How to catch mutual effects in cluster: comparative study of transitional and developed economies
In recent years, links between spatial proximity, and firms’ formal and informal contacts have become a sufficient subject for research in the field of innovation, competitiveness and sustainable economic growth. We introduce a model for the quantitative evaluation of the relationship between cluster participation and innovation capabilities, as well with a company’s growth in value. The paper focuses on comparison in mutual effects for companies from transitional and developed economies. We use a sample of 284 traded European companies between 2005 and 2009 which were carefully applied and subjected to panel data analysis techniques. Our empirical findings show the positive mutual effects on innovation capabilities measured as intangible assets and companies’ economic value added for both transitional and developed economies. Hereby these links are stronger in developed countries. Moreover, we identify the complementary factors to clustering, such as industry-level public R&D expenses, country innovation infrastructure development and location in a megalopolis.
The volume is dedicated to Boris Mirkin on the occasion of his 70th birthday. In addition to his startling PhD results in abstract automata theory, Mirkin’s ground breaking contributions in various fields of decision making and data analysis have marked the fourth quarter of the 20th century and beyond. Mirkin has done pioneering work in group choice, clustering, data mining and knowledge discovery aimed at finding and describing non-trivial or hidden structures—first of all, clusters, orderings, and hierarchies—in multivariate and/or network data.
This volume contains a collection of papers reflecting recent developments rooted in Mirkin's fundamental contribution to the state-of-the-art in group choice, ordering, clustering, data mining, and knowledge discovery. Researchers, students, and software engineers will benefit from new knowledge discovery techniques and application directions.
Monitoring trends is a key requirement for national and corporate policy makers to stay up-to-date with socio-economic and technological transformations, to anticipate emerging developments at the global and local levels, and to use this intelligence to prioritize areas for innovation and investment. This chapter aims at discussing how the results of trend monitoring can be integrated into the process of Science, Technology and Innovation policy formulation and business Research & Development planning processes. The chapter starts with an overview of the relevant innovation literature that gives a background in a broader theoretical context, where the technology monitoring activities can be better justified conceptually. This background provides to generate two models, which will portray positioning and functioning of Global Trend Monitoring in the policy and business planning process. Some practical aspects of how and in what form the results of Global Trend Monitoring should be provided to the target communities of policy makers and business planners are elaborated throughout the chapter.
It is well known that there are many indicators that reflect the efficiency of company operation. One of them - Economic Value Added (EVA). From the formula of calculating EVA follows that result of this criterion influence by a number of factors. In order to get objective results when calculating EVA it is recommended to make revisions in the operational profit and capital employed. However the number of necessary revisions hasn’t been determined yet. In this article it is presented, as adjustment and the accounting of separate factors (account articles) can lead to essential changes of EVA.
Knowledge management is becoming the most relevant and challenging issue of company’s strategy implementation in the new economy. Intellectual capital identification and evaluation is one of the most important issues in knowledge management. Our study focuses on the evaluating intellectual capital methods that allow finding out the most efficient way of intellectual capital management, including investment decision making. We suppose that the potential effectiveness of intellectual capital resources varies depending on a company size, industry and country. Therefore, to solve problems of intellectual capital evaluation we integrate two approaches that are relevant for studying the companies’ and industries’ behavior.
In this paper, we construct a new distribution corresponding to a real noble gas as well as the equation of state for it.
This paper aims to introduce and prove an estimation mechanism of cluster’s development conditions in the economy of region. The research is based on the assumptions of V. Chiesa’s work where four “driving forces” of cluster forming are defined. The empirical analysis of cluster forming conditions in economic sectors of Perm region is pres ented over 2004-2007 years. The introduced approach uses public statistical data only.
Smoking is a problem, bringing signifi cant social and economic costs to Russiansociety. However, ratifi cation of the World health organization Framework conventionon tobacco control makes it possible to improve Russian legislation accordingto the international standards. So, I describe some measures that should be taken bythe Russian authorities in the nearest future, and I examine their effi ciency. By studyingthe international evidence I analyze the impact of the smoke-free areas, advertisementand sponsorship bans, tax increases, etc. on the prevalence of smoking, cigaretteconsumption and some other indicators. I also investigate the obstacles confrontingthe Russian authorities when they introduce new policy measures and the public attitudetowards these measures. I conclude that there is a number of easy-to-implementanti-smoking activities that need no fi nancial resources but only a political will.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.