Proceedings of the 8th International Conference on Intellectual ...

Constantin Bratianu et al.
shows <strong>the</strong> direction <strong>of</strong> future development. In any production engineering field or any management
activity people do make decisions which have consequences. These decision making processes are
irreversible and we have to develop entropic thinking models in order to understand and to find <strong>the</strong>
best solutions.
2.2 Complexity dimension
Linear thinking model is used to approximate complexity <strong>of</strong> our environment. It is like we use
frequently linear segments to approximate curves <strong>of</strong> different shapes. Linear thinking has been
defined in literature in two different ways. One is starting from <strong>the</strong> ma<strong>the</strong>matical definition <strong>of</strong> linear
spaces (Bratianu, 2009; Bratianu & Vasilache, 2010), and o<strong>the</strong>r considers a broader perspective
given by <strong>the</strong> Cartesian dualism mind and body (Groves et al., 2008; Vance et al., 2007). In this
second case, <strong>the</strong> distinction is being made between cognitive intelligence and emotional intelligence.
Basically, linear thinking assumes that for a given transformation process, <strong>the</strong> output variables are
proportional with <strong>the</strong> input variables. Thus, if we know <strong>the</strong> input variables and <strong>the</strong> process constants
we just multiply <strong>the</strong>m and get <strong>the</strong> outputs variables. It is such an easy thinking model that most <strong>of</strong> our
everyday life is based on it. All measurements systems are developed according to linear thinking. In
research, we use frequently linear models especially to express physical material properties and <strong>the</strong>ir
behavior under different fields <strong>of</strong> mechanical, <strong>the</strong>rmal or electromagnetic forces. There are many
o<strong>the</strong>r fields <strong>of</strong> activities where people are using linear thinking, without even questioning its legitimacy
or accuracy. For instance, budgetary salaries are based on linear thinking, making hard any
differentiation among different people according to <strong>the</strong>ir individual experience, competence,
contribution and performance. Due to this fact, incentives and motivation are very low in any
budgetary systems, by comparison with performance based evaluation and payment in business
organizations. The most characteristic operation in linear thinking is addition.
Nonlinear thinking model uses correlations between output variables and input variables which have
nonlinear ma<strong>the</strong>matical formulations, like polynomials, exponentials, logarithms, sine and cosine
functions, integrals, derivatives etc. Of course, that is a much more difficult approach but it is closer to
real phenomena. The point we try to make is that a person who thinks only in a linear way cannot
understand accurately complex phenomena which have a nonlinear nature. Intellectual, emotional
and creative processes are highly nonlinear (Bratianu, 2011; Gardner, 2006; Goleman, 1995). It is a
mistake to evaluate <strong>the</strong>m based on linear models. Innovation and creativity are highly nonlinear
processes. Thus, for a successful management which develops innovative strategies in order to
obtain a strategic competitive advantage nonlinear thinking is <strong>the</strong> only possible approach. In <strong>the</strong> same
time managers must develop new metrics for progress evaluation and for excellence stimulation.
2.3 Uncertainty dimension
Deterministic thinking model is based on idea that things and events must be well defined and
determined before <strong>the</strong>y happen. Actually, <strong>the</strong>y happen due to our way <strong>of</strong> determining <strong>the</strong>m. Their
occurrence is certain. That means that <strong>the</strong>ir probability <strong>of</strong> happening is always equal to one. Also, we
may say that chances to occur such an event are 100%. There is no uncertainty and thus no risk
associated to such a deterministic thinking. For instance, 2+2=4 is true anytime, and everywhere.
There is no question about it. Actually, deterministic thinking is a social invention made in order to
reduce chaos and to enable some kind <strong>of</strong> activities to take place. One <strong>of</strong> <strong>the</strong> best examples <strong>of</strong>
deterministic thinking is <strong>the</strong> time schedule for trains and for airplanes. Without such a time schedule
no coordination <strong>of</strong> <strong>the</strong>ir circulation or flight can be done. Deterministic thinking is necessary in
organizing <strong>the</strong> traffic on public roads and highways. The rules established for car driving by legislation
is a clear model <strong>of</strong> a deterministic thinking. And we have to emphasize <strong>the</strong> fact that we need such
kind <strong>of</strong> thinking at social level. The question is how much <strong>of</strong> our social life, organizational life or family
life should be ruled by such a deterministic thinking? We should not forget that deterministic thinking,
excessive discipline and order in any organization kill incentives and innovation which might produce
outcomes in conflict with <strong>the</strong> well established order. Deterministic thinking has been used extensively
by scientists and engineers. Most <strong>of</strong> all <strong>the</strong> science laws we studied in schools and universities are
actually a product <strong>of</strong> a deterministic thinking.
Probabilistic thinking model is based on <strong>the</strong> fact that uncertainty is <strong>the</strong> rule and not <strong>the</strong> exception.
In nature, society and life events do not have certain outcomes. Events occurrence has a probabilistic
nature and <strong>the</strong>y may happen with some probabilities (Taleb, 2004). One <strong>of</strong> <strong>the</strong> most known example
is <strong>the</strong> wea<strong>the</strong>r forecast. We learn from TV programs or from newspapers how <strong>the</strong> wea<strong>the</strong>r will
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