This dissertation argues that the core of building smart cities is through the procurement and implementation of smart city technologies (SCTs) by either individual (i.e., smart city) or collaborative endeavors (i.e., smart governance). Given that urbanization problems (e.g., air pollution) usually spill over city boundaries, building smart cities as silos may not solve these problems. Therefore, utilizing smart governance in SCT procurement and implementation should be a better approach. Considering the potential benefits of smart governance, this dissertation addresses three overarching questions: (1) What is a smart city? (2) What is smart governance? and (3) Why do some cities choose to participate in smart governance while others do not? By developing a typology of smart governance, this dissertation categorizes three levels of smart governance based on cities' participation in cooperative procurement and implementation of SCTs. Data collected from the 2019 Smart Governance Survey confirm that the level of smart governance does vary among Texas cities. Applying transaction costs and institutional collective action (ICA) frameworks, the dissertation finds that public managers' perceptions on transaction costs and joint gains as well as cities' extant ICA mechanisms affect cities' participation in smart governance.

This research builds on social exchange theory and self-determination theory to better understand the relationships between employee engagement, demographic and personal attributes, and public service motivation (PSM). It hypothesizes that employee engagement and demographic and personal characteristics (education, income, gender, and parents working in civil service) will directly affect PSM. I also hypothesize that education, income, and gender will have an indirect effect and moderate the relationship between employee engagement and PSM. This dissertation uses a quantitative approach to investigate the hypotheses introduced with the conceptual model. This research uses structural equation modeling as a data analysis technique. Based on 704 valid questionnaires distributed to Saudi public employees in Riyadh, Jeddah, Dammam, and Assir, the analysis shows that a higher level of employee engagement will lead to a higher level of public service motivation. It also reveals that a higher level of education will lead to a higher level of PSM.; the hypothesis that income positively affects PSM is not supported. Thus, this study finds that there is no significant relationship between income and PSM. Being female is found to be negatively associated with PSM. Therefore, the hypothesis that females are lower PSM than males is supported. Parents of public …