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Economic Rationality-based Entrepreneurial vs. Employee Orientations by Entropy, Updating and Error Rates Computing: Evidence of Kenyan Credit Unions

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Unemployment is one of the greatest concerns of economies. Strong advocacy for entrepreneurship development by way of creating an enabling environment for funding entrepreneurs to start own businesses and training to ensure sustainability is an international objective. This paper contrasts financial decision making orientations for credit union entrepreneur members and credit union employee members of Unitas and Stima credit unions respectively who share the same return on assets. Three objectives were pursued. First was to establish that higher entropy does not necessarily result into a higher rationality level. Secondly, the paper set out to show that a low error rate is an important factor that leads to higher rationality levels, which results to better financial performance. Finally, it sought to establish that updating rate is critical to long run financial performance. A 9-point Likert longitudinal data for 2005 and 2015 was collected and converted into probabilities. Since the probabilities are subjective, cumulative prospect theory decision weights function was used to transform them into objective probabilities, and then fitted into a multi-period Bayesian rationality model. Unitas members with less than half the potential of Stima members and a lower rationality starting point catch up with Stima members within the 10 years. Stima’s endowment of a lower updating period did not give it any advantage. The single all important factor is the updating rate, which worked in favor of Unitas credit union members. The paper recommends that entrepreneurial union members should be supported more by the government to accelerate wealth creation, hence job creation.
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ISSN: 2151-6219
Kirika et al., Bus Eco J 2017, 8:3
DOI: 10.4172/2151-6219.1000318
Volume 8 • Issue 3 • 1000318Bus Eco J, an open access journal
ISSN: 2151-6219
Keywords: Entropy; Updating rate; Error rate; Decision weights
function; Entropy-q rationality model
Introduction
Unemployment is probably the greatest economic concern in the
world. Existing organizations and business enterprises are not sucient
avenues of providing employment, hence calling for more individuals to
venture out and identify human needs requiring address; and produce
goods and services to meet the needs, thereby creating employment
through entrepreneurship. e International Labor Organization in
2011 lamented that only 23.5% of the youth in the world are employed,
yet poorly so. Economic transformation of societies will hence require
entrepreneurship [1]. is creates broadly, two groups of people in
the economic production arena. One comprising employees earning a
living by being formally hired by assorted organizations and the other
one entrepreneurs who establish and run own business enterprises.
To represent these groups are two credit unions; namely, Unitas
and Stima, which happen to among the best performers in year
2012. Incidentally, one of the characteristics of the entrepreneurial
group studied (Unitas) was that they were high school dropouts or
graduates. ese are therefore likely to be necessity entrepreneurs
[2]. A majority of Stima members studied are Kenya Power Limited
employees. e entrepreneurial orientation is represented by Unitas
while employee orientation by Stima credit unions, respectively. Both
groups share the same return on assets. is paper sought to provide
evidence of these dierent economic decision making orientations
and the accompanying rationality progression over a ten year period
2005 through 2015. Entropy-q rationality model was used to show
that entrepreneurs’ as opposed to employees’ economic rationality is
composed of dierent proportions of the component variables in the
model, and that therefore these combinations can then be used to cra
a recruitment criterion for employees and possibly a funding criterion
for the entrepreneurs especially start-ups. e paradox examined is
the perception that more educated individuals should be better wealth
makers [3]. In the foregoing sections, Bayesian decision and bounded
rationality theories are reviewed; then the entropy-q rationality model
is introduced. Methodology comprised derivation of updating and
error rates computation, for ten year wealth movement diusion.
Statement of the Problem and Objectives
McCloskey’s [4] question “if you’re so smart, why aren’t you rich?”
features prominently in this paper. While many a scholars opine that
education is the key to economic prosperity, may be not directly or
rather not necessarily through entrepreneurship. However, it has been
found out that a higher level of entrepreneurial activity was higher in
more educated immigrants within the OECD countries than the less
educated immigrants agreeably so [5]. But there is a caveat here. In
the unpublished research conducted in 2016, it was found out that the
potential of nancial decision making ability of credit union members
was positively correlated with relative entropy but negatively correlated
with education. Surprisingly, education was highly correlated with
relative entropy; where entropy is the dierence in individual prospects
of beneting from rational nancial decisions from prospects of
benetting from irrational decisions [6]. is means that there is
substantial concurrence with McCloskey’s question. If education is the
*Corresponding author: Kirika SK, Department of Management, Jomo Kenyatta
University of Agriculture and Technology, Juja, Nairobi, Kenya, Tel: 0722-276580;
E-mail: stanleykirika@gmail.com
Received July 03, 2017; Accepted September 20, 2017; Published September
27, 2017
Citation: Kirika SK, Muturi W, Waititu A (2017) Economic Rationality-based
Entrepreneurial vs. Employee Orientations by Entropy, Updating and Error
Rates Computing: Evidence of Kenyan Credit Unions. Bus Eco J 8: 318. doi:
10.4172/2151-6219.1000318
Copyright: © 2017 Kirika SK, et al. This is an open-access article distributed under
the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and
source are credited.
Economic Rationality-based Entrepreneurial vs. Employee Orientations by
Entropy, Updating and Error Rates Computing: Evidence of Kenyan Credit
Unions
Kirika SK*, Muturi W and Waititu A
Department of Management, Jomo Kenyatta University of Agriculture and Technology, Juja, Nairobi, Kenya
Abstract
Unemployment is one of the greatest concerns of economies. Strong advocacy for entrepreneurship development
by way of creating an enabling environment for funding entrepreneurs to start own businesses and training to ensure
sustainability is an international objective. This paper contrasts nancial decision making orientations for credit union
entrepreneur members and credit union employee members of Unitas and Stima credit unions respectively who share
the same return on assets. Three objectives were pursued. First was to establish that higher entropy does not necessarily
result into a higher rationality level. Secondly, the paper set out to show that a low error rate is an important factor that
leads to higher rationality levels, which results to better nancial performance. Finally, it sought to establish that updating
rate is critical to long run nancial performance. A 9-point Likert longitudinal data for 2005 and 2015 was collected and
converted into probabilities. Since the probabilities are subjective, cumulative prospect theory decision weights function
was used to transform them into objective probabilities, and then tted into a multi-period Bayesian rationality model.
Unitas members with less than half the potential of Stima members and a lower rationality starting point catch up with
Stima members within the 10 years. Stima’s endowment of a lower updating period did not give it any advantage.
The single all important factor is the updating rate, which worked in favor of Unitas credit union members. The paper
recommends that entrepreneurial union members should be supported more by the government to accelerate wealth
creation, hence job creation.
Citation: Kirika SK, Muturi W, Waititu A (2017) Economic Rationality-based Entrepreneurial vs. Employee Orientations by Entropy, Updating and Error
Rates Computing: Evidence of Kenyan Credit Unions. Bus Eco J 8: 318. doi: 10.4172/2151-6219.1000318
Page 2 of 5
Volume 8 • Issue 3 • 1000318Bus Eco J, an open access journal
ISSN: 2151-6219
key to entrepreneurial generated riches, then educated people should
be the richest. is paper sought to provide evidence for this claim and
to numerically establish what brings about this dierence in wealth
accumulation between the educated and the less educated. e problem
is why does this dierence exist? Why the paradox, that all nations are
investing heavily in education; yet the highly educated do not create
as much wealth as the low educated cadres? Is there a quantitative
model that isolates specic determinants of nancial decision making
behaviour to explain this disparity?
In general, necessity entrepreneurs possess limited cognitive
decision making potential by reason of low end education achievement
as compared to opportunistic or even the serial ones [7]. By implication,
necessity entrepreneurs should accumulate the least wealth in the long
run. In contrast, employees formally engaged acquire such status
by reason of higher education achievement. eir private lives are
expected to be a reection of their enormous potential and endowment.
Unfortunately, in the long run, these necessity entrepreneurs are likely
to accrue more wealth than formal employees. Formal employees make
more nancial decisions mistakes than their low end counterparts [6].
A critical point here is that both necessity entrepreneurs and formal
employees under consideration reside in the same city; and therefore
can fairly access similar services and nancial information. is shows
existence of structural economic decision making setting unique
to each group even if they share similar economic decision making
rationality levels, such that necessity entrepreneurs accumulate more
wealth in the long run. While the general objective was to distinguish
these two nancial decision making orientations; entrepreneurial and
employment quantitatively, the three specic objectives pursued were
as follows. First, to establish the eect of entropy, this is proportional to
decision volume; on nancial decision making rationality.
According to the law of maximum entropy, maximization of the
overall entropy of the variables in question maximizes performance [8].
Any business man starts one with a view of making prots perpetually.
However, factors beyond control of the entrepreneur come into play
in ordinary life like crop failure for the farmer or market failure for
the merchandise enterprises leading to losses. On the part of the
employee, medical bills for chronic diseases for example may alter
the intended wealth trajectory in a certain period of wealth creation.
ese countable wealth decreases have been referred to as error rate. In
this connection, the paper secondly, set out to determine the eect of
error rate on nancial decision making rationality. Finally, it has been
observed that human beings do not regularly update their lessons in
their subsequent decision behavior to secure more informed decisions
[9]. If a son, holding brief in shop keeping for his hospitalized father,
requests the father how much of a particular stock should be ordered,
the father cannot have solid ground to respond to the question. is is
because he has not been around to track new customers and any new
information. Any response given to the son will contain some base rate
neglect. Base rate neglect is the opposite of updating rate. is takes us
to the nal objective; to establish the eect updating rate on nancial
decision making rationality, hence nancial performance measured by
wealth level.
Literature Review
Examination of economic decision making behavior patterns
requires a look at how humans process information. People make
decisions on the basis of two sources of information: the objective
external source and the internal source which usually combines
cognitive and aective domains. ey make mistakes oen but never
intend to make them [10]. e fact that they make mistakes reveals that
they are sometimes irrational implying that their rationality is bounded
[11]. To this end, a short digression into bounded rationality theory
suces.
Bounded Rationality eory
is theory states that human beings economic rationality is
never complete for two reasons: one, they possess limited cognitive
processing ability even if all information relevant to a decision was
available. Secondly, it is never possible to have all information pertinent
to a decision all the time. So, humans make ‘satiscing’ (good enough)
decisions instead of completely rational decisions [11]. Oen times,
people take decisions without fully processing available information
owing to time constraints yet the decision is urgent. is is against
one of the assumptions of rational decision making model, that there
is no cost or time constraint to a decision. Lots of empirical evidence
exists on bounded rationality. It has been cited that sustainable supply
chain management was hampered by bounded rationality on the part
of managers [12]. In a dierent scenario where real estate investments
were examined, the more fundamental rationality assumption by neo-
classical economics was rejected [13]. It was found that investors are
not completely rational. Again, in a study conducted in Germany, it was
found that farmers do not immediately switch to new banks oering
lower interest rates. is was partly attributed to migration charges and
partly due to bounded rationality. Farmers underestimated nancing
costs by about 10 times [14]. In the light of this evidence, Bayesian
decision theory has been used to construct a rationality measuring tool
which was used in analyzing the data collected.
Bayesian Decision eory and Cumulative Prospect
eory
Also known as the probability of causes, Bayes theorem determines
the probability of an event A was a consequence of nite one of the
events B1, B2, B3… Bn [15]. is applies for a single time period
process. Further, this process can be aggregated for multiple time
periods; which has been used to derive rationality levels that accord with
bounded rationality theory discussed previously. On the basis of Bayes
theorem, Bayesian decision theory and model derive. Besides, the same
breadth of logic gives birth to Bayesian statistics which is considered
more accurate than the conventional frequent statistics [16]. Analysis
by Bayesian decision theory entails two dimensions: observable variable
dimension and the unobservable variable dimension [17]. In this case,
the observable variable dimension is wealth while the unobservable
dimension is the rationality level that generated the wealth. While it
is possible to analyze any nite number of prior activities, only two
possibilities were envisaged. Either wealth increases or decreases
(binomial). is setting leads to eqn. 1.
(1 )
(1 ) (1 ) q (1 )
id
i d id
crp p
rp p r q
Γ=
− +−
(1)
Where, Г=current economic rationality
c=updating consistency rate – the ratio of updating to total decision
points
r=prior probability of making a rational decision
p=prospects of wealth increase aer a rational economic decision
q=prospects of wealth increase aer an irrational economic
decision
Citation: Kirika SK, Muturi W, Waititu A (2017) Economic Rationality-based Entrepreneurial vs. Employee Orientations by Entropy, Updating and Error
Rates Computing: Evidence of Kenyan Credit Unions. Bus Eco J 8: 318. doi: 10.4172/2151-6219.1000318
Page 3 of 5
Volume 8 • Issue 3 • 1000318Bus Eco J, an open access journal
ISSN: 2151-6219
i=number of wealth increases observed
d=number of wealth deceases observed
Entropy, Updating Rate and Error Rate
is refers to the distance (scalar) between two probability
distributions also known as Kullback-Leibler’s divergence. According
to the maximum entropy principle, the highest entropy generates the
highest productivity as represented in eqn. 2.
()
()
( ) ( ) ln ()
q
x
qx
Dq p qx I p
px
χ
= =
(2)
In this case, high rationality level is generated by individuals
with high entropies. But not just entropy, two individuals with same
entropies may generate dierent rationality levels other factors held
constant. is dierence emanates from dierent q-values. Recall that
q represents prospects of posting a wealth increase aer making an
irrational decision. is is equivalent to expecting gain from illogical
decisions like gambling. is q-value is inversely proportional to
entropy, so that higher the q-value, lower the entropy level. e
composite eect brings about the quantity entropy-q, which means the
quotient of entropy with q-value in eqn. 3.
ln ( / ) (1 ) ln {(1 ) / (1 )}q qp q q p+− − −
(3)
Unfortunately, most empirical studies involving Bayesian analysis
suer from validity issues by reason of use of subjective probabilities.
is problem has been adequately addressed through the use of
decision weights function from cumulative prospect theory by
Kahnemann and Tversky [18]. Part of economics denition, from
which nance branches, is that it ‘examines that part of individual and
social action most closely connected with the attainment and use of
material wellbeing [19]. e individual possesses two components with
regard to economic decisions; the rational and irrational component.
e rational component forms the foundation of classical and neo-
classical economics, while the irrational component forms the basis of
behavioral economics or behavioral nance. e irrational component
derives from human biases owed to the aective domain. To transform
subjective probabilities into objective ones from whose analysis
objective ndings may emerge, the decision weights function is used.
is is a single parameter model, where the parameter δ is the level of
individual optimism measured by the Life Orientation Test – Revised
as shown in eqn. 4 [20].
Methodology
A 9-point Likert Longitudinal data for 2005 and 2015 collected
from Unitas and Stima credit unions within Nairobi metropolitan was
converted into probabilities by deducting 1 from each score to make
the observations continuous by including the 0-1 interval which would
have been excluded and would have caused distortion in analysis. e
scores were then interpolated within the [0, 1] probability interval.
ese probabilities were subjective, so they were transformed into
objective probabilities by processing through the decision weights
function equation 4 [18].
{ }
1/
(1 )
o
s
oo
p
p
pp
δ
δ
δδ
=
+−
(4)
Where ps=subjective probability
po=objective probability
δ=coecient of optimism.
Using iteration method on an excel spreadsheet; the minimum
number of i and d were obtained which preserve continuity. e model
is discrete, therefore not dierentiable. Denitely, higher rationality
levels generate superior economic decisions to lower rationality levels.
Let us also recall that the super-ordinate goal of an individual is to
maximize their economic welfare, whose primary measure is return
on assets. Other measures like return on sales usually apply especially
in balance sheet presentation. Devoid of mistakes or misfortunes in
business, these return measures yield exponential assets or wealth
increases throughout over time as shown in Figure 1.
However, this is idealistic. In reality, businesses and individuals
alike, experience assorted shocks in the ordinary business of life to
post highs and lows over time. is is the real picture depicted in
Figures 2 and 3 and summarized in Table 1 on the consecutive rows
of number of increases and decreases, where i’s representing increases
is accompanied by a number of d’s. is Figure 1 shows an initial
level (Wo shown on Table 1) of wealth on the basis of which the
next level is generated exhibiting the Markov property as is used in
nancial accounting. at every subsequent nancial period’s income
depends on the immediate previous level of capital; ts pretty much
with Markov property. Figures 2 and 3 show a projection of wealth
in 2015 for Unitas and Stima members per individual, including the
increases and decreases shown in Table 1. e graph is generated by
simulation using the R-statistical soware. From these two Figures 2
and 3, a wealth level of Ksh2, 050,000 and Ksh2, 900,000 average per
member for Unitas and Stima, respectively. en from Table 1, initial
wealth levels were Ksh140, 000 and Ksh340, 000 for Unitas and Stima,
respectively. Finally, simple workings of the number of times each
member has turned the original value gives 2,000,000/140,000=14.286
0 50 100 150
0.0e+00 1.0e+09 2.0e+09
Time
Wealth
Figure 1: Idealistic wealth increases over time.
5 10 15
500000 1500000 2500000
Time
Wealth
Figure 2: Average Unitas members wealth projection by 2015 (time 15) using
initial wealth in 2005 (time 0).
Citation: Kirika SK, Muturi W, Waititu A (2017) Economic Rationality-based Entrepreneurial vs. Employee Orientations by Entropy, Updating and Error
Rates Computing: Evidence of Kenyan Credit Unions. Bus Eco J 8: 318. doi: 10.4172/2151-6219.1000318
Page 4 of 5
Volume 8 • Issue 3 • 1000318Bus Eco J, an open access journal
ISSN: 2151-6219
times and 2,667,000/340,000=8.334 times for a Unitas member and
Stima member respectively.
Unlike Unitas members, Stima members recorded 30 decisions
within the 10 years. is is twice as much as Unitas; displaying
enormous potential. is number of decisions is also supported by the
slightly more than twice entropy of the Stima members.
e summary of ndings is shown in Table 1. From this table,
rationalities of both groups get to the same point of declared rationality
values of 0.9669 and 0.9693 by year 2015 from an original of 0.8576
and 0.88 for Unitas and Stima respectively. However, the potential of
Unitas in terms of entropy is slightly less than half of that of Stima. Ten
years later, Unitas members who are entrepreneurs catch up with Stima
members who are employees in formal employment by virtue of having
acquired tertially level education. Update time is then computed using
eqn. 5 and which yields 10 months and 6.316 months, respectively for
Unitas and Stima members respectively. is means that within the 10
year period, Stima members updated aer every 6.316 months while
Unitas members, by reason of low level of education, took 10 months
to update their learning of economic decision making in the lives.
120
Update time = id+
(5)
Most surprising was that out of the 12 updates recorded by Unitas
members, only 2 were wealth decreases; an error rate of 16.67%.
In contrast, out of the 19 updates recorded by Stima members, 5 of
them led to the process error rate of 26.32%. Coupled with this is
the updating rate. From Table 1, Unitas updating rate stands at 0.8
while that of their Stima counterparts is 0.63. is means that Unitas
members make reference to previous learning 80% of the time while
Stima members do so 63.3% of the time. Unitas members are more
alert compared to Stima members. Paraphrased, the levels of guess
work in nancial decision making are 20% and 36.7% for Unitas and
Stima members respectively [21]. Error rate and Updating rate led to
Unitas members’ rationality level to increase at a higher rate, almost
catching up with Stima members’ rationality level by 2015 despite the
enormous potential of Stima members expressed in entropy terms.
e eect of updating rate results in real rationality levels of 76.34%
and 61.58% for Unitas and Stima members respectively. Noting that
Stima members had a higher average of declared rationality of 0.9724
compared to 0.9543 for Unitas, it means that updating rate bears such
a devastating eect.
e long and short of it is that employees are more laid back in
their nancial decision making decisions. is practice is observed
in behaviours like not bargaining for public transport fares, making
high cost house hold consumer goods that match their social class
seeking to be more esteemed by their peers among others. Employees
have more time to attend the gym and conclude the work day with a
drink in favorite joints. ese tendencies predispose the employee to
higher irrational consumption and investment behaviour unlike their
entrepreneurial friends in Unitas credit union. Unitas members who
are self-employed care a lot about all the resources at their disposal for
survival. ey close shop at upwards of 9.00 pm, are more price sensitive
than Stima members, plan their o-duties properly to ensure their small
businesses do not lose their customers, care less about their social class
and are therefore able to save more money in the long run compared
to Stima members. is has made this class of people create more jobs
sustainably than formally employed individuals. Self-employed people
are less nancially included. is goes a long way inculcating good
saving habits. In the meantime, the formally employed are inclined to
betting habits and over rely on loans, leading to debt vicious cycles.
0 5 10 15 20 25 30
500000 1500000 2500000
Time
Wealth
Figure 3: Average Stima members wealth projection by 2015 (time 30) using
initial wealth in 2005 (time 0).
Credit Union Group Unitas Members
(necessity
entrepreneurs)
Unitas Mgt (SACCO
employees)
Stima Members (company
employees)
Stima Mgt (SACCO
employees)
r 0.8576 0.5592 0.88 0.6866
q 0.5962 0.6904 0.5121 0.5613
p 0.8325 0.8709 0.8323 0.9365
entropy 0.1563 0.1105 0.2723 0.5606
Number of increases (i) 10 12 14 15
Number of decreases (d) 2 1 5 3
Declared rationality in 2005 (a) 0.8576 0.5592 0.88 0.6866
Declared rationality in 2015 (b) 0.9665 0.8934 0.9699 0.9361
Declared period rationality (avg) (c) 0.9543 0.8029 0.9724 0.9134
Return rate 0.2889 0.2735 0.2814 0.3208
Standard deviation 0.4604 0.0903 0.2579 0.2304
Net worth (Wo Sh’000) in 2005 140 8,27,386 320 23,209
Net worth (Wo Sh’000) in 2015 2000 92,83,271 2,667 2,62,494
Update time = 120/(i+d) 10 9.231 6.316 6.667
Error rate = d/(i+d) 0.1667 0.1667 0.2632 0.2
Update rate (d) 0.8 0.8667 0.6333 0.75
Real rationality for the period (c)x(d) 0.7634 0.6959 0.6158 0.6851
Wealth (net worth) turnover 14.286 times 11.22 times 8.334 times 11.31 times
Table 1: A summary of unitas and stima credit unions entropy-q, update rate and error rates.
Citation: Kirika SK, Muturi W, Waititu A (2017) Economic Rationality-based Entrepreneurial vs. Employee Orientations by Entropy, Updating and Error
Rates Computing: Evidence of Kenyan Credit Unions. Bus Eco J 8: 318. doi: 10.4172/2151-6219.1000318
Page 5 of 5
Volume 8 • Issue 3 • 1000318Bus Eco J, an open access journal
ISSN: 2151-6219
is is, in the long run, likely to turn them into dependents especially
where drug addiction is involved. e government should give the
entrepreneurial group the required attention.
Conclusion
It is common place to assume that education leads to acquisition
of formidable potential for wealth creation hence a better position in
social stratication. is study has, however, revealed that the grave
assumption is only one of several determinants and that it may not
be the most crucial. While high entropy endows the individual a
high potential for wealth creation, it must be accompanied by other
ingredients of updating rate and error rates favorably. While error
rate may at times be uncontrollable by the individual, updating rate
is purely an individual’s eort and which, from this study, emerged
as the most critical. Unitas members are necessity entrepreneurs who
seek to eke a living from small and medium business enterprises. ey
are very careful not to engage in nancial decisions detrimental to their
survival. For example a green grocer must wake up very early to get to
the market to secure purchases at wholesale prices and back to their
premises probably in the estates in good time to display merchandise
for customers. is daily prot is what the grocer survives on. is is
typical of a Unitas SACCO member, who possesses an entrepreneurial
orientation and who in the long run outperformed the formal
employee in wealth creation. On the other hand, e Stima SACCO
member – formally employed, who justiably claims that they invested
in education early in life can aord to wake up late, get to their work
station late, and somewhat still receive their salary intact come month
end. is habit breeds complacency which leads to making many
nancial decisions which are not well thought out. For instance, this
employee may secure a loan to buy expensive smart phones and other
gadgets in the comfort of their loan ability by reason of job security.
is is the employee orientation which results in underperformance in
wealth creation in the long run.
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