The Digital Maturity of Small- and Medium-Sized Enterprises in the Saguenay-Lac-Saint-Jean Region

This study examines the digital maturity of small- and medium-sized enterprises (SMEs) in the context of Industry 4.0. Despite growing awareness of the importance of digital transformation, many SMEs encounter structural and strategic challenges that impede their progress. Among their obstacles is the inadequacy of digital maturity models used to diagnose digital maturity levels in SMEs due to their typological, sectoral, geographical, and other specific characteristics. Using a constructivist and qualitative approach, we have developed a simplified, inclusive, and holistic assessment framework comprising six key dimensions (technology, culture, organization, people and human resources, strategic planning), associated with six progressive maturity levels. Our findings reveal that most SMEs studied in 2023 exhibit a beginner level of digital maturity. These enterprises are characterized by small-scale digital initiatives, often lacking a clear strategy, with limited or partial digitization of processes and heterogeneous technology adoption. The resulting self-assessment tool provides SMEs with practical guidance to launch, evaluate, and accelerate their digital transformation. This study contributes theoretically by proposing a practical digital maturity model and offering a tool to support SMEs and public policy. It highlights the need for tailored support, strategic alignment, and continuous training to unlock the full potential of Industry 4.0 in less urbanized and resource-constrained areas.

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Publication Details

Journal
Machines
Published
2025-09-09
DOI
https://doi.org/10.3390/machines13090835
Citations
4
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
4.97

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article

The Digital Maturity of Small- and Medium-Sized Enterprises in the Saguenay-Lac-Saint-Jean Region

Myriam Ertz, Gautier Georges Yao Quenum, Stéfanie Vallée
4 citations
Machines
Digital Transformation in Industry
4.97
article

The Digital Maturity of Small- and Medium-Sized Enterprises in the Saguenay-Lac-Saint-Jean Region

Myriam Ertz, Gautier Georges Yao Quenum, Stéfanie Vallée
article en
4 citations

Abstract

This study examines the digital maturity of small- and medium-sized enterprises (SMEs) in the context of Industry 4.0. Despite growing awareness of the importance of digital transformation, many SMEs encounter structural and strategic challenges that impede their progress. Among their obstacles is the inadequacy of digital maturity models used to diagnose digital maturity levels in SMEs due to their typological, sectoral, geographical, and other specific characteristics. Using a constructivist and qualitative approach, we have developed a simplified, inclusive, and holistic assessment framework comprising six key dimensions (technology, culture, organization, people and human resources, strategic planning), associated with six progressive maturity levels. Our findings reveal that most SMEs studied in 2023 exhibit a beginner level of digital maturity. These enterprises are characterized by small-scale digital initiatives, often lacking a clear strategy, with limited or partial digitization of processes and heterogeneous technology adoption. The resulting self-assessment tool provides SMEs with practical guidance to launch, evaluate, and accelerate their digital transformation. This study contributes theoretically by proposing a practical digital maturity model and offering a tool to support SMEs and public policy. It highlights the need for tailored support, strategic alignment, and continuous training to unlock the full potential of Industry 4.0 in less urbanized and resource-constrained areas.

MachinesVol. 13(9)
Université du Québec à Chicoutimi (CA)
Mitacs, Social Sciences and Humanities Research Council of Canada
Openalex Percentile: Top 5%
Digital Transformation in Industry
4.97
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The Digital Maturity of Small- and Medium-Sized Enterprises in the Saguenay-Lac-Saint-Jean Region — Myriam Ertz, Gautier Georges Yao Quenum, et al. · Machines (2025) | TGRS Research Map | TGRS