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Probabilistic assessment of financial risk in e-business associations

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Open access
Authors
Hussain, Omar
Dillon, Tharam S.
Hussain, Farookh Khadeer
Chang, Elizabeth
Date
2010
Type
Journal Article

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Hussain, Omar and Dillon, Tharam S. and Hussain, Farookh Khadeer and Chang, Elizabeth. 2011. Probabilistic assessment of financial risk in e-business associations. Simulation Modelling Practice and Theory. 19 (2): pp. 704-717.
Source Title
Simulation Modelling Practice and Theory
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Digital Ecosystems and Business Intelligence Institute (DEBII)
Remarks

NOTICE: This is the author’s version of a work that was accepted for publication in Simulation Modelling Practice and Theory. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Simulation Modelling Practice and Theory [19, 2, 2010] DOI 10.1016/j.simpat.2010.10.007

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Abstract

Business activities are a result of carefully formed associations between different users in order to achieve certain pre-decided outcomes. Decision-making in such associations is an important step and transactional risk analysis is one of the integral processes that facilitates this step. This paper presents an approach that determines the negative consequences (termed as financial risk) of forming e-business associations. Unlike other approaches, our model captures the different types of events and their uncertainties to determine the financial risk by using the convolution operator and expressing it as a probabilistic measure rather than as a crisp financial value. Such representation makes sense as the financial risk may be determined at a point of time in future where nothing is certain. Depending upon the complexity of the problem, we explain the different ways of using the convolution operator to determine the financial risk. The simulation result shows a better representation and understanding of the financial risk that will provide important inputs to the transactional risk analysis and the decision-making process.