Business & Management Studies

From moon landing to metaverse: Tracing the evolution of Technological Forecasting and Social Change

From moon landing to metaverse: Tracing the evolution of Technological Forecasting and Social Change

This article providing a global perspective on the journal’s publishing activity.

Authors

Anuj Sharma, Professor, Jindal Global Business School, O. P. Jindal Global University, Sonipat, Haryana, India.

Sascha Kraus, Free University of Bozen-Bolzano, Faculty of Economics & Management, Piazza Università 1, 39100 Bolzano, Italy; University of Johannesburg, Department of Business Management, Johannesburg, South Africa.

Satish Kumar, Department of Management Studies, Malaviya National Institute of Technology, Jaipur, Rajasthan 302017, India; Sunway Business School, Sunway University, Sunway City, 47500, Selangor, Malaysia; Faculty of Business, Design and Arts, Swinburne University of Technology Sarawak Campus, Kuching, 93350, Sarawak, Malaysia.

Weng Marc Lim, Sunway Business School, Sunway University, Sunway City, 47500, Selangor, Malaysia; Faculty of Business, Design and Arts, Swinburne University of Technology Sarawak Campus, Kuching, 93350, Sarawak, Malaysia; School of Business, Law and Entrepreneurship, Swinburne University of Technology, Hawthorn, 3122, Victoria, Australia.

Jaspreet Kaur, School of Business, University of Petroleum and Energy Studies, Dehradun, India.

Francesco Schiavone, Università degli Studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Italy; Paris School of Business, Rue Nationale 59, 75013, Paris, France.

Summary

Technological Forecasting and Social Change (TFSC) is one of the most prominent journals to focus on the methodologies and practices of technological forecasting and futures studies. This study aims to analyse the topical structure of TFSC and track the most cited articles published in the journal using a combination of a structural topic model (STM) and bibliometric analysis.

The STM reveals 18 prominent topics in TFSC, and the topical quality of the STM results is verified based on semantic coherence and topic exclusivity scores as well as an assessment of the correlations among topics. The STM also tracks the temporal variations in topical prevalence that occurred from 1969 to 2022, shedding light on the changing popularity of each topic.

The bibliometric analysis presents a decade-by-decade perspective on the most cited articles and the geographical dispersion of authors affiliated with TFSC, thereby providing a truly global perspective on the journal’s publishing activity.

Published in: Technological Forecasting and Social Change

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