Exploring Associations between Multimodality and Built Environment Characteristics in the U.S
Abstract
:1. Introduction
2. Literature Review
2.1. Multimodality
2.1.1. Needs for Multimodality
2.1.2. Factors Influencing Multimodality
2.2. Travel Behavior and Built Environment
2.3. Research Gaps and Contribution of This Study
3. Materials and Methods
3.1. Study Area and Data Collection
3.2. Variables
3.2.1. Dependent Variable: Operationalizing Multimodality
3.2.2. Independent Variables
3.3. Analytic Strategies
3.3.1. Ordinary Least Square Regression
3.3.2. Gradient Boosting Decision Tree Regressor
4. Results
4.1. How Did Multimodal Travel Behaviors Vary across the U.S.?
4.2. Was Multimodality Associated with Built Environment Characteristics in the U.S.?
Variables | Estimate | Std. Error | t-Value | p-Value | VIF |
---|---|---|---|---|---|
Constant | 0.359 | 0.007 | 48.780 | <0.001 | - |
Pop_den | 0.010 | <0.001 | 24.190 | <0.001 | 1.535 |
Diversity_HH_job | −0.082 | 0.063 | −1.294 | 0.196 | 1.017 |
Diversity_job | −0.023 | 0.003 | −7.851 | <0.001 | 1.592 |
Net_den | −5.998 | 1.140 | −5.262 | <0.001 | 6.031 |
Int_den | 2.223 | 0.123 | 18.091 | <0.001 | 3.936 |
Walkability index | 0.011 | <0.001 | 45.797 | <0.001 | 4.443 |
Job_proximity | 0.014 | <0.001 | 32.686 | <0.001 | 1.180 |
Auto_accessibility | −0.080 | 0.002 | −36.339 | <0.001 | 1.559 |
Transit_accessibility | 0.146 | 0.003 | 42.948 | <0.001 | 1.935 |
HH_size | 0.024 | 0.001 | 22.794 | <0.001 | 1.606 |
HH_income | 0.001 | <0.001 | 3.826 | <0.001 | 2.995 |
White | −0.018 | <0.001 | −37.876 | <0.001 | 6.550 |
Black | −0.015 | <0.001 | −30.829 | <0.001 | 4.905 |
Asian | 0.013 | 0.001 | 17.815 | <0.001 | 2.202 |
Single | 0.037 | <0.001 | 78.524 | <0.001 | 1.857 |
Low education | −0.002 | <0.001 | −5.323 | <0.001 | 2.960 |
No_car | 0.025 | <0.001 | 81.355 | <0.001 | 1.410 |
Work_at_home | 0.048 | 0.001 | 49.115 | <0.001 | 1.180 |
Model Statistics | |||||
Observations | 206,380 | ||||
R2 | 0.309 | ||||
Adjusted R2 | 0.309 |
4.3. To What Extent Did the Built Environment Characteristics Play a Role in Showing Multimodal Travel Patterns?
4.4. Were There Non-Linear Effects of Built Environment Factors on Multimodality?
5. Conclusions and Discussion
Funding
Data Availability Statement
Conflicts of Interest
References
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Name | Description | Equation | Data Source |
---|---|---|---|
Dependent Variable | |||
Multimodality index | Entropy index for multimodality | ACS | |
Independent Variables of Interest | |||
Pop_den | The total population per acre at the census block group level in 10,000 | ACS | |
Diversity_HH_job | Jobs to household balance in 1,000 | SLD | |
Diversity_job | Entropy index for job diversity at the census block group level using the eight-tier employment categories, including retail, office, industry, service, entertainment, education, healthcare, and public sectors | SLD | |
Net_den | Network density in 10,000 | SLD | |
Int_den | Intersection density in 10,000 | SLD | |
Walkability index | Walkability index characterized by components of the built environment that influence the likelihood of walking | SLD | |
Job_proximity | Percentage of residents who take less than 10 min to commute in 10 | SLD | |
Auto_accessibility | The relative regional accessibility measure by using the regional centrality index by auto | SLD | |
Transit_accessibility | The relative regional accessibility measure by using the regional centrality index by transit | SLD | |
Independent Variables | |||
HH_size | Average household size | ACS | |
HH_income | Median household income in 10,000 | ACS | |
White | Percentage of the residents who are non-Hispanic white in 10 | ACS | |
Black | Percentage of the residents who are non-Hispanic black in 10 | ACS | |
Asian | Percentage of the residents who are non-Hispanic Asian in 10 | ACS | |
Single | Percentage of the residents who have not married in 10 | ACS | |
Low education | Percentage of the residents who attained less than a bachelors’ degree, including high school and college, in 10 | ACS | |
No_car | Percentage of the residents who do not own a car in 10 | ACS | |
Work_at_home | Percentage of the residents who work at home in 10 | ACS |
Variables | Mean | Median | Std. Dev | Min | Max |
---|---|---|---|---|---|
Multimodality index | 0.555 | 0.525 | 0.27 | 0.000 | 1.588 |
Pop_den | 0.635 | 0.264 | 1.53 | 0.000 | 81.131 |
Diversity_HH_job | 0.001 | 0.001 | 0.01 | 0.000 | 1.631 |
Diversity_job | 0.539 | 0.576 | 0.22 | 0.000 | 0.994 |
Net_den | 0.001 | 0.001 | 0.00 | 0.000 | 0.012 |
Int_den | 0.007 | 0.006 | 0.01 | 0.000 | 0.193 |
Walkability index | 9.596 | 9.167 | 4.35 | 1.000 | 20.000 |
Job_proximity | 1.293 | 0.961 | 1.22 | 0.000 | 10.000 |
Auto_accessibility | 0.433 | 0.441 | 0.28 | 0.000 | 1.000 |
Transit_accessibility | 0.112 | 0.000 | 0.20 | 0.000 | 1.000 |
HH_size | 2.633 | 2.560 | 0.59 | 1.010 | 9.250 |
HH_income | 6.707 | 5.917 | 3.63 | 0.249 | 25.000 |
White | 7.313 | 8.232 | 2.63 | 0.000 | 10.000 |
Black | 1.314 | 0.299 | 2.23 | 0.000 | 10.000 |
Asian | 0.469 | 0.073 | 0.98 | 0.000 | 10.000 |
Single | 3.319 | 3.076 | 1.42 | 0.000 | 10.000 |
Low education | 7.008 | 7.521 | 2.04 | 0.000 | 10.000 |
No_car | 1.402 | 0.620 | 1.92 | 0.000 | 10.000 |
Work_at_home | 0.492 | 0.350 | 0.55 | 0.000 | 10.000 |
Variables | Impurity-Based Feature Importance | Permutation-Based Feature Importance | ||
---|---|---|---|---|
Importance | Rank | Importance | Rank | |
Built environment characteristics | ||||
Pop_den | 0.206 | 1 | 0.159 | 2 |
Diversity_HH_job | 0.019 | 15 | 0.010 | 17 |
Diversity_job | 0.011 | 18 | 0.004 | 18 |
Net_den | 0.036 | 7 | 0.034 | 9 |
Int_den | 0.018 | 16 | 0.015 | 16 |
Walkability index | 0.117 | 3 | 0.051 | 7 |
Job_proximity | 0.033 | 8 | 0.028 | 10 |
Auto_accessibility | 0.026 | 11 | 0.048 | 8 |
Transit_accessibility | 0.108 | 4 | 0.059 | 6 |
Neighborhood characteristics | ||||
HH_size | 0.024 | 13 | 0.022 | 12 |
HH_income | 0.031 | 9 | 0.020 | 15 |
White | 0.043 | 6 | 0.178 | 1 |
Black | 0.018 | 16 | 0.125 | 3 |
Asian | 0.023 | 14 | 0.021 | 13 |
Single | 0.101 | 5 | 0.061 | 5 |
Low education | 0.025 | 12 | 0.021 | 13 |
No_car | 0.133 | 2 | 0.116 | 4 |
Work_at_home | 0.029 | 10 | 0.027 | 11 |
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Lee, S. Exploring Associations between Multimodality and Built Environment Characteristics in the U.S. Sustainability 2022, 14, 6629. https://doi.org/10.3390/su14116629
Lee S. Exploring Associations between Multimodality and Built Environment Characteristics in the U.S. Sustainability. 2022; 14(11):6629. https://doi.org/10.3390/su14116629
Chicago/Turabian StyleLee, Sangwan. 2022. "Exploring Associations between Multimodality and Built Environment Characteristics in the U.S" Sustainability 14, no. 11: 6629. https://doi.org/10.3390/su14116629