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A Proposal for a Standard With Innovation Management System

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Ioannis Akritidis and Alexandros Kakouris<br />

The result <strong>for</strong> a fully adaptive entrepreneur (α=0.5, β=0.5) is shown by the (b) curves (with circular<br />

markers) in Figure 2. The fully adaptive learner has no predominant learning style and corresponds to<br />

the Minniti and Bygrave (2001) individual. Solid curves in Figure 2 show the evolution of the selfconfidence<br />

level <strong>for</strong> the 10 th option of the entrepreneur (i.e. the most promising <strong>for</strong> the entrepreneur<br />

without interaction with the market) while dashed curves show the evolution <strong>for</strong> the 50 th option (i.e. the<br />

most favoured by the market). The fully adaptive person gives the same confidence (~4%) <strong>for</strong> the two<br />

options after two time-steps. He also attains an asymptotic confidence (i.e. equilibrium) <strong>for</strong> the 50 th<br />

option of ~7% (~1% <strong>for</strong> the 10 th respectively) after 20 time-steps.<br />

An entrepreneur with converging learning style (α=0.2, β=0.5) attains the asymptotic values <strong>for</strong> his<br />

options more rapidly compared with the fully adaptive. The convergent one, shown by curves (c) with<br />

diamond markers in Figure 2, attains equal confidence (~4%) <strong>for</strong> the two options in almost 1.5 timesteps.<br />

He also attains a slightly higher asymptotic value (~7.5%) <strong>for</strong> the 50 th option much earlier.<br />

Practically, after the 10 th time-step the convergent has reached equilibrium. The result is due to the<br />

market evidence distribution which promotes an option in the converging style domain (dashed curve<br />

in Figure 1).<br />

Let now consider an entrepreneur with diverging learning style (α=0.8, β=0.5). The evolution of<br />

confidence levels are shown by the curves (a) with asterisk markers in Figure 2. The diverging<br />

entrepreneur attains equipartition of self-confidence much later (more than 5 time-steps) compared to<br />

the previous cases. He also reaches a significantly less asymptotic value (~5.5%) <strong>for</strong> the most<br />

favoured option in 20 time-steps. The “resistance” of the diverging entrepreneur to abandon his initial<br />

(diverging) 10 th option due to market evidence is much higher compared with the rest two.<br />

The present example illustrated a symmetrical case <strong>for</strong> entrepreneurs who are expected to empirically<br />

change their options (confidence on alternatives) due to the interaction with the market. Converging<br />

style situations correspond to supply-driven opportunities in the market whilst diverging ones<br />

correspond to demand-driven opportunities (Dimov 2007). As the increase of self-confidence <strong>for</strong> an<br />

entrepreneurial option is expected to lead to intentional action, the present simulation results are in<br />

agreement with Dimov’s (2007) findings.<br />

4. Discussion and implications<br />

Learning from experience is fundamental in business venturing. The model of Minniti and Bygrave<br />

(2001) simulates decision making of a rational entrepreneur who interacts with a market. The<br />

entrepreneur has an initial conception about his/her options; however, he/she is keen to learn from<br />

experience. The model supposes that the entrepreneur can change his/her options without calculating<br />

the costs <strong>for</strong> such a change (e.g. transactional costs). Krrznerian alertness has also to be considered<br />

<strong>for</strong> a more consistent simulation of entrepreneurial decision making (e.g. Parker 2007). However, new<br />

entrepreneurial knowledge and insight are expected to build upon prior knowledge and experience<br />

(Shane 2000). Thus, experiential learning models provide an initial base <strong>for</strong> simulating the evolution of<br />

small firms.<br />

The adoption of the learning style from Kolb’s (1984) theory complements existing decision making<br />

models by introducing individual difference features in the analysis. Such a consideration advances<br />

the effectiveness of the models to deal with SMEs and innovating firms where many decisions depend<br />

upon leading individuals. Corbett (2005, 2007) discussed effects of the learning style in the<br />

organisational context. The way to build effective entrepreneurial teams within an organisation is not<br />

straight<strong>for</strong>ward; however, learning styles underlie the process and the distribution of liabilities.<br />

Recently, Gemmell, Boland and Kolb (2011) discussed “entrepreneurial ideation” in the context of<br />

social creativity <strong>for</strong> innovating firms. Hence, the adoption of learning style is expected to have<br />

implications in the organisational context.<br />

The introduction of a personal “style” inducing “myopic” view on the market evidence in Minniti and<br />

Bygrave’s model may not explicitly refer to a learning style. An entrepreneurial style may be more<br />

appropriate; however there is poor development of such a style so far. Many personal attributes and<br />

traits are related to business venturing in literature; however, they have to be integrated in a concise<br />

framework. The adoption of other “styles” enables further quantitative analyses.<br />

Another consideration pertains to the number of options which a real entrepreneur considers and<br />

crosschecks. We expect an increase of options to elongate the time interval <strong>for</strong> an entrepreneur to act<br />

5

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