Risk assessment of E-Commerce projects using evidential reasoning

R.H. Khokhar, David Bell, J.W. Guan, Qing Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)


The purpose of this study is to develop a decision making system to evaluate the risks in E-Commerce (EC) projects. Competitive software businesses have the critical task of assessing the risk in the software system development life cycle. This can be conducted on the basis of conventional probabilities, but limited appropriate information is available and so a complete set of probabilities is not available. In such problems, where the analysis is highly subjective and related to vague, incomplete, uncertain or inexact information, the Dempster-Shafer (DS) theory of evidence offers a potential advantage. We use a direct way of reasoning in a single step (i.e., extended DS theory) to develop a decision making system to evaluate the risk in EC projects. This consists of five stages 1) establishing knowledge base and setting rule strengths, 2) collecting evidence and data, 3) determining evidence and rule strength to a mass distribution for each rule; i.e., the first half of a single step reasoning process, 4) combining prior mass and different rules; i.e., the second half of the single step reasoning process, 5) finally, evaluating the belief interval for the best support decision of EC project. We test the system by using potential risk factors associated with EC development and the results indicate that the system is promising way of assisting an EC project manager in identifying potential risk factors and the corresponding project risks.
Original languageEnglish
Title of host publicationFuzzy Systems and Knowledge Discovery: FSKD 2006
Number of pages10
Publication statusPublished - 2006

Publication series

NameLecture Notes in Computer Science
ISSN (Electronic)1611-3349


Dive into the research topics of 'Risk assessment of E-Commerce projects using evidential reasoning'. Together they form a unique fingerprint.

Cite this