Evolutionary NeuroBusiness

DRAFT ONLY, NOT YET PUBLISHED!!!

Gad Saad1, Angela A. Stanton

2,3, Nick Lee

4, Carl Senior

5, Michael J. Butler

4, Justin R.

Garcia6,7

1Marketing Department, John Molson School of Business, Concordia University,

Montreal, Canada.

2Center for Neuroeconomics Studies, Claremont Graduate University, California, USA.

3Max Planck Institute for Economics, Jena, Germany.

4Marketing Group, Aston Business School, Aston University, Birmingham, UK.

5School of Life & Health Sciences, Aston University, Birmingham, UK.

6Laboratory of Evolutionary Anthropology and Health, Departments of Anthropology

and Biological Sciences, Binghamton University, New York, USA.

7Institute for Evolutionary Studies, Binghamton University, New York, USA.

Introduction

One of the hallmarks of mature and prestigious sciences is their ability to generate

consilient bodies of knowledge. In a recent paper, Garcia and Saad (2008) demonstrated

the disjointed nature of the neuro-approaches in the business sciences (e.g.,

neuroeconomics and decisional neuroscience) (Garcia and Saad, 2008). Furthermore,

they argued that Darwinian theory could serve as the organizing meta-framework of the

nascent discipline of neuromarketing. Along those lines, the current paper pushes this

integrative objective further by placing several neuro-business disciplines under one

common umbrella using an evolutionary lens. Hence, whether exploring

neuroeconomics, neuromarketing, neuroentrepreneurship, or organizational neuroscience,

scholars in each of those disciplines should be cognizant of the evolutionary forces that

have shaped the human mind. Economic agents, consumers, employees, and

entrepreneurs exhibit behaviors, preferences, and emotions that are rooted in their

common and evolved biology. For example, the neuronal activation patterns that are

triggered when interviewing a beautiful candidate, when viewing an ad containing a juicy

hamburger, or when engaging in a risky entrepreneurial gamble, exist in their particular

forms because the human mind is an evolved computational system. Hence, to the extent

that most neuroscientists that have operated at the nexus of the brain sciences and

business have only tackled issues at the proximate level, they stand the very likely risk of

generating at best incomplete accounts of Homo consumericus, Homo corporaticus, and

Homo economicus.

Proximate and Ultimate Explanations

Evolutionary studies generally distinguish between proximate-level and ultimate-

level explanations of behavior. A proximate-level explanation – that which most

neuroscientists solely act – offers insight into what corporeal mechanisms influence a

trait and how the trait physically exists. Whereas ultimate-level explanations attempt to

explain why a particular trait exists in terms of adaptive and selective “evolutionary”

process. This distinction is used to investigate the behavior of a wide array of animals,

including the human animal. We include the human animal not to discount the vast

capabilities of the human species, but to accentuate the fact that humans, like all other

living organisms on earth, are the product of a complex evolved biological scaffolding

that supports our vast contemporary expressions. That is to say as biological organisms,

humans follow the same basic structural rules of other living organisms. Indeed, the most

complete approach to human behavior should consider both physiological components

(proximate mechanisms) and the adaptive or selective forces (ultimate mechanisms)

fundamental to behavior.

An example a biologist may use for understanding the proximate and ultimate

distinction is to consider the peafowl [Pavo]. The male peacock is well known for its

dramatic coloration and extravagant swooping tail-covert. The female peahen tends to be

much more subtle with dull coloration. The proximate-level explanation for this is that

the feathers require care, a particular diet to maintain full color expression, and have a

structural design which reflects light in such a way to produce iridescence. The ultimate-

level explanation is that this large cumbersome presentation is actually critical to the

peacocks courtship display, and a large, colorful, well-maintained plumage leads to

reproductive opportunities by impressing receptive females thus securing a male’s

genetic fitness. One could also address a variety of human behaviors while considering

both proximate and ultimate explanations. Obsessive or addictive gambling can trigger

pleasure circuits in the brain such as dopaminergic reward pathways (proximate-level)

but this may be a byproduct of displaced evolved tendencies for dopaminergically-

relevant motivations in a contemporary environment (ultimate-level). Aggression can be

a behavioral phenotype associated with heightened levels of neurotransmitters or

hormones such as testosterone (proximate-level) but may also be highly beneficial and

adaptive to an individual if properly paired with high-social function skills (ultimate-

level). Creativity and producing art may set off a cascade of responses in the brain

associated with imagery production (proximate-level) but these capabilities may

represent cognitive skills which were important to human survival and mate-choice

(ultimate-level). By considering both explanations, particularly with use of neuroimaging

technologies, we can begin to move beyond the illusion of explanatory depth provided by

atheoretical use of sophisticated technologies. This allows us to infuse research agendas

with a more complete evolutionary framework. A guiding framework may be

particularly important, both epistemologically and organizationally, for budding areas of

investigation. The allure of an evolutionary approach, by nature of evolutionary

principles, is that the approach can cut across a number of disparate fields (humanities,

social sciences, natural sciences, fine arts, business, engineering, medicine, etc) by using

a general framework of adaptation and selection to build complete understandings

(Wilson, 2007). By having a shared evolutionary perspective, researchers can “talk”

across fields and digest discipline-specific topics, as long as the underlying framework is

consistent.

Neuromarketing

Neuromarketing represents the application of neuroscientific technologies,

particularly neuroimaging, to marketing research. Lee et al. (2007) present

neuromarketing as the study of human behavior in the arena of markets and exchange of

goods, but with use of neuroscientific methods to better understand how the brain

operates during these processes. Rather than asking a research participant which product

they find most stimulating, neuromarketing allows the researcher to peer into the nervous

system and detect the body’s physiological response to various stimuli. The field largely

lies at the intersection of consumer behavior and cognitive neuroscience. Both these

fields have rich research streams and it is their neuromarketing intersection which offers

new questions for research investigation. An evolutionary framework has also been

successfully applied to both consumer behavior (Saad, 2007) and cognitive neuroscience

(Platek et al., 2007). In a recent review by Garcia and Saad (2008), an attempt was made

to infuse the entire nascent neuromarketing agenda with an evolutionary approach as

well. Four meta-domains were used to Darwinize the neuromarketing schema: survival,

kin selection, reciprocal altruism, and mating. Although not all neuromarketing studies

necessarily fell into these domains, these general categories were used to guide

discussion of evolutionarily-relevant purposive behaviors (see Garcia and Saad, 2008).

Although many behavioral neuroscience studies are open to both proximate-level

and ultimate-level interpretations, not all neuromarketing studies are by necessity open to

evolutionary interpretation. An example of this is the popular neuromarketing study by

McClure et al. (2004) on soft drink preference. This study suggested that while Coca-

Cola® and Pepsi

® are nearly identical in formula, brand knowledge influenced preference.

In blinded delivery, activation of the ventromedial prefrontal cortex was associated with

behavioral preference, but in a brand-cued experiment when told they were drinking

Coca-Cola® more participants reported taste preference. This corresponded with neural

activation suggesting that brand knowledge from memory and impression – likely a result

of advertisement campaigns – influenced behavioral preference (McClure et al., 2004).

Unlike in many other cases, an evolutionary approach would not necessarily add anything

predictive in guiding a study such as this. However, often consumption of food and

beverage can be related to human survival. If choice of consumption is based in part off

the emulation of those with high-status (e.g. celebrity endorsers), this also relates to

survival. For humans, much like other social organisms, status can determine access to

important resources which impact survivability and subsequent reproduction. Another

study on beverage consumption but with a much different focus, addressed subjects taste

preference for wine based on perceived price (Plassmann et al., 2008). In reality

participants tasted all the same wine, while being led to believe samples were from

varying prices. Participants reported increased fondness and displayed increased neural

activation during tasting of perceived higher priced wines. A heuristic of price

suggesting quality can lead one to believe that a more expensive wine is a better tasting

wine. The notion that consumption of more expensive wines are indicative of status and

prestige coupled with imaginary prices leads to a false impression which influences

choice and brain response. As mentioned earlier, status can be important for both

survival and reproduction. An example of how status can be used as a tool for attracting

a mate is by the display of resources. One study used sports cars, viewed as a proxy for

wealth and dominance and rated more socially desirable than other automobiles, to show

how preferred cultural objects (sports cars) can produce activation of the dopaminergic

reward circuitry including the ventral striatum, orbitofrontal cortex, anterior cingulated,

and occipital regions (Erk et al., 2002). Although status is influential when appealing to

a potential mate, actual mate-choice is a complex process.

It is known to evolutionists that people are attracted to beautiful faces when

defining beauty with regards to culturally relative qualities and general proxies for gene

quality such as facial symmetry and facial smoothness. At the same time, it is known to

marketers that beautiful endorsers are helpful in selling a product. Perhaps it is thus of no

surprise that perception of facial beauty is hard wired into the human brain (Senior,

2003). It is fitting that when choosing a possible dinner date, in addition to decision-

making selection networks, participants had increased activation of the

insula/ventrolateral prefrontal cortex and the paracingulate gyrus (Turk et al., 2004). The

ability to detect various displays by viewing another’s face is not only adaptive for

reasons of mate-choice, but is also used within the domain of kin selection. Kin

selection, the process of investing in kin and ultimately augment one’s own fitness,

fundamentally requires processes for kin detection. Inasmuch males have been found to

use facial resemblance to detect relatedness while showing increased recruitment of gryi

components (Platek et al., 2004). At the same time, human’s show a general predilection

towards juvenile-like neotenous features. However, such an affinity is increased when

adults view familiar infants as compared to unfamiliar infants, with images of familiar

producing medial orbitofrontal cortex activation, associated with preferential reward

(Bartels and Zeki, 2004). There exists a vast array of research possibilities within the

neuromarketing theme, and categorizing purposive consumer behavior into evolutionary

meta-domains provides a useful theoretical model when shaping a complete view of

human behavior and the mind.

Adaptive processes and the business brain: The case for organizational cognitive

neurosciences

The Oxford English Dictionary contains the following entry for the word ‘postal’:

postal

• adjective relating to or carried out by post.

— PHRASES go postal US informal go mad, especially from stress. With reference to

cases in which postal employees have run amok and shot colleagues.

Even a superficial knowledge of current events in recent years may lead to the

disheartening conclusion that the contemporary organization might not be the best place

to spend significant parts of our waking life. For example, one regularly hears of

individuals bringing suits against their former employers for issues such as harassment,

stress, and the physical or mental harm allegedly caused by working there. The rise in

conditions such as chronic fatigue syndrome may also have much to do with

contemporary working life. In worst-case scenarios, former employees even sabotage

their organizations, or – as implied by the OED above – go as far as embarking on

shooting sprees in their former workplaces.

At the same time, organizational researchers in the last 20-30 years have

expended considerable efforts on exploring issues related to the difficulties of

organizational life. Topics have included; burnout, role stress, psychological and physical

strains, among many others (e.g. Cooper, Dewe & O’Driscoll 2001; Lee & Ashforth

1996). Research has also explored in some depth the prevalence of unethical behavior in

the workplace (Tsalikis & Fritzsche 1989), as well as various other negative

organizational behaviors, such as bullying (Randall 1997) and other forms of ‘toxic’

behavior, including those enacted by leaders (e.g. Tepper 2000), whom logic would

suggest should act in the best interests of their employees, not the worst.

However, we appear little closer to understanding just what it is about the

workplace that effects so many in such a negative way. Certainly, we can show that

certain individuals can experience negative effects from working in organizations, and

that certain characteristics of firms may facilitate these effects. However, the major

question is not this, it is why those organizational characteristics have this influence on

individuals, given that it seems logical that organizations – designed as they are by the

very same species which will work in them – should be adapted to our own preferences

and tendencies.

Yet the industrial revolution showed that complex products could most profitably

be made by breaking them up into small specialized, repetitive tasks, to be made by

automatic machines. And as far back as the early 20th

Century, with the emergence of

‘scientific management’ (e.g. Taylor 1911), and the principles of Fordism, the place of

humans in this workflow was also treated as a mechanistic process, to be designed in

such a way as to maximise efficiency and minimise defects. In such a context, one could

be forgiven for wondering whether working in such organizations was what humans were

ideally suited to. Even so, it is undeniable that humans are the only species to have

organized itself into abstract organizations (i.e. not solely related to survival or

socialization), suggesting that perhaps something about this ability does confer a

collective advantage, if not an individual one.

It has not been until recently that scholars have begun to explore the neuroscience

of organizational behavior, in such a way as to begin to illuminate the issues briefly

touched on above. Organizational Cognitive Neuroscience (OCN) is a cross-disciplinary

perspective on organizational research which takes as its focus of study the interaction

between brain systems and cognitive mechanisms in mediating human behaviors in

response to organizational manifestations (Lee & Chamberlain 2007; Butler & Senior

2007). Such an approach looks to have some merit in the study of the effects of

organizational life on human beings, and also on how one can mitigate the more

deleterious effects that appear inherent to such contexts. At the same time, a significant

body of research has developed exploring how evolutionary adaptation has led to inherent

tendencies of human behavior in areas such as consumption (e.g. Saad 2007).

The purpose of the present paper is to build on previous reports (e.g., Nicholson

& White, 2006) and set out the utility of an OCN perspective in exploring the adaptive

processes that may impact on organizational behavior, and ultimately to show how OCN

and evolutionary psychology are inextricably interlinked in the study of organizational

behavior. We begin with a more thorough discussion of the principles of OCN, and how

the approach can illuminate our adaptive organizational behavior. From here the paper

moves on to provide details of the distinct evolutionary processes which are likely to be

of interest within an OCN framework, addressing the question of whether changes at the

neurophysiological level are likely to lead to changes in manifest organizational behavior

or response. Finally, we address examples of how organizational processes improve when

they are designed in a way that is sympathetic to our adaptive mechanisms. In this way,

we hope to highlight the link between OCN and evolutionary psychology, and show how

the two perspectives are in fact symbiotic.

The Organizational Cognitive Neuroscience Perspective

Organizational cognitive neuroscience (OCN) is a perspective brings together the

currently diverse research streams which use neuroscientific theories and methods to

investigate organizational research issues, under a common banner. The benefits of such

a conglomeration are manifold. In particular, it shows more clearly that theoretical

advancement is not dependent on appending advanced measurement tools to existing

theories, as implied by terms such as ’neuromarketing’. Instead, the organizational

cognitive neuroscience approach explicitly recognises that it is the interaction between

cognitive neuroscience and organizational research as distinct fields of research which is

critical – incorporating not just new methods, but also theoretical explanations. In such a

way, the field can lead to advances in both its parent disciplines.

The OCN approach conceptualizes human behaviour within, or in response to,

organizations or their manifestations (e.g. products, advertisements) as a set of layers,

each building upon the last to add more context-specific theory. At the highest and most

abstract level, we are interested in the behavior of individuals and groups at the

intersection between the organization and the human – for example as a worker, a

consumer, or similar. Yet much of this behavior is but a subset of human social behavior

in general. In other words it is a layer of theory added upon social psychology. In turn,

social psychology is founded on theories of cognitive psychology, which also impact

directly on many of our responses to organizational manifestations such as

advertisements and products. At an even more basic level, our cognitive mechanisms are

reliant on lower-level brain systems and structures, which could be termed the neural

level of analysis.

The organizational, social, and neural levels have been the focus of existing OCN

theory (e.g. Lee & Chamberlain 2007). Yet, at perhaps the most fundamental level are the

adaptive forces that have shaped our brain physiology in an evolutionary advantageous

manner. An understanding of the evolutionary adaptations which may underlie our

behavior at the social and ultimately organizational level is essential to full explanation of

why we behave in the way we do, and also critical in understanding the potential negative

(and positive) influence of organizational life on human beings.

To move back to the example of ‘scientific management’ previously alluded to;

an understanding of whether the ability to focus on repetitive small tasks may have

conferred an evolutionary advantage in the past (which therefore would have led to a

predilection for this ability in humans) may then lead to greater understanding of whether

scientific management principles are likely to be beneficial to employees. Importantly,

this is quite apart from the logical principles of the approach, which may indeed suggest

that it may be the most efficient manner with which to produce a complex product with

minimum defects. Indeed, the key social processes that humans have a predilection

towards within organizations are discussed subsequently.

It is not possible to fully understand a given organizationally-relevant behavior by

ignoring the various interweaved layers of theory introduced above. However, in the past,

organizational and business research has tended to focus primarily at the most abstract

levels, working in a ‘top-down’ manner. Conversely, focusing only on the neural level –

without taking into account either the more fundamental evolutionary level, or the more

abstract organizational and social levels – may ignore important contextual factors and

explanations for what is observed. OCN explicitly recognizes the symbiosis between the

layers of theory to develop more rigorous testable hypotheses, and ties this to advances in

research methods that can more accurately test these hypotheses. In the following section

we start to address this question by identifying the neural substrates of social processes

that occur in both within our general society as well as within organizations. The

rationale here is that such evidence would suggest that adaptive pressures are operating at

both the cortical and social level.

Evidence for adaptive processes in the brain?

Given the overlap between social behaviour that is evident within organizations, and that

which occurs in general society, it would seem likely that selective pressures would have

ensured that such behaviours remained in place, since effective social behaviour is a key

adaptation of human beings. Such adaptive processes are likely to ensure transmission of

the organizational culture. However, while such cultural transmission is likely to

underpin the maintenance of successful organizational behaviour, the theoretical model

behind such transmission at the cortical level has not yet been discussed.

The notion of neuronal group selection or ‘Neural Darwinism’ is one possible

mechanism by which a specific neural substrate for a particular social behaviour can

manifest itself. The identification of behaviours that overlap with general society and the

specific organizational context suggests that these specific behaviours have a unique

place in our organisational repertoire. Furthermore, the identification of discrete neural

substrates that are active during these behaviours can be taken to show that they are likely

to have an adaptive value, as selection pressures would have ensured their

neurobiological manifestation. Thus, by adopting an organizational cognitive

neuroscientific approach it is possible to identify behaviours that are not only

parsimonious with our evolutionary past but those that are likely to facilitate

organizational effectiveness. The implications of this theoretical model for understanding

the role that evolutionarily-imperative behaviour holds within organizations are

significant, and will be discussed subsequently.

Darwinian processes in the human brain

‘Neural Darwinism’ (ND) is a name given to a theory that describes how changes can

occur in synaptic networks (Edelman, 1993). The theory involves three main processes

that are analogous to the Darwinian selection pressures. The first of these processes is

described as developmental variation and primarily involves the structural changes in the

synaptic network that arises from the naturally occurring changes that manifest

themselves during early developmental periods (Edelman, 1988). While this is important

for understanding the theoretical nature of ND it is unlikely to have an impact in

understanding organizational behaviour (see e.g, Gillingwater & Gillingwater 2009).

However, it is very likely that the other two strands of this model will have greater utility

in understanding the impact that organizational cognitive neuroscience can have, these

strands are experiential selection and reentrant signalling.

Reentrant signalling is effectively the process by which experiential selection of

the synaptic networks occurs (Edelman, 1992). According to Hebb’s postulate, synaptic

connectivity is strengthened by recurring activity that is driven by a behavioural

response. In the context of organizations these behaviours, as noted below, could consist

of cognitions such as reciprocal cooperation or the recognition of social status. The

pattern of neuronal activity corresponding to these behaviours will cause a synaptic

network called a secondary repertoire to form (Edelman, 1993). These secondary

repertoires would then become the neuronal networks that in turn support organizational

behaviours. It is likely that any social behaviour that doesn’t have utility within

organizational behaviour would not reflex the development of such a secondary

repertoire. At this stage it is important to clarify whether or not any organizational

behaviours have a distinct neural substrate.

The neural substrates of organizational behaviour?

A recent case study identified a range of organizational behaviours that also had a

discrete neurological foundation (Yeats & Yeats, 2007). Social behaviours such as role

taking, morality, empathy, reciprocal cooperation and even perception of social status

were highlighted as important social behaviours during the organizational process and

will be reviewed here in turn.

The ability to mentally place oneself in the position of others is a fundamental

managerial skill (Yeats & Yeats, 2007). The ability to see yourself from another person

viewpoint is also an essential component of effective transformational leadership

behavior (Rooke & Torbert, 2005), The importance of this role is underscored by the fact

that a number of items on the multifactor leadership questionnaire (Bass & Avolio, 1995)

assess this specific ability. This ability also allows managers to access a range of outlooks

on various organizational problems and issues. However, while such a process may seem

to be a singular cognition it actually consists of a range of subordinate mental processes.

Firstly, the ability to remember factual information is necessary to allows

managers to visualise themselves in previous situations. Such declarative recall is now

known to be served by cortical regions within the medial temporal lobes, including the

hippocampus (Squire, 1992). Neuropsychological evidence that supports a role for these

regions in memory processes can be found with the extensive literature on patient ‘HM’

who had his medial temporal lobes, including the hippocampi, removed (see e.g., Corkin,

2002). This literature is so comprehensive that it is known immediately after his

operation, ‘HM’ failed to remember a single new fact for the rest of his life.

Conversely, the ability to place oneself in a future scenario is called prospection

this is distinct from theory of mind processes, which can also involve future cognitive

simulation, but from another person’s viewpoint (Buckner & Carroll, 2006). The

distinction between these two cognitive processes is not, however, supported by a

distinction at the neurophysiological level. Cortical regions within the paracingulate

cortex as well as the anterior aspect of the ventromedial prefrontal cortex are seen to be

primarily activated during both theory of mind and prospection tasks (Gallagher & Frith,

2003; Buckner & Carroll, 2006). Interestingly, there is emerging evidence that self

prospective cognitions are also seen with other species such as crows and apes which

would go some way to supporting the idea that these behaviours have a definite adaptive

value (Emery & Clayton, 2001; 2004).

While it may seem like common sense to assume that such empathic cognitive

skills are a requisite for the effective manager, some may argue that the computation of

moral decisions is not. However, the transformational/transactional leadership model

places moral behaviours firmly within this context (Currie & Lockett, 2007). It is the

transformational leader that identifies with the individual members of the immediate

work group, and ensures that they are supported appropriately to ensure that they reach

their maximum potential (Bass & Avolio, 1993).

Taking this in hand, moral psychology is currently enjoying vigorous empirical

(see e.g., Miller, 2008) with and it is now known that the frontal cortex, more specifically

the ventromedial prefrontal cortex plays an important role in the computation of prosocial

morality (Greene & Haidt, 2002; Moll et al, 2006). Such a cognitive mechanism would

have probably evolved to ensure that that we form social attachments and cooperative

social groups. Clearly the utility of a mechanism that facilities cooperative social

behaviour within work teams is obvious, and is also a diagnostic skill of the effective

transformational manager (Vera & Crossan, 2004).

The efficient exchange of expertise and information throughout the organisational

infrastructure is the hallmark of an effective organisation. Such reciprocal altruism is

another social process that is both fundamental to efficient functioning of work teams

(Koster & Sanders, 2006) and is also predominately human (Ridley, 1996). This

behaviour engenders activity in the same regions of the brain implicated in the sensation

of reward such as the nucleus accumbens, caudate nucleus as well as the ventromedial

prefrontal cortex (Rilling et al, 2002; Rilling, 2008). These same regions are involved in

driving people towards other socially salient motivators such as attractive people, food, or

even drugs of abuse (Senior, 2003; Berridge, 2009; Anselme, 2009) as well as playing a

role in motivating people to cooperate in work groups.

One of the most salient factors that can moderate cooperative behaviour within

the work group is perception of social status (Cummins, 2000). Understanding one’s own

social status when compared with others serves many important functions in the

workplace. Amongst these is as a mechanism to motivate people to ascend the social

ranks, and improve themselves via upward social comparisons (Wheeler, 1966). This is a

complex, yet universal, social behaviour which brain imaging studies in humans reveal is

mediated by the amygdala and ventromedial prefrontal cortex (Zink et al, 2008). It is

interesting to speculate that the perception of status, which is well-known to be present in

other species (see e.g., Mazur, 1973), has been hijacked by human organisational

processes and manifests itself in the mentor/mentee relationship (Bushardt et al, 1991;

Roche, 1979) which in turn may facilitate efficient communication of organisational

culture via a ‘natural pedagogy’ – which is the most evolutionary parsimonious form of

learning (Csibra & Gergely, 2009).

The processes above are all examples of social behaviours that have been adopted

by individuals within organisations. By identifying a neural substrate dedicated to such

behaviours, it is shown that they are likely to have an adaptive role. They are discrete

processes that exist within both organizations and general society.

The study of evolutionary processes and organizations?

While it is still a relatively new approach OCN has already provided many insights into

the social processes that occur within day-to-day organizations. By studying these

processes at the neurophysiological level it is possible to infer that they an adaptive

function. Core behaviours that have been incorporated within our organizational

repertoire that also engender cortical activity provide strong evidence for organizational

specific selection pressures occurring at the neurophysiological levels. The possible

mechanisms by which this would occur are discussed above. However, this is not to say

that placing people in brain scanners would provide evidence of evolutionary

parsimonious behaviours and that business practice should shift alongside these

behaviours. Prior to the neuroimaging protocols extensive work identifying the core

behaviours that underlie those that manifest themselves within the organization must be

carried out.

Introduction

In the following two sections of this paper, we review research findings of the

neuroeconomics and neuroentrepreneurship literature from the perspective of

evolutionary processes. What makes this difficult is that neuroeconomics does not often

evaluate its findings from an evolutionary view, and neuroentrepreneurship is a field in

its introductory stages. Hence in this section, rather than reviewing existing evolutionary

literature, we describe findings of neuroeconomics and what is to become the field of

neuroentrepreneurship, looking at them both from the perspective of human evolutionary

processes and how the human decision making facility influences human decision

making in a business context.

Evolutionary Neuroeconomics

The phrases "human irrationality" or "anomalous decision making" have become

disturbingly common ways of describing human choice outcomes when they don't meet

the predictions of the standard economic theories (Ariely, 2008; Baumeister, 2003;

Becker, 1962; Berridge, 2003; Brafman & Brafman, 2008; C. F. Camerer & Thaler,

1995; Chiang, 2008; Fehr & Tyran, 2005; Koenigs & Tranel, 2007; Sutherland, 2007;

Thaler, 1988). Most economists label decision making irrational when the transactions

made are not as advantageous to the person as they would be if he or she used the

mathematical models of maximization to derive optimal choice outcomes.

Decisions that are irrational imply that the humans who made them decided

irrationally. These terms have become so commonplace that they now appear in light

scientific and lay-language books and magazines nearly as often as in research articles in

refereed journals. One such light scientific review article is "The science of bubbles &

busts" in Scientific American (Stix, 2009), which explores "money illusion" in lay terms

focusing on scientific research results. The concept of money illusion is not new; it was

introduced in the late 1990 by Shafir and colleagues and has been discussed many times

since (Fehr & Tyran, 2005; Shafir, Diamond, & Tversky, 1997; Tyran, 2007), most

recently by (Weber, Rangel, Wibral, & Falk, 2009). Money illusion is the illusionary

increase of money even when its relative value is unchanged or has fallen. For example, a

10% increase in salary during a 15% inflationary period is an illusory increase, since

what one may purchase on the increased sum is actually decreased. The standard

economic theory assumes that people are fully aware of all information available to them

and act consistently in consideration of all of them (this thought is the basis of Milton

Friedman's theories of money). The Scientific American article starts with the statement

that economists "have fought for decades about" the influence of human irrationality,

particularly in the case of money illusion (Stix, 2009).

During money-illusion scenarios, one of the most prominently involved regions

activated in the brain (viewed through fMRI) is the ventromedial prefrontal cortex

(VMPFC), a region behind the bridge of the nose between the eyes, reaching deeply,

nearly to the center of the brain (Weber, et al., 2009). The VMPFC contains some brain

regions that are associated with emotions, such as risk and fear (Bechara, Damasion,

Damasio, & Lee, 1999; Bechara, Tranel, & Damasio, 2000; Clark, et al., 2008), as well as

regions that are associated with judgment and preferences (Paulus & Frank, 2003; Zald,

Mattson, & Pardo, 2002). Given that in the case of illusionary money the deciding brain

regions reach deeply into the emotional regions of the brain, it is not surprising that a

financial decision is not derived strictly with mathematical logic and accuracy. Thus the

question should not be (as it most often is) why humans end up with decisions that differ

from economic prediction (e.g. why the outcome reflects an "irrational" decision making

as per economic prediction), since the answer to that is simple: emotional brain regions

will make emotional decisions. Rather the question we should ask is why the emotional

brain regions are involved with monetary and quantitative nature decisions in the first

place.

The answer to this question is very complex and so far we only understand part of

the truth. We understand that humans use heuristics, or rules of thumb, for quick

decisions (Gigerenzer & Todd, 1999). Heuristics is driven by emotions, which are

context dependent memories of past decisions of some similarity or familiarity. Using

heuristics has, evolutionarily speaking, been an advantageous ability or skill when

"reasoning was not an option when facing down a wooly mammoth" ((Stix, 2009), page

82). Although today we don't face wooly mammoths, we do face other threats and things

we fear that still use the same circuitry in the brain today as it did during the wooly

mammoths' time. For example, we use such heuristics in getting out of near accidents,

avoid being attacked when walking on dark streets, and for soldiers of course, such quick

action is an invaluable life-saving resource--this list is obviously not exhaustive. Thus the

emotion-driven quick-action of heuristics, which once was a needed skill for survival and

provided evolutionary fitness to those who successfully applied it, is still a necessary and

beneficial skill for today's humans. As a result, these pathways in the human brain are as

active today as they were in the times of the wooly mammoth; they still provide

evolutionary fitness to those who apply them skillfully. Because humans are endowed

with emotions as well as mathematical logic - both needed for evolutionary fitness under

different circumstances - their decision-making processes often take more than one

pathways. Pathway one is intuitive (system 1) and pathway two is reasoning (system 2)

(D Kahneman, 2003; Stanovich & West, 2000). Research results show how these two

systems interrelate and remain flexible. For example, communication between the

prefrontal cortex (complex and calculative region of the brain (Barraclough, Conroy, &

Lee, 2004; Bechara, Damasio, Damasio, & Anderson, 1994)) and the amygdala

(emotional region (Adolphs, Tranel, & Buchanan, 2005; Adolphs, Tranel, Damasio, &

Damasio, 1995; Adam K. Anderson, 2007; A. K. Anderson, Christoff, Panitz, De, &

Gabrieli, 2003; Bartels & Zeki, 2000; Beauregard, Levesque, & Bourgouin, 2001;

Bechara, Damasio, Damasio, & Lee, 1999)) appears to be flexible. The brain region that

solves a particular task is age as well as context dependent (Banks, Eddy, Angstadt,

Nathan, & Phan, 2007; Barbas & Zikopoulos, 2007; A Bechara, et al., 1999; Bechara,

Damasio, Tranel, & Anderson, 1998; Braver, Paxton, Locke, & Barch, 2009).

Of the many fields studying human decision making, neuroeconomics is one of

the newest. Neuroeconomics is not a variation of economic thoughts and theories using

neuroscience but it is a new way of thinking about economic decision making. While

some of the tools used are new technologies, such as functional Magnetic Resonance

Imaging (fMRI), transcranial simulation, and other scanning techniques, experiments

using older technologies also perform neuroeconomic research, such as hormonal

manipulation and genetic evaluation. Interestingly, neuroeconomic researchers rarely

discuss the evolutionary processes behind a particular decision making procedure in the

brain and its outcome, although such discussion could help obliterate harmful terms from

use, such as human "irrational" decision-making.

Given that evolution has influenced human decision making processes from the

start, and since it is those processes that neuroeconomists study, it is important to shed

evolutionary light on why the findings of neuroeconomics in laboratory and field

experiments so often conflict with the assumptions of the rational economic models (see

a summary of most economic games used in experiments and the results in (C. Camerer,

2003)). Most evolutionary explanations are comprised of cultural anthropological

explanations that refer to the "social being" nature of humans, limiting the topic to

communication, kin-ties, altruism, and empathy as key factors of importance (see for

example (Ainslie & Haslam, 2002; Andreoni, Kolm, & Ythier, 2008; Boyd, Gintis,

Bowles, & Richerson, 2003; Brosnan & de Waal, 2002; Brown & Brown, 2005; Buck,

2002; Cobo-Reyes, Bra¤as-Garza, Espinosa, Jim‚nez, & Ponti, 2006; Fehr &

Fischbacher, 2003; Fowler, 2005; Gintis, Bowles, Boyd, & Fehr, 2003; Hill, 2002;

Kurzban, DeScioli, & O'Brien, 2007; Nunney, 2005; Ridley, 1996, 1997)). Another

explanation type is the physiological perspective of variations in chemical and genetics

components (de Quervain, 2004; Israel, et al., 2009; Lucas & Wagner, 2005; Millet &

Dewitte, 2006; Moll, et al., 2006; Richard P. Ebstein, et al., 2009; Ryo, Kai, & Akiko,

2006; Tankersley, Stowe, & Huettel, 2007; Zak, Stanton, & Ahmadi, 2007). Most often

the explanations go without connection to anything in decision making let alone to the

evolution of human beings. Some evolutionary explanations do exist but they are not

exhaustively of economic decisions (Adolf Tobeña, 2009; Barclay, 2004; Davis &

McLeod, 2003; Stewart-Williams, 2007; Warneken & Tomasello, 2006) and they

typically do not combine findings of neuroeconomics with explanations through

evolutionary processes. Here we extend neuroeconomic research by providing an

evolutionary background both to this new method as well as its findings.

Within evolutionary processes, natural selection maximizes the "outcome," which

is fitness in terms of survival. As a result, the best choice is always that which provides

the highest level of fitness for survival to the individual in a particular context. The

influence of context over the best choice can be seen in experiments that use economic

games in various cultural environments (elaborated further below). From the perspective

of evolutionary processes, we may look at the various cultures with their individual

environments as evolutionary and decision-making phenotypes, which would naturally

suggest different best choice-outcomes in each culture. Hence what might be an optimal

decision-choice in Beverly Hills, can be an unforgiveable cultural mistake in a small-

scale society of the Rain Forests of Borneo, or at best be an embarrassing choice for a

decision-maker in Paris. Standard economic theories model decision-making based on the

assumption of a "globally" useful model for maximizing behavior. This can be seen from

the mandatory use of the same economic models by every nation that wants to participate

in international trading--it must use the same economic measures as those countries that it

trades with, such as the measure of GDP, regardless of its culture and its traditions. Yet

the influence of cultural variations on decision choices in experiments shows that it is

inappropriate to use the same self-maximizing model across all societies because the

meaning of "self maximizing" varies across cultures. For instance, in some cultures the

consideration of "I" (as self) in economic terms is inappropriate (J. P. Henrich, et al.,

2001; J. P. Henrich, et al., 2005).

Research with Context-Based Decision Making

Standard economists suggest that the process of decision making in the brain is

irrelevant, since the desired information is the outcome, that is the choice itself (Gul,

Pesendorfer, Caplin, & Schotter, 2008; Harrison, 2008). This has been part of numerous

debates (C. Camerer, Loewenstein, & Prelec, 2004, 2005; C. F. Camerer, 2007; Caplin &

Schotter, 2008; Rustichini, 2005; Stanton, 2009a, 2009b; Zweig, 2007). Although this is

not center topic here, a very short explanation of the main argument is necessary for to

the discussion of evolutionary neuroeconomics. Researchers, who label decision-making

irrational based on decision outcomes that don't match the rational theories of economics-

-as in the case of the money illusion introduced at the beginning of this section--, ignore

the brain regions and processes that make those decisions. By overlooking the process,

researchers cannot see why a particular outcome may be rational in the context in which

the problem was presented (context based maximization). They cannot see why an

outcome, which might appear irrational taken out of context, should be the choice that

rational economic models need to learn to predict. Since they lack interest of the process,

they lack understanding of the variability of decision outcomes based on variability of the

processes themselves. Context based process variability provides valuable information

about why the "consistency" and the "irrelevance" axioms of the standard economics

theory often fails to hold in experiments.

Without understanding the context in which a decision was made, the outcome of

that decision is not informative about the rationality (or lack thereof) of the human who

made it. Since the outcome of a decision is not representative of the context in which that

decision was made (one may choose one apple over five oranges because one likes apples

five times more than oranges, or because the apples' sales person is cuter than the one

selling oranges), it cannot be said that the axiomatic representation of the condition was

met at the time of the decision. If we cannot guarantee that the axiomatic requirements

were met at the time of the decision making, we cannot say that the decision outcome is

representative of a rational or an irrational decision outcome (Stanton, 2009a, 2009b).

For example, game theoretic models are based on the assumption that people use

backward induction to make their choice. In backward induction person-one makes her

choice based on inferring what her opponent, person-two, would chose, and she chooses

based on that belief. However, the basis of game theoretic backward induction is the

belief that the opponent would always be rational (choose the two apples instead of one,

ceteris paribus). Live experiments, starting over twenty years ago, using various

economic and financial games, failed to show that the logic of game theory or rational

decision-making stands (Berg, Dickhaut, & McCabe, 1995; Guth, Schmittberger, &

Schwarze, 1982; D. Kahneman & Tversky, 1972, 1979; Smith, Suchanek, & Williams,

1988; Tversky & Kahneman, 1981). One possible reason is that since agents don't

generally act "rationally" as per economic definition, there is no reason for one agent-one

to believe that agent-two will act rationally. Another plausible explanation is that cultural

norms exert their force and agent-one's beliefs are according to the principles of

expectations under the particular norm rather than self-maximization. This suggests that

the backward induction theory requires the understanding and application of context.

The definition of what it means to be "rational" in standard economic theories is

very rigid. It fixes the environment such that in real life it is quite impossible to attain all

that is required. For example, it requires that subjects rank goods and be consistent about

that rank order, which implies that the ranking must be independent of context, which is

impossible (i.e. rank without consideration of slight differences whose influence is

temperamental, such as "ice cold water" might rank high outdoors in summer but low in a

very cold room the same moment in the same summer. A person is not able to separate

the utility of "ice cold water" from the condition in which it might be consumed, breaking

the independence requirements). Humans consistently compare and contrast choices but

not typically without context. A change in context may flip the rank-order, which then

becomes an irrational choice in economic theories. Some economists suggest that having

to choose, for example, ice cold water in hot summer outdoors represents a different

problem from considering the same ice cold water in a cold room of the same moment in

the same hot summer (Harrison, 2008). However, this implies that economic theories do

consider context after all, only assume that each context-variant represents a unique

problem. But this seems to be inconsistent with Gul and Pesendorfer's argument in which

they propose that context is irrelevant in standard economic theories (Gul, et al., 2008).

Economists who ignore brain processes of decision making also ignore that

requirements of the rational model are impossible to meet by any live human. Thus one

may argue that any form of experimental economics, including neuroeconomics, is not

economics, except that it uses a few elementary concepts from economic theories as a

stepping stone in order to evaluate human choice making (Stanton, 2009a, 2009b). To

illustrate with a well established economic experimental example, assume an

experimental subject is sitting in a computer booth trying to decide how much money to

share in the dictator game1 or ultimatum game

2. Over twenty years of experiments, robust

results have shown that humans in every society decide differently from the rational

model and that cultural variations and even the chance to express a reason for the

decisions and/or anger or happiness at the received amount may significantly influence

the decision of how much money people share (C. Camerer, 2003; Cameron, 1999; J.

Henrich, 2001; J. P. Henrich, 2004; J. P. Henrich, et al., 2005; Oosterbeek, Sloop, & Van

De Kuilen, 2004; Phillips, Pillutla, & Kara, 2007; Gad Saad & Gill, 2001; Slonim &

Ross, 1998). Rational models suggest that no sharing of money should take place in the

dictator game but in real life, the majority of people do share (see a summary in (C.

Camerer, 2003)). The term "irrational" or "anomalous" has often been used when

describing the outcomes of the dictator game and other similar economic games. As an

economic game within the frame of standard economics, the dictator game is not useful

since it shows that humans do not follow what the models of the theory predict.

1 In the dictator game, two subjects are randomly matched to divide some money amongst themselves.

Only one of the players (the dictator) receives endowment, usually $10, the other player (receiver) is

endowed with nothing. The player are anonymous and typically the experiment is double-blind in that

neither the players nor the researchers know the identity of the players and the individual decision-

amounts made. The Dictator decides how much money he or she sends to the Receiver, which could be

any amount between $0 and $10. There is no punishment if no money is sent. While the rational models

predict that no money will exchange hands, in reality the majority of people around the world (both in

laboratory and field experiments) do share, often equally (C. Camerer, 2003; Stanton, 2007).

2 The ultimatum game is very similar to the dictator game in its setup: two players randomly and

anonymously paired and only player one receives he initial endowment of say $10. Here however, if not

enough money is provided to the responder, he/she may reject the offer, in which case neither player

takes home any money. If the offer is accepted, both players take as much as agreed to. In experiments

around the world people share more than economic theory suggests, which is the smallest possible

amount of money--here $1. Experimental results show that people reject offers that are less than 30% of

the initial endowment given to player one and that most people (with some cultural variations) share half

(C. Camerer, 2003; Stanton, 2007)

Experimental economics, in general, is also stalled; it can measure how much humans

differ from the standard economic predictions, but that is all. Neuroeconomics, however,

can go further.

Using neuroeconomics, researchers can take advantage of manipulating the

context in which a player makes his decision. Context matters because it initiates a

biological response that influences human decision making. Sometimes the context

changed is the physiology of the player himself, whereas other times it is the external

environment. Examples of physiological changes include hormonal stimulants, which

may include the administering of hormones that normally participate in the decision

making process, or psychological manipulations, such as watching happy or sad faces,

short films of emotional or arousing content, listening to music of various kinds, or even

pain or the pleasure of caress or massage. In addition, neuroeconomists have started to

experiment with participants by evaluating genetic variants in decision making.

Experiments and research findings of some of these are discussed below.

Neuroeconomic Experiments

Status and the opportunity to dominate, however bogus or temporary, influences

preferences and choice outcomes - see for example the famous Stanford experiment with

volunteers randomly selected to be either prison guards or prisoners (Banuazizi &

Movahedi, 1975; Zimbardo, Haney, & Banks, 1973). Testosterone and dominance, status,

risk-taking, and aggression influence each other bidirectionally such that increased

testosterone levels increase aggression, dominance seeking, and risk preferences in men

and also, increased aggression, dominance, status, and risk increase testosterone levels

(Booth, Granger, Mazur, & Kivlingham, 2006; A. Mazur & Booth, 1998; Allen Mazur &

Lamb, 1980; Allan Mazur & Michalek, 1998; G. Saad & Vongas, forthcoming).

Coates and Herbert (2008) experimented on traders at the London Trading floor.

They measured the testosterone and cortisol levels of seventeen traders over a period of

several weeks, taking saliva samples before, during, and after each workdays. They found

that increased testosterone levels influence risk-taking and financial success (J. M. Coates

& Herbert, 2008). A recent research in neuroeconomics shows that men who were

provided an expensive sports car for a short time period and were asked to drive around

increased their testosterone levels whereas men provided an old family sedan for the

same length of time and purpose decreased theirs (G. Saad & Vongas, forthcoming). The

same study also found that in addition to the type of car, the type of roads driven were

also factors in testosterone level variations. Men who were asked to drive the sports car

on busy urban streets had their testosterone levels increase more than men driving the

same sports car on lone highways, whereas men who were asked to drive the old family

sedan in busy urban street had a greater fall in their testosterone levels than men who

drove the old sedan on lonely highways (G. Saad & Vongas, forthcoming). An increase

in status that is not visible if no one is looking (as in lonely highways) and thus the

associated testosterone increase will be less significant than status that is visible (show-

off effect). By contrast, a reduction in status is highly visible in busy urban streets,

pushing the testosterone levels of the unfortunate driver even lower in their shame.

Testosterone variation has an evolutionary function that is associated with sex and partner

selection. Since females are particularly attracted to high-status males at the time when

they are most likely to become pregnant--detailed next--men who are able to increase

their testosterone levels and gain increased status just at the right time, have the highest

evolutionary fitness in terms of reproduction opportunities.

The important factors to note in the above experiment examples is that men's

testosterone levels vary throughout the day. Since testosterone level variations influence

decision-making, these lead to variations in preferences and choice outcomes. Findings

by Van den Bergh and Dewitte (2006) show us the influence of variable testosterone

levels on preferences and economic decision-making and its connection to mating.

Increased testosterone levels in males of higher base-level testosterone influenced their

decision-outcome in the presence of young ladies (Van den Bergh & Dewitte, 2006), by

changing the amount of money they offered to their randomly assigned partners in

economic games. Men who have naturally high (basal) testosterone levels increase their

testosterone levels more and are influenced by the presence of young ladies more than

men who have lower basal testosterone levels (Van den Bergh & Dewitte, 2006). This

may imply, and would be interesting to test in experiment, that (1) some men's

preferences maybe less variable than others dependent on their basal testosterone levels

and (2) their decision outcomes may be more consistent than men with naturally high

basal testosterone levels.

The conclusion about men's testosterone levels variability is that this variation

may influence a decision to be irrational from the perspective of economics when

otherwise, from the perspective of evolutionary fitness, the decision is rational (context

matters). Evolutionary fitness opportunities override the logical time-consuming decision

making that is required by standard economic theories.

Men are not the only ones whose decisions are influenced by hormonal processes

that sometimes make decision outcomes appear irrational but which is otherwise rational

in terms of the evolutionary fitness of the individual. Neuroeconomic researchers found

that the ovulatory cycles drive hormonal changes such that female preferences become

variable based on the various stages of their monthly cycles. Ovulatory changes, for

example, influence women's preferences of clothing; they choose more revealing (higher

risk) dresses at the time of estrus than at other times of their cycles (Durante, Li, &

Haselton, 2008; Grammer, Renninger, & Fischer, 2004). Women's cognitive ability and

economic decision making also changes with their ovulatory cycles; cognitive ability is

reduced close to estrus when estrogen hormones are high but improve when high levels

of testosterone replace estrogen (Farage & Osborn, 2008). The cognitive ability

variations driven by hormonal variations may imply that IQ testing is dubious if

conducted without cyclical considerations and that male-female IQ test results may be

incomparable.

Preference changes driven by ovulatory cycles provides fitness advantage to

women as well as men. In addition to preference changes to durable goods, women also

change their preferences for the type of men they associate with at specific times of the

cycle. Near ovulation, women are more attracted to men with symmetrical and masculine

faces (I.S.; Penton-Voak & Perrett, 2000; I. S. Penton-Voak, et al., 1999; Thornhill &

Gangestad, 1999; Thornhill & Gangestad, 2003), men who display greater social

dominance (Gangestad, Simpson, Cousin, Graver-Apgar, & Christensen, 2004), and men

possessing deeper voices (Puts, 2005). In men these represent signs of higher levels of

testosterone, which, as discussed before, represent higher status. A higher status man may

be more likely to be able to provide bountiful supplies for easy survival to a mother and

child than a lower status man. However, once the period of estrus has past, just in case

she is pregnant, her preferences change to males of lower testosterone, who are less likely

to be aggressive and more likely to be caring fathers (Peters, Simmons, & Rhodes, 2009;

Roney, Hanson, Durante, & Maestripieri, 2006).

In sum, preferences change as a result of hormonal variations for both men and

women and these preference changes manifest themselves in changing consumer tastes.

Economic models that only look at the outcomes of choices without the processes behind

the decision-making of those outcomes, such as hormonal variations, cannot possibly

provide robust decision making forecast. Neuroeconomics, on the other hand, specifically

tests for and often stimulates various environments to understand decision making

processes. For example, in a series of hormonal experiments, neuroeconomists have

shown that by providing additional amounts (increasing the levels) of some of the

hormones used for some types of economic decision making, the outcome of the decision

can be influenced in any some directions. First Zak and colleagues took blood from

participants under various decision making tasks to see the activity of those hormones

that are predominantly involved in the trust game3, such as Oxytocin (Zak, Kurzban, &

3 In the trust game, two players are randomly and anonymously matched with both receiving a $10

endowment. The first player, called the trustor, can make a financial investment in the second player, the

trustee. Any money sent to the trustee triple in value. Thus if the trustor decides to send all of her $10,

Matzner, 2004, 2005). Next researchers exogenously gave various hormones (including

oxytocin) to experimental volunteers for the analysis of the hormonal influence on the

outcomes of the trust game (Kosfeld, Heinrichs, Zak, Fischbacher, & Fehr, 2005),

ultimatum game (Stanton, 2007; Zak, et al., 2007), and the dictator game (Stanton, 2007;

Zak, et al., 2007). Researchers also used various forms of hormonal stimulations, such as

massage (Vera, Jang Woo, Elisabeth, & Paul, 2008) and emotional films (Jorge A.

Barraza & Paul J. Zak, 2009) to see how the various hormonal levels changed in response

to the specific environmental stimuli changes the decision outcomes.

In these experiment, it was demonstrated that oxytocin (OT) increases trust

(Kosfeld, et al., 2005) and generosity (Stanton, 2007; Zak, et al., 2007). Arginine

vasopressin (AVP) was found to reduce generosity and trust but only when the number of

participating subjects in the experiment was small (Stanton, 2007). The finding that the

number of people present may also affect decision-making is not new; "herding" has

often shown to take place (see a great review by (Thaler & Sunstein, 2008)), but its

processes are not well understood. It has been demonstrated that OT is released in the TG

(Zak, et al., 2004, 2005), which influences the participants to trust more and to send more

money to their partners. However, Stanton's findings imply that "group size" might

matter in how much OT is released and when (Stanton, 2007). Stanton showed that the

administered AVP only influenced subjects in small groups (they became stingier) but

the trustee receives $30. At that point the trustor has $0 and the trustee $40. At this time the trustee

chooses how much (if any) to send back from the $40 to the trustor. While economic theories suggests

that 1) the trustor will not trust and won't send a penny to the trustee, and 2) if the trustee received any

money she will keep it all, in real life most turtors send some part to the trustee and most trutees return

just enough to cover the considerations of the trustor (C. Camerer, 2003).

had no affect on subjects in large groups (OT released and interfered with AVP). AVP

and OT are known as inhibitory to each other (Huber, Veinante, & Stoop, 2005; Legros,

2001) and that the V1aR receptor of AVP can be activated by OT (Bales, et al., 2007). Of

course other hormones also participate in the regulation of OT and AVP, such as

serotonin, which appears to regulate the two hormones in opposite direction (Ruscio,

Sweeney, Hazelton, Suppatkul, & Carter, 2007). This, combined with Stanton's group-

effect findings point to the possibility that in small groups OT does not release. From the

perspective of evolution, this makes sense: when faced with many strangers, release of

OT helps with fear and allows social behaviors to surface. However, when the number of

strangers is small, perhaps it is not necessary to release OT in large enough quantities to

block AVP receptors and inhibit AVP's manifestation on decision making. This is an area

of exciting future research, perhaps providing some clue to human herding behavior in

decision-making.

Multilevel Evolutionary Theory of Neuroeconomics

Some evolutionary theories go beyond natural selection of organisms and portray

the evolutionary forces within culture, entrepreneurship, population ecology, and alike

(for a review, see (Breslin, 2008)). In this regard, we may consider neuroeconomics as a

new field that evolved from standard economics. With its technologically more advanced

methods, its better applicability promotes its survival over standard economic theories in

some conditions but not all. As evolutionary theories go, one cannot say that one level of

evolution is "better" than another one. A classic example for why this is true, can be

learned from the lessons taught by the Indonesian Tsunami in 2004. While in many of the

more civilized regions thousands of lives were lost, in some small scale societies, such as

the Moken, only the life of a single child was lost, and in many other "primitive" tribes,

such as the Great Andamanese, Onges, Sentinelese and Shompens, no life was lost to the

tsunami at all (Lagorio, 2005). The "primitive" form of communication in small-scale

societies provided greater survival fitness than did the "civilized" form of

communication. From this example we can see that what is "more civilized" isn't always

better and that what might be advantageous in one type of culture, can be unfavorable in

another. Thus evolutionary fitness is specific to the niche environment in which decisions

have to be made. The importance of this to our discussion here is that while there is an

ongoing debate and disagreement between economists and neuroeconomists, once looked

through the lens of evolutionary purpose, the disagreements lose their meaning. In some

environments standard economic models are sufficient and in other environments

neuroeconomics is more suitable.

Evolutionary Neuroentrepreneurship

In management literature, the talent of the entrepreneur is synonymous with the

ability to handle risks. Although risk has been defined in a variety of ways, from the

perspective of economics, risk is equivalent to a simple gamble, like a casino game—the

odds are known. Where everything is known, there can be no "opportunity" for gains.

Entrepreneurs are known for creating or finding opportunities that others don't see.

Entrepreneurs don't play pure gambles. Rather an entrepreneur is surrounded with risks

that arise from lack of information.

Entrepreneurial research is made expressly difficult because agents have a

tendency to assess projects with bias and framing (D. Kahneman & Tversky, 1979;

Daniel Kahneman & Tversky, 2000). It is often assumed that these biases and framing are

systematic, e.g. remain the same both in size and in direction over time, but recent

research in neuroeconomics found that hormonal fluctuations influence perception and

create frames that are temporary and can vary over a very short period of time.

Neuroeconomics research also showed how hormonal variations influence bias and frame

bidirectionally. For example, Coates and Herbert found that increased levels of

testosterone biases agents toward taking greater risks (J. M. Coates & Herbert, 2008),

while McCaul et al., and Mazur and Lamb (Allen Mazur & Lamb, 1980; McCaul,

Gladue, & Joppa, 1992) showed that excitement, such as a game of chess or a favorite

sport team is winning, increases testosterone levels. Other hormones, such as OT, AVP,

testosterone and others, as discussed earlier, make experimental research that is based on

observation or survey methodology very difficult and inaccurate. One cannot assess

biases and framing through scales and surveys because they themselves create bias and

framing that act in unpredictable ways on individuals. What entrepreneurial research

needs is a new skill set with new tools and methods that neuroeconomics provides.

Neuroentrepreneurship thus is a new field that is evolving from applying neuroeconomic

knowledge and toolsets to entrepreneurial research. This allows researchers to peer into

the brains of entrepreneurs and to apply hormonal stimulus to monitor their influence on

decision making.

A key question neuroentrepreneurial research could answer is whether to be an

entrepreneur is a state (can be learned) or trait (genetic component). We may find that the

talent of the entrepreneur lies in a slightly different form of human brain from the brains

of those who chose not to be entrepreneurs. The hypothesis that entrepreneurial skills are

trait characteristics that one must be born with should not shock us. Should we find that

to be an entrepreneur is to handle risks differently from non-entrepreneurs (as it is

hypothesized by most entrepreneurial research literature (Barbosa, Gerhardt, & Kickul,

2007; Brockhaus Sr., 1980; Folta, 2005; Forlani, 2000; Grichnik, 2008; Kamalanabhan,

Sunder, & Manshor, 2006; Keh, 2002; Legoherel, Callot, Gallopel, & Peters, 2004;

Miner & Raju, 2004; Naldi, Nordqvist, Sjoberg, & Wiklund, 2007; Newman, 2007; Pe'er,

Vertinsky, & King, 2008; Stewart & Roth, 2001; Wu & Knott, 2006)), we should expect

to find that entrepreneurs have different concentrations of those neurons that handle risks

or that risks do not get resolved by the same regions of the brain as they are in the brains

of non-entrepreneurs. We might find that a successful entrepreneur has higher tolerance

for certain hormonal variations, such as cortisol and testosterone, as research with

financial traders found on the London Trading floor (J. M. Coates & Herbert, 2008).

Tolerance levels to risk are genetic (John M. Coates, Gurnell, & Rustichini, 2009).

Researchers also found that impulsivity is influenced by genetic predisposition of the

length of the serotonin transporter gene length (Hariri, 2002; Pattij & Vanderschuren,

2008) as is reaction to unfairness (Crockett, Clark, Tabibnia, Lieberman, & Robbins,

2008). Intertemporal discounting (a research field studying how people respond to the

connection of money and various length of time passing) is affected by hormonal

components whose genetic variations vary with time-tolerance. Research found that the

human brain associates the receiving of money with reward and the length of time one

may delay receiving the reward is associated with various genetic components, such as

dopamine (Boettiger, et al., 2007; McClure, Laibson, Loewenstein, & Cohen, 2004;

Takahashi, 2007).

Neuroentrepreneurship is one of the most exciting fields in business and

economics today; it has the opportunity to deliver solutions to some of the most

challenging issues in entrepreneurial research, providing long awaited breakthrough

answers.