Measuring the DUI mode of innovation efficiently: A short-scale approach

Abstract This paper advances the empirical measurement of the doing–using–interacting (DUI) mode of innovation, based on the conceptual framework of Alhusen et al. Res Policy 50(4):104214 (2021) and its survey-based operationalization of Reher et al. ifh Working Paper 45 (2024b). Using data from German SMEs, we examine whether the three-dimensional structure of DUI learning theorized in the literature can be mirrored empirically. Exploratory factor analysis (EFA) confirms this latent structure by identifying three main learning processes: (1) DUI internal (learning-by-doing and internal interaction), (2) DUI user-driven (learning-by-using), and (3) DUI external (learning-by-external-interaction). However, some factor loadings are problematic, suggesting that not all of the original indicators are suitable for measuring the DUI mode of innovation. Secondly, building on the latent structure identified through EFA, short scales of various lengths are developed using ant colony optimization (ACO) to address practical constraints in innovation surveys. This provides a starting point for the further development of DUI innovation indicators that are particularly suited to less R&D-intensive innovation contexts, such as small firms, low-tech sectors, and lagging regions, as well as corresponding short scales.

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Publication Details

Journal
Journal of Evolutionary Economics
Published
2026-02-21
DOI
https://doi.org/10.1007/s00191-026-00946-9
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Measuring the DUI mode of innovation efficiently: A short-scale approach

Kilian Bizer, Leonie Reher, Jörg Thomä
Journal of Evolutionary Economics
Innovation and Knowledge Management
article

Measuring the DUI mode of innovation efficiently: A short-scale approach

Kilian Bizer, Leonie Reher, Jörg Thomä
article en

Abstract

Abstract This paper advances the empirical measurement of the doing–using–interacting (DUI) mode of innovation, based on the conceptual framework of Alhusen et al. Res Policy 50(4):104214 (2021) and its survey-based operationalization of Reher et al. ifh Working Paper 45 (2024b). Using data from German SMEs, we examine whether the three-dimensional structure of DUI learning theorized in the literature can be mirrored empirically. Exploratory factor analysis (EFA) confirms this latent structure by identifying three main learning processes: (1) DUI internal (learning-by-doing and internal interaction), (2) DUI user-driven (learning-by-using), and (3) DUI external (learning-by-external-interaction). However, some factor loadings are problematic, suggesting that not all of the original indicators are suitable for measuring the DUI mode of innovation. Secondly, building on the latent structure identified through EFA, short scales of various lengths are developed using ant colony optimization (ACO) to address practical constraints in innovation surveys. This provides a starting point for the further development of DUI innovation indicators that are particularly suited to less R&D-intensive innovation contexts, such as small firms, low-tech sectors, and lagging regions, as well as corresponding short scales.

Journal of Evolutionary EconomicsVol. 36(1)
Institute for Small Business Economics (DE), University of Göttingen (DE)
Bundesministerium für Bildung und Forschung
Industry, innovation and infrastructure
Openalex Percentile: Top 50%
Innovation and Knowledge Management
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