The paper provides a number of proposed draft operational guidelines for technology measurement and includes a number of tentative technology definitions to be used for statistical purposes, principles for identification and classification of potentially growing technology areas, suggestions on the survey strategies and indicators. These are the key components of an internationally harmonized framework for collecting and interpreting technology data that would need to be further developed through a broader consultation process. A summary of definitions of technology already available in OECD manuals and the stocktaking results are provided in the Annex section.
This paper examines how export and export destination stimulates innovation by Russian manufacturing firms. The discussion is guided by the theoretical models for heterogeneous firms engaged in international trade which predict that, because more productive firms generate higher profit gains, they are able to afford high entry costs, and trade liberalization encourages the use of more progressive technologies and brings higher returns from R&D investments. We will test the theory using a panel of Russian manufacturing firms surveyed in 2004 and 2009, and use export entry and export destinations to identify the causal effects on various direct measures of technologies, skill and management innovations. We find evidence on exporters’ higher R&D financing, better management and technological upgrades. Exporters, most noticeably long-time and continuous exporters, are more active in monitoring their competitors, both domestically and internationally, and more frequently employ highly qualified managers. Exporters are more active in IT implementation. When it comes to export destination, we find that non-CIS exporters are more prone to learning. However, we cannot identify that government or foreign ownership shows any impact on learning-by-exporting effects.
The purpose of this paper is to develop the model of knowledge management influence on company performance for further empirical testing of the links between knowledge management practices and processes and organizational performance.
This study establishes a model for comprehensive analysis of knowledge management’s influence on performance and describes the preliminary results gained from the experience of 120 Russian companies. For further testing structural equation modelling and the partial least squares methods are proposed.
The results of the literature review justify the importance of the study conducting this study in the field of knowledge management and its connection to organizational performance in the developing market of Russia. A theoretical model for future empirical testing is provided and methods suggested for further data analysis and interpretation. The preliminary conclusions are discussed.
The focus on Russian firms limits the generalizability of the results. The non-response bias is also taken into account for further study.
This pilot study outlines the importance of knowledge management practices and processes for firm performance. The preliminary results will be interesting both for researchers and practitioners in the countries with the developing economies. The final results will provide new insights in understanding and formalizing the portrait of a typical Russian company with regards to knowledge management policies.
Few studies have been published on the knowledge management process within the Russian context. This study is expected to encourage future studies in this field. The present paper fills an important gap in the extant literature by conceptualizing the model for knowledge management performance analysis and proposes empirical testing of the relationship between knowledge management and firm performance in the context of a developing country that will be presented later as the direction for future study. This study is one of the first ever to study these relationships within the Russian context.
This study determines the factors that exert important influences on the success of collaborative research and development (R&D) projects. The study uses data from a cross-European sample of collaborative R&D projects under EU Framework Programs, supported with relevant qualitative evidence from a series of case studies, and focuses on three levels of possible factors: market, firm, and project levels. The results indicate that partnering firm innovation experience, innovation protection mechanisms, effective management of rules and regulations, and the existence of commercially driven projects that open up new technological areas are the factors with the strongest significant effect on product and/or process innovation. The findings contribute to understanding of how and under what conditions innovation can be developed in collaborative R&D projects.
The article suggests a technique that allows the university to develop a program of actions aimed at improving its innovation infrastructure. The need to develop such a program arises in connection with the deci sion to introduce the principles of innovation and entrepreneurship into the activities of the university. This meth odology combines benchmarking and balanced scorecard approaches, which allows to take into account the spe cifics of the strategy of a particular university and implement effectively the best practices of world leaders in the field of academic entrepreneurship.
The pocket data book contains main indicators characterizing S&T and innovation potential of the Russian Federation. There are the information about intellectual property, S&T output, data of international comparisons given.
The data book includes information of the Federal State Statistics Service, Federal Service for Intellectual Property, Organisation for Economic Co-operation and Development (OECD), Eurostat, UNESCO, World Intellectual Property Organisation, national statistical services of foreign countries, and results of own methodological and analytical studies of the HSE Institute for Statistical Studies and Economics of Knowledge.
In some cases, the presented data specify those published earlier.
This volume presents new results in the study and optimization of information transmission models in telecommunication networks using different approaches, mainly based on theiries of queueing systems and queueing networks .