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Sequential Decision-making in Interdependent Sectors with Multiobjective Inoperability Decision Trees: Application to Biofuel Subsidy Analysis


  • Joost Santos
  • Kash Barker
  • Paul Zelinke


Decision-making involving large-scale systems often involves considerations for temporal changes, interdependencies in organizational structures, multiple competing objectives, and risk and uncertainty, among others. In this paper we develop a risk-based methodology, the Multiobjective Inoperability Decision Tree (MOIDT). It integrates several dimensions of decision-making processes associated with interconnected systems in terms of: (i) evaluation of sequential policies; (ii) analysis of interdependencies; (iii) treatment of multiple objectives and their tradeoffs; and (iv) characterization of uncertainties. To demonstrate the integration of these four components, we present a case study to analyze the impact of government policies towards mass-scale biofuel production. Using a multi-period decision framework, the analysis utilizes economic input-output data to model the probabilistic demand adjustments for sectors that will likely be affected by biofuel policies.

Suggested Citation

  • Joost Santos & Kash Barker & Paul Zelinke, 2008. "Sequential Decision-making in Interdependent Sectors with Multiobjective Inoperability Decision Trees: Application to Biofuel Subsidy Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 20(1), pages 29-56.
  • Handle: RePEc:taf:ecsysr:v:20:y:2008:i:1:p:29-56 DOI: 10.1080/09535310801890672

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    References listed on IDEAS

    1. Rikard Forslid & Jan I. Haaland & Karen Helene M. Knarvik & Ottar Maestad, 2002. "Integration and transition: Scenarios for the location of production and trade in Europe," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 10(1), pages 93-117, March.
    2. Paul Krugman & Anthony J. Venables, 1995. "Globalization and the Inequality of Nations," The Quarterly Journal of Economics, Oxford University Press, vol. 110(4), pages 857-880.
    3. Karl Aiginger & Stephen W. Davies, 2004. "Industrial specialisation and geographic concentration: Two sides of the same coin? Not for the European Union," Journal of Applied Economics, Universidad del CEMA, vol. 7, pages 231-248, November.
    4. Gianmarco I. P. Ottaviano & Diego Puga, 1998. "Agglomeration in the Global Economy: A Survey of the 'New Economic Geography'," The World Economy, Wiley Blackwell, vol. 21(6), pages 707-731, August.
    5. J.Peter Neary, 2001. "Of Hype and Hyperbolas: Introducing the New Economic Geography," Journal of Economic Literature, American Economic Association, vol. 39(2), pages 536-561, June.
    6. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    7. repec:hhs:iuiwop:430 is not listed on IDEAS
    8. Julda Kielyte, 2008. "Estimating Panel Data Models in the Presence of Endogeneity and Selection," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 51(2), pages 1-19.
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    Cited by:

    1. Kasivisvanathan, Harresh & Barilea, Ivan Dale U. & Ng, Denny K.S. & Tan, Raymond R., 2013. "Optimal operational adjustment in multi-functional energy systems in response to process inoperability," Applied Energy, Elsevier, vol. 102(C), pages 492-500.
    2. repec:eee:reensy:v:94:y:2009:i:4:p:819-829 is not listed on IDEAS
    3. repec:eee:reensy:v:125:y:2014:i:c:p:92-102 is not listed on IDEAS
    4. Barker, Kash & Santos, Joost R., 2010. "Measuring the efficacy of inventory with a dynamic input-output model," International Journal of Production Economics, Elsevier, vol. 126(1), pages 130-143, July.
    5. Suzuki, Kengo & Uchiyama, Yohji, 2010. "Quantifying the risk of an increase in the prices of non-energy products by combining the portfolio and input-output approaches," Energy Policy, Elsevier, vol. 38(10), pages 5867-5877, October.
    6. Frini, Anissa & Guitouni, Adel & Martel, Jean-Marc, 2012. "A general decomposition approach for multi-criteria decision trees," European Journal of Operational Research, Elsevier, vol. 220(2), pages 452-460.
    7. 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.


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