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Record W4323317229 · doi:10.5430/ijba.v14n1p52

Financial Performance of Conventional and Islamic Banks: Evidence From Covid-19

2023· article· en· W4323317229 on OpenAlexvenueno aff
Abdullah Alawadhi, Ahmad F. AlQassar

Bibliographic record

VenueInternational Journal of Business Administration · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Profitability indexPandemicIslamBusinessVariance (accounting)2019-20 coronavirus outbreakEconomicsFinancial systemAccountingFinanceGeographyInternal medicine

Abstract

fetched live from OpenAlex

The COVID-19 pandemic had a devastating effect on the global economy, and Kuwait had its fair share. This study examines the impact of COVID-19 on the performance of banks in Kuwait. A pre-and post-COVID-19 statistical analysis was conducted between the largest conventional and Islamic banks in Kuwait. The correlation coefficient and analysis of variance are conducted at the 5% level of significance and 95% confidence level. Additionally, a comparative approach is adopted to ensure the proper analysis of the effect of COVID-19 on the performance of 10 banks in Kuwait. Findings reveal that the COVID-19 pandemic had a great impact on the profitability of the financial institutions in Kuwait; the COVID-19 pandemic did not have any negative effect on the performance of the stock prices of the banks in Kuwait.

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)0.001
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 score0.271
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.285
Teacher spread0.252 · 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
Published2023
Admission routes1
Has abstractyes

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