Distributed under Creative Commons CC-BY 4.0 Introduction Information systems in general and e-Government projects in particular, have many diverse and complex challenges that are not easy to overcome (Gil-Garcı´a & Pardo, 2005). The fact that systems are interconnected in e-Government poses a unique challenge for implementation because requirements stretch across different departments or agencies (Saha,
The paper discusses the findings of the case study of applying multiple-criteria decision-making (MCDM) method to select attributes of the Enterprise Architecture (EA) frameworks for an e-Government implementation in a developing country. The paper follows on earlier work by the same authors, which focussed on identifying critical success factors to deploy a good enterprise architecture proposed for e-Government projects in Botswana. The research continues to contribute to an e-Government service architecture, and here to explore the processes of selecting an appropriate enterprise architecture framework in the context of a developing country such as Botswana. This selection process aligns the organisational goals with the known attributes of EA Frameworks. The authors apply an MCDM tool, the Analytical Hierarchy Process (AHP) to select EA frameworks attributes from four alternatives which are; the Zachman Enterprise Architecture Framework (ZEAF), Federal Enterprise Architecture Framework (FEAF), The Open Group Architecture Framework (TOGAF) and Treasury Enterprise Architecture Framework (TEAF). These frameworks constitute the four common EA frameworks for e-Government projects. The research concludes that adopting enterprise architecture when developing e-Government helps to visualise business functions and to support ICT comprehensively. The government must select a suitable EA framework before they implement Enterprise Architecture. Also, the findings demonstrate that ZEAF attributes are the most preferred attributes. The results are also consistent with the literature review, and they establish the viability of utilising MCDM methods in EA projects to improve decision making.
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