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Record W2149198581 · doi:10.5539/ijms.v5n6p185

Customers Awareness and Satisfaction of Islamic Banking Products and Services: Evidence from the Kuwait Finance House

2013· article· en· W2149198581 on OpenAlexvenueno aff
Kamal Naser, Athmar Al Salem, Rana Nuseibeh

Bibliographic record

VenueInternational Journal of Marketing Studies · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessIslamWork (physics)MarketingShariaIslamic bankingConfidentialityFinancial servicesPhoneFinanceCustomer satisfactionAccountingComputer securityEngineeringComputer science

Abstract

fetched live from OpenAlex

The objective of this study is to explore the levels of customer awareness and satisfaction with Islamic financial products and services offered by the Kuwait Finance House (KFH). The attempt is also made to identify reasons behind dealing with the KFH. To achieve these objective, 650 questionnaires were distributed during the period between 15 April and 15 May 2011 to the KFH customers and 429 returned completed. The results of the questionnaire analysis revealed that a significant proportion of the KFH customers are not aware of many of the products currently on offer. The respondents are relatively satisfied with almost all aspects of the KFH, although some work needs to be done to improve the appearance, architecture, internal design and furniture of the bank. They also expect an increase in the parking facilities and to train staff to handle transactions over the phone. The respondents indicated that they deal with the KFH for its name and image, its guaranteed confidentiality, its trusted management and Sharia’h Supervisory Committee. The respondents also demonstrated that they hold accounts in Islamic and commercial banks to diversify their investments.

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)0.001
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 score0.084
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.019
GPT teacher head0.255
Teacher spread0.236 · 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

Citations33
Published2013
Admission routes1
Has abstractyes

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