Prior-Knowledge and Opportunity Identification

Prior-knowledge and opportunity identification

Jason Arentz • Frederic Sautet • Virgil Storr

Accepted: 28 May 2012 / Published online: 19 June 2012

� Springer Science+Business Media, LLC. 2012

Abstract An entrepreneur’s prior knowledge and

experience play a critical role in his ability to identify

and exploit entrepreneurial opportunities. Although

entrepreneurship research has acknowledged the role

that prior information and prior knowledge play in

opportunity recognition, few studies have explored

their role in entrepreneurial discovery. We test the role

of a particular prior knowledge in entrepreneurial

discovery within a laboratory setting. Participants

were randomly assigned to one of two treatment

groups. Those in the propitious treatment were given

prior knowledge that oriented them toward the arbi-

trage opportunity within the experiment, and those in

the unpropitious treatment were given prior knowl-

edge that oriented them away. As hypothesized, those

in the propitious treatment were significantly more

likely to discover the arbitrage opportunity.

Keywords Alertness � Discovery �Entrepreneurship � Opportunity � Prior knowledge

JEL Classifications D80 � L26

1 Introduction

In the last decade and a half, entrepreneurship research

has increasingly focused on the origins of entrepre-

neurial opportunities and the reasons why some

individuals recognize entrepreneurial opportunities

and others do not (Venkataraman 1997). Drawing on

the work of Israel Kirzner, entrepreneurship research

from the alertness perspective has made important

contributions regarding both the origins and identifi-

cation of entrepreneurial opportunities.

Research on the origin of opportunities has taken

cues from the work of Hayek on dispersed knowledge,

disequilibria, and false prices (Hayek 1945). The work

on entrepreneurial discovery, on the other hand, has

attempted to unearth the process by which these

disequilibria come to be known in the market. While it

is important to study the ways that entrepreneurs set up

firms and which psychological characteristics are most

conducive to successful entrepreneurship, it is also

important to understand how opportunities come to

be known in the first place. This article focuses on

J. Arentz

Sam M. Walton College of Business, University

of Arkansas, Fayetteville, AR, USA

e-mail: [email protected]

F. Sautet (&)

Department of Economics, Catholic University

of America, Washington, DC, USA


V. Storr

Department of Economics, George Mason University,

Fairfax, VA, USA


123

Small Bus Econ (2013) 41:461–478

DOI 10.1007/s11187-012-9437-9

opportunity identification, and tests Kirzner’s alert-

ness perspective and the role of prior knowledge using

a laboratory experiment.1

Traditionally, three determinants of entrepreneur-

ship have been emphasized in the literature: institu-

tions, social networks, and personal characteristics.

Following the works of Venkataraman (1997) and

Shane and Venkatarman (2000), however, it has

become more and more difficult to define the field in

purely behavioral terms, that is, in terms of who the

entrepreneurs are and what they do. Instead, more

research now regards as crucial understanding how

entrepreneurs come to recognize the existence of

opportunities (Eckhardt and Shane 2003). In other

words, they turn to the fundamental question: ‘‘why

are some entrepreneurial opportunities discovered and

not others?’’ (Shane 2000).

Our research draws on Kirzner’s (1973) postulate

that there is a link between prior knowledge and the

kind of profit opportunities to be discovered. An

entrepreneur’s prior knowledge and experience play a

critical role in his ability to direct his gaze to a specific

field in which he may identify and exploit entrepre-

neurial opportunities. Stated another way, individuals

will tend to be alert to what is in their interest to be

alert to and this is related to (a) the profit (monetary or

otherwise) that they may derive from the discovery

and (b) the content of their prior knowledge, which

may direct them to a certain field. In Kirzner’s view,

entrepreneurial discovery is the result of both a pull

(profit) and a push (alertness); the two work together in

concert. In that sense, Kirzner’s theory of entrepre-

neurial discovery echoes Louis Pasteur’s famous

assertion that ‘‘chance only favors the prepared mind.’’

Kirzner does not see, however, alertness itself as being

a function of prior knowledge. In other words, only the

field in which discovery takes place may be related to

prior knowledge, not alertness itself.

Although entrepreneurship research has acknowl-

edged the role that prior knowledge plays in oppor-

tunity recognition, few studies have explored its role

in entrepreneurial discovery (see Shane 2000 for a

notable exception). It is our goal in this paper to focus

on the role of prior knowledge in entrepreneurial

discovery. Following Shane (2000), we consider prior

knowledge as the sum of all knowledge that an

individual may (consciously or not) possess at a given

moment in time (for convenience we label this KT, i.e.

all the knowledge an individual acquires during the

course of his life). It is, however, difficult, if not

impossible, to test for the influence of all knowledge

on entrepreneurial discovery. We have therefore

constructed a means to identify and explore that role

in a laboratory setting. In this paper, we focus on prior

knowledge as defined as the receipt of information

prior to a specific event (for convenience we label this

Kt, i.e. the knowledge that an individual acquires in

time period t, which for our purposes is during the

experiment).

Following Kirzner’s framework (1973), we model

the entrepreneur as an economic agent who can perceive

a profitable disequilibrium, or arbitrage opportunity.

Participants were randomly assigned to one of two

treatment groups engaged in a contextualized market

simulation with a ‘‘hidden in plain sight’’ opportunity

for arbitrage. Because we are working in a laboratory

context, the design is much simpler than it would be in

the actual world where entrepreneurial opportunities

exist but are not often in plain sight. Since there is no

way to control for all subject knowledge prior to

entering the lab (KT), we instead randomize treatment

assignment so that the distribution of relevant knowl-

edge will be roughly the same for our two treatment

groups, and then provide additional knowledge relevant

to the opportunity in question, but that differs between

the groups. Stated another way, we ensure that Kt differs

slightly but in important respects across treatment

groups. We find that small differences in prior knowl-

edge (specifically, small differences in Kt) can result in

1 Kirzner (2005, p. 76) emphasizes a distinction between

information and knowledge, which states that the former is an

input in a process of learning that results in knowledge

(i.e. subjectively perceived and processed information). By

implication, any information an individual possesses is neces-

sarily subjectively perceived and processed in one way or

another (i.e. there is no such thing as a ‘‘raw datum’’ in the mind

of an individual). While our focus is on how differences in

information affect the kind of opportunity one may discover, we

recognize that ultimately, we are examining how differences in

knowledge matter across individuals for the kind of opportuni-

ties they discover. Indeed, entrepreneurship in Kirzner’s work is

fundamentally a theory of perceived information (i.e. knowl-

edge) that may lead to opportunity recognition through the

process of alertness. In other words, some knowledge may lead

to entrepreneurial discovery, while some other may not. In all

cases, Kirzner focuses on knowledge (i.e. perceived informa-

tion), not simply on ‘‘raw’’ information. Given the links between

information (i.e. ‘‘raw data’’) and knowledge (i.e. subjectively

perceived and processed information) and our goals in this

paper, however, we do not need to emphasize the distinction

between the two.

462 J. Arentz et al.

123

meaningful differences in the likelihood of opportunity

identification.

This article is among the first efforts to examine the

role of prior knowledge in entrepreneurial opportunity

identification using laboratory experiments. It is, thus,

important because it offers an alternate approach to case

studies in examining the role of prior knowledge in

entrepreneurial discovery. Additionally, it adds to the

small but growing literature that seeks to combine

experimental economics and entrepreneurship studies

(see, for instance, Fiet and Patel 2008), and it sheds

some light on our understanding of the role of prior

knowledge in opportunity identification. Indeed, the

experimental setting helps us expand on Kirzner’s view,

showing that, ex-post, alertness could also be seen as a

function of prior knowledge. We show that prior

knowledge (i.e. the perceived and processed informa-

tion that individuals possess) may influence alertness.

Our results show that prior knowledge may influence

not only the kind of opportunities an individual may

discover but also how alert an individual may be to these

kind of opportunities. In our laboratory setting, individ-

uals are not deliberately investing in prior knowledge in

order to better identify entrepreneurial opportunities, as

it is given to them, without them knowing the signif-

icance of the information that they are receiving. Rather

than being a weakness of our design, however, this is a

strength of our approach. In the real world the specific

knowledge relevant for opportunity identification can

only be established a posteriori (after the discovery has

taken place). As such, for Kirzner, opportunity identi-

fication results from genuine discovery and not from

deliberate search. Our experimental design thus offers a

cleaner test of the claim about the importance of prior

knowledge in directing an entrepreneur’s gaze. While

there is a great deal of research on the role of deliberate

search in opportunity discovery, the role of prior

knowledge is underexplored.

Our effort also offers a useful extension to the

handful of existing discussions of the role of prior

knowledge. Prior knowledge tends to be discussed as

if it were a set of blinders limiting entrepreneurial

vision. In other words, it acts as a flashlight aiming in

a particular direction and illuminating some objects

(i.e. opportunities) but not others. We find that prior

knowledge also operates like a pair of glasses, where

an entrepreneur’s vision (i.e. ability to identify

opportunities) is actually improved; prior knowledge

can actually result in a brighter and sharper flashlight.

Our analysis proceeds as follows. First, we discuss

the research that has been done on prior knowledge

and entrepreneurial discovery. Next, we develop and

test our hypothesis regarding the relationship between

prior knowledge and opportunity recognition using a

laboratory experiment. Afterwards, we discuss our

findings and the limits of our approach.

2 Prior knowledge and entrepreneurial discovery

Although entrepreneurship scholars have acknowl-

edged that understanding the origins and recognition

of entrepreneurial opportunities should be at the core of

entrepreneurship studies (Gaglio and Katz 2001), until

recently most research investigated the entrepreneurial

process after the opportunities have been created and

identified (Shane 2000). Rather than focusing on the

discovery of entrepreneurial opportunities, the empha-

sis has largely been on the factors affecting the

exploitation of those opportunities. In this behavioral

understanding of entrepreneurship the fundamental

physical, cultural, and psychological attributes of

people determine who becomes an entrepreneur. As

such, emphasis has been placed on the need for

achievement, the willingness to bear risk, self-efficacy,

internal locus of control, masculinity, and tolerance for

ambiguity (McClelland 1961; Hofstede 1980; Brock-

haus and Horowitz 1986; Chen et al. 1998; Hayton et al.

2002). Research on entrepreneurial discovery from an

alertness perspective, however, has grown in recent

times.2 Kaish and Gilad (1991), for instance, attempted

to test empirically the implications of the Kirznerian

framework of alertness. They found that entrepreneurs

tend to rely more on their own subjective impressions,

gathering information during their on and off hours, and

relying less on the conventional economics of projects.

2.1 Stages of entrepreneurial opportunity

identification

Kirzner (1973, 1979) sees alertness as the essence of

entrepreneurial activity. For Kirzner, entrepreneurship

2 See, for instance, Ardichvili et al. (2003); Baron (2004);

Buenstorf (2007); Dimov (2007a, b); Fiet and Patel (2008);

Gaglio and Katz (2001); Kaish and Gilad (1991); Plummer et al.

(2007); Shane (2000); Shane and Venkatarman (2000); Shep-

herd and DeTienne (2005); Tang et al. (2008).

Prior-knowledge and opportunity identification 463

123

consists primarily of the noticing of a new means-ends

framework that was hitherto not part of the agent’s

optimization set. Alertness, for Kirzner (1979), is

distinct from search and is instead the ability to spot

profit opportunities that have previously been over-

looked. The alertness perspective on entrepreneurship

and the market process assumes that people possess

different knowledge (it is dispersed) and interpret the

world differently (the perception of information is

subjective). These two tenets combined with idiosyn-

cratic life experiences mean that some entrepreneurs

will know about particular market characteristics or

will see the importance of some services to customers

when others will not.3 According to the alertness

perspective, then, discoveries do not primarily depend

on individuals’ inner psychological entrepreneurial

dispositions. Instead, there exist differences in the way

people notice aspects of their environment.

The entrepreneurial discovery process can be

conceived as involving (at least) four steps:

1. Unnoticed entrepreneurial profit opportunities

exist

2. Entrepreneurs notice hitherto unexploited oppor-

tunities

3. Entrepreneurs exploit the noticed opportunity

(which may generate new opportunities)

4. Entrepreneurs develop heuristics and accumulate

knowledge that may help them identify new

opportunities

As stated above, unnoticed entrepreneurial oppor-

tunities exist because we live in a world where

knowledge is dispersed and the future is unknowable.

Entrepreneurial opportunities, thus, exist because

individuals neither have perfect knowledge (as

described in standard microeconomics) nor do they

share the same knowledge (Hayek 1945; Kirzner

1973; Buenstorf 2007; Plummer et al. 2007). In other

words, prior knowledge is heterogeneous across

individuals.

Because knowledge is truly dispersed (i.e. KT

differs across individuals), buyers and sellers make

errors of over-optimism and over-pessimism. Because

market participants are necessarily ignorant, Kirzner

(1999, p. 6) explains they can be led ‘‘(i) over-

optimistically to insist on receiving prices that are ‘too

high’ (to enable them to sell all that they would like to

sell at those prices) [or on paying prices that are ‘too

low’ (to enable them to buy all that they would like to

buy at those prices)]; or (ii) over-pessimistically to

enter into transactions that turn out to be less than

optimal in the light of the true market conditions as

they in fact reveal themselves (e.g., a buyer discovers

that he has paid a price higher than that being charged

elsewhere in the market; a seller discovers that he has

accepted a price lower than that which has been paid

elsewhere in the market).’’ These errors mean that

there are entrepreneurial opportunities to buy low and

sell high thus earning a profit. Alert entrepreneurs may

notice these hitherto unexploited opportunities. Their

ability to make these discoveries depends on their

subjective perceptions (Kirzner 1979), their cognitive

abilities (Baron 2004), their capacity for bisociative

thinking (Ko and Butler 2006), the potential net

gain that results from disequilibrium (Kirzner 1973;

Eckhardt and Shane 2003), the networks they belong

to (Arenius and De Clercq 2005), their openness to

new options (Burmeister and Schade 2007), and

their prior knowledge (see discussion below). Differ-

ences in these attributes lead individuals to see

different opportunities in similar socio-economic

circumstances. Entrepreneurs attempt to exploit the

discovered opportunities. Their ability to be successful

depends on the institutional context and their creative

abilities. Although it is possible to distinguish between

the discovery and exploitation of entrepreneurial

opportunities conceptually, these stages are linked. If

successful, entrepreneurs develop heuristics that may

help them identify new opportunities. Stated another

way, entrepreneurs develop rules of thumb about how

to discover opportunities in the future based on their

experience of what was successful in the past. This

prior knowledge may become important when facing

future situations. It does not guarantee, however, the

discovery of new opportunities.

Although Kirzner (1973, 1979) and others have

written considerably about the discovery process, the

critical role played by prior knowledge remains

underexplored empirically. In particular, there is a

dearth of research that tests how sheer differences in

prior knowledge may be an explanatory element in

opportunity discovery, while abstracting as much as

possible from all other factors.

3 See, for instance, Lavoie (1991), Chamlee-Wright (1997),

Storr (2004, 2012), Tominc and Rebernik (2007) as well as Storr

and Butkevich (2007) for a discussion of how culture affects the

opportunity recognition.


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2.2 The role of prior knowledge

The work of Kirzner (1973) aims originally at solving

a fundamental void in standard microeconomics. In

the traditional approach, within a given means-ends

framework (i.e. the framework which links known

individual ends and the corresponding known and

available means within which individual choice is

being hypothesized), the action of an individual can be

easily determined; it is an optimization problem. This

does not tell us, however, how means-ends frame-

works are selected in the first place. In response,

Kirzner stipulated that entrepreneurship is the element

enabling individuals to discover, or notice, new

means-ends frameworks. Two aspects are fundamen-

tal to this noticing process in Kirzner’s view. First, the

entrepreneur’s interest is to be found in the promise of

pure gain, which pulls entrepreneurial alertness in the

direction of unknown gains from trade. Second, the

entrepreneur’s interest is directly linked to the pos-

session of relevant prior knowledge that may orientate

him towards some kind of opportunities and not others

(Kirzner 1973, 1979; Venkataraman 1997). These two

aspects of the entrepreneurial discovery process are

encapsulated in this quote from Kirzner: ‘‘human

beings tend to notice that which it is in their interest to

notice’’ (1985, p. 28).

In Kirzner’s research, prior knowledge and discov-

ery are related. An individual’s noticing potential is

not a direct function of prior knowledge (i.e. one

cannot invest in prior knowledge in order to positively

affect the likelihood of future discovery), but prior

knowledge may orientate one’s gaze at the world (i.e.

it may affect the kind of opportunities one may notice).

In other words, prior knowledge shapes what one may

be alert to. If one is a surgeon, one may discover

opportunities in the field of surgery, but being a

surgeon per se does not make one more alert to

opportunities. Two surgeons equally trained with

similar work experiences may be alert to opportunities

in surgery, but may not be equally alert to them. As

Venkataraman (1997) writes, a potential entrepre-

neur’s prior knowledge directs his gaze toward certain

opportunities and away from others.4

Despite the role of prior knowledge in the entre-

preneurial discovery process (and because of the

difficulty outlined above), only a few studies have

attempted to demonstrate the importance of that

concept and the role of prior knowledge through

traditional empirical work (Shane 2000; Corbett 2007;

Fiet and Patel 2008; Shepherd and DeTienne 2005).

Prior knowledge generally refers to an individual’s

distinctive knowledge about a particular subject

matter and may be the result of different things such

as work experience, education or unintentional expe-

riential learning (Shepherd and DeTienne 2005).5 The

standard typology can be found in Shane (2000) and

Ardichvili et al. (2003), which present three proposi-

tions regarding knowledge and opportunity recogni-

tion. The likelihood of successful entrepreneurial

opportunity recognition will increase through prior

knowledge of markets, prior knowledge of customer

problems, and prior knowledge of ways to serve

markets. Shane (2000), for instance, explored in his

empirical investigation of a three-dimensional print-

ing process (3DP) the role of prior knowledge and

found that because of differences in prior knowledge,

different individuals recognized different opportuni-

ties based on the same technical innovation. Similarly,

Ardichvili et al. (2003) present a theory of opportunity

identification as a multi-stage process involving

opportunity recognition, development and evaluation.

Accumulating relevant prior knowledge appears to

help entrepreneurs to think in a more intuitive way,

which is possibly related to higher alertness. This is

likely why some entrepreneurship research attempts to

demonstrate that entrepreneurs rely more on heuristics

than others and that entrepreneurs with some prior

knowledge are likely to focus on the relevant infor-

mation in their environment, which can encourage

opportunity identification. As Shepherd and DeTienne

(2005) explain, individuals with prior knowledge have

an increased ability to recognize important connec-

tions between concepts, which increase their ability to

recognize entrepreneurial opportunities. Moreover,

prior knowledge is generally not effective in isolation.

Cognitive properties necessary to value prior knowl-

edge, for instance, are also seen as playing an

4 Another way of stating it is to say that prior knowledge is

about directing one’s gaze not enhancing alertness.

5 Shepherd and DeTienne (2005, p. 93) give the following

example: ‘‘For example, Ed Pauls, the creator of NordicTrack,

epitomizes how prior knowledge allows individuals to identify

opportunities. Ed was a trained mechanical engineer whose

passion revolved around cross-country skiing. His passion was

unfulfilled when inclement weather prevented him from going

skiing. Thus, he invented an indoor cross-country ski machine.’’


123

important role (Shane and Venkatarman 2000).

Opportunities can only be identified if some relevant

prior knowledge is possessed along with the cognitive

properties for understanding its relevance.

In conclusion of this section, it is important to

emphasize that we define prior knowledge as the sum of

all knowledge that an individual may possess (con-

sciously or not) at a given moment in time (Shane 2000).

Of course, one cannot aspire to measure and control for

all prior knowledge that subjects possess. However, we

can overcome this difficulty by using the powerful tool

of randomly assigning subjects to one of the two

treatments. This allows us to specifically test the effect

of the controlled information subjects receive during the

experiment. The reason is that random assignment can

eliminate systematic differences in prior knowledge that

we cannot control. For convenience, we label total prior

knowledge as KT, and the specific knowledge that we

give subjects as Kt. Therefore, by randomizing subject

assignment, we eliminate any systematic differences in

KT, and isolate the treatment effect of Kt.

2.3 Prior knowledge, entrepreneurial discovery

and experimental economics

While there is much work to be done on the role of

prior knowledge in discovery, very few laboratory

experiments have looked at this question in general

and, to our knowledge, none have explored the effect

of prior knowledge on awareness and arbitrage.6

Demmert and Klein (2003), for instance, engaged

students in a quasi-lab experiment, with induced profit

incentives in a physical environment. The task was to

transport as much water as possible from point A to

point B, where end payments scaled with the volume

moved. The entrepreneurial discovery they were

looking for was the realization that the table used in

the experiment could be inverted and used as a larger,

makeshift bucket. In particular, they wondered if this

discovery would occur more often for higher payments

per liter of transported water. Their results were

inconclusive. Kitzmann and Schiereck (2005) repli-

cate the Demmert and Klein (2003) experiment but

likewise find the design difficult to control. Moreover,

a difficulty with these studies is the lack of control or

randomization of the relevant prior knowledge and

experiences of the participants. This is also the case

with the Shepherd and DeTienne (2005) experiment.

Shepherd and DeTienne (2005) ran a quasi-experi-

ment with 78 MBA students who read through a series

of comments from focus groups regarding problems

associated with footwear. The students were offered a

potential financial reward and were asked to find

solutions. The students also received various degrees

of information regarding the problems at hand to

evaluate the impact of prior knowledge on the solutions

found. They were also given superfluous information to

test their ability to recall the relevant information. The

authors found that individuals with higher levels of

relevant prior knowledge both identified more entre-

preneurial opportunities and the opportunities identified

were more innovative. Although their study adds to our

understanding of how prior knowledge affects oppor-

tunity discovery and how financial rewards affects

participants motivation in utilizing even minimal levels

of prior knowledge, it does not control for the specific

prior knowledge under consideration, nor randomize

out other influences, and therefore makes causal

identification problematic. Stated another way, it does

not control for the specific knowledge students acquired

during the experiment (Kt), nor does it eliminate the

possibility that there are systematic differences in KT

that is shaping the results. Thus, additional laboratory

confirmation is desirable.

Fiet and Patel (2008) also focus on discovery and

the role of prior knowledge in a laboratory experiment.

All 31 of their subjects participated in one of two

intensive, eight-week training sequences. Sixteen

were trained to be alert to opportunities in their

environment and the remaining 15 were trained in a

consideration set-based approach to search. Fiet and

Patel (2008) found that the search approach was

substantially more successful in its environment.

There are several reasons to believe, however, that

the authors’ test does not really compare alertness and

search. Discovering that a particular search strategy is

effective in identifying a particular kind of opportu-

nity, for instance, is itself a profit opportunity that

6 We should also note that many, if not most, economic

experiments involve some degree or component of alertness

(entrepreneurship). Unfortunately, since the entrepreneurial

process is so rarely studied explicitly, we can infer little by

way of causal relationships in those experiments. For example,

some of the discovery of specialization and exchange found in

Kimbrough et al. (2008) must undoubtedly be entrepreneurial.

Additionally, there have been several economic experiments

endeavoring to tease out the characteristics of successful

entrepreneurs (see, for instance, Burmeister and Schade 2007).


123

potential entrepreneurs might be alert to. The fact that

those participants who were given that knowledge

outperformed those who were not given that knowl-

edge is not necessarily a critique of alertness vis-a-vis

search. Moreover, participants were aware that they

were expected to identify new opportunities, i.e. the

search for new ventures is explicit. Consequently, the

experiment could be thought of as one in which the

entrepreneurial discovery has already occurred, so that

the task at hand is optimization.

Although these experimental studies have advanced

our knowledge of entrepreneurship and specifically the

role of prior knowledge in opportunity identification,

there still remain some key ways that these studies can

be extended or improved upon. The next section

outlines the experimental approach that we pursued.

2.4 Extending and exploring the role of prior

knowledge

As argued above, the discussion of the role of prior

knowledge in Kirzner’s work, as well as in that of

others such as Shane (2000), traditionally links prior

knowledge with the kind of opportunities one may

discover, not with the likelihood of discovery. While

we agree that one cannot deliberately engage in

learning in order to increase one’s own capacity to

discover opportunities, it may still be the case that

sheer differences in prior knowledge may be an

explanatory element in alertness and thus in opportu-

nity identification. We believe that a laboratory

experiment may be able to show that alertness can

also be seen, a posteriori, as a function of prior

knowledge. In other words, differences in prior

knowledge may explain differences in opportunity

identification. One’s noticing potential (i.e. alertness)

would thus be itself a function of prior knowledge,

even though no such link between specific prior

knowledge and the likelihood of identifying some

specific opportunity can ever be established a priori.

Thus, our hypothesis can be stated as follows:

H: The chance of discovering an opportunity for

profit is positively correlated with relevant prior

knowledge pointing towards the existence of such an

opportunity. In particular, members of the propitious

treatment group in our experiment are more likely to

discover the opportunity than are members of the

unpropitious treatment group.

3 Methodology

We ran a controlled, computerized, laboratory exper-

iment, using 64 paid student subjects from George

Mason University, following standard experimental

economics procedures. Each student was the sole

human participant in a virtual market with two goods

(one of which they produced), and three groups of

potential consumers (themselves and two other

groups). The primary unit of measurement was the

simple, binary, discovery or absence of discovery that

arbitrage was a profitable possibility.

Participants were randomly assigned to either the

propitious or the unpropitious treatment group. The

randomization eliminated systematic differences in

prior knowledge between subjects assigned to each

group, particularly with regards to the levels of

relevant prior knowledge (KT) they possessed before

entering the lab, their capacity for bisociative modes

of thinking, and other traits that might increase their

alertness to the opportunity in the experiment. Our

purpose in selecting this design was to ensure that any

systematic output differences between the two treat-

ment groups had to do with the differences in the

treatment they received and not any other factors

or characteristics that would affect entrepreneurial

alertness. While assessing and measuring such char-

acteristics may further our understanding, such mea-

surements are not the in the purview of this work.

The treatment occurs as soon as participants begin

the experiment. Our purpose was to test whether an

entrepreneur’s ability to identify profit opportunities

was influenced by her prior knowledge acquired

during the experiment (Kt). We emulated such

knowledge with a one-paragraph story that sets the

context for the experiment. The story places subjects

in the role of a manufacturer, Mr. Green, from a small

village who purchases fruit he has never seen before,

but enjoys, on his first visit to a distant town. Those in

the propitious treatment read a version of the story that

suggests, but does not explicitly state, an opportunity

for arbitrage within the experiment:

Mr. Green grew up in a small village called

Green Village, where he runs a small factory.

Mr. Green has always been very similar to his

fellow villagers. They usually like the same

drinks, food, clothing and art that Mr. Green

likes. On his 25th birthday, Mr. Green travels to


123

Brown Town, a small country town 150 miles

away. He spends the day shopping in the local

market and sampling the local food and drink.

Most of what he finds he is familiar with from his

home village, but that night he buys an exotic

fruit that he’s never had before, and he abso-

lutely loves it. Mr. Green thinks to himself that

the other villagers would probably like this fruit.

Mr. Green’s tastes are said to be very similar to his

fellow villagers, even suggesting that other villagers

might enjoy the fruit if they could try it.

For the unpropitious treatment, however, the story

framed participants (i.e. Mr. Green) as having very

different tastes from the other villagers, so that the

implication of an arbitrage opportunity is absent:

Mr. Green grew up in a small village called

Green Village, where he runs a small factory.

Mr. Green has always been a little different from

his fellow villagers. They usually do not like

the same drinks, food, clothing and art that

Mr. Green likes. On his 25th birthday, Mr. Green

travels to Brown Town, a small country town

150 miles away. He spends the day shopping in

the local market and sampling the local food and

drink. Most of what he finds he is familiar with

from his home village, but that night he buys an

exotic fruit that he’s never had before, and he

absolutely loves it.

Kt differed in small but meaningful ways between

the treatments. Notice there are two key differences

between the stories. Stated another way, subjects in the

propitious treatment are given two bits of prior

knowledge relevant to the identification of the entre-

preneurial opportunity that exists within our virtual

market. First, they are told that Mr. Green’s tastes are

similar to his fellow villagers, suggesting that if Mr.

Green discovered something he enjoyed, his fellow

villagers would also be interested in it. Subjects are

told explicitly that they can use Mr. Green’s tastes as a

barometer for the tastes of his fellow villagers.

Second, they are told that Mr. Green both loved the

exotic fruit that he has purchased and believes that his

fellow villagers would enjoy it as well. Although they

are not told explicitly that there is an opportunity for

Mr. Green to purchase fruit in Brown Town and to sell

that fruit in Green Village, the subjects in the

propitious treatment group are given relevant prior

knowledge before engaging in activities in our virtual

market that should make them more alert to that

opportunity.

So as to guard against convoluting session effects

and possible experimenter demand effects, all sessions

contained participants in both treatments, and all

instructions and stories were read silently and pri-

vately. Once participants were seated, no instructions

were read out loud. Questions raised by participants

were answered quietly and privately. Instructions

began with the story, and then advanced to interactive

practice for the market processes of production and

consumption. Comprehension was tested with a short

quiz at the end of the instructions. Wrong answers sent

participants to the beginning of the instructions to try

again. When all answers were submitted correctly, the

market phase began.

The story treatment was the only difference

between the two groups. All other aspects of play

and payoff were identical. After reading the treatment

stories, all participants experience identical instruc-

tions and game play. The virtual market appeared on

the computer screen as a three by three grid, with

image icons representing the participant’s factory,

boxes produced by the factory, the village, the distant

town, fruit purchased from the town, the participant

(as Mr. Green), and the participant’s wealth and

happiness. In the instructions, participants were

trained to drag and drop icons to perform actions,

much as one might drop a file into a folder. Dragable

icons included money, boxes, and fruit, which could

be dropped on the village, the town, or the player icon.

They were trained in the instructions on ‘‘a few of the

possible actions,’’ which were dropping money on the

factory to produce boxes, dropping boxes on the

village to earn money, dropping money in the town to

buy fruit, and dropping fruit on the character icon to

consume it for happiness points. The drag and drop

structure allowed for unrestricted action combinations

without overtly suggesting arbitrage.

The salient portion of the experiment was the sum

of money and happiness earned, which was paid out

individually and privately to the participants in US

dollars when the experiment ended.7 Participants are

7 Since the only action of interest to us is discovery, rather than

profit maximization or total welfare, details of the cost functions

and diminishing marginal valuations employed are not relevant,

and have therefore been omitted for the sake of space, focus, and


123

explicitly trained to perform production, consumption

and retail actions but are not shown explicitly that they

are able to buy fruit in the town and sell it in the

village. We claim that an entrepreneurial discovery

has occurred if the participant thinks to buy fruit from

the town and then sell it in the village, rather than

consume it directly.

3.1 Procedure

All experiment sessions occurred at the Interdisciplin-

ary Center for Economic Science (ICES) at George

Mason University. Participants were randomly

recruited from the George Mason student body, and

received $7 for arriving on time, in addition to

earnings from the experiment. Participants spent about

40 min to an hour in the laboratory.

Upon arrival, participants checked in, signed

waivers and drew a random number assigning them

to a computer station and treatment. Therefore both

treatments ran in all sessions, with equal numbers

(within one for odd turnouts) of each. Once logged in,

participants read the instructions and the story corre-

sponding to their treatment. Instructions included

practice dragging and dropping icons to perform

sample actions. Participants then took a short quiz,

which either returned them to the instructions or

allowed them to begin. Once the market loaded,

instructions were no longer available.

The experiment was not timed but ended if a

participant ran out of experimental money or after 90

actions. They then completed a brief questionnaire,

signed for and received their payments privately and

individually, and exited the lab.

3.2 Further remarks on our hypothesis

The discussion of the role of prior knowledge above

suggests that sheer differences in prior knowledge may

be an explanatory element in alertness and thus

opportunity identification. We hypothesized that the

fraction of participants who discovered the arbitrage

opportunity would be higher in the propitious

treatment than in the unpropitious treatment. More

individuals in the propitious treatment group, we

hypothesize, will think to buy fruit from the town and

then sell it in the village, rather than consume it

directly. With our design, we hope to isolate the prior

knowledge treatment effect on entrepreneurial alert-

ness. Although many other factors play important

roles in the entrepreneurial process of discovery, we

assert that the prior knowledge induced by the stories

accounts for any difference in discovery rates between

the treatment groups. If true, it would show that people

tend to discover what their prior knowledge orients

them towards.

Admittedly, any difference among individuals

within a group may be due to other factors such as

cognition, knowledge asymmetries, and experiential

learning (Shane 2000; Corbett 2007). Our design does

not screen for participants who came to the experiment

with prior knowledge or attitudes that might have

made them more or less alert to the entrepreneurial

opportunity but rather eliminates systematic effects

from such factors by randomizing treatment assign-

ments.8 We would expect that different subgroups of

participants might discover the arbitrage opportunity

at different rates. While this was not the focus of the

experiment, we do check for, and find, gender effects

on discovery rates, though we have no a priori reason

to believe that males or females are more likely to

discover the arbitrage opportunity.

4 Results

The data do support our hypothesis. Significantly more

people exhibited entrepreneurial discovery in the

propitious than in the unpropitious treatment. We

had 64 participants in total, evenly split between the

treatment groups. Of the 32 in the unpropitious

treatment, six discovered the arbitrage opportunity

(19 %). Of the 32 in the propitious treatment, twelve

discovered the arbitrage opportunity (38 %). A simple

one-sided t test reveals a statistical significance of

p \ 0.05 that sampling error is unlikely to account for

Footnote 7 continued

simplicity. Selling fruit in the village did produce the highest

profit, but that could not be known until after the discovery had

occurred. Similarly, relative earnings depended on how early

discovery occurred, if at all. Complete cost and payment sche-

dule details are available by request.

8 Although we did not screen for differences in KT, our design

eliminates systematic effects resulting from differences in KT by

randomizing treatment assignments.


123

higher discovery rates in the propitious treatment.9 See

Table 1 for a summary.

Furthermore, several questionnaire responses point

towards the importance of prior knowledge in the

identification of entrepreneurial opportunities.10 Con-

sider, for instance, the response from one woman in

the propitious treatment. ‘‘I remembered from the

story that Mr. Green thought that the townspeople may

like the fruit,’’ she writes, ‘‘so I tried selling it to them

and saw that there was a bigger profit.’’ The role of

prior knowledge in alertness here is clear. She did not

take the presented framework as fixed and given,

and was furthermore able to connect the seemingly

unrelated story experience with her task at hand.

Another woman, also from the propitious treatment,

makes a similar connection, fueled by a frustration that

the task she had learned in the instructions (producing

and selling boxes) was not especially lucrative. She

writes, ‘‘After realizing that the towns people only

gave me so much money for the boxes and while

knowing the towns people liked the same type of

things as Mr. Green did I figured giving the towns

people fruit would both make Mr. Green happy and get

him more money.’’ Note also that their comments

illustrate their alertness to the gains from trade and its

relationship to their prior knowledge. In both cases,

the realization was close to the surface.

In contrast, one gentleman from the unpropitious

treatment tried selling fruit back to the village in spite

of the expectation that they would not like it. ‘‘Just

because Mr. Brown did not like a lot of the same things

as the villagers,’’ he writes, ‘‘does not mean that the

villagers will not like the exotic fruit. After all, it is an

exotic fruit that Mr. Brown just discovered. Selling the

fruit to the villagers created a new craze, similar to

Dippin Dots Ice Cream of the late 90s and Slider

Burgers from the last 5 years. Since the village was

150 miles away from Brown Town, it created an exotic

import for the town and a unique competitive advan-

tage for Mr. Brown.’’ This subject left the room

ecstatic, and wanted to know how many other people

had made the same discovery. Note how his descrip-

tion demonstrates a larger leap of alertness. Even

though this participant misnames Mr. Green, calling

him Mr. Brown, he was able to see through to the

opportunity.

Additionally, we were surprised to find that the

treatment effect primarily occurred among women. As

seen in Table 2, two out of the ten (2/10) women in the

unpropitious treatment discovered the arbitrage

(20 %), while eight out of the 14 women in the

propitious treatment did (57 %). By contrast, four out

of the 22 men in the unpropitious treatment discovered

the opportunity (18 %), but only four out of the 18

men in the propitious treatment discovered it (22 %).

While the discovery rates for the two genders in the

unpropitious treatment are statistically indistinguish-

able, in the propitious treatment group, women

discover dramatically more often. We wish to remain

cautious about overstating this finding, but it suggests

that women might be more responsive to the prior-

knowledge difference, at least as experienced in this

environment. More precisely, we had no a priori

reason to expect a difference, but it would seem some

factor that correlates with gender also correlates with

sensitivity to our treatment design. Further research is

needed to determine the underlying cause of this

observation.11

Table 1 Treatment effect

Outcome Propitious Unpropitious Total

Discovery 12** 6 18

No discovery 20 26 46

Total 32 32 64

** indicates significance levels of p \ 0.05

9 We use a t test here simply for its familiarity and robustness to

non-normal distributions. For a non-parametric alternative, the

Wilcoxen Mann–Whitney yields p = 0.049. Table 2 relies on

the WMW because the sample sizes there are not large enough

to justify the t test. All statistics were generated by STATA 10;

code and data are available on request.10 We do not provide formal content analysis here. Nor can we

correct for the unfortunate fact that surveys done after the

experiment are necessarily soliciting retrospection (Gaglio and

Katz 2001). We cannot determine whether participants’ ex post

discussions of why they behaved as they did actually map to ex

ante motivation for their actions or if they are merely ex post

rationalizations. As a matter of future research, we would like to

have in-process descriptions of activity, though we expect such

invasive observation will have strong effects on the observed.

The full list of survey responses is available upon request.

11 Gender, being binary for our sample, is the only category

variable with enough observations and variance for us to

comment on. We could have added additional controls on group

composition differences, but as we discussed earlier, we are not

investigating a type identification algorithm, nor do we have any


123

Importantly, our findings—that only a portion (albeit

a greater portion in the treatment case) of subjects

discovered the opportunity—enrich the alertness per-

spective concerning opportunity discovery. Every sub-

ject perceives the same reality differently. Rather than an

opportunity being equally known to all, different people

will have different information and interpretations of the

world. Our results show that people who share some

(even a minimal amount of) common prior knowledge

may be more alert to a given profit opportunity than

others. The psychological profile or the disposition of the

entrepreneur does not seem to matter as much as her

tendency to be alert to what is in her interest to be alert to.

Ex-post, alertness can be seen as a function of prior

knowledge. Again, in the laboratory experiment setting,

individuals are not deliberately investing in prior

knowledge, as it is given to them, without them knowing

the significance of the information that they are receiv-

ing. Because our results show that prior knowledge (in

the sense of Kt) has an effect on the discovery rate, it can

be surmised that prior knowledge (in the sense of KT)

influences not only the kind of opportunities an individ-

ual may discover but also how alert an individual can be

to these kind of opportunities.12

These results give support to Shane’s (2000) findings

that idiosyncratic prior knowledge rather than unique

abilities make entrepreneurs better able to identify

opportunities. It also supports Shepherd and DeTienne

(2005) findings that individuals with higher levels of

relevant prior knowledge (i.e. members of the treatment

group) identified more entrepreneurial opportunities.

While our study does not rule out completely the

importance of special attributes, it does suggest that

prior knowledge has a strong influence on the discovery

process. Our results point to a direction of research that

emphasizes the cognitive approach to entrepreneurship

studies and the role of prior knowledge.

5 Limitations

Subjects were asked to participate in an environment

with a series of explicit rules. Those who are strictly

limited by the articulated rules may not discover that

there is more that can be done in the environment than is

addressed by the given rules. While the experiment is

about prior knowledge, it also tests indirectly any

bisociative mode of thinking through which individuals

may combine already known ideas together to get an

emergent concept (Ward 2004). Indeed, alertness may

imply better capacity to put together unrelated ideas (Ko

and Butler 2006). In this study we provide some

background knowledge that may or may not create a

new combination in the mind of the subject, but we do

not specifically focus on bisociative modes of thinking.

Additionally, there is a fine line between prior

knowledge that may be relevant to the opportunity

presented and prior knowledge that gives away the

existence of that opportunity. Our goal was to test the

former, which meant that the way the two treatment

stories were presented was crucial. The effort was to

change the level of relevant prior knowledge people

possess without making them explicitly aware of the

existence of an opportunity.13

Table 2 Gender

breakdown

** indicates significance

levels of p \ 0.05

Discovery by gender Propitious Unpropitious Difference (1-tail WMW)

Discovery female 8/14 = 57 % 2/10 = 20 % p = 0.037**

Discovery male 4/18 = 22 % 4/22 = 18 % p = 0.38

Difference (2-tail WMW) p = 0.046** p = 0.90

Footnote 11 continued

theoretical impetus for what sorts of secondary observations

might matter. With hundreds of additional data points, we might

get away with some data mining, but we feel such an enterprise

is better suited for a different type of study.12 The inference may seem unwarranted, but since Kt is a part of

KT, all else equal, we believe that it is logically correct to

surmise that what is true for Kt is also true for KT.

13 As one reviewer pointed out, neither treatment would be

considered a control group in the classic sense, in that both

groups are given some sort of prior knowledge. Our experiment

is therefore more analogous to a test of health effects from

various levels of dietary salt intake. In such an experiment, one

might be concerned that forbidding one group from having any

salt at all over a prolonged period would likely have adverse

effects. Therefore, the difference in salt intake between groups

would be the variable of interest. Similarly, after careful

consideration, we decided that reading no story at all would

confound our results, since both the contextualizing aspect of a

story and the prior knowledge itself would be at play. We opted

instead for equivalent depths of story emersion, but with

opposite vectors of relevant prior knowledge. It’s the difference

that matters, though of course the difference is impossible to

measure directly.


123

From the alertness perspective, many different

types of prior knowledge may influence discovery. We

use the laboratory advantage to administer one

particular difference in prior knowledge between two

treatment groups with regards to the existence of

potential customers. This does not mean that it

encompasses all the prior knowledge that will make

people more alert to the opportunity that is presented

to them. As Shane (2000) shows in his study on the

discoveries of application of the 3D process, each

discovery is related to its own market. Of the three

major dimensions of prior knowledge that Shane

(2000, p. 452) listed, we have mostly tested the

hypothesis that prior knowledge of ways to serve

markets may lead to opportunity discovery as well as

that of prior knowledge of customer problems.14

Additionally, subjects are in the particular context

of the laboratory, which may influence both the way

they intuit and interpret the information that is given to

them (Dimov 2007b; Shane 2000). Some individuals

may not display the alertness in this context that they

might in another. The design of our experiment,

however, brings one particular dimension to bear: the

role of prior knowledge. Similarly, as is the case for all

laboratory and field experiments, and all econometric

analysis, the question of generalizability remains

unresolved. One can easily imagine real world markets

where other factors such as risk or liquidity constraints

might crush out the effect of a similar prior knowl-

edge. However, the results of this experiment do

contribute to the growing body of evidence and theory

that prior knowledge is an important component of

entrepreneurial discovery.

While it was not our aim to test the importance of

financial rewards, it is important to state again that the

experiment involves the existence of financial

rewards. Financial rewards are simply an aspect,

albeit an important one, of the experiment. Partici-

pants were paid what they earned in the experiment in

US dollars, and the hidden arbitrage opportunity was

the most lucrative. It is because the opportunity is

beneficial to the subject that it is an entrepreneurial

opportunity (Kirzner 1973, 1979). The discovery of

the opportunity is a discovery of a profitable entre-

preneurial opportunity. While it is clear that the

magnitude of monetary profit associated with real

world opportunities may be a causal factor in their

discovery, it is not what we tested in this experiment,

since the profitability of the opportunity was identical

for both groups.

As noted above, Shane (2000) and Ardichvili et al.

(2003) have used a typology of prior knowledge in

their empirical work. While we believe that we have

mostly focused on prior knowledge of the ways to

serve the market and knowledge of consumer demand,

our description of prior knowledge may be opened to

criticism. Additionally, it can be said that only an

aspect of entrepreneurship is being studied here, that

is, entrepreneurship as the sheer recognition of an

opportunity. The arbitrage opportunities exist in our

experimental setting; they are objectively present

irrespective of what the subjects may think or imagine.

In other words, the type of discovery that is studied

does not seem to involve a creative act. While this may

be true at some level, participants nevertheless

perform an act of creation by bringing an unknown

(to them) opportunity to life. Moreover, from the

subject’s perspective, Mr. Green is bringing a new

product to the market and thus performs a creative act,

even if the opportunity exists independently of the

subject’s mind. In addition, our experiment was not

about showing the creative potential of subjects but

simply about testing the contention that prior knowl-

edge plays a role in entrepreneurial discovery. We do

not think, however, that this affects the quality of our

findings, as we believe that our laboratory setting

shows the influence of prior knowledge on the

discovery of an opportunity.

Additionally, the relationship between knowledge

and opportunity discovery may be contingent not only

on prior knowledge but on learning and cognition

(Corbett 2005; Dimov 2007b; Shane and Venkatarman

2000; Politis 2005). Prior knowledge can become a

constraint because it keeps individuals in the past and

thus stops them from being alert to new possibilities

(Ward 2004).15 While prior experience with computer

14 ‘‘Three major dimensions of prior knowledge are important

to the process of entrepreneurial discovery: prior knowledge of

markets, prior knowledge of ways to serve markets, and prior

knowledge of customer problems’’ (Shane 2000, p. 452). Also

Shepherd and DeTienne (2005, pp. 104–105) state that ‘‘it is

important for entrepreneurship scholars investigating the rela-

tionship between prior knowledge and the identification of

opportunities to distinguish between types of prior knowledge.’’

15 See Ward (2004, p. 175), for instance, ‘‘Sometimes knowl-

edge provides a bridge to the next new development and

sometimes it becomes a fence that blocks our path.’’


123

games may have inhibited some discoveries, we do not

believe that our treatment caused a constraining effect.

Rather, as we mentioned above, it is more likely that

differences in subjective perceptions, cognition, or

learning styles explain the differences of alertness

within each treatment group.16

6 Concluding remarks

We have shown that the alertness aspect of entrepre-

neurship is influenced by prior experience in a testable

way, and is consistent with the alertness perspective on

entrepreneurial discovery. Following our experiment,

it can be assumed that prior knowledge not only

influences the field in which a discovery can take place,

but also how alert an individual can be to opportunities

in a given field. Our two most important contributions,

therefore, are controlled, laboratory confirmation of

the alertness hypothesis, and a proof of concept for

future controlled experiments on entrepreneurial

building blocks. Rather than rely on new business

creation, psychological profiles, or survey data as

proxies for entrepreneurial activity, we can get at the

meaning of entrepreneurship in the cognitive sense

using controlled, replicable experiments.

We encourage humility and caution when turning

from any single experiment to policy implications.

One should not conclude from the study that because

prior knowledge is important to discovery, this might

have consequences for practitioners of entrepreneur-

ship and policy makers. While this experiment

suggests there is reason to believe in a connection

between prior knowledge and alertness, there is no

reason to think that we know more about teaching

people to discover opportunities. Even if we can show

that a number of thought processes exist through

which individuals may come to discover opportuni-

ties, it does not imply that these thought processes can

be replicated in ways that systematically improve

discovery of opportunities in the real world. In our

experiment, the prior knowledge given to participants

bore a relationship with the nature of the opportunity

hidden in the experiment, but known to the experi-

menters. In real life, opportunities are unknown to all.

Appendix

Instructions and screen shots

Welcome to today’s economics experiment!

You will be taking part in a decision making study.

We are interested in your decisions that you make on

your own. That means, now that the experiment has

started, no talking and no texting, please. Please turn

off all electronic devices and place them in your bag,

under the desk.

If you have any questions at any time during the

experiment, or have any trouble with the computer,

please raise your hand, and we will come to you to

answer your question.

Please click the ‘‘Story’’ button to continue.

Story

We’ll begin with a short story. In this experiment, you

will take the role of Mr. Green.

Mr. Green grew up in a small village called Green

Village, where he runs a small factory. Mr. Green has

always been very similar to his fellow villagers. They

usually like the same drinks, food, clothing and art that

Mr. Green likes. On his 25th birthday, Mr. Green

travels to Brown Town, a small country town 150

miles away. He spends the day shopping in the local

market and sampling the local food and drink. Most of

what he finds he is familiar with from his home village,

but that night he buys an exotic fruit that he’s never

had before, and he absolutely loves it. Mr. Green

thinks to himself that the other villagers would

probably like this fruit.

Previous

Next

Instructions part 1

You earn money in this experiment by increasing

Mr. Green’s wealth and happiness. At the end of the

experiment, we will add up Mr. Green’s gold coins and

happy points and pay you the total divided by 15.

We will now guide you step by step through a few

of the possible actions you can perform.

16 See Dimov (2007a, p. 576) who state that ‘‘Individuals’ prior

knowledge of the opportunity domain increases their likelihood

of acting on their initial opportunity insights only when their

style of learning is compatible with the situation at hand.’’


123

In this experiment, all actions are performed by

dragging and dropping pictures, just like you might

drag a file and drop it into a folder on your computer.

Practice dragging the gold coin below, and drop it

into the factory (then follow the instructions that

appear below).

Instructions part 2

By spending money in the factory, one gold coin, you

have created boxes. Now drag the boxes and drop them

in Green Village.

Instructions part 3

Notice that by selling boxes in Green Village, you

earned money. Now try spending money in Brown

Town to buy fruit.

Instructions part 4

Good. Now drag the boxes of fruit to Mr. Green.

Instructions part 5

Notice that when Mr. Green eats the fruit, his

happiness increases. Each week, Mr. Green’s happi-

ness increases by 5 with his first box of fruit, by 3 with

his second box, and by 1 with his third box.

Each drag and drop counts as one action. You can

perform 1 action per day, and there are 6 days per

week. After 15 weeks, the experiment will end, and

we will pay you your earning in this experiment plus

your on-time bonus of $7. The experiment will also

end if you run out of money.

How you earn money: Remember, at the end of the

experiment, we will add together Mr. Green’s happy

points and gold coins, and pay you in US dollars ($)

the total divided by 15.

You may review the story and instructions now by

clicking on ‘‘Story’’ below. When you are ready to

begin, click ‘‘Go to Quiz’’. However, once the

experiment begins, you will not be able to return to

the instructions.

Story

Go to Quiz

Quiz

Here is a little test. Pass, and the experiment will

begin. Otherwise, you will return to the story to try

again. Be alert!

If Mr. Green eats 2 boxes of fruit in 1 week, the

total number of happy points increases by


123

(A) 4

(B) 8

(C) 10

(D) 6

How far is Brown Town from Green Village?

(A) 75 Miles

(B) 100 Miles

(C) 150 Miles

(D) 200 Miles

Mr. Green is generally

(A) Similar to other people from Green Village

(B) Different from other people from Green Village

This first image is the starting screen for the market.


123

This second image shows the screen after a few

turns and in which both boxes and fruit have been

purchased.

The first box of fruit sold in the village earned 6

coins, the second 4, and the third 2. Since payment was

based on the linear sum of coins and happiness, the ex-

post optimal strategy is to consume one and sell two

boxes of fruit per week. We found that most subjects

who discovered arbitrage either followed this strategy

or simply alternated between selling and consuming

fruit, occasionally exploring other possible drag-drop

combinations.


123

The End.

Well, that about does it.

Please raise your hand now, and the experimenter

will come to check your earnings.

Happiness: 59

Money: 108

Earnings from the experiment: $12

Ontime show-up bonus: $7

Total Earnings: $19

Age:

Gender:

Class:

Major:

Please explain why you did what you did in this

experiment:

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Prior-Knowledge and Opportunity Identification

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