Efficient public transportation provides economic and social opportunities that increase accessibility to markets and employment as well as providing investment benefits. Key challenges to the U.S. public transportation industry include developing modes and increasing the availability of public transportation in a manner that meets the needs of individual users in a cost effective manner. A problem facing public transportation officials is the need to understand the factors that influence consumer decision-making and consumer attitudes toward public transportation. Feedback regarding experiences as well as expectations from commuters provides information for developing and improving public transportation. Thus, decision-making factors of end-users are keys to improving supply, growth, and understanding utilization of public transportation. Public transportation officials seek to improve the public transportation experience for commuters by increasing modes and benefits of the systems. The decision-making factors of the end-users require identification and examination in order to provide a high quality and efficient experience for commuters. The research questions of interest in the current dissertation are: (1) What are the decision-making factors affecting commuters’ attitudes toward public transportation? and (2) How do the end-user decision-making factors affect the supply of public transportation? The purpose of this research is to extend the current body of knowledge about decision-making factors by developing and testing a new theoretical model to measure the attitudes of public transportation end-users. This study has its theoretical foundation in the theory of planned behavior, theory of reasoned action, and rational choice theory. To understand how public transportation is affected by decision-making factors, it is necessary to analyze the relationships among the decision factors and attitudes. The findings of this study contribute by building theory and having implications for practice. This study employs a mixed methodology of qualitative and quantitative research. More specifically, the development of a framework and testing of that framework via collection of data using a survey instrument, semi-structured interviews, and data scraping of customer comments underpin the methodology employed in this study. To this end, Essay 1 develops a conceptual framework of decision-making factors that affect the supply of public transportation based on the extant literature. The integrated framework developed is operationalized using a survey to test a model that depicts the framework within the context to which the study was situated. The results of the structural model using PLS provide insights for the development of public transportation. Essay 2 involves two phases in the methodology. First, the study develops a causal loop that depicts the operationalized conceptual framework from Essay 1. Second, discussion panels were conducted to confirm the system dynamic causal loop visualization that was developed to fit the model. Finally, Essay 3 examines the conceptual framework developed and tested in the prior essays by analyzing electronic word of mouth (eWOM) of online comments. The third essay examines eWOM of current public transportation users that is available online. This eWOM data was examined using text mining and the resulting quantitative output was compared to the operationalized theoretical framework from the prior works. The results also illustrate the functionality of text analytics for confirmatory model assessment.

An in-depth-analysis was carried out on short, medium and long commuters using the National Household Travel Survey (NHTS) of 2001 and American Community Survey (ACS) of 2000 to determine the role of individual,household, trip and area related characteristics on commute length. The individuals with commute time less than or equal to 15 min were considered as short commuters and individuals with commute time greater than 15 min but less than 60 min were considered as medium commuters and the individuals with commute time 60 min or more were considered as long commuters. The commute time is considered as a link joining the residence and workplace locations. The availability of the desired mode used is considered as flexibility in moving the location of these points in the area. As the jobs get dispersed the lower income people face more and more transportation problems in linking the residence and workplace. There is a potential threat in their social, physical and economic isolation in the society. The individual, household, and area related characteristics are assumed to influence both the commute time and location of these points. The descriptive analysis using NHTS 2001 and ACS 2000 revealed that the characteristics of short and long commuters are different in nature. A commuter type choice model and commute length measurement models were used to estimate the influence of socio-demographic characteristics on the residential and workplace separation. Multinomial Logit Model (MNL) methodology was adopted to develop the commuter type choice model and Structural Equations Model methodology (SEM) was adopted with commute time and commute distance as endogenous variables to estimate the commute length on a continuous scale. The models confirmed the importance of demographic variables in explaining commuter length.

Flourishing economy, rapid industrialization and increasing trend of motorization have been shaping societies in the developing countries like India in an unprecedented manner.Infrastructure backlog amid such rapid growth in all imaginable directions has heavily exacerbated the urban transport crisis in these countries by alarming increase in vehicular travel demand, road fatalities, and environmental pollution. To address urban transport challenges, the necessary development and implementation of effective transport planning and policies have generally lagged in the developing countries compared to that seen in the developed countries due to several constraints including resource constraints, knowledge constraints, institutional constraints and so on. However, in the recent past, with the rapid development seen by several emerging economies and the explosive growth in transportation infrastructure investment, there is a growing interest in the development and implementati on of advanced travel demand modeling systems in developing countries. But lack of necessary research and exploration of travel behavior in a developing country context has left very limited knowledge for us to understand the extent of applicability of these advanced theories and methodologies in a different socio-cultural perspective. Assessing the practical relevance of the subject, this research adopts a comprehensive approach to explore the activity engagement pattern and time use behavior from a developing country standpoint. To accomplish this goal, a series of empirical and analytical studies are performed on a household travel survey data set available from Thane Metropolitan Area in India. The study also introduces new concepts and facilitates enhancements of existing modeling methodologies in the field of travel behavior and time use research. The study results provide very insightful findings and plausible interpretations consistent with a developing country perspective reco gnizing a wide spectrum of differences and similarities in activity patterns and time use behavior between a developed and a developing country. Specified model structures are meaningfully able to incorporate various socio-cultural and institutional constraints and reflected sensitivity to the behavioral variability between the contexts suggesting that advanced analytical techniques may be satisfactorily applied on the data set from developing countries which may contribute important ingredients in the development of advanced activity-based model system in the countries like India.