Saturday, November 9, 2013
Thomas Salon (Washington Marriott)
*Names in bold indicate Presenter
Electronic government (e-government) has been touted as a means of promoting transparency in government. Although there is no agreement on the definition of transparency in public administration, literature has identified the openness, accuracy, comprehensiveness, and timeliness of information as the core elements of transparency. By focusing on information openness, this research defines electronic transparency (e-transparency) as the extent to which government information is voluntarily disclosed through e-government. This research considers e-transparency as policy and technology innovation and institutional change in that it is new information disclosure policy using novel technologies. Some scholars in public administration have attempted to understand the degree of e-transparency by government. However, prior studies have described the status of e-transparency in general or reported anecdotal evidence. Thus, little is known about the driving forces behind e-transparency adoption. Considering e-transparency as innovation and institutional change, this research uses policy and technology innovation adoption and institutionalization literature as a theoretical framework to develop a model of e-transparency adoption. In this model, we argue that e-transparency adoption is function of motivation, barriers, capability and institutional pressures. Specifically, the focus of this study lies on state government’s contract e-transparency as a case of e-transparency adoption by state. As contract information is as part of fiscal information, this research incorporates fiscal transparency literature, which highlights economic and political incentives as key driving forces behind government’s fiscal information disclosure. By adding institutional perspective tp economic and political rationales of fiscal transparency, this research theorizes that states’ contract e-transparency depends on economic, political, and institutional factors. This model will be empirically tested using state-level data collected from multiple sources including 2011-2012 National Association of State Procurement Officials survey data, 2012 U.S. Public Interest Research Group survey data, Pew Research State data, etc.