Discriminant Validity Analysis: OTT Video Platform User Experience Survey Data
by Ya-Qin You·Updated 10d ago
5.5 KB1files
Available on 1 platform
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Description
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.
File format is XLS; users will need spreadsheet software or a library capable of reading Excel files.