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Record W2138594696 · doi:10.5539/ass.v10n13p131

Relationship of Strategy Execution Plan Dimensions on Organization Performance of Higher Educational Institution in Palestine

2014· article· en· W2138594696 on OpenAlexvenueno aff
Mohammed R A Siam, Haim Hilman

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsPalestinePlan (archaeology)InstitutionStructural equation modelingKnowledge managementPartial least squares regressionBusinessEducational institutionDomain (mathematical analysis)Process managementComputer sciencePsychologyPolitical sciencePedagogyMathematics

Abstract

fetched live from OpenAlex

Today undoubtedly, the environment has become increasingly uncertain toward higher learning institutions. Therefore, successful execution of strategies in the midst of this uncertainty has become very crucial for the organizations because the success or failure of learning institutions depends to a greater extent on their ability to understand both the internal and external forces in the learning domain. However, this paper investigates the relationship between strategy execution plan dimensions and organizational performance in the higher educational institutions in Palestine. The study generated a quantitative questionnaire data from 255 respondents representing the top, medium and low management level of the higher educational institutions in Palestine. Data was analyzed using the partial least squares-structural equation model PLS-SEM. Overall, the finding revealed that strategy execution plan dimensions are significantly related to organizational performance as hypothesized. Discussions on the findings, implication and limitation are also provided.

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)0.000
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 score0.763
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.027
GPT teacher head0.248
Teacher spread0.221 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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