MétaCan
Menu
Back to cohort
Record W3120826025 · doi:10.5267/j.msl.2020.12.021

The impact of strategic agility on employees’ performance in commercial banks in Jordan

2021· article· en· W3120826025 on OpenAlexvenueno aff
Mohammad Izzat Al Halalmeh

Bibliographic record

VenueManagement Science Letters · 2021
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessCLARITYMarketingSample (material)PopulationStrategic planningStrategic managementStrategic leadershipTest (biology)Simple random sample

Abstract

fetched live from OpenAlex

This study aimed to determine strategic agility impact on employees’ performance in commercial banks in Jordan. A self-administrated questionnaire was developed according to research objective and hypotheses. The research population consisted of all managerial employees in Jordanian commercial banks. A random sample was selected consisting of 250 staff members who have senior administrative and supervisory positions in the commercial banks. Statistical techniques were used to test the research hypotheses. The research concluded a set of outcomes, the most important is strategic agility with its dimensions have an impact on employee performance in the commercial banks in Jordan. The research also concluded that strategic agility dimensions (strategic sensitivity, core capabilities, clarity of vision, strategic goals information technology selection, and share responsibility) influence on employee's performance in commercial banks in Jordan. The study recommended that commercial banks in Jordan have to adopt strategic agility approach to improve their employee's performance. The commercial banks must exert their best efforts to rapidly adapt to surrounding environmental variables. Commercial banks have to pay attention to human capital, which plays a major role in achieving good performance.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.024
GPT teacher head0.265
Teacher spread0.241 · 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

Citations16
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueManagement Science LettersSame topicOrganizational and Employee PerformanceFrench-language works237,207