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Record W3027448367 · doi:10.5430/rwe.v11n2p82

SNS Characteristics of Mobile Communication Company Influencing Brand Attitude and Purchase Intention

2020· article· en· W3027448367 on OpenAlexvenueno aff
S.K. Hong, Inchae Park

Bibliographic record

VenueResearch in World Economy · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
FundersHansung University
KeywordsLikert scalePsychologyExplanatory powerRegression analysisAdvertisingBrand relationshipPredictive powerMarketingBrand awarenessBusinessStatisticsMathematics

Abstract

fetched live from OpenAlex

Background/Objectives: The purpose of this study is to investigate the influence of SNS characteristics on brand attitude and purchase intention as the importance of SNS marketing is increasing recently.Methods/Statistical analysis: The subjects of this study were consumers who have visited SNS of domestic mobile carriers in recent years. Data collection was conducted online. A total of 31 questions were included, including 6 general characteristics and 25 questions on the Likert 5-point scale. The collected data was utilized by SPSS Ver.22 statistical package for empirical analysis. The main analyzes were frequency analysis, validity, reliability, and multiple regression analysis.Findings: This study examined the effect of mobile carrier SNS characteristics on the purchase intention and empirically analyzed whether the brand attitude had a mediating effect on the relationship between SNS characteristics and purchase intention. The empirical results show that the measured variables correlate with each other. First, SNS characteristics have a positive effect on purchase intention. As a result of multiple regression analysis, the standardization coefficient (β) showed that information providing had the highest influence on purchase intention as .355***. The explanatory power (R2) of the relationship between SNS characteristics and purchase intention was .485 (48.5%). Second, SNS characteristics have a positive effect on brand attitude. Benefit had the highest impact on brand attitude of .418***. The explanatory power (R2) of SNS characteristics on the influence of brand attitude was .538 (53.8%). Third, brand attitude affects purchase intention. Finally, Brand attitude was partially mediated between SNS characteristics and purchase intention. The characteristics of SNS are important to increase purchase intention, and the mediating effect of brand attitude is verified.Improvements/Applications: This study emphasizes the importance of SNS characteristics through brand attitude to increase purchase intention. It will be an important resource for suggesting SNS marketing methods that effectively utilize SNS characteristics.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.326
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.103
GPT teacher head0.342
Teacher spread0.239 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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