Peaks, Slopes, Canyons and Plateaus: Identifying Technology Trends Throughout the Life Cycle

Abstract

A novel domain-independent approach to technology trend monitoring is presented in the paper. It is based on the ontology of a technology trend, hype cycles methodology, and semantic indicators which provide evidence of a maturity level of a technology. This approach forms the basis for implementation of text-mining software tools. Algorithms behind these tools allow users to escape from getting too general or garbage results which make it impossible to identify promising technologies at early stages (early detection, weak signals). Besides, these algorithms provide high-quality results in extraction of complex multiword terms which correspond to technological concepts forming a trend. Methodology and software developed as a result of this study are applicable to various industries with minor adjustments and require no deep expert knowledge from a user.

Investigating the future of the fuzzy front end: towards a change of paradigm in the very early design phases?

“…It was therefore assumed that the noise/signal ratio was acceptably similar across the five clusters (a manual selection of the pertinent contributions would have been extremely time-consuming). The Scopus database was used; selected documents forming cluster document sets included at least one general and one specific keyword in the Title, Abstract or Keywords (TAK) list. The number of contributions belonging to each cluster document sets is used to estimate the intensity of research and level of interest for each cluster, as a common approach employed in the literature(Efimenko and Khoroshevsky, 2017). Changes in bibliometric data over time (years of publication are here considered) are used to observe the evolution of the intensity of research. Based on these figures, S-shaped curves of the cumulated numbers of publications have been interpolated to determine growth potential for research in each cluster.…”