Abstract: The typical structure of the healthcare sector involves (specialist) intertwined practices co-occurring in formal or informal networks. These practices must answer to the concerns and needs of all related stakeholders. Multimorbidity and the need to share knowledge for scientific development are among the driving factors for collaboration in healthcare. To establish and keep up a permanent collaborative link, it takes effort and understanding of the network characteristics that must be governed. It is not hard to find practices of Network Governance (NG) in a variety of industries. Still, there is a lack of insight in this subject, including knowledge on how to establish and maintain an effective healthcare network. Consequently, this study's research question is: How is network governance organized in the healthcare sector? A systematic literature study was performed to select 80 NG articles. Based on these publications the characteristics of NG are made explicit. The findings demonstrate that combinations of governance style (relational versus contractual governance) and governance structure (lead versus shared governance) lead to different network dynamics. Furthermore, the results show that in order to comprehend how networks in the healthcare sector emerge and can be regulated, it is vital to understand the current network type. Additionally, it informs us of the governing factors. Zie https://www.hbo-kennisbank.nl/details/sharekit_han:oai:surfsharekit.nl:e4f8fa3a-4af8-42ef-b2dd-c86d77b4cec6
MULTIFILE
IT-based networking trends such as the rise of social media, crowd sourcing, open innovation, and cloud computing enable a profoundly different way of working and collaborating that challenges significantly traditional approaches of companies towards governance, i.e. the mechanisms a company employs to achieving business results and safeguarding information. Standard practices developed with a hierarchical model of the company in mind, are inadequate for providing sufficient correlation between governance mechanisms deployed and results achieved. Popular literature on the subject states that dealing effectively with such new technologies in a business environment requires relinquishing control and subverting to trust. This paper makes the case that deploying successfully new IT-based networking tools rather involves shifting one’s trust from a well-established and well-known governance system based on hierarchy and control towards another governance system, termed in the literature as network governance. This paper assesses when network governance is the better suited governance system. The presented theoretical model helps to understand how companies should use arising new technologies and which tasks are suited for network-driven IT-applications. Furthermore, the model enables to understand how network governance works to achieve business results and to safeguard information exchanges.
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There are three volumes in this body of work. In volume one, we lay the foundation for a general theory of organizing. We propose that organizing is a continuous process of ongoing mutual or reciprocal influence between objects (e.g., human actors) in a field, whereby a field is infinite and connects all the objects in it much like electromagnetic fields influence atomic and molecular charged objects or gravity fields influence inanimate objects with mass such as planets and stars. We use field theory to build what we now call the Network Field Model. In this model, human actors are modeled as pointlike objects in the field. Influence between and investments in these point-like human objects are explained as energy exchanges (potential and kinetic) which can be described in terms of three different types of capital: financial (assets), human capital (the individual) and social (two or more humans in a network). This model is predicated on a field theoretical understanding about the world we live in. We use historical and contemporaneous examples of human activity and describe them in terms of the model. In volume two, we demonstrate how to apply the model. In volume 3, we use experimental data to prove the reliability of the model. These three volumes will persistently challenge the reader’s understanding of time, position and what it means to be part of an infinite field. http://dx.doi.org/10.5772/intechopen.99709
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