TY - JOUR
T1 - Quantitative, value-driven risk analysis of e-services
AU - Ionita, Dan
AU - Wieringa, Roel
AU - Gordijn, Jaap
AU - Yesuf, Ahmed Seid
PY - 2019/9
Y1 - 2019/9
N2 - Modern e-services are provided by networks of collaborating businesses. However, collaborators, and even customers, don’t always behave as expected or agreed upon, and fraudsters attempt unfair exploitation, legally or illegally. Profitability assessments of e-services should therefore look beyond revenue streams and also consider threats to the financial sustainability of the service offering. More importantly, any such analysis should consider the business network in which the e-service is embedded. The e3 value method is an established modeling and analysis method that allows enterprises to estimate the net value flows of a networked e-business. Recently, the method and its ontology have been extended to cover aspects related to risk, e.g., fraud. In this paper, we introduce four new software-enabled risk and sensitivity analyses, which build upon this extension. The techniques are quantitative and therefore support making motivated risk mitigation decisions. We illustrate them in the context of three realistic case studies.
AB - Modern e-services are provided by networks of collaborating businesses. However, collaborators, and even customers, don’t always behave as expected or agreed upon, and fraudsters attempt unfair exploitation, legally or illegally. Profitability assessments of e-services should therefore look beyond revenue streams and also consider threats to the financial sustainability of the service offering. More importantly, any such analysis should consider the business network in which the e-service is embedded. The e3 value method is an established modeling and analysis method that allows enterprises to estimate the net value flows of a networked e-business. Recently, the method and its ontology have been extended to cover aspects related to risk, e.g., fraud. In this paper, we introduce four new software-enabled risk and sensitivity analyses, which build upon this extension. The techniques are quantitative and therefore support making motivated risk mitigation decisions. We illustrate them in the context of three realistic case studies.
KW - E-services
KW - Fraud
KW - Profitability estimation
KW - Risk analysis
KW - Value modelling
UR - http://www.scopus.com/inward/record.url?scp=85075761980&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85075761980&partnerID=8YFLogxK
U2 - 10.2308/isys-52150
DO - 10.2308/isys-52150
M3 - Article
AN - SCOPUS:85075761980
SN - 0888-7985
VL - 33
SP - 45
EP - 60
JO - Journal of Information Systems
JF - Journal of Information Systems
IS - 3
ER -