Keleti Faculty of Business and Management

We have never seen creativity. More precisely, we have never seen the creative process; what we have seen is the creative individual (ex ante) and the outcome of creativity (ex post). Therefore we try to understand creativity by examining creative individuals and their creations. In this paper we only consider the creation of new knowledge. We draw on a wide variety of backgrounds. We wander into the area of cognitive psychology to investigate who is talented for creativity. We also draw on arts, history and philosophy of science, stories of mystics, some great novels and essays we have read as well as our experience in both working with creatives and creating new knowledge. Based on this shaky foundation we will describe creativity as illumination, through jokes, as a quest for harmony, as being kissed by the muse.

It is the fourth time that we create a new management school. Every time it was different and every time we have learned a lot from the process of curriculum design in harmony with the voice of the times. In this paper we outline the process of curriculum design through our latest experience in creating the Strategic Partner School in Hungary. Although there are important characteristics of the Middle-East European market for post-experiential business education taken into consideration, the meta-level of the process, i.e. how to identify the relevant characteristics, can be applicable well beyond the area in which this study originated. Naturally, our way is not the only right way of curriculum design but our aim with this study is to stimulate thinking and discussion rather than selling a recipe.

Osnovni problem poslovnog rizika se najčešće sužava na ocjenu rizika. U gorem slučaju na pokušaj mjerenja rizika. Smatramo da je mjerenje nemoguće, a ocjena je jednostavna, što i ilustriramo jednim primjerom poslovne banke. U tom primjeru, pomoću DoctuS sistema baziranog na znanju, koristimo 600 logičkih pravila za ocjenu rizika davanja kredita. Rješenje upravljanja rizikom nije u izboru kriterija i njihovom mjerenju, već u "ako...onda" logičkim pravilima. To je jednostavno i korisno rješenje, no u radu ipak diskutiramo doprinos ocjene upravljanju.

The fundamental problem of business risk is usually reduced to risk evaluation; in a worst case to an attempt to measuring risk. We consider that measurement is impossible and evaluation is simple. To illustrate this, we present a case of business banking; in this case we use 600 logical rules to evaluate the loan risk regarding particular applicants. The solution of risk management is not in the criteria selection and their measurement but in the “if... then” logical rules. This is a simple and very useful solution but in paper we discuss the contribution of risk evaluation to risk management.

Skype innovated the communication and was acquired by eBay for nearly $4 billion altogether. They did something good and now they also do well. There are companies which reject any kinds of change but also seem to be doing well. How are both possible? In this paper we attempt to answer this question by establishing an evolutionary framework to examine organizations and particularly their approach to creativity and innovation. We re-examine the Neo-Darwinian school of evolution and formulate some objections while accepting some ideas, mostly from the Neo rather than from the Darwinian part; thus establishing our own evolutionary framework. Within this framework we discuss the evolution of ideas and the knowledge increase to understand the educational background of new generation decision takers. We also review the changes of the organizational strategy in the e-age; to get a picture of the organizational context of creativity and innovation we discuss the role of the dynamic and static quality in e-age organizations. Pulling all these together we describe four fitness categories of innovation; we use animal names as metaphors of the categories: the first swallows, the parrots that repeat, the bear awaking form the winter-long hibernation, and the frog that enjoys itself in the changeless swamp. One fitness is not better than another, only your fitness and your habitat (fitness landscape) must be in harmony. That we need for survival.

The e-era is obsolete. It is time for a step forward, to the f-era. In this new era the Kuhnian conception of paradigm should be replaced by the new f-paradigm; the e-knowledge-sharing should be replaced by f-knowledge-sharing . In all these «f» stands for «free». In many languages the need for knowledge is expressed by the words of thirst or hunger. This gave us the idea to use metaphors of restaurants to the different types of f-knowledge-sharing; we distinguish four types: the ‘buffet’-type, the ‘à la carte’-type, the ‘recommended by the chef’-type, and the ‘coffee-room’-type knowledge sharing.

Today one of the most challenging problems of an organization is how to make the decision taking faster in order to improve efficiency. Excellence resides in the differences of people’s tacit knowledge. In Knowledge Management excellence can be achieved if the leader delegates the Routine Decisions to others, while the Original Decisions are taken on basis of tacit knowledge. With Expert System Shell DoctuS, we can reduce the expressed rules to those meta-schemata that actually affect the decision. These meta-schemata are derived from a blend of explicit and tacit knowledge. The process of reducing the number rules we call reduction, which is the third kind of reasoning beside deduction and induction. The achievement is that we can get the same decision using the values of fewer attributes. According to our experience the benefits include knowledge discovery in every application (i.e. a part of tacit knowledge is made explicit) and the process of decision taking becomes faster and its cost is reduced.

In this paper we present two related results. The first is a model of personal knowledge which is based on the number of dots the person can see, and thus the dimensions of knowledge. E.g. one dot indicates dimensionless knowledge, two dots indicate one-dimensional knowledge, then the three dots for two-dimensional knowledge, and the highest knowledge level is the three-dimensional knowledge indicated by four dots. Based on qualitative examination of this model we determine which part of deliverable knowledge is appropriate for e-learning at the different knowledge levels of the teacher. The second result builds on this one; it is architecture of three dimensional knowledges in the discipline of leadership, particularly it covers the part appropriate for e-learning. To present this second result we use our next generation knowledge visualization tool, Knowledge Galaxy 1 .

Making an attempt to develop a curriculum for web-based learning, we have realized that the existing solutions have adopted the traditional content management principles of printed books. By doing so, these solutions do not make use of benefits of a web-based system, namely the multimedia and the interactivity. Our new solution puts these benefits into the focus. Combining the features of semantic networks, cognitive maps and machine learning, we have developed a new generation knowledge visualization tool called Doctus Knowledge Galaxy shell. In our solution the topics and keywords are not in a sequential order, thus enabling the e-learner to choose her/his own learning route. The monitoring system of Doctus Knowledge Galaxy also allow us to observe how much time the learner spends on particular keywords and which next keyword she/he chooses after concluding a previous one by passing the test. The most important achievement of Doctus Knowledge Galaxy is its clear and transparent structure, which enables the learners into fast navigation and provides the developers with useful information about the learning routes and performance of the learner.

In this paper we take the idea of e-learning a step further, from "e" to "f", in d icatin g th at th e p o st-e-learning is on the doorstep. T h e "f" stan d s fo r freed o m fo cu sin g on th e freed o m o f th e f-learner. As we will show, the demand for the freedom of the f-learner imposes certain boundaries to the freedom of the f-teacherthis is what we propose to handle by adopting the f-learning scenarios. For this quest we have developed a systems-description of the increase of personal knowledge, we analyze the interaction of the individual and organizational value systems, and we examine the possibilities of standardization of the user interfaces to finally be able to offer scenarios for f -learning. More precisely, we do not offer instant scenarios applicable in any situation but a conception of how scenarios can be developed, what they should contain and what should be taken into consideration during the development. The outcome of this research also indicates some new problems regarding the roles identified in f-learning.

The members of e-community are qualified on the partner basis (from whom he/she knows and where he/she passes the found knowledge). The knowledge is divided, not on the basis of organizational forms and standards. The organizational knowledge maps are mostly false inventories, as the stock -taking is possible only within the frameworks of other culture reliance. The Intelligent Portal contains artificial intelligence. First we use Doctus KBS shell to create knowledge-bases for particular decisions. Hard data are retrieved from databases and soft information from knowledge-bases. If we understand the matter of the web then we can use the interactivity to comprehend the new knowledge on the basis of Linux (free software) development conception. The easiest way to understand is to distinguish free pub-talk from free beer. Corporate University does not give away knowledge free, but we can freely talk about it or even modify it. This idea is based on following: everybody is free to access the knowledge shaped on the desk, to customize it, to spread either the customized or the desk-shaped knowledge. In the knowledge factory we realize the cooperation among experts on internet. Knowledge factory is more than a useful blend of newsgroup and forum.

In many languages the need for knowledge is expressed using the words for thirst or hunger. This gave us the idea to use metaphors of restaurants to describe the different ways of knowledge sharing; we distinguish four types: the 'buffet'-type, the 'à la carte'-type, the 'recommended by the chef'-type, and the 'coffee-room'-type knowledge sharing. To introduce the for restaurants we draw on some knowledge typologies from the literature and we added some new types as well. This paper focuses on the "à-la-carte-knowledge-sharing", where the waiter is the knowledge broker. The environment of the four restaurants for knowledge sharing is the business environment today; here we suggest to take a step further to the next letter after «e» and to start to speak of f-knowledge-sharing ; where the «f» stands for «free».

It is impossible to create model of decision process, as we know nothing about the original decision process. Although it is possible to build models that can get us to the spaces where our fitness is strong enough. These models can contain hard data and soft information as well.

Concept maps and expert systems are both in the soft toolbar of knowledge modelling. We have spent nearly two decades developing our expert system shell "Doctus". Several years ago we have seen the first concept mapping solutions and started using them very soon. Frequently we have found ourselves using both tools in a particular research or consultancy project and started to wander how the two could be combined to achieve synergies. We came up with several ideas, typically when we have faced a situation which called for one of the potential synergies. In this paper we present the first of these ideas in elaborated form of a conceptual model and we also mention few additional ideas as our plans for future research. In this first idea we combine different kinds of concept maps and our expert system in order to map organisational knowledge. The expert system here is used in machine learning mode, i.e. the resulting concept map will be capable of learning -this is our intelligent concept map.

We know for a long time that expert system (ES) must not know in a different way than how man knows. We would not expect men to adapt their thinking processes to the machine, would we? Evolution would not let peoples' minds adopt criteria weighting or fuzzy logic. This is why we developed our Doctus 1 knowledge-based expert system based on symbolic logicthat is the easiest to understand artificial knowledge representation to the decision taker. However, this is all history now... Now we perhaps understand decision takers bettermaybe it was worth observing them for nearly two decades. Decision takers, and we mean only the most experienced ones, want to be able to play around a bit with a particular decision and, eventually, they want some help in delegating the decisions they are bored with.

Our solution -MABE Methodological Frameworkaims to understand Value-Based Learning Organizations. The e-leaders (decision takers of these organizations) can only communicate using a hazy hierarchy of metaphors as the new ideas cannot be expressed using the old terminology. They and their organizations exist in a business world, in which the functioning is dominated by software; the employees are expected to be skilled searchers. We assume that the decision takers can change their attitude towards the set of expectations and their relations when facing a new solution; thus, they can achieve to get an objectionless solution. This requires a new mode of cognition, which we call the opportunistic browsing. Furthermore, they have to ensure that the decision they have taken is ethically correct, and as there is no single truth they need to adopt pluralistic ethics. The established framework is used to analyze the decisions of the e-leader, who keeps the original decisions to herself/himself and delegates the routine ones, thus achieving increased efficiency and effectiveness resulting in cost reduction and time savings.

Concept maps and expert systems are both in the soft toolbar of knowledge modelling. We have spent nearly two decades developing our expert system shell "Doctus". Several years ago we have seen the first concept mapping solutions and started using them very soon. Frequently we have found ourselves using both tools in a particular research or consultancy project and started to wander how the two could be combined to achieve synergies. We came up with several ideas, typically when we have faced a situation which called for one of the potential synergies. In this paper we present the first of these ideas in elaborated form of a conceptual model and we also mention few additional ideas as our plans for future research. In this first idea we combine different kinds of concept maps and our expert system in order to map organisational knowledge. The expert system here is used in machine learning mode, i.e. the resulting concept map will be capable of learning -this is our intelligent concept map.

Making an attempt to develop a curriculum for web-based learning, we have realized that the existing solutions have adopted the traditional content management principles of printed books. By doing so, these solutions do not make use of benefits of a web-based system, namely the multimedia and the interactivity. Our new solution puts these benefits into the focus. Combining the features of semantic networks, cognitive maps and machine learning, we have developed a new generation knowledge visualization tool called Doctus Knowledge Galaxy shell. In our solution the topics and keywords are not in a sequential order, thus enabling the e-learner to choose her/his own learning route. The monitoring system of Doctus Knowledge Galaxy also allow us to observe how much time the learner spends on particular keywords and which next keyword she/he chooses after concluding a previous one by passing the test. The most important achievement of Doctus Knowledge Galaxy is its clear and transparent structure, which enables the learners into fast navigation and provides the developers with useful information about the learning routes and performance of the learner.

Knowledge has become the most important producer of wealth in society and in organizations. Corporate success in today's economy comes from being able to acquire, codify, and transfer knowledge more effectively and with greater speed. Important aspect of knowledge management is extraction of the personal tacit knowledge and putting it into words and order, so that others can attain it and use it. Big enterprises need concept maps. In places where the knowledge workers are familiar it is a waste of money. Where more than 200 people use knowledge it is very time demanding to find requisite knowledge

The e-era is obsolete. It is time for a step forward, to the f-era. In this new era the Kuhnian conception of paradigm should be replaced by the new f-paradigm; the e-knowledge-sharing 1 should be replaced by f-knowledge-sharing 2 . In all these «f» stands for «free». In many languages the need for knowledge is expressed by the words of thirst or hunger. This gave us the idea to use metaphors of restaurants to the different types of f-knowledge-sharing; we distinguish four types: the "buffet"-type, the "à la carte"-type, the "recommended by the chef"type, and the "coffee-room"-type knowledge sharing.

Making an attempt to develop a curriculum for web-based learning, we have realized that the existing solutions have adopted the traditional content management principles of printed books. By doing so, these solutions do not make use of benefits of a web-based system, namely the multimedia and the interactivity. Our new solution puts these benefits into the focus. Combining the features of semantic networks, cognitive maps and machine learning, we have developed a new generation knowledge visualization tool called Doctus Knowledge Galaxy shell. In our solution the topics and keywords are not in a sequential order, thus enabling the e-learner to choose her/his own learning route. The monitoring system of Doctus Knowledge Galaxy also allow us to observe how much time the learner spends on particular keywords and which next keyword she/he chooses after concluding a previous one by passing the test. The most important achievement of Doctus Knowledge Galaxy is its clear and transparent structure, which enables the learners into fast navigation and provides the developers with useful information about the learning routes and performance of the learner.