Publication:
Enterprise architecture adoption model among public sector organizations

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Date
2021-03
Authors
Nor Azizah Binti Ahmad, Dr.
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Abstract
Enterprise architecture (EA) offers a holistic view on the effective integration of business, data, application, and technology in organizations as it enables communication between business and technical people through a mutually understandable language for devising coherent strategies, decision-making and information technology/information system desirable solutions in the organization. Despite these benefits, EA is still not widely embraced and its adoption rate in public sector is low. Hence, this study aims to identify the technological, organizational and environmental factors influencing EA adoption in Malaysia’s public sector organizations and then develop an EA adoption model for the Malaysian context. This study also determines whether EA adoption is moderated by organization type (Federal and State). The conceptual model developed in this study includes two technological factors, seven organizational factors and three environmental factors. Data were collected from five types of public sector organizations and involving 255 responses which were analyzed using partial least squares structural equation modelling. Findings of this study validated that five organizational factors (clear communication, normative pressure, expected benefit, good governance, organization size) and two environmental factors (coercive pressure and mimetic pressure) significantly influence EA adoption intention. However, both technological factors (sufficient ICT infrastructure and EA complexity) had insignificant influence on EA adoption intention. Based on the Importance Performance Map Analysis, the most critical factors of EA adoption intention are expected benefit (70.23%), communication (70.05%), good governance (68.3%), normative pressure (63.92%) and mimetic pressure (62.19%). The predictive accuracy and relevancy of the EA adoption model was 66.5% and 57.5% respectively. Further to that, this research confirmed the relationship between good governance and EA adoption was stronger for the local authority whereas the relationship between expected benefit and EA adoption was stronger for Federal public sector. Moreover, the multigroup analysis revealed that organizational factors (clear communication and expected benefit) and environmental factors (coercive pressure and mimetic pressure) were significant factors of EA adoption intention for Federal public sector. Meanwhile organizational factors (clear communication and good governance) and environmental factor (coercive pressure) were significant factors of EA adoption intention for State public sector. The predictive accuracy and relevancy for the EA adoption model for Federal public sector were 74.7% and 65.2% respectively while for State public sector, the predictive accuracy and relevancy of its EA adoption model were 65.0% and 54.5% respectively. These findings contributed significantly to the development of a clear guideline of factors that need to be considered for EA adoption by Federal and State public sector organizations. Overall, this research contributes to the body of knowledge and practices of EA and IS/IT adoption in the context of public sector in Malaysia.
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