Selection of information sources for identifying technology trends: A comparative analysis

Nadezhda Mikova () and Anna Sokolova ()
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Nadezhda Mikova: National Research University Higher School of Economics (Russia)
Anna Sokolova: National Research University Higher School of Economics (Russia)

HSE Working papers from National Research University Higher School of Economics

Abstract: Technology foresight is mainly conducted by applying a combination of qualitative and quantitative methods. An evidence-based approach implies covering a wide range of information sources, as well as the active application of quantitative methods for processing. Therefore, it is very important to select the right sources of data, extract core information from them, and interpret the results correctly. In theoretical works devoted to identifying technology trends, the most widely used information sources are scientific publications and patents. There are also authors who propose relying on additional sources of data (media, conferences, business-related resources, and others). However, the issue of applicability and comparison of core and extra sources of information for monitoring technology trends has not received sufficient coverage in the literature. In connection with this, the purpose of this paper is to conduct a comparative analysis of the results of technology monitoring by using various information sources (scientific publications, patents, media, foresight-projects, conferences, international projects, dissertations, and presentations). The proposed approach is tested on the area of green energy and the results are described and analyzed. Possible factors that can affect the results of data processing are considered and discussed in order to more efficiently use the comparative analysis of quantitative and qualitative procedures for identifying, correcting, and updating global technology trends on a regular basis.

Keywords: technology foresight; technology trends monitoring; evidence-based studies; quantitative methods; information sources; data clustering; green energy (search for similar items in EconPapers)
JEL-codes: O31 O32 O33 O38 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2014
New Economics Papers: this item is included in nep-ore and nep-ppm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in WP BRP Series: Science, Technology and Innovation / STI, February 2014, pages 1-25

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