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Record W3096353543 · doi:10.5267/j.msl.2020.10.037

Do strategic planning dimensions and transformational leadership contribute to performance? Evidence from the banking sector

2020· article· en· W3096353543 on OpenAlexvenueno aff
Sarminah Samad, Waleed Abdulkafi Ahmed

Bibliographic record

VenueManagement Science Letters · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsTransformational leadershipBusinessSample (material)Structural equation modelingLeadership styleStrategic leadershipStrategic planningKnowledge managementMarketingCost leadershipProcess managementAccountingBusiness administrationPublic relationsComputer sciencePolitical scienceCompetitive advantage

Abstract

fetched live from OpenAlex

While some organizations realize the important role of strategic planning (SP) and leadership in influencing their business performance, it is unknown what SP dimensions and leadership style are required to improve the performance of banking institutions. The purpose of this study is to investigate the effects of transformational leadership (TL) style and SP dimensions (strategic planning level, implementation and barriers) on organizational performance. To this end, a self-administered questionnaire is distributed to a sample of 246 managerial employees from private banks in Yemen. The analysis with structural equation modelling using partial least squares indicates that TL style and SP dimensions significantly influence the performance of Yemeni banks. The results reveal that TL and SP dimensions are profoundly needed to enable Yemeni banks to propel to improved bank performance. The results draw several pertinent implications for decision makers that will help enhance the performance of the banking sector. Limitations from the findings and recommendations for further research are put forward.

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)0.004
metaresearch head score (Gemma)0.015
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 score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.100
GPT teacher head0.245
Teacher spread0.145 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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