du.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Food Price Volatility Model for Country Risk Classification
Dalarna University, School of Technology and Business Studies, Microdata Analysis.
Dalarna University, School of Technology and Business Studies, Microdata Analysis.ORCID iD: 0000-0003-2317-9157
Dalarna University, School of Technology and Business Studies, Economics.ORCID iD: 0000-0002-9748-9572
2018 (English)In: International Journal of Risk Assessment and Management, ISSN 1466-8297, E-ISSN 1741-5241Article in journal (Refereed) Submitted
Abstract [en]

Decision makers require risk models which satisfies their preferences in decision making processes. A methodological approach to presenting a decision model that satisfies the preferences of the decision maker and aids the decision maker to classify countries into crisis groups based on the price volatility of food staple criteria is discussed in this paper. The price volatility of food staples is obtained from time series plots and a Multi-Criteria Decision Analysis method, the UTilitdditives DIScriminantes (UTADIS) classification methodological framework is applied on the price volatility data to develop a food price volatility classification model which suits the decision maker’s preferences. The methodological framework is better applied in this paper by aiding the decision maker to make informed judgements on the price volatility of food staples in predefining their risk classes. This introduces efficiency in the application of the methodological classification framework, by reducing to the barest minimum level, the misclassification errors between the decision makers preferred classification and the UTADIS method’s classification which estimates the utility function or classification model and the utility threshold or cut-off points which would classify the country alternatives into their authentic or original classes with the execution of the methodological framework just once. The resulting utility function or classification model is thus accurate enough to satisfy the preferences of the decision maker in classifying future datasets.

Place, publisher, year, edition, pages
2018.
National Category
Economics and Business
Research subject
Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-28646OAI: oai:DiVA.org:du-28646DiVA, id: diva2:1252274
Available from: 2018-10-01 Created: 2018-10-01 Last updated: 2018-10-01Bibliographically approved
In thesis
1. A data-driven decision support system for coherency of experts’ judgment in complex classification problems: The case of food security as a UN sustainable development goal
Open this publication in new window or tab >>A data-driven decision support system for coherency of experts’ judgment in complex classification problems: The case of food security as a UN sustainable development goal
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Everyday humans need to make individual or collective decisions. Often the decisions aim at achieving multiple goals (thus involving multiple criteria) and rely on the decision maker(s)’ intuition, internal data, as well as external sources of data. Faced with a complex decision problem of this kind, it is a great challenge to decisionmakers to be logically coherent over time with regard to their preferences. To aid in achieving coherency, operation researchers and decision analysts have developed formal methods to support decision makers. One such method is the UTADIS method that serves as the workhorse for this thesis. I received the request from UN officials who had to manage the sustainable development goals while addressing the issue of food security. They wished for a decision support system (DSS) that could aid in their classification of countries to mitigate the risk of failing on food security. The virtue of the DSS should be that their expert judgment was complemented by formal methods for better risk classification. The UTADIS method was fitting for the purpose, but it lacked implementability. In particular, it required an iterative approach engaging the experts multiple times, while not readily lending itself to making use of external data, making it inefficient as a DSS. The fundamental contribution of this thesis is that I have solved these shortcomings of the UTADIS method, such that it now readily can be used in a functionally efficient way for the desired purpose of the UN. In solving these problems, it is also more broadly implementable as a DSS, as I have validated the artifact to a DSS, by use of several demonstrations and exposed it to sensitivity analysis.

Place, publisher, year, edition, pages
Borlänge: Dalarna University, 2018
Series
Dalarna Doctoral Dissertations in Microdata Analysis ; 8
Keywords
Coherence, Efficiency, Decision Support System, Multi-Criteria, Risk, Classification Model, Decision Makers, Judgment, Alternatives, Prediction, Data, Integrate, Imprecision, Food Security, UTADIS
National Category
Other Computer and Information Science Economics and Business
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-28649 (URN)978-91-85941-79-7 (ISBN)
Public defence
2018-11-28, B311, Borlänge, 13:00 (English)
Opponent
Supervisors
Available from: 2018-10-30 Created: 2018-10-01 Last updated: 2019-06-17Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records BETA

Laryea, RuebenCarling, KennethCialani, Catia

Search in DiVA

By author/editor
Laryea, RuebenCarling, KennethCialani, Catia
By organisation
Microdata AnalysisEconomics
In the same journal
International Journal of Risk Assessment and Management
Economics and Business

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 1506 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf