MétaCan
Menu
Back to cohort
Record W4206832254 · doi:10.37956/jbes.v5i1.269

Leadership in the face of digital transformation in an Ecuadorian manufacturing company in 2020

2022· article· en· W4206832254 on OpenAlexaboutno aff
Carlos Alberto Ortíz Maldonado, María Belén Castillo Quintana

Bibliographic record

VenueJournal of business and entrepreneurial studie · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsTransformational leadershipTransactional leadershipLeadership styleDigital transformationQuarter (Canadian coin)BusinessPopulationKnowledge managementSociologyComputer sciencePublic relationsPolitical scienceGeographyWorld Wide Web

Abstract

fetched live from OpenAlex

The present research focused on determining the predominant leadership style in the productive areas of an Ecuadorian manufacturing company, and the level of digital transformation during the year 2020. The study was developed through cross-sectional descriptive research. The multifactorial leadership questionnaire and key performance indicators were used as instruments, which were applied digitally using Google forms. The population studied was 151 workers and the sampling technique was probabilistic. The results allowed determining that 74% of the transformational leadership guidelines are practiced, 77% of transactional leadership and 9% of laissez-faire. The level of digital transformation had an increase of 19% in the fourth quarter compared to the first quarter of the year, evidencing in practice the implementation of automation mechanisms, use of digital media and documents and implementation of technology. It was concluded throughnthe literature and theoretical review that to face the technological advance, the transformation leadership style with all its dimensions is the most appropriate because it promotes development, innovation and knowledge management

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.

How this classification was reachedexpand

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.088
GPT teacher head0.219
Teacher spread0.131 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of business and entrepreneurial studieSame topicBusiness, Innovation, and EconomyFrench-language works237,207