Acceptance of ELV Management: The Role of Social Influence, Knowledge, Attitude, Institutional Trust, and Health Issues

Abstract

The growth of Indonesia’s automotive sector has increased the number of end-of-life vehicles (ELVs), making ELV waste management a major issue. Most countries, such as Japan, China, and Europe, manage ELV waste well, but developing countries still do not. In developing countries, little is known about ELV social admissions. This study analyzes ELV management social acceptance in developing countries. Three hundred nine respondents from Jakarta, Bogor, Depok, Tangerang, and Bekasi (the district in Indonesia) were surveyed in a cross-sectional. A set of questions was designed to determine social acceptance (attitude, knowledge, social influence, institutional trust, health issues, and acceptance). After passing validity and reliability tests, the hypothesized research model was estimated using structural equitation. According to this study, social influence, attitude, knowledge, institutional trust, and health issues influenced public acceptance. The health issues variable was also a good moderator (Adj. R2 = 0.173, p < 0.001, average path coefficient = 0.299). The analysis of social acceptance models related to ELV management found that social influence, attitude, knowledge, and institutional trust play a role in one’s desire to accept a new rule, and health issues can strengthen a person in the admission process.

1. Introduction

Due to the rapid growth of the automotive industry in Indonesia, environmental pollution has become one of the biggest problems today. The Organization for Economic Cooperation and Development (OECD) states that the automotive sector grows by 4% every year. This increase in the automotive sector also contributes to environmental degradation by contributing to 5% of industrial waste worldwide [1]. Seeing the negative impact of the growth rate of the automotive industry, end-of-life vehicle (ELV) recycling is a mandatory thing that the Indonesian government must do, not only to overcome the impact on the environment but also to become a new source for industry finance.

Although vehicle sales in Indonesia are increasing slowly, the country has a higher rate of vehicle sales than Malaysia, as evidenced by the Organization Internationale des Constructeurs d’Automobiles’ record production of automobiles (OICA) [2]. From 2012 through 2021, Indonesia ranked fourth in overall automobile production after the United States and South Korea (see Figure 1). This shows that Indonesia has the highest automotive industry level in ASEAN (Association of South-East Asian Nations).

ELV is one of the most common household hazardous wastes [3,4,5]. ELV is considered dangerous because it can pollute the environment if not properly managed [6,7,8,9]. It is not easy to manage ELV because it has a complex structure [10]. ELV itself is expected to continue to increase, and it is estimated that by 2020 there will be 80 million units that fall into the ELV category. Kaminska [11], in her paper, explained that ELV waste contributes to human carcinogenic toxicity; this affects refraction and forms fine particles that can interfere with the lungs. Because oil waste, coolant, and gear oil are disposed of, ELV can have an impact on water quality [12,13,14].

Table 1. Hazardous ELV waste/components and their main characteristics [15].

Hazardous Waste Components	Characteristic
Waste liquid gas storage tank	Reactivity (R), flammability (F)
Unsafe airbag	Reactivity(R)
Waste battery	Toxicity (T), Corrosivity (C)
Waste gas purification catalysts	Toxicity (T)
Waste oil	Flammability (F)
Waste air conditioning refrigerant	Toxicity (T)

shows some components of ELV and their content.

The significance of implementing effective ELV management is to create a healthy environment and improve the automotive industry, which is not always accepted. In developing countries such as Indonesia, where most people prefer to use older or pre-owned vehicles for financial reasons, the implementation of ELV policies faces a formidable obstacle. Low environmental awareness is a significant contributor to the government’s difficulties in formulating ELV management policies.

The Indonesian government attempted to implement periodic emission test regulations, but these regulations were immediately rescinded due to widespread community opposition. The Euro 4 standardization has also been attempted, but it has not been successful in Indonesia. The high number of community rejections has always impeded stakeholders’ efforts to resolve this issue. In addition, social studies on the acceptance of regulations have never been conducted in Indonesia.

This article presents the findings of a survey conducted in Indonesia to determine the various factors that can predict public acceptance of ELV policy. Vehicles classified as ELVs are identified in this study based on their age (>15 years) and whether they can be used or repaired for a variety of reasons (accidents, natural disasters, absence of spare parts, and finances). The parameters employed are adaptations of existing acceptance models, such as the theory of planned behavior, the theory of reasoned action, and the theory of interpersonal behavior, in which we attempt to investigate internal factors such as knowledge, attitude, and institutional trust, as well as external factors (social influence) and health issues as moderator variables [16,17,18,19,20,21]. The study’s primary objective was to identify potential predictors of policy acceptance from a series of social influence, attitude, knowledge, institutional trust, and health issue constructs. The study’s second objective was to encourage policymakers to consider the fundamental aspects of social acceptance before making decisions.

1.1. End-of-Life Vehicles Practice

In 2000, the EU enacted a directive on ELV waste management by introducing the ELV Directive (2000/53/EC) [22]. It is intended to reduce waste coming from ELV. The recovery of ELV vehicles itself is targeted to reach 85% of the weight of the vehicle, with a maximum energy recovery of 5%, and 80% will be used as reusable and recyclable materials [23].

Recycling involves several processes. 1. Users deliver their vehicles to collection facilities; 2. Collection facilities are dealers or repair shops that collect ELVs; 3. An authorized ELV processing company disposes of hazardous vehicle parts in landfills, such as fuel, oil, tires, batteries, or air conditioning cooling gas, as well as reusable parts (referred to as “other components” in Figure 1), such as starters, suspensions, or engines; 4. Crushing plants receive the decontaminated ELV and crush it to separate it into three fractions using magnetic processes: ferrous metals, non-ferrous metals, and the rest (a mixture of rubber, foam, and plastic known as ASR); 5. The post-crushing plant receives non-ferrous metal fractions from crushing plants and separates primarily aluminum, zinc, and copper using vortex currents and density processes (see Figure 2) [22,23,24].

1.2. End-of-Life Vehicles Practices in Indonesia

The lack of regulations on automobiles and motorcycle recycling in Indonesia has negatively impacted the high number of ELVs on urban roads [25]. In addition, issues surrounding the waste management sector in Indonesia have not had a serious impact on increasing public awareness. The Yano Research Institute [26] stated that 248,676 ELVs were still operating and not properly managed in Indonesia in 2020 (see

Table 2. Number of ELV in Indonesia [22].

Year	2013	2014	2015	2016	2017	2018	2019	2020
No. of ELV	124.002	152.723	178.524	176.370	160.389	175.493	218.337	248.676

).

The informal sector manages ELV in Indonesia. They collect and recycle without establishing clear guidelines [27,28]. The informal sector handles industrial and B3 waste and then delivers it to the formal sector. This waste is collected by mobile scavengers and crews that are, on average, filled by the surrounding communities, and is then sold to collectors along with other recyclables that have economic value (cans, plastic); collectors play the role of intermediaries between collectors and “Bandar” who reach other formal and informal recycling plants. Collectors are responsible for collecting, selecting, separating, cleaning, and pre-maintaining, all of which is done manually with no training or occupational safety standards [26].

Although the car demolition industry in Indonesia is still unrecognized, some local companies have opened places to dismantle vehicles. The company buys used vehicles from junk collectors until it works with insurance companies to buy vehicles that can no longer be repaired. This disassembling practice carries out metal picking by performing open combustion for wire harnesses. The car’s body is also cut manually and used as pieces of steel. Informal recyclers only focus on recycling iron from vehicles, while other materials such as glass, tires, and plastic parts are processed separately.

This is an out-of-ordinary practice that has resulted in several mantlings of car bodies with a crowbar and other equipment, frequently resulting in employee accidents in the form of hand and foot injuries. Broken glasses are also common causes of employee injuries [29]. Workers have developed skin disorders because of the remaining oil, which is always thrown away carelessly [30]. As a result, they frequently experience respiratory issues or ISPA [31,32,33,34].

1.3. Dumpsites in Indonesia

Like other developing countries, Indonesia still does not have a recycling or vehicle waste recovery program. Vehicle waste is still dumped in landfills just like other solid waste. There are very few landfills in Indonesia, because of which these landfills can be overcapacitated. The Indonesian government has issued rule No. 18/2018 regarding waste management to combat this issue, but this regulation is ineffective against existing waste.

In Indonesia, waste management is commonly referred to as TPST (integrated waste management place). A TPST is a waste collection, sorting, reusing, recycling, and processing facility. After the TPST has processed waste, it is transferred to the TPA (landfill). A TPA is a safe location for humans and the environment to process and return waste to the environment. The significant distinction between TPST and TPA is the waste management system’s policy.

There are several TPSTs in Indonesia. These include Bantargebang in Bekasi, Suwung Landfill in Denpasar, Sarimukti Landfill in Bandung, Piyungan Landfill in Yogyakarta, and TPA Terjun in Medan. The number of landfills in Indonesia is insufficient to solve the country’s waste problem. As a result, vehicle waste (ELV) is still classified as solid waste and waste management has not yet been properly sorted. In Indonesia, scrap metal dealers typically dismantle vehicle waste by hand, with the intention of disposing of it in the existing landfills. In light of this, it can be asserted that the absence of landfills and waste management in Indonesia makes waste production a pressing issue.

2. Materials and Methods

2.1. Study Subjects

The study was conducted in JABODETABEK (Jakarta, Bogor, Depok, Tangerang, and Bekasi), Indonesia. This study involved a total of 309 adults over 18 years old who have vehicles such as motorcycles or cars. Sampling is a problem during the COVID-19 pandemic, so researchers have difficulties in getting larger samples. The selection of JABODETABEK itself as a sampling place is because JABODETABEK is a metropolitan city in Indonesia with a large population and the most populous number of vehicles in Indonesia.

2.2. Study Design

The current study is a cross-sectional survey conducted in Jakarta from November 2021 to February 2022. The study used self-administered questionnaires given to randomly selected respondents.

2.3. Participant

Cross-sectional studies using surveys were conducted on adult respondents. A total of 309 (213 male and 96 female) people in Jakarta participated in this study and completed the survey between November 2021 and February 2022. A simple random sampling technique selected participants. The participants’ attitude, knowledge, social influence, institutional trust, health issues, and acceptance of ELVs were investigated. All questionnaires that were filled out were then scored in detail.

2.4. Data Collection

Two researchers were assigned to administer the questionnaire. The selected volunteers were those who agreed to fill out the questionnaire. The participants were explained the purpose of research and provided a guide regarding how to fill out the questionnaire. The set of questions was self-managed and structured based on previous research. Twenty respondents took part in the questionnaire trial, and the results were used to make revisions. The questionnaires were written in Indonesian under the Enhanced Spelling System (EYD) so that all respondents could easily understand them. In the survey, 64 questions were divided into six main areas. In order to obtain valid data, those who participated in the survey were instructed to choose as many relevant criteria as they could. Demographic data such as gender, employment, income, and place of residence were provided in the first part of the study.

The second section delves into the participants’ perspectives on ELVs. The question section is designed to elicit public knowledge about ELV management. The fourth section contains a series of questions designed to elicit social influence, while the fifth section contains questions designed to elicit institutional trust. The sixth section is a series of statements about health issues caused by ELVs, and the final question was created to determine public acceptance of ELV management. Figure 3 provides a flowchart of the research process.

3. Results

3.1. Demographic Characteristic

As shown in

Table 3. Demographic characteristics of the participants (n = 309).

Demographic Factors	Classification	Frequency	Percentages
Gender	Male	213	68.90%
	Female	96	31.10%
Age	18–20	7	2.30%
	21–30	44	14.20%
	31–40	61	19.70%
	41–50	95	30.70%
	51–60	78	25.20%
	>60 years old	24	7.80%
Working status	Servant	163	52.80%
	Permanent private employee	92	29.80%
	Private employee on contract	17	5.50%
	Entrepreneur	37	12.00%
Income	<IDR 2500.000	39	12.60%
	2,500,000–3,500,000	18	5.80%
	3,501,000–4,500,000	24	7.80%
	4,501,000–5,500,000	19	6.10%
	5,501,000–6,500,000	2	0.60%
	7,501,000–8,500,000	14	4.50%
	8501,000–9500,000	25	8.10%
	9,501,000–10,500,000	24	7.80%
	>IDR 10,501,000	136	44.00%
Residence	Family house	62	20.10%
	Private house	209	67.60%
	Rent	8	2.60%
	Contract	16	4.50%
	Boarding house	14	4.50%
Educational level	Senior high school	24	7.80%
	Bachelor	82	26.50%
	Postgraduate	203	65.70%

, 395 survey responses were collected, 309 participants were involved in this analysis, and as many as 86 respondents’ data were excluded from the analysis due to being deemed invalid. Men made up as many as 213 (68.9%) of the study respondents, while women made up as many as 96 (31.1%). Most of them were civil servants, with 163 (52.8%) with incomes of more than IDR 10 million, which was the income of a majority of the respondents in this study (44%). More than half of the 209 respondents (67.6%) lived in private homes, and the majority of the respondents, 203 (65.7%), had a master’s or doctoral degree.

3.2. Questionnaire Analysis

Structural equation modeling (SEM) analysis is a method used in this study by combining aspects of simultaneous equations of systems, path analysis, or regression analysis with analytical factors. SEM analysis in this study was carried out using the WARPLS 7.0 application. Before the survey, the questionnaire’s reliability was confirmed using Cronbach’s alpha tests. The alpha coefficient ranged from 0 to 1, with 1 indicating the highest level of reliability. The scale used to determine the questionnaire’s reliability is shown in

Table 4. Cronbach alpha range.

Cronbach Alpha	Reliability
α ≥ 0.9	Excellent
0.9 > α ≥ 0.8	Good
0.8 > α ≥ 0.7	Acceptable
0.7 > α ≥ 0.6	Questionable
0.6 > α ≥ 0.5	Poor
A > 0.5	Extremely poor

.

A set of prepared questions was tested for reliability. The test results found that the alpha coefficient score for attitude questionnaires was 0.897, knowledge 0.865, social influence 0.866, institutional trust 0.896, health issues 0.961, and acceptance 0.846. Based on Table 4, the entire questionnaire can be used.

3.2.1. Social Influence Phase

In this study, the total number of answer options for the overall questions was 5. Whereas 1 and 2 are considered rejected in the calculation, 3 is considered neutral, and 4 and 5 are considered to agree.

Table 5. Social influence toward ELV management (n = 309).

No.	Item	Agree	Neutral	Disagree
1	The whole community supports the implementation of ELV regulations.	113	122	74
2	The government gives support in providing understanding related to ELV regulations	116	100	83
3	Important people in government support the implementation of the ELV policy.	68	121	120
4	All stakeholders recommend the implemention of ELV policy for the creation of a healthy automotive environment.	123	110	76
5	I saw the acceptance of society first before I followed a new rule.	129	111	69
6	I don’t want to accept the new rules until my friend/s accept them first.	125	102	82
7	I will only follow the new rules if I feel others will also agree.	141	68	100
8	The social environment determined my attitude to accept the new rules.	119	85	105
9	I spend a lot of time talking about my theme of new policies.	115	75	119
10	I often seek advice from my friends about the rules.	105	98	106
11	My friends or neighbours will often give me advice on good policies to follow.	120	82	107
%		37.59%	31.69%	30.72%

describes social influence for ELV management implementation. The majority of the respondents (37.59 %) agreed with the plan to implement ELV management in Indonesia because they perceive government and social influence, while approximately 31.69 % chose to be neutral, and the rest disagreed (30.72 %). The majority of the respondents agreed to support the implementation of ELV management, but the number is small compared to the number of respondents who refused and chose to remain neutral. This demonstrates that stakeholders must work to improve social influence for the implementation of ELV management to be accepted by the social community.

3.2.2. Attitudes towards ELV Phase

Table 6. Attitudes toward ELV management (n = 309).

No.	Item	Agree	Neutral	Disagree
1	I support the idea of end-of-life vehicles.	161	70	78
2	I want to implement the ELV policy.	186	84	39
3	I support the idea of end-of-life vehicles as it reduces the risk of accidents.	180	88	41
4	End-of-life vehicle management programs can help reduce air pollution and maintain environmental sustainability.	234	58	17
5	I will support all ideas relating to end-of-life vehicles included in the imposition of processing fee payments.	174	70	65
6	End-of-life management can make it easier for vehicle owners to dispose off their end-of-life vehicles.	183	61	65
7	The idea of end-of-life vehicles is very good and should be made a policy in the automotive field of the country.	178	54	77
8	Policies related to ELV can facilitate the end-of-life vehicle management process.	173	66	70
9	End-of-life vehicle policy must be mobilized to reduce the “broken car” problem faced by the state.	191	53	65
10	I agree with the imposition of affordable fees for end-of-life vehicle management.	171	64	74
11	This policy will make it easier for car owners to solve their ‘bad vehicles’ problems.	212	62	35
12	The government must launch a thorough campaign on end-of-life vehicle policies to improve community knowledge.	248	62	35
%		61.19%	21.15%	17.65%

describes the attitude of respondents related to ELV management. This section includes (a) agreeing to the idea; (b) security aspects; (c) aspects of affection and aesthetic value; and (d) incentive aspects of attitude toward policies/proposals.

From Table 6, it is found that 61.19% of the public has a good attitude towards ELV management, 21.15% choose to be neutral, and 17.65% do not behave well regarding ELV policy. It was also concluded from Table 6 that the majority of respondents have a positive attitude toward ELV management. This outcome is beneficial to the government’s implementation of ELV management. According to the study, attitude is a significant predictor of the acceptance of a new policy at the level of both individuals and society as a whole.

3.2.3. Knowledge towards ELV Phase

Table 7. Knowledge of ELV management (n = 309).

No.	Item	Agree	Neutral	Disagree
1	I know the concept of end-of-life vehicles (ELVs).	103	131	75
2	I know the concept of reuse for end-of-life vehicles.	99	125	85
3	I know the concept of recycling solid waste.	180	77	52
4	The importance of solid waste recycling should be emphasized as a policy goal	185	58	66
5	I know the benefits of implementing the ELV policy	129	103	77
6	Solid trash, such as automotive parts, can be retrieved at the end of life	132	85	92
7	Vehicle components that have been thoroughly examined for quality and endurance can be reused	162	52	95
8	The reuse process can help to ensure environmental sustainability.	146	63	100
9	Reuse has the potential to save energy.	146	63	100
10	Reuse can save by minimising the usage of new resources you consume.	157	74	78
%		46.57%	26.89%	26.54%

provides an overview of the respondents’ ELV management knowledge. This phase delved deeply into knowledge about the benefits of ELV management, the concept of recycling, and the classification of ELV waste.

According to Table 7, most respondents (46.57%) know ELV management, 26.89% of the respondents do not know, and 26.54% of the respondents lack knowledge of ELV management. These findings also showed that less than 50% of the respondents are knowledgeable about ELV management. This result also demonstrated that the government’s failure to educate the public about ELV management has resulted in low public awareness of ELV management. According to Bardal et al. [35], a community’s acceptance of rules may be hindered by the public’s lack of knowledge regarding a particular policy. Measures are required to increase public awareness of ELVs; alternatively, advertising and the procurement of seminars on the dangers of ELVs and the benefits of ELVs, when properly managed, can be used to educate the public.

3.2.4. Institutional Trust Phase

During this phase, a set of questions was developed to determine how much the respondents trust the government when it comes their ability to work, making policies, and knowing the public’s trust in the government paying attention to the community (see

Table 8. Institutional trust.

No.	Item	Trust	Neutral	Untrusted
1	To what extent do you agree with the following statement? “The current local government is capable of making good decisions regarding the problem of pollution.”	1.34	75	100
2	Overall, the local government is a capable and professional institution for creating policy.	117	80	112
3	The local government performs its role of creating policy advice very well.	144	67	98
4	I believe that the local government would act in my best interest.	89	130	90
5	The local government is interested in social well-being.	125	103	81
6	The local government is truthful in its dealings with me and society.	132	78	99
7	The local government keeps its commitments.	69	126	114
%		37.45%	30.47%	32.09%

).

According to Table 8, the majority of respondents (37.45%) trusted the role of the government in policymaking, while 30.47% chose to answer neutrally, and 32.09% did not trust the government. Although the percentage of respondents who trust the government is greater than the percentage who do not, the difference is not statistically significant, so it cannot be concluded that the majority of respondents believe in the government. The number of individuals who lack trust in the government remains a significant issue. According to Vries et al. [36], people’s reluctance to comply with government policies is caused by low public confidence in the government. An increase in the public’s confidence in the government’s leadership ability is a formidable challenge.

3.2.5. Health Issue Phase

Table 9. Health issue phase.

No.	Item	Agree	Neutral	Disagree
1	Smoke from old vehicles can cause respiratory illnesses.	237	39	33
2	Vehicle fumes include carcinogenic qualities, which can cause cancer.	255	37	17
3	Smoke exposure can increase the risk of heart disease.	168	39	2
4	Inhaling old vehicle fumes can cause neurological disorders such as stroke and dementia.	251	47	11
5	Vehicle fumes can disrupt my reproductive system.	243	55	11
6	Oil from the rest of the vehicle can cause neurological diseases such as stroke and dementia. Used vehicles are a toxic waste.	191	86	32
7	Oil waste from used vehicles poses a risk of kidney and nerve damage.	189	97	22
8	Skin disorders can be caused by exposure to leftover oil from used autos.	202	86	21
9	Resting Freon on ELVs can cause neck swelling.	197	104	8
10	Freon can irritate the eyes, nose, and tongue.	209	88	12
11	The process of destruction of ELVs traditionally causes musculoskeletal injuries (injuries to muscles, bones, joints).	178	108	23
12	Metals emitted by out-of-service vehicles can cause nervous system damage.	222	68	19
13	The lack of safety standards in end-of-life vehicles (ELVs) increases the risk of road accidents.	203	68	38
%		70.10%	23.54%	6.36%

summarizes ELV’s statements on health and safety issues. The statement provided in this section focuses on ELV-related issues such as health, safety, and environmental impact.

According to Table 9, the majority of respondents (70.10%) were aware of the health, safety, and environmental impacts that ELVs can cause. In comparison, only 6% were unaware of the impact of ELVs, and as many as 23.54% chose to be neutral. As shown in Table 9, 70.10% of respondents were extremely worried about health-related issues. Because most of the study’s respondents have undergraduate and postgraduate degrees, it’s natural that they know about health problems, but most Indonesians with low education levels are not aware of this issue [37,38,39]. Following research conducted by Bai et al. [16], which indicates that health aspects can increase public awareness of accepting and enforcing regulations that can have an impact on their health, it can be seen that the people of Indonesia are very concerned about their health, making it easier for policymakers to design and implement ELV policies that can directly help to reduce pollution.

3.2.6. Acceptance towards ELV Management Phase

Table 10. Social acceptance phase.

No.	Item	Agree	Neutral	Disagree
1	I choose a used vehicle as a private vehicle because it is cheap.	253	42	14
2	Buying an old car will make a loss for me.	180	91	38
3	The government should support infrastructural development to facilitate the recovery of end-of-life vehicles.	206	42	61
4	I support the idea of end-of-life vehicle management charges if required.	232	63	14
5	The issue of debt burden on the bank made me choose to use the old vehicle instead of the new vehicle.	114	78	17
6	I will not keep old vehicles over 15 years old as they are not safe to use.	122	107	80
7	I am willing to sell my old vehicles in support of government policy.	242	53	14
8	I will do periodic emissions tests to look at my vehicle’s eligibility.	159	91	59
9	I will not keep an old vehicle above 15 because it belongs to a wearable vehicle.	59	113	137
10	Because of the bank’s debt burden, I chose to use the old vehicle rather than the new vehicle.	232	56	21
11	I will do periodic emissions tests to see the feasibility of my vehicle.	143	58	108
%		58.87%	24.07%	17.07%

summarizes the respondents’ acceptance of ELV policies. During this phase, a series of questions focused on the respondents’ desires to follow government policies related to vehicle emissions, sell their old vehicles, and support ELV policies. According to the results of these questions, most respondents supported the assessment of ELV management (58.87%). In total, 17.07% of those polled opposed the ELV policy, while the remaining 24.07% were undecided.

Table 10 demonstrates that more than 50% of the respondents were aware of the ELV policy’s implementation, but the government has much work to do in improving the presentation of those who wish to accept this policy. In total, 41.14% of the respondents chose to be neutral and even opposed the implementation of this policy. Government work increases trust by focusing on multiple factors, which include social influence, attitude, knowledge, institutional trust, and health considerations [40].

3.2.7. Relationships between Social Influence Variables, Attitudes, Knowledge, Institutional Trust, Health Issues, and Acceptance

Several independent variables were chosen to examine the direct and indirect relationships between the respondents’ acceptance of ELV management and subsequent path analysis. The analysis model employed is similar to that used in previous studies on regulatory acceptance [32,33,34,35]. The path proposed in this study is depicted in Figure 4. Overall, the regression model had a good model fit (Adj. R2 = 0.703, F = 58.2, p = 0.00). Table 6 summarizes the effects of each of the variables in the model on the acceptance of ELV management.

Table 11. Direct and indirect effects of independent variables on ELV management acceptance.

	Direct Effect Betacoef. (p-Value)	Indirect Effect Beta Coef. (p-Value)
Social influence	0.26 (0.00)	0.94 (0.00)
Attitude	0.16 (0.00)	0.61 (0.00)
Knowledge	0.36 (0.00)	0.47 (0.00)
Institutional trust	0.35 (0.00)

details the direct and indirect standard effects of the selected variables on social acceptance (social influence, attitude, knowledge, and institutional trust).

The model’s findings indicate that social influence, attitude, and knowledge contribute significantly to institutional trust. Following that, it is demonstrated that health issues modifies the relationship between institutional trust and acceptance. The strongest relationship in this model is between social influence and knowledge (β = 0.527), followed by the strongest relationship between social influence and attitude (β = 0.334), and the weakest relationship in this model is between knowledge and institutional trust (β = 0.124). Overall, the regression model had a good model fit (Adj. R2 = 0.173, p < 0.001, average path coefficient = 0.299).

The effect of health issues as a mediator variable capable of strengthening or weakening the relationship between institutional trust and acceptance is depicted in Figure 5. According to Figure 5, the health issues variable has a value of β = 0.30 and a p-value of 0.01, indicating that it is capable of acting as a good mediator by improving the relationship between institutional trust and acceptance, as indicated by the increase in the R2 value; before the moderator variable was added, R2 was 0.12; after adding the moderator variable, R2 increased to 0.20.

4. Discussion

In this paper, we conducted a survey to collect data on the relative impact of various levels of individuals (social influence, attitude, knowledge, institutional trust, and acceptance) on policy acceptance and to determine whether health issues can increase a person’s acceptance of policies. This is the first study in Indonesia to examine the social factors influencing public acceptance of ELV management. Additionally, the paper contributes to the literature on public attitudes toward policies to mitigate the negative consequences of older vehicle use. In this paper, we present a framework for delving deeply into the public’s reaction to ELV policy, assuming that public acceptance is critical to the government’s successful implementation of the ELV rules. We created this framework in response to the problems associated with ELV vehicles in Indonesia and other developing countries.

This study identified social acceptance patterns associated with ELV management. According to the findings, social influence, knowledge, attitude, institutional trust, and medical issues have a significant impact on social acceptance. This study revealed that each variable has a significant effect on acceptance. Using health issues as moderator variables, the findings of this study also reveal a new pattern of acceptance. As demonstrated by the increase in the value of R2 from 0.12 to 0.20, health issues have been shown to strengthen the relationship between social influence, knowledge, attitude, and institutional trust in regard to acceptance. Moreover, our proposed acceptance model is a good model (Adj. R2 = 0.703, F = 58.2, p = 0.00), which is capable of predicting an individual’s acceptance of ELV management.

The following sections summarize the major findings. First, we discovered that an overwhelming majority of respondents supported the implementation of ELV management. They believe that ELV management will provide solutions to urban air pollution and enable the capital’s vehicle fleet to be reduced. The findings are consistent with previous research on low-emission zone acceptance [41,42], which indicated that the respondents expected to accept a cap on the number of vehicles on urban roads to create pollution-free areas. Additionally, the respondents expected adequate and comfortable public transportation to reduce costs, decrease the number of vehicles operating in urban areas, and reduce air pollution. The data we obtained appears to be associated with periodic emissions testing policies implemented in Indonesia to reduce the number of unfit-for-use vehicles.

Secondly, this study confirms previous research [43,44]; bivariate analysis revealed a significant correlation between acceptance of ELV management and trust in government, attitudes, knowledge, and social benefits, as well as concerns about the health consequences of ELVs that are still used and not properly managed. This factor can be incorporated into conceptual models to explain environmental policy. The results of this test are consistent with the theory of planned behavior, in which the factors that drive an individual’s acceptance come from society and the individual himself. At the societal level, we see the variable of social influence, which provides full encouragement so that individuals are willing to accept and implement a policies; at the individual level, attitudes, knowledge, and trust in government are factors that greatly contribute to increasing acceptance.

Thirdly, based on the path analysis results, we determined that social influence has been the primary factor explaining the difference in acceptance between individuals. According to previous research [45,46,47], social influence is the most influential variable in determining acceptance, followed by attitudes and knowledge. Additionally, our data indicates that institutional trust plays a significant role in acceptance. In recent research, individual trust in government has increased an individual’s desire to follow every rule imposed by the government. Intriguingly, in Indonesia, attitude has a relatively small effect on people’s acceptance.

Additionally, our model demonstrates that, consistent with previous research [48,49,50], the critical role of health concerns can increase a person’s acceptance of regulations. In our analysis, social influence, attitude, and knowledge had a significant indirect effect on acceptance. We can conclude from the data that prior social influence directly affects attitude and knowledge, mediated by institutional trust, which are positively associated with policy acceptance. Finally, as evidenced in this study, health issues can act as good moderators, increasing or decreasing the relationship between institutional trust and acceptance.

This research is the first of its kind conducted in Indonesia related to ELV management, which is seen from a social point of view, where so far research related to ELV has always focused on technical issues. The findings of this study have a variety of implications. Policymakers should emphasize the positive impact of ELV management on the community’s and environment’s quality of life. Additionally, the fact that the government’s indifference to the problem of ELV can have enormous consequences for the community’s health, the environment, and the automotive industry means that ELV policy cannot be implemented immediately because some groups continue to oppose the regulation because of perceived injustices. In this sense, the government’s involvement in supporting the community through education about the potential health consequences of ELV policies should be considered in increasing social acceptance of ELV policies. For practitioners, this study proposed models that can assist in evaluating various social acceptance factors. Regarding the acceptance of ELV management, greater emphasis should be put on the significance of health concerns in increasing acceptance.

5. Conclusions

In this paper, we aim to understand the factors that explain the social acceptance of the ELV policy. Our findings added to the understanding of people’s attitudes towards new policies to reduce the negative impact of ELVs on the environment. We used a questionnaire to gather supporting data for the current ELV concerns in Indonesia. Our research may still be limited, so that we cannot reach a thorough conclusion about public acceptance. This paper argues that social influence indirectly contributes to increased social acceptance, and health issues significantly strengthen or weaken a person’s acceptance of policies related to the environment.

The findings of this study have the potential to serve as the foundation for the development of new policies in which the government is required to pay attention to aspects of the formation of social acceptance. Additionally, the findings of this study show that the low level of public trust in government can serve as an evaluation for the government to increase their credibility.

We must acknowledge that this study has numerous limitations. First, the study sample was small due to the COVID-19 pandemic. Secondly, since this research was limited to JABODETABEK, it cannot describe the acceptance of the ELV policy by the entire Indonesian population. In this study, we did not consider the ELV policy instruments of other nations. Comparing ELV admissions from various nations will enhance comprehension. Thirdly, the majority of the population in this study had a master’s or doctorate degree and tended to live in their own homes or families, causing them to have a high awareness of the impact of ELVs. Fourth, this research does not adhere to a particular theory. Despite some limitations, the model proposed in this study can serve as a useful reference for predicting social acceptance of ELVs in the JABODETABEK region.

For future research, several other variables, such as past experience, perceived usefulness, behavioral intention to use, and perceived ease of use, can be used to examine social acceptance factors more comprehensively. A qualitative approach is also employed to gain a comprehensive understanding of an individual’s acceptance of ELV policies. In addition, longitudinal studies can be chosen to obtain more comprehensive pictures of community acceptance behavior.