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Record W2943976786 · doi:10.5267/j.msl.2019.4.023

Innovative work behavior of Vietnam telecommunication enterprise employees

2019· article· en· W2943976786 on OpenAlexvenueno aff
Thị Phương Linh Nguyễn

Bibliographic record

VenueManagement Science Letters · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicBusiness and Economic Development
Canadian institutionsnot available
FundersĐại học Kinh tế Quốc dân
KeywordsWork (physics)BusinessTelecommunicationsMarketingComputer scienceEngineering

Abstract

fetched live from OpenAlex

The telecommunications industry plays an important role in the socio-economic development. In Vietnam, this is one of the industries with rapid growth but unsustainable, promoting the development in width without focusing on depth development. To aim for sustainable growth and deep development, every enterprise needs to consider and implement innovative work behavior (IWB). By both qualitative and quantitative methods, the author focused on researching IWB of Vietnam telecommunications enterprise employees. The results showed that the behavior of innovation should be considered both the behavior of innovative work of individuals and the behavior of innovative work of individuals and colleagues. At the same time, the study also concluded that there were differences in gender, age, education qualification and working experience of Vietnam telecommunication enterprise employees when evaluating and scoring two scales of acts of innovation. Research results contributed both theoretically and practically to scholars and managers of Vietnam telecommunications enterprises.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.211
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2019
Admission routes1
Has abstractyes

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