Exploring the Relationship between Supply Chain Agility, Consumer and Electric Vehicle Characteristics, and Purchase Intentions in Thailand: A Structural Equation Modeling Approach

Abstract

This research on electric vehicle purchasing intentions in Thailand using Structural Equation Modeling aimed to achieve the following objectives: Firstly, to investigate the factors influencing consumers’ intentions to purchase electric vehicles. Secondly, to examine the impact of consumer characteristics on supply chain agility (SCA). Thirdly, to analyze how electric vehicle characteristics influence supply chain agility. Lastly, to assess the influence of supply chain agility on consumers’ purchasing intentions. The study sampled individuals in Thailand holding personal driver’s licenses and intending to purchase electric cars, totaling 350 respondents selected randomly. Data analysis employed descriptive statistics including frequency, percentage, and mean values. The validity and reliability of the questionnaires were ensured through factor loading and Cronbach’s Alpha tests. Our findings indicated that consumer characteristics, electric vehicle features, and supply chain agility significantly affect purchasing intentions. Consumer-specific factors like social influence, environmental concern, and perceptions of electric vehicles were found to impact purchase intentions. Electric vehicle characteristics such as battery longevity, perceived benefits, and value also influenced purchase intentions. Additionally, supply chain agility factors including flexibility, speed in innovation, and responsiveness to customer needs were identified as influential. The research underscores the importance for manufacturers to prioritize initiatives that enhance customer experience with electric vehicles, alleviating concerns and fostering confidence in their use, thereby encouraging adoption without apprehensions about potential issues.

1. Introduction

In both developed and developing nations, primary production activities typically involve extracting raw materials from natural sources, resulting in direct and indirect environmental impacts, including the depletion of natural resources and generation of waste in natural ecosystems [1]. The automotive industry has responded to concerns about global warming by prioritizing sustainable development and energy use, with efforts focused on increasing the adoption of renewable energy sources.

One of the most prevalent modes of transportation is road travel, utilizing vehicles that offer convenience and higher speed compared to other modes. However, vehicle transportation contributes significantly to pollution through carbon dioxideemissions. Transitioning from combustion engines to electric engines presents a viable alternative for vehicle transportation. Presently, Bangkok has 11 million registered vehicles, with provinces accounting for an additional 31 million, totaling 42 million vehicles. Estimates from ttb analytics project that sales of electric passenger cars will triple by 2023, potentially reaching 40,000 units [2].

Currently, the market of electric vehicles is rapidly expanding, with electric vehicle sales dramatically increasing 65% in 2022, and the electric vehicle market share is 14% when compared with total car market. The forecast of global EV sales in 2024 is 17 million cars [3].

The majority of vehicles in Thailand are powered by gasoline, necessitating significant imports of this fuel source. Gasoline prices exhibit high volatility and are influenced by various factors, such as interest rates, the COVID-19 pandemic, and geopolitical tensions. As gasoline is a finite resource, its prices tend to increase over time, impacting the overall cost of living.

Electric vehicles represent a viable option for environmentally friendly transportation, catering to diverse needs such as commuting and personal use. The development of efficient batteries is critical for enhancing the operational longevity of electric vehicles. Customer attitudes towards electric vehicles and their acceptance of the underlying technology are pivotal factors influencing purchasing decisions. Factors contributing to the development of electric cars in Thailand include environmental consciousness, public acceptance, and economic considerations. Moreover, government policies pertaining to electric vehicles, such as tax incentives, support for technology advancements, and promoting domestic production, play a crucial role in fostering the growth of the electric vehicle sector. The characteristics of electric cars are instrumental as they directly impact customer convenience and satisfaction levels.

Moreover, limited research exists on electric vehicles regarding the interrelationship among consumer characteristics, electric vehicle features, supply chain agility, and purchasing intentions specifically within Thailand. Most studies on technology acceptance and adoption have predominantly centered on countries like China and the United States, owing to their large populations and high income levels. Through an investigation into consumer purchasing intentions, the researcher sought to identify which variables exert a more pronounced influence on consumer purchasing intentions within the Thai context.

Consequently, this study examines the behavioral factors contributing to the low purchasing intention for electric vehicles in Thailand. It employs behavioral theory and technology acceptance to develop a conceptual framework. The research aimed to address the following questions: What behavioral variables influence consumer purchasing intentions in Thailand? Does supply chain agility have an impact on consumers’ purchasing intentions?

In accordance with the research questions, a conceptual framework was developed and presented. Consumer characteristics encompass social, demographic, psychological, and personal variables. Variables related to electric vehicles include economic factors, technical specifications, and considerations of risks and benefits. Supply chain agility variables encompass infrastructure readiness, preparedness, and pre- and post-sales service capabilities.

2. Materials and Methods

• Literature review

The study employed the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) as foundational variables. A systematic literature review was conducted to develop the conceptual framework, providing detailed information on the independent and dependent variables.

• Theory of Planned Behavior (TPB)

Attitude and behavior have a direct impact on human intention. Behavior is shaped by societal beliefs and conduct, making individuals conscious of their actions. This theory elucidates human behavior by addressing the needs reflected in their actions, with the primary component being the intention to perform a behavior. It is utilized to predict outcomes in health and behavior, such as eating habits, smoking, and product purchases [4].

• Theory of Technology Acceptance Model (TAM)

The Technology Acceptance Model (TAM) is a widely recognized framework for evaluating the acceptance of new technology. It identifies two key factors influencing people’s willingness to adopt a new technology: perceived ease of use and perceived benefits [5]. For instance, older adults who find technology challenging to use for entertainment purposes are likely to reject it. Applying the TAM to examine consumers’ intention to purchase electric vehicles is essential, as it assesses the acceptance of technology in terms of the convenience of using electric vehicles and the benefits that consumers gain from them.

This research seeks to create a conceptual framework and formulate a research question by leveraging the Theory of Planned Behavior and the Technology Acceptance Model. The focus is on identifying four latent variables that impact consumer purchasing intentions: consumer characteristics, electric vehicle characteristics, and supply chain agility.

Utilizing the Theory of Planned Behavior and the Technology Acceptance Model, this study aimed to develop research hypotheses concerning the intention to purchase electric vehicles. The Theory of Planned Behavior guided hypothesis formulation related to purchase intentions, as it focuses on behavior in this domain. Moreover, the Technology Acceptance Model was employed to generate hypotheses regarding technology acceptance, specifically in relation to electric vehicle characteristics and supply chain agility. One limitation of applying the Theory of Planned Behavior and the Technology Acceptance Model to the study of electric vehicle purchase intentions is the issue of latent consumer characteristics variables. Specifically, the characteristics of consumers in Thailand may differ from those in other countries, potentially leading to unique consumer traits that are not accounted for in international studies. This variation could result in findings that differ from those in other research.

• Research hypotheses
• Consumer characteristics and supply chain agility

Supply chain agility embodies a proactive strategy to synchronize marketing and strategic operations, highlighting exemplary business practices. The food production industry encounters complexities arising from global population growth and changing consumer characteristics, requiring operational adaptations throughout the value supply chain. Cultural and health shifts in food consumption are intensifying amid demographic and social changes, forcing food producers to modify their operations to stay competitive [6]. Regarding consumer characteristics influencing electric vehicle adoption, these include personality traits, environmental perceptions, product attributes, charging policies, and subjective norms. Research indicates that the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism, and openness) are pivotal in shaping intentions to adopt electric vehicles, albeit neuroticism may show deviations in its impact [6]. The significance of consumer characteristics in influencing decisions related to both food and automobile purchases underscores their pivotal role in shaping consumer behavior.

Internal collaboration within organizations is essential for optimizing resource utilization in digitalized supply chain management. Adopting digitalization across the supply chain and enhancing supply chain agility can provide competitive advantages, aligning with changing consumer preferences and mitigating operational risks through improved collaboration [7].

Hypothesis H1.

Consumer characteristics have a positive and significant effect on supply chain agility.

• Electric vehicle characteristics and supply chain agility

The key characteristics of electric vehicles that greatly influence supply chain agility include the demand for essential metals such as lithium, nickel, cobalt, and manganese. This demand is driven by the worldwide deployment of electric vehicles across various battery technology scenarios. Moreover, the electric vehicle supply chain underscores the significance of raw material supply, environmental impact assessments, and cost analyses, with particular emphasis on risk management and sustainability [8]. Supply chain agility and information capability are critical for business operations, as they enhance economic and business performance. These factors positively influence cost reduction and supply chain efficiency. Enhancing supply chain resilience and information capability can lead to improved business outcomes [9]. Manufacturing flexibility positively impacts supply chain resilience and sustainability. By employing a decision-making framework for supply chain agility, manufacturing can enhance service excellence and societal performance. Supply chain agility contributes to business sustainability and provides a competitive edge over rivals [10].

Hypothesis H2.

Electric vehicle characteristics have a positive and significant effect on supply chain agility.

• Consumer characteristics and electric vehicle characteristics

The issue of capacity degradation is significant in lithium-ion batteries, widely utilized in electric vehicles and consumer electronics. Concerns about consumer safety related to battery usage in electric vehicles are growing, emphasizing the need to address multiple aspects of battery safety. Analyzing battery performance across various seasonal conditions, mileage usage, charging infrastructure, and stages of electric vehicle ownership is essential for understanding consumer psychology and purchase intentions toward electric vehicles [11]. Middle-income individuals residing in urban areas and owning their vehicles are primary users of electric vehicle charging stations. Criteria for selecting charging stations include technological familiarity, convenience, and accessibility. However, electric vehicle owners who charge their batteries overnight at home generally show less concern about public charging stations. Moreover, personal experiences with electric vehicle charging and self-identity play significant roles in shaping perceptions and utilization of public charging infrastructure [12].

Hypothesis H3.

Consumer characteristics have a positive and significant effect on electric vehicle characteristics.

• Supply chain agility and consumer purchasing intention

Blockchain technology has been integrated into food safety standards due to its ability to enhance the traceability of raw materials and ensure quality control throughout the food supply chain. Consumers derive increased benefits from accessing records of food origins and verifying food information. The use of blockchain labels in food products enhances consumers’ perceived value by providing transparent and reliable information through food labeling [13]. The perceived sustainability of short food supply chains (SFSC) is influenced by consumers’ product knowledge, which drives their information-seeking behavior. SFSC directly impacts consumers’ intentions to purchase, as those with strong purchasing intentions are more inclined to buy food products. Food sellers can leverage social media platforms to disseminate information that influences consumers’ purchasing intentions [14]. Supply chain agility is pivotal in shaping consumer purchase intentions for electric vehicles. Studies highlight that a responsive and efficient supply chain is critical for satisfying consumer demands, which, in turn, significantly affects their willingness to buy electric vehicles [15]. Additionally, consumers’ control over resources, environmental awareness, and acceptance of technology products significantly influence their behavioral intention to purchase electric vehicles, highlighting the importance of supply chain agility in meeting these consumer needs [16].

Hypothesis H4.

Supply chain agility has a positive and significant effect on consumers’ purchasing intentions.

• Consumer characteristics and consumer purchasing intention

Social networks exert a substantial influence on consumer purchasing behavior in Cameroon, primarily through advertising perception and psychological predispositions. Additionally, consumers’ purchasing intentions significantly shape their consumption behaviors, underscoring the importance for enterprises to grasp the role of social media communication in shaping consumer intentions and behaviors [17]. Consumer attitudes towards environmental concerns influence their preference for environmentally friendly food packaging and subsequent purchasing behavior. The intention to purchase and the ability to control one’s behavior collaboratively contribute to the adoption of environmentally friendly packaging options. Consumer characteristics play a pivotal role in shaping preferences towards environmentally sustainable food packaging solutions [18].

Hypothesis H5.

Consumer characteristics have a positive and significant effect on consumer purchasing intention.

• Electric vehicle characteristics and consumer purchasing intention

Electric vehicles contribute to mitigating carbon dioxide emissions, and consumer intentions to purchase them are significantly influenced by environmental awareness. Variables such as attitudes towards green products and perceived value play key roles in shaping consumer purchasing intentions. Consumers gather information on electric vehicles through green advertising, which is instrumental in enhancing their purchasing intentions. Effective management by electric vehicle manufacturers further strengthens consumer interest and intention to purchase electric vehicles [19]. In Thailand, heightened environmental awareness prompts increased consumer interest in purchasing electric vehicles. The primary factors influencing consumer purchasing intentions are the prices of electric vehicles and environmental consciousness. Factors such as charging infrastructure availability and government policies do not significantly impact consumer purchasing intentions. Nevertheless, there is a need for government initiatives to bolster environmental awareness among consumers, while electric vehicle manufacturers should consider reducing prices to further encourage purchasing intentions [20].

Hypothesis H6.

Electric vehicle characteristics have a positive and significant effect on consumer purchasing intention.

A review of the literature was conducted to examine the variables associated with intentions to purchase electric vehicles. Based on this review, a conceptual framework for the research was developed and is depicted in Figure 1.

• Methodology
• Research design

This exploratory research began with a review of the literature related to electric vehicle purchase intentions and the associated latent variables. The research objective was then established, which was to investigate the relationship between consumer characteristics, electric vehicle characteristics, and supply chain agility, and how these factors influence the intention to purchase electric vehicles.

• Data collection process

This study adopted a quantitative approach, employing a questionnaire as the primary research tool. The questionnaire was structured into two sections: the first section gathered demographic information, while the second section focused on exploring analytical aspects and relationships among variables. A Likert scale was utilized in the questionnaire, where respondents rated their agreement levels from 1 (strongly disagree) to 5 (strongly agree). The researcher collected survey results and conducted a statistical analysis to interpret the findings.

The study focuses on exploring the intention to purchase electric vehicles in Thailand for two main reasons. Firstly, there is a notable surge in the demand for electric vehicles within the country. Secondly, international investors, particularly from China and Thailand, have selected Thailand as a manufacturing hub for electric vehicles, catering to both domestic distribution and international export markets.

The sample population used in the research comprised people who use cars, have a personal car driver’s license, live in Thailand, and intend to buy an electric vehicle. The sample used in this study was a random sample representative of the study population. However, the exact population size is unknown. Therefore, the researcher used the method of calculating the sample using the formula of W.G. Cocharn. The confidence level was set at 95%. A total of 350 samples were collected using a random collection method.

• Data analysis

Data analysis began with the process of data cleaning, which included identifying multivariate outliers using the Mahalanobis Distance technique in SPSS. Version 26 Outliers with a p-value less than 0.001 were eliminated. Next, construct validity was tested using factor loading values greater than 0.4, and the reliability of the questionnaire was assessed using Cronbach’s alpha, with values greater than 0.7 indicating acceptable reliability. Subsequently, descriptive statistics and Structural Equation Modeling (SEM) analysis were used in the AMOS statistical program.

3. Results

3.1. Demographic Results

Table 1. Demographic profile.

Items	Details	Frequency	Percentage
Gender	Male	92	26.3
	Female	258	73.7
Age	20–29 years	170	48.5
	30–39 years	105	30.0
Income USD (monthly)	40–49 years	59	16.8
	More than 49 years	16	4.7
	215–515	26	7.4
	516–828	250	71.4
	829–1142	36	10.3
	More than 1142	38	10.9
Education level	Lower than bachelor’s degree	46	13.1
	Bachelor’s degree	272	77.7
	Master’s degree	27	7.2
	Higher than master’s degree	7	2.0
Vehicle currently in use	Vehicle engines use gasoline	340	97.1
	Electric vehicles	10	2.8

shows the demographic characteristics of the participants. According to the demographic profile, 73.7% of the participants were female, 48.5% were 20–29 years old, 71.4% had a monthly income of THB 18,001–29,000, 77.7% had a bachelor’s degree, and 97.14% used gasoline engine vehicles.

3.2. Validity and Reliability Results

Cronbach’s alpha was used to analyze the reliability of the research instrument, which collected data from the participants. Cronbach’s alpha is a popular statistic for testing questionnaire reliability and is widely used; it was used for reliability testing in this research. In addition, the researcher used confirmatory factor analysis to measure the convergent validity and the discriminant validity to measure various aspects of behavior and performance according to the stated aims and in accordance with the principles of that theory.

Thus, the reliability of this study was tested. The researcher used Cronbach’s alpha, subtracted mean variance (AVE), and composite reliability (CR) as tools to measure all respondents’ opinions.

In addition, Cronbach’s alpha was used to check the reliability of the structural equation variables. The reliability of the equation must have a Cronbach’s alpha value greater than 0.7, indicating a relationship between the latent variables. In this study, the Cronbach’s alpha was between 0.93–0.96, which was greater than 0.7, according to the specified criteria (

Table 2. Measurement model.

Construct	Variables	Factor Loading	CR	AVE	Cronbach’s Alpha
Consumer characteristics	CC4	0.646	0.94	0.87	0.96
	CC2	0.683
	CC3	0.658
	CC1	0.720
Electric vehicle characteristics	EVC3	0.597	0.93	0.95	0.95
	EVC2	0.599
Supply chain agility	EVC4	0.627
	EVC1	0.773
	SCA4	0.559	0.94	0.93	0.96
	SCA2	0.566
	SCA3	0.575
	SCA1	0.695
Consumer purchasing intention	CPI2	0.597	0.92	0.89	0.93
	CPI3	0.627
	CPI1	0.672
	CPI4	0.717

).

3.3. Testing the Validity of Variables

According to the theory of validity, the CR value must be greater than 0.7 to be considered an objective measurable instrument and the AVE value must be greater than 0.5 (Bagozzi, Yi, and Phillips, 1991). The CR values of each variable of the study were 0.92–0.94, i.e., higher than 0.7. The AVE values of each variable in the study were 0.87–0.95, i.e., higher than 0.5. Regarding the research results, the CR and AVE values demonstrate the validity of this research scale (Table 2).

The reliability levels of each variable were determined, and the reliability coefficient results for consumer characteristics (CC) and supply chain agility (SCA) were high at 0.96. The reliability coefficient results for electric vehicle characteristics (EVC) were high at 0.95, and the reliability coefficient results for consumer purchasing intention (CPI) were high at 0.93.

3.4. Structural Equation Model Analysis (SEM) Results

Path analysis and hypothesis testing were used for the research model analysis to predict consumer purchasing intention (CPI), which is influenced by consumer characteristics (CC), electric vehicle characteristics (EVC), and supply chain agility (SCA).

The results of the path analysis are presented in

Table 3. Path analysis and hypothesis testing.

Hypothesis	Path	Path Coefficient	p-Value	Relationship
H1	CC >>> SCA	0.21 *	0.002	Supported
H2	EVC >> SCA	0.30 ***	0.003	Supported
H3	CC >> EVC	0.43 **	0.001	Supported
H4	SCA >> CPI	0.25 *	0.002	Supported
H5	CC >> CPI	0.19 ***	0.001	Supported
H6	EVC >> CPI	0.57 *	0.002	Supported

Note: * Sig at 0.05 level, ** Sig at 0.01 level, *** Sig at 0.001 level.

. The path coefficient results were less than 1. Thus, the hypothesis testing results showed that consumer characteristics (CC) had a significant and positive relationship with supply chain agility (SCA) (H1) (β = 0.21, p < 0.05). Electric vehicle characteristics (EVC) had a significant and positive relationship with supply chain agility (SCA) (H2) (β = 0.30, p < 0.05). Consumer characteristics (CC) had a significant and positive relationship with electric vehicle characteristics (EVC) (H3) (β = 0.43, p < 0.05). The supply chain agility (SCA) had a significant and positive relationship with consumer purchasing intention (CPI) (H4) (β = 0.25, p < 0.05). Consumer characteristics (CC) had a significant and positive relationship with consumer purchase intention (CPI) (H5) (β = 0.19, p < 0.05). The electric vehicle characteristics (EVC) had a significant and positive relationship with consumer purchasing intention (CPI) (H6) (β = 0.57, p < 0.05).

4. Discussion

According to the research findings supporting the theory, consumer characteristics (CC) demonstrated a significant and positive correlation with supply chain agility (SCA). H1 was validated as consumer characteristics play a crucial role in influencing adjustments within electric vehicle manufacturers’ supply chains, driven by consumer demands for innovation. The adoption of driverless cars is seen as advantageous for both the environment and society. External environmental factors and individual characteristics influence the decision-making process regarding the purchase of driverless cars. As consumers become increasingly concerned about environmental issues, there is a growing shift towards electric vehicles, which underscores the importance of innovation in this sector [21].

Consumers’ perceptions regarding the benefits and value of electric vehicles drive enhancements in the efficiency of electric vehicle production, particularly concerning battery longevity. The characteristics of electric vehicles positively and significantly impacted supply chain agility, confirming H2. Consumers’ perceptions of the risk associated with Internet banking influence their adoption of this innovative financial service. Therefore, raising awareness about risk factors is crucial for encouraging consumer adoption of Internet banking [22].

Consumer characteristics exert a positive and substantial influence on the characteristics of electric vehicles, thereby supporting H3. Understanding consumer perceptions is pivotal in shaping the value proposition in electric vehicle production. Exploring how consumers perceive risks and their impact on the perceived value and utility of electric vehicles will influence consumer intentions to purchase them. Perceptions of financial, environmental, and psychological benefits are expected to correlate positively with consumers’ perceptions of value [23].

Supply chain agility demonstrates a positive and significant impact on consumer purchasing intentions, thereby supporting H4. The capability of entrepreneurs contributes to innovation and sustainability in the business operations of small- and medium-sized enterprises. Entrepreneurs must analyze the business environment effectively to develop new products that align with customer needs [24]. The concept of the circular economy emphasizes sustainability, social responsibility, and economic growth. Integrating blockchain technology into supply systems and supply chain development processes can enhance operational efficiency, sustainability, and contribute to business expansion. Blockchain technology benefits the circular economy by lowering production costs, increasing operational efficiency, and facilitating improved communication within supply chains [25].

Advancements in technology and the Internet have made website development relatively straightforward. However, challenges in website development stem not only from technological factors but also from creators who may not fully understand their customers’ genuine needs. Developing a high-quality website is crucial for fostering customer confidence and satisfaction. Therefore, it is essential for website developers to deeply understand customer preferences and behaviors when designing online sales platforms to retain existing customers and attract new ones [26]. Consumer characteristics are found to have a positive and significant influence on consumers’ purchasing intentions (H5).

Smart speakers represent a novel technology that enhances consumer convenience. Features of smart speakers that are user-friendly and beneficial positively influence consumer attitudes. The suitability of this technology for practical use significantly shapes consumers’ purchasing attitudes towards smart speakers [27]. The COVID-19 pandemic prompted the creation of tracking applications, raising privacy concerns among users that impact their adoption of such applications. Nevertheless, ongoing innovations have led to a positive reception among users towards using these applications [28]. Additionally, the characteristics of electric vehicles exhibit a positive and significant influence on consumer purchasing intentions, thereby confirming H6.

5. Conclusions

• Theoretical contributions

The findings of this study provide empirical support for the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) as discussed in the literature review. This research contributes new theoretical insights and practical implications concerning the intention to purchase electric vehicles. Traditionally, TPB and TAM have been applied to understand consumer purchase intentions in sectors such as food or clothing. However, this study focuses uniquely on factors influencing the intention to purchase electric vehicles in Thailand, expanding upon previously unexplored theoretical ground. In the context of Thai consumers, supply chain agility emerges as a crucial factor influencing electric vehicle purchase intentions, underscoring the importance of aligning electric vehicle features with consumer preferences to enhance purchasing intent.

The research indicates that consumer purchase intentions in Thailand are impacted by several factors, including electric vehicle characteristics, consumer preferences for innovation, and supply chain agility. Consumers who prioritize innovation are particularly inclined towards purchasing electric cars. Furthermore, the perceived utility of vehicle features has a positive influence on consumers’ intentions to buy electric vehicles. Enhancing the supply chain to better align with consumer needs and electric vehicle attributes further enhances consumer purchase intentions.

• Practical implications

The findings of this study yield several practical implications. Firstly, electric vehicle manufacturers must acknowledge the significance of consumer characteristics, particularly in fostering innovations that influence consumer purchase intentions. This involves adapting the electric vehicle production process to meet consumer demands within the specific context of the Thai market, where consumers have embraced innovations in electric vehicles and exhibit a positive attitude towards purchasing them.

Secondly, addressing consumer concerns regarding battery longevity has driven electric car manufacturers to develop batteries capable of longer driving ranges. Designing user-friendly electric vehicles significantly impacts consumer purchase intentions. Therefore, manufacturers must focus on designing electric vehicles that offer convenience, thereby enhancing incentives for consumer adoption.

Thirdly, supply chain agility, which involves rapid response in production, delivery, and customization to meet customer demands, has been shown to affect consumer purchase intentions. Thus, electric car manufacturers need to thoroughly understand consumer needs before designing and producing electric vehicles to effectively meet these needs.

Lastly, consumer characteristics, electric vehicle features, and supply chain agility collectively exert a positive influence on consumer purchase intentions. Electric vehicle manufacturers should innovate within the industry by leveraging insights into consumer needs to produce electric vehicles that resonate with their preferences. Educating consumers about electric vehicles remains crucial to raising awareness and fostering interest. Positive driving experiences with electric vehicles also play a significant role in enhancing consumer awareness and increasing purchase intentions.

• Research limitations and future research areas

The limitations of this study include the constraints in defining a diverse range of variables, as it focuses on purchase intention behavior. This area involves numerous additional factors, such as variables related to acquiring information about electric vehicles and regulatory issues that influence purchasing decisions.

Future research should incorporate variables related to economic, geographic, and technological advancements. Including these factors will provide a clearer understanding of the structural equations that influence the decision to purchase electric cars.