PROGRESS IN GEOGRAPHY ›› 2021, Vol. 40 ›› Issue (4): 671-680.doi: 10.18306/dlkxjz.2021.04.011
• Articles • Previous Articles Next Articles
ZHANG Xue1,2(), ZHOU Suhong1,2,*(
), CHEN Fei3
Received:
2020-06-17
Revised:
2020-10-19
Online:
2021-04-28
Published:
2021-06-28
Contact:
ZHOU Suhong
E-mail:zhangx396@mail2.sysu.edu.cn;eeszsh@mail.sysu.edu.cn
Supported by:
ZHANG Xue, ZHOU Suhong, CHEN Fei. Impact of the built environment on residents’ car commuting based on trip chain[J].PROGRESS IN GEOGRAPHY, 2021, 40(4): 671-680.
Tab.1
Individual socioeconomic attributes"
变量 | 样本数 | 比例/% | |||||||
---|---|---|---|---|---|---|---|---|---|
性别 | 男性 | 489 | 49.80 | ||||||
女性 | 493 | 50.20 | |||||||
年龄 | 19~30岁 | 384 | 39.10 | ||||||
31~45岁 | 378 | 38.50 | |||||||
46~59岁 | 220 | 22.40 | |||||||
教育 | 高中及以下 | 329 | 33.50 | ||||||
大专或本科 | 644 | 65.58 | |||||||
研究生 | 9 | 0.92 | |||||||
就业 | 全职就业 | 975 | 99.29 | ||||||
半职就业 | 7 | 0.71 | |||||||
是否拥有小汽车 | 有 | 355 | 36.15 | ||||||
无 | 627 | 63.85 | |||||||
月收入 | 4000元及以下 | 205 | 20.88 | ||||||
4001~8000元 | 580 | 59.06 | |||||||
>8000元 | 197 | 20.06 |
Tab.3
Binary Logistic regression of the car commuting on weekdays"
变量 | 未考虑其他活动出行 | 考虑其他活动出行 | |||||
---|---|---|---|---|---|---|---|
模型1 | 模型2 (居住地) | 模型3 (工作地) | 模型4 (居住地和工作地) | 模型5 (前项出行交互作用) | 模型6 (后项出行交互作用) | ||
常数项 | -5.237** | -5.610*** | -5.267*** | -5.322*** | -5.305*** | -8.454*** | |
社会经济属性 | |||||||
年龄 | 31~45岁 | 0.956** | 0.963** | 0.999** | 1.222** | 1.223** | 1.268** |
46~59岁 | -0.421 | -0.287 | -0.313 | -0.012 | -0.082 | -0.217 | |
是否有小汽车 | 有 | 3.181*** | 3.392*** | 3.241*** | 3.360*** | 3.465 *** | 3.551*** |
月收入 | 4001~8000元 | 1.872** | 1.602** | 1.811** | 1.356* | 1.374* | 1.525* |
>8000元 | 2.576*** | 2.195*** | 2.388*** | 1.954** | 2.007 ** | 2.173** | |
出行特性 | |||||||
有无出行同伴 | 有 | 2.250*** | 2.163*** | 2.292*** | 2.036*** | 2.402*** | 2.507*** |
出行时间 | -1.926*** | -1.649** | -1.910*** | -1.958*** | -2.187*** | -2.086*** | |
X | -3.021 | ||||||
Y | 2.850 | ||||||
建成环境 | |||||||
H_土地利用混合度 | -0.794** | -0.721** | -0.782** | -0.196 | |||
H_建设密度 | 0.381 | 0.271 | 0.273 | -2.690 | |||
H_交叉口密度 | -0.192 | -0.339 | -0.061 | -1.139 | |||
H_可达性 | -0.089 | -0.134 | -0.402 | 3.157 | |||
W_土地利用混合度 | -0.171 | -0.193 | -0.195 | -0.503 | |||
W_建设密度 | -0.205 | 0.128 | 0.041 | 1.430 | |||
W_交叉口密度 | 0.198 | 0.262 | 0.411 | -4.609 | |||
W_可达性 | 0.069 | 0.041 | 0.219 | 3.052 | |||
H_土地利用混合度×X | -0.581 | ||||||
H_建设密度×X | 1.925 | ||||||
H_交叉口密度×X | -5.322 | ||||||
H_可达性×X | 2.540* | ||||||
W_土地利用混合度×X | -0.816 | ||||||
W_建设密度×X | 1.175 | ||||||
W_交叉口密度×X | -1.440 | ||||||
W_可达性×X | -0.757 | ||||||
H_土地利用混合度×Y | -0.767 | ||||||
H_建设密度×Y | 3.016 | ||||||
H_交叉口密度×Y | 1.377 | ||||||
H_可达性×Y | -3.653 | ||||||
W_土地利用混合度×Y | 0.170 | ||||||
W_建设密度×Y | -1.569 | ||||||
W_交叉口密度×Y | 4.881 | ||||||
W_可达性×Y | -2.632 | ||||||
伪R2 | 0.529 | 0.571 | 0.539 | 0.583 | 0.621 | 0.619 | |
-2 log likelihood | 183.96 | 170.54 | 180.70 | 165.55 | 153.54 | 154.04 | |
P | 0.001 | 0.103 | <0.001 | 0.014 | <0.001 | 0.013 |
Tab.4
Regression results of the built environment and after work trip interaction"
居住地交互影响 | 工作地交互影响 | ||||
---|---|---|---|---|---|
变量 | 系数 | 变量 | 系数 | ||
常数项 | -6.049** | 常数项 | -5.306*** | ||
年龄 | 31~45岁 | 0.945* | 年龄 | 31~45岁 | 1.259** |
46~59岁 | -0.537 | 46~59岁 | -0.323 | ||
是否有小汽车 | 有 | 3.508*** | 是否有小汽车 | 有 | 3.272*** |
月收入(元) | 4001~8000元 | 1.831** | 月收入 | 4001~8000元 | 1.854** |
>8000元 | 2.175*** | >8000元 | 2.215*** | ||
有无出行同伴 | 有 | 2.666*** | 有无出行同伴 | 有 | 2.639*** |
出行时间 | -1.532* | 出行时间 | -2.166*** | ||
H_土地利用混合度 | -1.006*** | W_土地利用混合度 | -0.245 | ||
H_建设密度 | 0.437 | W_建设密度 | 0.166 | ||
H_交叉口密度 | -0.385 | W_交叉口密度 | 0.329 | ||
H_可达性 | -0.184 | W_可达性 | 0.054 | ||
L_土地利用混合度 | -0.044 | L_土地利用混合度 | -0.021 | ||
L_建设密度 | -0.012 | L_建设密度 | 0.006 | ||
L_交叉口密度 | 0.184* | L_交叉口密度 | 0.033 | ||
L_可达性 | -0.065 | L_可达性 | 0.007 | ||
H×L_土地利用混合度 | 0.022 | W×L_土地利用混合度 | -0.125 | ||
H×L_建设密度 | -0.109 | W×L_建设密度 | -1.050* | ||
H×L_交叉口密度 | 0.677 | W×L_交叉口密度 | -0.447 | ||
H×L_可达性 | 0.011 | W×L_可达性 | 0.756 | ||
伪R2 | 0.622 | 伪R2 | 0.592 | ||
-2 log likelihood | 140.42 | -2 log likelihood | 149.60 | ||
Sig | 0.011 | Sig | <0.001 |
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