MétaCan
Menu
Back to cohort
Record W3133915359 · doi:10.5539/ass.v17n3p71

Impact of Situational Leadership on Strategic Capabilities in Kuwait National Petroleum Company (KNPC)

2021· article· en· W3133915359 on OpenAlexvenueno aff
Naser Fhad Naser Alajmi, Ayyoub. A. Alsawalhah

Bibliographic record

VenueAsian Social Science · 2021
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsSituational ethicsLeadership styleSituational leadership theoryBusinessStrategic planningWork (physics)Public relationsSample (material)Knowledge managementMarketingLeadership studiesPsychologyEngineeringPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This study aimed to identify the impact of situational leadership on the strategic capabilities of the Kuwait National Petroleum Company, and the case study approach was followed to achieve the objectives of the study. The study population consists of employees in the Kuwait National Petroleum Company, and a convenience sample of 100 employees has been drawn to distribute the study questionnaire to them. It was found that there is an impact of situational leadership in its dimensions (leadership skills, leadership styles, participation in decision-making, and situational planning) on the strategic capabilities of the Kuwait National Petroleum Company. The study recommends the need to work on establishing an organizational environment that stimulates and supports the strategic capabilities of the company, by paying attention to the factors of situational leadership within the company, and educating the company’s employees about the goals and importance of situational leadership and the consequences thereof through training courses and holding conferences and workshops in order to enhance strategic capabilities.

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 score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.298
Teacher spread0.232 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAsian Social ScienceSame topicOrganizational and Employee PerformanceFrench-language works237,207