Social Support, Source Credibility, Social Influence, and Impulsive Purchase Behavior in Social Commerce
Bibliographic record
Abstract
Social commerce (s-commerce)—the use of social media to support electronic commerce—has become pervasive. This paper aims to investigate an important type of consumer behaviour that could generate considerable economic value: impulsive purchase behaviour. Specifically, we focus on the role of peer influence. Social influence theory posits that the process via which peers change a consumer’s behaviour can be interpreted along two dimensions: informational and normative. Furthermore, drawing from literature, source credibility and social support are proposed as the antecedent factors of the influencing processes in this context. We surveyed 303 s-commerce participants in Sina Weibo to empirically test the research model. The results indicate that peers’ expertise and trustworthiness are significantly related to both types of social influence that could exert an influence on a consumer. Further, consumers’ exchange of informational and emotional social support significantly facilitates social influence among them. This study contributes to both the s-commerce and the impulsive purchase literature by revealing the role of peer influence in consumers’ impulsive consumption behaviour in the s-commerce setting. The practical implications are also illustrated in the paper.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".