An Advanced Stochastic Risk Assessment Approach Proposal Based on KEMIRA-M, QFD and Fine–Kinney Hybridization

Gülin Feryal Can () and Pelin Toktaş ()
Additional contact information
Gülin Feryal Can: Industrial Engineering Department, Başkent University, Bağlıca Kampüsü Fatih Sultan Mahallesi, Eskişehir Yolu 18.km 06970 Ankara, Turkey
Pelin Toktaş: Industrial Engineering Department, Başkent University, Bağlıca Kampüsü Fatih Sultan Mahallesi, Eskişehir Yolu 18.km 06970 Ankara, Turkey

International Journal of Information Technology & Decision Making (IJITDM), 2021, vol. 20, issue 01, 431-468

Abstract: In this study, an advanced stochastic risk assessment approach based on integration of advanced version of quality function deployment (AV-QFD) and Modified Kemeny Median Indicator Rank Accordance (KEMIRA-M) is proposed. It is aimed to perform a new criterion weighting procedure based on four different distributions as uniform, symmetric triangular, left asymmetric triangular, right asymmetric triangular distributions. The AV-QFD includes correlations between criteria (top roof of QFD), risk degrees (RDs) of risk types (RTs) (customer needs part of QFD), correlations between RTs and criteria sets (CSs) (in the middle of QFD) to obtain the criteria priorities. Correlations on the top roof of QFD comprises three types: correlations between criteria in the first CS, correlations between criteria in the second CS and correlations between criteria in both CSs. Additionally, Fine–Kinney method is performed in AV-QFD to compute RDs of RTs in the customer needs part. Then for each expert, the correlation-based importance degree (CBID) of each criterion is obtained to rank criteria for each CS. MATLAB code was performed to see the effect of different trial numbers and replications on risk assessment. It was observed that although uniform distribution provides the best value, the same alternative ranking was obtained for all distributions. In addition, right asymmetric triangular distribution converged to the best value rapidly in practice made in this study.

Keywords: KEMIRA-M; advanced QFD; Fine–Kinney; distribution; correlation (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219622021500036
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijitdm:v:20:y:2021:i:01:n:s0219622021500036

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219622021500036

Access Statistics for this article

International Journal of Information Technology & Decision Making (IJITDM) is currently edited by Yong Shi

More articles in International Journal of Information Technology & Decision Making (IJITDM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().