Research on Slow Travel Consumer Behavioral Feature Extraction and Decision Support Based on Intelligent Data Analysis
19 mar 2025
INFORMAZIONI SU QUESTO ARTICOLO
Pubblicato online: 19 mar 2025
Ricevuto: 13 nov 2024
Accettato: 22 feb 2025
DOI: https://doi.org/10.2478/amns-2025-0376
Parole chiave
© 2025 Jing Wang, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Figure 4.
Decision support satisfaction analysis
| Test variable | Decision support satisfaction | Descriptive statistics | ANOVA test | |||
|---|---|---|---|---|---|---|
| N | M | SD | F | p | ||
| Perceptual usefulness | Satisfaction | 276 | 5.632 | 1.236 | 14.32 | 0.006 |
| Discontent | 45 | 5.415 | 0.698 | |||
| Perceptual intrusion | Satisfaction | 272 | 3.268 | 1.362 | 17.25 | 0.005 |
| Discontent | 49 | 2.514 | 0.697 | |||
Reliability Test of Questionnaire
| Variable name | Cronbach’s Alpha | Term number |
|---|---|---|
| Perceptual usefulness | 0.865 | 4 |
| Perceptual intrusion | 0.896 | 5 |
Validity Test of Questionnaire
| Variable name | KMO | Approximate card square test | p |
|---|---|---|---|
| Perceptual usefulness | 0.833 | 633.57 | 0.000 |
| Perceptual intrusion | 0.845 | 641.52 | 0.000 |
The basic situation of the experimental sample
| Sample characteristics | Subcategory | Frequency | Percentage |
|---|---|---|---|
| Gender | Male | 123 | 38.32% |
| Female | 198 | 61.68% | |
| Age | 18-30 | 156 | 48.60% |
| 31-40 | 110 | 34.27% | |
| 41-50 | 33 | 10.28% | |
| 51-60 | 22 | 6.85% | |
| Education | Secondary school | 17 | 5.30% |
| Specialty | 50 | 15.58% | |
| Undergraduate | 200 | 62.31% | |
| Master’s degree | 54 | 16.82% | |
| Monthly income interval (Yuan) | ≥2000 | 30 | 9.35% |
| 2001-4000 | 45 | 14.02% | |
| 4001-6000 | 57 | 17.76% | |
| 6001-8000 | 54 | 16.82% | |
| 8001-10000 | 74 | 23.05% | |
| ≤10000 | 61 | 19.00% |