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

Author

Listed:
  • Krista Danielle S. Yu

    (De La Salle University)

  • 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)

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.

Suggested Citation

  • Krista Danielle S. Yu & Kathleen B. Aviso & Michael Angelo B. Promentilla & Joost R. Santos & Raymond R. Tan, 2016. "A weighted fuzzy linear programming model in economic input–output analysis: an application to risk management of energy system disruptions," Environment Systems and Decisions, Springer, vol. 36(2), pages 183-195, June.
    • Handle: RePEc:spr:envsyd:v:36:y:2016:i:2:d:10.1007_s10669-016-9599-0
    DOI: 10.1007/s10669-016-9599-0
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    as
    1. Chang, Ching-Chih, 2010. "A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China," Applied Energy, Elsevier, vol. 87(11), pages 3533-3537, November.
    2. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    3. Shi, Xunpeng, 2016. "The future of ASEAN energy mix: A SWOT analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 672-680.
    4. Lenzen, Manfred, 1998. "Primary energy and greenhouse gases embodied in Australian final consumption: an input-output analysis," Energy Policy, Elsevier, vol. 26(6), pages 495-506, May.
    5. Rehman Akhtar & Joost Santos, 2013. "Risk-based input–output analysis of hurricane impacts on interdependent regional workforce systems," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(1), pages 391-405, January.
    6. Azam, Muhammad & Khan, Abdul Qayyum & Bakhtyar, B. & Emirullah, Chandra, 2015. "The causal relationship between energy consumption and economic growth in the ASEAN-5 countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 732-745.
    7. Okadera, Tomohiro & Geng, Yong & Fujita, Tsuyoshi & Dong, Huijuan & Liu, Zhu & Yoshida, Noboru & Kanazawa, Takaaki, 2015. "Evaluating the water footprint of the energy supply of Liaoning Province, China: A regional input–output analysis approach," Energy Policy, Elsevier, vol. 78(C), pages 148-157.
    8. Ilkka Kananen & Pekka Korhonen & Jyrki Wallenius & Hannele Wallenius, 1990. "Multiple Objective Analysis of Input-Output Models for Emergency Management," Operations Research, INFORMS, vol. 38(2), pages 193-201, April.
    9. Amine El Haimar & Joost Santos, 2015. "A stochastic recovery model of influenza pandemic effects on interdependent workforce systems," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 987-1011, June.
    10. Adam Rose & Shu‐Yi Liao, 2005. "Modeling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions," Journal of Regional Science, Wiley Blackwell, vol. 45(1), pages 75-112, February.
    11. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    12. Cellura, Maurizio & Longo, Sonia & Mistretta, Marina, 2011. "The energy and environmental impacts of Italian households consumptions: An input–output approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 3897-3908.
    13. Joost R. Santos & Yacov Y. Haimes, 2004. "Modeling the Demand Reduction Input‐Output (I‐O) Inoperability Due to Terrorism of Interconnected Infrastructures," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1437-1451, December.
    14. Baghersad, Milad & Zobel, Christopher W., 2015. "Economic impact of production bottlenecks caused by disasters impacting interdependent industry sectors," International Journal of Production Economics, Elsevier, vol. 168(C), pages 71-80.
    15. Apergis, Nicholas & Lau, Marco Chi Keung, 2015. "Structural breaks and electricity prices: Further evidence on the role of climate policy uncertainties in the Australian electricity market," Energy Economics, Elsevier, vol. 52(PA), pages 176-182.
    16. Costantini, Valeria & Martini, Chiara, 2010. "The causality between energy consumption and economic growth: A multi-sectoral analysis using non-stationary cointegrated panel data," Energy Economics, Elsevier, vol. 32(3), pages 591-603, May.
    17. Natina Yaduma & Mika Kortelainen & Ada Wossink, 2015. "The environmental Kuznets curve at different levels of economic development: a counterfactual quantile regression analysis for CO 2 emissions," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 4(3), pages 278-303, November.
    18. Patrick T. Harker & Luis G. Vargas, 1987. "The Theory of Ratio Scale Estimation: Saaty's Analytic Hierarchy Process," Management Science, INFORMS, vol. 33(11), pages 1383-1403, November.
    19. Stern, David I. & Common, Michael S. & Barbier, Edward B., 1996. "Economic growth and environmental degradation: The environmental Kuznets curve and sustainable development," World Development, Elsevier, vol. 24(7), pages 1151-1160, July.
    20. Yasuhide Okuyama, 2007. "Economic Modeling for Disaster Impact Analysis: Past, Present, and Future," Economic Systems Research, Taylor & Francis Journals, vol. 19(2), pages 115-124.
    21. Mahamat Hamit-Haggar, 2009. "Total Factor Productivity growth, Technological Progress, and Efficiency Changes: Empirical Evidence from Canadian Manufacturing Industries," Working Papers 0905E, University of Ottawa, Department of Economics.
    22. Tan, Raymond R., 2011. "A general source-sink model with inoperability constraints for robust energy sector planning," Applied Energy, Elsevier, vol. 88(11), pages 3759-3764.
    23. Krista Danielle S. Yu & Raymond R. Tan & Kathleen B. Aviso & Michael Angelo B. Promentilla & Joost R. Santos, 2014. "A Vulnerability Index For Post-Disaster Key Sector Prioritization," Economic Systems Research, Taylor & Francis Journals, vol. 26(1), pages 81-97, March.
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    Cited by:

    1. Xiaoxiang Xu & Mingqiu Liao, 2022. "Prediction of China’s Economic Structural Changes under Carbon Emission Constraints: Based on the Linear Programming Input–Output (LP-IO) Model," Sustainability, MDPI, vol. 14(15), pages 1-13, July.
    2. Qifeng Qiao & Peter A. Beling, 2016. "Decision analytics and machine learning in economic and financial systems," Environment Systems and Decisions, Springer, vol. 36(2), pages 109-113, June.

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