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Record W4411555767 · doi:10.32479/irmm.18270

The Impact of Digital Leadership on SMEs’ Innovation Performance: A Mediation-Moderated Model of Digital Capability and Innovation Culture

2025· article· en· W4411555767 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

VenueInternational Review of Management and Marketing · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigitalization and Economic Development in Agriculture
Canadian institutionsAlgonquin College
Fundersnot available
KeywordsMediationModerated mediationBusinessKnowledge managementPsychologyComputer scienceSocial psychologySociology

Abstract

fetched live from OpenAlex

Small and medium enterprises (SMEs) endeavor to achieve sustainability in the digital transformation age while leaders strive to develop their digital capabilities in response to the changes in the management landscape. The primary aim of this study is to investigate the effect of digital leadership (DL) on Kuwait’s SME innovation performance. Further, examine the intermediate role of digital capability (DC) and innovation culture (IC) in the relationship between digital leadership and innovation performance. This study adopted a quantitative method. It administered a questionnaire survey to collect the data and managed to gather 274 valid data from out of 400 Kuwaiti SME owners and CEOs. The results revealed that digital leadership profoundly influenced the innovation performance of Kuwaiti SMEs. Digital capability was critical in mediating the relationship between SMEs’ digital leadership and innovation performance, and innovation culture was pivotal in moderating the same relationship.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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