Policy Instruments for the Improvement of Customers’ Willingness to Purchase Electric Vehicles: A Case Study in Iran

Elham Allahmoradi, Saeed Mirzamohammadi, Ali Bonyadi Naeini, Ali Maleki, Saleh Mobayen and Paweł Skruch
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Elham Allahmoradi: School of Management, Economics and Progress Engineering, Iran University of Science and Technology, Tehran 13114-16846, Iran
Saeed Mirzamohammadi: School of Industrial Engineering, Iran University of Science and Technology, Tehran 13114-16846, Iran
Ali Bonyadi Naeini: School of Management, Economics and Progress Engineering, Iran University of Science and Technology, Tehran 13114-16846, Iran
Ali Maleki: Sharif Policy Research Institute (SPRI), Sharif University of Technology, Azadi Street, Tehran 14588-89694, Iran
Saleh Mobayen: Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu 64002, Taiwan
Paweł Skruch: Department of Automatic Control and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland

Energies, 2022, vol. 15, issue 12, 1-17

Abstract: Given the various advantages of electric vehicles compared to conventional gasoline vehicles in terms of energy efficiency and environmental pollution (among others), this paper studies the factors affecting customers’ willingness to purchase electric vehicles. An integrated discrete choice and agent-based approach is applied to model the customers’ choice for the valuation of electric vehicles based on the internal reference price. The agent-based model evaluates customers’ preferences for a number of personal and vehicle attributes, according to which vehicle they chose. Data from 376 respondents are collected to estimate a random-parameter logit model where customers are asked to reveal their preferences about five attributes of electric vehicles, including travel range, top speed, charge cost, government incentives, and price. The role of social networks of customers and their threshold purchase price is also examined in the agent-based model. The scenario simulation results indicate that the allocation of government incentives for electric vehicles, decreasing electric vehicle/non-electric vehicle price gap, expanding electric vehicle travel range, increasing gasoline prices, and enhancing electric vehicle top speed stimulate electric vehicle market shares, respectively.

Keywords: agent-based model; discrete choice model; electric vehicles; market research; transport policy; willingness to pay (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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