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  4. Job Postings Analysis as a Tool for Technology Foresight
 
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2025
Conference Paper
Title

Job Postings Analysis as a Tool for Technology Foresight

Abstract
The quantitative analysis of job postings data has already proven to be an insightful methodology for answering anticipatory research questions in various scientific disciplines, such as human resources management, leadership, or economics. But despite its forward-looking potential, the data source has not yet been heavily exploited for data-driven foresight purposes, opening up the research gap of exploring job postings as an additional foresight data source and its analysis as an innovative new tool for technology foresight. This study utilizes online job postings data to answer future-oriented research questions in the context of artificial intelligence technology. Applying text mining techniques to the job description texts of global job advertisements from 2023 and 2024, we identify the most in-demand AI disciplines, their recruiting dynamics over time and in different countries, as well as industry-specific AI skill trends.
Author(s)
Scheuffele, Marie
University of Liechtenstein
Martini, Melanie  orcid-logo
Fraunhofer-Institut für Naturwissenschaftlich-Technische Trendanalysen INT  
John, Marcus  
Fraunhofer-Institut für Naturwissenschaftlich-Technische Trendanalysen INT  
Brecht, Leo
University of Liechtenstein
Mainwork
XXXVI ISPIM Innovation Conference - "Innovation Powered by Nature" 2025  
Conference
International Society for Professional Innovation Management (ISPIM Conference) 2025  
Open Access
File(s)
Download (1.34 MB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.24406/publica-4888
Language
English
Fraunhofer-Institut für Naturwissenschaftlich-Technische Trendanalysen INT  
Keyword(s)
  • Job postings analysis

  • data-driven foresight

  • artificial intelligence

  • technology skills

  • text mining

  • recruiting dynamics

  • regional analysis

  • industry analysis

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