Barriers to widespread adoption of plug-in electric vehicles in emerging Asian markets: An analysis of consumer behavioral attitudes and perceptions

Dasharathraj K. Shetty, Smaran Shetty, Lewlyn Raj Rodrigues, Nithesh Naik, Chetana Balakrishna Maddodi, Namesh Malarout, Nilakshman Sooriyaperakasam

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Electric vehicles (EVs) are one of the near-term practical solutions in-vehicle technology, which can reduce emissions leading to the greenhouse effect and dependence on fossil fuels that are correlated with conventional vehiclesconventional vehicles (CVs). Several interferences are yet to be overcome for widespread adoption of EVs, despite many benefits provided to the consumers. The tendencies of customers to resist new technology is one of the major barriers in EV adoption. Hence, the policy-related decisions that showing grim concerns of EV have a greater level of success. This research aims to identify potential environmental and socio-technical barriers to purchase of EVs and it determines if governmental policies and awareness of individuals affect the customer decisions purchasing an EV. This research tries to convey valuable insights into perceptions and preferences of technology enthusiasts, individuals who are greatly connected to latest technology developments, and those who are well equipped to sort out the numerous differences between CVs and EVs. These results can provide direction to EV engineer’s decision in including customer preference into EV engineering design. It can also help policymakers in developing transportation and energy policies. A survey-based study was conducted with a sample of 1230 people from urban cities of emerging Asian markets, i.e. India and Srilanka. The data collected were analyzed, which found perception of economic benefits, functional characteristics of EVs, awareness, knowledge, and familiarity of EVs as significant parameters, which directly have an impact on the purchase behavior of fully EVs.

Original languageEnglish
Article number1796198
JournalCogent Engineering
Volume7
Issue number1
DOIs
Publication statusPublished - 01-01-2020

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Chemical Engineering(all)
  • Engineering(all)

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