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Online Customer Experience (OCE) In Textile Industry E-retailing: Novel Commercial Strategy To Expand Into The Current Market

2023· article· en· W4366549174 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal For Multidisciplinary Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsMinnow Environmental (Canada)
Fundersnot available
KeywordsBusinessMarketingTextile industryTextileValue (mathematics)Customer advocacyCustomer to customerCustomer retentionAdvertisingComputer scienceService (business)

Abstract

fetched live from OpenAlex

Online-Customer-Experience (OCE) can be characterized as a psychological connection between a consumer and a business. Engaging the customers brings them closer to the brand, company, and organization. OCE aids in the continuous demonstration of dedication to the customer and in the value’s creation. In today's uncertain business environment, it seems to be critical for businesses to retain their consumers close to them. In this research, the OCE in the textile-industry market was assessed. The research examined at and thus the variables affecting customer interaction, effects of potential disillusionment of customers. To achieve such, a qualitative approach involving 200 applicants was conducted in April 2023 using an online survey method. Allen Solley and Peter England would be used as instances to enquire online questionnaires about the online textile-industry.

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.

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)0.007
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.002
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 head0.237
GPT teacher head0.551
Teacher spread0.315 · 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