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

Constantin Bratianu et al.
probably be next days, but nobody can assure us that <strong>the</strong> forecast is going to be 100% accurate. To
understand and to use properly such a wea<strong>the</strong>r forecast we must develop a probabilistic thinking.
That means to accept <strong>the</strong> fact that some events or some outcomes may happen with some
probabilities, which actually means to accept <strong>the</strong> uncertainty related to <strong>the</strong>ir occurrence. However, any
uncertainty has an associated risk we must understand and in <strong>the</strong> same time we try to reduce
possible negative outcomes generated by this risk. Thus, probabilistic thinking is much more difficult
and sometimes it is hard to accept it, but developing such kind <strong>of</strong> thinking model we will be better
prepared for a future which is unknown and uncertain. For any company or nonpr<strong>of</strong>it organization <strong>the</strong>
external environment becomes more dynamic and changeable, which means more uncertainty for its
future configurations. In order to understand this new trend and to take sound decisions concerning
future developments <strong>of</strong> our activities we must be able to deal with probabilistic events and with <strong>the</strong>ir
associated risks.
2.4 Innovation dimension
Intelligent thinking model reflects <strong>the</strong> processing capability <strong>of</strong> a decision maker in choosing <strong>the</strong> best
solution for a given operational context. Intelligent thinking operates with known explicit and tacit
knowledge. There is no new knowledge creation. Intelligent thinking is based on <strong>the</strong> multiple
intelligence concept developed by Gardner (2006), and on <strong>the</strong> new findings <strong>of</strong> <strong>the</strong> cognitive sciences
(Pinker, 1997; Pinker, 2007; Frith, 2007). Intelligent thinking is very flexible. It searches for many
alternatives <strong>of</strong> <strong>the</strong> given problem and for many possible combinations <strong>of</strong> all known data, information
and knowledge such that from all <strong>the</strong>se combinations to produce <strong>the</strong> best answer. Intelligent thinking
cannot be developed and used in inertial and deterministic business environments characterized by
mediocrity. Intelligent thinking is necessary in research environments. Here it is very important to find
all possible combinations for <strong>the</strong> given facts and information and to find <strong>the</strong> best interpretations for <strong>the</strong>
laboratory or numerical experiments done.
Creative thinking model implies production <strong>of</strong> new knowledge. The production <strong>of</strong> new knowledge can
be delivered by continuous increments or by significant jumps. Knowledge creation becomes more
and more important in any fields <strong>of</strong> activity, but mostly in R&D due to stronger competition and forces
and globalization processes. Creative thinking is mostly needed when we are experiencing changing
environments, characterized by new aspects and phenomena. Creative thinking does not provide <strong>the</strong>
best solution for a given problem, like intelligent thinking does, but it provides a new way <strong>of</strong> solving
that problem or even a completely new solution (De Bono, 1994; Christensen, 2003; Tidd, Bessant &
Pavitt, 2001). We would like to emphasize <strong>the</strong> fact that intelligent thinking and creative thinking are
complementary thinking models, since intelligence implies creativity and creativity implies intelligence.
2.5 Strategic thinking
Strategic thinking represents an integration process <strong>of</strong> <strong>the</strong> most advanced thinking models we
presented above. Strategic thinking deals with <strong>the</strong> future, and that means to incorporate time both
quantitatively and qualitatively. Time is very important as a measure and as a direction <strong>of</strong>
development and improvement. Also, it is important to think <strong>of</strong> change not as a uniform variable
process with zero acceleration, but as a variable process with its own rate <strong>of</strong> change. Thus, strategic
thinking must incorporate <strong>the</strong> entropic thinking model. On <strong>the</strong> complexity dimension, strategic thinking
must incorporate nonlinear thinking model since it is able to approach complexity much better than
<strong>the</strong> linear cognitive approximation. In <strong>the</strong> future all events are probable, that means that <strong>the</strong>y are
uncertain. The incorporated model will be probabilistic thinking. Finally, <strong>the</strong> future needs smart and
creative solutions. In conclusion, strategic thinking will incorporate <strong>the</strong> following thinking models:
entropic thinking, nonlinear thinking, probabilistic thinking, intelligent thinking and creative thinking.
3. Research design and results
The purpose <strong>of</strong> this research is to evaluate <strong>the</strong> degree <strong>of</strong> development <strong>of</strong> strategic thinking <strong>of</strong>
students enrolled in economics and business in <strong>the</strong> main university programs <strong>of</strong>fered in Romania. We
considered both undergraduate students and graduate students in master programs. We elaborated a
questionnaire based on our own experience containing 47 items, such that we could cover all <strong>the</strong>
thinking models presented above on <strong>the</strong> four dimensions: time, complexity, uncertainty and
innovation. For evaluation we used a Likert scale with 5 possible choices (from totally agreement to
totally disagreement). Also, we formulate some questions for student identification (gender, age,
undergraduate/ graduate, university, rural/ urban area). For checking <strong>the</strong> validity <strong>of</strong> our questionnaire
we performed a pilot testing on a group <strong>of</strong> 125 students from <strong>the</strong> Faculty <strong>of</strong> Business Administration,
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