User satisfaction with battery electric vehicles in South Korea

https://doi.org/10.1016/j.trd.2020.102306Get rights and content

Highlights

  • This study explores influential factors on battery electric vehicle (BEV) users’ satisfaction.

  • BEV users satisfaction survey was conducted.

  • Operational cost-saving intention is a key factor for enhancing the level of satisfaction.

  • Satisfaction with range and charging is closely associated with user satisfaction.

  • BEV user satisfaction, intention to repurchase and recommend are positively inter-related.

Abstract

Battery electric vehicles (BEVs) have been promoted by the government over the last several years, driven by public concern over pollutant emissions from internal combustion engines. However, the conditions related to driving BEVs are not yet satisfactory for many BEV users, as evident from sluggish market growth compared with general market forecasts. Thus, a fundamental aspect of diagnosing the current conditions of BEV operation is to evaluate BEV user satisfaction. This study establishes hypothetical links between potential factors and BEV user satisfaction, and between BEV use satisfaction and intention to repurchase and recommend. The hypothetical links are specified using a partial least squares structural equation model (PLS-SEM) and estimated based on a survey of actual BEV owners (N=160) who had driven BEVs for at least six months. The outcomes of PLS-SEM suggest that seven relations out of nine hypothetical links were statistically significant. In particular, it is noticeable that the intention for cost-saving during operation is a key factor for BEV user satisfaction and that user satisfaction with range and charging has a positive effect on the overall satisfaction of BEV users. Furthermore, those who are satisfied with BEVs have the intention to repurchase and recommend BEVs to others. Because this study was conducted based on actual experience of BEV users, the findings could enhance understanding of the BEV driving environment and, thus, pave the way to provision of better service for BEV users.

Introduction

In the past decade, battery electric vehicles (BEVs) have drawn attention as a potential solution to environmental issues in the transportation sector, which is heavily dependent on fossil fuels. Consequently, many countries have promoted BEVs and have gradually substituted BEVs for internal combustion engine vehicles (ICEVs). Hence, the number of registered BEVs has increased from 16.42 thousand in 2010 to 1208.9 thousand in 2016, which is 1.1% of the global automobile market (Global EV Outlook 2017, IEA). This growth has recently become more prominent, driven by the diminishing cost of BEV technologies, prevalence of charging facilities, various incentives and the diversity of BEV models in the market (Liu et al., 2017).

As more BEVs have been sold, more drivers have experienced BEV technologies. The attitudes of these experienced drivers can help us to diagnose the current status of BEV operation and, consequently, to formulate realistic and effective strategies for BEV promotion. A direct way of understanding user attitudes is to evaluate user satisfaction and its relationship with various influential factors. To this end, consumer satisfaction surveys are widely used for post-choice evaluation of specific products, because satisfaction is inevitably tied to the purchase and consumption of a product (Day, 1984, Oliver, 2014).

In the traditional automotive industry, many consumer-satisfaction studies have already been conducted to provide better service for ICEV users (Jahanshahi et al., 2011, Jajaee and Ahmad, 2012). In these studies, satisfaction has been evaluated for various dimensions, such as purchase-related attributes, vehicle performance and operational environment. However, the outcomes of ICEV satisfaction studies are not transferable to BEVs because BEVs differ from ICEVs in operational and technological aspects such as source of propulsion, fuel type and charging/refuelling (Brennan and Barder, 2016).

Only a few studies have been conducted using data collected from actual BEV users, although extensive research has been done to understand potential consumer perceptions of BEVs because BEVs have recently become available (Figenbaum and Kolbenstvedt, 2016, Ouyang et al., 2018, Helveston et al., 2015). Recent studies have mainly focused on evaluating actual purchasing behaviour of consumers or on identifying factors that influence the adoption of BEVs (Mersky et al., 2016, Simsekoglu, 2018, Lee et al., 2019, Hardman and Tal, 2016). In addition, research on usage behaviour of BEV users—such as charging (Flammini et al., 2019) and travel patterns (Han et al., 2016)—is gradually being conducted. Through these studies, there has been considerable progress in understanding the behaviour of those purchasing and using BEVs.

However, the studies of consumer attitudes toward and levels of satisfaction with BEVs are still insufficient and there are many behavioural changes that need to be revealed. This is simply because there have not been many BEV users with sufficient experience with BEVs—at least six months of experience—to evaluate post-purchase behaviour (Igbaria et al., 1996). Most previous studies focused on strategies to promote the widespread adoption of BEVs rather than on evaluating and improving the operational environment of BEVs.

To shed light on this, we performed face-to-face surveys of actual BEV owners to evaluate their satisfaction levels and potential factors influencing satisfaction. Additionally, we considered their intentions to repurchase or to make recommendations. In the remainder of this paper, Section 2 provides an in-depth literature review and builds hypotheses among the attributes of BEV operation, satisfaction and intention to repurchase and recommend. Section 3 describes the survey data and the partial least squares structural equation model (PLS-SEM). Section 4 documents the outcomes of the PLS-SEM and Section 5 presents a discussion of the findings and implications for strategies to promote BEVs.

Section snippets

Literature review and hypotheses development

Satisfaction is a direct and widely used measure for diagnosing the conditions of use of a certain product. Because these are not directly observed, consumers are asked about their levels of satisfaction with a product, with answers given on Likert or interval scales in survey questionnaires (Hill and Alexander, 2017, Kwon et al., 2020). The factors that affect the level of satisfaction are latent and psychological. In this section, based on a literature review, we identify potential

Data collection and description

In this study, an offline-based questionnaire was developed and responses were collected via face-to-face surveys from BEV users in South Korea1

Analysis methods and results

In this study, hypotheses were verified using a variance-based partial-least-squares structural equation model (PLS-SEM). Two types of structural equation model (SEM) are commonly used as statistical techniques to verify correlations and hypothetical causal relationships between variables. The first is a covariance-based structural equation model (CB-SEM); the other one is the PLS-SEM (Hair et al., 2011). Unlike the CB-SEM model, which conducts estimation using maximum likelihood (ML), PLS-SEM

Summary and conclusions

BEVs have been actively promoted in the recent automotive market. However, actual BEV user studies, which can directly diagnose the current status (i.e., level of satisfaction) of BEV use and help formulate a strategy for planning and operating BEVs, are not sufficient. Therefore, this study evaluated potential factors that affect BEV user satisfaction and the consequential effects of satisfaction on the intention to repurchase and recommend. To this end, we constructed a hypothetical structure

CRediT authorship contribution statement

Yeongmin Kwon: Conceptualization, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing - original draft. Sanghoon Son: Data curation, Resources. Kitae Jang: Conceptualization, Funding acquisition, Project administration, Supervision, Writing - review & editing.

Acknowledgment

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (NRF-2019R1A2C2008161).

Declaration of Competing Interest

The authors declare that there is no conflict of interest regarding the publication of this paper

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