Literature review (a summary of previous research)
The topic of factors influencing the intention of using the bus has garnered much attention in the past The factor of moral concerns was found to be influencing the intention to use the bus in Ho Chi Minh City
(Satoshi & Hong, 2009) Many other factors also influence the behavioral intention including the perception of traffic participants on the usefulness of the bus, how much they find the bus easy to use, social pressure, and perceived behavioral control and attractiveness of personal vehicles (Cheng
& Chao, 2010; Luu, 2022) These large-scale researches’ limitation is that they do not fully explain to what extent those factors affect a segment of the population In the case of students, Volosin (2014) found that students’ travel designs change considerably from those of the rest of the populace
One reason is that university students belong to the relatively low-income category of the population and their travel behavior is typically different
(Khattak et al, 2011) Research has found that relaxed traveling, safety during travel, and time-saving are the most important attributes of service quality for most students (Javid & Al-Kasbi, 2021).
reason for research ieee eects ceeetenteeeteeeteenneees 2 1.2 Atm of research ieee eeeeeeeeeeeneeeeeneeneeeeeneesieneenesaees 3 1.3 Research questIO's L2 022211201 1111111211121111 1111k 3 1.4 Research focus, sample, and scope .-cc 22-2 3
Observing that there is limited research on what impacts students on their intention to use the bus service in Ho Chi Minh City, the author saw this as an opportunity to expand and make contributions to the topic By understanding the factors that influence students’ intention to use the bus system, some suggestions and recommendations can be made to make the bus service more attractive to students, thus reducing traffic congestion and pollution For the reasons stated above, the author decided to research on the topic “Factors influencing the intention of UEH students to use the bus system in Ho Chi Minh City” Researching UEH students will make the data-collection process less time-consuming
1.2 Aim of research ® Determine the factors that influence the intention of using the bus system amongst students at the University of Economics of Ho Chi Minh City e Analyze the factors that influence the UEH students’ intention to use the bus system ® Provide suggestions and recommendations for the government to increase the usage and attractiveness of the bus system amongst UEH students
1.3 Research questions e Which factors affect the intention of UEH students to use the bus system? ® To what extent do those factors affect the intention of UEH students to use the bus for commuting? ® What are some suggestions that can be made to improve the usage and effectiveness of the bus system amongst UEH students?
1.4, Research focus, sample, and scope
Research f0CUS 0 0 cece eeceeeceeeeteesteeeeeeteeeneeeneeees 3
The focus of this research is factors influencing the intention to use the bus system.
Research sampÌe L2 11 12211122 1111211 rà 3
The sample for this research is 268 active UEH students who reside in Ho Chi Minh City at the time of collecting samples.
Research scope . T1 111211 11 1101118112 vk 3
The process of investigating, surveying, and data collection was conducted by our group in mid-November and ended in early December
2023, spanning almost a month This research only focuses on a particular
4 location: Ho Chi Minh City and a subset of the population, which are UEH students
This research is done using the method of qualitative research and quantitative research ® Qualitative research: Drawing on the theoretical basis and research in the past, the author constructed a unified measurement scale and research model They then finalized the survey and started data collecting
Quantitative research: Data was collected under an online survey form using Google Forms, utilizing the online sampling method The survey was sent to willing participants who were well-informed and understood the purpose of said survey and its contribution to the research The author distributed the survey through social hubs of the University of Economics on Facebook and messaging their peers online as well as through face-to-face interactions at school
The layout of this research is divided into five chapters:
THEORETICAL BASIS AND PROPOSED
Concept about intention to use a servIce
Intention to use a service or product is the subjective probability a person feels about a product/service from which they can decide whether they may or may not perform certain behaviors regarding the product/service in the future
Concepts about public bus transportation
Public bus transportation is a transportation system for passengers by group travel system for use by the general public operated on established routes and charged a posted fee for each trip.
Concepts about public bus transportation
Electric bus transportation is a new type of transportation in today's world and attracts a fairly large number of users thanks to its high quality and environmentally friendly effect on the environment
The theory of planned behavior - TPB
The theory of planned behavior is a theory that was developed as an improvement to the theory of reasoned action - TRA (Ajzen & Fishbein,
1975), whose limitation is assuming the intention of behavior is the sole influence to said behavior The theory suggests that the decision to engage in a behavior is not only affected by attitude, and subjective norms (SN) but also perceived behavioral control (Figure 2.1)
Figure 2.1 Model depicting the theory of planned of behavior - TPB
Technology acceptance model - TAM
The Technology acceptance model was built by Fred Davis (1989) and Richard Bagozzi (1992) based on the two theories TRA and TPB To better understand and explain the acceptance and usage of technology by
9 people The model introduced two new elements directly affecting people’s attitudes which are perceived usefulness (PU) and perceived ease of use
Figure 2.2 The technology acceptance model - TAM
2.3.3 Integration of TPB AND TAM
The integration of the TPB theory and the TAM model was proposed by Taylor & Todd (1995) in order to have a better and more in-depth understanding when investigating the factors which influence the actual behavior as well as undermining the limitations involved when using the
TPB theory and TAM model separately The new model retains all of the existing elements (figure 2.3)
Subjective Perceived norms behavioral control
Figure 2.3 Model Integrating the TPB theory and the TAM Model
In this research, the author decided to make adjustments to the integrated model of the TPB theory and the TAM model in order to
10 construct an appropriate model for investigating the factors influencing the intention of UEH students to use the bus system by excluding the following independent variables: perceived ease of use, perceived behavioral control, and adding the following independent variables: bus station, alternative options and electric bus
Perceived usefulness (PŨ) - 2 c2 222222222 s2 10
Perceived usefulness is the extent to which a person believes engaging in a specific behavior will help achieve their goals or have positive outcomes An individual can perceive a behavior to be useful or unuseful which will affect their behavioral intention Research made by
Beirao & Cabral (2007) revealed that the advantages of public transit consisted of low cost, stress-free, safety reasons, positive environmental impact, etc According to Chen & Chao (2011), perceived usefulness was a strong factor that influenced car drivers in Tatwan to shift toward public transportation From these findings, the author proposes the hypothesis:
Hypothesis H/: Perceived usefulness has a positive impact on intention to use the bus system.
Bus stop (Bồ) Q2 00122 112222122 xe ưe 10
Bus stops are an integral part of the public bus service They are essentially the first contact points between passengers and the bus Bus stops provide a place to conveniently and comfortably wait for the bus arrival and safely travel to their destinations Shaaban & Kim (2016) found that upgrades to bus shelters positively influence satisfaction and bus usage amongst students From previous sources and their reasonings, the author proposes the hypothesis:
Hypothesis H2: Bus stop has a positive impact on intention to use the bus system.
Subjective norms (SN) L L2 HH Hà II
According to Azjen (1985), subjective norms are the perceived social pressure or expectation on a person to engage in a particular behavior The theory of planned behavior clearly distinguishes attitude from subjective norms, stating that the latter reflects the importance of external opinions on the behavioral intention Chen & Chao (2010) proved that subjective norms were the leading influence that positively impacts bus usage From these points, the author proposes the hypothesis:
Hypothesis H3: SubJective norms have a positive impact on intention to use the bus system.
Alternative options (AÔ) HH Ha II
Alternatives options refer to other means of transport other than using the public bus to commute Truthfully speaking, many alternative options for travel nowadays are more attractive than the bus system Beirao
& Cabral (2007) have pointed out various strengths of personal vehicles: freedom/independence, convenience, rapidity, flexibility, etc Based on various sources, the rise of ride-hailing services also undermines bus usage From the reasons stated and findings, the author proposes the hypothesis Hypothesis H4: Alternative options have a negative impact on the intention to use the bus system.
Electric bus (EB) - 2 22211220111 1211121 111111121222 II
An electric bus is a bus that runs on electricity instead of fossil fuels According to various sources, electric buses have some advantages over conventional buses Hamarcu & Eren (2020) stated that electric buses emit zero tailpipe emissions, ensuring cleaner air for cities and better air quality Some electric buses also offer cheaper prices for passengers These factors can have a positive influence on bus usage For the reasons mentioned, the author proposes the hypothesis:
Hypothesis H5: electric bus has a positive impact on intention to use bus system
Environmental awareness (EÀA) -c 22-552 12
Environmental awareness indicates a person’s consciousness of environmental issues According to Steg & Vlek (1997), a car owner who has a higher awareness of the environment will use their car for commuting less often This can raise incentives to use public transportation like buses From this reasoning, the author proposes the hypothesis:
Hypothesis H6: environmental awareness has a positive impact on the intention to use the bus system
RESEARCH METHODOLOGY
Measurement scaÌ€s ác nh HH 21 T11 H1 11k re 12 1 Perceived useftllness .- ác SH re 13 2 SubJe€CtIV€ TIOFTT§: - ¿22 2 22 222222211152 521111 15232 1x+2 13 3 cdưiọDùDùDùDỤẶỤẶỤẶẠ
All variables are measured with a 5-point Likert scale The authors have rewritten some questions in order to fit the context of the topic
Variable Question Original question Source code
PUI Using the bus 1s very For me, taking public affordable transport to commute next time would overall be cheap
PU2 Using the bus is very safe For me, taking public Chen & Chao transport to commute next
13 time would overall be safe
Using the bus 1s very For me, taking public comfortable transport to commute next time would overall be a pleasant
The bus is very punctual
Travelling from home to the station is very easy
(Go! bus, BusMap ) are very useful
My friend and family My friends and family think recommend me to use the that I should use future urban bus rail transit
Society encourages the Using the bus is a developing use of bus trend in modern society
The city government has Government policy will initiatives to encourage influence my choice of taking bus use public transport
Using the bus is civilized and polite
Variable code Question Original question
BSI The station 1s very clean Cleanliness Shaaban &
BS2 The station has seats Based on previous researches
BS3 The station has a good protective roof Shade Shaaban &
Kim (2016) Table 3.3 Bus stops scale
Variable Question Original question Source code
EAI Using the bus reduces _ Using the bus reduces Hoang & Tran pollution environmental pollution (2017)
EA2 Using the bus reduces traffic congestion
EA3 Using the bus reduces _ Using the bus reduces the use private vehicles of personal vehicles
EA4 Using the bus saves Using the bus reduces costs for Nguyen & society resources society Thach (2023)
I am aware of plans to deploy electric buses in the city
Electric buses will attract more user
Electric buses will be more modern
Electric buses will be more safe
Using electric buses will help improve the environment
Based on previous researches Table 3.5 Electric buses scale
Using a private vehicle is more convenient
Using private vehicles is more convenient than using the bus
Using ride-hailing services is more convenient
Other choices will be more flexible
Based on previous researches Based on previous researches
Table 3.6 Alternative options scale 3.1.7, Intention to use the bus system
Variable Question Original question Source code
ITI I have the intention to I intend to use the bus to travel Aoife (2001) use the bus Borith,
H2 I have the intention to My intention to switch from Chen & Chao use the bus in place motorcycle (or car) to public (2010) for other vehicles transport when commuting next time is strong
IT3 I have the intention to Author’s suggestion call upon others to use the bus
Table 3.7 Intention to use the bus system scale
Research methos - - c c 21 2121115121115 111 11111 16g L7
3.2.1 Methods of analysis and synthesis
To analyze students' intention to use the bus system at UEH, the researchers separated it into smaller factors to understand the research objective, including the following factors: perceived ease of use, perceived usefulness, incentives for electric buses, subjective norms, availability of alternatives Within each factor, researchers also divided it into questions to clearly understand the characteristics and nature of the problem
The synthetic method is the opposite of the analytical method After making judgments and integrating the characteristics of the factors, the group proceeds to synthesize them to test the influence of the independent variable on the dependent variable.
3.2.2, The method of data collection
This is the method most people apply and implement in scientific research articles and the research group used this data collection method by referencing and synthesizing data from relevant research articles content related to students’ intention to use the bus
In addition to collecting from previous research articles, the authors created a questionnaire and collected directly from the opinions and assessment levels of UEH students
The non-experimental method is a method of collecting data based on observation and drawing rules and assessments The authors have implemented a practical form of the experimental method which is the method of asking experts' opinions: Consult with instructors on questions, content, etc related to the research purposes
Quantitative research .- + c1 2:1 111122111 111111 1121222 18 1 Research subJect - c2 cà 1122122 121 1111211111122 1x2 18
All UEH students are currently still studying at the University living in Ho Chi Minh City
This study will conduct EFA factor analysis and regression analysis
A few criteria for deciding the minimum sample size for EFA and regression analysis from previous research are:
For EFA factor analysis: According to Hair, Anderson, Tatham, and Black (1998), the minimum sample size is 5 times the total observed variables This is the appropriate sample size for research that uses factor analysis (Comrey, 1973; Roger, 2006) The formula for calculating the sample size is as follows: Sample size N = 5*m, m is the observed variable that used Likert's scale in the research The total number of observed variables that used the Likert scale in this research is 26 So, the minimum sample size for this research using the formula is 130
For regression analysis: According to Tabachnick and Fidell (1996), the minimum sample size needed is calculated using the following formula: Sample size N = 50 + 8*m, m is the number of observed variables in the research that used the Likert’s scale This research has a total of 26 observed variables that used the Likert scale So, the minimum sample size for this research using the formula is 258
From here, our group decided to use 268 survey results for the research
In this study, two methods of non-probability sampling will be applied:
Convenience sampling: The authors create a questionnaire about “Factors influencing the intention of UEH students to use the bus system.”” and post it on Facebook groups, classes, and fan pages with a large number of UEH students.
19 ¢ Snowball method: The authors shared the questionnaire with the friends at UEH and asked them to survey and share it with their friends at UEH
To ensure the sample size of N = 268 students, the authors used Internet survey tools, shared on social networking sites, and survey groups with a large number of UEH students, group class, and friends
Cronbach’s Alpha: The coefficient used to check the reliability of the scale and remove the observed variables that do not ensure reliability based on the following criteria: e¢ Using Cronbach’s alpha to test the variability of each measurement scale ® Cronbach’s Alpha coefficient of the scale greater than 0.6 1s accepted ® Incase the Cronbach’s Alpha value is smaller than 0.6, then we need to remove the variables To help the Cronbach’s Alpha or Cronbach’s Alpha If Item Deleted coefficient of the variable to be the largest and continue to run until the Cronbach’s Alpha coefficient of the scale reaches 0.6 or higher
After testing the reliability and removing unqualified variables, our group continues to conduct the EFA to check the variability of measurement scales EFA will reduce the number of observed variables and the group observed variables into factors based on the following criteria: ¢ KMO coefficient (Kaiser-Meyer-Olkin) is used to consider the suitability of the factor The KMO coefficient must have a value of 0.5 or higher ® Bartlett’s test of sphericity is used to examine the correlation between the observed variables in a factor and has Barlett’s Test sig coefficient | are kept in the model
20 ¢ Total Variance Explained > 50% shows that the EFA model is suitable Considering the variation is 100%, this value shows how much % of the extracted factors are condensed and how many % of the observed variables are lost ® Factor Loading, also known as the factor weight, represents the correlation relationship between the observed variable and the factor The higher the factor loading coefficient, the greater the correlation between that observed variable and the factor and vice versa The authors take the load factor 0.4 as the standard level (with N = 268) so that the observed variable has good statistical significance
When completing the EFA test, the authors create representative factors of each group of observed variables and use data of representative factors to continue doing Pearson Correlation analysis to consider the correlation between independent variables and dependent variables, and identify some cases where dynamic collinearity may occur based on the following criteria: ® The Sig value is less than 0.05 and the absolute value of the Pearson correlation coefficient is greater than 0, the authors will conclude that there is a correlation between the independent variable and the dependent variable and vice versa ® In addition, question the phenomenon of multicollinearity between independent variables if the Sig value is less than 0.05 and high Pearson correlation coefficient
After concluding the correlation between the independent variables and the group dependent variable, the authors continue to do a multivariable regression analysis to clarify this correlation Testing the hypothesis of the model proposed by the authors, and making a conclusion about the multicollinearity question includes the following steps: ® Testing the appropriation of the model through the adjusted R- squared coefficient (taking 0.5 as a landmark to distinguish between the good model and the bad model) At the same time, the sig value in the ANOVA table is less than 0.05 (with statistical significance) ¢ Residual normal distribution test based on Histogram, Normal P-P Plot ® The conclusion of the multicollinearity question is based on the VIF coefficient (less than 10).
21 ® Provide the regression equations (standardized and unstandardized) based on the obtained results to evaluate the influence of the factors on the dependent variable
CHAPTER 4; RESEARCH RESULTS 4.1 Descriptive statistics of the survey sample
Figure 4.1, Pie chart depicting genders participating in the survey
Gender: There are 164 females (61.2%) and 104 males (38.8%) There is a disproportionate gender because of the location of the research (UEH University)
Figure 4.2 Pie chart depicting batch of students
Batch of students: 100% of participants are UEH students and there are 231 Ist year (86.2%), 24 2nd year (9%), 10 3rd year (3.7%), and 3 4th year (1.1%)
PU2 Using the bus 268 1 5 3.6 1.036 is very safe
PU4 The bus is very 268 1 5 3.48 1.065 punctual
PUS5 Travelling 268 l 5 3.35 1.12 from home to the station is very easy
PU6 Commonly 268 1 5 413 0.989 used bus app (Gol
Bus, BusMap, ) is very useful
BSI Bus stops are 268 1 5 3.13 1.018 very clean
BS2 Bus stops have seats
BS3 Bus stops have good protective roof
SN1 My friend and family recommend me to use the bus
SN2 Society encourage the usage of bus
SN3 The city government has initiatives to encourage bus use
SN4 Using the bus is civilized and polite
AOI Using a private vehicle is more convenient
AO2 Using ride- hailing services is more convenient
AO3 Walking will be better
AO4 Other choices will be more flexible
EBI I am aware of plans to deploy electric buses in the city
EB? Electric buses will attract more user
EB4 Electric buses will be more safe
EBS5 Using electric buses will help improve the environment
EAI Using the bus reduces pollution
EA2 Using the bus reduces traffic jam
EA3 Using the bus reduces private vehicles
EA4 Using the bus saves society resources
IT1 I have the intention to use the bus
IT2 I have the intention to use the bus in place for other vehicles
IT3 I have the intention to call upon others to use the bus
Table 4.1 Descriptive table of survey response:
The mean of most observed variables is greater than 3 on a scale of
5 Most participants have the opinion of Neutral, Agreed, or Totally Agreed A few observed variables that participants highly agree with and have a mean greater than 4 include: e PUI: Using the bus is very affordable ® PU6: Commonly used bus app (Go!Bus, BusMap ) is very useful ® SN2: Society encourage the usage of bus
25 e AOI: Using a private vehicle is more convenient ® EB3: Electric buses will be more modern ® EBS: Using electric buses will help improve the environment e EAI: Using the bus reduces pollution ® EA3: Using the bus reduces private vehicles
There is one variable that has a mean lower than 3 and it is IT2 :] have the intention to use the bus in place for other vehicles
The standard deviation of the variables ranges from 0.86 to 1.199, this means that there are variations in the opinion of different participants 4.2 Analytical data from key questions
From the collected data, our groups began to test the reliability of each scale using Cronbach’s Alpha test based on 2 criteria: ® The Corrected Item-Total Correlation > 0.3 ( Nunnally, 1978) ® Cronbach’s Alpha value (Hoang & Chu, 2008):
+ From 0.8 to near |: The scale is very good
+ From 0.7 to near 0.8: The scale is good
+ From 0.6 and up: The scale is usable
Cronbach’s Alpha Number of items
Table 4.2 Reliability statistics of “Perceived Usefulness”
Variables Scale Scale Corrected Cronbach’s Conclusion meanif variance Item-Total Alpha if
PUI Using 17.86 15.141 0.560 0.785 Suitable the bus is variable very affordable
PU2 Using 18.62 13.741 0.658 0.762 Suitable the bus is variable very safe
PU3 Using 18.92 13.443 0.653 0.762 Suitable the bus is variable very comfortable
PU4 The bus is very punctual
PUS Travelling from home to the station is very easy
Commonly used bus app (Go!
Table 4.3 Table of results to evaluate the reliability of the scale “Perceived
The result of Cronbach’s Alpha of the scale is 0.811 > 0.6; The corrected item-total correlation coefficients of the observable variables in the scale are all greater than 0.3 observable variables that can make Cronbach's Alpha coefficient greater
Therefore, all observable variables are accepted and will be than 0.811
Usefulness” used in the next factor analysis
BS1 Bus stops are very clean
Cronbach’s Alpha Number of items
Table 4.4 Reliability statistics of “Bus stops”
Scale variance if Item deleted 3.809
There is no case of eliminating any
Cronbach’s Alpha if item Deleted 0.821
Suitable variable Suitable stops have seats
BS3 Bus stops have good protective roof
Table 4.5 Table of results to evaluate the reliability of the scale
The result of Cronbach’s Alpha of the scale is 0.786 > 0.6; The corrected item-total correlation coefficients of the observable variables in the scale are all greater than 0.3 However, Item BS1 has Cronbach’s Alpha if Item Deleted result equal to 0.821, larger than the original Cronbach’s Alpha result of 0.786, but considering the diversity of the scale, the author decided to still keep this Item for the next factor analysis
SNI My friend and family recommend me to use the bus
SN2 Society encourage the usage of bus
SN3 The city government has initiatives to
Cronbach’s Alpha Number of items
Table 4.6 Reliability statistics of “Subjective norms”
Scale variance if Item deleted 6.575
Cronbach’s Alpha if item Deleted 0.803
Suitable variable encourage bus use
Using the bus is civilized and polite
Table 4.7 Table of results to evaluate the reliability of the scale
The result of Cronbach’s Alpha of the scale is 0.803 > 0.6; The corrected item-total correlation coefficients of the observable variables in the scale are all greater than 0.3 There is no case of eliminating any observable variables that can make Cronbach's Alpha coefficient greater than 0.803 Therefore, all observable variables are accepted and will be used in the next factor analysis
Cronbach’s Alpha Number of items
Table 4.8 Reliability statistics of “Alternative options”
AOI Using a private vehicle is more convenient
AO2 Using ride-hailing services is more convenient
AO3 Walking will be better
Scale variance if Item deleted 5.079
Cronbach’s Alpha if item Deleted 0.607
29 choices will variable be more flexible
Table 4.9 Table of results to evaluate the reliability of the scale