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dc.contributor.authorHussain, Omar
dc.contributor.authorChang, Elizabeth
dc.contributor.authorHussain, Farookh
dc.contributor.authorDillon, Tharam S.
dc.date.accessioned2017-01-30T12:09:51Z
dc.date.available2017-01-30T12:09:51Z
dc.date.created2008-11-12T23:32:53Z
dc.date.issued2007
dc.identifier.citationHussain, Omar Khadeer and Chang, Elizabeth and Hussain, Farookh Khadeer and Dillon, Tharam S.. 2007. A methodology to quantify failure for risk-based decision support system in digital business ecosystems. Data and Knowledge Engineering 63: 597-621.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/18767
dc.identifier.doi10.1016/j.datak.2007.03.014
dc.description.abstract

In digital business ecosystem architecture it is rational for the trusting agent to analyse the possible risk according to its demand before interacting with a probable trusted agent. Doing so would assist the trusting agent in its decision process and would also give the trusting agent a hint of the direction in which the interaction might head. The possible risk in an interaction is a combination of the probability of failure and the possible consequences of failure of an interaction. In this paper, we propose a methodology by which the trusting agent determines the probability of failure in interacting with a probable trusted agent. The determined probability of failure by the trusting agent is according to the specific demand of its future interaction with the probable trusted agent.

dc.publisherElsevier Science
dc.subjectTrusting agent
dc.subjectFailureLevel
dc.subjectCriteria
dc.subjectTrusted agent
dc.titleA methodology to quantify failure for risk-based decision support system in digital business ecosystems
dc.typeJournal Article
dcterms.source.volume63
dcterms.source.startPage597
dcterms.source.endPage621
dcterms.source.titleData and Knowledge Engineering
curtin.note

Hussain, Omar Khadeer and Chang, Elizabeth and Hussain, Farookh Khadeer and Dillon, Tharam S. (2007) A methodology to quantify failure for risk-based decision support system in digital business ecosystems, Data and Knowledge Engineering 63:597-621.

curtin.note

The link to the published article is: http://dx.doi.org/10.1016/j.datak.2007.03.014

curtin.note

Copyright 2007 Elsevier B.V. All rights reserved.

curtin.departmentCentre for Extended Enterprises and Business Intelligence
curtin.identifierEPR-2507
curtin.accessStatusOpen access
curtin.facultyCurtin Business School
curtin.facultySchool of Information Systems


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