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Найдены 23 публикации
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Статья
Ena O., Mikova N., Saritas O. et al. Scientometrics. 2016. Vol. 108. No. 3. P. 1013-1041.

This paper introduces a systematic technology trend monitoring (TTM) methodology based on an analysis of bibliometric data. Among the key premises for developing a methodology are: (1) the increasing number of data sources addressing different phases of the STI development, and thus requiring a more holistic and integrated analysis; (2) the need for more customized clustering approaches particularly for the purpose of identifying trends; and (3) augmenting the policy impact of trends through gathering future-oriented intelligence on emerging developments and potential disruptive changes. Thus, the TTM methodology developed combines and jointly analyzes different datasets to gain intelligence to cover different phases of the technological evolution starting from the ‘emergence’ of a technology towards ‘supporting’ and ‘solution’ applications and more ‘practical’ business and market-oriented uses. Furthermore, the study presents a new algorithm for data clustering in order to overcome the weaknesses of readily available clusterization tools for the purpose of identifying technology trends. The present study places the TTM activities into a wider policy context to make use of the outcomes for the purpose of Science, Technology and Innovation policy formulation, and R&D strategy making processes. The methodology developed is demonstrated in the domain of “semantic technologies”.

Добавлено: 28 августа 2016
Статья
Ivanova I., Leydesdorff L. Scientometrics. 2014. Vol. 99. No. 3. P. 927-948.
Добавлено: 27 января 2016
Статья
Lovakov A., Agadullina E. Scientometrics. 2019. Vol. 119. No. 2. P. 1157-1171.
Добавлено: 26 марта 2019
Статья
Pislyakov V., Dyachenko E. Scientometrics. 2010. Vol. 83. No. 3. P. 739-749.

We consider the “Matthew effect” in the citation process which leads to reallocation (or misallocation) of the citations received by scientific papers within the same journals. The case when such reallocation correlates with a country where an author works is investigated. Russian papers in chemistry and physics published abroad were examined. We found that in both disciplines in about 60% of journals Russian papers are cited less than average ones. However, if we consider each discipline as a whole, citedness of a Russian paper in physics will be on the average level, while chemistry publications receive about 16% citations less than one may expect from the citedness of the journals where they appear. Moreover, Russian chemistry papers mostly become undercited in the leading journals of the field. Characteristics of a “Matthew index” indicator and its significance for scientometric studies are also discussed.

Добавлено: 26 сентября 2012
Статья
Pislyakov V. Scientometrics. 2009. Vol. 79. No. 3. P. 541-550.
Добавлено: 25 января 2013
Статья
Dranev Y., Kotsemir M. N., Syomin B. Scientometrics. 2018. Vol. 116. No. 3. P. 1565-1587.
Добавлено: 12 июня 2018
Статья
Burmaoglu S., Saritas O., Kıdak L. B. et al. Scientometrics. 2017. Vol. 112. No. 3. P. 1419-1438.
Добавлено: 20 февраля 2019
Статья
Paul-Hus A., Bouvier R. L., Ni C. et al. Scientometrics. 2015. Vol. 102. No. 2. P. 1541-1553.
Добавлено: 9 февраля 2016
Статья
Katchanov Y. L., Markova Y., Natalia A. Shmatko. Scientometrics. 2016. Vol. 108. No. 2. P. 875-893.
Добавлено: 6 июня 2016
Статья
Fursov K., Kadyrova A. Scientometrics. 2017. Vol. 111. No. 3. P. 1947-1963.

 

 

 

 

 

Добавлено: 15 октября 2016
Статья
Dyachenko E. Scientometrics. 2017. Vol. 113. No. 1. P. 105-122.
Добавлено: 13 октября 2017
Статья
Dyachenko E. Scientometrics. 2014. Vol. 101. No. 1. P. 241-255.
Добавлено: 4 октября 2015
Статья
Kotsemir M. N., Shashnov S. A. Scientometrics. 2017. Vol. 112. No. 3. P. 1659-1689.
Добавлено: 27 июня 2017
Статья
Oleinik A. N., Кирдина С. Г., Popova I. P. et al. Scientometrics. 2017. Vol. 113. No. 1. P. 417-435.
Добавлено: 21 октября 2017
Статья
Marzi G., Dabić M., Daim T. et al. Scientometrics. 2017. Vol. 113. No. 2. P. 673-704.
Добавлено: 27 сентября 2018
Статья
Moskaleva O., Pislyakov V., Sterligov I. et al. Scientometrics. 2018. Vol. 116. No. 1. P. 449-462.
Добавлено: 20 мая 2018
Статья
Batagelj V., Ferligoj A., SQUAZZONI F. Scientometrics. 2017. Vol. 113. No. 1. P. 503-532.
Добавлено: 1 ноября 2018
Статья
Saritas O., Burmaoglu S. Scientometrics. 2015. Vol. 105. No. 1. P. 497-508.

An increasing number of quantitative and qualitative methods have been used for future-oriented technology analysis (FTA) to develop understanding of situations, enable creativity, engage experts, and provide interaction. FTA practitioners have used frequently one or a suitable mixture of these methods for their activities. Changing policy and strategy making contexts as well as enabling technologies increased the need and possibility for performing adaptive Foresight studies in order to improve decision making about the future and using making better use of limited resources. This study performs a scientometric analysis of the publications in the major FTA journals with the aim of understanding the dynamics of using Foresight methods across time. Among the other branches of FTA, including forecasting, futures, and technology assessment, a special emphasis is given on Foresight as a systematic and inclusive way of exploring long term futures, developing visions and formulating policies for action. The study aims at detecting the key Trends and Weak Signals regarding the use of existing methods and emerging ones with potential uses for Foresight activities. Further implications will be achieved with the generation of networks for quantitative and qualitative methods. This will demonstrate the most frequently combined Foresight methods by researchers and practitioners. Where possible the methods will also be cross-fertilised with the key thematic areas to illustrate the relationships between policy domains and industrial sectors covered by the scope of study with methodological choice. This output is considered to be taken as a methodological guide for any researchers, practitioners or policy makers, who might embark upon or involved in a Foresight activity. Further outputs of the study will include the identification of centres of excellence in the use of Foresight methods and collaboration networks between countries, institutions and policy domains. Overall, the paper demonstrates how scientometric tools can be used to understand the dynamics of evolution in a research field. Thus, it provides an overview of the use of methods in Foresight, and how it is distinguished from the other FTA activities; the evolutionary characteristics of methodological design and factors influencing the choice of methods; and finally a discussion on the future potentials for new cutting-edge approaches. 

Добавлено: 7 октября 2015
Статья
Katchanov Y. L., Markova Y. V. Scientometrics. 2017. Vol. 113. No. 1. P. 313-333.
Добавлено: 5 октября 2017
Статья
Cugmas M., Ferligoj A., Kronegger L. Scientometrics. 2018. Vol. 106. No. 1. P. 163-186.

  

Добавлено: 2 ноября 2018
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