Thinking Patterns and Knowledge Dynamics

Thinking Patterns and Knowledge Dynamics Constantin Bratianu Bucharest University of Economic Studies, Bucharest, Romania [email protected]

Reference: Bratianu, C. (2007). Thinking patterns and knowledge dynamics. In B. Martins & D. Renyi (Eds.). th Proceedings of the 8 European Conference on Knowledge Management. Consorci Escola Industrial de Barcelona, Spain, 6-7 September 2007. Vol.1, pp.152-156. Reading, UK: Academic Conferences Ltd.

Abstract: Literature research shows that knowledge is considered mostly as a potential, being identified under different forms of intangible assets. This view is particularly important in organizational intellectual capital evaluation. However, in knowledge management and in decision making processes knowledge dynamics becomes more and more important. In this perspective, knowledge is considered as being a cognitive structure that can be processed by our thinking patterns to generate new structures. Like in energy field, where potential energy can be transformed into kinetic energy by different mechanisms, in the knowledge field, potential knowledge can be transformed into action as a result of a decision making process. The efficiency of such a transformation depends on the performance of the thinking pattern used, and of the cognitive experience of the manager. The purpose of this paper is to present some generic thinking patterns, and the way in which they contribute to knowledge dynamics with direct consequences on the managerial decision making processes. Our research is based on a theoretical approach, integrating fundamental concepts and ideas from generic science within a new perspective. We are interested mainly in defining six generic thinking patterns and their specific operating performances. The reference system we have taken for this analysis is defined by three fundamental and independent dimensions: time, complexity, and nature of events. On the time dimension we shall consider inertial and dynamic thinking patterns. The inertial thinking pattern is based on cognitive inertia phenomenon, and the absence of time as a basic variable in the events we consider. The inertial thinking pattern is opposing always to change. The dynamic thinking pattern contains time as a basic variable for describing events, and it is capable of understanding and promoting change. Dynamic thinking is necessary in developing strategic thinking. On the complexity dimension we shall consider linear and nonlinear thinking patterns. Linear thinking is a cognitive approximation of the nonlinear thinking. It is characterized by a linear correlation between the inputs and the corresponding outputs of a transformation process. It is frequently used in everyday decision making and in many organizational processes. The nonlinear thinking is characterized by nonlinear correlations between inputs and outputs, in concordance with events and phenomena complexity. On the nature of events dimension we shall consider deterministic and probabilistic thinking patterns. Deterministic thinking is based on events which are certain. Certainty is the generic context for using this thinking pattern. However, life is full of random events and an infinite series of uncertainties. For this type of situations we should be able to use the probabilistic thinking pattern. In the present paper we define, describe and show the practical implications of all of these above thinking patterns. Keywords: intellectual capital, knowledge, knowledge management, thinking patterns. 1. Introduction We are living in a very complex world which is infinite in any meaningful direction we may consider. The deeper we want to penetrate this world, the more and more unknown problems we encounter. However, from biological and psychological point of view, our brain power is limited. Thus, we are facing a real paradox, which can be defined by considering simultaneously our limited brain power and the infinity of the environment we are living in. How can we understand this infinite environment by using an individual finite mind? The only possible answer is by using cognitive approximations, structured into thinking patterns, or mental models. That means actually that we construct mental representations of the environment we are living in, and we deal with these representations in our everyday decision making. As Senge (1990, p.175) remarked, our “mental models determine not only

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how we make sense of the world, but how we take action”. They are deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action. They are powerful instruments in the decision making process, contributing directly to knowledge processing and knowledge dynamics. They are important constituents of the organizational intellectual capital (Andriessen 2004, Andriessen and Tissen 2000, Stewart 1999). Also, researchers in organizational learning show the importance of individual thinking patterns in generating organizational knowledge (Argyris 1999, March 2003, Sherwood 2002). Actually, the similarities between individual mental processes and organizational mental processes are very close. As Albrecht notes “we often describe human beings as doing their thinking with both a conscious mind and an unconscious mind. An organization also has both a conscious mind and an unconscious mind” (2003, p.10). The conscious mind is linked mostly to the explicit knowledge, while the unconscious mind is linked mostly to tacit knowledge. 2. Thinking patterns 2.1 Fundamental reference values Thinking patterns are cognitive models able to approximate the real world and to help us understand the environment we are living in. Regardless of its specificity and approximation power, a thinking pattern is composed of three main functional structures: a knowledge basis, a set of inference rules and a set of fundamental reference values. From a dynamical perspective, the most stable functional structure is represented by this set of basic values. They are actually, cultural values specific for a given education which stand up as reference values for any decisions we make (Bratianu et al 2006, Keeney 1992). Basic cultural values for an American thinking model might be different than those specific for an European model or a Japanese model. For instance, in the American model some of the most common values are individual working and competitiveness, while in the Japanese model they are team working and cooperation. Thus, for similar working contexts, the American thinking model may yield a different decision than the Japanese thinking model. Due to their highly specific cultural values thinking models cannot be transferred just as they are from a country to another country. They must be adjusted according to traditions, culture and education which are specific for the host country. Basic reference values can be changed in time, but it requires a strong motivation, hard work and a stimulating environment. It is very important to stress the fact that environment should be supportive and not against such a change of cultural values. For instance, in the European former socialist countries building new economies based on new market values is a very difficult and slow process, because most of the old environment which still exists is not supportive. Thus, this transition to a new economy based on new economic and social values might take a generation time. 2.2 Inference rules The set of inference rules contains all operations which actually contribute to information and knowledge processing, and decision taking. Here we find all mathematical and logical operations we learned in schools and in universities. For instance, a simple inference rule could be a comparison of the type A > B. If we have a set of different numbers and apply this inference rule we end up with an ordered set of increasing/decreasing numbers. Using these inference rules we can perform any qualitative and quantitative analysis. Although it might be obvious, we have to stress the fact that not everybody has the same set of inference rules. For instance, some people do not know what an exponential function is, or what is the difference between addition and integration. For them, it would be very difficult to understand more complex phenomena like nuclear fission and fusion, or even a water steam explosion. The more complex these inference rules are, the more powerful the thinking pattern is. There are many inference rules which we constructed ourselves based on our direct experience of life. These rules reflect tacit knowledge and due to this fact they are difficult sometimes to be explained. For instance, when a little child touch by any chance a flame with his fingers, it hurts and next time he will avoid touching a flame again. This is an inference rule he obtained by a direct experience, without any explanation given by his parents. Successful people build their own inference rules and took good decision which saved their lives and contributed to their achievements. In the same time, many other people failed because they used their old thinking models for the new and hostile environment. There are also inference rules established by legislation, for a given social behaviour. These rules contribute to implement and sustain a certain social order and they are specific to each country. To illustrate this point we may consider, for instance, the traffic regulations for driving automobiles on public roads and highways in a given country. A driver is supposed to learn and to obey to these traffic rules, without questioning their consistency or any logic. For instance, in countries like Great Britain and Japan drivers use the left side of the road, while in countries like France and Germany drivers use the right side of the road.

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2.3 Knowledge basis The third functional structure of a thinking model is the knowledge basis. It contains all the data, information and knowledge one person may have at a certain moment of his life. This is the most dynamic functional structure since it can absorb always new information and knowledge if there is a certain motivation. The more data, information and knowledge one may have the more powerful his thinking model is. However, knowledge is a fuzzy concept because during its long history it has been defined and used by specialists coming from different scientific fields, who defined the concept from their own perspective. Also, the concept is context dependent, which means to adapt its meanings to a given social, economical, political, cultural and scientific environment. Due to this cultural and scientific dependence, Nonaka and Takeuchi (1995) identified two streams of semantic evolution: the Cartesian dualism of body and mind, and the Japanese oneness of the body and mind. The kernel of Descartes’ theory of knowledge is represented by the famous expression: Cogito, ero sum. It makes mind more certain than matter, and my mind (for me) more certain than the minds of others. The conclusion is that my existence is derived from the fact that I think (Russel 1972). Thus, the Cartesian doubt contributed in a definite way to this general perspective that mind and body are and operates as two distinct entities, and only the mind is responsible for knowledge generation and knowledge processing. In this context, knowledge of external things must be by the mind, not by the senses. In the Japanese tradition, there is a strong emphasis on the oneness of body and mind. They are integrated into one entity and knowledge can be acquired through direct experience of the body. According to this tradition samurai had to develop their wisdom through physical education. Physical exercises contributed not only to the building and strengthening samurai bodies but also to the formation of their character, which included a certain way of thinking (Kaufman 1994). Polanyi (1983) defined the knowledge obtained through a direct experience of life as tacit knowledge. The other type is defined as being explicit knowledge. The oneness conception about our thinking and understanding life consider that knowledge should be the outcome of the fusion process between tacit knowledge and explicit knowledge (Allee, 1997; Baumard, 2001; Davenport and Prusak, 2000; Nonaka and Takeuchi, 1995; Polanyi, 1983). Think about people living in equatorial zones where there is never snow. They heard, read and may be viewed in movies snow. Thus, they have the explicit part of the concept of snow. Yet, they have never had the chance to touch, to smell or taste snow. Thus, their understanding about snow is incomplete and their concept about snow is somehow different than that of people living in countries where wintertime brings in snow. In this perspective, the tacit knowledge is very powerful. 3. Time dimension 3.1 Inertial thinking The simplest cognitive model is given by the inertial thinking. Its main characteristic is that time is not a fundamental variable of this model. Thinking process in an inertial mode is timeless. That means that events and phenomena remain unchanged in time, like physical objects in their inertial states. Let us consider the following example. When we come late evening at home and the light is off, we know where the light on/off button is and we switch it on. How do we know? We use an inertial thinking and as a result we consider that all things remained unchanged into their positions since we left the house early in the morning. Thus, inertial thinking gives us a sense of stability and safety. We do not worry about what happens in our absence since objects are motionless. However, any event development in life or any phenomenon in nature involves change, and change can occur only in time. There is no possible change in a static environment. As a result of this situation, an inertial thinking model cannot accept change and it cannot explain change. People who are dominated by inertial thinking will be afraid of any change and they will oppose it anytime. This is one of the main reasons why the adaptation of social, economical and political life in the European former socialist countries is such a slowly process. 3.2 Dynamic thinking The dynamic thinking pattern does incorporate time as a fundamental variable. All events and processes develop in time since they generate change. Time becomes a measurable dimension of them. Time can be characterized by a direction of evolution or not. When a process can develop from an initial state to a final state and then can develop in the reverse direction going through all same intermediate equilibrium states until it reaches the initial state, it is a reversible process. Otherwise, it is an irreversible process. All processes we know in life, society and nature are irreversible processes. Biologically, we grow and get older and never we can reverse our life into childhood. Even from ancient times philosophers observed that one cannot swim in the same water in a given river since

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change generates irreversibility. In this perspective, reversibility is a theoretical approach used in Thermodynamics for ideal processes, in order to simplify mathematical solutions. We are living in a highly nonequilibrium mode and strongly irreversible world. Time means more then just intervals elapsed between different moments or stages of some considered processes. Time has direction, from past toward present and from present toward future. We may say that real processes have orientation or direction in time. Irreversibility can be measure by using entropy, a concept introduced first in Thermodynamics and then generalized in many other fields of science and engineering (Handscombe and Patterson 2004). Actually, the entropy measures the degree of irreversibility for a given process and not its absolute irreversibility. Since irreversibility generates a kind of history of developing different processes, scientists say that entropy is a kind of time arrow. It shows the direction of future development. Since real processes are irreversible and they develop in highly nonequilibrium environments, we have to develop thinking patterns able to make us understand these real processes. These models contain an oriented and measurable time axis, fact for which we may call them entropic thinking models. 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 the best solutions. Also, dynamic patterns help us to establish targets and to elaborate strategies for future achievements (Dess et al 2006). We would like to emphasize the fact that although this above analysis may seem obvious, it is not. School education contributed very little in developing our understanding for a strongly dynamic and entropic world, and for developing necessary abilities for future oriented thinking and decisions making. 4. Complexity dimension 4.1 Linear thinking Linear thinking patterns are used to approximate complexity of our environment. It is like we use frequently linear segments to approximate curves of different shapes. Basically, linear thinking assumes that for a given transformation process, the output variables are proportional to the input variables. Thus, if we know the input variables and the process constants we just multiply them and get the outputs variables. It is such an easy thinking model that most of our everyday life is based on it. Eventually, we may believe that it is the only way of thinking. All measurements systems are developed according to linear thinking. Let us consider measuring temperature of a heated water. The thermometer we use, regardless of its units given in degrees Celsius or Fahrenheit, has a scale based on a linear equation. Purchasing goods by measuring their mass it is also a linear process. However, if purchasing is based on negotiations, then it is not anymore a linear process. In research, we use frequently linear models especially to express physical material properties and their behavior under different fields of mechanical, thermal or electromagnetic forces. There are many other fields of 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 their 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. Due to this fact, in linear models it is functioning the principle of superposition we learned in high school. This principle is frequently used also in research, when we decompose a complex problem into several smaller problems and find first their solutions. Then, we just aggregate these simple solutions to obtain the solution of the initial complex problem. This approach works well as long as the real problem expresses some linear phenomena. Otherwise, this approach is misleading. 4.2 Nonlinear thinking Biological and psychological phenomena, as well as many social and natural processes are nonlinear. When their departure from linear mode is significantly large we must use a nonlinear thinking. That means to use correlations between output variables and input variables which have nonlinear mathematical 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 and he will try to evaluate them by using simple linear models. Intellectual, emotional and creative processes are highly nonlinear (Gardner 2006, Goleman 1995). It is a mistake to evaluate them based on linear models. Yet, we may recall that about 20-30 years ago, when programming was a job in itself, programmers were paid proportional to the number of program lines they wrote. Thus, a highly nonlinear activity has

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been evaluated by using a linear thinking model. As a consequence of this mistake, programmers were interested to increase artificially the number of lines, in order to show how much they worked. Eventually, they produced programs with huge number of lines which increased the computational time and thus, increased their inefficiency. 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 the only possible approach. In the same time managers must develop new metrics for progress evaluation and for excellence stimulation. Linear metrics proved to be not suitable for these new phenomena. Quality management based especially on the continuous improvement concept, known in many fields of activity as the Deming cycle, can be developed and applied only as a nonlinear process. Knowledge engineering and management are also highly nonlinear processes. Knowledge, unlike physical quantities cannot be increased by addition or superposition effects. Education in Science and Engineering is concentrated mostly on information and explicit knowledge transfer from professors to students. However, good scientists and engineers should have also developed certain skills and capabilities which are highly nonlinear. They must be able to integrate the explicit knowledge they get from professors and from books with their own tacit knowledge and with the experience they can get converted or transferred from their professors. Thus, transferring such kind of skills and experience from one generation to another generation requires nonlinear thinking models and nonlinear educational approaches. 5. Nature of events and phenomena 5.1 Deterministic thinking The deterministic thinking model is based on idea that things and events must be well defined and determined before they happen. Actually, they happen due to our way of determining them. Their occurrence is certain. That means that their probability of 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 of activities to take place. One of the best examples of deterministic thinking is the time schedule for trains and for airplanes. Without such a time schedule no coordination of their circulation or flight can be done. Another deterministic thinking model is the daily working program of a given company, or the time schedule for students and professors. Deterministic thinking is necessary in organizing the traffic on public roads and highways. We have already referred to this aspect when we talked about basic values of a thinking model. However, the rules established for car driving by legislation is a clear model of a deterministic thinking. And we have to emphasize the fact that we need such kind of thinking at social level. Otherwise, how would proceed drivers if traffic rules would have been formulated in a different thinking model. For instance, how it would be if the rules would say that in Great Britain driving on public roads is on the left side with a probability of 50%? Actually, legislation promotes deterministic thinking, as well as some unwritten rules which come from history and try to introduce order in social behavior. We learn all of these rules in schools or later in our life and do our best to respect them. The question is how much of 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 the well established order. Deterministic thinking has been used extensively by scientists and engineers. Most of all the Science laws we studied in schools and universities are actually a product of a deterministic thinking. 5.2 Probabilistic thinking In nature, society and life events do not have certain outcomes. Events occurrence has a probabilistic nature and they may happen with some probabilities (Taleb 2004). One of the most known example is the weather forecast. We learn from TV programs or from newspapers how the weather will probably be next days, but nobody can assure us that the forecast is going to be 100% accurate. To understand and to use properly such a weather forecast we must develop a probabilistic thinking. That means to accept the fact that some events or some outcomes may happen with some probabilities, which actually means to accept the uncertainty related to their occurrence. However, any uncertainty has an associated risk we must understand and in the 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 of thinking model we will be better prepared for a future which is by its own nature unknown and uncertain. For any company or nonprofit organization the 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

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decisions concerning future developments of our activities we must be able to deal with probabilistic events and with their associated risks. That means to develop our ability to identify potential risks, to evaluate their magnitude and to conceive measures to reduce possible negative consequences. Let us think of some natural disasters as earthquakes, tornados, typhoons etc. Their occurrence is highly uncertain, but if we understand their nature and their impact on our houses, cities, transportation systems, bridges and living conditions we can be able to develop some technological systems or managerial programs such that we may reduce their destruction force. One may asks how it is possible to develop such kind of probabilistic thinking models in schools or universities. It is not so easy and it is requiring a nonconventional approach from professors and authors of textbooks. For instance, if in a Physics book a student finds some problems to be solved by simply using given formulas, then his mind will be trained for a deterministic thinking. Now, let us consider same problems but with incomplete data and with several possible answers. In such a situation students must input by themselves some necessary data based on their own learning experience and then solve these problems for different outcomes. Also, they have to provide interpretations for each solution and to judge their accuracy. Such kind of education is much more difficult to be done, but finally students will be able to develop their own thinking and in a probabilistic way. 6. Conclusions In a basic framework defined by time, complexity and nature of events we can define some thinking patterns which play an important role in generating individual and organizational intellectual capital. The thinking patterns are developed throughout our education experience and they define actually the power of the decision making process. These thinking patterns are: inertial and dynamic thinking (time dimension), linear and nonlinear thinking (complexity dimension), deterministic and probabilistic thinking (nature of events dimension). We define, describe and show how these thinking patterns influence the way we understand the real world, and the way we can improve our decision making capacity by developing more powerful models. References Albrecht, K. (2003) The power of minds at work. Organizational intelligence in action, AMACOM, New York. Allee, V. (1997) The knowledge evolution. Expanding organizational intelligence, ButterworthHeinemann, Boston. Andriessen, D. (2004) Making sense of intellectual capital. Designing a method for the valuation of intangibles, Elsevier, Amsterdam. Andriessen, D. and Tissen, R. (2000) Weightless wealth. Find your real value in a future of intangibles assets, Prentice Hall, London. nd Argyris, C. (1999) On organizational learning, 2 edition, Blackwell Business, Oxford. Baumard, P. (2001) Tacit knowledge in organizations, SAGE Publications, London. Bratianu, C., Jianu, I. and Vasilache, S. (2006) “Integrators for organizational intellectual capital”, Paper read at the IC Congress, May 3-4, Inholland University, Amsterdam. Davenport, T.H. and Prusak, L. (2000) Working knowledge. How organizations manage what they know, Harvard Business School Press, Boston. nd Dess, G.G., Lumpkin, G.T. and Eisner, A.B. (2006) Strategic management. Text and cases, 2 edition, Mcgraw Hill Irving, Boston. Gardner, H. (2006) Multiple intelligences. New horizons, Basic Books, New York. Goleman, D. (1995) Emotional intelligences, Bantam Books, New York. Handscombe, R.D. and Patterson, E.A. (2004) The entropy vector, World Scientific, London. Kaufman, S.F. (1994) The martial artist’s book of five rings. The definitive interpretation of Miyamoto Mushashi’s classic book of strategy, Tuttle Publishing, Boston. Keeney, R.L. (1992) Value-focused thinking, Harvard University Press, Cambridge. March, J. (2003) The pursuit of organizational intelligence, Blackwell Business, Oxford. Nonaka, I. and Takeuchi, H. (1995) The knowledge creating company. How Japanese companies create the dynamics of innovation, Oxford University Press, Oxford. Polanyi, M. (1983) The tacit dimension, Peter Smith, Gloucester. Russel, B. (1972) A history of western philosophy, Simon and Schuster, New York. Senge, P. (1990) The fifth discipline. The art & practice of the learning organizations, Random House, London. Sherwood, D. (2002) Seeing the forest for the trees. A manager’s guide to applying systems thinking, Nicholas Brealey Publishing, London.

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Stewart, T.A. (1999) Intellectual capital. The new wealth of organizations, Nicholas Brealey Publisher, London. nd Taleb, N.N. (2004) Fooled by randomness. The hidden role of chance in life and in the markets, 2 edition, Penguin Books, London.

CHALLENGES FACED BY THE ROMANIAN COMPANIES IN IMPLEMENTING KNOWLEDGE MANAGEMENT Constantin Bratianu, Ionela Jianu Academy of Economic Studies, Bucharest

Abstract: In the new economy, knowledge represents the most important source of wealth. The way companies succeed in managing it has a significant impact on their future. Those which disregard the importance of knowledge as the main driver of future performance will have a difficult time competing with other companies or even surviving in a rapidly changing business environment. The new rules in the knowledge based economy need new approaches in businesses. Most companies in Romania need to make some changes in order to effectively manage knowledge. The purpose of this paper is to present a critical analysis of the main challenges faced by the Romanian companies in implementing the knowledge management. We shall take into consideration the following aspects: leadership, strategic thinking, innovation, human resources and the organizational culture. Keywords: knowledge, knowledge management

1. INTRODUCTION In the landscape of modern business, knowledge represents the most important source of wealth, while the importance of the classical factors of production is diminishing continuously. In this perspective, the capability of a company to manage its intangible assets is by far more important in its success than the management of tangible assets (Dess, Lumpkin and Eisner, 2006; Gamble and Blackwell, 2001). This is not a simple endeavor, but the companies which disregard the importance of knowledge as the main driver of performance will have a difficult time competing in a dynamic global environment or even surviving. The challenges to be faced in implementing knowledge management are many, but companies need to cope with them if they want to succeed in a business environment where the consumers’ preferences are changing much more rapidly than in the past and existing knowledge becomes obsolete after shorter life cycles. For Romania, the challenges are even bigger, since our economy is still based on the extensive utilization of the classical factors of production and our economic thinking models reflect this reality ( Gheorghiu, Pislaru and Turlea, 2004). In the perspective of joining the European Union, one of the most important challenges for the Romanian companies is changing the production system towards one based significantly on knowledge and innovation. Effective knowledge management can help companies in this direction (Kermally, 2002). In this paper, we shall analyze the main challenges faced by Romanian companies in implementing knowledge management, taking into consideration the following aspects: leadership, strategic thinking, innovation, human resources and the organizational culture. 2. LEADERSHIP Leadership refers to the ability of a person to motivate and direct the others towards the organizational goals. It is a key ingredient in any management initiative, especially in a challenging one like managing knowledge. Knowledge has always been important throughout history (Stewart, 1997). But in today’s dynamic business environment, knowledge is more important than ever. Moreover, there is a need for a systematic and well-planned approach to knowledge. Kermally argues

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that managing knowledge is about creating an environment within an organization that facilitates the creation, transfer and sharing of knowledge, this being one of the key attributes of effective leadership (Kermally, 2002). An effective leader should be a model for its employees, as demonstrated by many research studies. Robert Buckman, CEO at Buckman Laboratories, a chemical company based in Memphis, USA, but having business in more than eighty nations, argues that in every company, people are “boss-watchers”. If the managers make clear that they value sharing corporate knowledge and are models in this respect (sharing themselves knowledge with employees), knowledge will be shared. Also, if they promote the people who do the best job about sharing knowledge, there is no need for any other incentives (Stewart, 1997). However, there is a danger of sharing information and knowledge for the sake of it, in order to obtain some kind of advantages and not necessarily to stimulate the organizational knowledge creation process. In the case of Romania, and probably of the other former socialist countries, sharing knowledge has been not a common practice. Knowledge means power and many of the former leaders were afraid of loosing their positions and advantages if they would share with all the others their knowledge. Thus, their leadership model was based on secrecy, as much as possible. In exchange, they shared all kinds of irrelevant information and were trying to put people’s attention on wrong tracks by telling jokes and funny stories. Management communication has been based mostly on a top-down flow of orders and indications. The bottom-up flux of information has been always of the reporting type. The free flow of information was based mostly on gossip and trifles. Unfortunately, much of this situation continued for many years. Even now, it is hard to talk about a new communication style. Thus, we need a new leadership vision able to change this mentality and to open the flow of information and knowledge to all the employees. The leadership challenge is to promote a new perspective based on trust and interest of sharing personal and organizational knowledge. It is necessary to encourage through different methods the knowledge processes of socialization, externalization, internalization and combination through which tacit and explicit knowledge can flow among people in a company (Nonaka and Takeuchi, 1995; Bratianu, 2006). 3. STRATEGIC THINKING When we speak about knowledge management and strategy, a distinction between the companies that operate in the knowledge business (consulting firms, law firms, software developers etc) and companies in other business sectors might be helpful to make things clearer. For the companies in the first category the relationship between strategy and knowledge is obvious. What about the companies in the other category? Davenport and Prusak argue that those companies need a business strategy supported by knowledge, rather than a knowledge management strategy (Davenport and Prusak, 2000). Their arguments come from the logic of consistency, since there is no way to develop a solid knowledge management in a company structured and managed according to industrial era principles. Unfortunately, in Romania most of the companies are based on industrial era management. Thus, the first priority in this direction is to change the classical industrial management based on short term thinking into a strategic management, based on strategic thinking. Companies must have a vision and a mission and they have to search for the future using new thinking models. Thus, the management based on linear and deterministic thinking should be changed on the management based on nonlinear and random thinking models. That means to decrease the excessive control practiced in the Romanian companies, and to increase the planning function. Strategic thinking is based on dynamic, nonlinear, random, intelligent and creative thinking models (Bratianu and Murakawa, 2004). The biggest challenge for the Romanian companies is to change their approach to long term planning, taking into consideration the more and more dynamic business environment. Moreover, they need to define clear objectives for their companies and to find the best ways to use knowledge to their long term advantage (Dess, Lumpkin and Eisner, 2006). The new economy requires new approaches. The guiding principles that worked so far might not be appropriate for an economy where the most important resource is represented by knowledge. Therefore, new strategic challenges are facing all the companies. The new economy might lead to behaviors that a few decades ago could have been considered strange. There are companies that are collaborating with their competitors, this being referred to as “coopetition”. This term was coined by Ray Noorda, founder of the networking software company Novell. Branderburger and Nalebuff show that this concept represents a new mindset and that “Business is cooperation when it comes to creating a pie and competition when it comes to dividing it up” (Branderburger and Nalebuff, 1997).

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In the perspective of Romania joining the European Union, the competition will be even fiercer than in the present. And Romanian companies need to consider this strategic option as well. That means, they must develop their competitive capability and in the same time to be strong enough to open their options to international cooperation. Developing a real competitive capability is indeed a forthcoming challenge, since our companies have been used to produce in a quasi static and noncompetitive environment. 4. INNOVATION The capability of any company for continuous innovation is the key to sustainable competitive advantage. Innovation does not refer only to new products, services or processes, but also to new ways of looking at things, and it is strongly linked with knowledge management: “Knowledge and innovation are a two-way process – knowledge is a source of innovation and innovation in turn becomes the source of new knowledge” (Kermally, 2002, p.130). In fact, the Japanese authors Nonaka and Takeuchi (1995) argue that the essence of innovation is about re-creating the world according to a particular ideal or vision. In order to do that it is necessary to have an adequate mindset at the individual level, and a stimulating organizational culture at the company level. Innovation cannot be obtained in a pressurized organizational culture due to a dictatorial management. The Romanian companies developed through the last half of this past century an organizational culture based on negative motivation and on inhibiting any innovation attitude. Although the new market economy generated some changes in the business environment, changing the organizational culture is a very slow process. Thus, we consider that one of the most important challenge for the Romanian companies is to understand the essential role played by the innovation in developing a real competitiveness capability for the new business environment. In the same time, it is important to identify all the organizational resistances, and to develop strategies to overcome them. Creating a new mentality able to encourage ideas generation and performance rewarding constitutes a real challenge for all Romanian companies. Innovation is one of the most important forces in obtaining a strategic advantage in a strong competitive market, and we have to learn this new reality (Dess, Lumpkin and Eisner, 2006). 5. HUMAN RESOURCES Human resources (HR) might be a misleading term. HR were important in the industrial era management, and HR are very important in the knowledge management environment. Apparently, nothing changed. However, HR changed completely the stress put on working potential. HR mean actually three major fields of interests for the working potential: physical work, emotional intelligence and rational intelligence. Physical work played its most important role during industrial era, when Fr. Taylor made his first research concerning scientific management: “…the greatest prosperity can exist only as the result of the greatest possible productivity of the men and machines of the establishment – that is, when each man and each machine are turning out the largest possible output” (Taylor, 1998, p.2). After more than 100 years, “the largest possible output” changed from tangible objects into intangible things. In the same time, the concept of productivity changed significantly: “Productivity of the knowledge worker is not – at least not primarily – a matter of the quantity of output. Quality is at least as important” (Drucker, 1999, p.142). It would be a wrong approach to evaluate the productivity of a university professor based on how many students he passes or fails in his class. The quality of knowledge transferred to his students becomes the new target for evaluation. In these new conditions of increasing the importance of the knowledge work, the Romanian companies face the real challenge of changing completely the meaning of the HR management, and the concept of productivity. The physical work field should be replaced more and more with the rational intelligence and knowledge production, and the emotional intelligence should be used for motivating people. 6. ORGANIZATIONAL CULTURE The organizational culture is a part of the intellectual capital of any company (to be more precise it is part of the structural capital of a company). The culture refers to the set of values, norms, standards for behavior, and shared expectations that develop within a certain organization in time. The longer the history of the company, the stronger is the organizational culture. It influences the way

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in which individuals, groups and teams interact with each other and cooperate to achieve organizational goals. As we previously mentioned, effective knowledge management is supported by an organizational culture that will facilitate the sharing and creation of knowledge. Do Romanian companies have such cultures? Probably a positive answer cannot be done, except for very few companies. The creation of such cultures will be a very difficult task, since in many Romanian companies the level of bureaucracy is very high. Although a lot of companies sustain the idea of a participative management, sometimes the management of Romanian companies is strongly dominated by control, sometimes excessive and inadequately applied. Moreover, organizational learning, that is very important in a knowledge based company, requires a culture based on free communication, team spirit and trust. We were speaking earlier about the importance of a creative organizational environment based on trust and that should stimulate the creative flow of knowledge. Creativity means initiative, crossing of boundaries, taking risks and accepting mistakes as stepping stones to move forward. In a blame culture that unfortunately characterizes many of the Romanian companies, creativity is just blocked. The challenge is therefore to change completely such an organizational culture into a stimulating and rewarding one. It is a very slow and rather difficult process but it should be done if the companies should survive in the coming future. 7. CONCLUSIONS Although the field of knowledge management is relatively new to most Romanian companies, they can no longer ignore it. The capability of a company to manage its intangible assets are by far more important in their success than the investment in tangible assets and performing classical operational management of these tangible assets. The new rules in the new economy might require some changes in the way a business operates. Unless they know the challenges they have to face and find solutions to deal with such challenges, most companies will have a difficult time competing or even surviving in a dynamic business environment. Although the field of knowledge management is relatively new to most Romanian companies, they can no longer ignore it. The capability of a company to manage its intangible assets are by far more important in their success than the investment in tangible assets and performing classical operational management of these tangible assets. The new rules in the new economy might require some changes in the way a business operates. Unless they know the challenges they have to face and find solutions to deal with such challenges, most companies will have a difficult time competing or even surviving in a dynamic business environment. Although the field of knowledge management is relatively new to most Romanian companies, they can no longer ignore it. The capability of a company to manage its intangible assets are by far more important in their success than the investment in tangible assets and performing classical operational management of these tangible assets. The new rules in the new economy might require some changes in the way a business operates. Unless they know the challenges they have to face and find solutions to deal with such challenges, most companies will have a difficult time competing or even surviving in a dynamic business environment. REFERENCES Brandenburger A., Nalebuff H., Co-opetition, Currency Doubleday, New York,1997. th Bratianu, C., “Knowledge Dynamics in Organizations”, in: The Proceedings of the 6 biennal International Economic Symposium SIMPEC2006, Vol.1, pp.51-57, Infomarket, Brasov, 2006. Bratianu, C., “Knowledge Welding”, in: Welding and Joining Technologies for a sustainable development and environment, Proceedings, pp.5-15, International Institute of Welding, Timisoara, 2006. Bratianu, C., Murakawa, H., Strategic thinking, Transactions of JWRI, Vol.33, No.1, pp.79-89, Osaka University, Osaka, 2004. Davenport, T., Prusak, L, Working Knowledge- How Organizations Manage What They Know, Harvard Business School Press, Boston, 2000. nd Dess, G.G., Lumpkin, G.T., Eisner, A.B., Strategic Management, 2 Edition, McGraw-Hill Irwin, Boston, 2006. st Drucker, P., Management challenges for the 21 century, Harper Business, New York, 1999. Gamble, P.R., Blackwell, J., Knowledge Management. A State of the Art Guide, Kogan Page, London, 2001.

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Gheorghiu R., Pîslaru D., Ţurlea G., Competitivitatea pe bază de inovare a economiei româneşti în contextul Strategiei de la Lisabona, Open Society Institute, Budapest. http://www.cerope.ro/pub/study53ro.htm, 2004. Jones G., George J., Contemporary Management, Third Edition, McGraw-Hill Irwin, New York, 2003. Kermally S., Effective Knowledge Management, John Wiley & Sons, West Sussex, 2002. Lungescu C. D., The Organizational Behavior and the Management of the Romanian Economy's Reorganization, PhD Dissertation, Babes Bolyai University, Cluj, 2005 (in Romanian). Nonaka, I., Takeuchi, H., The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford University Press, New York, 1995. Roos J., Roos G., Edvinsson L., Dragonetti N., Intellectual Capital: Navigating in the New Business Landscape, MacMillan, London 1997. Stewart, T., Intellectual Capital- The New Wealth of Organizations, Nicholas Brealey Publishing House, London, 1999. Taylor, Fr., The principles of scientific management, Dover publications, Inc., New York, 1998.

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