Title: Sensitivity analysis of a risk classification model for food price volatility

Authors: Rueben Laryea; Kenneth Carling; Catia Cialani; Roger G. Nyberg

Addresses: School of Technology and Business Studies, Dalarna University, Röda vägen 3, 781 70 Borlänge, Sweden ' School of Technology and Business Studies, Dalarna University, Röda vägen 3, 781 70 Borlänge, Sweden ' School of Technology and Business Studies, Dalarna University, Röda vägen 3, 781 70 Borlänge, Sweden ' School of Technology and Business Studies, Dalarna University, Röda vägen 3, 781 70 Borlänge, Sweden

Abstract: A sensitivity analysis to vary the weights of an accurate predictive classification model to produce a mixed model for ranking countries on the risk of food price volatility is carried out in this paper. The classification model is a marginal utility function consisting of multiple criteria. The aim of the sensitivity analysis is to derive a mixed model to be used in ranking of country alternatives to aid in policy formulation. Since in real-life situations the data that goes into decision making could be subjected to possibilities of alterations over time, it is essential to aid decision makers to vary the weights of the criteria using both subjective and objective information to introduce imprecision and to generate relative values of the criteria with a scale to form a mixed model. The mixed model can be used to rank future relative alternative value data sets for policy formulation.

Keywords: risk; sensitivity analysis; multiple criteria; weights; decision maker; classification model; imprecision; uncertainty; data; price volatility.

DOI: 10.1504/IJRAM.2018.095807

International Journal of Risk Assessment and Management, 2018 Vol.21 No.4, pp.374 - 382

Received: 12 Jul 2017
Accepted: 11 Jun 2018
Published online: 22 Oct 2018 *

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