Investigating the adoption of enterprise application integration in healthcare organisations using an actor-oriented approach
This dissertation focuses on Enterprise Application Integration (EAI) adoption in healthcare organisations. EAI has emerged to support organisations overcoming their integration problems and it has been adopted by many organisations in various sectors. Despite its importance, the healthcare domain develops EAI solutions at a slower pace and it can be characterised as a laggard comparing to other sectors. The small number of EAI applications in healthcare has resulted in limited research in this area with many issues, like its adoption requiring further investigation. The normative literature analyses the factors that influence EAI adoption in healthcare (MAESTRO model) but it has not yet explored the role of actors during the adoption process. This dissertation makes a step forward and contributes to the body of knowledge as it: (a) highlights the role of healthcare actors and attitudes towards EAI adoption, (b) introduces an actor-oriented approach, (c) derives and proposes a structured method, named Individual, Group, Organisational, Human, Controllers, Acceptors, Providers, Supporters (IGOHcaps), to model how actors might be identified (structured because such a rationale is explicable and such a method is more readily usable when transferred to others), (d) identifies those actors involved in this process, by using the proposed IGOHcaps method and (e) combines the actor-oriented approach with the factors influencing EAI adoption. The author claims that such an approach is significant and novel as: (a) it extends established norms for EAI adoption, by incorporating an actor-oriented analysis and (b) the actors' differing views emerging could enable decision making bodies to produce more robust proposals for EAI adoption. The author discusses the application of this approach by using a qualitative, interpretive, multiple case study research strategy. Empirical data collected from two case organisations show that such an approach contributes towards more robust decisions for EAI adoption and indicates that it is acceptable by the organisations and the interviewees (actors), participated in this research. Despite these results cannot be generalised, they can allow others to relate their views with the ones reported in this dissertation. This dissertation introduces tests and presents a novel approach and model for EAI adoption in healthcare and contributes to the body of knowledge by extending the literature.