Discriminant Validity Analysis: OTT Video Platform User Experience Survey Data

A 2026 survey of 230 users on OTT video platforms measured 21 user experience items on seven-point Likert scales. The dataset supports a Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis investigating how UX dimensions like convenience, interaction, and emotional experience influence functional value, satisfaction, and usage intention. It was authored by Ya-Qin You and published on figshare.

Use Cases

• Validate structural equation models based on user experience constructs like convenience/fluency and emotional experience.
• Analyze the mediating role of satisfaction between service-quality experience and usage intention.
• Train predictive models for user satisfaction or usage intention using survey-derived UX dimensions.
• Conduct discriminant validity analysis on latent constructs measured by multi-item scales.

Strengths

• Dataset includes model fit statistics (SRMR=0.075) and predictive performance metrics (R² values up to 0.760).
• Analysis is based on 5,000 bootstrap resamples, which suggests a rigorous validation of the structural model.
• Survey data from 230 users provides a foundation for statistical analysis.

Limitations

• Row count is unknown, which may limit suitability assessment for certain modeling tasks.
• Column-level documentation is absent; field semantics must be inferred after download.
• The 5.5 KB file size indicates a very small dataset, likely containing only summary statistics or model outputs rather than raw survey responses.

Provenance

Source

figshare

Collection Method

Survey data collection from users of OTT video platforms.

Freshness

Last updated 2026-05-29 17:35:01; freshness should be verified.