The impact of end-user decision-making in the supply of public transportation

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.