MétaCan
Menu
Back to cohort
Record W4306399650 · doi:10.1111/caim.12522

Critical success factors for the innovativeness of the electronic industry: An analysis in developed and developing countries

2022· article· en· W4306399650 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCreativity and Innovation Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsStructural equation modelingOriginalityBusinessDimension (graph theory)Sample (material)Construct (python library)Knowledge managementMarketingConceptual modelCritical success factorSet (abstract data type)Industrial organizationBusiness administrationComputer sciencePsychologyCreativityMathematics

Abstract

fetched live from OpenAlex

The purpose of this study is to investigate the influence of critical success factors (CSFs) on the innovativeness of the electronic industry. We propose a novel conceptual model. To validate the model, we used structural equation modelling. Data were collected in a survey with 261 responses from companies in Brazil, Canada and the USA. A multigroup analysis was carried out. The results for the whole sample show that all the CSF investigated have a positive and significant influence at 1% on innovativeness, with the greatest influence obtained by the construct innovative culture and strategy, followed by research and development infrastructure, management knowledge and the innovative environment. The originality lies (1) in a proposition of a novel theoretical model that investigates both the individual effect and joint action of the constructs related to CSF, in a broader set of CSF; (2) in a deeper analysis of the relationship between innovativeness with the innovation performance of organizations in the electronic industry; (3) in a different dimension of analysis comparison considering three different innovation systems; and (4) in a managerial contribution by encouraging the construction of an organizational culture that has as its values the constant search for innovation and for encouraging the creation of innovative solutions.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.009
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.044
GPT teacher head0.306
Teacher spread0.263 · 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