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Record W2080359907 · doi:10.5539/ijms.v5n5p64

Factors Which Affecting Customer Satisfaction in the Garment Industry of Bangladesh

2013· article· en· W2080359907 on OpenAlexvenueno aff
Md. Alauddin, Saiful Islam Tanvir, Farjana Mita

Bibliographic record

VenueInternational Journal of Marketing Studies · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsFactory (object-oriented programming)Product (mathematics)BusinessMarketingQuality (philosophy)ClothingProduction (economics)Service (business)Customer satisfactionEconomicsComputer science

Abstract

fetched live from OpenAlex

Contentment of customer on goods and services of industries are conscientious as the most imperative featureheading towards the competitiveness and accomplishment in global business pursuit. Bangladesh is the largestmanufacturer and exporter of global garments product. This manuscript is an endeavor en route for come acrossthe aspects which affecting purchaser satisfaction of garments industry of Bangladesh. The collision of differentvariables such as Quality of Product, Accepted Quality Level, Production Cost, On Time (Experienced)Shipment, Standard Lead Time, Measurement of Product Security, Proper Sampling, Service andCommunication with the Employee, Expertise of the Employee, and Referral of the Factory to customersatisfaction has been scrutinized. The cram has been predestined upon the prime data which is composed fromdifferent garments factories of Bangladesh situated in Dhaka, Narayngang, Gazipur, Tongi, Savar & EPZ etcwith the prearranged opinion poll. Data investigation was ended with SPSS software. The numericalinvestigation manner engaged inside this cram is Aspect Investigation. Following the scrutiny, it’s originated soas to the most customers of the garments industry of Bangladesh are more sentient about expertise of theemployee of the factory to tenacity their problem arose, Referral of the Factory, and Measurement of ProductSecurity Offered by the Factory, and Production Cost Offered by the Factory and Quality of ProductManufactured by the Factory.

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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.045
GPT teacher head0.309
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

Citations4
Published2013
Admission routes1
Has abstractyes

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