Justifying the decisions for EAI implementations: a validated proposition of influential factors

TLDR

Enterprise integration is strategically vital for competitive advantage, yet traditional EDI and ERP solutions fall short of fully automating and supporting intra‑ and inter‑organisational processes, creating a demand that has led to the emergence of more flexible enterprise application integration (EAI). The study addresses the limited normative literature on EAI by aiming to identify influential factors for its adoption. To fill this gap, the authors propose a justification and evaluation model for EAI adoption. The model serves as a decision‑making tool for organizations considering EAI adoption.

Abstract

Enterprise integration is considered to be of great strategic significance in the support of organisations to achieve a competitive advantage. Traditional approaches to integration such as electronic data interchange (EDI) have provided a wide range of benefits but have not managed to fully automate and integrate business processes and applications. In addressing many of the limitations of EDI to piece together disparate systems, enterprise resource planning (ERP) solutions introduced an alternative approach to integration. Although ERP systems overcome significant integration problems, they have failed to adequately support intra and inter‐organisational integration. There has been a great demand by organisations to overcome integration problems and become more competitive. In this respect, enterprise application integration (EAI) has emerged to address intra and inter‐organisational integration in a more flexible and maintainable way. The normative literature remains limited regarding this emerging area and there is consequently a need for further research and contribution in identifying influential factors for EAI adoption. In addressing this relative void in the literature, this paper proposes a model for the justification and evaluation of EAI adoptions. The proposed model can be used by organisations as a tool for decision making when considering the adoption of EAI.