ASSIGNMENT 2: Neuromarketing: Debunking the Myths? Graduate School of Business MARKETING MANAGEMENT 555 ASSIGNMENT 2 Neuromarketing: Debunking the Myths? Actual Count: 3624 (Excluding cover, contents and reference pages) Page 0 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? TABLE OF CONTENTS INTRODUCTION………………………………………………………………………………………………………. 2 Neural Correlates ……………………………………………………………………………………………….. Ethics of Neuromarketing ……………………………………………………………………………………. 8 Free will & Decision-making ………………………………………………………………………………. 9 CONCLUSION ………………………………………………………………………………………………………… 11 REFERENCES:………………………………………………………………………………………………………… 2 Page 1 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? INTRODUCTION Neuromarketing, argues Lee, Broderick, & Chamberlain (2007) is an emerging interdisciplinary field that combines economics, neuroscience and psychology, with Neuromarketing being term just six years ago says Smidts (2002). The goal of neuromarketing suggests Laybourne & Lewis, (2005) and Smidts (2002) is to study how the brain is physiologically affected by marketing strategies and advertising.
Brain activity resulting from viewing an advertisement is monitored and measured using neuroimaging techniques such as functional magnetic resonance imaging (fMRI), as shown in Figure 1, and electroencephalography (EEG) is used in order to evaluate the Figure 1 fMRI Image effectiveness of these strategies (Laybourne & Lewis 2005). McClure et al (2004) says neuromarketing studies usually measure preference between products in terms of brand familiarity or product preference.
As a viewer may hold a cognitive bias in traditional marketing studies, measures such as the product preference for a particular advertisement is sometimes difficult to measure argues Schaefer, Berens, Heinze, & Rotte (2006). Walter, Abler, Ciaramidaro, & Erk, (2005) suggest in neuromarketing studies, brand familiarity and product preference have been correlated with neural activity. Further, consumer protection groups and academics view the field of neuromarketing with caution due to the possible ethical implications of designing advertisements to intentionally cause specific neurological effects (Commercial Alert, 2003).
Laybourne & Lewis (2005) and Smidts (2002) says functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are intrinsic neuromarketing are neuroimaging techniques and comprise the neuroscience aspect of the field. fMRI requires a participant to lay on a bed, with their head located inside the ring of a scanner. Researchers can measure the neural activity throughout the brain in terms of blood flow via oxygen usage by monitoring the participant? s brain with fMRI. As a contrast for this technique researchers can also use EEG equipment as it is fairly portable and light. Using numerous electrodes that are placed on the articipant? s scalp in a Figure 2 Brain Cap Page 2 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? net-like fashion, as shown in Figure 2, EEGs can measure brain activity by assessing electrical activity at the scalp. Using both behavioural responses as well as neural activations Fugate (2007) says researchers are able to use neuroimaging to monitor and conduct marketing studies of the participant? s response. Fugate (2007) explains neuromarketing as being the process that involves asking subjects to perform experimental tasks and control tasks whilst being wired to various electronic devices.
Researchers are able to compare differences in the images produced during the respective tasks as the devices generate instant, colourful images of a working brain. Researchers are then able to see what parts of the brain have responded to the stimuli used (Fugate 2007). Fugate (2007) describes the mechanics behind neuromarketing, as a revolution in the marketing, however, Fugate (2007) has overlooked some critical scientific concepts, specifically the corollary nature to neuromarketing research. Nneuromarketing as a concept suggests Smidts (2002) emerged prior to the word actually being used in 2002, despite suggestions otherwise.
Many studies lacked the spatial resolution to make any useful claims as to the mechanisms behind effective and ineffective advertising techniques due to limitations of neuroimaging techniques conducted in the past few decades (Smidts 2002). An example argues Reeves, Lang, Thorson, and Rothschild (1989), is their claim that in an EEG study television scenes with negative content causes activation of the frontal portion of the right hemisphere while positive messages cause greater left hemisphere activity in the frontal region.
It is important to note that as only four electrodes were used (in addition to the two reference electrodes) cortical arousal was only monitored in terms of frontal versus occipital (Reeves, Lang, Thorson, and Rothschild 1989). Now days, EEG systems are much more precise and often have up to 256 electrodes to monitor brain activity. Many other studies from the same time period by Krugman, (1971); Rothschild, Hyun, Reeves, Thorson, & Goldstein (1988); Rothschild & Hyun (1990); Weinstein, Appel, & Weinstein (1980) also employ „hemisphere? activations as key findings.
Nonetheless, suggest Weinstein et al (1980) it is not the fact that earlier research in „neuromarketing? has been imprecise that is of greatest importance, but rather how quickly the field has evolved over the last few years. Page 3 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? Conditioning & Marketing Two methods are typically employed in neuromarketing research as means of evaluating an individual? s preference between products: product preference and brand familiarity. Product Preference Product preference comparisons involve two known brands or products, which is unlike brand familiarity.
Walter et al. (2005) uses an example of male participants being asked to rate a car? s looks regardless of cost and practical requirements, given the choice between a high performance sports vehicle, a midsized vehicle and a small car. Participants ranked the sports car first, followed by the med-sized car, with the small car ranked last. Walter et al (2005) suggested the sports cars as a primary reinforcer for social dominance, representing independence, power and speed. In this example, the sports car acted as a secondary reward.
Money or cultural goods are secondary rewards that reinforce behaviour only after prior learning, through associations with primary rewards (innate reinforcers including food, water, and sexual stimuli). The three main functions of rewards as outlined by Walter et al (2005) can: (a) induce positive effect, (b) induce learning via positive reinforcement, and (c) induce consuming behaviour for acquiring the reward. Sports cars are preferred, as seen from the study conducted by Walter et al (2005), as they correlate with primary rewards that we innately seek.
They also represents characteristics that we perceive our culture values. Morgan et al (2002), as cited by Walter et al, (2005) say this study was also adapted from a previous study of dominance and social hierarchy involving prime mates. In short, given two identifiable products, preference will be given towards one over the other, which is due primarily to the preferred product having more reinforcing qualities in terms of secondary reinforcers we identify as being relevant at a personally level, as well as to our cultural heritage. (Walter et al 2005) Brand Familiarity Comparisons between amiliar and unfamiliar products are defined as brand familiarity (Campbell and Keller 2003). When a consumer first sees an advertisement for an unfamiliar brand Campbell and Keller (2003) suggest they feel negative uncertainty towards it as it is unfamiliar. However, repetition of an advertising message, argues Campbell and Keller (2003), Page 4 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? at low levels, decreases this uncertainty and increases the effectiveness. One way that products can earn the trust of the consumer and become more familiar, suggest Fugate (2007), is through the use of celebrity endorsements.
Repeated exposures can decrease the effectiveness of the advertisement by annoying the viewer, argues Campbell & Keller (2003), so therefore advertisers must keep in mind not to advertise too much. Consumers can only store knowledge for the familiar, but not the unfamiliar, so repeated exposures for an already familiar product provides more time for the consumer to process the advertisement and their associated experiences from using the product (Fugate 2007). Consumer can become bored and even annoyed more easily for unfamiliar brands as there is less knowledge to process (Fugate 2007).
Therefore, for consumers to recognise a new brand entering into the markets Campbell & Keller (2003) suggest they need to be conservative in their marketing efforts by not overdo it. More identifiable brands, such as Pepsi, are able to advertise more often with less concern of annoying their audience argues Campbell & Keller (2003). Neural Correlates A key principle of neuromarketing, suggest Damasio (1996), is that it is based on finding a neural correlates for buying consumers such as product preference and brand familiarity.
As most studies are only able to monitor neural activity observationally it is important to acknowledge that researchers are only able to seek a correlate and do not induce product preference via neural stimulation (Damasio 1996). Interestingly, peer reviewed evidence has been found linking brand familiarity and product preference with the medial prefrontal cortex, says Damasio (1996). The medial prefrontal cortex (mPFC), suggest Damasio (1996), is a repository of linkages between bioregulatory states and factual knowledge.
In the more specific instance of advertising , this translates into experiences and product information being linked to positive effect, via the mPFC (Damasio 1996). IMAGE 1. mPFC Studies by Kable and Glimcher (2007) point to the medial prefrontal cortex (mPFC) as the locus of interest for neuromarketing studies are quite notable. As outlined in the sports car study earlier Walter et al (2005) advise product preference has been correlated with the activation of Page 5 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? several brain regions in the reward circuitry of the brain, including the mPFC.
Preference has also been correlated with mPFC activity independent of prices argues Knutson, Rick, Wimmer, Prelec, & Loewenstein (2007) and was found to be predictive of subsequent purchasing. Studies by Paulus & Frank (2003) observed when using a visual discrimination task as a control they found coinciding results when a simpler preference judgement study was conducted. McClure et al. (2004) conducted one of the most compelling neuromarketing studies. Researchers conducting a study monitored neural activity when drinking either Coca-Cola or Pepsi (see Figure 3).
Using an fMRI for an experiment McClure et al (2004) had two conditions, (a) brand-cued delivery, and (b) blind taste test. When conducting a blind taste test, brain activity between the Coca-Cola and Pepsi was observed as being nearly identical. However, in the brand-cued condition, significant differences were observed in with neural activity, primarily in the ventromedial prefrontal cortex (McClure et al 2004). Figure 3 Coke Vs Pepsi The significant observation was no neural activation differences were identified when no brand nformation was provided, but when brands were identified, product preference and brand familiarity came into play with Coca-Cola being generally preferred by the participants, which caused significantly more activity in the ventromedial prefrontal cortex region of the brain says McClure et al (2004). An important aspect of the study is that no choices are made by the participant; the soft drink were given to the participants in the fMRI in small quantities; the manipulation was based when the brand was first announced; the finding was based on the activated regions on the brain as measured by the fMRI.
Brand preference and previous conditioning is only demonstrated in brand-cued delivery, and only then is there significant ventromedial prefrontal cortex activation. Koenigs & Tranel (2008) in a follow-up to the McClure et al (2004) study shed more light on the paradox of cola preference. Koenigs and Tranel (2008) explain that subjects tend to prefer Pepsi over Coca-Cola, or have no reliable preference, in a blind-taste test, yet Coca-Cola consistently Page 6 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? outsells Pepsi therefore creating a Pepsi paradox.
When brand information is available, CocaCola is preferred, however, when brand information is not provided, no reliable preferences can be made, which is creating the paradox (Koenigs and Tranel 2008). Cola preference was counterbalanced in the McClure et al (2004) study. Koenigs and Tranel (2008) tested predictions from previous studies by using participants with damaged prefrontal cortex. Koenigs and Tranel (2008) discovered that when patients are presented with brand information, it makes no difference on their preferences.
The conclusion was this finding mirrors effects found in normal individuals participating in blind-taste tests. Gladwell (2005) suggest the strong brand image of Coca-Cola, not taste, is the reason Coca-Cola is preferred over Pepsi. Several studies have connected brand familiarity with mPFC. Schaefer et al (2006) and Schaefer & Rotte (2007) report that when comparing familiar and unfamiliar products with mPFC activity differences in neural activity are detected, which can also be connected to neurolearning literature of novelty detection in rat lesion studies suggest Dias & Honey (2002). Campbell and Keller (2003) suggest relative to behavioural principles, brand familiarity is of extreme importance to advertisers. Fear the unknown pushed consumers away, and in advertising, this fear creates uncertainty for product that results in consumers selecting a known product. For culturally familiar brands relative to unfamiliar brands Schaefer and Rotte (2007) demonstrate this as superior frontal activity and increased mPFC. In short, studies conducted McClure et al (2004), Paulus & Frank (2003), Walter et al (2005) have linked medial prefrontal cortex (mPFC) activation to preference judgements.
Further, Schaefer et al (2006) and Schaefer & Rotte (2007) suggest mPFC can be attributed to the preference for the familiar over the unfamiliar, assuming that the consumer is going to buy a product either way (i. e. a vehicle). Preferences between the available choices in terms of their relative value, suggests Montague (2008), is the next step in the consumer decision making. Consumers can evaluate their choices by weighing the pros and cons of all the available choices (Montague 2008). Research by Sutherland (2004) shows that this process is primarily undertaken by the medial prefrontal cortex, which some have dubbed the „liking centre? f the brain. Several other areas have been implicated as key brain regions relevant to neuromarketing research, suggest Walter et al (2005), other than the medial prefrontal cortex. Some of these Page 7 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? regions include the ventral striatum, amygdala and orbitofrontal cortex, (Walter et al 2005). The ventral striatum says Knutson et al (2007), Walter et al (2005), is the reward center of the brain and has been correlated with self-reported self arousal but only as an indicator of the predicted value of the reward.
This is used as a mechanism for learning as it is thought of as prediction error. The amygdale says Walter et al (2005) has also been correlated with reward intensity in neuromarketing studies, however, is commonly known for its role in processing emotional information. The orbitofrontal cortex (OFC), says Walter et al (2005), consists of mainly two regions: the lateral and medial (and is mainly thought of as a measure of preference. The medial OFC is activated by rewarding stimuli, which includes the medial prefrontal cortex. Lateral OFC activity is correlated with punishing stimuli.
The use of neuroimaging is not limited to neural activation measures says Fugate (2007). For example, in terms of hormonal secretions such as dopamine neuroimaging quantitatively measure this affect (Fugate, 2007). Though the field is expanding rapidly there is much to discover in terms of neural correlates and interest to neuromarketing, suggests Fugate (2007). Ethics of Neuromarketing In order to enhance a commercial gain a major issue for research in neuromarketing is the ethical concerns of neuroimaging. Neuromarketing is nowhere near ready to allow researchers to design a marketing campaign, so addictive that overrides an individual? free will. Founded or unfounded concerns are being allayed regarding this. A consumer protection group in America, known as Consumer Alert, has filed complaints to the US federal government, as well as a US senate committee, and universities, protesting the ethics of neuromarketing. Consumer Alert believe neuromarketing as “find[ing] a buy button inside the skull” (Commercial Alert 2003, 1). Commercial Alert (2003, 3) claims: “Our children are suffering from extraordinary levels of obesity, type 2 diabetes, anorexia, bulimia, and pathological gambling, while millions will eventually die from the marketing of tobacco. According to Consumer Alert (2003), the rise of neuromarketing will bring an end to free will. Lee et al (2007, 202) suggest “Unfortunately, the barely concealed disdain for the idea of „neuromarketing? in the neuroscience literature is clearly based on the opinion that marketing research is a commercial activity purely designed to sell products to the public… ” which many Page 8 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? academics are also hesitant to embrace (Thompson, 2003).
Neuroscience academics tend to focus on more medically relevant questions, though there are many journals dedicated to economics and marketing (Thompson, 2003). As such, some believe that “brain imaging will be used in ways that infringe personal privacy to a totally unacceptable degree” (Editorial, 2004b, 71). An anonymous author in Nature Neuroscience, took a similar stance, saying “Neuromarketing is little more than a new fad exploited by scientists and marketing consultants to blind corporate clients with science. ” (Laybourne & Lewis 2005, 29). Neuromarketing research may help reduce the problems raised by Commercial Alert (2003).
For example, Montague, Hyman, & Cohen (2004) say, by examining the differences between the brain activity of compulsive overpurchasers may help to understand why these compulsive individuals tend to spend outside of their means. In addition, it can provide useful information for how clinicians treat these disorders by looking at the correlations between buying behaviour and clinical disorders. For example, the reward circuitry of the brain and in value-based decisionmaking and the medial prefrontal cortex are quite important says Montague, Hyman, & Cohen (2004).
Two significant ethical issues are present in neuromarketing research argues Murphy, Illes, and Reiner (2008), being: (a) protection of consumer autonomy if neuromarketing reaches critical effectiveness, and (b) protecting vulnerable parties from harm. To mitigate, recommendations for a „code of ethics? to be adopted by the neuromarketing industry are proposed by Murphy et al (2008). Some of the recommendations include (1) accurate representation of scientific methods to businesses and the media, (2) full disclosure of ethical principles used in the study, and (3) protecting research subjects from any coercion.
Free will & Decision-making Murphy et al (2008) suggests that if neuromarketing ever does reach critical effectiveness then the concerns of Commercial Alert (2003) may not be unfounded after all as neuromarketing may infringe on an individual? s free will. The importance of neuromarketing is not restricted to neuroimaging, but also includes computational neuroscience, which is the study of quantifying the component steps that underlie a given behavioural process. Value-based decision-making, for example, can be broken down into five steps suggest Rangel, Camerer, & Montague, (2008), Page 9 of 18
ASSIGNMENT 2: Neuromarketing: Debunking the Myths? which are: (1) identifying the decision problem; (2) weighing the possible choices; (3) making a decision based upon the evaluation of the choices available; (4) after carrying out the decision, consider the resulting consequences; and (5) learn from the decision-making process in order to make better decisions in the future. Montague (2008, 584) says, “Viewed this way, it? s easy to see why „free? choice is an unconstructive way to conceptualize the way humans choose… “.
Vohs & Schooler (2008) suggests that free will and the ability to manipulate perception of it have also recently become apparent. However, it has been many years, suggests Libet, Gleason, Wright, & Pearl (1983) since neuroimaging studies have suggested that neural activity does precede conscious intention, especially if it can be monitored. The decision of whether or not to buy a product is a result of from balancing the gain of obtaining the product, says Knutson et al (2007), offset by the act of actually having to purchase for the product, which is an interplay of corresponding valuations and choices.
Using computational neuroscience, rather than neuroimaging, Walvis (2008), is able to connect neuroscience with common marketing principles. Walvis (2008) suggests three propositions of how the brain organises information and states, “These three propositions function similarly to the basis of an artificial neural network model, implicating the importance of what other „elements? the brand is associated with, the strength of these associations, and the sheer number of associations that are present between the brand and other „elements? in the network” (Walvis, 2008, 182).
These form the basis, say (Walvis, 2008, 186) for the “Three Branding Laws”, based upon how engaging the branding environment is to the consumer, how repetitive and targeted the branding efforts are, and how personally relevant the brand? s marketing strategy is to the consumer. The stronger these pathways and connections are, the more likely a given product will be selected by a consumer. We can again quantify factors involved in choice behaviour, through the use of an artificial neural network, by using these laws says Walvis (2008).
Neuromarketing can greatly improve marketing techniques when using a strong neuroscientific basis for branding, as suggested by Walvis (2008), even without the use of neuroimaging, but rather employing other aspects of neuroscience. Page 10 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? CONCLUSION Fugate (2007) suggests a revolution will soon overcome current market research as a consequence of several key implications of neuromarketing. Researchers are better able to evaluate an advertisement? s effectiveness much more scientifically, when applying neuromarketing techniques, in terms of how the ad affects the viewer? emotional state (i. e. , excitement or humour) as well as the viewer? s attention to the ad. Product appeal, suggested by Walter et al (2005) and the „sports car? study are also identified with respect to the findings with the reward circuitry of the brain. Neuromarketing was shown to be able to connect and quantify the effects of celebrity endorsements, suggested by Fugate (2007) that links the auditory and visual stimuli of the celebrity as they cause hormonal secretions in consumers that identify with the product endorsement, which can lead to a positive emotional response and feelings of trust.
As researched by McClure et al (2004), logo/brand selection and emotional attachment was shown to be significant with consumers, which explained the result that Coca-Cola outperforms Pepsi. Only time will tell how much of an effect these new techniques will have on marketing success as the future implications of neuromarketing show great potential. Neuromarketing, in its current stage, is by no means adequate in determining if an advertisement is effective. Stimulating the medial prefrontal cortex does not mean that an advertisement will be effective as it is only a corollary response.
The medial prefrontal cortex region of the brain is also the subject of other research studies, which include those in fear conditioning as suggested by Baratta, Lucero, Amat, Watkins, & Maier (2008), provocation resulting in eating disorders (Uher et al. , 2004), and startle responses (Day-Wilson, Jones, Southam, Cilia, & Totterdell, 2006). The field shows great promise as being the next step in market research despite the current flaws in neuromarketing research.
Advertisers are likely to be more successful in making a longer lasting impression on the consumer if they took advantage to the many psychology studies that have been previously conducted as they would be better able to direct their efforts towards a target demographic. It is debatable if improved marketing capabilities are good or bad for the consumer; however, with ethics being enforced through legislation I feel we are seeing the myths of neuromarketing being debunked. Page 11 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? REFERENCES: Baratta, V. , Lucero, T. , Amat, J. , Watkins, L. & Maier, S. 2008. Role of the ventral medial prefrontal cortex in mediating behavioral control-induced reduction of later conditioned fear. Learning & Memory, 15(2), 84–87. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Campbell, M. , & Keller, L. 2003. Brand familiarity and ad repetition effects. Journal of Consumer Research, 30, 292–304. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Commercial Alert. 2003. Commercial alert asks Emory University to halt neuromarketing experiments. Commercial Alert News Release. Page 12 of 18
ASSIGNMENT 2: Neuromarketing: Debunking the Myths? http://www. commercialalert. org/PDFs/neuromarketingrel. pdf accessed 26 February, 2011). Damasio, A. 1996. The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philosophical transactions of the Royal Society of London, Series B, Biological sciences, 351, 1413–1420. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Day-Wilson, K. , Jones, D. , Southam, E. , Cilia, J. , & Totterdell, S. 2006. Medial prefrontal cortex volume loss in rats with isolation rearing-induced deficits in prepulse inhibition of acoustic startle.
Neuroscience, 141(3), 1113–1121. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Dias, R. , & Honey, R. C. 2002. Involvement of the rat medial prefrontal cortex in novelty detection. Behavioral Neuroscience, 116(3), 498–503. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Editorial. 2004a. Brain scam? Nature Neuroscience, 7(10), 1015. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Editorial. 2004b. Neuromarketing: beyond branding. The Lancet Neurology, 3, 71. http://proquest. umi. com. dbgw. lis. urtin. edu. au (accessed 26 February, 2011). Fugate, D. L. 2007. Neuromarketing: a layman? s look at neuroscience and its potential application to marketing practice. Journal of Consumer Marketing, 24(7), 385–394. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Gladwell, M. 2005. Blink. New York: Time Warner Book Group. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Kable, J. W. , & Glimcher, P. W. 2007. The neural correlates of subjective value during intertemporal choice. Nature Neuroscience, 10(12), 1625–1633. http://proquest. mi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Page 13 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? Knutson, B. , Rick, S. , Wimmer, G. E. , Prelec, D. , & Loewenstein, G. 2007. Neural predictors of purchases. Neuron, 53, 147–157. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Koenigs, M. , & Tranel, D. 2008. Prefrontal cortex damage abolishes brand-cued changes in cola preference. Social Cognitive & Affective Neuroscience, 3(1), 1–6. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Krugman, H. 1971.
Brain wave measures of media involvement. Journal of Advertising Research, 11, 3–9. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Laybourne, P. , & Lewis, D. 2005. Neuromarketing: the future of consumer research? Admap, 461, 28–30. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Lee, N. , Broderick, A. J. , & Chamberlain, L. 2007. What is „neuromarketing?? A discussion and agenda for future research. International Journal of Psychophysiology, 63, 199–204. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011).
Libet, B. , Gleason, C. , Wright, E. , & Pearl, D. 1983. Time of conscious intention to act in relation to onset of cerebral activity (readiness-potential). the unconscious initiation of a freely voluntary act. Brain, 106(Pt 3), 623–642. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). McClure, S. , Li, J. , Tomlin, D. , Cypert, K. , Montague, L. , & Montague, P. 2004. Neural correlates of behavioral preference for culturally familiar drinks. Neuron, 44, 379– 387. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Montague, R. 2006.
Why choose this book? : How we make decisions. Toronto: Penguin Group. Montague, R. 2008. Free will. Current Biology, 18(4), R584–R585. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Page 14 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? Montague, R. , Hyman, S. , & Cohen, J. 2004. Computational roles for dopamine in behavioural control. Nature, 431, 760–767. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Murphy, E. , Illes, J. , & Reiner, P. 2008. Neuroethics of neuromarketing. Journal of Consumer Behavior, 7, 293–302. ttp://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Paulus, M. , & Frank, L. 2003. Ventromedial prefrontal cortex activation is critical for preference judgments. Neuroreport, 14, 1311–1315. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Rangel, A. , Camerer, C. , & Montague, P. R. 2008. A framework for studying the neurobiology of value-based decision making. Nature Reviews Neuroscience, 9(7), 545–556. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Reeves, B. , Lang, A. , Thorson, E. , & Rothschild, M. 989. Emotional television scenes and hemispheric specialization. Human Communication Research, 15(4), 493–508 http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Rothschild, M. , & Hyun, Y. 1990. Predicting memory for components of TV commercials from EEG. Journal of Consumer Research, 16, 472–478. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Rothschild, M. , Hyun, Y. , Reeves, B. , Thorson, E. , & Goldstein, R. 1988. Hemispherically lateralized EEG as a response to television commercials. Journal of Consumer Research, 15, 185–198. ttp://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Schaefer, M. , & Rotte, M. 2007. Favorite brands as cultural objects modulate reward circuit. Neuroreport, 18, 141–145. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Page 15 of 18 ASSIGNMENT 2: Neuromarketing: Debunking the Myths? Schaefer, M. , Berens, H. , Heinze, H. , & Rotte, M. 2006. Neural correlates of culturally familiar brands of car manufacturers. Neuroimage, 31, 861–865. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Sutherland, M. 004. Synopsis of reported neuromarketing studies. Neuroreport, 28, 15–18. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Thompson, C. 2003. There? s a sucker born in every medial prefrontal cortex. Nature Reviews Neuroscience, 6(3), 11-12. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Uher, R. , Murphy, T. , Brammer, M. , Dalgleish, T. , Phillips, M. , Ng, V. 2004. Medial Prefrontal Cortex Activity Associated With Symptom Provocation in Eating Disorders. American Journal of Psychiatry, 161(7), 1238–1246. http://proquest. mi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Vohs, K. , & Schooler, J. 2008. The value of believing in free will: Encouraging a belief in determinism increases cheating. Psychological Science, 19(6), 49-54. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Walter, H. , Abler, B. , Ciaramidaro, A. , & Erk, S. 2005. Motivating forces of human actions: Neuroimaging reward and social interaction. Brain Research Bulletin, 67, 368–381. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Walvis, T. 2008.
Three laws of branding: Neuroscientific foundations of effective brand building. Journal of Brand Management, 16, 176-194. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Weinstein, S. , Appel, V. , & Weinstein, C. 1980. Brain-activity responses to magazine and television advertising. Journal of Advertising Research, 20(3), 57–63. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Welberg, L. 2007. Shopping centres in the brain. Nature Reviews Neuroscience, 8(2), 84-85. http://proquest. umi. com. dbgw. lis. curtin. edu. au (accessed 26 February, 2011). Page 16 of 18