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Record W2079865122 · doi:10.5539/ibr.v5n4p134

Improving Customer Service in the Banking Industry-Case of Ghana Commercial Bank (GCB)-Ghana

2012· article· en· W2079865122 on OpenAlexvenueno aff
George Kofi Amoako

Bibliographic record

VenueInternational Business Research · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessProfitability indexMarketingCustomer retentionCustomer advocacyCustomer to customerCustomer serviceService (business)Customer profitabilityPopulationFinancial servicesFinanceService quality

Abstract

fetched live from OpenAlex

Customer service has become so vital and significant to consider especially in the financial business sector whether locally or globally. As banks continue to provide an increasing number of financial services and products, they face the challenge of integrating these disparate systems into a coherent, efficient infrastructure, while delivering the highest level of customer service and convenience without exposing their customers to the bank’s internal system integration problems. However, banks in Ghana especially Ghana Commercial Bank (GCB) needed to improve and formalize its customer service and public relations programs. A descriptive research method was used to gather data from the respective target population. Customer service at GCB from the customers’ perspective is not satisfactory but has led to the increase in number of new customers, maintenance of existing customer and increase in profitability among others.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

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 studies0.0070.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.107
GPT teacher head0.371
Teacher spread0.264 · 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

Citations33
Published2012
Admission routes1
Has abstractyes

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