Factors That Influence the Adoption of Enterprise Architecture by Public Sector Organizations: An Empirical Study

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Ahmad N.A.
Drus S.M.
Kasim H.
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Institute of Electrical and Electronics Engineers Inc.
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The adoption of enterprise architecture (EA) is deemed to be low despite EA's substantial benefits to organizations, especially in the public sector, as evidenced by the scarce literature on the EA adoption stage, which focuses on the decision or intention to adopt EA. This research attempts to identify the significant factors that influence EA adoption in the public sector by using the technology-organization-environment framework and organizational theory. The conceptual model was validated using partial least squares structural equation modeling with data collected from 255 key informants from public sector organizations. Empirical results show that clear communication, coercive pressure, expected benefit, good governance, mimetic pressure, normative pressure, and organizational size have a significant influence on the adoption of EA by public sector organizations. Surprisingly, top management support, ICT infrastructure, EA complexity, organizational readiness, and external support have a nonsignificant influence on EA adoption by public sector organizations. The implications of the findings are also discussed in theoretical, contextual, and practical aspects of EA adoption in the context of public sector organizations. This model facilitates decision-makers in focusing only on the significant factors in the organizational and environmental context that influence EA adoption in Malaysian public sector organizations. Subsequently, the findings may contribute to better insights for EA initiators in their EA implementation plan and strategic planning to support EA implementation among Malaysian public sector organizations. � 2013 IEEE.
Least squares approximations; Enterprise Architecture; Environmental contexts; Malaysian public sectors; Organizational readiness; Partial least square (PLS); Public sector organization; Structural equation modeling; Technology-organization-environment frameworks; Decision making