How well can early adopters of electric vehicles be identified?

Patrick Plötz,Till Gnann

doi:10.3390/wevj6040928

Abstract

Electric vehicles have recently been introduced to market in Europe. Policy makers as well as car manufacturers have great interest to understand the first group of electric vehicle users, the so-called ‘early adopters’. Several studies have tried to determine the potential early adopters of electric vehicles from different angles. However, the number of available studies is limited and little is known about the actual statistical significance of characteristics for this important user group. Here we characterize the potential first users of electric vehicles from an economic perspective and ask which driving profiles make an electric vehicle cost-effective. To this end, we analyze a large database of German driving profiles and find the share of potential first users from different city sizes and statuses of employment. We first find the potential and in a second step study the statistical significance and robustness of the result by (1) performing Chi-square tests of the differences between potential early adopters and other vehicle owners and (2) varying important input parameters of our estimates. We find our characterization of the early adopters to be robust if battery prices and consumption costs are sufficiently favorable for a not too small group of users.

Highlights

Electric vehicles (EVs) are an innovative propulsion technology that can help to reduce green house gas emissions from the transport sector as well as local emissions [1, 2]
For the identification of potential early adopters we follow the methodology of Biere et al [9] and study the statistical significance of the approach in detail
The main point of our study is to determine whether a potential group of users in our sample shows higher likelihood of buying an EV than could be expected from their share of car ownership is more than a result of random fluctuations

Summary

Introduction

Electric vehicles (EVs) are an innovative propulsion technology that can help to reduce green house gas emissions from the transport sector as well as local emissions [1, 2]. Electric propulsion is more efficient than propulsion via internal combustion engines and can support the shift from oil to other energy sources [1, 3]. Reliable estimates of the characteristics of future consumers of EVs are still limited [5, 6, 7] and the actual significance of these studies is disputable. The goal of the present paper is to test the significance of different user groups’ characterization as potential early adopters. For the identification of potential early adopters we follow the methodology of Biere et al [9] and study the statistical significance of the approach in detail. The main point of our study is to determine whether a potential group of users in our sample shows higher likelihood of buying an EV than could be expected from their share of car ownership is more than a result of random fluctuations

Objectives

Results

Discussion

Conclusion