1. Introduction
Petroleum extraction and the application of combustion engines, allowing both power and economy of the gasoline engine, have become an essential automotive power, automobile manufacturing technology is widely popular and applied across the world, and the automobile has become a significant means of transportation. Based on statistics from China’s Ministry of Public Security, China’s automobile fleet grew to 307 million by end of March 2022 [
1]. Increasing numbers of automobiles create enormous petroleum demand. In 2022, the China Energy Research Institute released a report showing that China’s apparent petroleum consumption reached 715 million tons in 2021 [
2]. This enormous demand resulted in much focus on its price. International petroleum prices also rose sharply from 2020 to June 2022, subject to political military conflicts, new coronavirus epidemics, and supply–demand conflicts [
3], and domestic petroleum prices rose by 70%from 6800 per ton in November 2020 to 11,600 per ton in June 2022 [
4,
5]. The significant increase in petroleum prices raises the cost of motorized travel and induces travel behavior or vehicle choice changes [
6,
7]. Additionally, air pollution, the greenhouse effect, and respiratory diseases caused by heavy automotive usage are increasingly prominent.
With the breakthrough of the automotive sector restructuring the industry to tackle the rising gasoline prices, energy crisis, environmental pollution, and other issues, new energy vehicles (NEVs) with economic, energy-saving, and environmental protection features have emerged as new trends. The advent of NEVs has given individuals more alternatives under fluctuating fuel prices. According to the “New Energy Vehicle Industry Development Plan (2021–2035)”, NEVs in China’s passenger car market mainly include pure electric vehicles and plug-in hybrid (including extended-range) vehicles (PHVs). The goal is to reach 20% sales by 2025 and mainstream the sales of pure electric vehicles by 2035 [
8]. Therefore, against the backdrop of enormous development opportunities, numerous scholars have conducted empirical research on whether consumers are willing to purchase NEVs, further exploring the audience of NEVs in the passenger car market. These studies have mainly explored the factors that affected consumer purchase intention, and gasoline price is one of the numerous factors that have been focused on by scholars. For example, Shafiei et al. [
9] found that when gasoline prices rise, NEV prices decrease, and there is no range anxiety, so consumers are more inclined to purchase NEVs. Sun et al. [
10] found that when gasoline prices rise and the price increase of NEVs does not exceed CNY 27,000, car owners are more inclined to purchase pure electric vehicles. With gasoline prices reaching an unprecedented high in February–March 2022, a total of 6200 comments were collected by trawling the comment data from online media. A text network analysis was plotted through text co-word matrix analysis and is presented in
Figure 1. The following outcomes surface: topics such as electric vehicles, gasoline prices, and charging time become hot topics of user and media attention, and the charging infrastructure facilities for NEVs are also an essential factor considered by consumers. Thus, consumers will consider more factors when considering whether to purchase NEVs. Current studies generally focus on factors such as gasoline prices’ impact on NEV purchase intentions, but empirical research on individuals’ willingness to switch mode choices is lacking; research has shown that switching intentions are not equivalent to purchase intentions and that their intrinsic mechanisms are distinct [
11,
12,
13]. Moreover, research on gasoline prices has focused on objective facts, but without understanding the changes in consumer perception of gasoline prices from psychological perspectives. Against the background of the sharp rise in gasoline prices reaching high levels, there are significant theoretical implications and practical value in testing the willingness of individuals to switch from fuel vehicles to NEVs.
The sharp rise in gasoline prices may drive switching to NEVs. Government subsidies for vehicle purchases are retreating each year and will be eliminated by the end of 2022, which may hinder people from switching to NEVs. Through text network analysis, it has been found that charging time and charging infrastructure are also key factors of concern for consumers. Promoting NEVs has become an important measure for the automotive industry to reduce emissions against the backdrop of “dual carbon development”. During the critical period when multiple factors including high gasoline prices, subsidy policy removal, and low-carbon development are at play, it is urgent and crucial to investigate individual psychological needs for NEVs. This will help predict individuals’ switching travel behavior and environment protection attitudes and effectively predict the future market share of NEVs, assisting companies in developing appropriate marketing plans and providing a basis for policymakers. This paper empirically studies the intention of individuals aged 18 and above to adopt NEVs from consumers’ perspectives on factors including rising gasoline prices and subsidy policy removal. Considering that NEVs are not individuals’ preferred means of transportation, this study focuses on behavior changes and exploring whether they are willing to switch from fuel vehicles to NEV.
Social cognitive theory (SCT) is among the crucial theories to illustrate individual behavior change, highlighting the interaction between behavior, the individual, and the environment [
14], and is widely applied to knowledge sharing behavior [
15,
16]. Boateng et al. [
17] applied SCT to internet banking technology adoption studies and showed that trust and social characteristics significantly affect the intention to use online banking systems. SCT can provide theoretical foundations for effectively assessing individuals’ decisions to switch to NEVs under the effects of gasoline prices. Nevertheless, few studies have investigated this theory in NEV adoption behavior. Therefore, the model was constructed from the environment and personal factors, and we added perceived risks and infrastructure barriers to deeply analyze the crucial factors of personal intention towards switching to NEVs. In addition, structural equation modeling can test the correlation between variables based on theoretical knowledge by fitting assumptions and data information, but it cannot directly determine causal relationships between variables. Moreover, if the relationship between the independent and dependent variables is non-linear, SEM may lead to a decrease in prediction accuracy. To address these limitations, the nonlinear relationships are further analyzed by employing Bayesian networks (BN) to test for causal relationships between variables and provide strong inferential knowledge evidence for dealing with uncertain relationships in SEM. Therefore, this study integrates structural equation modeling (SEM) and Bayesian network (BN) research methods to verify the causal relationships between elements, which provides decision-making support to reveal the factors affecting individuals’ switching intention to NEVs.
The studies contribute to:
Analyzing the mechanisms that affect consumer switching to NEVs despite record high fuel prices and the imminent elimination of vehicle purchase subsidies, and providing insights into green behavior in the context of “dual carbon” development goals;
The first application of SCT to construct a theoretical framework of consumer switching intention to NEVs, integrating structural equation modeling and Bayesian network causality modeling methods to diagnose key factors and provide effective countermeasures for the future formulation of relevant policies and measures to increase the market share and usage of NEVs.
The remainder of this paper is structured as follows.
Section 2 provides the theoretical framework and research hypotheses.
Section 3 shows the questionnaire design, data collection process, and research methods.
Section 4 presents the results of the research.
Section 5 contain discussion and policy implications.
2. Theoretical Framework and Research Hypotheses
According to SCT, human behavior is primarily driven by environmental and personal influences [
14]. Bandura indicates that environmental factors are categorized into the micro-environment of family, friends, and neighbors and the macro-environment of social, economic, cultural, and legal aspects [
18]. Subjective norms are categorized as significant environmental factors in numerous SCT works [
19,
20,
21]. Subjective norms enable individuals to be more likely oriented to healthy behaviors, including knowledge sharing activities [
22], social networking posts [
21], video course participation [
19], etc. Against the background of SCT, Guo [
23] believed that the natural and social environments constitute the environmental factors that influence people’s perceptions and behaviors toward green consumption, while environmental consciousness is perceived as a social attribute of individuals [
24]. In addition, Zhao et al. [
25] proposed new insights based on SCT that social face consciousness can influence engaging in corrupt behavior. Drawing on previous studies, this study chose subjective norms reflecting the effect of surrounding relatives, friends, and news, environmental consciousness indicating individual social attributes and pro-environmental behaviors, and face consciousness representing social status as significant environmental factors that may influence individuals’ intention to switch to NEVs.
In terms of individual factors, outcome expectations and self-efficacy are two representative factors. Outcome expectations are beliefs about expected outcomes that individuals believe arise under specific conditions [
26]. Lin and Chang [
27] argue that outcome expectations can be categorized into different types by scenario characteristics. Within this, the perceived benefits and rewards of initial expectations are considered the most common individual psychological determinants in SCT [
28]. Both are variables whose remarkable effects on users’ behavioral intentions have been confirmed in numerous studies [
15,
16,
21,
22]. Bandura indicated that attitudes could serve as personal internal beliefs that drive and regulate behavior. This was also confirmed in Zhou and Hsiao’s studies; individuals’ attitudes toward behavior directly influence learning behavior using YouTube and continuous participation in courses using videoconferencing, while attitudes can mediate between environmental factors and individual actions [
19,
29]. As such, this study seeks to explore the interaction between initial expectations, perceived monetary benefits, self-efficacy, and attitudes as significant personal cognitive factors and environmental factors, along with the impact on individuals’ intention towards switching to NEVs. Meanwhile, infrastructure barriers and perceived risks will be incorporated into the model to examine whether people’s perceptions regarding the quality of NEVs and the associated charging facilities will prevent them from switching to NEVs.
In conclusion, based on SCT, this research focuses on two major perspectives, environmental factors and personal factors, to explore the important factors that may affect individuals’ intention to switch to NEVs. The theoretical framework is shown in
Figure 2.
2.1. Environmental Factors
2.1.1. Subjective Norms
Subjective norms (SN) are an important environmental factor in SCT that refer to the degree of social pressure individuals feel when implementing or not implementing a behavior [
30,
31]. Setiawan et al. [
32] believe that this social pressure originates from friends, family members, and others in the community. Battacherjee [
33] suggests that subjective norms contain influences from external sources such as news reports, mass media, etc. It has been confirmed in studies by Screen et al. [
34] that when consumers are uncertain about the outcome of their behavior, they might decide based on media reports or seek others’ opinions. Yen [
21] explores the influence of subjective norms as a significant factor in SCT on posting behavior on social networking sites. Van Tonder et al.’s [
35] studies indicated that subjective norms positively influence consumers’ green attitudes, thereby generating positive green consumption intentions.
Subjective norms refer to the pressure that household residents perceive from their surrounding relatives or friends and news reports when choosing NEVs in this study (for example, the opinions of relatives and media reports about NEVs will have substantial effects on my decision). Wang et al. [
36] indicated that subjective norms positively and significantly affect individuals’ intentions for green product purchases. Subjective norms representing societal pressures were confirmed to affect consumer intentions toward purchasing NEVs in a study of NEV purchase intentions [
37]. Therefore, our study considered that individuals who are skeptical about new technological product quality, among other things, are more susceptible to news reports and relatives or friends when they consider adopting NEVs. The following assumptions are proposed based on the above.
Hypothesis (H1). Subjective norms have a positive impact on self-efficacy.
Hypothesis (H2). Subjective norms have a positive impact on attitudes.
Hypothesis (H3). Subjective norms have a positive impact on switching intentions.
2.1.2. Environmental Consciousness
Environmental consciousness (EC) refers to the formation of the conservation concept through direct attention to issues and learning about environmental protection, which will affect people’s knowledge, attitude, intention, and action [
38,
39,
40]. According to Cerri and Tan’s study [
41,
42], environmental consciousness is a significant factor in exploring consumers’ pro-environmental behavior. Darvishmotevali and Altinay [
43] explore the effect of environmental consciousness as a factor in SCT on proactive support for environmental behavior and indicate that environmental consciousness plays a mediating role and significantly influences proactive support for environmental behavior. Zhang et al.’s [
44] studies indicate that environmental consciousness significantly affects consumers’ attitudes toward purchasing energy-efficient appliances and indirectly results in consumers’ willingness to pay premiums for energy-efficient appliances.
People with stronger social responsibility are more willing to implement green consumption behaviors, those who believe that green consumption brings positive outcomes are more inclined to consume green, and environmentally conscious people have a higher propensity to implement green consumption behaviors [
45,
46,
47]. NEVs have green product label characteristics for their cleaner power sources, higher energy efficiency conversions, and stronger emission reduction and environmental benefits [
48,
49]. Degirmenci and Breitner [
50] concluded that environmental consciousness has stronger effects on attitudes and purchase intentions than price value and mileage confidence. This study defines environmental consciousness as the environmental value contribution and green identity embodiment that residents expect from switching to NEVs, advantages that fuel vehicles do not have. Hypotheses are proposed below.
Hypothesis (H4). Environmental consciousness has a positive impact on attitudes.
Hypothesis (H5). Environmental consciousness has a positive impact on switching intentions.
2.1.3. Face Consciousness
Chinese people with a background of collectivist values care about others’ perceptions and are more interested in showing others their identity, namely face consciousness. Face consciousness (FC) refers to the desire of individuals to enhance, maintain, and avoid losing their self-image when interacting socially [
51]. In this study, face consciousness is defined as selecting NEVs as a behavior to highlight status and identity. In SCT research, Zhao et al. [
25] found that social face consciousness affects individuals’ intention to engage in corrupt behavior. Influenced by Confucian culture, Chinese people’s consumption values are more easily shaped by face consciousness [
52,
53]. Highly face-conscious people are more eager to gain praise and recognition from society members and prefer products that highlight their status in the consumption process, such as buying branded products, etc. [
54,
55]. Regarding face consciousness and pro-environmental behavior, since people who perform pro-environmental behavior show their environmental literacy and cast positive images on society and others, people with high face consciousness are more willing to perform pro-environmental behavior to obtain respect from others [
56,
57]. Compared with fuel car users, people who use NEVs may feel “superior” in their social circle, which may derive from a positive image and social prestige. In summary, Hypotheses 6 and 7 are proposed.
Hypothesis (H6). Face consciousness has a positive impact on attitudes.
Hypothesis (H7). Face consciousness has a positive impact on switching intentions.
2.2. Personal Factors
2.2.1. Perceived Monetary Benefit
Perceived monetary benefit (PMB) refers to the possibility that an individually perceived action will produce a positive outcome in terms of economic benefits [
58]. In detail, individuals behave in ways they believe will generate the expected results and concentrate on aspects that will increase their economic benefits. When people are convinced that their behavior benefits them financially, they strengthen their behavioral intentions [
59]. Davenport and Prusak [
60] conclude that individuals compare the costs of their behavior with the external rewards of their behavior before sharing knowledge; individuals are willing to share knowledge only when they expect the rewards to outweigh the costs. In SCT, Wang et al. [
24] indicated that perceived monetary benefits significantly affect changes in behavioral patterns.
In this study, the perceived monetary benefit refers to the perceived economic cost savings that consumers experience when switching from gasoline to new energy vehicles. Electric vehicles (EVs) powered by electricity are more affordable to travel with compared to fuel vehicles [
61]. The perceived reduction in travel costs from EVs is more pronounced when gasoline prices rise sharply and remain elevated. The higher the desired cost reduction, the higher the perceived monetary benefit [
44]. Wang and Zhang et al. [
62,
63] showed that perceived monetary benefits have a significant positive impact on consumers’ purchase intentions and are the crucial path that affects consumer purchase intentions. The most direct manifestation of the benefits is not only gasoline prices but also vehicle prices, government purchase subsidies, and tax incentives. Consumer perception of the benefits before moving to new energy vehicles is an essential prerequisite for the switching intention to occur. The following Hypotheses, 8 and 9, are proposed.
Hypothesis (H8). Perceived monetary benefit has a positive impact on self-efficacy.
Hypothesis (H9). Perceived monetary benefit has a positive impact on switching intentions.
2.2.2. Self-Efficacy
Self-efficacy (SE) refers to speculation and judgment by action subjects on whether the self can achieve goals [
64,
65]. In SCT, self-efficacy is an effective driver of individual behavior. Tsai et al.’s studies indicated that self-efficacy directly affects user intention to share knowledge [
16]. Some studies also concluded that individuals with higher self-efficacy have more confidence in their abilities, are more committed to their behavior in the face of difficulties, and, therefore, are better able to control the implementation of their behavior [
66].
This study defines self-efficacy as consumers being able to directly and effectively perceive whether they have the strength and ability to switch to NEVs. Lin et al. [
67] showed that self-efficacy promotes green consumption behavior positively and that enhanced self-efficacy in green consumption is a core element in determining whether green consumption is implemented. Consumers with high self-efficacy are confident in their abilities and will try hard to complete their purchases [
68]. In this studied scenario, even if consumers tend towards pro-environmental behavior, assessments on the degree of difficulty in switching to NEVs should be at the top of the list, and these assessments cover convenience, economic status, etc. Especially when gasoline prices rise, subsidies are removed, vehicle prices fluctuate, etc., consumers’ evaluation of their economic situation will heavily determine whether or not to purchase NEVs and switch their travel mode. Thus, we propose the following hypotheses.
Hypothesis (H10). Self-efficacy has a positive impact on attitude.
Hypothesis (H11). Self-efficacy has a positive impact on switching intentions.
2.2.3. Attitude
Attitude (ATT) is the psychological state that reflects an individual’s preference or dispreference for specific things [
18,
69]. This research refers to the favorability of individuals switching to NEVs. The SCT suggests that an individual’s attitude toward behavior can accurately predict their intention to engage in that behavior [
69,
70]. Lin and Lee found that knowledge sharing attitudes were significantly associated with encourage knowledge sharing intentions [
22].
A study of consumers’ intentions to switch from BS4- to BS6-compliant vehicles with emission standards in India found that consumers’ attitudes towards BS6 vehicles with emission standards were associated with environmental protection preferences, and consumers holding positive attitudes towards environmental protection would prefer BS6 vehicles [
71]. This study hypothesizes that individual attitudes regarding the environment and fuel prices will reflect their psychological attitudes toward using NEVs, with favorable feelings toward NEVs motivating them to abandon their existing fuel vehicles in favor of NEVs. Therefore, we propose Hypothesis 12.
Hypothesis (H12). Attitude has a positive impact on switching intentions.
2.3. Perceived Risk
Perceived risk (PR) refers to the unpredictability of the outcome perceived by individuals when accepting new technology or using new services [
72]. It is strongly subjective; if an individual perceives risks in this behavior, then his final decision-making may be affected. Currently, scholars prefer to link “perceived risk” to consumer psychological activities during the purchase process. Kamal and Chen et al. [
73,
74] indicated that consumers affected by perceived risk largely change, delay, or cancel their purchase decision making. Mitchell [
75] concluded that consumers are more inclined to risk aversion rather than maximizing their benefits when purchasing products, which makes the explanation of perceived risk in consumer behavior stronger and more powerful. Multiple dimensions of perceived risk have been confirmed in studies of NEV purchase intentions to significantly negatively influence vehicle purchase intentions [
76,
77,
78]. Since NEVs involve many technological innovations, they are often accompanied by multiple dimensions of risk. In this research context, perceived risk is defined as the subjective assessment by individuals of negative effects that may be triggered by the adoption of NEVs, including fears about performance safety, long charging times, operational complexity, and other risks. These concerns will prevent them from choosing NEVs. Hence, Hypothesis 13 is proposed below.
Hypothesis (H13). Perceived risk has a negative impact on switching intentions.
2.4. Infrastructure Barrier
The infrastructure barrier (IB) refers to the degree of completeness in charging facilities for NEVs [
79]. This research refers to the individual perceived charging facility status of NEVs. As an essential ancillary facility for electric vehicles, the number and availability of charging stations are significant factors affecting the promotion of NEVs. The imperfection of charging facilities will lead to mileage anxiety among consumers, which, in turn, will affect the adoption of NEVs [
80,
81]. Numerous studies show that consumers are highly focused on the timely charging of NEVs; even individuals interested in NEVs will fear running out of power halfway through journeys if no sufficient charging infrastructure is provided within reasonable driving distances. This so-called “range anxiety” will inhibit the market spread of NEVs [
82,
83,
84]. In SCT research, Schade and Schuhmacher [
85] examined digital infrastructure as an external factor to explore its impact on entrepreneurial behavior and showed that digital infrastructure significantly drives entrepreneurial behavior. Wang et al.’s research indicates that improved infrastructure positively influences the intentions to purchase NEVs [
62]. In this research, the favorable perception of new energy vehicles indirectly reflects the demand for charging infrastructure, which will prompt individuals to take into account the infrastructure implications before switching to NEVs. Hence, Hypothesis 14 is proposed.
Hypothesis (H14). Infrastructure barriers have a positive impact on switching intentions.
5. Discussion
This study attempts to construct factor relation models of consumer vehicle SI from SCT in the context of record high fuel prices in China and the imminent removal of subsidy policy, and integrates structural equation modeling with Bayesian networks to quantify the effect degree and infer and diagnose the significant relationships between factors from the perspective of probability. The following section discusses the model results by dividing them into three sections.
For environmental factors, the SEM results show that subjective norms, environmental consciousness, and face consciousness have immediate significant effects on personal factors. They also showed that subjective norms and environmental consciousness exerted positive effects on consumer vehicle SI (
β = 0.114,
p < 0.05; β = 0.095,
p < 0.05). Face consciousness has a significant positive effect on consumer attitudes but a negative effect on switching intentions, which is inconsistent with previous results. We propose that this is related that market development characteristics. According to the 2022 auto industry production and sales released by the China Association of Automobile Manufacturers, China’s passenger car market is characterized by “high-end fuel vehicles and comprehensive NEVs” [
101]. The switch from fuel to NEVs does not provide consumers with a perceived improvement in image and status. Consistent with the conclusions of previous related SCT studies [
19,
20,
21], environmental factors serve an essential function in explaining changes in individuals’ behavioral intentions, while having significant direct effects on behavioral intentions. The Bayesian inference and diagnosis results showed that when the subjective norm and environmental consciousness nodes varied from the low to high level, the high-state vehicle SI presented an increasing trend; conversely, when the node switching intention was in the high state, the prior probability of high-level subjective norm and environmental consciousness rose from 24.6% and 80.1% to 28.3% and 86.3%. The sensitivity analysis shows that environmental consciousness exerts greater sway over switching intentions. These conclusions show that when gasoline prices rise sharply to break through to record highs, the perceived external environment will have consequences for the psychological tendency of vehicle switching intentions. Firstly, as a technological innovation product, NEVs are novel to consumers who have never come into contact with them, and most people have a cautious wait-and-see attitude toward new things. At this point, the positive evaluation of NEVs by surrounding friends and news reports will definitely affect consumers’ propensity to switching. In addition, emotional approval from family members makes significant contributions to consumers’ behavioral decisions; if the surrounding family members and friends favor NEVs, the individual’s intention to switch to NEVs will rise. Secondly, the power source of new energy vehicles is relatively clean, they have low emission pollution, and they are quiet compared to fuel vehicles. When consumers perceive and realize that the adoption of NEVs will preserve the environment, protect ecology, relieve fossil fuel dependence, and raise our quality of travel and living environment, they will then subjectively evaluate the behavioral activities of switching to NEVs, which will generate bright visions and expectations of switching to NEVs, and ultimately they tend to select NEVs as their usual travel mode in the future.
For personal factors, the SEM outcomes indicated that perceived monetary benefits, self-efficacy, and attitudes all significantly and directly affected personal vehicle SI (
β = 0.238,
p < 0.01;
β = 0.156,
p < 0.05;
β = 0.240,
p < 0.001). The direct effect of personal factors on behavioral intention alteration is shared with the conclusions of previous studies of SCT [
15,
16,
27]. The Bayesian inference and diagnosis showed that when perceived monetary benefit, self-efficacy, and attitude node switched from the low to high states, the high level of switching intention tended to rise. Moreover, the attitude and self-efficacy nodes were the sub-nodes that produced the maximum increase in switching intention. When switching intentions were in the low states, perceived monetary benefits, self-efficacy, and attitudes all showed an upward trend at low levels as well. The sensitivity analysis outcomes also reflect the significance of attitudes and self-efficacy. This indicates that personal factors play an invaluable role in consumer vehicle SI. As major adopters and purchasers of new energy vehicles, certain financial ability is the prerequisite, especially when factors such as rising gasoline prices, retreating subsidies, and vehicle price fluctuations affect the consumers’ financial capability related to purchasing and adoption. It is inevitable for consumers to evaluate whether they have sufficient financial capacity when making the behavioral switch to new energy vehicles for travel. The model also showed that infrastructure barriers positively promote consumer switching to NEVs (
β = 0.140,
p < 0.01), which is consistent with previous findings [
62]. The availability and convenience of charging infrastructure affect consumers’ vehicle switching intentions to some degree. Despite the fact that the perceived risk is not significant in this study, we believe that firstly, vehicle manufacturers have enhanced the security of new energy vehicles, secondly, positive government and corporate advocacy have contributed to the low perceived risk of new energy vehicles, and finally, the massive accumulation of users for new energy vehicles has generated a positive reputation in China.
In the Bayesian network model, the Bayesian inference and diagnosis results indicate that the factors of attitude, self-efficacy, environmental consciousness, and infrastructure barriers are crucial predictors of consumer intentions toward switching to new energy vehicles. This conclusion was further corroborated by the results of the sensitivity analysis. Meanwhile, the results of structural equation modeling confirm the correlation relationship between personal factors, environmental factors, and consumers’ vehicle switching intentions. From the Bayesian network model and structural equation model results, both models exhibit consistent findings, indicating that the causal relationships between variables derived from the structural equation analysis are reliable, which is in line with previous research findings [
102]. Bayesian networks quantify the uncertainty of parameters and structure among variables through probabilities, effectively identifying key determining factors that affect consumers’ intentions to switch to new energy vehicles, and providing more comprehensive and compelling evidence for the conclusions of structural equations. By combining SEM with Bayesian network models, we identified key impact factors on consumers’ vehicle switching intentions, leveraging the empirical evidence-based confirmatory power of SEM while highlighting the Bayesian network’s ability to handle nonlinear relationships and its predictive and diagnostic capabilities.
6. Conclusions and Policy Implications
The significant increase in gasoline prices has the potential to drive consumers toward the adoption of new energy vehicles. However, the reduction in government subsidies may impede consumer behavior toward switching, and the inadequate charging infrastructure in China may also act as a barrier to consumer adoption. The combination of these factors could potentially impact consumer decision making. This study is helpful in analyzing the mechanisms that may affect consumers’ switching to new energy vehicles and in understanding and predicting the changing trends of consumers’ switching intention to new energy vehicles under the impact of multiple factors, which may provide effective countermeasures for the future formulation of relevant policy measures to accelerate the development of new energy vehicles. The SCT modeling results showed that personal factors had a significant positive impact on consumers’ willingness to switch from owning no vehicle or owning a traditional gasoline vehicle to adopting a new energy vehicle. Some variables related to environmental factors had a negative impact on the switching intention. Additionally, when the price of gasoline rises, consumers’ perception of the cost savings associated with new energy vehicles becomes a significant driving factor, thus increasing their intention to switch to a new energy vehicle. Bayesian network analysis indicated that under the influence of multiple factors, approximately 51% of consumers had a high intention to switch to a new energy vehicle. Additionally, in terms of attitudes representing consumers’ intentions to switch new energy vehicles, self-efficacy, environmental consciousness, and perceived infrastructure readiness are significant predictors of individual vehicle switching intentions. The following policy implications are presented based on the research results.
First, enterprises should dynamically adjust their production, marketing, and vehicle pricing strategies in response to changes in gasoline prices. Governments should also make appropriate adjustments to subsidy policies and taxes based on gasoline price fluctuations. Whether an individual family owns fuel cars or is without a car, they will gradually switch to NEVs when the technology and infrastructure of NEVs become more mature in the future. However, the development of NEVs is related to green growth strategy initiatives and the realization of automotive strong country goals. Their implementation process will become the center of attention of the government, vehicle enterprises, and individuals. When gasoline prices rise sharply, the higher travel expenses drive people to clean, efficient, and cost-effective modes of travel. To rapidly increase their market share and improve their brand effect and competitiveness, vehicle manufacturers can dynamically adjust their R&D, production plans, and marketing strategies for NEVs based on factors such as gasoline prices and policy guidance, and appropriately adjust the prices of NEVs. For different income groups, they can customize the launch of models within the same price range, but also offer the purchase of vehicles to drive electricity bundled sales, etc. For the government, the push–pull policy can be implemented based on the gasoline price situation. When gasoline prices rise, the government can appropriately reduce the subsidies for NEVs and, conversely, appropriately increase them when gasoline prices fall. In the process of regulating and promoting NEVs, the government should also strengthen the regulation of the market.
Second, with the promotion of NEVs, the market demand for NEVs will expand and the market share will be further enhanced. The universality and convenience of charging facilities will focus the attention of users. It is recommended that the government should first formulate charging specification standards and regulatory mechanisms, followed by market demand analysis to popularize and improve charging supporting facilities, and then finally categorize and launch the service methods of power exchange, super-fast charging, fast charging, general charging, and slow charging according to the user needs of various locations. Improving consumers’ perception of charging infrastructure will further enhance people’s willingness to switch vehicles.
Third, environmental issues are also a major concern of society, and promoting NEVs already serves as a crucial measure to mitigate emissions in the automotive industry under the “double carbon” target. Raising people’s environmental awareness will facilitate consumers’ switching to NEVs. It is recommended that the government and vehicle manufacturers enhance the environmental effects brought by NEVs through short videos, posters, and slogans. The government can also impose pollution charges on existing fuel vehicles with varying emission standards and displacements, which is one measure to improve consumers’ intention to switch vehicles. Additionally, to continue growing the adoption of NEVs and further mitigate the pollution problems caused by traffic, the government could appropriately exempt private NEVs from highway tolls. The above policy recommendations from an environmental perspective will encourage consumers to switch to NEVs.
While our study has yielded interesting findings, it is not without limitations, which provide directions and suggestions for future research. Firstly, the sample collected in this study may not represent the attitudes of most consumers towards new energy vehicles after an increase in oil prices, as the online data collection conducted may not include consumers who do not use the internet, and the representativeness of online platforms may not be uniform across the country. For example, young people and well-educated groups are overrepresented in our sample, which may be due to the skewed participation of users of Questionnaire Star. Future research should expand to offline consumers and increase the sample size to further reduce sampling bias. Secondly, our study only focused on the influence of psychological latent variables on consumers’ conversion intention, but consumer groups with different genders, ages, and incomes have significant heterogeneity, which may lead to different attitudes toward switching to new energy vehicles. In future research, objective variables should be combined with psychological latent variables to explore the impact of the heterogeneity of different groups on the conversion to new energy vehicles, comprehensively considering the factors that affect consumers’ conversion intention. Lastly, our study only focused on consumers who either owned traditional fuel vehicles or did not own a vehicle at all, but not those who already owned new energy vehicles. Exploring their intention to switch through face-to-face interviews, semi-structured in-depth interviews, and other survey forms is worthy of future research.