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Record W3022680849 · doi:10.5539/ass.v16n5p82

Impact of Strategic Thinking on Achievement of Entrepreneurship in Al Manaseer Group (MG)

2020· article· en· W3022680849 on OpenAlexvenueno aff
Feras A. Al Zu’bi

Bibliographic record

VenueAsian Social Science · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsOpportunismEntrepreneurshipDimension (graph theory)NormalityCreative thinkingReliability (semiconductor)Need for achievementTest (biology)PsychologyStrategic thinkingStrategic managementMarketingManagementMathematics educationEconomicsBusinessSocial psychologyCreativityStrategic planningMathematics

Abstract

fetched live from OpenAlex

One of the most critical abilities that entrepreneurs of today’s business firms must have is strategic thinking (ST). Despite its role- rooted in full vision of entrepreneurial activities, especially the creation of new business projects, it has been ignored over the years in entrepreneurship (ENT) literature. This study seeks to explore if ST can promote ENT, and how with its dimensions - systems thinking (SsT), creative thinking (CT), and opportunism intelligence (OI), impacts the achievement of ENT in MG. For research purposes, a questionnaire including 26 questions was conducted. First, reliability analysis was implemented to identify and eliminate irrelevant variables. Also, the researcher used Kolmogroph - Esmirnov test to consider the normality of variables' distribution. Finally, to analyze the impact of ST and its dimension on the achievement of ENT, simple and multiple linear regressions were performed. In light of results, ST and its components has a significant positive impact on ENT achievement. The OI was the most significant positive impact. This research provides a missing gap in strategic management studies enables us to have more actual view of entrepreneurs and ENT. Directions for further research are also suggested.

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 score0.876
Threshold uncertainty score0.400

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 head0.047
GPT teacher head0.274
Teacher spread0.227 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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