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Record W2802952430 · doi:10.17722/ijme.v10i3.985

Assessing satisfaction among Islamic Bank Customers’ in Bangladesh

2018· article· en· W2802952430 on OpenAlexvenueno aff
Kashrima Nawreen, Suhaily Shahimi

Bibliographic record

VenueInternational Journal of Management Excellence · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamCustomer satisfactionBusinessContext (archaeology)MarketingService qualityQuality (philosophy)CompassionService (business)

Abstract

fetched live from OpenAlex

This study is conducted to assess the level of customer satisfaction in Islamic banks from the context of Bangladesh. In the process, 300 questionnaires were distributed, and 236 were returned completed. The results of the questionnaire analysis reveal that there is significant relationship between three of the independent variables, namely- tangible products, personnel service quality and level of commitment to customer satisfaction. In contrast, level of compassion does not have a significant relationship with customer satisfaction. The analyses further reveal that the respondents were satisfied with the overall Islamic Banks’ infrastructure operating in Bangladesh, and most of the respondents did not have intentions to switch to the conventional counterparts. However, the main reason for the account holders to switch to Islamic banks is because they wanted to deal with Shahriah compliant banking. The analyses also indicate that a significant percentage of the respondents have accounts with both Islamic banks and conventional banks. The study has suggested that Islamic Banks should enhance Shahriah compliant framework to generate more income, experience speedy growth, and remain sustainable in the long run.

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)0.002
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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