International Journal of Business and Economy (IJBEC) eISSN: 2682-8359 | Vol. 4 No. 3 [September 2022]
Journal website: http://myjms.mohe.gov.my/index.php/ijbec
ASSESSING INDONESIAN CONSUMER ADOPTION OF ELECTRIC VEHICLES USING THE EXTENDED UTAUT2
MODEL
Irfanto N1* and Aprilianty F2
1 2 School of Business and Management, Institut Teknologi Bandung, Bandung, INDONESIA
*Corresponding author: [email protected]
Article Information:
Article history:
Received date : 21 July 2022 Revised date : 25 August 2022 Accepted date : 1 September 2022 Published date : 10 September 2022
To cite this document:
Irfanto, N., & Aprilianty, F. (2022).
ASSESSING INDONESIAN CONSUMER ADOPTION OF ELECTRIC VEHICLES USING THE EXTENDED UTAUT2 MODEL.
International Journal of Business and Economy, 4(3), 74-87.
Abstract: The number of users of electric vehicles in Indonesia is still relatively low. This study aims to create an understanding of why the population of electric vehicles in Indonesia is still low by assessing the consumer adoption of electric vehicles in Indonesia using all the variables included in the Unified Theory of Acceptance and Use of Technology 2 Model, also adding several variables found on the previous study such as Technophilia, Perceived Environmental Knowledge, Perceived Functional Risk, Perceived Financial Risk, Perceived Time Risk. The study methodology is based on a quantitative approach to collecting the primary data.
The questionnaire of this study was adapted and developed from previous studies. People who specifically have experience driving electric vehicles in Indonesia were targeted and resulting 103 people's questionnaire forms were analyzed. The SEM-PLS was used to conduct some tests to ensure the data is valid and reliable, and also to test the study hypothesis. Only Performance Expectancy and Habit had a significant impact on behavioral intention to use electric vehicles.
Subsequently, also only Habit and Behavioral Intention significantly impact the Use Behavior of electric vehicles. It indicates that the adoption level of electric vehicles in Indonesia is still low. Additionally, the recommendation was made to boost the adoption rate of electric vehicles in Indonesia by understanding the significant and insignificant variables tested. Lastly, The UTAUT2 theory will be used for the future research of adoption of electric vehicles.
1. Introduction
The previous studies showed that common vehicles that still use gasoline fuel have several bad impacts towards the environment. Joskow et al. (1998) found that one of the largest contributors and causing the primary second carbon dioxide emissions worldwide is terrestrial transportation, due to the use of conventional fuel. Electric vehicles are a viable technology for establishing a sustainable transportation sector in the future (Nanaki, 2021). This pollution can be minimized because of the use of electricity as the energy source rather than use gasoline.
According to Droppa (2022), worldwide sales of electric vehicles achieved 6.75 million units in 2021, showing growth of 108% from 2020. This year, sales of electric cars expected to reach approximately 9.5 million units, after resolving the supply and logistical issues. Knowing the global development trend for electric vehicles, the Indonesian government took some actions towards the implementation of policy. The government is committed to promoting the growth of the electric vehicle technology industry (Aziz et al., 2020). Based on Presidential Decree No. 55/2019 on the Acceleration of the Battery-Based KBL Program for Road Transportation, the development of electric or battery-powered cars may be accelerated by offering incentives to the automotive industry. The adoption process of technology has influenced and constructed by several variables to understand the user intention of using new technology as what Venkatesh et al. (2003) and Venkatesh et al. (2012) establish in their study. The framework model is therefore known as the Unified Theory of Acceptance (UTAUT) model. In this case, electric vehicles are considered as new technology adopted by the customer. The importance of using UTAUT Model is due to Venkatesh’s model includes demographic, also experience factors built into it, making it more ideal for product-oriented research in the business-to- customer sector (Chang, 2012).
2. Literature Review
Below is the previous study that related with this study topic area that state the objective, measures, and the findings.
Table 1: Journal Matrix of Previous Study
Title Objective Measures Research Findings
(Venkatesh, V., Thong, J.,
& Xu, X. 2012)
Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of
Acceptance and Use of Technology
The purpose of this research is to investigate the adoption and utilization of technology in consumer perspective
● Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition, Hedonic Motivation, Price Value, Habit, Behavioral Intention, Use Behavior
● Compared to the original UTAUT theory, the variance explained has increased significantly.
● Age, gender, and experience moderate habit.
● With an increased experience, the impact of behavioral
intention on usage will diminish.
● All the variables developed in UTAUT has significantly impact the behavioral intention and the actual usage
(Gunawan, I., Redi, A., Santosa, A., Maghfiroh,
Predict interest in electric
● Attitude Towards Use, Subjective
● Attitudes towards the use of electric vehicles
Keywords: Electric Vehicles, Consumer Adoption, Behavioral Intention, Use Behavior, UTAUT2, Indonesia.
M., Pandyaswargo, A., &
Kurniawan, A. 2022)
Determinants of Customer Intentions to Use Electric Vehicle in Indonesia: An Integrated Model Analysis
vehicles adoption in Indonesia, using integrated model perceived risk, TPB, and UTAUT2
Norm, Perceived Behavior Control
●Performance Expectancy, Effort Expectancy, Hedonic Motivation, Price Value, Habit
● Perceived Physical, Performance, Financial, Social, and Time Risk
is positively impacted by price value, effort expectancy, hedonic motivation, and performance expectancy
● Attitudes towards the use of electric vehicles is positively impacted by habit at an insignificant level
(Abbasi, H., Johl, S., Shaari, Z., Moughal, W., Mazhar, M., Musarat, M., Rafiq, W., Farooqi, A., &
Borovkov, A. 2021)
Consumer Motivation by Using Unified Theory of Acceptance and Use of Technology towards Electric Vehicles
To evaluate consumer motivation and environmental knowledge towards electric vehicles by using the UTAUT model
● Performance Expectancy, Effort Expectancy, Social Influence
● Technophilia
● Perceived Environmental Knowledge
● Consumer intention is not significantly influenced by performance expectancy.
● Consumer intention is positively and significantly influenced by the effort expectancy, social influence, technophilia, perceived environmental knowledge
2.1 Problem Statement
For its operating purposes, the government expects to have 132,983 electric automobiles and 398,530 electric motorbikes by 2030 (Shofa, 2022). It has potential to reduce fuel consumption by 6 million kilo liters per year and reduce greenhouse gas emissions by 7.23 million tons of CO2 (Pribadi, 2021). The electric vehicle population in Indonesia, however, is still low (Shofa, 2022). According to the Transportation Ministry, it estimated that Indonesia only had 14,400 electric vehicles as of mid-November 2021. There were 12,464 electric motorbikes and 1,656 electric passenger cars among the total. When compared to the current sales of electric cars in Indonesia up to 2021, which are only 1900 electric cars, this target requires extraordinary efforts to actualize. Director General of ILMATE, Taufiek Bawazier, who is charge in the ministry of industry in Indonesia, said that currently the uptake of electric cars in Indonesia is still far from expectations. Knowing the difficulties of how consumers would new technology, in this case is how to accept the electric vehicle, Venkatesh et al. (2012) established the UTAUT2 model, which is one of the most extensively used models to better understand the intention of the adoption process of new technology. This primary research result is expected to be classified into the process of customer adoption towards the electric vehicle and establish the best strategy for the development of the automotive industry electric vehicle in Indonesia to overcome the problem that might affect the customer's intention to use an electric vehicle.
3. Method
Electric vehicles adoption in Indonesia needs to be identified in the beginning. Subsequently, the literature review and research methodology will also be employed, followed by quantitative approach, and survey. Lastly, there will be discussion based on the findings.
3.1 Materials
A quantitative technique is used to finish the study, which entails completing a survey in order to collect data. Below the technique and method of data collection will be explained.
3.1.1 Samples
The respondent will be both male and female participants of any age. This study will collect data for minimum 100 respondents. The characteristic of the respondent will be people who domiciled in Indonesia and have experience for driving electric vehicles.
3.1.2 Site
This research targeted the respondents who live in Indonesia, specifically live in the big city that has a high chance for the respondents experiencing driving electric vehicles.
3.1.3 Procedures
Quantitative analysis, as defined by Aliaga and Gunderson (2002), will be employed since it is appropriate for the goal of this study. The survey also will be used as the research approach since it suits with Jackson (2009) explanation. Due to its potential to collect vast volumes of data in a relatively short length of time, an online questionnaire is determined to be the ideal instrument for collecting the data needed to complete this research. Judgemental sampling will be implemented in order to offer the details.
Figure 1: Conceptual Framework of the Modified UTAUT2 Model
• Performance Expectancy (PE)
According to Venkatesh et al. (2003), It has been continuously expected as the most significant aspect of behavioral intention, and performance expectation is defined as the extent to which the adoption of a technology will assist customers in accomplishing particular activities. Other research that has used UTAUT as the foundation theory to explain the adoption of electric vehicles have revealed that the variable has a significant influence on behavioral intention (Venkatesh, et al., 2012; Gunawan et al., 2022) Based on the findings of this study, the following hypothesis will be developed:
H1: Performance expectancy has a significant influence on behavioral intention to use electric vehicles in Indonesia
• Effort Expectancy (EE)
Venkatesh et al., (2003) explained that effort expectation is the degree to which a user expects a product to be easy to use. Venkatesh et al., (2012) discovered that the output of the effort expectation in the UTAUT2 had a substantial effect on behavioral intention. Furthermore, Gunawan et al., (2022) found that effort expectancy had an influence on behavioral intention in their study on adoption of electric vehicles uptake. Based on the findings of this study, the following hypothesis will be developed:
H2: Effort expectancy has a significant influence on behavioral intention to use electric vehicles in Indonesia
• Social Influence (SI)
Social influence was described by Venkatesh et al., (2003) as the extent to which an individual believes it is vital for them to accept the new system. Based on the findings of the study by Venkatesh et al. (2003), social influence has a considerable impact on behavioral intention.
Other research that has used UTAUT2 as the foundation theory to explain the adoption of electric vehicles indicated that the variable has a significant influence on behavioral intention (Venkatesh, et al., 2012). Based on the findings of this study, the following hypothesis will be developed:
H3: Social influence has a significant influence on behavioral intention to use electric vehicles in Indonesia.
• Facilitating Condition (FC)
According to Venkatesh et al., (2003), facilitating condition is a person's notion that the necessary organizational and technological infrastructure is already in place to make system utilization more straightforward. Other research that has used UTAUT2 as the foundation theory to explain the adoption of electric vehicles have found that facilitating has a significant influence on behavioral intention (Venkatesh, et al., 2012). Based on the findings of this study, the following hypothesis will be developed:
H4a: Facilitating condition has a significant influence on behavioral intention to use electric vehicles in Indonesia.
H4b: Facilitating condition has a significant influence on the use behavior of electric vehicles use in Indonesia.
• Hedonic Motivation (HM)
Venkatesh et al., (2012) defined hedonic motivation as the enjoyment of customers or pleasure in utilizing technology. Venkatesh et al., (2012) and Gunawan et al., (2022) discovered that hedonic motivation has an influence on behavioral intention in their studies of electric vehicles adoption uptake. Based on the findings of this study, the following hypothesis will be developed:
H5: Hedonic motivation has a significant influence on behavioral intention of electric vehicles use in Indonesia.
• Price Value (PV)
Pricing value is termed as the cognitive compensation between the projected advantages and the expense of employing the technology (Venkatesh et al., 2012). Several researchers have discovered that price value influences or has a considerable impact on behavioral intention (Venkatesh, et al., 2012; Gunawan et al., 2022). Based on the findings of this study, the following hypothesis will be developed:
H6: Price value has a significant influence on behavioral intention to use electric vehicles in Indonesia.
• Habit (HA)
Habit, as described by Venkatesh et al., (2012), is the degree to which people tend to do things as a result of learning. Additionally, habit is related to both behavioral intention and use behavior, In the other studies, Gunawan et al., (2022) found that habit had an influence on behavioral intention in their study on adoption of electric vehicles uptake. Based on the findings of this study, the following hypothesis will be developed:
H7a: Habit has a significant influence on behavioral intention to use electric vehicles in Indonesia.
H7b: Habit has a significant influence on the use behavior of electric vehicles use in Indonesia
• Moderating Factors o Gender
Gender, as defined by the World Health Organization, refers to the roles, attitudes, activities, qualities, and opportunities that any culture believes appropriate for boy and girl or man and woman. Gender was believed to have a moderating effect on various connections between the components in the UTAUT model by Venkatesh et al. (2003) research.
o Age
According to Venkatesh et al. (2003), age is a measurement of an individual's development that is expressed in terms of the number of years necessary for the growth of an average individual. It was shown that age had impacts that moderated the numerous interactions that took place inside the construct in UTAUT.
o Experience
According to Venkatesh et al. (2012), the capacity to use the specified technology signified by the length of experience and is often operationally defined as the passage of time from an individual's first usage of technology. Simply described, it is the process of improving one's ability to use technology through time.
H8a: Age, gender, and experience duration are moderating variable between the relationship of facilitating condition and behavioral intention
H8b: Age, gender, and experience duration are moderating variable between the relationship of hedonic motivation and behavior intention
H8c: Age and gender are moderating variable between the relationship of price value and behavioral intention
H8d: Age, gender, and experience are moderating variable between the relationship of habit and behavioral intention
H8e: Age, gender, and experience duration are moderating variable between the relationship of habit and use behavior
H8f: Experience duration is moderating variable between the relationship of behavioral intention and use behavior
• Technophilia (TEC)
Osiceanu (2015) explains that technophilia is characterized as a strong attraction to and curiosity with new technology. Consumers who are tech-savvy and wary of new items are more likely to have intention to buy (Egbue & Long, 2012). Numerous researches have demonstrated that technophilia has a significant influence on the behavioral intention for the adoption of electric vehicles (Abbasi et al., 2021). Based on the findings of this study, the following hypothesis will be developed:
H10: Technophilia has a significant influence on behavioral intention to use electric vehicles in Indonesia
• Perceived Environmental Knowledge (PEK)
Arcury and Johnson (2012) explain that Perceived Environmental Knowledge refers to a person's knowledge of an environment, ecosystem, and the influence of human actions on the environment. Customer interest in purchasing environmentally friendly items is considerably increased by perceived environmental knowledge, therefore, enhanced environmental understanding extends customer consumption habits (Rashid, 2009). In the case of adoption of electric vehicles, many studies have shown that perceived environmental knowledge has significantly influenced the behavioral intention (Abbasi et al., 2021). Based on the findings of this study, the following hypothesis will be developed:
H11: Perceived environmental knowledge has a significant influence on behavioral intention to use electric vehicles in Indonesia
• Perceived Functional Risk (PFR)
The perception that product innovations may not work optimally after going through the testing phase increases the functional risk, which deals with performance uncertainty (Ram & Sheth, 1989). Gunawan et al., (2022) found that Perceived Functional Risk has a negative impact on attitudes towards the use of electric vehicles. As a result, the following hypothesis was chosen for this study:
H12: Perceived Functional Risk has a significant influence on behavioral intention to use electric vehicles in Indonesia
• Perceived Financial Risk (PFN)
Financial risk is the likelihood that customers will incur losses as a result of paying more than is necessary to receive the product (Murphy & Enis, 1986). Gunawan et al. (2022) found that Perceived Financial Risk has a negative has a negative impact on attitudes towards the use of electric vehicles. As a result, the following hypothesis was chosen for this study:
H13: Perceived Financial Risk has a significant influence on behavioral intention to use electric vehicles in Indonesia
• Perceived Time Risk (PTR)
Perceived time risk is to determine lost time by the individuals, to ineffectively try to make people uncomfortable as they decide whether to purchase or adopt certain goods and services.
(Mitchell, 1992). Gunawan et al. (2022) found that Perceived Time Risk has a negative impact on attitudes towards the use of electric vehicles. As a result, the following hypothesis was chosen for this study:
H14: Perceived Time Risk has a significant influence on behavioral intention to use electric vehicles in Indonesia.
3.2 Measurement
The questionnaire is divided into three sections as explained below:
• A Likert scale of 1 to 5 will be used to evaluate any additional variables or constructs (with 1 disagree and 5 denoting agree).
• The demographic part will be evaluated by filling out the researcher's options.
• The behavioral component will be assessed in two ways: some respondents will fill out the section based on choices suggested by the researcher, while others will fill out the section freely.
3.3 Data Analysis
Partial Least Square (PLS) will be used in the study's structural equation modeling (SEM) to minimize the explained variation within an endogenous component as what Fornell and Bookstein (1982) explained.
3.3.1 Validity and Reliability
In order to calculate the indicator dependability coefficient, Wong (2013) states that each outside load can be squared. A value of 0.7 or above is preferred. Fornell and Lacker (1982) explain that the square root of the average variance extracted (AVE) counts for each latent construct must be greater than the correlation coefficients between the latent variables (0.5 or higher) to pass the discriminating validity test, while both tests must pass for the average variance extracted (AVE) counts to pass the convergent validity test. All the data gathered is pass the validity and reliability test.
4. Results and Discussion
• Performance Expectancy towards Behavioral Intention
H1 is acceptable since performance expectation was determined by this research's calculations to have a significant influence on behavioral intention of adopting electric vehicles in Indonesia. Performance expectancy has the largest significant impact on behavioral intention, according to the findings, which are in line with those of prior research by Venkatesh et al.
(2012) and Gunawan et al. (2022). This implies that people who use electric vehicles place a high value on their electric vehicles’ capacity to help users increase their productivity. This happens due to the performance expectancy concerns the expectations of electric vehicles users for their performance and future status in the context of transportation usage.
• Effort Expectancy towards Behavioral Intention
H2 is unacceptable since effort expectancy was determined by this research’s calculation to have an insignificant influence on behavioral intention of adopting electric vehicles in Indonesia. The outcome conflicts with those of studies by Venkatesh et al. (2012) and Gunawan et al. (2022) that explain the adoption of electric vehicles have found that social influence has a significant influence towards behavioral intention. This shows that while adopting electric vehicles, customers do not take the convenience of utilizing the electric vehicles itself. This happens due to the fraught complications as what Anfinsen (2019) explain, such the distance that an electric vehicle can go on a single charge that electric vehicles’ user might consider that utilizing an electric vehicle in not easy as gasoline vehicles.
• Social Influence towards Behavioral Intention
H3 is unacceptable since social influence was determined by this research’s calculation to have an insignificant influence on behavioral intention of adopting electric vehicles in Indonesia.
The outcome conflicts with those of studies by Venkatesh et al. (2012) that explain the adoption of electric vehicles have found that social influence has a significant influence towards behavioral intention. This implies that the decision for using electric vehicles is a personal decision. This happens due to the number of electric vehicles users in Indonesia still relatively small so that the power of influence to each other also still low.
• Facilitating Condition towards Behavioral Intention and Use Behavior
H4a and H4b is unacceptable since facilitation condition was determined by this research’s calculation to have an insignificant influence on behavioral intentions also on use behavior of adopting electric vehicles in Indonesia. The outcome conflicts with those of studies by Venkatesh et al. (2012) that explain the adoption of electric vehicles have found that facilitating condition has a significant influence towards behavioral intention and also use behavior. This suggests that the majority of users did not possess any necessary technological knowledge and assistance, also they lack or fail to seek assistance from other users when they run into problems when utilizing electric vehicles. This happens due to the lack of the infrastructure to support the development of electric vehicles in Indonesia, especially lack of the charging stations (Maulia, 2022).
• Hedonic Motivation towards Behavioral Intention
H5 is unacceptable since hedonic motivation was determined by this research’s calculation to have an insignificant influence on behavioral intention of adopting electric vehicles in
Indonesia. The outcome conflicts with those of studies by Venkatesh et al. (2012) and Gunawan et al. (2022) that explain the adoption of electric vehicles have found that hedonic motivation has a significant influence towards behavioral intention. This suggests that the enjoyment or delight that users derive from using the electric vehicles do not play a significant role in their decision to embrace electric vehicles. This happens due to the same feeling of driving an electric vehicle compared with gasoline vehicles. The drivers do not need to pick up any new abilities to drive (EfficiencyMaine, 2022).
• Price Value towards Behavioral Intention
H6 is unacceptable since price value was determined by this research’s calculation to have an insignificant influence on behavioral intention of adopting electric vehicles in Indonesia. The outcome conflicts with those of studies by Venkatesh et al. (2012) and Gunawan et al. (2022) that explain the adoption of electric vehicles have found that price value has a significant influence towards behavioral intention. This suggests that when selecting electric vehicles, people do not weigh the trade-off between the benefits of electric vehicles and the costs associated with using them. This happens due to the high price of the electric vehicles itself as what Alsamydai and Yousif (2019) explain, so that people consider that the value of electric vehicles usage is not worth the price compared to the gasoline vehicles. For Indonesia market itself, the price of electric vehicles is considered as high (Rahadiansyah, 2021).
• Habit towards Behavioral Intention and Use Behavior
H7a and H8a is acceptable since habit was determined by this research's calculations to have a significant influence on behavioral intentions and also on use behavior of adopting electric vehicles in Indonesia. In earlier research by Venkatesh et al. (2012) and Gunawan et al. (2022), habit was discovered to have a considerable influence on behavioral intention and use behavior.
The results are consistent with those findings. This suggests that a user is more likely to accept and utilize electric vehicles the more people use and become familiar with the system. This happens because of the advanced technology of electric vehicles such dynamic acceleration and regenerative braking that electric vehicle users may experience continuously when the more using electric vehicles (RenaultGroup, 2020).
• Moderating Factors
Among the other hypotheses, only H8f is acceptable since experience duration was determined by this research’s calculation to moderate the relationship between behavioral intention and use behavior. The outcome conflicts with the study by Venkatesh et al. (2012) that explains age, gender, and experience duration will moderate the relationship between facilitating condition, hedonic motivation, price value, and habit with behavioral intention and use behavior. In addition, H8c and H8e are partially accepted through one of its indicators.
Specifically, age is acceptable for becoming moderating variable between the relationship of price value and behavioral intention, and also gender is acceptable for becoming moderating variable between the relationship of habit and behavioral intention.
• Behavioral Intention towards Use Behavior
H9 is acceptable since behavioral intention was determined by this research's calculations to have a significant influence on use behavior and also on use behavior of adopting electric vehicles in Indonesia. In earlier research by Venkatesh et al. (2012) and Gunawan et al. (2022), behavioral intention was discovered to have a considerable influence on use behavior. This
suggests that the factors in this study's analysis that were connected to behavioral intention alone were sufficient to promote users' adoption of the electric vehicles. This happens due to the more intention that people must use electric vehicles, the more people start and often to use electric vehicles.
• Technophilia towards Behavioral Intention
H10 is unacceptable since technophilia was determined by this research’s calculation to have an insignificant influence on behavioral intention of adopting electric vehicles in Indonesia.
The outcome conflicts with those of studies by Abbasi et al. (2021) that explain the adoption of electric vehicles have found that technophilia has a significant influence towards behavioral intention. This suggests that when selecting electric vehicles, people have a lack of attraction and curiosity about electric vehicles as a new technology. This happens due to the lack presence of supporting ecosystem for electric vehicles in Indonesia (Kharisma, 2022).
• Perceived Environmental Knowledge towards Behavioral Intention
H11 is unacceptable since perceived environmental knowledge was determined by this research’s calculation to have an insignificant influence on behavioral intention of adopting electric vehicles in Indonesia. The outcome conflicts with those of studies by Abbasi et al.
(2021) that explain the adoption of electric vehicles have found that perceived environmental knowledge has a significant influence towards behavioral intention. This suggests that when selecting electric vehicles, people have a lack of understanding regarding the green environment. This happens because Indonesian people has lack awareness related to environmental sustainability, specifically due to the dependence on fossil energy (Andika, 2022).
• Perceived Functional Risk towards Behavioral Intention
H11 is unacceptable since perceived functional risk was determined by this research’s calculation to have an insignificant influence on behavioral intention of adopting electric vehicles in Indonesia. The outcome conflicts by Gunawan et al. (2022) that explain the adoption of electric vehicles have found that perceived functional risk has no significant influence on the attitude towards use of electric vehicles in Indonesia. This suggests that when people try to utilize electric vehicles, they believe that the electric vehicles will work ineffectively. This happens due the battery issue regarding the battery performance such, the battery life cycle that electric vehicles users might suffers (Kh, 2022).
• Perceived Financial Risk towards Behavioral Intention
H12 is unacceptable since perceived financial risk was determined by this research’s calculation to have an insignificant influence on behavioral intention of adopting electric vehicles in Indonesia. The outcome conflicts by Gunawan et al. (2022) that explain the adoption of electric vehicles have found that perceived financial risk has no significant influence on the attitude towards use of electric vehicles in Indonesia. This suggests that when people try to utilize electric vehicles, they believe that they will incur losses because of paying more than is necessary to receive electric vehicles. This happens due to the post-sale which is still unclear what will happen in the future that might affect the economic value for the buyer (Anshori, 2022).
• Perceived Time Risk towards Behavioral Intention
H13 is unacceptable since perceived time risk was determined by this research’s calculation to have an insignificant influence on behavioral intention of adopting electric vehicles in Indonesia. The outcome conflicts by Gunawan et al. (2022) that explain the adoption of electric vehicles have found that perceived time risk has no significant influence on the attitude towards use of electric vehicles in Indonesia. This suggests that when people try to utilize electric vehicles, they believe that they will lose their time. This happens due to the risk of electric vehicles users might suffer, as what Anfinsen (2019) explain, such the duration of the charging time.
5. Conclusion
The goals of this to use the extended UTAUT2 model to analyze the adoption of electric vehicles in Indonesia, to determine whether the recently added factors to the model have a significant impact on that adoption, and to provide recommendations for electric vehicles that will help Indonesia adopt it more quickly. Through the use of the SEM-PLS approach was used in this study's analysis of the data. According to this study, it turns out that only 2 out of 12 indicators that significantly impact the behavioral intention to use electric vehicles in Indonesia, that are performance expectancy and habit. Additionally, habit and behavioral intention also have an impact on the use behavior of electric vehicles in Indonesia. Effort expectancy, social influence, facilitating condition, hedonic motivation, price value, habit, technophilia, perceived environmental knowledge, perceived functional risk, perceived financial risk, and perceived time risk are the variables not significantly impacting the behavioral intention to use electric vehicles in Indonesia. Therefore, it can be concluded that the consumer adoption of electric vehicles in Indonesia is still low due to the high number of rejected variables in this study that influence the intention to use and the actual use of electric vehicles in Indonesia.
6. Acknowledgement
First and foremost, I want to express my gratitude to Allah SWT for providing me with the best chance and direction. Additionally, to who have contributed to my development over the past three incredible years. They are my nuclear family, my mother and father, my sister and my brother-in-law, my unborn nephew. To mention all my extended family. Also Mrs. Fitri Aprilianty as my supervisor. To add, my Hegar Asih friend, Hilal, Jawul, Fito, Fikri. Also, Technische Hogeschool friends. Also, Matthew Alan and Diana Marchella.
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