Name
Abstract | ||
|---|---|---|
As the ideal transportation mode for the last mile trips of the residents in the city, shared bicycles are becoming more and more popular, and the market of the shared bicycles is experiencing rapid development. The explosive growth of shared bicycles brings many conveniences but also issues. There are many shared bicycles illegally parked around the areas where people are concentrated, which not only caused huge traffic impact, but also affected the normal life of urban residents seriously. Although there have been many studies on public bicycles before, the research on shared bicycles is scattered, fragmented, and there are few quantitative studies. To explore the current operation status of shared bicycle, the cause of the problem, management methods, and provide practical suggestions and opinions on the future operation and development of shared bicycles in the city, after investigating the shared bicycle travel data in Yangpu District, Shanghai, the data obtained is summarized and analyzed with the statistical methods. AMOS and SPSS22.0 are used to analyze the data in depth in this paper. Also, with the establishment of hypothesis, a path diagram and structural equation model is proposed, and path coefficient is calculated. The model is identified, evaluated, and corrected. The extent of the influence of the factors on user satisfaction of the shared bicycle is determined. All the latent variables proposed in this paper passed the significance test. Moreover, there are significant positive correlations between various factors analyzed in this paper and user satisfaction of shared bicycles. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1007/s12652-019-01422-y | JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING |
Keywords | DocType | Volume |
User satisfaction, Shared bicycle, Structural equation modeling | Journal | 13 |
Issue | ISSN | Citations |
3 | 1868-5137 | 1 |
PageRank | References | Authors |
0.40 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaomei Xia | 1 | 1 | 0.40 |
| Huipeng Jiang | 2 | 1 | 0.40 |
| jin wang | 3 | 243 | 36.79 |