Addressing equity issue in multi-actor policymaking via a system-of-systems approach: Aviation emissions reduction case study



Finding equitable policy solutions is critical for developing sustainable energy use. This paper presents a system-of-systems (SoS) formalism for addressing the equity issue in multi-actor policymaking. In a SoS, the control of the overall system performance is shared among a network of actors. In contrast to a single optimal solution that aggregates objectives of actors, the solution concept of iso-performance is formulated and employed to illuminate multiple solutions and hence the ‘space’ for actors to compromise. By specifically accounting for the equity issue, the level of sacrifice each actor makes for each iso-performance solution is computed. To demonstrate the approach, a case study is presented about policymaking to reduce fuel life cycle aviation emissions in the United States based on the year 2020 reduction target, involving government, airlines, jet fuel refinery companies, and aircraft and engine manufacturers. A resource allocation mixed integer programming model is employed to calculate carbon emissions resulting from airlines’ deployment of aircraft fleet to meet changing air transport demand. The paper discusses three iso-performance solutions; each of them requires a different level of sacrifice from each actor. Such an insight can inform policymaking in determining the magnitude of compensation required when a particular solution is pursued.


System-of-systems equity multi-actor policymaking iso-performance solutions aviation emissions 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Agusdinata, D.B. (2008). Exploratory modeling and analysis: a method to deal with deep uncertainty. PhD Thesis, Delft University of TechnologyGoogle Scholar
  2. [2]
    Agusdinata, D.B. & DeLaurentis, D.A. (2009). System-of-systems methodology for designing overall policies to tackle aviation environmental impacts. In: The TRB 88th Annual Meeting, Washington DCGoogle Scholar
  3. [3]
    Agusdinata, D.B. & Dittmar, L. (2009). Adaptive policy design to reduce carbon emissions: a system-of-systems perspective. IEEE Systems Journal, 3(4): 509–519CrossRefGoogle Scholar
  4. [4]
    Breiman, L., Friedman, J.H., Olshen, C.J. & Stone, C.J. (1984). Classification and Regression Trees. Monterey, WadsworthGoogle Scholar
  5. [5]
    Costanza, R. & Patten, B.C. (1995). Defining and predicting sustainability. Ecological Economics, 15(3): 193–196CrossRefGoogle Scholar
  6. [6]
    Crossley, W.A. & DeLaurentis, D.A. (2007). System-of-systems approach for assessing new technologies in NGATS. Purdue UniversityGoogle Scholar
  7. [7]
    DeLaurentis, D.A., Kang, T. & Lim, S. (2004). Solution space modeling and characterization for conceptual air vehicles. AIAA Journal of Aircraft, 41(1): 73–84CrossRefGoogle Scholar
  8. [8]
    Deng, X. & Papadimitriou, C. (1994). On the complexity of cooperative solution concepts. Mathematics of Operations Research, 19(2): 257–266CrossRefMATHMathSciNetGoogle Scholar
  9. [9]
    Duke, R.D. & Geurts, J.L.A. (2004). Policy Games for Strategic Management: Pathways into the Unknown. Amsterdam, Dutch University PressGoogle Scholar
  10. [10]
    Energy Information Administration. (2006). Issues in focus: annual energy outlook 2006 with projections to 2030. Available via DIALOG. Cited March 15, 2009
  11. [11]
    European Commission. (2006). Proposal for a directive of the European Parliament and the Council amending Directive 2003/87/EC so as to include aviation activities in the scheme for greenhouse gas emission allowance trading within the Community. COM(2006) 818 final, BrusselGoogle Scholar
  12. [12]
    Haimes, Y.Y. (2008). Models for risk management of systems of systems. Int. J. System of Systems Engineering, 1(1/2): 222–236CrossRefGoogle Scholar
  13. [13]
    Hileman, J.I., Wong, H.M., Ortiz, D., Brown, N., Maurice, L. & Rumizen, M. (2008). The feasibility and potential environmental benefits of alternative fuels for commercial aviation. In: 26th International Congress of the Aeronautical Sciences (ICAS), Anchorage, USAGoogle Scholar
  14. [14]
    Hipel, K.W., Fang, L.P. & Heng, M. (2010). System of systems approach to policy development for global food security. Journal of Systems Science and Systems Engineering, 19(1): 1–21CrossRefGoogle Scholar
  15. [15]
    Hipel, K.W., Jamshidi, M.M., Tiem, J.M. & White, C.C. (2007). The future of systems, man, and cybernetics: application domains and research methods. IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Reviews, 37(5): 726–743CrossRefGoogle Scholar
  16. [16]
    IPPC. (1999). IPCC Special Report: Aviation and the Global AtmosphereGoogle Scholar
  17. [17]
    Jamin, S., Schafer, A., Ben-Akiva, M.E. & Waitz, I.A. (2004). Aviation emissions and abatement policies in the United States: a city-pair analysis. Transportation Research Part D-Transport and Environment, 9(4): 295–317CrossRefGoogle Scholar
  18. [18]
    Kim, B.Y., Fleming, G.G., Lee, J.J., Waitz, I.A., Clarke, J.P., Balasubramanian, S., Malwitz, A., Klima, K., Locke, M., Holsclaw, C.A., Maurice, L.Q. & Gupta, M.L. (2007). System for assessing aviation’s global emissions (SAGE), part 1: model description and inventory results. Transportation Research Part D-Transport and Environment, 12(5): 325–346CrossRefGoogle Scholar
  19. [19]
    Lee, J., Lukachko, S., Waitz, I. & Schafer, A. (2001). Historical and future trends in aircraft performance, cost, and emissions. Annual Review of Energy and the Environment, 26: 167–200CrossRefGoogle Scholar
  20. [20]
    Li, S., Song, B. & Zhang, H. (2007). Method for multivariate analysis with small sample in aircraft cost estimation. Journal of Aircraft, 44(3): 1042–1045CrossRefMathSciNetGoogle Scholar
  21. [21]
    Maier, M.W. (1998). Architecting principles for systems-of-systems. Systems Engineering, 1(4): 267–284CrossRefGoogle Scholar
  22. [22]
    Marais, K. & Weigel, A. (2006). A framework to encourage successful technology transition in civil aviation. In: IEEE/AIAA 25th Digital Avionics Systems Conference, Portsmouth, ORGoogle Scholar
  23. [23]
    McCullers, L.A. (1984). Aircraft configuration optimization including optimized flight profiles, multidisciplinary analysis and optimization — Part 1. NASA CP-2327Google Scholar
  24. [24]
    McKay, M.D., Beckman, R.J. & Conover, W.J. (1979). Comparison of 3 methods for selecting values of input variables in the analysis of output from a computer code. Technometrics, 21(2): 239–245CrossRefMATHMathSciNetGoogle Scholar
  25. [25]
    Mozdzanowska, A. & Hansman, R.J. (2008). System transition: dynamics of change in the US air transportation system. MITGoogle Scholar
  26. [26]
    Rao, J., Badhrinath, K., Pakala, R. & Mistree, F. (1997). A study of optimal design under conflict using models of multi-player games. Engineering Optimization, 28(1–2): 63–94CrossRefGoogle Scholar
  27. [27]
    Sage, A.P. (2008). Risk in system of systems engineering and management. Journal of Industrial and Management Optimization, 4(3): 477–487MATHMathSciNetGoogle Scholar
  28. [28]
    Scheelhaase, J. & Grimme, W. (2007). Emissions trading for international aviation — an estimation of the economic impact on selected European airlines. Journal of Air Transport Management, 13(5): 253–263CrossRefGoogle Scholar
  29. [29]
    Sherry, L., Shortle, J. & Kumar, V. (2009). Why equity is elusive: dynamical properties of overscheduled national airspace system resources. In: 9th AIAA Aviation Technology, Integration, and Operations Conference (ATIO), Hilton Head, South CarolinaGoogle Scholar
  30. [30]
    Simon, H. (1972). Theories of bounded rationality. In: McGuire and Radner (eds.): Decision and Organization. North-Holland, NYGoogle Scholar
  31. [31]
    Simon, H.A. (1973). The Organizations of complex systems. In: Pattee, HH (ed.) Hierarchy Theory — The Challenge of Complex System. George Braziller, Inc., New YorkGoogle Scholar
  32. [32]
    The Economist. (March 2009). The budget and the environment: whom the cap fitsGoogle Scholar
  33. [33]
    Tirovolis, N. & Serghides, V. (2005). Unit cost estimation methodology for commercial aircraft. Journal of Aircraft, 42(6): 1377–1386CrossRefGoogle Scholar
  34. [34]
    Vaillancourt, K. & Waaub, J.P. (2004). Equity in international greenhouse gases abatement scenarios: a multi-criteria approach. European Journal of Operational Research, 153: 489–505CrossRefMATHGoogle Scholar
  35. [35]
    Wang, L.Z., Fang, L.P. & Hipel, K.W. (2008). Basin-wide cooperative water resources allocation. European Journal of Operational Research, 190(3): 798–817CrossRefMATHGoogle Scholar
  36. [36]
    Yang, C., McCollum, D., McCarthy, R. & Leighty, W. (2009). Meeting an 80% reduction in greenhouse gas emissions from transportation by 2050: a case study in California. Transportation Research Part D-Transport and Environment, 14(3): 147–156CrossRefGoogle Scholar

Copyright information

© Systems Engineering Society of China and Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.System-of-Systems Laboratory (SoSL), College of EngineeringPurdue UniversityWest LafayetteUSA
  2. 2.School of Aeronautics and AstronauticsPurdue UniversityWest LafayetteUSA

Personalised recommendations