In addition to understanding the context-specific variables that make the system complex [51], it is equally important to succeed in introducing novel concepts and forms that support the multi-actor collaboration.
The actor-oriented architecture is composed of three elements: (1) actors who have the capabilities and values to self-organize; (2) commons where the actors accumulate and share resources; and (3) protocols, processes, and infrastructures that enable multi-actor collaboration (see Table 2).
This holistic perspective on multi-actor collaboration for innovation recognises the key importance of the exchange of different types of knowledge of different actors in systems, related in this context to the multiple changes in public health systems that are needed for innovation.
The context of uncertainty interacts with classical drivers of actor collaboration in policy processes.
Klein Woolthuis et al. developed a matrix that distinguishes actors and conditions within an innovation system that influence actor collaboration for innovation [ 28].
In The Netherlands, examples of attempts to create such multi-actor networks (knowledge platforms) include academic collaborative centres, which are structural collaborations between universities and municipal health services [ 5, 35, 37] with dedicated systemic intermediation to optimise interactions.
For these multi-problem, multi-actor systems, we have not yet developed clear value chains, much less business models.
A multi-layer, multi-actor structured world forces the PMS into dialogue-based development.
The end result of the model is the service cost per actor for a multi-actor, multi-service deployment.
Concerning process quality a multi-actor perspective is preferable in most cases, because it relates to interactions between actors.
The design follows an understanding of governance as a multi-level and multi-actor process.
