Journal article
How do post content and poster characteristics affect the perceived usefulness of user-generated content?
Electronic commerce research and applications, Vol.65, 101395
05/2024
DOI: 10.1016/j.elerap.2024.101395
Abstract
•This study proposes two new variables—domain relevance and domain specificity—thereby enriching the dimension of content quality.•We found a non-linear relationship between domain specificity and the perceived usefulness of UGC.•We found that features of both argument quality and source credibility influence the perceived usefulness of UGC.
This study, guided by the elaboration likelihood model, explores the impact of user-generated content features, including argument quality and source credibility, on perceived usefulness. Analyzing social media posts in finance and health, the study’s econometric analysis reveals that these features influence perceived usefulness through central and peripheral cues. Newly identified features, domain relevance, and domain specificity are significantly associated with perceived usefulness. Specifically, domain relevance positively impacts perceived usefulness, while a U-shaped relationship exists for domain specificity. Subsequently, the study discusses the implications for user-generated content and management practices.
Details
- Title: Subtitle
- How do post content and poster characteristics affect the perceived usefulness of user-generated content?
- Creators
- Jie She - Changsha UniversityTao Zhang - Shanghai University of Finance and EconomicsJianzhang Zhang - Hangzhou Normal UniversityQingqing Chang - Shanghai Lixin University of Accounting and FinanceQun Chen - Department of Culture Management, Shanghai Publishing and Printing College, Shanghai, ChinaWeiguo Fan - University of IowaYong Li - Changsha University
- Resource Type
- Journal article
- Publication Details
- Electronic commerce research and applications, Vol.65, 101395
- Publisher
- Elsevier B.V
- DOI
- 10.1016/j.elerap.2024.101395
- ISSN
- 1567-4223
- eISSN
- 1873-7846
- Grant note
- DOI: 10.13039/501100001809, name: National Natural Science Foundation of China
- Language
- English
- Date published
- 05/2024
- Academic Unit
- Business Analytics
- Record Identifier
- 9984583617102771
Metrics
2 Record Views