TY - JOUR
T1 - An approach for reconciling different perspectives and stakeholder views on risk ranking
AU - Goerlandt, Floris
AU - Reniers, Genserik
PY - 2017
Y1 - 2017
N2 - Risk ranking is a widely used technique for selecting and prioritizing multiple risks facing an organization or decision maker. In industrial practice and in academic work, risk ranking methods are commonly based an implicit risk conceptualization, adopting a particular foundational perspective and accounting for selected factors. Nevertheless, different stakeholders may adhere to various risk conceptualizations, applying different foundational perspectives and accounting for different factors in the ranking process. Identifying a gap in the literature to coherently consider these different foundations, this paper presents an approach for reconciling different foundational perspectives and stakeholder views, accounting for uncertainties about these. The approach is presented based on three foundational perspectives (the expected value, uncertainty and moral perspective), and developed as a Bayesian Network – Influence Diagram. The main use of the model is to make possible controversies in risk prioritization explicit, facilitating stakeholder deliberation. The model can easily be extended with new perspectives on risk ranking, or adapted based on additional knowledge about other aspects, e.g. relating to risk perception. The graphical representation allows insights into the contribution of various aspects, facilitating the selection of appropriate risk management actions. The developed model is applied to an example, suggesting that the envisaged benefits of the proposed approach are plausible. It is concluded that the novel approach has a clear potential for reconciling different foundational perspectives and stakeholder views on risk ranking. Nevertheless, it is stressed that the conceptual contribution made in this paper should be more elaborately tested in practical settings, substantiating the findings further.
AB - Risk ranking is a widely used technique for selecting and prioritizing multiple risks facing an organization or decision maker. In industrial practice and in academic work, risk ranking methods are commonly based an implicit risk conceptualization, adopting a particular foundational perspective and accounting for selected factors. Nevertheless, different stakeholders may adhere to various risk conceptualizations, applying different foundational perspectives and accounting for different factors in the ranking process. Identifying a gap in the literature to coherently consider these different foundations, this paper presents an approach for reconciling different foundational perspectives and stakeholder views, accounting for uncertainties about these. The approach is presented based on three foundational perspectives (the expected value, uncertainty and moral perspective), and developed as a Bayesian Network – Influence Diagram. The main use of the model is to make possible controversies in risk prioritization explicit, facilitating stakeholder deliberation. The model can easily be extended with new perspectives on risk ranking, or adapted based on additional knowledge about other aspects, e.g. relating to risk perception. The graphical representation allows insights into the contribution of various aspects, facilitating the selection of appropriate risk management actions. The developed model is applied to an example, suggesting that the envisaged benefits of the proposed approach are plausible. It is concluded that the novel approach has a clear potential for reconciling different foundational perspectives and stakeholder views on risk ranking. Nevertheless, it is stressed that the conceptual contribution made in this paper should be more elaborately tested in practical settings, substantiating the findings further.
KW - Expected value
KW - Foundational issues
KW - Moral considerations
KW - Risk ranking
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85015799699&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2017.02.129
DO - 10.1016/j.jclepro.2017.02.129
M3 - Article
AN - SCOPUS:85015799699
SN - 0959-6526
VL - 149
SP - 1219
EP - 1232
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
ER -