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The purpose of this paper is to present a social network approach for identification of micro-organizational re-design interventions to make more efficient and fluid the knowledge flow in a rehabilitation multidisciplinary team. The structural information of different kinds of knowledge networks within a team is augmented with additional analyses aimed at collecting information about the ways through which participants use knowledge, the motivation behind knowledge exchange, and the non-human knowledge sources used by subjects to perform their work. This paperwork was supported by CNCSIS – UEFISCDI, project number PNII – IDEI 810/2008.

The authors propose a definition of knowledge network including human and non-human knowledge source (documents and knowledge repositories) as it is more adequate for the analysis of knowledge flows in multidisciplary medical teams. The mapping and analysis of the network are carried out through: elicitation of knowledge flows between people within and outside the team through a structured questionnaire; mapping of the knowledge flows toward non-human knowledge sources; and identification of critical aspects and proposal of re-engineering interventions to make knowledge flow more efficient and effective.

The analysis of the critical aspects emerged in the field study identifies a number of opportunities to improve the efficiency and effectiveness of knowledge sharing through the re-design of the team network. The re-design interventions concern three main features of knowledge network: “knowledge centralization,” “Over-reliance on External experts,” “Unshared knowledge tools and sources.”

The originality of the work resides in applying social network analysis (SNA) for healthcare management settings, proving evidence and guidelines to show how healthcare organizations can benefit from the adoption of SNA-based approaches.

This paper attempts to identify the strength of the relation between the quality characteristics of companies that are activating in an economy and their performance.

In the quality characteristics sphere were included almost all the elements related to company's behaviour on a market, in an uncertain environment and in the relations developed with stockholders. And what theory can better shape this relation than grey systems theory, a theory of uncertainty and of continual changes? At first, all of these qualitative characteristics that are reflecting company's activity have been divided into six categories for a better reality reflection. A performance indicator was also depicted by taking into consideration each company's managerial objectives.

By applying grey relational analysis (GRA) in a case of eight Romanian firms, the results were convincing: not only that these characteristics determine firm's evolution, but, by knowing them and acting properly on them, firm's extreme situations (such as insolvency or bankruptcy) can be avoided.

The method exposed in the paper can be used for any company for evaluating the linkage between its main characteristics and the way its performance can evolve.

The paper succeeds in identifying the linkage between the characteristics of a company at a certain point and its performance by using one of the newest developed theories: grey systems theory.

The present paper tries to give a new vision on the firm's future evolution forecasting. By taking into account some of the current values of its symptoms and applying one of the most used models in the grey systems theory, namely the GM(1,1), the predictions related to its future symptoms' values can be determined. Having these projected values and the grey economic-financial matrix, K, the future diseases that can hit a company can be depicted along with their causes. The paper aims to discuss these issues.

Forecasting the future development of a firm is always an important issue in firm's survival in nowadays economy. Most of all, it is extremely important to be aware all the time about the inner and outer factors than can make a difference between a successful and a bankrupt firm. For this, here the authors have used three GM(1,1) models for forecasting the future symptoms (expressed through financial indicators) and performance indicator of a firm. Each time, based on the determined accuracy rate, a specific GM model has been chosen for every indicator's forecasting.

Considering some previous researches and findings in bankruptcy modelling and diagnosis, this paper enlarges their applicability by adding the possibility to make future predictions on the indicators' evolution and to observe and to better manage their causes. As it was expected, the GM(1,1) models used for the forecasting of the various time series variables taken into account were different from one case to another, choosing the best-specific model for each variable case conducted to more accurate data-fit, with direct results in the causes hierarchy.

By knowing the main causes that determine a certain state in firms' development and understanding them, the manager can action upon them in a manner that can make the difference between a bankrupt and a real successful firm.

The paper succeeds in enlarging the view regarding bankruptcy forecasting by adding a dynamic view over the considered variables. If, in most of the cases when facing with financial forecasting, a single model is used for predictions, here the best GM model has been chosen for each variable based on the obtained accuracy rate. The results are concluding.

The purpose of this paper is to discuss how tacit and explicit knowledge determine grey knowledge and how these are stimulated through interactions within networks, forming the grey hybrid intelligent systems (HISs). The feedback processes and mechanisms between internal and external knowledge determine the apparition of grey knowledge into an intelligent system (IS). The extension of ISs is determined by the ubiquity of the internet but, in our framework, the grey knowledge flows assure the viability and effectiveness of these systems.

Some characteristics of the Hybrid Intelligent Knowledge Systems are put forward along with a series of models of hybrid computational intelligence architectures. More, relevant examples from the literature related to the hybrid systems architectures are presented, underlying their main advantages and disadvantages.

Due to the lack of a common framework it remains often difficult to compare the various HISs conceptually and evaluate their performance comparatively. Different applications in different areas are needed for establishing the best combinations between models that are designed using grey, fuzzy, neural network, genetic, evolutionist and other methods. But all these systems are knowledge dependent, the main flow that is used in all parts of every kind of system being the knowledge. Grey knowledge is an important part of the real systems and the study of its proprieties using the methods and techniques of grey system theory remains an important direction of the researches.

The paper discusses the differences among the three types of knowledge and how they and the grey systems theory can be used in different hybrid architectures.

The purpose of this paper is to realise a complete analysis at the company level using grey systems theory for shaping the relations among variables.

Starting from the symptoms that can be identified and moving forward to causes that determine a specific stage in a company's development and long‐term survival, all the aspects that can appear and affect a company's performance and bankruptcy are taken into account. Also, due to the fact that all the activities that took place in a company are running in an uncertain and a continually changing environment, grey systems theory was chosen to better shape the relations among the implied variables. Even when referring to a company's diagnosis or to its prediction, the involved aspects are presented and depicted. A numeric example is also computed in the last part of the paper.

The results are convincing: not only that the diagnosis of the company can show the main elements, factors that are affecting a company's activity, but even the main identified factors can be used for a prediction on a company's future evolution.

The method exposed in the paper can be used by any company for realising the diagnosis of the actual stage in which a firm could be situated and even for making further predictions regarding its evolution.

The paper succeeds in realising both diagnosis and prediction of a firm's current and future stage by using one of the newest developed theories: grey systems theory.

By making an analogy with the human body, the purpose of this paper is to underline the relations between a firm's failure causes and its current situation, in terms of the syndrome that can be identified at its level.

For this reason, some elements taken from medicine, such as symptoms, causes and syndromes are presented and characterized from the point of view of the firm.

It is shown that knowing the type of syndrome and the relation between it and the causes that determined its occurrence, a firm's situation can be improved and its life can be lengthened. The study was conducted on 19 firms and the results are conclusive.

By knowing the main causes that determine a certain type of bankruptcy syndrome, the firm's management can properly intervene to establish a new order and a new equilibrium, which can “save” the firm from an imminent collapse, bringing it to a normality situation and even leading it, in future, to increased performance.

The paper succeeds in shaping the relation between a firm's situation, its symptoms, the bankruptcy syndrome and the causes that led to a certain situation. Using one of the newest developed theories – the grey systems theory – and one of the newest concept used in firms' diagnosis – the bankruptcy syndrome – the paper extends the characteristics of this term and uses it in determining the causes that generate anomalies at firm level.

The purpose of this paper is to analyse the role of computational intelligence techniques in the process of communities' formation.

The paper develops a high performance genetic algorithm for community formation based on collective intelligence capacity. An experimental study is presented to illustrate the algorithm.

Collective intelligence does not represent the sum of individual intelligences, it is the ability of the community to complete more tasks than single individuals. The paper reveals the need for mechanisms that allow a large group of professionals to make decisions better than single individuals.

The genetic algorithm proposed in the paper may be used to obtain the optimal structure of a community, in terms of number of members and their role in the community.

The key concept is a new fitness index, an intelligence index, which is the optimal combination between intelligence and cooperation, and allows not only community formation, but also intelligence to be the driving principle in the community formation process.

The purpose of this paper is to summarize the advances in grey system theory research and various application achievements in science and engineering. At the same time, it commemorates the 40th anniversary of the birth of grey system theory and the 10th anniversary of Grey Systems–Theory and Application.

Firstly, the innovations of theoretical research in grey system theory were summarized and some of the widely recognized new results are briefly described. By searching and combing the research results of grey system theory in China national knowledge infrastructure (CNKI) database and Web of Science by Institute for Scientific Information (ISI), this paper shows the rapid development trend of grey system theory in the past 40 years, and the successful applications of grey system theory in the fields of social sciences, natural sciences and engineering technologies.

More than 227 thousands literature were found by input 10 phrases such as grey system, grey number and sequence operator etc. in CNKI database. After entering the new century, the number of grey system papers included in CNKI database is increasing rapidly. Since 2008, more than 10 thousands papers have been included per year and more than 15 thousands papers have been included per year since 2014. Grey system method and model are widely used in physics, chemistry, biology and other fields of natural science, as well as transportation, electric power, machinery and other fields of engineering technology, and a large number of valuable results have been achieved.

It can be seen that the grey system theory plays an important role in promoting China’s scientific and technological progress, innovation and development and high-level talent training from tens of thousands of literatures marked with important national science and technology projects and a large number of grey system literatures published by China’s double first-class universities and double first-class discipline construction universities.

Both innovations of theoretical research and practical application play important role in the growth of new theory. The innovations of theoretical research provide methods and tools for practical application, which is conducive to improve application efficiency and broaden application fields. A large number of practical applications needs have become the source of theoretical innovation and the solid background for the birth of theoretical innovation achievements.