Contingency factors framework for an e-government governance approach

Abstract

Governments around the world face important challenges by trying to define what could be the most efficient governance design to conduct their e-government development. To effectively implement e-government, a country requires a comprehensive governance design that needs to be dynamic and based on the contextual characteristics, so as a result, issues such as authority and accountability can be assigned properly. The goal of this research was to use structural contingency theory to elaborate an e-government governance framework that may orientate decision makers to design governance in a way that is dynamic and coherent to their contexts. Three main processes were conducted. Process one identified what may be the e-government governance contingency factors, required to describe context; process two applied a Delphi method to a Korean expert panel to study the fluctuations of the factors and their importance according to each e-government maturity stage, describing context, which by contingency theory allowed the generation of governance contingency propositions that were used to construct the research’s framework; process three conducted a case study in a top performing country, Singapore, to validate the framework’s recommendations. Overall results showed that contingency factors had a stable growth tendency according to the e-government maturity, which based on the contingency propositions is equivalent to an e-government governance design that goes from a level of centralization to a level of decentralization, running in parallel with a country´s e-government maturity. The implications may be valuable for the governance design of countries implementing e-government located at the different stages of maturity, may contribute to the e-government governance study with the proposed framework, and could be added to the governance evolution discussion by arguing that highest performance is associated with a specific e-government governance evolution pattern.