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Service Ecosystems Supporting High Reliability Assets

Swinburne Institute of Technology, Business School, Hawthorne 3122, Victoria, Australia
Systems 2017, 5(2), 32;
Received: 4 February 2017 / Revised: 13 March 2017 / Accepted: 22 March 2017 / Published: 3 April 2017
(This article belongs to the Special Issue Service Systems)
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The owners/operators of complex assets such as production systems, military equipment and power stations aim to achieve high reliability with financial sustainability over long periods of time, and rely on a combination of internal and external socio-technical support systems to achieve this. Changes in the operational environment and technological advances may stimulate the need/opportunity for innovative reconfiguration of the assets and/or the related support systems. These assets and their support arrangements may be regarded as elements of a broader industry ecosystem. Drawing on analogies with natural ecosystems suggested in the literature, a concept of a service ecosystem is presented. Ten service system, management, engineering and design (SSMED) concepts elaborated by Spohrer and Kwan are represented in operational terms by interlinked networks of actors, of resources and of activities whose interconnections may change dynamically, combined with a business model perspective that indicates why particular configurations might make sense. Six support system case studies illustrate how effective service ecosystems are informed by multiple viewpoints including reliability assurance, business models and linkages with context-specific knowledge networks to stimulate the identification of innovative support solution architectures. View Full-Text
Keywords: systems of systems; Service-Dominant logic; business models; SSMED; multidisciplinary analysis; innovation; reliability; knowledge; service ecosystems systems of systems; Service-Dominant logic; business models; SSMED; multidisciplinary analysis; innovation; reliability; knowledge; service ecosystems

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Beckett, R. Service Ecosystems Supporting High Reliability Assets. Systems 2017, 5, 32.

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