Evolution and recombination of topics in Technological Forecasting and Social Change

Ivan Savin*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

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Technological Forecasting and Social Change (TFSC) is one of the main outlets in the literature on technological change. To assist its editors and future contributors in understanding the evolution of the journal, we review studies published between 1970 and 2022 identifying 25 main themes ranging from scenario foresight and forecasting methods that dominated the journal agenda in the first decades through innovation diffusion and patent analysis that gained popularity in 2006–2019 to social interaction and financial markets which experienced momentum in the last couple of years. We find that studies concentrated on more recent topics like firm performance, financial markets and environmental regulation have been cited more frequently and were contributed more often by scientists from China compared to the US. Inspired by the fact that studies recombining two or more topics are more impactful in terms of citations, we construct a graph of topics, both for the overall sample of 6240 studies reviewed and three periods of TFSC existence corresponding to different editors-in-chief. Our results illustrate knowledge complementarities explored in the journal so far and may indicate directions for further research.

Original languageEnglish
Article number122723
Number of pages14
JournalTechnological Forecasting and Social Change
Publication statusPublished - Sept 2023


  • Computational linguistics
  • Knowledge recombination
  • Literature review
  • Machine learning
  • Topic modelling


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