MétaCan
Menu
Back to cohort
Record W2097382179 · doi:10.17722/ijme.v2i2.13

A Study on Agewise Satisfaction Level of Customers in Banking Sector

2013· article· en· W2097382179 on OpenAlexvenueno aff
Mohan S. Rode

Bibliographic record

VenueInternational Journal of Management Excellence · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessIndustrial organizationCustomer satisfactionMarketing

Abstract

fetched live from OpenAlex

As a sequel to market diversification and deregulation as a part of financial sector reforms, the banking industry has been exposed to a fiercely competitive environment epitomized by the emergence of a ‘buyers market’. The gradual entry of private and foreign banks into Indian banking industry has transformed the hitherto protected and regulated banking environment to a liberalized and highly competitive one. In this changed banking scenario, the importance and significance of the customers has increased manifold. The dictum bank exists because of its customers’ has become more pronounced and relevant in the present context.  Banks have to devise suitable systems and mechanisms to satisfy the needs and expectations of various segments of customers for their survival. Against this backdrop, this above matter attempts to introspect about the past, makes an assessment of the present and outlines the strategy for the future in the context of customer service in banks.

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)0.005
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.072
GPT teacher head0.268
Teacher spread0.195 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Management ExcellenceSame topicInsurance and Financial Risk ManagementFrench-language works237,207