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Record W4410590220 · doi:10.1016/j.jik.2025.100728

Knowledge management and SMEs’ digital transformation: A systematic literature review and future research agenda

2025· article· en· W4410590220 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Innovation & Knowledge · 2025
Typearticle
Languageen
FieldEngineering
TopicDigital Transformation in Industry
Canadian institutionsDalhousie University
FundersEvald ja Hilda Nissin SäätiöLiikesivistysrahastoKAUTE-Säätiö
KeywordsDigital transformationKnowledge managementTransformation (genetics)Systematic reviewPolitical scienceEngineering ethicsBusinessSociologyManagement scienceComputer scienceEngineeringMEDLINE

Abstract

fetched live from OpenAlex

This study aims to identify and explain different collaborative approaches, delineate external actors' roles, and examine the interplay between knowledge exploration and exploitation processes for digital transformation. We conducted a search of academic papers using research terms such as “Digital*, Digital transfor*, industry 4.0 (I4.0), industry 5.0, knowledge exploration, knowledge acquisition, ecosystem collaboration*, knowledge networks, and open innovation” in both the Scopus and Web of Science databases. Altogether, 108 papers met the criteria (e.g., ABS 2 & 2+ ranking of journals, only journal papers, and focusing on small- and medium-size enterprises (SMEs) digital transformation) for conducting a systematic literature review in this research. The results indicate that external actors play specific roles in supporting SMEs' digital transformation. We found that customers and suppliers push and encourage SMEs in their digital transformation, while coopetition can elicit greater technological benefits for SMEs with close technological and economic proximity. Intermediaries provide knowledge-brokering services, facilitate innovation processes, and enable technology transfer and capacity-building for SMEs’ digital transformation. Government initiatives, such as favorable policymaking and financial support, are important in promoting and facilitating a collaborative environment for technology development among SMEs. This study’s results present two distinct collaborative mechanisms that SMEs can utilize for digital transformation: (I) core value chain and network actors’ collaborations, which provide linear processes for knowledge exploration and exploitation, and (II) ecosystem and innovation platform-based collaborations, in which SMEs adopt the ambidextrous approach as a nonlinear process for knowledge exploration and exploitation for digital transformation. Certain organizational-level factors (organizational capabilities, micro-foundations, operational capabilities, organization strategies, and culture) are important for SMEs’ knowledge exploitation in digital transformation. The study also presents an integrated framework and offers directions for future research and important insights for practitioners.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.321
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it