Knowledge creation dynamics of technological forecasting and social change special issues

Rohail Ashraf*, Muhammad Asif Khan, Rafiq Ahmed Khuhro, Zeeshan Bhatti

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Technological Forecasting and Social Change (TFSC) is a leading peer-reviewed journal that addresses issues at the intersection of technology and society. The central strategy of the journal is to actively solicit and publish Special Issues (SIs). These SIs were first launched in 1979 to highlight and solicit manuscripts from the emerging issues of the discipline. This paper aims to analyze SIs and to highlight impact on TFSC as compared to Regular Issues (RIs). Using bibliometric analysis, this study first establishes that SIs have a higher impact on the field and the rate of citations per annum. The study then identifies leading actors (authors, affiliated institutions, and countries) and journals (knowledge inflow/outflow) that have contributed to the success of TFSC-SIs. Finally, SIs were identified. These clusters were compared with the knowledge clusters developed by Singh et al. (2020) for the entirety of TFSC journals, and four clusters unique to SIs were identified i.e. (Climate Change & Energy, Entrepreneurship and Innovation, Sustainability and, Social Media & Internet of Things). It is observed that these unique SI clusters have received disproportionate attention during the last decade and are likely to influence the future trajectory of the journal.
    Original languageEnglish
    Article number121663
    JournalTechnological Forecasting and Social Change
    Volume180
    Early online date12 Apr 2022
    DOIs
    Publication statusPublished - 1 Jul 2022

    Keywords

    • knowledge structures
    • knowledge dynamics
    • bibliometrics
    • bibliographic coupling
    • knowledge clusters

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