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Risk profiling of food security impediments using decision maker’s behavioural preference towards operational risk management

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

For different decision makers, their approach towards management of operational risks differs due to difference in background and behavioural preferences. For such reasons, they attach different importance to various perspectives to manage operational risks. Present study conducts and analyses risk profiling of food security impediments, in which operational risk has come up as an important impediment. Based on three perspectives namely, social, economic, and operational, the research first evaluates severity of impediments in food security. Risk profiling is then conducted on the basis of decision makers’ preferences towards different perspectives. Integration of fuzzy set theory and evidential reasoning algorithm along with decision makers’ behavioural preferences have been used for the analysis. The proposed model generates a continuum of scenarios towards relative importance of three perspectives. It is observed that despite changing the importance of perspectives, a few risks show robustness in their severity, while other ones are sensitive to small changes. Based on these dynamic changes in risk-percept, insightful risk profiling is presented in this research. The risk profiling approach uniquely helps decision makers to adequately plan their course of actions to deal with operational risks associated with food security.

Original languageEnglish
JournalAnnals of Operations Research
DOIs
Publication statusAccepted/In press - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger

Keywords

  • Evidential reasoning algorithm
  • Food secure system
  • Food security impediments
  • Operational risk planning
  • Risk profiling

ASJC Scopus subject areas

  • General Decision Sciences
  • Management Science and Operations Research

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