MétaCan
Menu
Back to cohort
Record W4402870928 · doi:10.5267/j.jpm.2024.9.002

Factors affecting Jordanian Islamic banks towards competitive advantage

2024· article· en· W4402870928 on OpenAlexvenueno aff
Mefleh Faisal Mefleh Al-Jarrah, Abdalla Mohammad Al Badarin, Murad Ali Ahmad Al-Zaqeba

Bibliographic record

VenueJournal of Project Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamBusinessCompetitive advantageGeographyMarketingArchaeology

Abstract

fetched live from OpenAlex

There are challenges Jordanian Islamic banks face in maintaining and enhancing their competitive advantage in a rapidly evolving and increasingly competitive market. This paper aims to examine the factors that affect Jordanian Islamic banks towards competitive advantage, in addition to examining the roles of strategic intelligence and organizational creativity in enhancing Jordanian Islamic banks' competitiveness. However, this paper relied on the descriptive analytical approach, and the study population included general manager, department manager, branch manager, head of department based on Banks structures and annual reports from 2018 to the end of 2023. A stratified random sample was used, approximately 243 questionnaires were examined. The results indicated that organizational creativity and strategic intelligence play a crucial role in building competitive advantage. Also, organizational creativity contributes to achieving superiority by creating an innovative organizational environment, while strategic intelligence reflects the ability to make smart decisions that enhance competitive effectiveness. This paper also demonstrated the importance of managing and harnessing information effectively in order to enhance strategic intelligence. However, this paper contributes to the understanding of success factors in Islamic banking and provides actionable insights for managers navigating the complexities of the banking sector, emphasizing the importance of innovation, differentiation, and strategic decision-making for sustained growth and competitiveness.

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)0.005
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.021
GPT teacher head0.270
Teacher spread0.249 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Project ManagementSame topicIslamic Finance and Banking StudiesFrench-language works237,207