Rebooting Healthcare: Deploying Collaborative Networks to Enhance Healthcare Effectiveness
Master thesis
Permanent lenke
http://hdl.handle.net/11250/2580005Utgivelsesdato
2018Metadata
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- Master of Science [1816]
Sammendrag
The following Master Thesis investigates how Collaborative Networks may be
sustained in healthcare, by investigating their value creation and value
appropriation activities. Collaborative Networks have appeared, due to the
knowledge creation benefits these yield. In contrast to traditional forms of formal
inter-firm relations, community-based organizational designs rely on selforganizing
actors, who jointly create value. To facilitate this collaborative value
creation, the Collaborative Network organizations provide social- and technical
infrastructures. Hence, for the value creation to be sustained, these organizations
need to survive. Despite successful examples, little is still known about how
Collaborative Networks can be sustainably arranged.
This thesis is conducted as a qualitative case study, with semi-structured
interviews of several Collaborative Networks in healthcare, so-called Learning
Networks, conducting research- and Quality Improvement initiatives. The
interviews surfaced motivation and coordination as the core drivers of value
creation in the Learning Networks, which presently are sustained by external
funding sources. We find that the networks are not presently configured for
financial value appropriation. A link between value appropriation and value
creation is discovered, signaling that present value is sub-optimized. By increasing
the financial value appropriated by the network organizer, we argue how the
Learning Networks not only can ensure their sustainability, but even enhance their
value creation activities. We argue that the Learning Networks should move away
from their current scope of learning activities, to more permanent providers of care,
so-called Learning Health Systems.
Beskrivelse
Masteroppgave(MSc) in Master of Science in Business, Strategy - Handelshøyskolen BI, 2018