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Travel Behavior Analysis Focusing on Private Vehicle Usage and Switch to Public Transport in Ho Chi Minh City NGUYEN Ngoc Thi TRAVEL BEHAVIOR ANALYSIS FOCUSING ON PRIVATE VEHICLE USAGE AND SWITCH TO P[.]
Travel Behavior Analysis Focusing on Private Vehicle Usage and Switch to Public Transport in Ho Chi Minh City NGUYEN Ngoc Thi TRAVEL BEHAVIOR ANALYSIS FOCUSING ON PRIVATE VEHICLE USAGE AND SWITCH TO PUBLIC TRANSPORT IN HO CHI MINH CITY by NGUYEN Ngoc Thi Submitted to the Graduate School of Environmental Studies In Partial Fulfillment of the Requirements for the Degree of Doctor of Engineering at Nagoya University July 2018 Academic Advisers: Professor Morikawa Takayuki Professor Tanikawa Hiroki Associate Professor Miwa Tomio Abstract A public transport (PT) system that is a low carbon transport option is vital for sustainable urban development However, introducing this type of system in developing cities may be a challenge given residents’ common practice of using private vehicles, especially motorcycles Take Ho Chi Minh City as an example, the usage preference of private vehicle users for their own vehicles, the current bus system, and the future PT system were investigated This research aims to develop analyses based on using practical data about vehicle usage and applying feasible methods and/or improving them for understanding the situation and for finding solutions boosting sustainable travel behaviors in the city Methodologies of demand modeling, discrete choice models were used to explore individual behaviors on the private vehicle usage and switch to PT The advantage of revealed preference data, stated preference data, and experiment design were taken in specific analyses The preference of private vehicle users on their own vehicles is analyzed using revealed data A joint discrete-continuous model based on the copula approach is used to overcome selectivity bias in the data and to address the relationship between vehicle type choice (a discrete outcome) and usage (a continuous outcome) by specifying a joint distribution The analysis found significant roles of socioeconomic attributes on the individual choice, a trend of modal shift from motorcycles to cars, and CO2 emissions from this trend The motivations so that the private vehicle users switch to PT were analyzed using a revealed-stated preference data The analyses followed a two-stage approach consisting of a multiple-indicator–multiple-cause model for capturing psychological determinants and a bivariate ordered probit model for explaining the decisions of each user group on usage frequencies of the current buses and the new PT system The new PT usage was found to be correlated with bus usage The significant roles were explored in factors of access/egress time, fare/cost, congestion/comfort, social interaction, agreement to the PT projects, dissatisfaction with PT, distance from home to workplace, motorcycle ownership, occupation, and age In addition, by adding a component of latent class assignment, the heterogeneity among motorcycle users was detected in choice models in the latent classes The “collectivistic” and “individualistic” tendencies in the two latent classes were found to make the individuals behave in different ways Lastly, by adding a dimension of in-vehicle occupancy into the traditional social interaction that reflects individual’s behavior and other people’s behavior, an equilibrium calculation on both positive and negative mass effects was able to conduct based on loop procedures The results give envision on travel demand for commuting trips by PT in the future situation Thesis Supervisor: Morikawa Takayuki Title: Professor, Graduate School of Environmental Studies Acknowledgments This work was partly supported by the Japanese Government (Monbukagakusho: MEXT) Scholarship awarded through the Forefront Studies Program on Civil and Environmental Engineering for Sustainable Co-Development of Nagoya University It was also partly supported by the Nagoya University Transportation and Environment Dynamics (NU TREND) Laboratory I wish to express my appreciation to those who have helped in carrying out this thesis I am particularly indebted to Professor Morikawa Takayuki who gave me the opportunity to study in Nagoya University As my thesis supervisor, he provided me with valuable suggestions and insightful guidance during the planning and development of research works Special thanks should be also given to Associate Professor Miwa Tomio, who worked as my academic advisor and gave me precious advice throughout my research works I am grateful for his willingness, patience, and enthusiastic encouragement Professor Tanikawa Hiroki has served as a committee member He gave me very useful comments and suggestions from his extensive experiences that significantly improved the clarity of this thesis My gratitude are also expressed to Lecturer Sato Hitomi for her great help in collecting data Professor Yamamoto Toshiyuki and Associate Professor Kanamori Ryo gave me helpful comments Lecturer Tashiro Mutsumi, Ms Kikata Chiharu, and Ms Tsuda Junko provided me with their valuable assistances through my stay in Nagoya University I would like to acknowledge the support of Associate Professor To Hien T., Ms Nguyen Nguyen T., and Mr Tran Vu of VNUHCM-University of Science in conducting the pilot survey I would like to thank my lab mates, Chu Dung T., Tosa Cristian, Gong Lei, Phyu Phyu Thwe, Mothafer Ghasak, Li Yan Yan, Liu Zhiquang, Hao Mingyang, Ye Lanhang, Ban Takumi, Tang Routian, and Sangeetha Ann I learned both academic and non-academic things from them Discussions with Chu and Tosa are extremely useful in conducting empirical analyses Finally, my sincere thanks are extended to my parents and my husband for their understanding and encouragement throughout my study Table of contents Abstract Acknowledgments Table of contents List of Figures List of Tables List of Abbreviations 10 Introduction 11 1.1 Background 11 1.1.1 Overloaded Traffic Infrastructure in Ho Chi Minh City 11 1.1.2 Select a “Green” Mode: the Planned Public Transport System 12 1.1.3 Travel behavior analysis 13 1.2 Problem Statements and Objective of this Research 14 1.3 Outline of the Thesis 14 Literature Reviews 16 2.1 Local Context and Public Transport Development 16 2.2 Role of Travel Behavior Analysis in Transport Planning 17 2.3 Habitual Travel Choice 17 2.4 Barriers and Motivations of Sustainable Travel Behavior 19 2.5 Summary 19 Data Collection 20 3.1 A Dataset of Vehicle Type Choice and Usage 20 3.2 First Revealed Preference-Stated Preference Survey on Public Transport 21 3.3 Second Revealed Preference-Stated Preference Survey on Public Transport 23 3.4 Auxiliary Data 25 Vehicle Type Choice, Usage, and CO2 Emission 27 4.1 Methodology for Discrete-Continuous Choices 28 4.2 Modeling Framework 29 4.2.1 Multinomial Logit Component of Vehicle Type Choice 30 4.2.2 Regression Component of Usage 30 4.2.3 Joint Model 31 4.3 Data Preparation 33 4.4 Results and Discussion 38 4.4.1 Model Estimation Results 38 4.4.2 Model Application 42 4.5 Summary 44 Trips Motivations on Switching to Public Transport Modes for Commuting 46 5.1 State of the Analysis 46 5.1.1 Role of Psychological Determinants in Travel Behavior Analysis 46 5.1.2 Effects of Social Interaction 47 5.1.3 Combination of Revealed Preferences and Stated Preferences 48 5.2 Modeling Framework 49 5.2.1 MIMIC Model 49 5.2.2 Bivariate Ordered Probit Model 50 5.3 Data Preparation 52 5.4 Results and Discussion 56 5.4.1 Results of the MIMIC Model 56 5.4.2 Results of the Bivariate Ordered Probit Model 58 5.5 Summary 62 Latent Classes in Response to the Planned Public Transport System 64 6.1 Latent Class Assignment: A brief review 64 6.2 Methodological Framework 65 6.3 Data Preparation 69 6.4 Results and Discussion 71 6.4.1 Latent Classes 71 6.4.2 Utility Function of PT Usage 73 6.4.3 6.5 Summary 76 Positive and Negative Mass Effects: Equilibrium in Public Transport 78 Usage 7.1 Implications for Policy Making 75 Methodological Framework 79 7.1.1 Modeling 79 7.1.2 Equilibrium Analysis 81 7.2 Data Preparation 83 7.3 Results and Discussion 86 7.3.1 Psychological Determinants 86 7.3.2 Utility of PT Usage 88 7.3.3 Mass Effects and Equilibrium 91 7.3.4 Implications for Policy Making 93 7.4 Summary 94 Conclusions and Future works 95 References 99 Appendix A 109 Appendix B 121 List of Figures Figure 1.1 Travel demand is growing 12 Figure 2.1 The process of script-based choice (Gärling et al., 2001) 18 Figure 3.1 Example of a case in the first experiment 22 Figure 3.2 Example of a case in the second experiment 24 Figure 4.1 CO2 emissions in various scenarios 44 Figure 5.1 Distribution of occupation among motorcycle users and car users 52 Figure 5.2 Distribution of decisions on usage frequencies of PT 55 Figure 5.3 Reasons not to use the new PT system more frequently 55 Figure 5.4 Relationships among latent variables 58 Figure 6.1 Methodological framework 66 Figure 6.2 Improvement in modeling framework 67 Figure 6.3 Outcome probabilities 74 Figure 6.4 Sensitivity analysis for Class “Collectivistic” 76 Figure 6.5 Sensitivity analysis for Class “Individualistic” 76 Figure 7.1 Modeling framework 80 Figure 7.2 Flow chart of the algorithm for calculating equilibrium points 82 Figure 7.3 Distribution of choice in frequencies of PT usage for commuting trips 86 Figure 7.4 Structural relationships for latent variables 88 Figure 7.5 Equilibrium for the two-dimensional social interaction 92 Figure 7.6 Output of the equilibrium for the three-dimensional social interaction analysis 92 List of Tables Table 3.1 Description of factors in the first experiment 22 Table 3.2 Description of factors in the second experiment 24 Table 4.1 Distribution of vehicle type choices and usage 35 Table 4.2 Descriptions of the explanatory variables 36 Table 4.3 Estimation result of the ordered probit model for income 37 Table 4.4 Estimation result of the ordered probit model for expenditure 37 Table 4.5 Estimated parameters of the joint model 40 Table 4.6 Validation results 41 Table 4.7 Changes in the 10th year compared with the base case 43 Table 5.1 Intervals specific for categories 51 Table 5.2 Summary statistics by private vehicle users 53 Table 5.3 Descriptive statistics of indicators and socioeconomic variables for psychological determinants 54 Table 5.4 Relationship between latent variables and indicators 57 Table 5.5 Relationship between causal variables and latent variables and DIF effects 57 Table 5.6 Estimated parameters of the bivariate ordered probit models 60 Table 6.1 Descriptive statistics (N=591) 70 Table 6.2 Latent class choice model for the usage frequency of PT of motorcycle users 72 Table 7.1 Demographic Statistics (N=1030) 84 Table 7.2 Descriptive Statistics of Indicators for Psychological Determinants (N=1030) 85 Table 7.3 Relationship between Latent Variables/Psychological Determinants and Indicators 87 Table 7.4 Testing DIF 87 Table 7.5 The utility model of PT usage 90 Table 7.6 Sensitivity 94 List of Abbreviations AIC Akaike’s information criterion APV Awareness of problems relating to private vehicles APP Agreement to public transport projects CNG Compressed Natural Gas CP Car passion DB Dissatisfaction with bus DIF Differential item functioning DPT Dissatisfaction with the new public transport system HCMC MIMIC Ho Chi Minh City Multiple-indicator–multiple-cause MC Motorcycle PT Public Transport RP RUM Revealed reference Random Utility Maximization SD Standard deviation SP Stated preference VND Vietnamese Dong, the currency of Vietnam 10 Introduction 1.1 Background The motivation of this study is from the transportation situation of Ho Chi Minh City (HCMC) in that the current traffic infrastructure is overloaded by a huge amount of private vehicles and the effectiveness of the planned public transport (PT) system is questioned Along with the rapid economic growth, population growth, and urbanization, the transportation system would be worse if the private vehicle dependency is not reduced and the new PT system is not preferred 1.1.1 Overloaded Traffic Infrastructure in Ho Chi Minh City HCMC is the biggest city Vietnam with an area of 2096 km2 and a population of 8.4 million people Because most of the population (80%) live in urban areas, the density in these areas has reached about 14000 people/km2 (HCMC Statistical Office, 2017) Regarding the transportation system, based on roadway, both the road density and land area for transportation are now substandard The road density is 1.9 km/km2 compared with the standard of 10 km/km2 The land area for transportation is 8.2% compared with the standard of 24% (Vietnam Government, 2011) While the infrastructure is overloaded, travel demand is growing year by year The data of five recent years shows a quick increase in the number of motorcycles and cars along with an increase of population (see Figure 1.1) Notably, the PT system with only buses witnesses a steady decrease in usage in the same period Emberger (2016) reported a modal split of around 3% pedestrians, 1% cycling, 6% PT, 9% cars, and 81% motorcycles The trend of private vehicle dependency may continue to increase because the quality of the current bus system is poor, and people’s wealth may encourage the use of private vehicles (Dargay and Gately, 1999; Dalkmann and Huizenga, 2010) Consequently, the transport system faces challenges in terms of capacity constraints and environmental problems The urban space has been pressured by traffic congestion, not only during rush hours This causes a certain loss of time and difficulties in accessing services Also, the unsafety becomes serious There were over 700 people died because of traffic accidents in 2017 (Ministry of Public Security, 2018) The ambient air is polluted by noise and traffic emissions that are mainly caused by motorcycles (Ho and Clappier, 2011) 11 Figure 1.1 Travel demand is growing 1.1.2 Select a “Green” Mode: the Planned Public Transport System The environmental problem of transportation is related to the energy used by traditional modes of transportation When considering urban sustainability and efficiencies in transport and energy use, both private and PT have been explored In general, PT, which is a mass transit system, has been suggested as more effective than private vehicles because of its high capacity, resulting in less congestion on roadways and less energy consumption per passenger Kii and Hanaoka (2003) argue that the effectiveness of PT depends on the urban structure If population density is low, demand will be small, resulting in higher energy consumption per passenger with PT than with private vehicles Moreover, technological progress towards cleaner vehicles makes private vehicles more attractive when considering environmental benefits Even in a dense city, transit-oriented development has the unavoidable challenge of public adoption Kenworthy (2008) found in many cities that a successful PT system depends on its extent and quality In Los Angeles, Chester et al (2013) found that the environmental goal is only achieved with a modal shift of between 20 and 30% A combination of high capacity, high population density, and a modal shift contribute to the cleanness of PT systems In HCMC, there are several reasons PT should be a good selection First, PT helps reduce the pressure created by a huge number of private vehicles (7.4 million) on urban spaces with a population density of about 4,000 persons/km2 (HCMC Statistical Office, 2017) Second, most of the private vehicles currently operated in HCMC use traditional fuels, which pollute the environment A mass replacement of these vehicles with cleaner private vehicles is not easy to accomplish (see Egbue et al (2017) for the case of electric vehicles) Third, the new PT system includes cleaner technologies The 12 buses are able to use cleaner fuels, such as compressed natural gas (CNG) and electricity, while the other modes of railway lines use electricity The government has planned for a future PT system in HCMC, which includes new technological modes such as bus rapid transit (BRT), metro, monorail, and tramway The projects are expected to be finished by 2030 and meet a travel demand of 35% of the general population (Vietnam Government, 2016) In that, the length of railway will be 216 km and the length of busway will be 100 km The system is designed to go through the city center and connect to suburban areas, rural areas, and nearby provinces The connection of many PT lines creates many transfer stations that are useful for traveling across the city area When the projects are finished, residents will have more choices for traveling in daily life In another aspect, although the quality of the PT system is improved, a switch to using the PT system might be not as expected because people have been familiar with using private vehicles for a long time Examples include the low usage rates of the better new systems found in neighbor cities such as Jakarta, Bangkok, and Manila (Tuan, 2015; Feng and Sun, 2013) This shows that the investment in the infrastructure itself is not sufficient 1.1.3 Travel behavior analysis It is a fact that PT development is more difficult in developing cities The reason of local context is supposed to be in relation to the habit of using private vehicles Moreover, the preferences can differ among individuals The issues could be clarified through investigations on travel behaviors of private vehicle users Avineri (2012) indicated that travel behavior analysis is important for seeking alternative policies For the problem of private vehicle dependency, the individuals’ choice of vehicle type and usage have been examined in developed countries rather than developing countries (Golob et al., 1997; Lai and Lu, 2007) The two choices are found to be interrelated and better to be captured by a simultaneous approach using a copula than by two-stage approaches (Spissu et al., 2009) The vehicle choice among segments was considered in (Banerjee et al., 2010) A number of annual vehicle miles is considered a habit indicator (Gärling and Axhausen, 2003) For the problem of motivations of switching to PT, many studies indicate the important roles of service quality and socioeconomic characteristics (dell’Olio et al., 2011; Redman et al., 2013; Satiennam et al., 2016) Psychological determinants have been used to enhance the explanations of individual choices on PT usage (Ben-Akiva et al., 2002; Morikawa et al., 2002) based on both sequential and simultaneous approaches Raveau et 13 al (2010) show that the effectiveness of these approaches is not different In addition, an equilibrium between in-vehicle occupancy and PT capacity was analyzed (Batarce et al., 2016) 1.2 Problem Statements and Objective of this Research The passenger transport system plays an essential role in urban development In the context of HCMC, developing public transport (PT) and achieving a certain modal shift are considered the best solutions However, the current problem of private vehicle dependency would be an obstacle Even though the new PT system is established, its effectiveness would be challenged by the preference on usage Regarding travel behavior analysis, for the private vehicle dependency, such studies of choices of vehicle type and usage are still new in developing cities The diversity of private vehicles is rarely mentioned Moreover, CO2 emissions resulted from the choices have not been considered For the preference on PT usage, the modal shift has been considered as a sudden shift of mode choice which is hard to expect in a private vehicle-dependent city The impacts of past habit, social interaction, and the heterogeneity among individuals have not been considered In addition, the equilibrium relating to the in-vehicle occupancy is rarely investigated Regarding HCMC as a case study, there is a lack of empirical studies to address specific characteristics in the local context There are three research questions as follows: • How to understand the situation of private vehicle dependency considering the diversity of private vehicles in the market and the dependency’s impacts on CO2 emissions in HCMC? • How to encourage PT usage among private vehicle users in the city? • How to capture the equilibrium in the new situation of PT usage? The objective of this research is to develop analyses based on using practical data about vehicle usage and applying feasible methods and/or improving them for understanding the situation and for finding solutions for boosting sustainable travel behaviors in HCMC Four analyses are presented to address answers to the questions The study is expected to be helpful for policy debates to improve the urban transport system in HCMC 1.3 Outline of the Thesis This thesis includes eight chapters Chapter reviews the characteristic of local context in PT development, the role of travel behavior analysis in transportation planning, and the issues of habitual travel choice This chapter also summarizes the prior studies on barriers 14 and motivations of sustainable travel behavior Chapter presents the data collection The reasons for seeking the data are clarified and then, how datasets were collected is presented Chapter 4, Chapter 5, Chapter 6, and Chapter present four empirical analyses about the usage of private vehicles, the current PT system, and the future PT system Depending on the kind of analyses, the methodology and data usage are presented in each of these chapters In Chapter 4, a discrete-continuous model is estimated using a revealed preference data on private vehicles to address the vehicle type choice, usage, and CO2 emission The following three chapters address the issues concerning the PT usage, at present and in the future Chapter incorporates psychological determinants, captured by MIMIC model, into a bivariate ordered probit model of PT usage to find latent motivations so that private vehicle users switch to PT for commuting trips In Chapter 6, a component of latent class assignment is added to address the heterogeneity among individual choices on PT usage In Chapter 7, the issues of positive mass effect and negative mass effect are discussed The two effects were captured in a numerical equilibrium analysis that provides a prediction of travel demand for commuting trips by PT in the future Finally, some conclusions and future works are given in Chapter 15 Literature Reviews A transportation system is sustainable when it is accessible, safe, environmentally-friendly, and affordable (European Conference of Ministers of Transport, 2004) Depending on the local context, components of the transportation system will be designed appropriately In general, a trend of PT development is encouraged Indeed, many studies found that modal shifts to PT are beneficial to both transport efficiency and environment, especially on air pollution reductions (Kwan and Hashim 2016) However, both researchers and policymakers have faced a challenge in persuading the private vehicle users to switch to use PT The challenge is in relation with the understanding of the role of travel behavior analysis in transport planning and the characteristics of habitual travel choice in addition to the list of barriers and motivations of sustainable travel behavior 2.1 Local Context and Public Transport Development Although PT has been encouraged to develop in many cities, the systems’ effectiveness is not equal The first concerned point should be the local context Three notable examples would be presented in an order of development to show the uncertainty First, in Tokyo, the railway system was built in 1927 and has been developed continuously since then At that time, the residents might not have many mode choices for their traveling Motorcycles and cars were expensive Therefore, the appearance of PT provided a helpful traveling mode Due to the consecutive developments, Tokyo is owning one of the best PT systems in the world The high coverage of PT with many service types increases the convenience it makes to residents’ traveling Although a trend of automobile development is happening in most cities in the world, Tokyo’s residents seem to be less impacted by this trend The usage rate of PT has remained from 70 to 80% (Tuan, 2015) Next, Taipei developed their PT system later They early have a bus system, but the MRT system has just operated since 1996 Motorcycles have become common at the time Although they currently have a dense system of buses and MRT, the motorcycle share has remained more than 30% Finally, Jakarta started developing their PT system by introducing a BRT network recently The system began operation in 2004 However, the motorcycle share continued increasing from 26% in 2002 to 63% in 2010 (Tuan, 2015) Although studies point out detailed factors rather than directly point out a general effect of local context, reviewing the examples might initially express the contribution the local context makes on the PT development At least, in the historical aspect, the local 16 context might provide conditions for formatting the habitual travel choice that would be reviewed below 2.2 Role of Travel Behavior Analysis in Transport Planning Travel behavior is the way people behave in relation to transportation such as the mode they use or the route they choose It is normally explained based on the rational economic forces (Button, 2014) Following that, individuals will perform their behavior with an intention that is identified as the will to attain a goal (Gollwitzer, 1993) The intention is sourced from deliberation in maximizing their utility, as explained by the Random Utility Maximization (RUM) theory The travel behavior analysis is understood as an analysis of the utility function based on the data about travel behavior The data basically reflects individuals’ preference By the analysis, factors contributing to the preference will be explored Because travel behavior will change in different circumstances of transportation facilities, the travel behavior analysis will help reveal the travel demand in these circumstances To some extents, the analysis will be helpful for transport planning in predicting future travel behaviors (Button, 2014) Policymaking will benefit from understanding the travel behavior in marketing strategies on target measures In addition to identifying infrastructural and technological issues, many studies have proposed that appropriate solutions to sustainable mobility require sufficient recognition of the behavior of commuters (Avineri, 2012; Garcia-Sierra et al., 2015; Steg and Vlek, 2009) Banister (2008) indicated the central role of green transportation in sustainable urban development and the key elements including the best use of technology and public acceptability for behavioral change Because of this, many models have been developed to explain specific choice behaviors (Ben-Akiva and Bierlaire, 1999; Train, 1986; Washington et al., 2011) Survey data is found to be helpful in this case Notable examples are found in the studies on the influences of alternative policies to control vehicle pollution (Chen and Wang, 2016; Kaffashi et al., 2016; West; 2004) 2.3 Habitual Travel Choice A habitual choice is separated from an intention by performing behavior without deliberation (Gärling and Garvill, 1993) Because of the habit, people will behave in the same way rather than choosing an alternative This might trouble the RUM theory in that 17 people give a rational decision on choosing an alternative with the highest utility in the choice set (Train, 1986) In this way, modeling individual choice in transport planning, which is based on intention, is challenged (Gärling and Axhausen, 2003) Gärling et al (2001) addressed the development of the habitual choice, shown in Figure 2.1 That is, a preference-based choice is firstly made with deliberation The positive outcomes will encourage maintaining choosing the choice for next times After that, the choice will become a script-based choice with less deliberation The memory retrieval of script would be used instead for the new habit Figure 2.1 The process of script-based choice (Gärling et al., 2001) Fujii et al (2001) found that when the habit is broken, individual choices will be deliberate Individuals will be in perceptions on the other alternatives such as PT given a force for deliberating This work could be done by asking for the individual concern on their choice in an experiment (Garvill et al., 2003) or by building a new habit to break the old one by free initial experiences (i.e., an example of a case of bus use) (Fujii and Kitamura, 2003) The RUM is then able to apply properly In addition, Gärling and Axhausen (2003) suppose that indicators of habit should be included in models of individual choice at the disaggregate level For travel behaviors such mode choice, an example of the indicator would be annual vehicle miles and PT trips in last weeks Another example is the usage of the current revealed behavior in stated preference surveys 18 2.4 Barriers and Motivations of Sustainable Travel Behavior The review on the barriers and motivations of sustainable travel behavior is restricted to the switch from private vehicles to PT, a sustainable mode of transport Private vehicles are convenient, reliable, secure, and able to access to more destinations compared to PT As a general trend, people desire to own a private vehicle for their demand (Hiscock et al., 2002) Steg (2005) indicated that private vehicles have their symbolic and affective values Paulley et al (2006) found the negative impact of car ownership on the demand for PT Moreover, the habitual choice is seen as one of the main reasons for unsuccessful sustainable mobility project (Møller, 2002) The motivation for a modal shift has been argued based on many aspects, including PT service quality, individual perceptions, and contexts (Mugion et al., 2018; Redman et al., 2013) Among them, the service quality is mostly mentioned Beirão and Sarsfield Cabral (2007) suppose that the service levels required by commuters are key to increase PT usage Paulley et al (2006) also show the important role of the service quality and fares Besides investing in infrastructure, these can be used as “soft” measures to encourage voluntary modal shifts (Cairns et al 2008) PT can be seen as a product that requires marketing strategies for commercialization In addition, the awareness on negative environmental impacts of car usage has been supposed to be significant on changing travel behavior, but Anable (2005) found that its role is not sufficient 2.5 Summary Policymaking has focused on investing infrastructure and developing services Reviews on the local contexts and the PT development show that the investment itself might not be always successful From that, the role of travel behavior analysis in transport planning, the problem of travel habitual choice, and barriers and motivations are considered The previous studies show that how successful the PT system depends on individuals’ response to the system and on the break made in their habit Analyzing the complex travel behavior is necessary for the travel demand management To boost behavioral changes (i.e., switch to use PT), there are many barriers and motivations that have been considered In HCMC, these issues have not been stressed heavily in transport planning as well as in policy making The literature review has been served as a base to the current research work for seeking solutions for encouraging PT in the city In addition, detailed literature reviews relating to specific analyses would be made for each of the chapters 4, 5, 6, and 19 Data Collection This dissertation uses three datasets A dataset of private vehicle usage was derived from a project The two other datasets of preferences on PT usage were collected by two questionnaire surveys in December 2016 and June 2017, respectively This chapter aims to clarify why and how the datasets were collected The data usages would be detailed in each analysis in chapters 4, 5, 6, and 3.1 A Dataset of Vehicle Type Choice and Usage Because of the first purpose of the dissertation on understanding how people choose and use their own vehicle, a dataset of individual information on who use private vehicles as their main mode of transportation in daily life is needed The dataset was taken from a project promoting PT usage through Park-and-Bus Drive and Transportation Eco point systems in 2014 The project is in collaboration with private commercial facilities and is funded by the Nikken Sekkei Research Institute, Japan In the project, a data on 2066 individuals, living in HCMC, was obtained by face-to-face and mail interviews The respondents were selected randomly The distributed questionnaire contained four parts In the first part, respondents were asked about their mode choice and the characteristics of their private vehicles and parking, if they were using private vehicles (i.e., a motorcycle or car) This included information on the brand, age of the vehicle, odometer reading, and technological details, such as engine type, volume, fuel type, and emission control technology, as well as their habits when starting the engine, parking place, parking fee, and a number of passengers In the second part, respondents were asked to state their opinions about the Park-and-Bus Drive system, and relevant problems, using four-point scales ranging from positive to negative In the third part, the PT eco point system was explained to respondents Using the system, they can purchase a monthly shopping ticket and use the parking lot at the shopping center for free Then, they take the bus and receive an award of eco-points, which can be exchanged as a shopping discount at the shopping center Next, they were required to indicate whether they agreed to purchasing a shopping ticket, how much they were willing to pay, and the acceptable return rate of eco points In the fourth part, the questions focused on the characteristics of respondents These included gender, age, educational background, monthly income, monthly transportation expenditure, occupation, number of family members, distance from home to workplace, and home location 20