Name
Abstract | ||
|---|---|---|
The primary objective of this study is to analyze the characteristics of commuting activities within the historical districts in cities of China. The impacts of various explanatory variables on commuters' travels are evaluated using the structural equation modeling (SEM) approach. The household survey was conducted in the historical districts in Yangzhou, China. Based on the data, various individual and household attributes were considered exogenous variables, while the subsistence activity characteristics, travel times, numbers of three typical home-based trip chains, trip chains, and travel mode were considered as the endogenous variables. Commuters in our study were classified into two main groups according to their working location, which were the commuters in the historic district and those out of the district. The modeling results show that several individual and household attributes of commuters in historic district have significant impacts on the characteristics of travel activities. Additionally, the characteristics of travel activities within the two groups are quite different, and the contributing factors related to commuting travels are different as well. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1155/2014/253289 | Computational Intelligence and Neuroscience |
Keywords | Field | DocType |
transportation | Subsistence agriculture,Structural equation modeling,Computer science,China,Regional science,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
2014 | 1 | 1687-5273 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||