# Revealing Motives for Car Use in Modern Cities—A Case Study from Berlin and San Francisco

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## Abstract

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## 1. Introduction

#### 1.1. Motives for Car Use

#### 1.2. Motives for Car Use in Extended Discrete Choice Models

#### 1.3. Comparison of Car Use in Cities

#### 1.4. Motivation and Scope of This Work

- Discovering affective and instrumental motives for car use in modern cities;
- Applying a cost-efficient survey design to measure influences of long-distance travel behavior on everyday car use;
- Revealing the impact of population density and public transit supply on the frequency of car use;
- Giving insights in the decision-making process and explain more of the overall heterogeneity in pure regression model through the integration of motives in the HCM.

## 2. Concept of a Travel Skeleton and Data Collection

## 3. Data Description and Statistical Analysis

## 4. Attitudinal Constructs

## 5. Methodology Approach

#### 5.1. Ordered Hybrid Choice Model

#### 5.2. Construct of Reduced Form Model

## 6. Applied Model Specification of Motives for Car Use

- sociodemographic characteristics (person and household);
- long-distance travel activities;
- everyday travel;
- spatial structure at residential location;
- motives for car use.

## 7. Results of the Ordered Hybrid Choice Model

#### 7.1. Effects on Instrumental and Affective Motives

#### 7.2. Direct Effects on Car Use

#### 7.3. Overall Effects on Car Use

## 8. Discussion and Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Motives for car use. The 1–5 Likert-scaled questions as described in Table 1.

Indicators | Psychological Questions |
---|---|

${I}_{1}^{AM}$ | I feel free and independent when I drive a car. |

${I}_{2}^{AM}$ | I like to drive a car. |

${I}_{3}^{AM}$ | Driving a car means fun and passion for me. |

${I}_{4}^{AM}$ | Driving a car means freedom to me. |

${I}_{5}^{AM}$ | Being able to use my driving skill when driving a car is fun for me. |

${I}_{6}^{AM}$ | When I sit in the car I feel safe and protected. |

${I}_{7}^{AM}$ | The make of a car is important to me. |

${I}_{1}^{IM}$ | The functioning of a car is more important to me than the make of a car. |

${I}_{2}^{IM}$ | A car is primarily a means to an end for me. |

${I}_{3}^{IM}$ | I only use a car to get from A to B. |

${I}_{4}^{IM}$ | It doesn’t matter to me what vehicle type I drive. |

${I}_{5}^{IM}$ | I constantly have to be mobile in order to comply with my everyday obligations. |

${I}_{6}^{IM}$ | My everyday organization requires a high degree of mobility. |

Person Characteristics | ||||

Yes | No | |||

Age over 30 years | 78.23% | 21.77% | ||

Fulltime job | 57.30% | 42.70% | ||

Male | 52.27% | 47.73% | ||

Own bicycle | 48.92% | 51.08% | ||

Always | Sometimes | Never | ||

Share of car disposal | 46.66% | 23.20% | 30.14% | |

Household Characteristics | ||||

Yes | No | |||

Premium car in household | 20.45% | 79.55% | ||

Household from Berlin | 47.73% | 52.27% | ||

<$2500 | $2500–$5000 | $5001–$8000 | >$8000 | |

Share of income classes | 16.75% | 32.54% | 31.34% | 24.76% |

Type 1 | Type 2 | Type 3 | Type 4 | |

Share of household type | 31.22% | 18.30% | 25.72% | 24.76% |

Mobility and Car Use Characteristics | ||||

Yes | No | |||

Commuting by car | 73.09% | 26.91% | ||

Monomodal behavior | 29.19% | 70.81% | ||

Large number of daytrips | 4.07% | 95.93% | ||

Large number of vacation trips | 8.73% | 91.27% | ||

Long-distance trips by car | 23.56% | 76.44% | ||

Spatial Characteristics | ||||

Yes | No | |||

High population density | 39.71% | 60.29% | ||

High public transit accessibility | 25.84% | 74.16% | ||

N = 836 |

Factors | ||
---|---|---|

Affective Motive (AM) | Instrumental Motive (IM) | |

Indicators in PFA | ||

${I}_{1}^{AM}$ | 0.84496 | 0.04663 |

${I}_{2}^{AM}$ | 0.82794 | 0.08091 |

${I}_{4}^{AM}$ | 0.80952 | 0.01878 |

${I}_{5}^{AM}$ | 0.76738 | 0.07639 |

${I}_{3}^{AM}$ | 0.76463 | −0.04576 |

${I}_{6}^{AM}$ | 0.62815 | −0.01329 |

${I}_{7}^{AM}$ | 0.54755 | −0.23227 |

${I}_{3}^{IM}$ | −0.03506 | 0.69449 |

${I}_{2}^{IM}$ | −0.13355 | 0.64428 |

${I}_{1}^{IM}$ | 0.09295 | 0.58612 |

${I}_{4}^{IM}$ | −0.15331 | 0.49222 |

${I}_{6}^{IM}$ | 0.21989 | 0.27218 |

${I}_{5}^{IM}$ | 0.23032 | 0.26416 |

High factor loadings (> 0.3) are bolded.; n = 836 |

**Table 4.**Main parameter estimates. (A) Parameters of the structural equation of the choice model; (B) Parameters of the structural equations of the latent variables.

Log-likelihood | −12,116.04 | ||||||

Log-likelihood of choice component | −557.26 | ||||||

Log-likelihood of null model (choice component) | −918.44 | ||||||

McFadden pseudo-${R}^{2}$ | 0.39 | ||||||

N | 836 | ||||||

Thresholds of the choice component | |||||||

${\tau}^{\left(1\right)}$ | 1.814 | ||||||

${\tau}^{\left(2\right)}$ | 3.075 | ||||||

(A) | (B) | ||||||

Parameter | Value | Parameter$\alpha $from variable | on latent variable | ||||

affective motive | instrumental motive | ||||||

${\beta}_{age>30}$ | 0.472 | *** | Age > 30 years | −0.194 | ** | 0.172 | * |

${\beta}_{fulltime}$ | 0.148 | Fulltime job | 0.210 | *** | 0.079 | ||

${\beta}_{male}$ | 0.003 | Male | 0.398 | *** | −0.375 | *** | |

${\beta}_{bicycle}$ | −0.078 | ||||||

${\beta}_{car-sometimes}$ | 0.183 | Car disposal - sometimes | 0.660 | *** | 0.286 | ** | |

${\beta}_{car-always}$ | 1.214 | *** | Car disposal - always | 1.126 | *** | 0.294 | *** |

${\beta}_{premiumcar}$ | 0.235 | ** | Premium car in household | 0.664 | *** | −0.035 | |

${\beta}_{berlin}$ | 0.097 | From Berlin | 0.014 | 0.980 | *** | ||

${\beta}_{lowincome}$ | −0.322 | ** | Low income | 0.308 | *** | 0.290 | ** |

${\beta}_{hhtype3}$ | 0.320 | *** | |||||

${\beta}_{hhtype4}$ | 0.200 | * | |||||

${\beta}_{highdaytrips}$ | 0.533 | * | |||||

${\beta}_{highvacation}$ | −0.085 | ||||||

${\beta}_{commuting\_car}$ | 1.000 | ||||||

${\beta}_{long-distance\_car}$ | 0.304 | *** | |||||

${\beta}_{monomodal}$ | −0.194 | * | |||||

${\beta}_{density}$ | −0.047 | ||||||

${\beta}_{pt\_accessibility}$ | −0.112 | ||||||

${\gamma}_{affective}$ | 0.398 | *** | |||||

${\gamma}_{instrumental}$ | 0.020 | ||||||

$\sigma $ | 0.970 | *** |

Variable | Direct Effect | Effect via LV Affective Motive | Effect via LV Instrumental Motive | Effect via LVs Combined | Overall, Effect | Overall, Effect in Ordered Probit |
---|---|---|---|---|---|---|

Age > 30 years | 0.472 | −0.077 | 0.003 | −0.074 | 0.398 | 0.347 |

Fulltime job | 0.148 | 0.000 | 0.002 | 0.002 | 0.233 | 0.206 |

Male | 0.003 | 0.158 | −0.007 | 0.151 | 0.154 | 0.139 |

Own bicycle | −0.078 | −0.078 | −0.146 | |||

Car disposal - sometimes | 0.183 | 0.262 | 0.006 | 0.268 | 0.451 | 0.355 |

Car disposal - always | 1.214 | 0.448 | 0.006 | 0.454 | 1.668 | 1.414 |

Premium car in household | 0.235 | 0.264 | −0.001 | 0.263 | 0.498 | 0.434 |

From Berlin | 0.097 | 0.006 | 0.019 | 0.025 | 0.122 | 0.121 |

Low income | −0.322 | 0.122 | 0.006 | 0.128 | −0.194 | −0.157 |

Household type 3 | 0.320 | 0.320 | 0.233 | |||

Household type 4 | 0.200 | 0.200 | 0.228 | |||

High daytrips | 0.533 | 0.533 | 0.559 | |||

High vacation trips | −0.085 | −0.085 | −0.135 | |||

Commuting by car | 1.000 | 1.000 | 1.000 | |||

Long-distance trips by car | 0.304 | 0.304 | 0.305 | |||

Monomodal behavior | −0.194 | −0.194 | −0.180 | |||

High population density | −0.046 | −0.046 | 0.022 | |||

High public transit accessibility | −0.112 | −0.112 | −0.159 |

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## Share and Cite

**MDPI and ACS Style**

von Behren, S.; Bönisch, L.; Niklas, U.; Chlond, B. Revealing Motives for Car Use in Modern Cities—A Case Study from Berlin and San Francisco. *Sustainability* **2020**, *12*, 5254.
https://doi.org/10.3390/su12135254

**AMA Style**

von Behren S, Bönisch L, Niklas U, Chlond B. Revealing Motives for Car Use in Modern Cities—A Case Study from Berlin and San Francisco. *Sustainability*. 2020; 12(13):5254.
https://doi.org/10.3390/su12135254

**Chicago/Turabian Style**

von Behren, Sascha, Lisa Bönisch, Ulrich Niklas, and Bastian Chlond. 2020. "Revealing Motives for Car Use in Modern Cities—A Case Study from Berlin and San Francisco" *Sustainability* 12, no. 13: 5254.
https://doi.org/10.3390/su12135254