Knowledge Management in Russian Companies: Overall Score
The main objective of this paper is to understand and describe how knowledge management practices are organized in Russian firms of different industries and the extent to which these practices have been adopted to support the business strategy. Based on hierarchical cluster analysis of 104 Russian companies, this study highlights the specific combinations of KM practices and accents made by Russian managers in this area.
In many organizations implementation of innovation is initiated by the management with application of so-cold “top-down” approach: strategic targets and key success factors with the initiatives of its achieving are formed and consolidated in different regulations, procedures, rules and instructions, which are brought to concrete employees later. The feedback from employees is occurred on the fact of initiative execution in form of corrective procedures locally, but the forming of innovation is still the top-management prerogative.
Such centric approach is mostly demotivating approach for initiative employees, who generate, implement and use innovation ideas. For this problem correction hybrid methods are used. The creation of special department inside the company is supposed to be done. It bears duties of innovation catalyst (usually R&D and HR departments have this role). Among other things this department is responsible for inspiration of average executive on development of innovation, determination and consolidation of corporate values and standards of behavior. In the end, the employees orientation on single corporate targets, the increase of corporate spirit would again “top-down” imposed and the department is just the retransmitter of values that are determined by the management.
How should the politics of relations between colleagues, clients and partners be naturally created and how to establish the awareness by the company employees of their personal responsibility and their personal role in corporate values realization, creation of innovation atmosphere inside the organization that does not resist the innovation? The approach, which is described in this article, supposes the forming of distributed network inside the organization with the transfer to it the general effort in the sphere of creating innovations and implementing the corporate ethics principals.
These proceedings represent the work of researchers participating in the 11th International Conference on Intellectual Capital, Knowledge Management & Organisational Learning – ICICKM 2014, which this year is being held at The University of Sydney Business School, The University of Sydney, Australia. The Conference Co‐Chairs are Dr John Dumay from Macquarie University, Sydney, Australia and Dr Gary Oliver from the University of Sydney, Australia. The conference will be opened with a keynote by Göran Roos, Advanced Manufacturing Council, Adelaide, Australia who will address the topic of “Intellectual capital in Australia: Economic development in a high cost economy”. The second day will be opened with a from James Guthrie, University of Sydney, Australia on the topic of “Intellectual Capital and the Public Sector Research: Past, Present, and Future”. The ICICKM Conference constitutes a valuable platform for individuals to present their research findings, display their work in progress and discuss conceptual advances in many different branches of intellectual capital, knowledge management and organisational learning. At the same time, it provides an important opportunity for members of the IC, KM and OL communities to come together with peers, share knowledge and exchange ideas. ICICKM has evolved and developed over the last decade, and the range of papers accepted in this year’s conference ensures an interesting two‐day event. Following an initial submission of 144 abstracts that have undergone a double blind peer review process, 53 Research papers, 13 PhD Research papers, 1 Master’s Research paper, 1 Work‐in‐Progress papers are published in the ICICKM 2014 Conference Proceedings, representing work from Australia, Canada, China, Colombia, Czech Republic, Denmark, Estonia, Finland, France, Iran, Italy, Japan, Malaysia, New Zealand, Nigeria, Poland, Romania, Russia, Saudi Arabia, Singapore, Slovakia, South Africa, South Korea, Sweden, Taiwan, UK and USA. We hope that you have an enjoyable conference.
Data Correcting Algorithms in Combinatorial Optimization focuses on algorithmic applications of the well known polynomially solvable special cases of computationally intractable problems. The purpose of this text is to design practically efficient algorithms for solving wide classes of combinatorial optimization problems. Researches, students and engineers will benefit from new bounds and branching rules in development efficient branch-and-bound type computational algorithms. This book examines applications for solving the Traveling Salesman Problem and its variations, Maximum Weight Independent Set Problem, Different Classes of Allocation and Cluster Analysis as well as some classes of Scheduling Problems. Data Correcting Algorithms in Combinatorial Optimization introduces the data correcting approach to algorithms which provide an answer to the following questions: how to construct a bound to the original intractable problem and find which element of the corrected instance one should branch such that the total size of search tree will be minimized. The PC time needed for solving intractable problems will be adjusted with the requirements for solving real world problems.
We present a complex analysis of business models for large, medium and small Russian commercial banks from 2006 to 2009. The Russian banks are grouped based on homogeneity criteria of their financial and operational outcomes. The banks’ structure of assets and liabilities, profitability and liquidity ratio are taken into account. The results show how the banks are adjusted their business models before and after the financial turmoil taken place in 2008. In addition, the prevailing banking business models observed for the leading banks in Russia are defined. The banks often changing their business models are found and analyzed.
The paper investigates the process of evolutionary transformation of cooperation and integration modes of industrial and construction enterprises in St.-Petersburg. The study has been performed at the period since 1998 to nowadays. The network form of integration was chosen as the main objet of this research. The paper is aimed at identifying the path of knowledge management development in different types of networks.
One of the peculiarities of the network form of integration is the high level of independence of the network participants that interact with each other. Key issues in this cooperation would be the following:
How to organize an effective transfer of knowledge and technologies within a network?
How to find a balance between open systems of innovation and the protection of the intellectual property of network participants?
How to evaluate the intellectual capital of a network? Is it necessary to make an assessment for each participant separately? Should one take into account synergies that increase the value of the intellectual capital because of the network participants’ interaction and knowledge sharing?
How to increase competitiveness of each company and of the whole network by the effective use of the intellectual capital?
How to measure the impact of open innovations on the intellectual capital of the companies interacting within a network?
Thus, it is important to reveal how knowledge management system is developing within a network of inter-related enterprises.
On the base of interviews of top-managers of companies in industrial and construction companies there were identified five different types of networks and knowledge management systems within these types. It is demonstrated how the knowledge management model is growing and becoming mature from the amorphous type of network cooperation to the integrated type. Factors, influencing this evolutionary development, have been revealed. Also, the paper proposes an approach to the evaluation of knowledge management systems based upon the value-based management indicators.
For the development of technological innovations it is essential to ensure competent and modern commercialization within the framework of balanced business models. Multifactor cluster analysis of business models of contemporary high-technology companies and industries shows that the most effective commercialization emanate in the framework of four basic models. Company's profitability does not depend directly on the level of its technologies, but is determined by the quality of these business models. Besides trends in high-technology industries demonstrate raising segmentation and differentiation of markets and more frequent utilization of value network models.
The analysis of region differentiation of microentrepreneurship development and indexes of judicial statistics based on the current data of statistical recording are given in the article. The capabilities of cluster analysis for revelation of typological groups of the Russian region depending on the level of entrepreneurial activities and the results of law enforcement practice are represented.
This paper presents a pattern behavioral analysis of 100 largest Russian commercial banks by total assets during an eight- year period: from the first quarter of 1999 to the second quarter of 2007. Bank performance indicators are analyzed. Structural similarities in the development of the banks are examined. A cluster analysis is applied to determine banks with a similar structure of operations. This analysis allows to estimate how the structure of the Russian banking system has been changing over time. In particular, it allows to identify prevailing patterns in the behavior of Russian commercial banks and to analyze the stability of their position in a particular pattern.
How seriously does the degree of trust in basic social and political institutions for people from different countries depend on their individual characteristics? To answer this question, three types of models have been estimated using the data of the fifth wave of the World Value Survey: the first one based on the assumption about a generalized relationship for all countries, the second one taking into account heterogeneity of countries (using introduction of the country-level variables), the third type applying a preliminary subdivision of countries into five clusters. The obtained results have been used for suggestion of possible actions to increase public confidence in the basic institutions.
This article describes the application of currently most promising methods of (1) network (graph) theory, (2) content analysis and (3) subject-oriented approach to business process modeling for creating and automation of innovative process and therefore for maximization of ROI (return on investments) in intellectual and social capital of enterprises. Described approach delivers opportunities for unstructured information utilization in order to increase efficiency of innovation activity in organizations. As a result, virtual community with a multiple content centers is created presenting a prototype of intellectual neural network with distributed association nodes. In a course of development, instant full-text indexation takes place and taxonomic picture of different branches for such community is formed. In due course system gathers the statistics and builds-up maps of intercommunication with priority allocation of most discussed topics. A group of predetermined experts begins discussion on development prospects of this or that subject afterwards. The strategic map of investments into innovative development that can be offered to group of investors for competitive investments eventually turns out. In this process all steps except final (gathering of experts) are human nondependant, what increase efficiency of this process in general.