Research on Precision Marketing and Smart Tourism Service Optimization of Online Marketing Driven E-commerce Platform Based on Big Data and Machine Learning
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Mar 19, 2025
About this article
Published Online: Mar 19, 2025
Received: Nov 08, 2024
Accepted: Feb 11, 2025
DOI: https://doi.org/10.2478/amns-2025-0426
Keywords
© 2025 Aifang Zhang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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The path analysis of the wisdom travel experience segmentation dimension
| Path | Normalization factor | S.E. | C.R. | P | ||
|---|---|---|---|---|---|---|
| Behavioral intention | ← | Intelligent travel marketing inspection | 0.075 | 2.215 | 0.024 | |
| Behavioral intention | ← | Intelligent travel service experience | 0.148 | 0.073 | 1.912 | 0.045 |
| Behavioral intention | ← | Intelligent maintenance experience | 0.128 | 0.068 | 1.918 | 0.049 |
| Behavioral intention | ← | Intelligent integrated management experience | 0.259 | 0.074 | 3.012 | 0.003 |
| Behavioral intention | ← | Intelligent travel product experience | 0.069 | 0.059 | 0.915 | |
| Perceived value | ← | Intelligent travel marketing inspection | 0.082 | 2.718 | 0.008 | |
| Perceived value | ← | Intelligent travel service experience | 0.187 | 0.084 | 2.036 | 0.039 |
| Perceived value | ← | Intelligent maintenance experience | 0.194 | 0.075 | 2.485 | 0.015 |
| Perceived value | ← | Intelligent integrated management experience | 0.175 | 0.084 | 2.136 | 0.036 |
| Perceived value | ← | Intelligent travel product experience | 0.168 | 0.063 | 2.069 | 0.048 |
| Behavioral intention | ← | Perceived value | 0.365 | 0.074 | 5.136 | |
The scores of each variable
| Variable | N | Minimum value | Maximum value | Mean | Standard deviation | Degree of bias | Kurtosis |
|---|---|---|---|---|---|---|---|
| A1 | 378 | 1 | 5 | 3.845 | 0.614 | -1.458 | 3.948 |
| A2 | 378 | 1 | 5 | 3.876 | 0.637 | -0.843 | 2.054 |
| A3 | 378 | 1 | 5 | 3.765 | 0.763 | -0.715 | 1.148 |
| A4 | 378 | 1 | 5 | 3.861 | 0.641 | -1.056 | 2.445 |
| A5 | 378 | 1 | 5 | 3.834 | 0.628 | -0.856 | 2.045 |
| A6 | 378 | 1 | 5 | 4.086 | 0.715 | -0.686 | 0.815 |
| A7 | 378 | 1 | 5 | 3.971 | 0.539 | -0.848 | 4.358 |
| A8 | 378 | 2 | 5 | 3.982 | 0.557 | -0.725 | 2.763 |
| A9 | 378 | 1 | 5 | 3.763 | 0.799 | -0.856 | 1.086 |
| A10 | 378 | 1 | 5 | 3.768 | 0.731 | -0.756 | 1.039 |
| A11 | 378 | 1 | 5 | 3.715 | 0.937 | -0.582 | -0.015 |
| A12 | 378 | 1 | 5 | 3.526 | 0.852 | -0.456 | -0.126 |
| A13 | 378 | 1 | 5 | 3.715 | 0.775 | -0.648 | 0.569 |
| A14 | 378 | 1 | 5 | 3.706 | 0.827 | -0.826 | 0.825 |
| A15 | 378 | 1 | 5 | 3.746 | 0.772 | -0.485 | 0.368 |
| A16 | 378 | 1 | 5 | 3.708 | 0.826 | -0.615 | 0.154 |
| A17 | 378 | 1 | 5 | 3.625 | 0.883 | -0.726 | 0.185 |
| A18 | 378 | 1 | 5 | 3.587 | 0.854 | -0.498 | -0.049 |
| A19 | 378 | 1 | 5 | 3.541 | 0.935 | -0.425 | -0.295 |
| A20 | 378 | 1 | 5 | 3.689 | 0.848 | -0.285 | -0.157 |
| A21 | 378 | 1 | 5 | 3.436 | 0.915 | -0.352 | 0.069 |
| A22 | 378 | 1 | 5 | 3.596 | 0.805 | -0.648 | 0.308 |
| A23 | 378 | 1 | 5 | 3.584 | 0.905 | -0.429 | 0.428 |
| B1 | 378 | 1 | 5 | 3.548 | 0.728 | -0.728 | 1.265 |
| B2 | 378 | 1 | 5 | 3.759 | 0.647 | -0.625 | 1.169 |
| B3 | 378 | 2 | 5 | 3.848 | 0.625 | -0.648 | -0.067 |
| B4 | 378 | 1 | 5 | 3.454 | 0.732 | -0.348 | -0.018 |
| B5 | 378 | 1 | 5 | 3.658 | 0.705 | -0.386 | 1.785 |
| C1 | 378 | 1 | 5 | 3.918 | 0.695 | -0.758 | 0.658 |
| C2 | 378 | 2 | 5 | 3.928 | 0.698 | -0.563 | 1.265 |
| C3 | 378 | 2 | 5 | 3.958 | 0.625 | -0.578 | 1.715 |
| C4 | 378 | 1 | 5 | 3.978 | 0.728 | -0.848 | 1.325 |
Variable measurement
| Serial number | Latent variable | Variable | Describe |
|---|---|---|---|
| 1 | Intelligent travel marketing inspection | A1 | Easy access route |
| A2 | The platform is easy to use and smooth | ||
| A3 | Learn about relevant activities | ||
| A4 | Platform understanding | ||
| A5 | Learn about relevant activities | ||
| 2 | Intelligent travel service experience | A6 | Intelligent service is deeper in the scenic area |
| A7 | Get to your destination faster | ||
| A8 | Improve shopping efficiency | ||
| A9 | Improve meal efficiency | ||
| A10 | Quick response consulting and complaints | ||
| A11 | Check-in quickly | ||
| 3 | Intelligent maintenance experience | A12 | Wifi coverage wide, network speed block |
| A13 | Quickly find rescue methods and equipment | ||
| A14 | Improve checkout efficiency | ||
| 4 | Intelligent integrated management experience | A15 | Quick booking and check-in |
| A16 | Better arrangements | ||
| A17 | Feel fresh and interesting | ||
| 5 | Intelligent travel product experience | A18 | The situational experience is interesting |
| A19 | Facilitate the acquisition of the program information | ||
| A20 | Interactive devices are fresh and interesting | ||
| A21 | Show fresh and interesting | ||
| 6 | Intelligent infrastructure experience | A22 | Sightseeing safety |
| A23 | labeling | ||
| 7 | Perceived value | B1 | Compared with the cost I need, it is worth it for me to travel with wisdom |
| B2 | Compared with the energy I need, it is worth the use of smart travel | ||
| B3 | Compared with the time I need to spend, it is worth it for me to travel with wisdom | ||
| B4 | Compared with the risks I need, it is worth the use of smart travel | ||
| B5 | Compared with the various costs I have to pay, intelligent travel generally meets my needs | ||
| 8 | Behavioral intention | C1 | I will share my wisdom travel experience on the micro blog and the circle of friends |
| C2 | Smart travel will make me more likely to consume more products or services | ||
| C3 | If someone asks me for advice, I will recommend smart ways to travel | ||
| C4 | In the future, I will choose the smart tourist attractions |
Age, degree, monthly income, career impact on each variable
| Variable | Age | Educational background | Monthly income | Occupation | |
|---|---|---|---|---|---|
| Intelligent travel experience | F | 3.559 | 4.926 | 1.095 | 0.718 |
| Significance | 0.048 | 0.001 | |||
| Perceived value | F | 5.569 | 2.826 | 1.268 | 0.315 |
| Significance | 0.002 | 0.034 | |||
| Behavioral intention | F | 6.345 | 5.756 | 0.866 | 0.548 |
| Significance | 0.002 | 0.002 | |||
Independent sample t test of related variables for gender differences
| Variable | Mean t test | ||||
|---|---|---|---|---|---|
| T | Df | Sig. (double side) | Mean difference | ||
| Intelligent travel experience | Let’s say the variance is equal | 1.6548 | 383.452 | 0.0856 | |
| Let’s say that the variance is not equal | 1.6948 | 373.469 | 0.0915 | 0.0841 | |
| Perceived value | Let’s say the variance is equal | 0.7584 | 383.452 | 0.0389 | |
| Let’s say that the variance is not equal | 0.7669 | 381.656 | 0.4485 | 0.0385 | |
| Behavioral intention | Let’s say the variance is equal | 1.6348 | 383.452 | 0.0945 | |
| Let’s say that the variance is not equal | 1.6348 | 371.596 | 0.1565 | 0.0945 | |
| Variable | Standard error value | 95% confidence interval of the difference | / | ||
| Lower limit | Upper limit | ||||
| Intelligent travel experience | Let’s say the variance is equal | 0.0496 | -0.0152 | 0.1823 | |
| Let’s say that the variance is not equal | 0.0458 | -0.0152 | 0.1825 | ||
| Perceived value | Let’s say the variance is equal | 0.0526 | -0.0625 | 0.1463 | |
| Let’s say that the variance is not equal | 0.0515 | -0.0625 | 0.1485 | ||
| Behavioral intention | Let’s say the variance is equal | 0.0596 | -0.0198 | 0.2158 | |
| Let’s say that the variance is not equal | 0.0548 | -0.0195 | 0.2365 | ||