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Record W3202702247 · doi:10.5539/ibr.v14n11p15

The Usage of Social Media for Improving the Customer Satisfaction: The Mediating Role of Electronic Services Quality

2021· article· en· W3202702247 on OpenAlexvenueno aff
Raad Mamduh Khaleel Khashman

Bibliographic record

VenueInternational Business Research · 2021
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsSocial mediaCustomer satisfactionService qualityPersonalizationQuality (philosophy)MarketingDimension (graph theory)BusinessSample (material)Test (biology)PsychologyService (business)Computer scienceWorld Wide WebMathematics

Abstract

fetched live from OpenAlex

The study aims to identify the impact of social media usage on customer satisfaction and the mediating role of electronic service quality through its dimensions (website design, reliability, customization, responsiveness, and trust) in the Vitas Jordan Company. A quantitative approach was used to answer the study questions and to test hypotheses. About (500) questionnaires were distributed using the Simple Random Sample technique to achieve the study purposes. (392) questionnaires were valid for analysis, based on the Statistical Package for Social Sciences (SPSS. V.25) and (AMOS) software. The findings of the study revealed that there is a significantly positive impact of social media usage on customer satisfaction and a significantly indirect positive impact of social media usage on customer satisfaction through the electronic Services Quality dimension as a mediating variable. The study recommended that managers concentrate and maintain the use of social media for providing unique services and responding to customers’ inquiries in a timely manner. In addition, the need to enhance the use of Twitter and Instagram in marketing champions. 

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.856
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.347
Teacher spread0.313 · 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 teacher head, 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

Citations2
Published2021
Admission routes1
Has abstractyes

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