Diffusion of alternative fuel vehicles considering dynamic preferences

Consumer preferences are a crucial element of models aimed at understanding and predicting the diffusion of Alternative Fuel Vehicles (AFVs). Previous AFVs diffusion studies have considered static preferences, but preferences for complex products such as AFVs are likely to change under different market conditions. Therefore, using static preferences for demand forecasts may compromise the accuracy of those predictions. This study aims at incorporating dynamic preferences on a reference AFVs diffusion model and analyzing if adapting subsidy policies according to those preferences will provide more cost-effective results on AFVs adoption. A System Dynamics model adapted to the Portuguese market was developed to study the impact of considering dynamic preferences and several incentive policies adapted to such preferences.Two system dynamics models are developed for comparative purposes: one considering static preferences and other one considering dynamic preferences. According to the results derived from these models, the model with dynamic preferences predicts a higher market penetration of AFVs, mainly due to the increment of Plug-in Hybrid Electric vehicles and Battery Electric Vehicle market shares. These results show that considering dynamic consumer preferences has a significant impact on AFVs diffusion predictions. The subsidies scenarios allow concluding that designing subsidies according to the evolution of preferences stimulated AFVs adoption more effectively.

• Record URL:
  • https://doi.org/10.1016/j.techfore.2019.06.002
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0040162518316469
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00401625
• Supplemental Notes:
  • © 2019 Elsevier Inc. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Oliveira, Gabriela D
  • Roth, Richard
  • Dias, Luis C
• Publication Date: 2019-10

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 83-99
• Serial:
  • Technological Forecasting and Social Change
  • Volume: 147
  • Issue Number: 0
  • Publisher: Elsevier Science Publishing Company, Incorporated
  • ISSN: 0040-1625
  • Serial URL: http://www.sciencedirect.com/science/journal/00401625

Subject/Index Terms

• TRT Terms: Alternate fuels; Consumer preferences; Electric vehicles; Market penetration; Plug-in hybrid vehicles
• Geographic Terms: Portugal
• Subject Areas: Energy; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01718545
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 30 2019 10:09AM