Consumer Perceptions in the Alternative Fuel Vehicle Market: A Systematic Literature Review and Bibliometric Analysis ^†

Abstract

The use of alternative fuels is a crucial element in achieving global sustainability, as it plays a pivotal role in reducing the environmental impact of the transport sector. This study aims to provide a comprehensive and systematic review of the literature on consumer knowledge and awareness of alternative fuel vehicles (AFVs) in accordance with the PRISMA guidelines and bibliometric analysis. The findings indicate that electric vehicles represent the dominant focus of AFV research, while other technologies receive minimal attention. The study underscores the necessity for targeted information strategies to address consumer misconceptions and overcome market barriers, thereby facilitating the growth of AFV market share. This research offers insights that can inform future studies, policy decisions, and industry stakeholders in promoting sustainable transport choices.

1. Introduction

The growth of the market for alternative fuel vehicles (AFVs) is key to global environmental sustainability, as they can make a significant contribution to reducing greenhouse gas emissions from transport [1,2]. AFVs, especially electric vehicles, hydrogen fuel cell vehicles, and other clean energy technologies, have a role to play in the future of green transport. However, the uptake of such vehicles depends largely on consumer perceptions and attitudes, which are also key to the successful market introduction of new technologies. Electric vehicles (EVs) are the most popular alternative means of propulsion today. Electric vehicles are considered one of the most important green technologies [3]. The global EV market has adapted to the growing environmental concerns of consumers and governments. Global sales of plug-in electric light vehicles (PEVs) more than doubled between 2020 and 2021. This market diversity affects consumers in different ways, influencing their perceptions of electric vehicles and the drivers for PEV purchases [4]. When consumers consider buying a vehicle, they intuitively take several factors into account. For example, some studies point out that the high initial cost of AFVs, the lack of charging infrastructure, and the lack of knowledge often hinder consumer adoption [5]. However, environmental awareness and openness to technological innovations positively influence the interest in AFVs [6]. Therefore, it is natural to try to explain consumer acceptance of alternative powertrains by using analytical tools that consider multiple dimensions of reality, in particular objectively quantifiable factors such as costs and usage constraints. Several studies have shown that the cost of ownership, range, availability of charging infrastructure, and charging time are the most important factors influencing the adoption of EVs [7]. The adoption and use of new technologies is essential in modern industries, especially in the automotive sector, where continuous innovation is key. The modeling of technology adoption and the study of related consumer behavior is an emerging research topic [8,9,10]. Previous studies have shown that user adoption or rejection depends on a few factors such as personality traits, attitudes towards technology, demographic characteristics, and consumer behavior [11,12]. One of the most comprehensive models that has attempted to unify the key factors of technology acceptance is the Unified Theory of Acceptance and Use of Technology [13], which have been widely used in the automotive industry [11]. Technology acceptance models have also shown that, when introducing new technologies, personal perceptions and attitudes become key factors in consumer decision making. Therefore, future research should better understand the social and psychological drivers of technological innovation in order to better design and introduce new technologies [14].

The aim of this research is to prepare a systematic literature review and meta-analysis along the PRISMA guidelines. For this purpose, the study conducts a bibliometric analysis of the scientific literature on the adoption of different alternative fuel vehicles (AFVs) to identify the most frequently discussed topics and keywords, and to explore the interconnections between keywords and research trends. Consequently, the following research questions were formulated:

• RQ1: What are the most frequently used keywords in the literature on the acceptance of AFVs?
• RQ2: What are the most common relationships between keywords in the literature on AFVs?
• RQ3: What dominant themes and clusters emerge in the literature on AFVs?

2. Materials and Methods

The study prepared a systematic literature review along the PRISMA guidelines. The PRISMA model is a widely recognized framework for conducting systematic reviews and meta-analyses of research. The PRISMA guidelines were formulated in 2009 and have since undergone several updates to keep pace with evolving methodologies and reporting requirements in this area [15,16]. The primary aim of the PRISMA model is to enhance the transparency and completeness of reporting in systematic reviews, thereby improving the overall quality and reliability of these studies. The PRISMA framework provides a checklist of 27 items that authors should consider when preparing a systematic review [17,18].

In the present study, a search of the Web of Science database was undertaken. The keywords used for the search were variations of different alternative fuel vehicles and consumer attitudes: (“alternative fuel vehicles” OR “AFV” OR “electric vehicles” OR “hydrogen vehicles” OR “hydrogen fuel cell vehicles” OR “hydrogen fuel-cell vehicles” OR “HFCV” OR “hydrogen internal combustion engine” OR “HICEV” OR “hybrid vehicles” OR “clean energy vehicles”) AND (“consumer acceptance” OR “consumer adoption” OR “consumer attitudes”). The precise but consistent use of keywords is very important, as the study aims to assess not only consumer perceptions of one type of vehicle but also the acceptance of different types of alternative fuel vehicles. This stems from the assumption that the acceptance of a more widely known electric vehicle may be higher than, for example, a less common hydrogen vehicle.

The keyword search yielded a total of 262 results. The period considered was 2020–2024, which already contained fewer publications, at 154 publications. Further filtering was applied by research area, with the inclusion criterion being that the research area was business economics. A further inclusion criterion was that the publication type was articles, resulting in 40 records, all in English (the exclusion criteria would have been a language different from English). The results of the search using the inclusion and exclusion criteria are illustrated in the following Figure 1.

3. Results and Discussion of Bibliometric Analysis

Figure 2 shows the keywords of the scientific publications on the adoption of alternative fuel vehicles. The colors and the network connections help to understand which topics and keywords dominate in the literature under review, and the strength and frequency of the links between them.

The analysis (Figure 2) shows that, in the literature reviewed, networks are built around the following three main keywords: electric vehicles, adoption, and consumer attitudes. Several types of vehicles appeared in the search domain, such as hydrogen vehicles, hybrid vehicles, and clean energy vehicles; however, the keyword “electric vehicles” dominates, being the largest cluster in the figure. Other alternative types appear to a small extent in the relationship map, with electric vehicles being the most frequently discussed topic in the literature. Electric vehicles therefore play a very dominant role in the research. This may also reflect the focus of interest from the consumer and research side, as well as the corporate side, which may be strongly influenced by the relatively advanced state of the technology and its frequent media coverage. The keywords most often associated with electric vehicles are “adoption”, “policy”, “barriers”, and “consumer attitudes”. One of the objectives of network analysis is to identify the relationships and background factors. The research considers not only technological but also social, economic, and political aspects. The process of “consumer acceptance” and “adoption” is closely linked to electric vehicles. Based on this analysis, much of the research focuses on understanding what factors influence consumer acceptance and actual purchase decisions. Consumer attitudes, including environmental awareness, openness to technological innovations, and personal preferences, are key determinants of the process of acceptance and adoption.

Furthermore, network analysis organizes keywords into clusters. In the case of this research, four clusters emerged. In the green cluster, “electric vehicles” is central, while “policy” and “infrastructure” are also key factors. The green cluster therefore mainly covers environmental and infrastructure research. The blue and red clusters mainly represent consumer-oriented research. In the blue cluster, the consumer plays the central role. The main factors are “acceptance”, “consumer attitude”, and “preferences”. The red cluster is also related to the consumer, with “consumer attitude”, “acceptance”, and early technology use. So, these studies best summarize the model of acceptance of new technologies, with a particular focus on alternative propulsion vehicles. While it is true that the study of electric vehicles dominates, the technology acceptance models identified towards them may also be relevant for other AFVs. Sustainability aspects of the topic should also be considered. AFVs typically aim at reducing negative impacts on the environment. The purple cluster brings together research that has specifically addressed the environmental aspects of the topic. This cluster includes the theory of environmental concerns and planned behavior, which integrates environmental factors that influence adoption.

The keyword map illustrated the strength and structure of the relationships. Figure 3 below shows the frequency and concentration of keywords.

This density map shows that the keyword “electric vehicles” appears with the highest density, further confirming the dominance seen in the previous network map. The density map also visually highlights the areas of greatest interest in research. The yellow areas indicate the highest keyword concentrations, with the highest densities around the keywords “electric vehicles”, “adoption”, and “consumer attitudes”. This is in line with the previous figure, where the keywords displayed were central to the network. Overall, the density map and the network map together provide a comprehensive picture of the current state of the art in the field of alternative fuel vehicle research. The visual representation of the frequency and interconnections of keywords helps to understand research trends, major themes, and their interconnections.

4. Conclusions

4.1. Conclusions from the Bibliometric Analysis

At the beginning of the research, three research questions were formulated to identify the most used keywords, the relationships between keywords, and the dominant themes and clusters emerging in the scientific literature. The study answered all three questions. The conclusions drawn from the results are presented below.

The keyword network of the bibliometric analysis provided an excellent illustration of the dominance of electric vehicles in research. This suggests that this is the area of greatest research and consumer interest. It may also imply that electric vehicles are at the center of research because of their prevalence and awareness. The results suggest that electric vehicles are most likely to be known and adopted by most consumers. Technologies such as hydrogen vehicles may still seem too distant for consumers. Such new technologies are most likely to be positively received by the early-adopter group, while other consumers need more time. Future research should continue to focus on the adoption of electric vehicles and the challenges associated with this, but not exclusively. It is important that research should not only cover electric vehicles but also other alternative fuel vehicles such as hydrogen vehicles. This is to obtain a more comprehensive picture of market trends and to help future adoption. Today, hydrogen buses are already used in public transport and some passenger car manufacturers are also involved. It would certainly be useful to assess consumers’ knowledge and perceptions, even in comparison with electric vehicles. If hydrogen becomes the technology of the future, early attitudes and acceptance studies could greatly facilitate its market introduction/spread. Consumer attitudes are essential before the introduction of new technologies, as they have a major impact on market penetration.

4.2. Research Limitations and Directions

Although this study offers a comprehensive overview of consumer perceptions regarding the alternative fuel vehicle market, several avenues for further research emerge. For instance, additional content analysis and meta-analysis of the literature reviewed could enhance the comprehension of particular consumer attitudes and knowledge gaps pertaining to diverse types of AFVs, extending beyond electric vehicles. Furthermore, future research should investigate the social and psychological factors that influence the adoption of lesser-known technologies, such as hydrogen fuel cell vehicles. The study is limited by its narrow temporal scope and its exclusive reliance on publications in the Web of Science database. Extending the timeframe and including additional databases could yield a more diverse array of research results.

There are two further objectives for future research directions. Firstly, a detailed content analysis and meta-analysis of the literature sources examined in this study, which are still incomplete due to scope limitations, is essential. Subsequently, a primary questionnaire survey will be conducted, focusing on consumer knowledge and attitudes towards alternative vehicle technologies. The questionnaire is logically divided into the following four main parts: general driving habits, subjective knowledge of alternative driving technologies, objective knowledge of alternative driving technologies, and demographic characteristics.