IDEAS home Printed from https://ideas.repec.org/a/spr/envsyd/v36y2016i2d10.1007_s10669-016-9599-0.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10669-016-9599-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10669-016-9599-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rui Huang & Arunima Malik & Manfred Lenzen & Yutong Jin & Yafei Wang & Futu Faturay & Zhiyi Zhu, 2022. "Supply-chain impacts of Sichuan earthquake: a case study using disaster input–output analysis," 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. 110(3), pages 2227-2248, February.
    2. Jian Jin & Haoran Zhou, 2023. "A Demand-Side Inoperability Input–Output Model for Strategic Risk Management: Insight from the COVID-19 Outbreak in Shanghai, China," Sustainability, MDPI, vol. 15(5), pages 1-22, February.
    3. Krista Danielle S. Yu & Kathleen B. Aviso & Joost R. Santos & Raymond R. Tan, 2020. "The Economic Impact of Lockdowns: A Persistent Inoperability Input-Output Approach," Economies, MDPI, vol. 8(4), pages 1-14, December.
    4. 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.
    5. Selerio, Egberto & Maglasang, Renan, 2021. "Minimizing production loss consequent to disasters using a subsidy optimization model: a pandemic case," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 112-124.
    6. Shahbaz, Muhammad & Hoang, Thi Hong Van & Mahalik, Mantu Kumar & Roubaud, David, 2017. "Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis," Energy Economics, Elsevier, vol. 63(C), pages 199-212.
    7. Mikhailov, L., 2004. "A fuzzy approach to deriving priorities from interval pairwise comparison judgements," European Journal of Operational Research, Elsevier, vol. 159(3), pages 687-704, December.
    8. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea," Energies, MDPI, vol. 10(12), pages 1-22, December.
    10. Madjid Tavana & Mariya Sodenkamp & Leena Suhl, 2010. "A soft multi-criteria decision analysis model with application to the European Union enlargement," Annals of Operations Research, Springer, vol. 181(1), pages 393-421, December.
    11. P. Daniel Wright & Matthew J. Liberatore & Robert L. Nydick, 2006. "A Survey of Operations Research Models and Applications in Homeland Security," Interfaces, INFORMS, vol. 36(6), pages 514-529, December.
    12. Zola, Fernanda Cavicchioli & Colmenero, João Carlos & Aragão, Franciely Velozo & Rodrigues, Thaisa & Junior, Aldo Braghini, 2020. "Multicriterial model for selecting a charcoal kiln," Energy, Elsevier, vol. 190(C).
    13. Weijiang Li & Jiahong Wen & Bo Xu & Xiande Li & Shiqiang Du, 2018. "Integrated Assessment of Economic Losses in Manufacturing Industry in Shanghai Metropolitan Area Under an Extreme Storm Flood Scenario," Sustainability, MDPI, vol. 11(1), pages 1-19, December.
    14. Iman Rahimi Aloughareh & Mohsen Ghafory Ashtiany & Kiarash Nasserasadi, 2016. "An Integrated Methodology For Regional Macroeconomic Loss Estimation Of Earthquake: A Case Study Of Tehran," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 61(04), pages 1-24, September.
    15. Fabio Blanco-Mesa & Anna M. Gil-Lafuente & José M. Merigó, 2018. "Subjective stakeholder dynamics relationships treatment: a methodological approach using fuzzy decision-making," Computational and Mathematical Organization Theory, Springer, vol. 24(4), pages 441-472, December.
    16. Elena Ianchovichina & Maros Ivanic, 2016. "Economic Effects of the Syrian War and the Spread of the Islamic State on the Levant," The World Economy, Wiley Blackwell, vol. 39(10), pages 1584-1627, October.
    17. Tseng, Fang-Mei & Chiu, Yu-Jing & Chen, Ja-Shen, 2009. "Measuring business performance in the high-tech manufacturing industry: A case study of Taiwan's large-sized TFT-LCD panel companies," Omega, Elsevier, vol. 37(3), pages 686-697, June.
    18. Lorenzo Carrera & Gabriele Standardi & Francesco Bosello & Jaroslav Mysiak, 2014. "Assessing Direct and Indirect Economic Impacts of a Flood Event Through the Integration of Spatial and Computable General Equilibrium Modelling," Working Papers 2014.82, Fondazione Eni Enrico Mattei.
    19. Mohamed Hanine & Omar Boutkhoum & Abderrafie El Maknissi & Abdessadek Tikniouine & Tarik Agouti, 2016. "Decision making under uncertainty using PEES–fuzzy AHP–fuzzy TOPSIS methodology for landfill location selection," Environment Systems and Decisions, Springer, vol. 36(4), pages 351-367, December.
    20. Pradeep V. Mandapaka & Edmond Y. M. Lo, 2023. "Assessing Shock Propagation and Cascading Uncertainties Using the Input–Output Framework: Analysis of an Oil Refinery Accident in Singapore," Sustainability, MDPI, vol. 15(2), pages 1-24, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:envsyd:v:36:y:2016:i:2:d:10.1007_s10669-016-9599-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.