brain-imaging

detection of visual scene encoding in long-term

memory for TV commercials. Journal of Adver-

tising Research 41: 13–21.

Sanfey AG. 2007. Social decision-making: insights

from game theory and neuroscience. Science

318: 598–602.

Sanfey AG, Loewenstein G, McClure SM, Cohen JD.

2006. Neuroeconomics: cross-currents in research

on decision-making. TRENDS in Cognitive

Sciences 10: 108–116.

Sanfey AG, Rilling JK, Aronson JA, Nystrom LE,

Cohen JD. 2003. The neural basis of economic

decision-making in the ultimatum game. Science

300: 1755–1758.

Schaefer M, Berens H, Heinze H-J, Rotte M. 2006.

Neural correlates of culturally familiar brands

of car manufactures. NeuroImage 31: 861–865.

Selnes F. 1993. An examination of the effect of

product performance on brand reputation, satis-

faction and loyalty. European Journal of Market-

ing 27(9): 19–35.

Seymore B, Singer T, Dolan R. 2007. The neurobiol-

ogy of punishment. Naturereviews Neuro-

science 8: 300–311.

Shocker AD, Ben-Akiva M, Boccara B, Nedungadi P.

1991. Consideration set influences on consumer

decision-making and choice: issues, models,


DOI: 10.1002/cb


and suggestions. Marketing Letters 2(3): 181–

197.

Simon H, Dolan RJ. 1998. Price Customization.

Marketing Management 7(3): 11–17.

Singer T, Fehr E. 2005. The neuroeconomics of

mind reading and empathy. The American

Economic Review 95(2): 340–345.

The Lancet. 2004. Neurology 3: 71.

The Texas Heart Institute Website: http://

www.texasheartinstitute.org/HIC/Topics/Meds/

betameds.cfm [4.3.2008].

Tversky AD, Kahneman, D. 1971. Belief in the law

of small numbers. Psychological Bulletin 76(2):

105–110.

Vanhuele M, Dreze X. 2002. Measuring the price

knowledge shoppers bring to the store. Journal

of Marketing 66(4): 72–85.


Volckner F. 2007. The dual role of price: decom-

posing consumers’ reactions to price. Journal of

the Academy of Marketing Science, online pub-

lication date 25 September 2007.

Winer RS. 1986. A reference price model of brand

choice for frequently purchased products. Jour-

nal of Consumer Research 13: 250–256.

Wood JN, Grafman J. 2003. Human prefrontal cor-

tex: processing and representational perspect-

ives. Nature Reviews 4: 139–147.

Yoon C, Gutchess AH, Feinberg F, Polk TA. 2006.

A functional magnetic resonance imaging study

of neural dissociations between brand and per-

son judgments. Journal of Consumer Research

33: 31–40.

Zaltman G. 2000. Consumer researchers: take a hike!.

Journal of Consumer Research 26(4): 423–428.


DOI: 10.1002/cb

a current overview of consumer neurosciencephd.meghan-smith.com/wp-content/uploads/2015/09/co… ·...

Documents