This dissertation examines electric vehicle acquisition decision-making in public and private fleets in the United States, with an emphasis on fleets operating in California. Large numbers of vehicles are acquired for fleet use each year, however, fleet decision-making processes are largely unknown. The high average mileage and emissions of these vehicles makes the replacement of fleet vehicles with electric vehicles an important step in reaching zero-emission vehicle, air quality, and greenhouse gas emission reduction goals. Additionally, California’s Advanced Clean Cars, Advanced Clean Fleets, and Advanced Clean Trucks policies have solidified the state’s commitment to electrifying the on-road vehicle fleet. To support these policies, which are subsequently being adopted in other states and nations, this dissertation seeks to understand fleet decision-maker’s perceptions of electric vehicles.To understand fleets’ willingness and ability to adopt electric vehicles, this dissertation utilizes data collected from interviews with decision-makers in fleets. These interviews sought to understand fleet decision-making, decision-maker’s perceptions of electric vehicles, what is preventing them from adopting electric vehicles, and how these issues can be overcome. These interviews provide insights into the unique perspectives of individuals involved in the decision-making process. In Chapter 2 of this dissertation electric vehicle adoption in fleets operating light-duty vehicles is explored. This chapter compares the acquisition processes for conventional vehicles and plug-in electric vehicles (PEVs) to provide a complete picture of the ways in which current acquisition processes allow or dissuade light-duty PEV acquisitions. Self-Determination Theory (SDT) is used to provide a deeper understanding of the underlying motivations for conventional vehicle and PEV acquisition decisions. Understanding these motivations provides a clearer view of what influences light-duty fleet acquisitions and what aspects of fleet acquisitions stakeholders should seek to influence to increase fleet electrification. Chapter 3 of the dissertation examines barriers to electric vehicle adoption in fleets operating heavy-duty trucks. Barriers to heavy-duty electric truck adoption are classified into six categories: technological, economic, social, socio-technological, techno-economic, and socio-economic. The research is intended to inform stakeholders about issues which need to be addressed in the pursuit of 100% electric heavy-duty trucks and the need to address social, economic, and technological issues rather than taking one-dimensional approaches to overcoming barriers. Chapter 4 examines which actors and decision-making structures are involved in decision-making in fleets with medium- and heavy-duty trucks. This chapter is guided by a hybrid of concepts from organizational structure and Social Network Analysis. These theories are used to characterize fleets according to their internal decision-making structures and external social network heterogeneity, exploring whether these structures impact decision-making in fleets with medium- and heavy-duty trucks. Differences in internal structure, external network heterogeneity, and actor involvement between battery electric and conventional truck acquisition decisions are explored. Understanding these organizational attributes can provide insights into which fleet types will require greater levels of support to transition to electric trucks while identifying actors involved in these decisions can identify other groups that will play a role in supporting truck electrification. The chapters presented in this dissertation present key findings which underlie fleet decision-making around electric vehicle adoption. We find that barriers to electric vehicle adoption are discussed as such because of their differences from incumbent fossil fuel vehicles. While fleets often expect electric vehicle technologies to advance to a point where they reach operational parity with fossil fuels, many perceived barriers can be partially or fully addressed through education or operational changes. Fleet managers are found to be driven by their desire to try new technologies, lessen environmental impact, improve their public image, and use grants.