Open data policies, as well as e-government policies, are usually associated with many promises that range from transparency to efficiency gains for the public administration. However, how...Show moreOpen data policies, as well as e-government policies, are usually associated with many promises that range from transparency to efficiency gains for the public administration. However, how effective these policies are in meeting the (high) expectations of practitioners, politicians, and citizens is a topic of debate. In this thesis we focus on the Italian case, in which transparency is often evoked as a solution to many societal problems, to investigate the relationship between transparency and institutional and organizational features of local governments. The thesis also introduces the concept of open data mediated transparency as a way to complement the concept of open government. Open data mediated transparency aims at capturing how open data sharing through the Italian National Open data portal translates into transparency. To measure this concept, this study uses the four dimensions of governmental transparency developed by the Pew Institute and adapts them to the Italian case. The following question is central in this thesis: what are the institutional and organizational factors that influence open data mediated transparency in Italian local governments? Objectives: This thesis has three research objectives. First, the thesis aims to assess the implementation of open data initiatives in Italian municipalities through the attainment of transparency goals. Second, the study wishes to improve our understanding of the open data phenomenon in the context of Italian local administration. The final goal of this thesis is to investigate institutional and organizational factors that might influence how transparent Italian local administrations are and, therefore, how open data policies are implemented in Italy. Methods: The study is based on a quantitative deductive approach. A Poisson regression is used to test the different hypotheses. Key findings: The results of the analysis show that there is no support for population size, level of education of the personnel of the public administration, organizational resistance, and political affiliation as factors that affects open data mediated transparency. Overall, open data mediated transparency varies greatly among municipalities with few local administrations sharing transparent and relevant datasets. The results are discussed and lead to suggestions for future research and policy recommendations.Show less
