Title |
Redefining neuromarketing as an integrated science of influence
|
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Published in |
Frontiers in Human Neuroscience, February 2015
|
DOI | 10.3389/fnhum.2014.01073 |
Pubmed ID | |
Authors |
Hans C. Breiter, Martin Block, Anne J. Blood, Bobby Calder, Laura Chamberlain, Nick Lee, Sherri Livengood, Frank J. Mulhern, Kalyan Raman, Don Schultz, Daniel B. Stern, Vijay Viswanathan, Fengqing Zhang |
Abstract |
Multiple transformative forces target marketing, many of which derive from new technologies that allow us to sample thinking in real time (i.e., brain imaging), or to look at large aggregations of decisions (i.e., big data). There has been an inclination to refer to the intersection of these technologies with the general topic of marketing as "neuromarketing". There has not been a serious effort to frame neuromarketing, which is the goal of this paper. Neuromarketing can be compared to neuroeconomics, wherein neuroeconomics is generally focused on how individuals make "choices", and represent distributions of choices. Neuromarketing, in contrast, focuses on how a distribution of choices can be shifted or "influenced", which can occur at multiple "scales" of behavior (e.g., individual, group, or market/society). Given influence can affect choice through many cognitive modalities, and not just that of valuation of choice options, a science of influence also implies a need to develop a model of cognitive function integrating attention, memory, and reward/aversion function. The paper concludes with a brief description of three domains of neuromarketing application for studying influence, and their caveats. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 15 | 23% |
Spain | 3 | 5% |
United Kingdom | 3 | 5% |
France | 2 | 3% |
Turkey | 2 | 3% |
Ireland | 2 | 3% |
Netherlands | 2 | 3% |
Brazil | 1 | 2% |
Switzerland | 1 | 2% |
Other | 6 | 9% |
Unknown | 29 | 44% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 55 | 83% |
Scientists | 8 | 12% |
Science communicators (journalists, bloggers, editors) | 2 | 3% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Switzerland | 1 | <1% |
Ecuador | 1 | <1% |
Brazil | 1 | <1% |
Canada | 1 | <1% |
United States | 1 | <1% |
Unknown | 151 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 24 | 15% |
Student > Ph. D. Student | 18 | 12% |
Student > Bachelor | 14 | 9% |
Professor | 13 | 8% |
Student > Doctoral Student | 13 | 8% |
Other | 32 | 21% |
Unknown | 42 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Business, Management and Accounting | 26 | 17% |
Psychology | 14 | 9% |
Social Sciences | 11 | 7% |
Neuroscience | 10 | 6% |
Computer Science | 9 | 6% |
Other | 37 | 24% |
Unknown | 49 | 31% |