Subject Applied Statistics For Business & Economics Topic Factors Influencing The Intention Of Ueh Students To Use The Bus System.pdf

` BỘ GIÁO DỤC VÀ ĐÀO TẠO : TRUONG DAI HOC KINH TE TP HO CHi

ABSTRACT

As the economy of Ho Chi Minh City continues growing, there has been and will continue to be an influx of both the total population and the number of private vehicles in the city This increase will substantially worsen the already severe problem of congestion and pollution in the city caused by traffic For years, the city has been trying to come up with a solution to solve the traffic jam problem As of today, the most effective method of reducing private vehicles, pollution, and congestion worldwide is to promote public transportation In Vietnam, the backbone of the public transportation system is the bus system, but the harsh reality is that the bus system is still not favorable in the public consciousness Nowadays, in Ho Chi Minh City the group of people that use the bus system the most are university students because of financial reasons and convenience to commute to campuses To understand all the variables that can have an impact on a student's intention to use the bus, the authors have researched the topic of "Factors influencing the intention of UEH students to use the bus system for commuting to campus."

The topic is based on the theoretical bases compiled by the authors with key influencing factors such as Perceived Usefulness (PU), Bus Stops (BS), Subjective Norms (SN), Alternative Options (AO), Electric Buses (EB), and Environmental Awareness (EA) With the data collected from 268 UEH students, the results show that 5 factors have statistical significance Out of the 5, Perceived Usefulness (PU), Bus Stops (BS), Electric Buses (EB), and Environmental Awareness (EA) have a positive impact on the Intention to use the bus system (IT) On the other hand, Alternative Options (AO) will have a negative impact on_ students’ intentions From this study, the authors have been able to reach a meaningful conclusion and have given plausible recommendations that can help improve the current bus system

II Table of contents

150.00 ]

LIST OF ACRONYMS 2 .L S222 H1 21111111111 2 ng Vv LIST OF TABLES uo cececceccecceeeececeeeeceseneeteeseseesceaeeeeecaeeneeeeeeaes VI LIST OF FIGURES S2 2220121121211 11 111111111 1115 112011012 xe Vul CHAPTER 1: INTRODUCTION 200 cccecccteeeteenseteeensaeeeenenes l 1.1 Introduction to the topic, literature review, and reason for ` 0 .ỒỒỎ l 1.1.1 Introduction to the topIc - ¿2-5 22252221122 s s2 l 1.1.2 Literature review (a summary of previous research) 2

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CHAPTER 2: THEORETICAL BASIS AND PROPOSED RESEARCH MODDEL, - 2 2012110111 1111114111 11111111111 1111111111116 11 11 v2 4 PC ỌỤỪVẶ 4 2.2 Related concepfs - - - - 0 201120112111 12111111 111181111 7 2.2.1 Concept 0Ÿ S€TVIC€ 0 2000122221211 11 2201 1182 11g 7 2.2.2 Concept about consumer buying behavior 7

2.2.3 Concept about 1ntention - 5 2 2251222221222 7 2.2.4 Concept about intention to use a servIce 7

2.2.4 Concepts about public bus transportation 8

2.2.5 Concepts about public bus transportation 8

Phi 8

2.3.1 The theory of planned behavior - TPB - 8

2.3.2 Technology acceptance model - TAM 9

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2.3.3 Integration of TPB AND TAM u cece cece ceceneteeenes 9 P ca nh C gadd 10 2.4.1 Perceived usefulness (PŨ) - 2 c2 222222222 s2 10 2.4.2 Bus stop (Bồ) Q2 00122 112222122 xe ưe 10 2.4.3 Subjective norms (SN) L L2 HH Hà II 2.4.4 Alternative options (AÔ) HH Ha II 2.4.5 Electric bus (EB) - 2 22211220111 1211121 111111121222 II 2.4.6 Environmental awareness (EÀA) -c 22-552 12 2.5 Proposed research model 5c 2 2 S22 23122222 2zzxk2 12

CHAPTER 3: RESEARCH METHODOLOGY 12

3.1 Measurement scaÌ€s ác nh HH 21 T11 H1 11k re 12 3.1.1 Perceived useftllness - ác SH re 13 3.1.2 SubJe€CtIV€ TIOFTT§: - ¿22 2 22 222222211152 521111 15232 1x+2 13 3.1.3 cdưiọDùDùDùDỤẶỤẶỤẶẠ 14 3.1.4 Environmental awareness ác nhe, 14 Ea 15 3.1.6 Alternative OptIOI§ - L 2 2 221220111211 112 115111 cey 15 3.1.7 Intention to use the bus system -¿ 16 3.2 Research methos - - c c 21 2121115121115 111 11111 16g L7 3.2.1 Methods of analysis and synthesIs - - - 17 3.2.2 The method of data collection .-sc s25 c+2z s22 L7 3.2.3 Non-experimental method +52 552 5s25<<s252 17 3.3 Research 0n 44 18 3.4 Quantitative research - + c1 2:1 111122111 111111 1121222 18 3.4.1 Research subJect - c2 cà 1122122 121 1111211111122 1x2 18 KV 000 -6⁄⁄:i 18 3.4.3 Choose a research sample cece cece cceetteteetenees 19 3.4.4 Data collection method ác n2 re 19 3.5 Data analysis method - 5: 22 22211112111 1211 11122131252 19 3.5.1 Cronbach”s Alpha Reliability test - 19 3.5.2 EEFA - Exploratory Factor AnalysIs 20 3.5.3 Pearson Correlatlon AnalÌysIs 2 c2 c 222cc s22 20

IV

3.5.4 Multivariable Regression AnalysSIs - 21

CHAPTER 4: RESEARCH RESULTS - 52 S25 S222 se 21

4.1 DescrIptive statIsties of the survey sample 21 ñhn c na 21 4.1.2 Batch of student ác n2 21211 1110111112 rà 22 4.1.3 Survey reSUÏfS - 2.1 2011110 11112111 1111111111111 xk2 22 4.2 Analytical data om key questlons - 5: 25 4.2.1 Reliability test: Cronbach Alpha -: 25 4.2.2 Factor Analysis Results for Dependent Variable Seales 32 4.2.3 Pearson CorreÏafIOH - ác: cc S1 2112111111221 rreg 35 4.2.4 Regression AnaÌy§Is - n1 211212 21H hà 37 CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS 42 5.1 COMCIUSIONL 00 cece eee eeeneeceeesenneseeeeeeeesesaesesteeeneeeneeenes 42 5.2 Contribution t0 tOpIC 2 1 221122111011 1121112111 1111112 43 5.3 RecomimmendafIOIs - á- c2 2112112 12111111 11212111 1111 1k6 43 5.4 Limitations of research cece eee eecee cee tee centre saeeneeeeeeee 43

REFERENCES Q2 n1 9110110111 1011111111 01 11111611 0111 kh 44

APPENDIE Án HH HH HH HH HH HH kh 46

LIST OF ACRONYMS PU: Perceived usefulness

BS: Bus stops SN: Subjective norms AO: Alternative options EB: Electric buses

EA: Environmental awareness IT: Intention to use the bus

SPSS: Statistical Package for the Social Sciences

VI LIST OF TABLES

Table 2.1 Factors influencing intention to use the bus system Table 3.1 Perceived usefulness scale

Table 3.2 Subjective norms scale Table 3.3 Bus stops scale

Table 3.4 Environmental awareness scale Table 3.5 Electric buses scale

Table 3.6 Alternative options scale

Table 3.7 Intention to use the bus system scale Table 4.1 Descriptive table of survey response: Table 4.2 Reliability statistics of “Perceived Usefulness” Table 4.3 Table of results to evaluate the reliability of the scale “Perceived Usefulness”

Table 4.4 Reliability statistics of “Bus stops”

Table 4.5 Table of results to evaluate the reliability of the scale “Bus stops”

Table 4.6 Reliability statistics of “Subjective norms”

Table 4.7 Table of results to evaluate the reliability of the scale “Subjective norms”

Table 4.8 Reliability statistics of “Alternative options” Table 4.9 Table of results to evaluate the reliability of the scale “Alternative options”

Table 4.10 Reliability statistics of “Electric buses”

Table 4.11 Table of results to evaluate the reliability of the scale “Electric buses”

Table 4.12 Reliability statistics of “Environmental awareness” Table 4.13 Table of results to evaluate the reliability of the scale “Environmental awareness”

Table 4.14 Reliability statistics of “Intention to use the bus” Table 4.15 Table of results to evaluate the reliability of the scale “Intention to use the bus”

Table 4.16 Results of KMO and Bartlett tests of independent variables

Table 4.17 Result of EFA

Table 4.18 Pearson Correlation Table Table 4.19 Model fit table

Table 4.20 ANOVA table Table 4.21 Coefficient table

VI LIST OF FIGURES

Figure 2.1 Model depicting the theory of planned of behavior — TPB

Figure 2.2 The technology acceptance model - TAM

Figure 2.3 Model Integrating the TPB theory and the TAM Model

Figure 2.4.Model of factors influencing intention to use the bus

system

Figure 3.1 Research process

Figure 4.1 Pie chart depicting genders participating the survey Figure 4.2 Pie chart depicting batch of students

Figure 4.1 Regression analysis model

Figure 4.2 Normalized Residual Frequency chart Histogram Figure 4.3 Normalized Residual Frequency chart Normal P-P Plot

Figure 4.4 Normalized Residual Frequency chart Scatterplot:

Various factors can lead to traffic congestion Economic expansion and increased urbanization lead to more people and vehicles in the city As the city grows and develops, more people move in to seek better opportunities and services As a result, this leads to more motorcycles and cars on the road, meaning more traffic problems It is safe to assume that traffic congestion in Ho Chi Minh City is a pressing issue that requires urgent attention and action from the authorities and the public For years, the People’s Committee of Ho Chi Minh City has implemented many policies to alleviate this problem, and they are particularly invested in improving the public transport system like buses Some notable changes are offering financial support utilizing decreasing the bus ticket price for seniors and students, establishing more bus routes, and motivating the population to download bus applications like Go!Bus, introducing and implementing electric buses to widespread usage, etc Despite the city’s immense effort, their actions have proved in recent years not to be impactful enough in decreasing the traffic congestion rate Every year, bus transportation contributes to only about 14% of the city’s traffic flow based on a past report According to the Ho Chi Minh City Police Department, the number of passengers transported via buses currently only equals approximately 50% of the previous period before COVID-19 In the same paper, it is also noted that people stopped commuting by bus due to several reasons like inconsistent punctuality among buses The buses being punctual is especially important to university students since they have to attend their lectures and examinations on time Some other reasons include limited routes dedicated to buses, the convenience of personal vehicles, safety and sanitary reasons, etc Moreover, young people like university

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students nowadays are becoming more and more accustomed to new technological advancements, combined with the exponential growth of several online ride-hailing services like Grab-bike, Gojek, Be, etc This has made technology drivers to be a far more popular alternative to buses among students Furthermore, after being in commission for over a year, the electric bus “VinBus”, which has garnered much popularity and positive feedback from the public, is facing the possibility of being out of service

Given the decline in usage and many shortcomings of buses as a means of transport in Ho Chi Minh City It is very important to discover and understand the underlying factors that directly or indirectly influence the intention of Ho Chi Minh City residents to use the bus to travel within the city Knowing this will help the Vietnamese government and the People’s Committee of Ho Chi Minh City make improvements to their policies and also find suitable solutions so that they can increase the usage and attractiveness of the public bus system, therefore reducing the impact of traffic congestion as well as improve environmental well-being A shift to public transport could lead to improved environmental conditions and better health and well-being of the people (Haghshenas & Vaziri, 2012) 1.1.2 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)

1.1.3 reason for research

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

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 1.6 Research structure

The layout of this research is divided into five chapters: Chapter 1: Introduction

Chapter 2: Theoretical Basis and Proposed Research Model Chapter 3: Research Methodology

Chapter 4: Research Results

Chapter 5: Conclusions and Recommendations

CHAPTER 2; THEORETICAL BASIS AND PROPOSED RESEARCH MODEL

2.1 Related researches

No Positive impact Negative impact Perceived |Bus | Subjective | Environmental | Electric Alternative usefulness | stops | norms awareness buses options 1 Factors x x x

affecting urban people’s intention to

use buses in Vietnam (Nguyen & Thach, 2023)

Obstacles towards using buses in Thua Thien Hue Province (Hoang & Tran, 2017)

The influence of bus service satisfaction on University students’ mode choice (Shaaban & Kim, 2016)

Why are Hanoi students giving up on bus ridership? (Nguyen & Pojani, 2022)

Psychologic al

determinants of the intention to use the bus in Ho Chi Minh City (Satoshi &

Hong, 2009)

Behavioral intention to use public transport based on theory of planned behavior (Ambak et al., 2016)

Public transportatio n in Hanoi: Applying an integrative model of behavioral intention (Ng & Phung, 2021)

Habitual or reasoned? Using the theory of planned behavior, technology acceptance model, and habit to examine switching intentions toward public transit (Chen & Chao, 2010)

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2.2.2, Concept about consumer buying behavior

Kotler & Keller (2011) state that consumer buying behavior is the study of the ways of buying and disposing of goods, services, ideas, or experiences by individuals, groups, and organizations to satisfy their needs and wants

2.2.3 Concept about intention

Intention is a plan or how someone will behave in certain situations in certain ways, whether they do it or not (Fishbein & AJzen, 1975) In addition, consumer intention relates to customers' wants and needs in selecting related products, services, and suppliers (David at el., 1989)

2.2.4 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

8 2.2.4, 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

2.2.5, 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

2.3 Theoretical basis

2.3.1 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)

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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)

Perceived usefulness

Perceived ease of use

Perceived usefulness

r Attitude Behavioral

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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

2.4, Hypothesis

2.4.1 Perceived usefulness (PU)

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

2.4.2 Bus stop (BS)

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

2.4.3 Subjective norms (SN)

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:

HH

Hypothesis H3: SubJective norms have a positive impact on intention to use the bus system

2.4.4 Alternative options (AO)

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

2.4.5 Electric bus (EB)

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

2.4.6 Environmental awareness (EA)

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

2.5 Proposed research model

Figure 2.4 Proposed model

CHAPTER 3: RESEARCH METHODOLOGY 3.1 Measurement scales

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 3.1.1, Perceived usefulness

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

PU3 PU4 PUS PU6

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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 Commonly used bus apps (Go! bus, BusMap ) are very useful

Table 3.1 Perceived usefulness scale 3.1.2, Subjective norms:

Variable code SNI SN2 SN3 SN4

Question Original question

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

Table 3.2 Subjective norms scale

(2010)

Based on previous researches Based on previous researches Based on previous researches Source Borith, Kasem, & Takashi (2010) Hoang & Tran (2017) Chen & Chao (2010) Hoang & Tran (2017)

previous researches BS3 The station has a good protective roof Shade Shaaban &

Kim (2016) Table 3.3 Bus stops scale

Question Original Source question

EBI EB2 EB3 EB4 EBS

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 Based on previous researches Based on previous researches Based on previous researches Based on previous researches Table 3.5 Electric buses scale

3.1.6, Alternative options Variable

code AOI AO2 AO3 AO4

Question

Using a private vehicle is more convenient

Original question Using private vehicles is more convenient than using the bus

Using ride-hailing services is more convenient

Walking will be better Other choices will be more flexible

Source Hoang & Tran (2017) Based on previous researches 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,

Kasem, & Takashi

(2010)

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 3.2 Research methods

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

3.2.3 Non-experimental method

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

3.3 Research process

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

3.4.3 Choose a research sample

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.

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¢ 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

3.4.4 Data collection method

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

3.5 Data analysis method

3.5.1, Cronbach’s Alpha Reliability test

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

3.5.2, EFA - Exploratory Factor Analysis

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 <0.05 (statistically significant)

® Eigenvalue is used to determine the number of factors in EFA analysis With this criterion, only factors with Eigenvalue > | are kept in the model

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¢ 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 3.5.3 Pearson Correlation Analysis

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

3.5.4, Multivariable Regression Analysis

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).

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® 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

4.1.2 Batch of student

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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%)

4.1.3 Survey results

Descriptive statistics

N Minimum Maximum Mean Std Deviation 268 1 5 4.36 0.899 PU2 Using the bus 268 1 5 3.6 1.036 is very safe

PU3 Using the bus 268 1 5 3.3 1.092 1s very comfortable

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

EB3 Electric buses 268 268 268 268 268 268 268 268 268 268 268 268 268

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3.68 3.65 4.05 3.95 3.64 4.19 3.9 3.08 3.86 3.6 3.91 4.27

1.054 1.065 1.126 0.943 1.041 01.041 0.996 0.960 1.097 0.948 1.199 0.942 0.906

will be more modern

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

268 268 268 268 268 268 268 268 268

24

3.67 4.32 4.27 3.62 4.19 3.93 3.47 2.93 3.16

0.955 0.896 0.921 1.144 0.86 0.954 1.166 1.126 1.134 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

® 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

4.2.1 Reliability test: Cronbach Alpha

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 Perceived usefulness:

Cronbach’s Alpha Number of items

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 PU6 Commonly used bus app (Go!

Bus,

BusMap ) Is very useful

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

18.74 18.87 18.09

14.394 14.676 14.506

26 0.537 0.458 0.582 Usefulness” used in the next factor analysis

Bus stops: Variables BS1 Bus stops are very clean BS2 Bus

Cronbach’s Alpha Number of items 0.786

Table 4.4 Reliability statistics of “Bus stops” Scale

mean if Item Deleted 7.33 6.78

Scale variance if Item deleted 3.809 3.107

There is no case of eliminating any 3

Corrected Item-Total Correlation 0.516 0.720

0.789 0.808 0.779 Cronbach’s Alpha if item Deleted 0.821 0.604

Suitable variable Suitable variable Suitable variable Conclusion Suitable variable Suitable

stops have seats BS3 Bus stops have good protective roof

6.81 3.258

27

0.651 0.682

variable Suitable variable Table 4.5 Table of results to evaluate the reliability of the scale

“Bus stops”

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

Subjective norms: Variables

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 0.803 4

Table 4.6 Reliability statistics of “Subjective norms” Scale

mean if Item Deleted 11.64 10.74 10.85

Scale variance if Item deleted

6.575

6.874 6.340

Corrected Item-Total Correlation 0.523 0.628 0.657

Cronbach’s Alpha if item Deleted 0.803 0.750 0.733

Conclusion Suitable variable Suitable variable Suitable variable