INTRODUCING A DATA-DRIVEN APPROACH FOR VALIDATING THE PRACTICAL RELEVANCE OF EMERGING INNOVATION FIELDS — TREND INSIGHTS ON TECHNOLOGIES AND TWIN TRANSFORMATION

Foresight of emerging innovation fields via bibliometrics is often criticised for its perceived limitations in articulating practical relevance or anticipating application success. To overcome these deficiencies, foresight researchers and practitioners usually rely on expert interviews to qualitatively validate their quantitative findings. This study introduces a novel data-driven approach to validate the relevance of technology trend topics for businesses and to detect early implementation efforts by technology leaders. By combining a bibliometric analysis of scientific publications with trend insights from online job postings as an innovative foresight data source, we use the presumably most early-phased data sources of both perspectives — science and practice — for our assessment of future innovation fields. Our results indicate an emerging need for twin transformation, with sustainability management and digital transformation being two of the three most important innovation domains in our trend analysis. Furthermore, our study bridges the gap between scientific advancements and commercial viability.

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Publication Details

Journal
International Journal of Innovation Management
Published
2025-05-30
DOI
https://doi.org/10.1142/s1363919625400122
Primary Topic
Big Data and Business Intelligence
Type
article
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article

INTRODUCING A DATA-DRIVEN APPROACH FOR VALIDATING THE PRACTICAL RELEVANCE OF EMERGING INNOVATION FIELDS — TREND INSIGHTS ON TECHNOLOGIES AND TWIN TRANSFORMATION

Leo Brecht, Marie Scheuffele, NIELS FETKENHEUER
International Journal of Innovation Management
Big Data and Business Intelligence
article

INTRODUCING A DATA-DRIVEN APPROACH FOR VALIDATING THE PRACTICAL RELEVANCE OF EMERGING INNOVATION FIELDS — TREND INSIGHTS ON TECHNOLOGIES AND TWIN TRANSFORMATION

Leo Brecht, Marie Scheuffele, NIELS FETKENHEUER
article en

Abstract

Foresight of emerging innovation fields via bibliometrics is often criticised for its perceived limitations in articulating practical relevance or anticipating application success. To overcome these deficiencies, foresight researchers and practitioners usually rely on expert interviews to qualitatively validate their quantitative findings. This study introduces a novel data-driven approach to validate the relevance of technology trend topics for businesses and to detect early implementation efforts by technology leaders. By combining a bibliometric analysis of scientific publications with trend insights from online job postings as an innovative foresight data source, we use the presumably most early-phased data sources of both perspectives — science and practice — for our assessment of future innovation fields. Our results indicate an emerging need for twin transformation, with sustainability management and digital transformation being two of the three most important innovation domains in our trend analysis. Furthermore, our study bridges the gap between scientific advancements and commercial viability.

International Journal of Innovation ManagementVol. 29(05n06)
University of Liechtenstein (LI)
Openalex Percentile: Top 80%
Big Data and Business Intelligence
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INTRODUCING A DATA-DRIVEN APPROACH FOR VALIDATING THE PRACTICAL RELEVANCE OF EMERGING INNOVATION FIELDS — TREND INSIGHTS ON TECHNOLOGIES AND TWIN TRANSFORMATION — Leo Brecht, Marie Scheuffele, et al. · International Journal of Innovation Management (2025) | TGRS Research Map | TGRS