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Unlocking resilience of German family-owned SMEs: The dynamic nexus of artificial intelligence adoption, knowledge acquisition, and frugal innovation

Irfan Saleem et al.

International Journal of Entrepreneurship and Innovation2026https://doi.org/10.1177/14657503261425121article
AJG 2ABDC C
Weight
0.50

What the paper says

This article investigates how artificial intelligence (AI) adoption could affect knowledge acquisition and frugal innovation (FI) associations to enhance a family firm's resilience. In Germany, family-owned small and medium-sized enterprises (SMEs) constitute the backbone of the economy, often characterised by long-term orientation, strong regional embeddedness, and conservative financing practices, which make them particularly relevant for studying resilience under technological disruption. A framework for this study is proposed and tested by integrating effectuation logic and the Diffusion of Innovations (DOI) theory. This research used a quantitative research technique and structural equation modelling, using data from family-run, SMEs in Germany, which account for a large share of employment and a significant portion of innovation activity in the Mittelstand context. The study employs time-lagged data to capture these dynamics. The study posits that AI adoption (AIA) has a crucial moderating function, and FI acts as a mediator in explaining organisational resilience (OR). This research combines effectuation logic and the DOI theory to answer the contradiction between augmentation and automation. The second contribution pertains to FI and its role in the nomological network involving AIA and OR. Third, this study advances methodological rigour in family firm research by applying a time-lagged SEM design, thereby contributing evidence from the comparatively underexplored context of German family SMEs.

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https://doi.org/https://doi.org/10.1177/14657503261425121

Or copy a formatted citation

@article{irfan2026,
  title        = {{Unlocking resilience of German family-owned SMEs: The dynamic nexus of artificial intelligence adoption, knowledge acquisition, and frugal innovation}},
  author       = {Irfan Saleem et al.},
  journal      = {International Journal of Entrepreneurship and Innovation},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/14657503261425121},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.