Jaâfar Berrada
Biographic Data
| ID | 8777524 |
|---|---|
| NAME | Jaâfar Berrada |
| GIVEN NAMES | Jaâfar |
| FAMILY NAME | Berrada |
| SIGNATURE | BERRADA J |
| AFFILIATIONS | VeDeCoM Institute |
| ORCID | 0000-0001-8016-8847 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
How to identify factors influencing mode choice behaviors within a heterogeneous metropolitan area? A novel approach midway between data science and econometrics
Estimating factors influencing mode choice behaviors has posed a significant challenge for decision makers. In this paper, we propose a three-step method to estimate mode choice between public transportation and private vehicles within a heterogeneous metropolitan area. First, we implement a deep learning model, Altaïr, capable of inferring travel times and travel flows by leveraging multi-source input data (Step 1). To identify homogeneous sub-r…
The impacts of combining incentives on carpooling for commuting in the Paris region
Carpooling is one solution to help reduce the negative externalities of solo driving. The aim of this study is to analyze the effect of incentives on solo drivers' intention to carpool. A questionnaire survey was carried out among 1, 329 participants, including 590 (38.39%) residents of the Paris metropolitan area who use a car to get to work. Modal choice estimates were modeled using multinomial logit and binomial logit econometric models for ca…
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The impacts of combining incentives on carpooling for commuting in the Paris region
Carpooling is one solution to help reduce the negative externalities of solo driving. The aim of this study is to analyze the effect of incentives on solo drivers' intention to carpool. A questionnaire survey was carried out among 1, 329 participants, including 590 (38.39%) residents of the Paris metropolitan area who use a car to get to work. Modal choice estimates were modeled using multinomial logit and binomial logit econometric models for ca…
How to identify factors influencing mode choice behaviors within a heterogeneous metropolitan area? A novel approach midway between data science and econometrics
Estimating factors influencing mode choice behaviors has posed a significant challenge for decision makers. In this paper, we propose a three-step method to estimate mode choice between public transportation and private vehicles within a heterogeneous metropolitan area. First, we implement a deep learning model, Altaïr, capable of inferring travel times and travel flows by leveraging multi-source input data (Step 1). To identify homogeneous sub-r…
Urban Transport and Accessibility (2 works) · Business (1 work) · Consumer Market Behavior and Pricing (1 work) · Econometric model (1 work) · Economic and Environmental Valuation (1 work) · Economic geography (1 work) · Economics (1 work) · Engineering (1 work) · Explanatory power (1 work) · Geography (1 work)