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An empirical analysis of the factors and measures of Enterprise Architecture Management success

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  • Matthias Lange
  • Jan Mendling
  • Jan Recker

Abstract

Enterprise Architecture Management (EAM) is discussed in academia and industry as a vehicle to guide IT implementations, alignment, compliance assessment, or technology management. Still, a lack of knowledge prevails about how EAM can be successfully used, and how positive impact can be realized from EAM. To determine these factors, we identify EAM success factors and measures through literature reviews and exploratory interviews and propose a theoretical model that explains key factors and measures of EAM success. We test our model with data collected from a cross-sectional survey of 133 EAM practitioners. The results confirm the existence of an impact of four distinct EAM success factors, ‘EAM product quality’, ‘EAM infrastructure quality’, ‘EAM service delivery quality’, and ‘EAM organizational anchoring’, and two important EAM success measures, ‘intentions to use EAM’ and ‘Organizational and Project Benefits’ in a confirmatory analysis of the model. We found the construct ‘EAM organizational anchoring’ to be a core focal concept that mediated the effect of success factors such as ‘EAM infrastructure quality’ and ‘EAM service quality’ on the success measures. We also found that ‘EAM satisfaction’ was irrelevant to determining or measuring success. We discuss implications for theory and EAM practice.

Suggested Citation

  • Matthias Lange & Jan Mendling & Jan Recker, 2016. "An empirical analysis of the factors and measures of Enterprise Architecture Management success," European Journal of Information Systems, Taylor & Francis Journals, vol. 25(5), pages 411-431, September.
  • Handle: RePEc:taf:tjisxx:v:25:y:2016:i:5:p:411-431
    DOI: 10.1057/ejis.2014.39
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    Cited by:

    1. Bokolo Anthony Jnr & Sobah Abbas Petersen, 2023. "Validation of a Developed Enterprise Architecture Framework for Digitalisation of Smart Cities: a Mixed-Mode Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 1702-1733, June.
    2. Bokolo Anthony Jnr & Sobah Abbas Petersen, 2023. "Using an extended technology acceptance model to predict enterprise architecture adoption in making cities smarter," Environment Systems and Decisions, Springer, vol. 43(1), pages 36-53, March.

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