Detecting and Validating Global Technology Trends Using Quantitative and Expert-Based Foresight Techniques

35 Pages Posted: 31 Aug 2018

See all articles by Ilya Kuzminov

Ilya Kuzminov

Higher School of Economics

Pavel Bakhtin

National Research University Higher School of Economics

Elena Khabirova

National Research University Higher School of Economics

Irina V. Loginova

National Research University Higher School of Economics

Date Written: August 29, 2018

Abstract

This paper contributes to the conceptualisation and operationalisation of the “technology trend” discussion in the scope of the Technology Foresight paradigm. It proposes a consistent logical approach to analysing technology trends and increase predictive potential of futures studies. The approach integrates Big Data analysis into the Foresight studies’ toolset by means of applying text mining, namely computerised analysis of large volumes of unstructured text-based industry-relevant analytics. It comprises methodological results such as analytical decomposition of the trend concept, including trend attributes (inherent characteristics) and various trend types and empirical results of detection and classification of global technology trends in the agricultural sector. The study makes a significant contribution to the development of a conceptual apparatus for trend analysis as a sub-area of Foresight methodology. The agricultural field is used to demonstrate the application the methodology. The empirical results can be applied by federal and regional authorities responsible for promoting development of the sectors to design relevant strategies and programmes, and by companies to set their long-term marketing and investment priorities.

Keywords: technology trends, innovation, science and technology forecasting, science and technology progress, foresight, text mining, survey, bibliometrics, patent analysis

JEL Classification: C55, O1, O3

Suggested Citation

Kuzminov, Ilya and Bakhtin, Pavel and Khabirova, Elena and Loginova, Irina V., Detecting and Validating Global Technology Trends Using Quantitative and Expert-Based Foresight Techniques (August 29, 2018). Higher School of Economics Research Paper No. WP BRP 82/STI/2018. Available at SSRN: https://ssrn.com/abstract=3240516 or http://dx.doi.org/10.2139/ssrn.3240516

Ilya Kuzminov

Higher School of Economics ( email )

Myasnitskaya street, 20
Moscow, Moscow 119017
Russia

Pavel Bakhtin

National Research University Higher School of Economics ( email )

Myasnitskaya street, 20
Moscow, Moscow 119017
Russia

Elena Khabirova (Contact Author)

National Research University Higher School of Economics ( email )

Myasnitskaya street, 20
Moscow, Moscow 119017
Russia

Irina V. Loginova

National Research University Higher School of Economics ( email )

Myasnitskaya street, 20
Moscow, Moscow 119017
Russia

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
37
Abstract Views
256
PlumX Metrics