IDEAS home Printed from https://ideas.repec.org/f/pba1851.html
   My authors  Follow this author

Javier Bas

Personal Details

First Name:Javier
Middle Name:
Last Name:Bas
Suffix:
RePEc Short-ID:pba1851
Terminal Degree:2020 Departamento de Análisis Económico: Teoría Económica e Historia Económica; Facultad de Ciencias Económicas y Empresariales; Universidad Autónoma de Madrid (from RePEc Genealogy)

Affiliation

Departamento de Análisis Económico: Economía Cuantitativa
Facultad de Ciencias Económicas y Empresariales
Universidad Autónoma de Madrid

Madrid, Spain
http://www.uam.es/departamentos/economicas/econcuan/
RePEc:edi:dquames (more details at EDIRC)

Research output

as
Jump to: Articles

Articles

  1. Bas, Javier & Zofío, José L. & Cirillo, Cinzia & Chen, Hao & Rakha, Hesham A., 2022. "Policy and industry implications of the potential market penetration of electric vehicles with eco-cooperative adaptive cruise control," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 242-256.
  2. Bas, Javier & Cirillo, Cinzia & Cherchi, Elisabetta, 2021. "Classification of potential electric vehicle purchasers: A machine learning approach," Technological Forecasting and Social Change, Elsevier, vol. 168(C).

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Bas, Javier & Zofío, José L. & Cirillo, Cinzia & Chen, Hao & Rakha, Hesham A., 2022. "Policy and industry implications of the potential market penetration of electric vehicles with eco-cooperative adaptive cruise control," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 242-256.

    Cited by:

    1. Qian, Lixian & Huang, Youlin & Tyfield, David & Soopramanien, Didier, 2023. "Dynamic consumer preferences for electric vehicles in China: A longitudinal approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    2. Omid Ghaffarpasand & Mark Burke & Louisa K. Osei & Helen Ursell & Sam Chapman & Francis D. Pope, 2022. "Vehicle Telematics for Safer, Cleaner and More Sustainable Urban Transport: A Review," Sustainability, MDPI, vol. 14(24), pages 1-20, December.

  2. Bas, Javier & Cirillo, Cinzia & Cherchi, Elisabetta, 2021. "Classification of potential electric vehicle purchasers: A machine learning approach," Technological Forecasting and Social Change, Elsevier, vol. 168(C).

    Cited by:

    1. Li, Lixu & Wang, Zhiqiang & Xie, Xiaoqing, 2022. "From government to market? A discrete choice analysis of policy instruments for electric vehicle adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 143-159.
    2. Qian, Lixian & Huang, Youlin & Tyfield, David & Soopramanien, Didier, 2023. "Dynamic consumer preferences for electric vehicles in China: A longitudinal approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    3. Upadhyay, Nitin & Kamble, Aakash, 2023. "Examining Indian consumer pro-environment purchase intention of electric vehicles: Perspective of stimulus-organism-response," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    4. Jia, Wenjian & Chen, T. Donna, 2023. "Investigating heterogeneous preferences for plug-in electric vehicles: Policy implications from different choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    5. Zhiqiang Xu & Mahdi Aghaabbasi & Mujahid Ali & Elżbieta Macioszek, 2022. "Targeting Sustainable Transportation Development: The Support Vector Machine and the Bayesian Optimization Algorithm for Classifying Household Vehicle Ownership," Sustainability, MDPI, vol. 14(17), pages 1-17, September.
    6. Yu, Baojun & Li, Changming & Mirza, Nawazish & Umar, Muhammad, 2022. "Forecasting credit ratings of decarbonized firms: Comparative assessment of machine learning models," Technological Forecasting and Social Change, Elsevier, vol. 174(C).

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Javier Bas should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.