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Record W4364357733 · doi:10.18280/ijsdp.180318

Factors Affecting Innovative Work Behavior among Employees in Algeria Petroleum Sector

2023· article· en· W4364357733 on OpenAlex
Anes Hebbaz, Siti Zubaidah Othman, Oussama Saoula

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicBusiness and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Work behaviorPetroleumBusinessEngineeringGeology

Abstract

fetched live from OpenAlex

With the development of digitalization, there is a growing need for the business organizations to work through some innovative practices.However, such organizational practices are primarily linked with the employees behaviour towards innovation which is further linked with the job demand and learning goal orientation.The purpose of this study is to investigate how job demands (JD) affect innovative work behavior (IWB).Additionally, the study will look into how Learning Goal Orientation (LGO) functions as a mediating factor in the relationship between JD and IWB.Data from 225 employees working in production division of Sonatrach petroleum company in Algerian were gathered via a self-administered survey.Partial Least Squares-Structural Equation Modeling was used to analyse the data (PLS-SEM).The study's findings revealed no statistically significant difference in the direct link between JD and IWB.It was found that the LGO mediates the link between JD and IWB to some extent.The finding implies that by emphasising learning goals, firms can proactively enhance individuals' innovativeness at work.Future research should also take into account other crucial factors including job security and the work environment's mediating role in learning goal orientation across various industries and geographical regions.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.467

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 head0.023
GPT teacher head0.248
Teacher spread0.224 · 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