A weighted fuzzy linear programming model in economic input–output analysis: an application to risk management of energy system disruptions

Krista Danielle Yu, Kathleen B. Aviso, Michael Angelo B. Promentilla, Joost R. Santos and Raymond R. Tan
Additional contact information
Kathleen B. Aviso: De La Salle University
Michael Angelo B. Promentilla: De La Salle University
Joost R. Santos: The George Washington University
Raymond R. Tan: De La Salle University

Environment Systems and Decisions, 2016, vol. 36, issue 2, 183-195

Abstract: Abstract Climate change exposes economic systems to numerous risks, including reduced agricultural production and electric power supply shortages. The interdependent nature of economic systems causes disruptions in any sector to cascade to other sectors via forward and backward linkages. This work develops an optimization model with which allocation of scarce goods or resources can be optimized; the model uses an overall index of satisfaction of fuzzy economic output goals under conditions of scarcity caused by climatic disruptions. The proposed model includes a vulnerability measure that integrates information elicited from expert judgment. A case study based on a scenario of drought-induced electricity shortage in the Philippine economy is examined. Results show that trade, transportation and service-oriented industries suffer losses in gross domestic product in the Philippine case.

Keywords: Input–output analysis; Fuzzy linear programming; Risk management; Analytic hierarchy process (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10669-016-9599-0

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