Description
Despite this growing adoption of enterprise architecture (EA), there has been little academic research that provides compelling empirical evidence of the impact of EA on organizational performance. We argue that the lack of strong empirical evidence is due to the complexity of EA configurations and to the limitations of the traditional correlation-based methods used for uncovering the complex causal relationships. This research intends to examine how EA elements are combined with organizational and environmental elements to produce high or low organizational performance. We identify four EA design factors including centralization, modularity, standardization, and open platforms. Then, we analyze empirical field data, using fuzzy-set qualitative comparative analysis (fsQCA), an emerging set-theoretic configurational methodology. We seek to explain how the EA design factors play different roles in the multiple equifinal configurations to achieve high organizational performance. We present our preliminary result and discuss its implications for EA design.
Recommended Citation
LEE, GWANHOO; Lee, Zoonky; and Park, YoungKi, "CONFIGURATIONAL APPROACH TO UNCOVERING THE EFFECT OF ENTERPRISE ARCHITECTURE DESIGN ON ORGANIZATIONAL PERFORMANCE" (2015). AMCIS 2015 Proceedings. 2.
https://aisel.aisnet.org/amcis2015/EntSys/GeneralPresentations/2
CONFIGURATIONAL APPROACH TO UNCOVERING THE EFFECT OF ENTERPRISE ARCHITECTURE DESIGN ON ORGANIZATIONAL PERFORMANCE
Despite this growing adoption of enterprise architecture (EA), there has been little academic research that provides compelling empirical evidence of the impact of EA on organizational performance. We argue that the lack of strong empirical evidence is due to the complexity of EA configurations and to the limitations of the traditional correlation-based methods used for uncovering the complex causal relationships. This research intends to examine how EA elements are combined with organizational and environmental elements to produce high or low organizational performance. We identify four EA design factors including centralization, modularity, standardization, and open platforms. Then, we analyze empirical field data, using fuzzy-set qualitative comparative analysis (fsQCA), an emerging set-theoretic configurational methodology. We seek to explain how the EA design factors play different roles in the multiple equifinal configurations to achieve high organizational performance. We present our preliminary result and discuss its implications for EA design.