The effect of excessive use of social networking sites on customer loyalty, mediating role of perceived usefulness, essential information, behavioral intention
Bibliographic record
Abstract
The use of social media for young people has encouraged communication and socialization with other users massively and excessively. Besides, activities by the community of social media users have allocated much time. This condition exposed productivity as a challenge in the place and family communication. This study explores the effect of excessive use of social networking sites on customer loyalty with the mediating role of perceived usefulness, behavioral intention, and essential information. This research focused on adult-young people who use social networking media daily. Data collection used questionnaires designed with a five-point Likert scale and distributed online through Google Forms link. The respondents were given rewards through internet charge vouchers to encourage them, respondents, to complete the questionnaires. The questionnaire was distributed successfully to 932 prospective respondents during 2019-2023 through social media (WhatsApp, Line) and e-mail. Four hundred seventy-two (472) respondents were considered to meet the sample criteria as an adult-young group—data processing using Partial Least Square (PLS) with SmartPLS Software version 4.0. The results found that excessive use of social networking sites positively affects perceived usefulness, essential information, and behavioral intention. Perceived usefulness positively influences essential information and behavioral intention. The essential information increases behavioral intention and customer loyalty. The results also found that behavioral intention positively impacts customer loyalty. The practical contribution of research to young adults can determine the top priority in using social networking sites so as not to interfere with work activities and good relationships between family members. The film industry can promote products through social media effectively and efficiently. The theoretical contribution of research by enriching marketing behavior theory and technology acceptance model to improve user welfare and comfort.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".