Table 4 Regression model of built environment and urban vitality.

From: Investigating the relationship between built environment and urban vitality using big data

Variable

Variable name

B

Standard error

Beta

t

P

VIF

R2

Adjust R2

F

Diversity

Landscape

0.354

0.067

0.399

5.258

0.000***

1.951

0.654

0.64

F = 44.323 P = 0.000***

Food

− 0.176

0.122

− 0.163

− 1.441

0.152

4.332

Hotel

0.464

0.086

0.486

5.388

0.000***

2.75

Shopping

0.215

0.091

0.192

2.366

0.020**

2.223

Traffic

0.054

0.107

0.049

0.503

0.616

3.167

Design

Openness

0.107

0.063

0.144

1.695

0.093*

1.037

0.185

0.15

F = 5.319 P = 0.000***

Enclosure

0.107

0.11

0.151

0.978

0.330

3.436

Walkability

0.035

0.132

0.04

0.263

0.793

3.306

Greenness

− 0.24

0.08

− 0.269

− 3

0.003***

1.154

Imageability

0.35

0.102

0.301

3.441

0.001***

1.098

Distance

Road

0.19

0.054

0.22

3.486

0.001***

1

0.522

0.514

F = 65.519 P = 0.000***

Bus station

0.614

0.057

0.684

10.83

0.000***

1

Destination

Accessibility − 500 m

− 0.223

0.109

− 0.298

− 2.038

0.044**

5.443

0.536

0.52

F = 34.021 P = 0.000***

Transportation-500 m

− 0.227

0.096

− 0.236

− 2.359

0.020**

2.55

Transportation-1200 m

0

0.115

0

0.001

0.999

2.983

Accessibility − 1200 m

0.88

0.127

1.127

6.923

0.000***

6.73

  1. Dependent variable: Urban vitality.
  2. ***, **, *represent 1%, 5%, and 10% significance levels, respectively.
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