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Factors affecting students' intention to use electric buses in Ho Chi Minh city
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The research "Factors affecting students' intention to use electric buses in Ho Chi Minh city" will provide a multi-dimensional view of the transition to electric buses, with the hope that the results from this research will contribute to the construction of a public transportation system. effective, sustainable, and beneficial to both the community and the environment.
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Nội dung Text: Factors affecting students' intention to use electric buses in Ho Chi Minh city
- FACTORS AFFECTING STUDENTS' INTENTION TO USE ELECTRIC BUSES IN HO CHI MINH CITY Tang Minh Huong*, Luong Truong Son, Tran Van Thuan, Tang Thi Bao Nhu HUTECH University *Corresponding: tm.huong@hutech.edu.vn ABTRACT In the context of the challenge of climate change and increasingly serious air pollution, the search for and application of sustainable transportation solutions is undeniable. In this context, electric buses have emerged as an effective solution, playing an important role in reducing emissions and creating an environmentally friendly public transport system. After analyzing based on survey questionnaires from 200 people, the research results showed 6 factors with the level of influence in descending order including: (1) Service quality, (2) Environmental awareness ( Environmental awareness ), (3) Usefulness, (4) Attractiveness of personal vehicles, (5) Perceived behavioral control, (6) Descriptive norms. Therefore, this research topic will provide a multi-dimensional view of the transition to electric buses, with the hope that the results from this research will contribute to the construction of a public transportation system. effective, sustainable, and beneficial to both the community and the environment. Keywords: intention, electric bus, students, Ho Chi Minh City 1. Introducion Traffic jams are becoming an alarming problem in Ho Chi Minh City. Continuous traffic jams cause the rate of CO2 emissions into the environment to increase, thereby causing a series of climate changes. Climate events such as the hole in the ozone layer, global warming causing ice melt at the poles, etc. According to Nam Viet (2023) in Hanoi City, according to the Department of Transport, in the latest year 2022, the entire city had 7.7 million vehicles including electric vehicles, cars, and motorbikes. Of which, there are 6.5 million motorbikes, 1 million cars, and 182 thousand electric vehicles. In Ho Chi Minh City, the entire city has 8.8 million vehicles and 7.8 million motorbikes. The rapidly increasing number of vehicles is putting pressure on the urban environment from emissions. Because during operation, vehicles using fossil fuels release gases such as CO, VOC and NO2 into the atmosphere. These emissions increase 4-5 times compared to normal when traffic congestion occurs. The prolonged traffic congestion in Ho Chi Minh City is the result of asynchronous development. between economic growth and transportation infrastructure. Environmental pollution, including air pollution, is a burning problem in rapidly developing cities. The main cause comes from the massive increase in personal means of transport, causing both traffic congestion and environmental pollution. Emissions from these types of vehicles are one of the main causes affecting human health. Recognizing this situation, in recent years people have always prioritized electric vehicles to alleviate this situation, in which students have played a large part in switching to electric buses to travel. again. With the desire to better understand students' intention to use electric buses through factors, our team conducted a survey of 150 students with the topic "Factors affecting the intention to use electric buses." Students' electric buses" has captured factors such as: students intend to use it because electric buses reduce noise, feel that electric buses are environmentally friendly, students choose because it is not too convenient. useful, thinking that they want to experience and give another opinion. Therefore, to increase the love and desire to use electric buses, we need to pay more attention to the needs and opinions of students. One of the weaknesses of transportation infrastructure is that there is no green public transportation system capable of meeting most of the travel needs of students in the city. Therefore, the key goal of the city government is to build and develop a large, modern green public transportation system to solve the current traffic congestion situation. Despite the growing body of literature on sustainable transportation and the adoption of electric vehicles (EVs) globally, there remains a notable gap in understanding the specific factors that influence students' intentions to use electric buses within the urban context of Ho Chi Minh City. Previous studies have extensively explored the general population's attitudes towards electric vehicles and public transportation in various cities around the world. However, they have often 234
- overlooked the unique motivations, barriers, and environmental awareness that specifically affect student populations, particularly in developing countries like Vietnam. Additionally, while there is some research on the adoption of electric vehicles in Vietnam, there is a scarcity of studies that focus on electric buses and even less on the intention to use them among students. This gap is significant, considering the distinct socio-economic, cultural, and infrastructural challenges and opportunities in Ho Chi Minh City that could influence students' transportation choices differently compared to other demographics and locations. Therefore, this study aims to fill this research gap by investigating the specific factors that drive students' intentions to use electric buses in Ho Chi Minh City, contributing to a better understanding of sustainable transportation adoption among young adults in emerging economies. Stemming from the necessity of the above issues, the authors chose the topic: "Factors affecting students' intention to use electric buses in Ho Chi Minh City". 2. Literature review 2.1 Background theory According to the concepts of Ajzen, I. (1991, p. 181), Davis and colleagues (1989) all see consumer intention to use 4 as related to customers' wants and needs in choosing products. Choose related products, services, suppliers, purchasing locations... Customers will have different intentions depending on each customer's characteristics, requirements, and purposes. Thus, the intention to use a product/service is the subjective probability of a person's perception of the product/service so that they can make a decision whether they may or may not perform certain behaviors. for future products/services. Intention to use is a specific plan or intention about how to use a product, service or resource. For products, it is often related to the goals and benefits that the user expects to achieve through use. This intention can influence consumers' purchasing or usage decisions. The theory of intention to use often comes from the fields of psychology and management, with many studies aimed at understanding user behavior. The most famous model is the 'Technology Acceptance Model' (TAM) proposed by Davis in the 1980s. It focuses on two main factors: convenience and usefulness of technology. Another model is the “Unified Theory of Acceptance and Use of Technology” (UTAUT), which integrates previous models and considers the impact of factors such as individual motivation, previous experiences and social factors. These studies provide a theoretical basis for understanding why and how users make decisions to use a particular product or service. 2.2 Proposed theoretical model Figure 1. Research model on students' intention to use electric buses in Ho Chi Minh City Based on the analyzed theoretical foundation, there are 6 factors that affect students' intention to use electric buses that have been considered in this study: (1) service quality, (2) environmental awareness, (3) usefulness, (4) personal vehicle attractiveness, (5) perceived behavioral control, (6) descriptive norms. Service quality: Service quality is an important factor affecting bus usage behavior (Domencich TA et al., 1970) and has been proven to have a positive impact in many studies by Ali Ahmed Mohammedi and his colleagues. (2013), White P. et al (2006), Dargay J. and Hanly M. (2002),... You can also refer to the studies of Weinstein A. (2000), Nathanail E. 235
- (2007) provided criteria for measuring bus service quality. Therefore, based on the above studies, hypothesis H1 is proposed as follows: H1(+): Service quality has a positive impact on students' intention to use electric buses. Environmental awareness: Environmental awareness has a positive influence on Hanoi people's intention to choose buses. This hypothesis has been tested for positive effects in many studies. Heath Y. and Gifford R. (2002) proved that this factor affects the behavior of using public transportation of Victoria University students. Environmental awareness is commitment and responsibility, which has can aim towards what has been mentioned about nature, humans must be responsible for their actions and decisions according to Heatlth Y. and Gifford R.( 2002), Economics & Urbanism, Giasasvi P et al. ( 2011). Many researchers have found that environmental awareness has a positive relationship with intention to use electric buses. Therefore, in the context of this research, based on the above documents, hypothesis H2 is posed as follows: H2(+): Environmental awareness has a positive impact on students' intention to use electric buses. Usefulness: Usefulness is based on the C-TPB-TAM combination theory of Taylor and Todd (1995). The degree to which a person believes that using particular application systems will increase his or her efficiency/productivity for a particular job. (Davis, 1986), Hasslinger et al (2007). Perception of usefulness: Davis (1986) stated that, perception of usefulness is people's feeling about the benefits and effectiveness in their work that a new method can bring them. to the intention to use the new method. Research by Heath and Gifford (2002) in the UK emphasized that in order for students to use public transportation services, this transportation system must be convenient, with flexible service times and continuous trip frequency. ., if these conditions are not well guaranteed, even if the cost is low, it will be difficult to change the behavior of students using personal vehicles. Similarly, Chen and Chao (2010) affirmed that the perception of the effectiveness of new, useful, and low-cost transportation methods will promote the application and deployment of KMRT transportation systems in businesses. transportation industry in Taiwan. Based on the above descriptions, hypothesis H3 is established as follows: H3(+): Convenience and usefulness has a positive impact on students' intention to use electric buses. The appeal of personal vehicles: Beirao and Cabral (2007) said that the appeal of personal vehicles is expressed in the following aspects: freedom from constraints; Can go to every corner of the city; convenient; fast; flexible and autonomous. Chen, CF, & Chao, WH (2011) also added to the model of Beirao and Cabral (2007) the factor of personal vehicle usage habits of people in Kaohsiung city, Taiwan with a high rate of Motorbike and car usage rates are 65% and 19%, respectively. According to Dang Thi Ngoc Dung (2012), the attractiveness of personal vehicles is a barrier to using public transportation for its benefits. Many empirical studies have found a negative impact of this variable and formed the hypothesis H4 as follows: H4(-): The attractiveness of personal vehicles has a negative impact on students' intention to use electric buses. Perceived behavioral control: is an individual's perception of the ease or difficulty of performing a specific behavior; this depends on the availability of resources and opportunities to perform the behavior (Ajzen & Fishbein, 1985). If individuals believe it is easier to use public transportation, they will do it. Donald and colleagues (2014) found that the most important variable in predicting intention was perceived behavioral control. From the description above hypothesis H5 is given as follows: H5(+): Perceived behavioral control affects students' intention to use electric buses in the same direction. Descriptive norms: “Descriptive norms” reflect externally imposed rules that arise from “what is important for others to do themselves” in specific social contexts (Cialdini et al., 1990; Rivis & Sheeran, 2003).The views and behaviors of significant others such as friends and family members provide cues that people can refer to in deciding what to do. Descriptive norms are often accompanied by expectations that people will behave according to trust. In a study conducted by Bamberg et al. (2007) , they emphasize the importance of social context and personal norms in using public transport. Research results show that descriptive norms have a positive impact on public transport use (aspect of students' intention to use electric buses). From the above studies, hypothesis H6 is proposed as follows: H6(+): Descriptive norms have a positive impact on students' intention to use electric buses. 236
- To improve students' intention to use electric buses, the team investigated the causes and effects. However, in evaluating each cause, the team identified the core cause as "The appeal of personal vehicles" which greatly affects students' intention to use electric buses. Thereby, the group believes that the government and businesses need to focus on this core cause to be able to propose appropriate solutions, contributing to increasing the intention to use green public transportation (here, buses). electricity) in today's times. 2.3 Research methods 2.3.1 Building a measurement scale The study mainly uses the Likert scale from 1 (strongly disagree) to 5 (strongly agree). This is a commonly used scale in research describing the effects on the intention to use green public transport: Table 1. Preliminary scale Element Reference source Edvardsson, Thomsson and Ovretveit (1994) and Feigenbaum Service quality (1991) Environmental awareness Heatlth and Gifford (2002) and Giasasvi P et al (2011) Convenience and usefulness Taylor and Todd(1995) and Davis, 1986 The appeal of personal vehicles Beirao and Cabral (2007) and Chen, CF, & Chao, WH ( 2010) Perceived behavioral control Ajzen, (1991) and Taylor and Todd (1995) Descriptive norms Beirao and Cabral (2007) Intention to use electric buses of students in Ho Chi Minh City Bamberg et al. 2007; Donald et al., 2014. 2.3.2 Data collection and analysis methods The overall research subjects are students in Ho Chi Minh City with the age range from 18 to 25 years old. The official survey was conducted in Ho Chi Minh City with the survey subjects being people who have ever used cars. electric bus. Subjects answered a number of questions about the influence of factors on their intention to use electric buses. Due to objective factors, the research team conducted 100% quantitative research using an online survey. Of the number of ballots received after the survey period, after filtering invalid ballots, the group used 200 ballots to conduct official analysis. The study used Cronbach's Alpha as the most popular test score reliability coefficient with single management and eliminated variables with small correlation coefficients between total variables, testing the preliminary scale using the EFA exploratory factor. Building a regression model to analyze the influence of factors on students' intention to use electric buses. 2.3.3 Analyze results Among the 200 people, in terms of age, because the research subjects were students who intended to use electric buses, the age group included in the survey was 18 years old or older, ensuring the objectivity of the intention to use buses. However, the research analysis will focus on people aged 18-25 years old. Regarding personal occupation, statistical results show that the majority of consumers participating in the survey are students with the number 200 accounting for 100% of the total survey participants. These are people who have used electric buses. Table 2. Results of testing the reliability of Cronbach's alpha scale of influencing factors Indicator Cronbach's Indicator is The scale Conclude number Alpha eliminated All indicators have total variable correlation > Service quality 4 0.635 2 0.3, Cronbach's Alpha coefficient > 0.5 Realize about All indicators have total variable correlation > 4 0.790 0 environment 0.3, Cronbach's Alpha coefficient > 0.5 Convenience and All indicators have total variable correlation > 4 0.818 0 usefulness 0.3, Cronbach's Alpha coefficient > 0.5 237
- The attraction of All indicators have total variable correlation > 3 0.817 0 private vehicles 0.3, Cronbach's Alpha coefficient > 0.5 Check awareness All indicators have total variable correlation > 4 0.837 first control behavior 0.3, Cronbach's Alpha coefficient > 0.5 All indicators have total variable correlation > Descriptive standards 3 0.701 0 0.3, Cronbach's Alpha coefficient > 0.5 Intention to use electric All indicators have total variable correlation > buses of students in Ho 3 0.733 0 0.3, Cronbach's Alpha coefficient > 0.5 Chi Minh City - Cronbach's Alpha reliability test With the above test results, eliminating additional variables cannot increase the reliability of the scale. Thus, the variables are eligible to continue performing factor analysis. - EFA exploratory factor analysis After analyzing the reliability of the scale, the research team used the EFA exploratory factor analysis method on both the independent and dependent variables to evaluate, using Varimax rotation. In the EFA analysis for independent variables, the KMO Bartlett's and Bartlett's tests are both statistically significant, but must be performed multiple times (due to having to eliminate indicators with small correlations and correlations with many components). main part). The final results were as follows: KMO =0.841 and Sig Bartlett's = 0.000 with a total extracted variance of 63.04%. Since then, the research team has identified 6 main groups of factors (with changes in some indicators) related to students' intention to use electric buses that will be used in the analytical model instead of 6 latent variable as originally assumed by the theoretical model. • Factor group 1: Service quality includes 4 variables (H1-1, H1-2, H1-3, H1-4) • Factor group 2: Environmental awareness includes 4 variables (H2-1, H2-2, H2-3, H2-4) • Factor group 3: Convenience and usefulness includes 4 variables (H3-1, H3-2, H3-3, H3-4) • Factor group 4: Attractiveness of personal vehicles includes 3 variables (H4-1, H4-2, H4-3) • Factor group 5: Perceived behavioral control includes 4 variables (H5-1, H5-2, H5-3, H5-5) • Factor group 6: Descriptive standards include 3 variables (H6-1, H6-2, H6-3, H6-4) For the dependent variable: KMO coefficient is 0.780, Bartlett's Test with Sig = 0.000. No observed variables were removed; The total variance extracted of the dependent variables is 64.73%. The results show that the scale chosen for the dependent variable in the model meets the requirements, the variables are convergent, and are suitable for analytical use. The factors (principal components) are saved with results from X1 to X6 and dependent variable N. Table 3. Results of linear regression analysis of the model - Results of impact testing The regression results show that all factors in the research team's hypothesis have an impact on students' intention to use electric buses in the study area. The results of testing the impact of independent variables on the dependent variable in the research model are as follows: 238
- X1: Service quality: According to the research team's initial hypothesis, service quality has an impact on students' intention to use electric buses. The analysis results show that the path coefficient β1=0.140, t-value = 2.083, p= 0.039. That indicates a significant impact of service quality on the intention to use electric buses. This means hypothesis X1 is accepted. X2: Environmental awareness: The coefficient of the link β2 = 0.079, T-Value = 1.767, P = 0.079. These results suggest a positive but not statistically significant relationship at the conventional alpha level of 0.05 with the dependent variable, indicating a modest impact. Given the P-value exceeds the standard threshold for statistical significance, the hypothesis associated with X2 cannot be conclusively accepted without further consideration of a higher significance level or additional evidence. X3: Convenience and usefulness: The coefficient of the link β3 = -0.161, T -Value = -2.243, P = 0.026 synonymous with this factor has a positive relationship and a great impact on dependency variables. Hypothesis X3 is accepted. X4: The attraction of personal vehicles: The link coefficient β4 = 0.231, T-Value = 3.393, P
- Public transportation plays an indispensable role in urban development, especially large-scale cities with tens of millions of people today in Vietnam. Therefore, for urban areas to develop sustainably, public transportation must be the area that receives the most investment attention. So applying technology will help bring people access and interest in public transportation. It will bring many benefits to the people and the country, be environmentally friendly, save raw materials, limit CO2 emissions that cause environmental pollution, etc. In order for buses in particular and public transport in general to develop, the city will continue to research to rationalize route flows, increase connectivity as well as enhance the application of science and technology to attract passengers. The construction of public transportation technology applications has contributed to increasing convenience, helping passengers easily access and use services and creating information channels for passengers to reflect and evaluate service quality.Transportation Smart traffic is a close combination between people, vehicles and infrastructure. 3.4. Comprehensive upgrade of the public transportation system from infrastructure to vehicles and staff service attitude To reduce emissions, Ho Chi Minh City in general and the country in particular have proposed solutions to replace personal vehicles with the use of public passenger transport such as buses and trams. ... With its own advantages, electric buses are now gradually becoming a daily means of transportation for people because of their ease of access, cheap ticket prices, punctuality, and high passenger density... 3.5. Financial support and incentive policies for bus use Financial support and incentive policies are measures and urgent actions that governments, organizations, individuals, or related parties take to create favorable conditions and encourage people, businesses, and management agencies using electric buses. The policy's goal is to promote the transition from fossil fuel-based vehicles to electric vehicles, reduce emissions, and support a sustainable transportation environment. 4. Conclusion Environmental issues are one of the issues that have been in an alarming state over the years. The quality of the living environment in big cities, especially Ho Chi Minh City, is getting worse and worse. With the deteriorating environmental situation, the use of electric buses is to limit the amount of emissions released into the environment, reduce the use of personal vehicles, and promote the use of public transportation, which is the car. electric buses to contribute to building a green, clean, beautiful and more environmentally friendly public transport system to improve the quality of the living environment. The research team has built and adjusted a research model to suit the context and research object, including 6 factors and 21 observed variables affecting the intention to use electric buses, including 6 factors. (independent variables) are service quality, environmental awareness, convenience and usefulness, attractiveness of personal vehicles, perceived behavioral control and descriptive norms that strongly influence the intention to use vehicles. Electric buses for students in Ho Chi Minh City. The research team, after conducting data collection and in-depth analysis combined with other methods, recorded 6 factors in the model that influence students' intention to use electric buses in the City. Ho Chi Minh. The research results have reference value in analyzing factors affecting students' intention to use electric buses, from which suggestions can be made to help students use electric buses more. Furthermore, raise awareness of environmental protection from students in particular and everyone in general. Build routes exclusively for electric buses to increase the speed of each trip: to increase the speed of the bus and reduce waiting time for each trip as well as partly avoid the problem of congestion. car. Build separate routes for electric buses, integrate 4.0 automation technologies on dedicated routes for buses and apply them to monitoring, management and operation of the public bus system. Organize more seminars to propagate changes in the habit of using personal vehicles: organize seminars at colleges and universities in Ho Chi Minh City to propagate the benefits of vehicles Electric buses are good for the environment in order to change the habit of using personal vehicles, which can have a negative impact on the air today. Helps students 240
- become aware of the current environmental situation, so they have a more general view of environmental issues and raises awareness of environmental protection. Building smart technology applications: applying 4.0 technology to management and development contributes to increasing convenience, making it easier for customers to access and use services and create information channels for passengers to reflect , assessment of service quality. So applying technology will help bring people access and interest in public transportation. It will bring many benefits to the people and the country, be environmentally friendly, save raw materials, limit CO2 emissions that cause environmental pollution,... Comprehensively upgrade the public transportation system from infrastructure to vehicles and staff service attitude: upgrading the infrastructure of the public transportation system is not just for buses but It is also a transportation system that makes travel and transportation more convenient, limits traffic jams and reduces emissions into the environment. Besides, the human factor is also a prerequisite, so the driver team on the bus routes needs to be trained to bring the best quality of service to consumers. Some limitations such as the popularity of electric buses are still limited because there are not as many electric bus routes as traditional buses, so access to users is still limited, the appeal of electric buses is still limited. has not yet hit consumers because people's awareness of environmental protection issues is still not recognized. In addition, electric buses are facing the problem of not having enough revenue to cover expenses. After pilot operation, the number of passengers decreased. increased but revenue is still not enough to cover costs due to low subsidy rates. REFERENCES 1. Nam Viet, 2023. Cars and motorbikes - the main culprits causing air pollution. https://www.bao Giaothong.vn/o- to-xe-may-thu-pham-chinh-gay-o-nhiem-khong-khi-192231112102841874.htm , November 20, 2023 2. Dang Thi Ngoc Dung, (2012). Factors affecting the intention to use the metro subway system in Ho Chi Minh City - Fulbright Master's Thesis - Ho Chi Minh City University of Economics 3. Ajzen, I. (1991), “The Theory of Planned Behavior”, Organization Behavior and human Decision Processes, No. 50,pp. 179-211 4. Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340 5. Mohammed, A. Shakir, Factors that affect transport mode preference for graduate students 6. in the national university of Malaysia by logit method, Journal of Engineering Science and Technology, 8 (2013) 351-363. 7. J. Dargay, M. Hanly, The demand for local bus services in England, Journal of Transport Economics and Policy, 36 (2002) 73-91 8. Heath, Y. & Gifford, R. (2002), “Extending the Theory of Planned Behavior: Predicting the Use of Public Transport”, Journal of Applied Social Psychology, No. 32, pp. 2154-2189 9. C. Chen, WH Chao, Habitual or reasoned? Using the theory of planned behavior, technology acceptance model, and habit to examine switching intentions toward public transit, Transportation research part F, traffic psychology and behavior, 14 (2011) 128-137. 10. Weinstein, Customer satisfaction among transit riders, How customers rank the relative importance of various service attributes, Transportation Research Record, 1735 (2000) 11. E. Nathanail, Measuring the quality of service for passengers on the Hellenic railways, Transportation Research Part A, Policy and Practice, 42 (2008) 12. S. Taylor, P. Todd, An integrated model of waste management behavior, A test of household recycling and composting intentions, Environment and behavior, 27 (1995) 13. Beirão, G. and Cabral, J.S. (2007), "Understanding public attitudes towards transport and private car: A qualitative study", Transport Policy, vol. 14, no. 6, p. 478-489. 14. Cialdini, RB, Reno, RR, and Kallgren, CA (1990). A Focus Theory of Normative Conduct: Recycling the Concept of Norms to Reduce Littering in Public Places. Journal of Personality and Social Psychology, 58(6), 1015-1026. 15. Robert Huttenback, Lance E. Davis, 1986. Mammon and the Pursuit of Empire: The Political Economy of British Imperialism, 1860-1912 241
- 16. Hasslinger, A., Hodzic, S., & Opazo. (2007). Consumer behavior in online shopping. Kristianstad University. 17. Donald, I., Cooper, S.R., 2004. A facet approach to extending the normative component of the theory of reasoned action. Br. J. Soc. Psychol., 40(4), 599-621. 18. Rivis, A., & Sheeran, P. (2003). Social influences and the theory of planned behavior: Evidence for a direct relationship between prototypes and young people's exercise behavior. Psychology and Health, 18, 567–583. 19. Bamberg, S., Hunecke, M., Blobaum, ¨ A., 2007. Social context, personal norms and the use of public transportation: Two field studies. Journal of Environmental Psychology 27 (3), 190–203. 242
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