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Complexity
Volume 2017, Article ID 1967645, 23 pages
https://doi.org/10.1155/2017/1967645
Review Article

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Eindhoven University of Technology, Eindhoven, Netherlands

Correspondence should be addressed to Auke Hoekstra; ln.eut@artskeoh.e.a

Received 6 June 2017; Revised 17 October 2017; Accepted 12 November 2017; Published 28 December 2017

Academic Editor: Ettore Bompard

Copyright © 2017 Auke Hoekstra et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. R. K. Pachauri and L. Mayer, “Intergovernmental panel on climate change,” in Climate Change 2014: Synthesis Report, Intergovernmental Panel on Climate Change, Geneva, Switzerland, 2015. View at Google Scholar
  2. Paris Agreement, Wikipedia, 2017.
  3. Energy Modeling, Wikipedia, 2017.
  4. “Lazard’s Levelized Cost of Energy Analysis”.
  5. P. Dowling and M. Gray, “End of the Load for Coal and Gas? Challenging Power Technology Assumptions,” Carbon Tracker, 2016. View at Google Scholar
  6. D. Coady, I. Parry, L. Sears, and B. Shang, “How large are global fossil fuel subsidies?” World Development, vol. 91, pp. 11–27, 2017. View at Publisher · View at Google Scholar · View at Scopus
  7. L. Merrill, Tackling Fossil Fuel Subsidies And Climate Change: Levelling the Energy Playing Field, Nordic Council of Ministers, 2015.
  8. N. Stern, “The economics of climate change: the stern review,” The Economics of Climate Change: The Stern Review, pp. 1–692, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. J. Blazejczak, F. G. Braun, D. Edler, and W.-P. Schill, “Economic effects of renewable energy expansion: a model-based analysis for Germany,” Renewable & Sustainable Energy Reviews, vol. 40, pp. 1070–1080, 2014. View at Publisher · View at Google Scholar · View at Scopus
  10. D. Connolly, H. Lund, and B. V. Mathiesen, “Smart energy europe: the technical and economic impact of one potential 100% renewable energy scenario for the european union,” Renewable & Sustainable Energy Reviews, vol. 60, pp. 1634–1653, 2016. View at Publisher · View at Google Scholar · View at Scopus
  11. G. Escribano Francés, J. M. Marín-Quemada, and E. San Martín González, “RES and risk: Renewable energy's contribution to energy security. a portfolio-based approach,” Renewable & Sustainable Energy Reviews, vol. 26, pp. 549–559, 2013. View at Publisher · View at Google Scholar · View at Scopus
  12. D. Scholten and R. Bosman, “The geopolitics of renewables; exploring the political implications of renewable energy systems,” Technological Forecasting & Social Change, vol. 103, pp. 273–283, 2016. View at Publisher · View at Google Scholar · View at Scopus
  13. N. S. Hetherington, “Isaac newton's influence on adam smith's natural laws in economics,” Journal of the History of Ideas, vol. 44, no. 3, pp. 497–505, 1983. View at Publisher · View at Google Scholar
  14. D. A. Walker, “Walrasian economics,” Walrasian Economics, pp. 1–357, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. J. B. Shoven and J. Whalley, “A general equilibrium calculation of the effects of differential taxation of income from capital in the U.S.,” Journal of Public Economics, vol. 1, no. 3-4, pp. 281–321, 1972. View at Publisher · View at Google Scholar · View at Scopus
  16. R. A. Chumacero and K. S. Hebbel, “General equilibrium models: an overview,” Doc. Trab. Banco Cent. Chile, vol. 307, 2004. View at Google Scholar
  17. M. E. Burfisher, Introduction to Computable General Equilibrium Models, Cambridge University Press, 2017.
  18. A. M. Borges, “Applied general equilibrium models: an assessment of their usefulness for policy analysis,” OECD Econ. Stud, vol. 1986, p. 43, 1986. View at Google Scholar
  19. G. Fagiolo and A. Roventini, “Macroeconomic policy in DSGE and agent-based models redux: New developments and challenges ahead,” JASSS, vol. 20, no. 1, article no. 1, 2017. View at Publisher · View at Google Scholar · View at Scopus
  20. V. Mosini, Equilibrium in Economics: Scope and Limits, Routledge, 2008.
  21. L. Bergman, “Chapter 24 CGE modeling of environmental policy and resource management,” in Handbook of Environmental Economics, M. K.-G and J. R. Vincent, Eds., vol. 3, pp. 1273–1306, Elsevier, 2005. View at Google Scholar · View at Scopus
  22. P. J. Kehoe and T. J. Kehoe, “A primer on static applied general equilibrium models,” Fed. Reserve Bank Minneap. Q. Rev.-Fed. Reserve Bank Minneap, vol. 18, no. 2, p. 2, 1994. View at Google Scholar
  23. A. S. Hosny, “Survey of recent literature on CGE trade models: with special reference to the case of egypt,” Journal of World Economic Research, vol. 2, no. 1, p. 9, 2013. View at Publisher · View at Google Scholar
  24. C. Böhringer, T. F. Rutherford, and W. Wiegard, “Computable general equilibrium analysis: Opening a black box,” ZEW - Zentrum für Europäische Wirtschaftsforschung/Center for European Economic Research, ZEW Discussion Paper, pp. 3–56, 2003. View at Google Scholar
  25. F. S. Mishkin, “Will monetary policy become more of a science?” The Science and Practice of Monetary Policy Today: The Deutsche Bank Prize in Financial Economics 2007, pp. 81–103, 2010. View at Publisher · View at Google Scholar · View at Scopus
  26. M. Goodfriend, “How the world achieved consensus on monetary policy,” Journal of Economic Perspectives (JEP), vol. 21, no. 4, pp. 47–68, 2007. View at Publisher · View at Google Scholar · View at Scopus
  27. J. Galí and M. Gertler, “Macroeconomic modeling for monetary policy evaluation,” Journal of Economic Perspectives (JEP), vol. 21, no. 4, pp. 25–45, 2007. View at Publisher · View at Google Scholar · View at Scopus
  28. A. Herbst, F. Toro, F. Reitze, and E. Jochem, “Introduction to energy systems modelling,” Swiss Journal of Economics and Statistics, vol. 148, no. 2, pp. 111–135, 2012. View at Google Scholar
  29. E. A. Stanton, F. Ackerman, and S. Kartha, “Inside the integrated assessment models: four issues in climate economics,” Climate and Development, vol. 1, no. 2, pp. 166–184, 2009. View at Publisher · View at Google Scholar · View at Scopus
  30. C. Read, Logic, Deductive and Inductive, Grant Richards, 1st edition, 1898.
  31. D. Colander, R. P. F. Holt, and J. B. Rosser Jr., “The changing face of mainstream economics,” Review of Political Economy, vol. 16, no. 4, pp. 485–499, 2004. View at Publisher · View at Google Scholar · View at Scopus
  32. C. A. E. Goodhart, “The continuing muddles of monetary theory: A steadfast refusal to face facts,” Economica, vol. 76, no. 1, pp. 821–830, 2009. View at Publisher · View at Google Scholar · View at Scopus
  33. A. Kirman, “The economic crisis is a crisis for economic theory,” CESifo Economic Studies, vol. 56, no. 4, Article ID ifq017, pp. 498–535, 2010. View at Publisher · View at Google Scholar · View at Scopus
  34. D. Colander et al., The financial crisis and the systemic failure of academic economics, 2009.
  35. P. Krugman, How Did Economists Get It So Wrong? The New York Times, 2009.
  36. R. J. Caballero, “Macroeconomics after the crisis: time to deal with the pretense-of- knowledge syndrome,” Journal of Economic Perspectives (JEP), vol. 24, no. 4, pp. 85–102, 2010. View at Publisher · View at Google Scholar · View at Scopus
  37. G. Dosi and A. Roventini, “The irresistible fetish of utility theory: from “pleasure and pain” to rationalising torture,” Intereconomics, vol. 51, no. 5, pp. 286-287, 2016. View at Publisher · View at Google Scholar · View at Scopus
  38. F. Ackerman, “Still dead after all these years: interpreting the failure of general equilibrium theory,” Journal of Economic Methodology, vol. 9, no. 2, pp. 119–139, 2002. View at Publisher · View at Google Scholar
  39. T. Balint, F. Lamperti, A. Mandel, M. Napoletano, A. Roventini, and A. Sapio, “Complexity and the economics of climate change: a survey and a look forward,” Ecological Economics, vol. 138, pp. 252–265, 2017. View at Publisher · View at Google Scholar
  40. F. Ackerman, Can We Afford the Future?: the Economics of a Warming World, Zed Books, 2009.
  41. R. S. Pindyck, “Climate change policy: what do the models tell us?” Journal of Economic Literature, vol. 51, no. 3, pp. 860–872, 2013. View at Google Scholar
  42. K. Arrow, M. Cropper, C. Gollier et al., “Determining benefits and costs for future generations,” Science, vol. 341, no. 6144, pp. 349-350, 2013. View at Publisher · View at Google Scholar · View at Scopus
  43. R. L. Revesz, P. H. Howard, K. Arrow et al., “Global warming: improve economic models of climate change,” Nature, vol. 508, no. 7495, pp. 173–175, 2014. View at Publisher · View at Google Scholar · View at Scopus
  44. S. Dietz and N. Stern, “Endogenous growth, convexity of damage and climate risk: How Nordhaus' framework supports deep cuts in carbon emissions,” Economic Journal, vol. 125, no. 583, pp. 574–620, 2015. View at Publisher · View at Google Scholar · View at Scopus
  45. J. D. Farmer, C. Hepburn, P. Mealy, and A. Teytelboym, “A third wave in the economics of climate change,” Environmental and Resource Economics, vol. 62, no. 2, pp. 329–357, 2015. View at Publisher · View at Google Scholar · View at Scopus
  46. N. Stern, “Economics: current climate models are grossly misleading,” Nature, vol. 530, no. 7591, pp. 407–409, 2016. View at Publisher · View at Google Scholar · View at Scopus
  47. B. Fatih, World Energy Outlook 2016, International Energy Agency, 2016.
  48. International Energy Agency, World Energy Model Documentation, International Energy Agency, 2016.
  49. K. Johnsen, Solar Power, Electricity Grids, Energy Models and the World Energy Model - Why Is Solar Underestimated in the WEM of the IEA, The University of Bergen, 2016.
  50. Perspectives for the Energy Transition, xOECD/IEA and IRENA, 2017.
  51. R. S. Nickerson, “Confirmation bias: a ubiquitous phenomenon in many guises,” Review of General Psychology, vol. 2, no. 2, pp. 175–220, 1998. View at Publisher · View at Google Scholar · View at Scopus
  52. W. Samuelson and R. Zeckhauser, “Status quo bias in decision making,” Journal of Risk and Uncertainty, vol. 1, no. 1, pp. 7–59, 1988. View at Publisher · View at Google Scholar · View at Scopus
  53. J. T. Jost, M. R. Banaji, and B. A. Nosek, “A decade of system justification theory: accumulated evidence of conscious and unconscious bolstering of the status quo,” Political Psychology, vol. 25, no. 6, pp. 881–919, 2004. View at Publisher · View at Google Scholar · View at Scopus
  54. R. R. Nelson, “Recent evolutionary theorizing about economic change,” Journal of Economic Literature, vol. 33, no. 1, pp. 48–90, 1995. View at Google Scholar
  55. L. Tesfatsion and K. L. Judd, Eds., Handbook of Computational Economics Volume 2: Agent-Based Computational Economics, vol. 13 of Handbooks in Economics, Elsevier/North-Holland, 2006.
  56. L. Tesfatsion, “Agent-based computational economics: growing economies from the bottom up.,” Artificial Life, vol. 8, no. 1, pp. 55–82, 2002. View at Publisher · View at Google Scholar · View at Scopus
  57. J. D. Farmer and D. Foley, “The economy needs agent-based modelling,” Nature, vol. 460, no. 7256, pp. 685-686, 2009. View at Publisher · View at Google Scholar · View at Scopus
  58. J. Foster, “Why is economics not a complex systems science?” Journal of Economic Issues, vol. 40, no. 4, pp. 1069–1091, 2006. View at Publisher · View at Google Scholar · View at Scopus
  59. L. Tesfatsion, Agent-Based Computational Economics: A Brief Guide to the Literature, Iowa State Univ., 1998.
  60. D. A. Robalino and R. J. Lempert, “Carrots and sticks for new technology: abating greenhouse gas emissions in a heterogeneous and uncertain world,” Integrated Assessment, vol. 1, no. 1, pp. 1–19, 2000. View at Publisher · View at Google Scholar
  61. C. C. Jaeger, K. Hasselmann, G. Leipold, D. Mangalagiu, and J. D. Tàbara, “Reframing the problem of climate change: from zero sum game to win-win solutions,” Reframing the Problem of Climate Change: From Zero Sum Game to Win-Win Solutions, pp. 1–258, 2013. View at Publisher · View at Google Scholar · View at Scopus
  62. G. Dosi and R. R. Nelson, “Technical change and industrial dynamics as evolutionary processes,” Handbook of the Economics of Innovation, vol. 1, no. 1 C, pp. 51–127, 2010. View at Publisher · View at Google Scholar · View at Scopus
  63. M. D. Gerst, P. Wang, A. Roventini et al., “Agent-based modeling of climate policy: an introduction to the ENGAGE multi-level model framework,” Environmental Modeling and Software, vol. 44, pp. 62–75, 2013. View at Publisher · View at Google Scholar · View at Scopus
  64. B. Rengs, M. Scholz-Wäckerle, A. Gazheli, M. Antal, J. van den Bergh, and M. Scholz-Wäckerle, “Testing innovation, employment and distributional impacts of climate policy packages in a macro-evolutionary systems setting,” 2015, http://www.foreurope.eu/fileadmin/documents/pdf/Workingpapers/WWWforEurope_WPS_no080_MS19.pdf.
  65. S. C. Isley, R. J. Lempert, S. W. Popper, and R. Vardavas, “An Evolutionary Model of Industry Transformation and the Political Sustainability of Emission Control Policies,” 2013, https://www.rand.org/pubs/technical_reports/TR1308.html.
  66. D. W. Bunn and J. I. Muñoz, “Supporting the externality of intermittency in policies for renewable energy,” Energy Policy, vol. 88, pp. 594–602, 2016. View at Publisher · View at Google Scholar · View at Scopus
  67. M. Raberto, B. Ozel, L. Ponta, A. Teglio, and S. Cincotti, “From financial instability to green finance: the role of banking and monetary policies in the Eurace model, 2016”.
  68. D. Helbing, “Globally networked risks and how to respond,” Nature, vol. 497, no. 7447, pp. 51–59, 2013. View at Publisher · View at Google Scholar · View at Scopus
  69. L. Brouwers, K. Hansson, H. Verhagen, and M. Boman, “Agent models of catastrophic events,” in Modelling Autonomous Agents in a Multi-Agent World, 10th European workshop on Multi Agent Systems, 2001. View at Google Scholar
  70. S. Hallegatte, “An adaptive regional input-output model and its application to the assessment of the economic cost of Katrina,” Risk Analysis, vol. 28, no. 3, pp. 779–799, 2008. View at Publisher · View at Google Scholar · View at Scopus
  71. R. Bierkandt, L. Wenz, S. N. Willner, and A. Levermann, “Acclimate—a model for economic damage propagation. Part 1: basic formulation of damage transfer within a global supply network and damage conserving dynamics,” Environment Systems and Decisions, vol. 34, no. 4, pp. 507–524, 2014. View at Publisher · View at Google Scholar · View at Scopus
  72. L. Wenz, S. N. Willner, R. Bierkandt, and A. Levermann, “Acclimate—a model for economic damage propagation. Part II: a dynamic formulation of the backward effects of disaster-induced production failures in the global supply network,” Environment Systems and Decisions, vol. 34, no. 4, pp. 525–539, 2014. View at Publisher · View at Google Scholar · View at Scopus
  73. A. Haas and C. Jaeger, “Agents, bayes, and climatic risks - A modular modelling approach,” Advances in Geosciences, vol. 4, pp. 3–7, 2005. View at Publisher · View at Google Scholar · View at Scopus
  74. A. Mandel, S. Fürst, W. Lass, F. Meissner, C. Jaeger, and S. Fürst, “Lagom generic: an agent-based model of growing economies,” in European Climate Forum, Working Paper, vol. 1, 2009. View at Google Scholar
  75. S. Wolf, S. Fürst, A. Mandel et al., “A multi-agent model of several economic regions,” Environmental Modelling & Software, vol. 44, pp. 25–43, 2013. View at Publisher · View at Google Scholar
  76. F. Lamperti, G. Dosi, M. Napoletano, A. Roventini, and A. Sapio, “Faraway, so close: coupled climate and economic dynamics in an agent-based integrated assessment model,” 2017. View at Publisher · View at Google Scholar
  77. R. Smead, R. L. Sandler, P. Forber, and J. Basl, “A bargaining game analysis of international climate negotiations,” Nature Climate Change, vol. 4, no. 6, pp. 442–445, 2014. View at Publisher · View at Google Scholar · View at Scopus
  78. M. A. Janssen and E. Ostrom, “Chapter 30 governing social-ecological systems,” in Handbook of Computational Economics, L. Tesfatsion and K. L. Judd, Eds., vol. 2, pp. 1465–1509, 2006. View at Publisher · View at Google Scholar · View at Scopus
  79. R. Lempert, J. Scheffran, and D. F. Sprinz, “Methods for long-term environmental policy challenges,” Global Environmental Politics, vol. 9, no. 3, pp. 106–133, 2009. View at Publisher · View at Google Scholar · View at Scopus
  80. M. Janssen and B. De Vries, “The battle of perspectives: a multi-agent model with adaptive responses to climate change,” Ecological Economics, vol. 26, no. 1, pp. 43–65, 1998. View at Publisher · View at Google Scholar · View at Scopus
  81. D. C. Earnest, “Coordination in large numbers: an agent-based model of international negotiations,” International Studies Quarterly, vol. 52, no. 2, pp. 363–382, 2008. View at Publisher · View at Google Scholar · View at Scopus
  82. S. Greeven, O. Kraan, É. J. L. Chappin, and J. H. Kwakkel, “The emergence of climate change mitigation action by society: an agent-based scenario discovery study,” JASSS, vol. 19, no. 3, article no. 9, 2016. View at Publisher · View at Google Scholar · View at Scopus
  83. S. C. Isley, R. J. Lempert, S. W. Popper, and R. Vardavas, “The effect of near-term policy choices on long-term greenhouse gas transformation pathways,” Global Environmental Change, vol. 34, pp. 147–158, 2015. View at Publisher · View at Google Scholar · View at Scopus
  84. J. Sun and L. Tesfatsion, “Dynamic testing of wholesale power market designs: an open-source agent-based framework,” Computational Economics, vol. 30, no. 3, pp. 291–327, 2007. View at Publisher · View at Google Scholar · View at Scopus
  85. A. Weidlich and D. Veit, “A critical survey of agent-based wholesale electricity market models,” Energy Economics, vol. 30, no. 4, pp. 1728–1759, 2008. View at Publisher · View at Google Scholar · View at Scopus
  86. E. Guerci, M. A. Rastegar, and S. Cincotti, “Agent-based modeling and simulation of competitive wholesale electricity markets,” in Handbook of Power Systems II, pp. 241–286, Springer, Berlin, Germany, 2010. View at Publisher · View at Google Scholar
  87. M. Saguan, N. Keseric, P. Dessante, and J.-M. Glachant, “Market power in power markets: Game theory vs. agent-based approach,” in Proceedings of the 2006 IEEE PES Transmission and Distribution Conference and Exposition: (TDC'06), August 2006. View at Publisher · View at Google Scholar · View at Scopus
  88. E. Guerci and S. Sapio, “Comparison and empirical validation of optimizing and agent-based models of the Italian electricity market,” in Proceedings of the 2011 8th International Conference on the European Energy Market, EEM 11, pp. 849–856, May 2011. View at Publisher · View at Google Scholar · View at Scopus
  89. G. Sáenz de Miera, P. del Río González, and I. Vizcaíno, “Analysing the impact of renewable electricity support schemes on power prices: the case of wind electricity in Spain,” Energy Policy, vol. 36, no. 9, pp. 3345–3359, 2008. View at Publisher · View at Google Scholar · View at Scopus
  90. A. Banal-Estañol and A. Rupérez Micola, “Behavioural simulations in spot electricity markets,” European Journal of Operational Research, vol. 214, no. 1, pp. 147–159, 2011. View at Publisher · View at Google Scholar · View at MathSciNet
  91. O. Browne, S. Poletti, and D. Young, “How does market power affect the impact of large scale wind investment in 'energy only' wholesale electricity markets?” Energy Policy, vol. 87, pp. 17–27, 2015. View at Publisher · View at Google Scholar · View at Scopus
  92. J. K. Kok, C. J. Warmer, and I. G. Kamphuis, “Powermatcher: multiagent control in the electricity infrastructure,” in Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 75–82, New York, NY, USA, July 2005. View at Publisher · View at Google Scholar
  93. P. Vytelingum, T. D. Voice, S. D. Ramchurn, A. Rogers, and N. R. Jennings, “Agent-based micro-storage management for the smart grid,” in Proceedings of the 9th International Joint Conference on Autonomous Agents and Multiagent Systems 2010 (AAMAS '10), pp. 39–46, 2010. View at Scopus
  94. E. Kiesling, M. Günther, C. Stummer, and L. M. Wakolbinger, “Agent-based simulation of innovation diffusion: a review,” Central European Journal of Operations Research, vol. 20, no. 2, pp. 183–230, 2012. View at Publisher · View at Google Scholar · View at Scopus
  95. N. Schwarz and A. Ernst, “Agent-based modeling of the diffusion of environmental innovations - an empirical approach,” Technological Forecasting & Social Change, vol. 76, no. 4, pp. 497–511, 2009. View at Publisher · View at Google Scholar · View at Scopus
  96. A. Faber, M. Valente, and P. Janssen, “Exploring domestic micro-cogeneration in the Netherlands: an agent-based demand model for technology diffusion,” Energy Policy, vol. 38, no. 6, pp. 2763–2775, 2010. View at Publisher · View at Google Scholar · View at Scopus
  97. T. Zhang, S. Gensler, and R. Garcia, “A study of the diffusion of alternative fuel vehicles: an agent-based modeling approach,” Journal of Product Innovation Management, vol. 28, no. 2, pp. 152–168, 2011. View at Publisher · View at Google Scholar · View at Scopus
  98. E. Karakaya, A. Hidalgo, and C. Nuur, “Diffusion of eco-innovations: a review,” Renewable & Sustainable Energy Reviews, vol. 33, pp. 392–399, 2014. View at Publisher · View at Google Scholar · View at Scopus
  99. M. A. Janssen and W. Jager, “Stimulating diffusion of green products - Co-evolution between firms and consumers,” Journal of Evolutionary Economics, vol. 12, no. 3, pp. 283–306, 2002. View at Publisher · View at Google Scholar · View at Scopus
  100. G. Silverberg, G. Dosi, and L. Orsenigo, “Innovation, diversity and diffusion: a self-organisation model,” The Economic Journal, vol. 98, no. 393, p. 1032, 1988. View at Publisher · View at Google Scholar
  101. P. Windrum, T. Ciarli, and C. Birchenhall, “Consumer heterogeneity and the development of environmentallyfriendly technologies,” Technological Forecasting & Social Change, vol. 76, no. 4, pp. 533–551, 2009. View at Publisher · View at Google Scholar · View at Scopus
  102. A. Tavoni, A. Dannenberg, G. Kallis, and A. Löschel, “Inequality, communication, and the avoidance of disastrous climate change in a public goods game,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 108, no. 29, pp. 11825–11829, 2011. View at Publisher · View at Google Scholar · View at Scopus
  103. F. Vona and F. Patriarca, “Income inequality and the development of environmental technologies,” Ecological Economics, vol. 70, no. 11, pp. 2201–2213, 2011. View at Publisher · View at Google Scholar · View at Scopus
  104. B. Maya Sopha, C. A. Klöckner, and E. G. Hertwich, “Exploring policy options for a transition to sustainable heating system diffusion using an agent-based simulation,” Energy Policy, vol. 39, no. 5, pp. 2722–2729, 2011. View at Publisher · View at Google Scholar · View at Scopus
  105. M. Bleda and M. Valente, “Graded eco-labels: A demand-oriented approach to reduce pollution,” Technological Forecasting & Social Change, vol. 76, no. 4, pp. 512–524, 2009. View at Publisher · View at Google Scholar · View at Scopus
  106. J. Schumpeter, Capitalism, Socialism and Democracy, Routledge, 2013. View at Publisher · View at Google Scholar
  107. R. N. Foster, Innovation: The Attackers Advantage, Summit Books, New York, NY, USA, 1986.
  108. J. M. Utterback and W. J. Abernathy, “A dynamic model of process and product innovation,” Omega , vol. 3, no. 6, pp. 639–656, 1975. View at Publisher · View at Google Scholar · View at Scopus
  109. W. B. Arthur, “Competing technologies, increasing returns, and lock-in by historical events,” The Economic Journal, vol. 99, no. 394, p. 116, 1989. View at Publisher · View at Google Scholar
  110. V. Vinge, Marooned in Realtime, Bluejay Books, 1986.
  111. R. Kurzweil, Age of Spiritual Machines: When Computers Exceed Human Intelligence, Penguin, New York, NY, USA, 1st edition, 1999.
  112. R. Kurzweil, “The Law of Accelerating Returns,” in Alan Turing: Life and Legacy of a Great Thinker, C. Teuscher, Ed., pp. 381–416, Springer, Berlin, Germany, 2004. View at Google Scholar
  113. J. A. Mathews and E. S. Reinert, “Renewables, manufacturing and green growth: energy strategies based on capturing increasing returns,” Futures, vol. 61, pp. 13–22, 2014. View at Publisher · View at Google Scholar · View at Scopus
  114. L. E. Yelle, “The learning curve: historical review and comprehensive survey,” Decision Sciences, vol. 10, no. 2, pp. 302–328, 1979. View at Publisher · View at Google Scholar
  115. A. B. Atkinson and J. E. Stiglitz, “A new view of technological change,” The Economic Journal, vol. 79, no. 315, pp. 573–578, 1969. View at Publisher · View at Google Scholar
  116. M. J. Anzanello and F. S. Fogliatto, “Learning curve models and applications: literature review and research directions,” International Journal of Industrial Ergonomics, vol. 41, no. 5, pp. 573–583, 2011. View at Publisher · View at Google Scholar · View at Scopus
  117. C. A. Mack, “Fifty years of moore's law,” IEEE Transactions on Semiconductor Manufacturing, vol. 24, no. 2, pp. 202–207, 2011. View at Publisher · View at Google Scholar
  118. A. J. C. Trappey, C. V. Trappey, H. Tan, P. H. Y. Liu, S.-J. Li, and L.-C. Lin, “The determinants of photovoltaic system costs: an evaluation using a hierarchical learning curve model,” Journal of Cleaner Production, vol. 112, pp. 1709–1716, 2016. View at Publisher · View at Google Scholar · View at Scopus
  119. J. L. Bower and C. M. Christensen, “Disruptive technologies: catching the wave,” Long Range Planning, vol. 28, no. 2, p. 155, 1995. View at Publisher · View at Google Scholar
  120. C. M. Christensen, The Innovators Dilemma, Harvard Business School Press, 1997.
  121. C. M. Christensen, M. E. Raynor, and R. McDonald, “What Is Disruptive Innovation?” Harvard Business Review, 2015, https://hbr.org/2015/12/what-is-disruptive-innovation. View at Google Scholar
  122. R. Meyer and E. J. Johnson, “Empirical generalizations in the modeling of consumer choice,” Marketing Science, vol. 14, no. 3_supplement, pp. G180–G189, 1995. View at Publisher · View at Google Scholar
  123. R. Adner and D. Levinthal, “Demand heterogeneity and technology evolution: implications for product and process innovation,” Management Science, vol. 47, no. 5, pp. 611–628, 2001. View at Publisher · View at Google Scholar · View at Scopus
  124. R. N. Stern, J. Pfeffer, and G. Salancik, “The external control of organizations: a resource dependence perspective,” Social Science Research Network, Rochester, vol. 8, no. 4, p. 612, 1978. View at Google Scholar
  125. R. Adner, “When are technologies disruptive? a demand-based view of the emergence of competition,” Strategic Management Journal, vol. 23, no. 8, pp. 667–688, 2002. View at Publisher · View at Google Scholar · View at Scopus
  126. J. B. Barney, “Strategic factor markets: expectations, luck, and business strategy,” Management Science, vol. 32, no. 10, pp. 1231–1241, 1986. View at Publisher · View at Google Scholar
  127. R. Amit and P. J. H. Schoemaker, “Strategic assets and organizational rent,” Strategic Management Journal, vol. 14, no. 1, pp. 33–46, 1993. View at Publisher · View at Google Scholar
  128. G. S. Becker, “Investment in human capital :a theoretical analysis,” Journal of Political Economy, vol. 70, pp. 9–49, 1962. View at Publisher · View at Google Scholar
  129. G. C. Unruh, “Understanding carbon lock-in,” Energy Policy, vol. 28, no. 12, pp. 817–830, 2000. View at Publisher · View at Google Scholar · View at Scopus
  130. G. C. Unruh, “Escaping carbon lock-in,” Energy Policy, vol. 30, no. 4, pp. 317–325, 2002. View at Publisher · View at Google Scholar · View at Scopus
  131. D. G. Victor, “The politics of fossil-fuel subsidies,” Social Science Research Network, Rochester, 2009. View at Publisher · View at Google Scholar
  132. G. C. Unruh and J. Carrillo-Hermosilla, “Globalizing carbon lock-in,” Energy Policy, vol. 34, no. 10, pp. 1185–1197, 2006. View at Publisher · View at Google Scholar · View at Scopus
  133. A. Hoekstra, Characteristics of Dutch EV drivers, 2017.
  134. E. Musk, The Secret Tesla Motors Master Plan (just between you and me [Master, thesis], 2006.
  135. A. Hoekstra, Modelling the Total Cost of Ownership of Electric Vehicles in the Netherlands, 2017.
  136. Bloomberg Finance, Electric Vehicle Outlook 2017, Bloomberg New Energy Finance, 2017.
  137. B. Elzen, F. Geels, and K. Green, System Innovation and the Transition to Sustainability, Edward Elgar Publishing, 2004. View at Publisher · View at Google Scholar
  138. F. Berkhout, A. Smith, and A. Stirling, “Socio-technological regimes and transition contexts,” Syst. Innov. Transit. Sustain. Theory Evid. Policy Edw. Elgar Chelten, vol. 44, no. 106, pp. 48–75, 2004. View at Google Scholar
  139. F. Sengers, A. J. Wieczorek, and R. Raven, “Experimenting for sustainability transitions: a systematic literature review,” Technological Forecasting & Social Change, 2015. View at Publisher · View at Google Scholar · View at Scopus
  140. F. G. N. Li, E. Trutnevyte, and N. Strachan, “A review of socio-technical energy transition (STET) models,” Technological Forecasting & Social Change, vol. 100, pp. 290–305, 2015. View at Publisher · View at Google Scholar · View at Scopus
  141. G. Holtz, F. Alkemade, F. De Haan et al., “Prospects of modelling societal transitions: position paper of an emerging community,” Environmental Innovation and Societal Transitions, vol. 17, pp. 41–58, 2015. View at Publisher · View at Google Scholar · View at Scopus
  142. I. Bailey and G. A. Wilson, “Theorising transitional pathways in response to climate change: Technocentrism, ecocentrism, and the carbon economy,” Environment and Planning A, vol. 41, no. 10, pp. 2324–2341, 2009. View at Publisher · View at Google Scholar · View at Scopus
  143. S. Jolly, R. Raven, and H. Romijn, “Upscaling of business model experiments in off-grid PV solar energy in India,” Sustainability Science, vol. 7, no. 2, pp. 199–212, 2012. View at Publisher · View at Google Scholar · View at Scopus
  144. A. Smith and R. Raven, “What is protective space? reconsidering niches in transitions to sustainability,” Research Policy, vol. 41, no. 6, pp. 1025–1036, 2012. View at Publisher · View at Google Scholar · View at Scopus
  145. R. Kemp, J. Schot, and R. Hoogma, “Regime shifts to sustainability through processes of niche formation: the approach of strategic niche management,” Technology Analysis and Strategic Management, vol. 10, no. 2, pp. 175–195, 1998. View at Publisher · View at Google Scholar · View at Scopus
  146. J. Schot and F. W. Geels, “Strategic niche management and sustainable innovation journeys: theory, findings, research agenda, and policy,” Technology Analysis and Strategic Management, vol. 20, no. 5, pp. 537–554, 2008. View at Publisher · View at Google Scholar · View at Scopus
  147. G. Dosi, “Technological paradigms and technological trajectories. a suggested interpretation of the determinants and directions of technical change,” Research Policy, vol. 11, no. 3, pp. 147–162, 1982. View at Publisher · View at Google Scholar · View at Scopus
  148. R. R. Nelson and S. G. Winter, An Evolutionary Theory of Economic Change, Digitally Reprinted, The Belknap Press of Harvard Univ. Press, Cambridge, UK, 2004.
  149. R. Hoogma, R. Kemp, and J. Schot, “Experimenting for sustainable transport,” The Approach of Strategic Niche Management, 2002. View at Google Scholar
  150. F. W. Geels, “Technological transitions as evolutionary reconfiguration processes: A multi-level perspective and a case-study,” Research Policy, vol. 31, no. 8-9, pp. 1257–1274, 2002. View at Publisher · View at Google Scholar · View at Scopus
  151. B. Carlsson and R. Stankiewicz, “On the nature, function and composition of technological systems,” Journal of Evolutionary Economics, vol. 1, no. 2, pp. 93–118, 1991. View at Publisher · View at Google Scholar · View at Scopus
  152. A. Bergek, M. Hekkert, and S. Jacobsson, “Functions in innovation systems: a framework for analysing energy system dynamics,” in Innovation for a Low Carbon Economy: Economic, Edward Elgar Publishing, 2008. View at Google Scholar
  153. F. W. Geels, M. P. Hekkert, and S. Jacobsson, “The dynamics of sustainable innovation journeys,” Technology Analysis and Strategic Management, vol. 20, no. 5, pp. 521–536, 2008. View at Publisher · View at Google Scholar · View at Scopus
  154. T. Meelen and J. Farla, “Towards an integrated framework for analysing sustainable innovation policy,” Technology Analysis and Strategic Management, vol. 25, no. 8, pp. 957–970, 2013. View at Publisher · View at Google Scholar · View at Scopus
  155. J. Markard and B. Truffer, “Technological innovation systems and the multi-level perspective: towards an integrated framework,” Research Policy, vol. 37, no. 4, pp. 596–615, 2008. View at Publisher · View at Google Scholar · View at Scopus
  156. S. van den Bosch and J. Rotmans, Deepening, Broadening and Scaling up: a Framework for Steering Transition Experiments, 2008.
  157. F. Alkemade, M. P. Hekkert, and S. O. Negro, “Transition policy and innovation policy: friends or foes?” Environmental Innovation and Societal Transitions, vol. 1, no. 1, pp. 125–129, 2011. View at Publisher · View at Google Scholar · View at Scopus
  158. R. F. Malina and S. Kauffman, At Home in the Universe: The Search for Laws of Self-organization and Complexity, Oxford University Press, 1995.
  159. J. Rotmans and D. Loorbach, “Complexity and transition management,” Journal of Industrial Ecology, vol. 13, no. 2, pp. 184–196, 2009. View at Publisher · View at Google Scholar · View at Scopus
  160. J. Schot, L. Kanger, and G. Verbong, “The roles of users in shaping transitions to new energy systems,” Nature Energy, vol. 1, no. 5, p. 16054, 2016. View at Publisher · View at Google Scholar
  161. S. van den Bosch, “Transition Experiments: Exploring societal changes towards sustainability,” 2010.
  162. D. Loorbach, F. Avelino, A. Haxeltine et al., “The economic crisis as a game changer? Exploring the role of social construction in sustainability transitions,” Ecology and Society, vol. 21, no. 4, article no. 15, 2016. View at Publisher · View at Google Scholar · View at Scopus
  163. J. W. Eising, T. van Onna, and F. Alkemade, “Towards smart grids: identifying the risks that arise from the integration of energy and transport supply chains,” Applied Energy, vol. 123, pp. 448–455, 2014. View at Publisher · View at Google Scholar · View at Scopus
  164. H. de Haan, “The dynamics of functioning investigating societal transitions with partial differential equations,” Computational and Mathematical Organization Theory, vol. 14, no. 4, pp. 302–319, 2008. View at Publisher · View at Google Scholar · View at Scopus
  165. A. Van Der Vooren and F. Alkemade, “Managing the diffusion of low emission vehicles,” IEEE Transactions on Engineering Management, vol. 59, no. 4, pp. 728–740, 2012. View at Publisher · View at Google Scholar · View at Scopus
  166. N. Bergman, L. Whitmash, J. Köhler, M. Schilperoord, and J. Rotmans, “Modelling Socio-Technical Transition Patterns and Pathways,” 2008, http://jasss.soc.surrey.ac.uk/11/3/7.html.
  167. G. Holtz and C. Pahl-Wostl, “An agent-based model of groundwater over-exploitation in the Upper Guadiana, Spain,” Regional Environmental Change, vol. 12, no. 1, pp. 95–121, 2012. View at Publisher · View at Google Scholar · View at Scopus
  168. G. Yücel, “Analyzing Transition Dynamics: The Actor-Option Framework for Modelling Socio-Technical Systems,” 2010. View at Publisher · View at Google Scholar · View at Scopus
  169. K. A. West, “Mediated Modeling: A Systems Approach to Environmental Consensus Building Marjan van den Belt . Mediated Modeling: A Systems Approach to Environmental Consensus Building. Island Press. Washington D.C. 339 paper. 2004. ISBN: 1-55963-961-X.,” Natural Areas Journal, vol. 26, no. 2, pp. 221-222, 2006. View at Publisher · View at Google Scholar
  170. J. Vennix, Group Model Building: Facilitating Team Learning Using System Dynamics, Wiley, New York, NY, USA, 1 edition, 1996.
  171. E. Trutnevyte, J. Barton, Á. O'Grady, D. Ogunkunle, D. Pudjianto, and E. Robertson, “Linking a storyline with multiple models: a cross-scale study of the UK power system transition,” Technological Forecasting & Social Change, vol. 89, pp. 26–42, 2014. View at Publisher · View at Google Scholar · View at Scopus
  172. T. Hansen and L. Coenen, “The geography of sustainability transitions: review, synthesis and reflections on an emergent research field,” Environmental Innovation and Societal Transitions, vol. 17, pp. 92–109, 2015. View at Publisher · View at Google Scholar · View at Scopus
  173. E. Trutnevyte, M. Stauffacher, M. Schlegel, and R. W. Scholz, “Context-specific energy strategies: coupling energy system visions with feasible implementation scenarios,” Environmental Science & Technology, vol. 46, no. 17, pp. 9240–9248, 2012. View at Publisher · View at Google Scholar · View at Scopus
  174. F. W. Geels and J. Schot, “Typology of sociotechnical transition pathways,” Research Policy, vol. 36, no. 3, pp. 399–417, 2007. View at Publisher · View at Google Scholar · View at Scopus
  175. G. P. J. Verbong and F. W. Geels, “Exploring sustainability transitions in the electricity sector with socio-technical pathways,” Technological Forecasting & Social Change, vol. 77, no. 8, pp. 1214–1221, 2010. View at Publisher · View at Google Scholar · View at Scopus
  176. G. Verbong and F. Geels, “Future electricity systems: visions, scenarios and transition pathways,” in Governing the Energy Transition: Reality, Illusion or Necessity? pp. 203–219, 2012. View at Publisher · View at Google Scholar · View at Scopus
  177. M. Mead and M. Margaret, https://en.wikiquote.org/wiki/Margaret_Mead.
  178. T. Piketty, Capital in the Twenty-First Century, Harvard University Press, 2017.
  179. M. Mazzucato, The Entrepreneurial State: Debunking Public Vs. Private Sector Myths, Anthem Press, 2015.
  180. T. Seba, Clean Disruption of Energy and Transportation: How Silicon Valley Will Make Oil, Nuclear, Natural Gas, Coal, Electric Utilities and Conventional Cars Obsolete by 2030, 2014.
  181. Neil Strachan, “UKERC Energy Research Landscape: Energy Systems Modelling,” 2011, http://ukerc.rl.ac.uk/Landscapes/Modelling.pdf.
  182. G. P. J. Verbong, S. Beemsterboer, and F. Sengers, “Smart grids or smart users? involving users in developing a low carbon electricity economy,” Energy Policy, vol. 52, pp. 117–125, 2013. View at Publisher · View at Google Scholar · View at Scopus
  183. B. Walrave, K. S. Podoynitsyna, M. Talmar, G. P. Verbong, and A. G. L. Romme, Technology Ventures And Their Ecosystem within the Socio-Technical Settings: A Systemic Framework, Catania Italy Univ., Catania, Italy, 2013.
  184. E. M. Rogers, Diffusion of Innovations, Simon and Schuster, 4th edition, 2010.
  185. S. O. Negro, F. Alkemade, and M. P. Hekkert, “Why does renewable energy diffuse so slowly? a review of innovation system problems,” Renewable & Sustainable Energy Reviews, vol. 16, no. 6, pp. 3836–3846, 2012. View at Publisher · View at Google Scholar · View at Scopus
  186. F. Schmalfuß, K. Mühl, and J. F. Krems, “Direct experience with battery electric vehicles (BEVs) matters when evaluating vehicle attributes, attitude and purchase intention,” Transportation Research Part F: Traffic Psychology and Behaviour, vol. 46, pp. 47–69, 2017. View at Publisher · View at Google Scholar · View at Scopus
  187. Bertha Benz Memorial Route, Wikipedia, 2017.
  188. B. Nykvist and M. Nilsson, “Rapidly falling costs of battery packs for electric vehicles,” Nature Climate Change, vol. 5, no. 4, pp. 329–332, 2015. View at Publisher · View at Google Scholar · View at Scopus
  189. K. Gillingham, R. G. Newell, and W. A. Pizer, “Modeling endogenous technological change for climate policy analysis,” Energy Economics, vol. 30, no. 6, pp. 2734–2753, 2008. View at Publisher · View at Google Scholar · View at Scopus
  190. G. Dosi and Y. Kaniovski, “On “badly behaved” dynamics - Some applications of generalized urn schemes to technological and economic change,” Journal of Evolutionary Economics, vol. 4, no. 2, pp. 93–123, 1994. View at Publisher · View at Google Scholar · View at Scopus
  191. G. P. J. Verbong and F. W. Geels, “Pathways for sustainability transitions in the electricity sector: multi-level analysis and empirical illustration,” in Proceedings of the 2008 1st International Conference on Infrastructure Systems and Services: Building Networks for a Brighter Future, INFRA 2008, November 2008. View at Publisher · View at Google Scholar · View at Scopus
  192. A. C. Clarke, Profiles of the Future, Warner Books Inc, New York, NY, USA, 1985.
  193. T. Postmes, R. Spears, and S. Cihangir, “Quality of decision making and group norms,” Journal of Personality and Social Psychology, vol. 80, no. 6, pp. 918–930, 2001. View at Publisher · View at Google Scholar · View at Scopus
  194. T. Havranek, Z. Irsova, K. Janda, and D. Zilberman, “Selective reporting and the social cost of carbon,” Energy Economics, vol. 51, pp. 394–406, 2015. View at Publisher · View at Google Scholar · View at Scopus
  195. O. US EPA, “The Social Cost of Carbon,” 2017, https://www.epa.gov/climatechange/social-cost-carbon.
  196. Frauenhofer Institute, “Levelized Cost of Electricity, Fraunhofer Institute for Solar Energy Systems ISE,” 2013, http://www.ise.fraunhofer.de/en/publications/studies/cost-of-electricity.html.
  197. W. D. Nordhaus, “Expert opinion on climatic change,” AM.SCI, vol. 82, no. 1, pp. 45–51, 1994. View at Google Scholar · View at Scopus
  198. T. M. Lenton, H. Held, E. Kriegler et al., “Tipping elements in the Earth’s climate system,” Proceedings of the National Adacemy of Sciences of the United States of America, vol. 105, no. 6, pp. 1786–1793, 2008. View at Google Scholar
  199. M. Ikefuji, R. J. Laeven, J. Magnus, and C. Muris, “Expected Utility and Catastrophic Risk,” SSRN Electronic Journal, 2013. View at Publisher · View at Google Scholar
  200. M. L. Weitzman, “Fat tails and the social cost of carbon,” American Economic Review, vol. 104, no. 5, pp. 544–546, 2014. View at Publisher · View at Google Scholar · View at Scopus
  201. J. Pycroft, L. Vergano, C. Hope, D. Paci, and J. C. Ciscar, “A tale of tails: uncertainty and the social cost of carbon dioxide,” Social Science Research Network, 2011. View at Publisher · View at Google Scholar
  202. I. C. Hwang, R. S. J. Tol, and M. W. Hofkes, “Fat-tailed risk about climate change and climate policy,” Energy Policy, vol. 89, pp. 25–35, 2016. View at Publisher · View at Google Scholar · View at Scopus
  203. S. Dietz and N. Stern, “Endogenous growth, convexity of damage and climate risk: how Nordhaus' framework supports deep cuts in carbon emissions, 2014”.
  204. W. D. Nordhaus, “An Analysis of the Dismal Theorem,” Social Science Research Network, 2009. View at Google Scholar
  205. R. S. Tol, “The social cost of carbon: trends, outliers and catastrophes,” Social Science Research Network, 2008. View at Publisher · View at Google Scholar
  206. R. F. Harrod, Towards a Dynamic Economics, Macmillan, London, UK, 1948.
  207. A. C. Pigou, The Economics of Welfare, Macmillan, London, UK, 1932.
  208. F. P. Ramsey, “A mathematical theory of saving,” The Economic Journal, vol. 38, no. 152, p. 543, 1928. View at Publisher · View at Google Scholar
  209. W. D. Nordhaus, “A review of the stern review on the economics of climate change,” Journal of Economic Literature (JEL), vol. 45, no. 3, pp. 686–702, 2007. View at Publisher · View at Google Scholar · View at Scopus
  210. L. H. Goulder and R. C. Williams, “The choice of discount rate for climate change policy evaluation,” Climate Change Economics, vol. 3, no. 4, p. 1250024, 2012. View at Publisher · View at Google Scholar
  211. R. B. Howarth, “Discounting, uncertainty, and revealed time preference,” Land Economics, vol. 85, no. 1, pp. 24–40, 2009. View at Publisher · View at Google Scholar · View at Scopus
  212. L. Kaplow, E. Moyer, and D. A. Weisbach, “The social evaluation of intergenerational policies and its application to integrated assessment models of climate change,” B.E. Journal of Economic Analysis and Policy, vol. 10, no. 2, article no. 7, 2010. View at Google Scholar · View at Scopus
  213. E. A. Stanton, “Negishi welfare weights in integrated assessment models: the mathematics of global inequality,” Climatic Change, vol. 107, no. 3, pp. 417–432, 2011. View at Publisher · View at Google Scholar · View at Scopus
  214. C. Spataru, Whole Energy System Dynamics: Theory, modelling and Policy, Routledge, 2017.
  215. S. C. Bhattacharyya and G. R. Timilsina, “A review of energy system models,” International Journal of Energy Sector Management, vol. 4, no. 4, pp. 494–518, 2010. View at Publisher · View at Google Scholar · View at Scopus
  216. N. Neshat, M. R. Amin-Naseri, and F. Danesh, “Energy models: methods and characteristics,” J. Energy South. Afr, vol. 25, no. 4, pp. 101–111, 2014. View at Google Scholar
  217. C. F. Nicholson, “Review of methods for modelling systems evolution , ILRI,” Working Paper, 2007. View at Google Scholar
  218. S. Sumari, R. Ibrahim, N. H. Zakaria, and A. H. Ab Hamid, “Comparing three simulation model using taxonomy: system dynamic simulation, discrete event simulation and agent based simulation, discrete event simulation and agent based simulation,” International Journal of Management Excellence, vol. 1, no. 3, pp. 54–59, 2013. View at Publisher · View at Google Scholar
  219. A. Borshchev, “The Big Book of Simulation Modeling,” 2015, https://www.amazon.com/Big-Book-Simulation-Modeling-Multimethod-ebook/dp/B00YO0K1ZQ/ref=sr_1_2?ie=UTF8&qid=1483289768&sr=8-2&keywords=Borshchev.
  220. R. Maidstone, “Discrete event simulation, system dynamics and agent based simulation: discussion and comparison,” System, pp. 1–6, 2012. View at Google Scholar
  221. D. H. Meadows, Thinking in Systems: A Primer, Chelsea Green Publishing, 2008.
  222. J. W. Forrester, “The beginning of system dynamics,” in Banquet Talk at the international meeting of the System Dynamics Society, vol. 13, Stuttgart, Germany, 1989. View at Google Scholar
  223. J. Köhler, M. Grubb, D. Popp, and O. Edenhofer, “The transition to endogenous technical change in climate-economy models: a technical overview to the innovation modeling comparison project,” Energy, vol. 27, pp. 17–55, 2006. View at Google Scholar · View at Scopus
  224. S. H. Strogatz, Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, Westview Press, 2014.
  225. D. C. Karnopp, D. L. Margolis, and R. C. Rosenberg, System Dynamics: Modeling, Simulation, and Control of Mechatronic Systems, John Wiley & Sons, 2012.
  226. W. K. DLR, “Review of Multibody Computer, Codes for Vehicle System Dynamics,” Veh. Syst. Dyn, vol. 22, pp. 3–31, 1993. View at Google Scholar
  227. B. C. Dangerfield, “System dynamics applications to european health care issues,” Journal of the Operational Research Society, vol. 50, no. 4, pp. 345–353, 1999. View at Publisher · View at Google Scholar · View at Scopus
  228. G. P. Richardson and P. Otto, “Applications of system dynamics in marketing: editorial,” Journal of Business Research, vol. 61, no. 11, pp. 1099–1101, 2008. View at Publisher · View at Google Scholar · View at Scopus
  229. Y. Barlas, “System dynamics: systemic feedback modeling for policy analysis,” System, vol. 1, p. 59, 2007. View at Google Scholar
  230. J. M. Lyneis and D. N. Ford, “System dynamics applied to project management: a survey, assessment, and directions for future research,” System Dynamics Review, vol. 23, no. 2-3, pp. 157–189, 2007. View at Publisher · View at Google Scholar · View at Scopus
  231. J. D. Sterman, “Learning in and about complex systems,” System Dynamics Review, vol. 10, no. 2-3, pp. 291–330, 1994. View at Publisher · View at Google Scholar
  232. J. D. Sterman, “System dynamics modeling: tools for learning in a complex world,” California Management Review, vol. 43, no. 4, pp. 8–25, 2001. View at Publisher · View at Google Scholar · View at Scopus
  233. D. H. Meadows, D. L. Meadows, J. Randers, and W. W. Behrens, The Limits to Growth: A report for the Club of Rome's Project on the Predicament of Mankind, Universe Books, New York, NY, USA, 1972. View at Publisher · View at Google Scholar
  234. G. M. Turner, “A comparison of the limits to growth with 30 years of reality,” Global Environmental Change, vol. 18, no. 3, pp. 397–411, 2008. View at Publisher · View at Google Scholar · View at Scopus
  235. J. Sterman, The Energy Transition and the Economy: A System Dynamics Approach, Massachusetts Institute of Technology, 1982.
  236. R. F. Naill, “A system dynamics model for national energy policy planning,” System Dynamics Review, vol. 8, no. 1, pp. 1–19, 1992. View at Publisher · View at Google Scholar · View at Scopus
  237. R. F. Naill, “Managing the energy transition: a system dynamics search for alternatives to oil and gas,” Use of COAL2 Model, 1977. View at Google Scholar
  238. A. Ford, “System dynamics and the electric power industry,” System Dynamics Review, vol. 13, no. 1, pp. 57–85, 1997. View at Publisher · View at Google Scholar · View at Scopus
  239. I. Dyner, R. A. Smith, and G. E. Pena, “System dynamics modelling for residential energy efficiency analysis and management,” Journal of the Operational Research Society, vol. 46, no. 10, pp. 1163–1173, 1995. View at Publisher · View at Google Scholar · View at Scopus
  240. A. Aslani, P. Helo, and M. Naaranoja, “Role of renewable energy policies in energy dependency in Finland: system dynamics approach,” Applied Energy, vol. 113, pp. 758–765, 2014. View at Publisher · View at Google Scholar · View at Scopus
  241. K. Chyong Chi, W. J. Nuttall, and D. M. Reiner, “Dynamics of the UK natural gas industry: system dynamics modelling and long-term energy policy analysis,” Technological Forecasting & Social Change, vol. 76, no. 3, pp. 339–357, 2009. View at Publisher · View at Google Scholar · View at Scopus
  242. B. Walrave and R. Raven, “Modelling the dynamics of technological innovation systems,” Research Policy, vol. 45, no. 9, pp. 1833–1844, 2016. View at Publisher · View at Google Scholar · View at Scopus
  243. A. Bergek, S. Jacobsson, B. Carlsson, S. Lindmark, and A. Rickne, “Analyzing the functional dynamics of technological innovation systems: a scheme of analysis,” Research Policy, vol. 37, no. 3, pp. 407–429, 2008. View at Publisher · View at Google Scholar · View at Scopus
  244. V. de Gooyert, E. Rouwette, H. van Kranenburg, E. Freeman, and H. van Breen, “Sustainability transition dynamics: towards overcoming policy resistance,” Technological Forecasting & Social Change, vol. 111, pp. 135–145, 2016. View at Publisher · View at Google Scholar · View at Scopus
  245. T.-H. Kwon, “Strategic niche management of alternative fuel vehicles: a system dynamics model of the policy effect,” Technological Forecasting & Social Change, vol. 79, no. 9, pp. 1672–1680, 2012. View at Publisher · View at Google Scholar · View at Scopus
  246. J. W. Forrester, “System dynamics - The next fifty years,” System Dynamics Review, vol. 23, no. 2-3, pp. 359–370, 2007. View at Publisher · View at Google Scholar · View at Scopus
  247. P. Krugman, “What's new about the new economic geography?” Oxford Review of Economic Policy, vol. 14, no. 2, pp. 7–17, 1998. View at Publisher · View at Google Scholar · View at Scopus
  248. C. Karlsson, M. Andersson, and T. Norman, Handbook of Research Methods and Applications in Economic Geography, Edward Elgar Publishing, 2015. View at Publisher · View at Google Scholar
  249. H. A. Bulkeley, V. C. Broto, and G. A. S. Edwards, An Urban Politics of Climate Change: Experimentation and the Governing of Socio-Technical Transitions, Routledge, 2014.
  250. B. Truffer, “The geography of sustainability transitions: Think/act, globally/locally,” 2016.
  251. J. Banks, J. S. Carson, and L. Barry, Discrete-event system simulation, Pearson, 2005.
  252. E. M. Goldratt and J. Cox, The Goal: A Process of Ongoing Improvemen, North River Press, Great Barrington, Mass, USA, 30th edition, 2014.
  253. C. S. Bale, L. Varga, and T. J. Foxon, “Energy and complexity: new ways forward,” Applied Energy, vol. 138, pp. 150–159, 2015. View at Publisher · View at Google Scholar
  254. T. Lorenz, “Abductive fallacies with agent-based modeling and system dynamics,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface, vol. 5466, pp. 141–152, 2009. View at Publisher · View at Google Scholar · View at Scopus
  255. B. Visser, “Complexity, robustness, and performance: trade-offs in organizational design,” Social Science Research Networ, 2002. View at Publisher · View at Google Scholar
  256. F. Berkes, J. Colding, and C. Folke, Navigating Social - Ecological Systems: Building Resilience for Complexity and Change, Cambridge University Press, Cambridge, UK, 2008. View at Publisher · View at Google Scholar
  257. G. W. Klau and R. Weiskircher, “Robustness and resilience,” in Network Analysis, U. Brandes and T. Erlebach, Eds., vol. 3418 of Lecture Notes in Computer Science, Springer, Berlin,Germany, 2005. View at Publisher · View at Google Scholar
  258. E. O. Wilson, The Insect Societies, Harvard University Press, Cambridge, UK, 1971.
  259. R. Dawkins, The Selfish Gene, Oxford University Press, 1976.
  260. B. Goodwin and P. Saunders, Theoretical Biology: Epigenetic and Evolutionary Order from Complex Systems, Edinburg University Press, 1989.
  261. I. Prigogine, Introduction to Thermodynamics of Irreversible Processes, 1967.
  262. M. Gell-Mann, The Quark and the Jaguar: Adventures in the Simple and the Complex, 1995. View at MathSciNet
  263. P. Cilliers and D. Spurrett, “Complexity and post-modernism: understanding complex systems,” South African Journal of Philosophy, vol. 18, no. 2, pp. 258–274, 1999. View at Publisher · View at Google Scholar
  264. J. H. Holland and J. S. Reitman, “Cognitive Systems Based on Adaptive Algorithms,” SIGART Bull, no. 63, p. 49, 1977. View at Publisher · View at Google Scholar
  265. F. Fukuyama and J. H. Holland, “Hidden order: how adaptation builds complexity,” Foreign Affairs, vol. 75, no. 4, p. 137, 1996. View at Publisher · View at Google Scholar
  266. J. H. Holland, Complexity: A Very Short Introduction, Oxford University Press, New York, NY, USA, 2014.
  267. J. H. Holland, “Studying complex adaptive systems,” Journal of Systems Science & Complexity, vol. 19, no. 1, pp. 1–8, 2006. View at Publisher · View at Google Scholar · View at MathSciNet
  268. T. Parsons, É. Durkheim, A. Marshall, and V. Pareto, “The Structure of Social Action. A Study in Social Theory with Special Reference to a Group of Recent European Writers,” Max Weber, 1937. View at Google Scholar
  269. R. J. Eidelson, “Complex adaptive systems in the behavioral and social sciences,” Review of General Psychology, vol. 1, no. 1, pp. 42–71, 1997. View at Publisher · View at Google Scholar · View at Scopus
  270. J. Epstein and R. Axtell, Growing Artificial Societies: Social Science From the Bottom Up (Complex Adaptive Systems), Brookings Institution Press, 1996.
  271. R. M. Axelrod, The Complexity of Cooperation: Agent-Based Models of Competition And Collaboration, Princeton University Press, Princeton, NJ, USA, 1997.
  272. R. Axelrod, “Advancing the Art of Simulation in the Social Sciences,” in Simulating Social Phenomena, D. R. Conte, P. D. R. Hegselmann, and P. D. P. Terna, Eds., vol. 456 of Lecture Notes in Economics and Mathematical Systems, pp. 21–40, Springer, Berlin, Germany, 1997. View at Publisher · View at Google Scholar
  273. E. D. Beinhocker, The Origin of Wealth: The Radical Remaking of Economics and What it Means for Bu, Harvard Business School Press, London, UK, 2007.
  274. D. Elder-Vass, The Causal Power of Social Structures: Emergence, Structure and Agency, Cambridge University Press, 2010. View at Publisher · View at Google Scholar · View at Scopus
  275. J. Grin, J. Rotmans, and J. Schot, Transitions to Sustainable Development: New Directions in the Study of Long Term Transformative Change, Routledge, New York, NY, USA, 1st edition, 2011. View at Publisher · View at Google Scholar · View at Scopus
  276. A. Rip and R. Kemp, “Technological change,” in Human Choice and Climate Change, S. Rayner and E. L. Malone, Eds., pp. 327–399, Battelle Press, 1998. View at Google Scholar
  277. J. H. Kwakkel, W. E. Walker, and V. A. W. J. Marchau, “Classifying and communicating uncertainties in model-based policy analysis,” International Journal of Technology, Policy and Management, vol. 10, no. 4, pp. 299–315, 2010. View at Publisher · View at Google Scholar · View at Scopus
  278. R. J. Lempert, Shaping the Next One Hundred Years: New Methods for Quantitative, Long-Term Policy Analysis, Rand Corporation, 2003.
  279. W. E. Walker, M. Haasnoot, and J. H. Kwakkel, “Adapt or perish: a review of planning approaches for adaptation under deep uncertainty,” Sustainability, vol. 5, no. 3, pp. 955–979, 2013. View at Publisher · View at Google Scholar · View at Scopus
  280. P. W. B. Atkins, R. E. Wood, and P. J. Rutgers, “The effects of feedback format on dynamic decision making,” Organizational Behavior and Human Decision Processes, vol. 88, no. 2, pp. 587–604, 2002. View at Publisher · View at Google Scholar · View at Scopus
  281. B. Brehmer, “Dynamic decision making: human control of complex systems,” Acta Psychologica, vol. 81, no. 3, pp. 211–241, 1992. View at Publisher · View at Google Scholar · View at Scopus
  282. E. Diehl and J. D. Sterman, “Effects of feedback complexity on dynamic decision making,” Organizational Behavior and Human Decision Processes, vol. 62, no. 2, pp. 198–215, 1995. View at Publisher · View at Google Scholar · View at Scopus
  283. D. N. Kleinmuntz, “Information processing and misperceptions of the implications of feedback in dynamic decision making,” System Dynamics Review, vol. 9, no. 3, pp. 223–237, 1993. View at Publisher · View at Google Scholar · View at Scopus
  284. J. D. Sterman, “Modeling managerial behavior: misperceptions of feedback in a dynamic decision making experiment,” Management Science, vol. 35, no. 3, pp. 321–339, 1989. View at Publisher · View at Google Scholar
  285. M. A. Bedau, “Weak Emergence,” Noûs, vol. 31, pp. 375–399, 1997. View at Publisher · View at Google Scholar
  286. A. Borshchev, The Big Book of Simulation Modeling: Multimethod Modeling with Anylogic 6, AnyLogic, 2013.
  287. J. D. Sterman, “All models are wrong: reflections on becoming a systems scientist,” System Dynamics Review, vol. 18, no. 4, pp. 501–531, 2002. View at Publisher · View at Google Scholar · View at Scopus
  288. T. C. Schelling, “Models of Segregation,” American Economic Review, vol. 59, no. 2, pp. 488–493, 1969. View at Google Scholar
  289. J. H. Holland and J. H. Miller, “Artificial adaptive agents in economic theory,” Am. Econ. Rev, vol. 81, no. 2, pp. 365–71, 1991. View at Google Scholar
  290. J. M. Epstein, “Agent-based computational models and generative social science,” Complexity, vol. 4, no. 5, pp. 41–60, 1999. View at Publisher · View at Google Scholar
  291. E. Bonabeau, “Agent-based modeling: methods and techniques for simulating human systems,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 99, no. 3, pp. 7280–7287, 2002. View at Publisher · View at Google Scholar · View at Scopus
  292. S. De Marchi and S. E. Page, “Agent-based models,” Annual Review of Political Science, vol. 17, pp. 1–20, 2014. View at Publisher · View at Google Scholar · View at Scopus
  293. E. Bruch and J. Atwell, “Agent-based models in empirical social research,” Sociological Methods & Research, vol. 44, no. 2, pp. 186–221, 2015. View at Publisher · View at Google Scholar · View at MathSciNet
  294. K. H. Van Dam, Capturing socio-technical systems with agent-based modelling [Ph.D. thesis], Delft University of Technology, 2009.
  295. K. H. van Dam, I. Nikolic, and Z. Lukszo, Agent-Based Modelling of Socio-Technical Systems, Springer Publishing Company, 2014.
  296. R. Hilscher, “Review of A Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology (Wiley Series in Modeling and Simulation),” 2017, http://jasss.soc.surrey.ac.uk/20/1/reviews/2.html.
  297. Z. Wang, J. D. Butner, V. Cristini, and T. S. Deisboeck, “Integrated PK-PD and agent-based modeling in oncology,” Journal of Pharmacokinetics and Pharmacodynamics, vol. 42, no. 2, pp. 179–189, 2015. View at Publisher · View at Google Scholar · View at Scopus
  298. S. R. Sukumar and J. J. Nutaro, “Agent-based vs. equation-based epidemiological models: A model selection case study,” in Proceedings of the 2012 ASE International Conference on BioMedical Computing, BioMedCom 2012, pp. 74–79, December 2012. View at Publisher · View at Google Scholar · View at Scopus
  299. Y. Li, M. A. Lawley, D. S. Siscovick, D. Zhang, and J. A. Pagán, “Agent-based modeling of chronic diseases: a narrative review and future research directions,” Preventing Chronic Disease, vol. 13, no. 5, article no. E69, 2016. View at Publisher · View at Google Scholar · View at Scopus
  300. R. A. Nianogo and O. A. Arah, “Agent-based modeling of noncommunicable diseases: a systematic review,” American Journal of Public Health, vol. 105, no. 3, pp. e20–e31, 2015. View at Publisher · View at Google Scholar · View at Scopus
  301. G. Fioretti, “Agent-based simulation models in organization science,” Organizational Research Methods, vol. 16, no. 2, pp. 227–242, 2013. View at Publisher · View at Google Scholar · View at Scopus
  302. G. I. Hawe, G. Coates, D. T. Wilson, and R. S. Crouch, “Agent-based simulation for large-scale emergency response: a survey of usage and implementation,” ACM Computing Surveys, vol. 45, no. 1, article no. 8, 2012. View at Publisher · View at Google Scholar · View at Scopus
  303. R. B. Matthews, N. G. Gilbert, A. Roach, J. G. Polhill, and N. M. Gotts, “Agent-based land-use models: a review of applications,” Landscape Ecology, vol. 22, no. 10, pp. 1447–1459, 2007. View at Publisher · View at Google Scholar · View at Scopus
  304. D. C. Parker, S. M. Manson, M. A. Janssen, M. J. Hoffmann, and P. Deadman, “Multi-agent systems for the simulation of land-use and land-cover change: a review,” Annals of the Association of American Geographers, vol. 93, no. 2, pp. 314–337, 2003. View at Publisher · View at Google Scholar · View at Scopus
  305. W. Shen, Q. Hao, H. J. Yoon, and D. H. Norrie, “Applications of agent-based systems in intelligent manufacturing: an updated review,” Advanced Engineering Informatics, vol. 20, no. 4, pp. 415–431, 2006. View at Publisher · View at Google Scholar · View at Scopus
  306. F. Bousquet and C. Le Page, “Multi-agent simulations and ecosystem management: a review,” Ecological Modelling, vol. 176, no. 3-4, pp. 313–332, 2004. View at Publisher · View at Google Scholar · View at Scopus
  307. A. Negahban and L. Yilmaz, “Agent-based simulation applications in marketing research: an integrated review,” Journal of Simulation, vol. 8, no. 2, pp. 129–142, 2014. View at Publisher · View at Google Scholar · View at Scopus
  308. T. Ma and Y. Nakamori, “Modeling technological change in energy systems - From optimization to agent-based modeling,” Energy, vol. 34, no. 7, pp. 873–879, 2009. View at Publisher · View at Google Scholar · View at Scopus
  309. E. J. L. Chappin and G. P. J. Dijkema, “Agent-based modelling of energy infrastructure transitions,” International Journal of Critical Infrastructures, vol. 6, no. 2, pp. 106–130, 2010. View at Publisher · View at Google Scholar · View at Scopus
  310. V. Rai and A. D. Henry, “Agent-based modelling of consumer energy choices,” Nature Climate Change, vol. 6, no. 6, pp. 556–562, 2016. View at Publisher · View at Google Scholar · View at Scopus
  311. P. Ringler, D. Keles, and W. Fichtner, “Agent-based modelling and simulation of smart electricity grids and markets - A literature review,” Renewable & Sustainable Energy Reviews, vol. 57, pp. 205–215, 2016. View at Publisher · View at Google Scholar · View at Scopus
  312. R. Roche, B. Blunier, A. Miraoui, V. Hilaire, and A. Koukam, “Multi-agent systems for grid energy management: A short review,” in Proceedings of the 36th Annual Conference of the IEEE Industrial Electronics Society, IECON 2010, pp. 3341–3346, November 2010. View at Publisher · View at Google Scholar · View at Scopus
  313. P. Vrba, V. Marik, P. Siano et al., “A review of agent and service-oriented concepts applied to intelligent energy systems,” IEEE Transactions on Industrial Informatics, vol. 10, no. 3, pp. 1890–1903, 2014. View at Publisher · View at Google Scholar · View at Scopus
  314. F. Sensuß, M. Genoese, M. Ragwitz, and D. Möst, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, Working paper sustainability and innovation, 2007.
  315. R. Marks, “Chapter 27 market design using agent-based models,” in Handbook of Computational Economics, K. L. Judd, Ed., vol. 2, pp. 1339–1380, Elsevier, 2006. View at Google Scholar · View at Scopus
  316. J. Babic and V. Podobnik, “A review of agent-based modelling of electricity markets in future energy eco-systems,” in Proceedings of the 1st International Multidisciplinary Conference on Computer and Energy Science, SpliTech 2016, pp. 1–9, July 2016. View at Publisher · View at Google Scholar · View at Scopus
  317. J. G. Veneman, M. A. Oey, L. J. Kortmann, F. M. Brazier, and L. J. De Vries, “A review of agent-based models for forecasting the deployment of distributed generation in energy systems,” in Proceedings of the 2011 Grand Challenges on Modeling and Simulation Conference, pp. 16–21, Vista, CA, USA, June 2011. View at Scopus
  318. B. Chen and H. H. Cheng, “A review of the applications of agent technology in traffic and transportation systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 11, no. 2, pp. 485–497, 2010. View at Publisher · View at Google Scholar · View at Scopus
  319. A. L. C. Bazzan and F. Klügl, “A review on agent-based technology for traffic and transportation,” The Knowledge Engineering Review, vol. 29, no. 3, pp. 375–403, 2014. View at Publisher · View at Google Scholar · View at Scopus
  320. US Department of Transportation, “A Primer for Agent-Based Simulation and Modeling in Transportation Applications,” https://www.fhwa.dot.gov/advancedresearch/pubs/13054/13054.pdf.
  321. N. Ronald, R. Thompson, and S. Winter, “Simulating demand-responsive transportation: a review of agent-based approaches,” Transport Reviews, vol. 35, no. 4, pp. 404–421, 2015. View at Publisher · View at Google Scholar · View at Scopus
  322. G. B. Rens, A belief-desire-intention architechture with a logic-based planner for agents in stochastic domains, 2010.
  323. P. Taillandier, E. Amouroux, D. A. Vo, and A.-M. Olteanu-Raimond, “Using belief theory to formalize the agent behavior: application to the simulation of avian flu propagation,” in Principles and Practice of Multi-Agent Systems, N. Desai, A. Liu, and M. Winikoff, Eds., vol. 7057, pp. 575–587, Springer, Berlin, Germany, 2010. View at Publisher · View at Google Scholar · View at Scopus
  324. P. Taillandier, O. Therond, and B. Gaudou, “A new BDI agent architecture based on the belief theory. Application to the modelling of cropping plan decision-making,” in Proceedings of the 6th Biennial Meeting of the International Environmental Modelling and Software Society: Managing Resources of a Limited Planet, iEMSs 2012, pp. 2463–2470, July 2012. View at Scopus
  325. R. Walz, J. H. Köhle, C. Lerch, and J. H. Köhler, “Towards modelling of innovation systems: An integrated TIS-MLP approach for wind turbines,” Fraunhofer Institute for Systems and Innovation Research (ISI), 2016. View at Google Scholar
  326. L. Coenen, R. Raven, and G. Verbong, “Local niche experimentation in energy transitions: a theoretical and empirical exploration of proximity advantages and disadvantages,” Technology in Society, vol. 32, no. 4, pp. 295–302, 2010. View at Publisher · View at Google Scholar · View at Scopus
  327. GAMA User Manual, 2017, http://gama-platform.org/.
  328. B. Eckel, Thinking in Java, Prentice Hall, 4th edition, 2006.
  329. K. H. van Dam, I. Nikolic, and Z. Lukszo, Springer Science & Business Media, 2012.
  330. A. Drogoul, D. Vanbergue, and T. Meurisse, “Multi-agent based simulation: where are the agents?” in Multi-agent-based simulation II, vol. 2581, pp. 1–15, Springer, 2003. View at Publisher · View at Google Scholar · View at Scopus
  331. “Comparison of agent-based modeling software,” Wikipedia, 2017.
  332. D. B. Borenstein, “A composite constraints approach to declarative agent-based modeling,” 2015, https://arxiv.org/abs/1503.08880.
  333. G. Basso, N. Gaud, F. Gechter, V. Hilaire, and F. Lauri, “A framework for qualifying and evaluating smart grids approaches: focus on multi-agent technologies,” Smart Grid and Renewable Energy, vol. 4, no. 4, pp. 333–347, 2013. View at Publisher · View at Google Scholar
  334. Leopoldina - Nationale Akademie der Wissenschaften, acatech - Deutsche Akademie Technikwissenschaften, and Union der Deutschen Akademien der Wissenschaften, Consulting with energy scenarios: requirements for scientific policy advice, 2016.
  335. G. Verbong and D. Loorbach, Governing the Energy Transition, 2012. View at Scopus
  336. H. V. D. Parunak, R. Savit, and R. L. Riolo, “Agent-Based Modeling vs. Equation-Based Modeling: A Case Study and Users’ Guide,” in Multi-Agent Systems and Agent-Based Simulation, J. S. Sichman, R. Conte, and., and N. Gilbert, Eds., pp. 10–25, Springer, Berlin, Germany, 1998. View at Google Scholar
  337. M. Lengnick, “Agent-based macroeconomics: a baseline model,” Journal of Economic Behavior & Organization, vol. 86, pp. 102–120, 2013. View at Publisher · View at Google Scholar · View at Scopus
  338. N. Q. Huynh, H. X. Huynh, A. Drogoul, and C. Cambier, “Co-modeling: an agent-based approach to support the coupling of heterogeneous models,” in Nature of Computation and Communication, P. C. Vinh, E. Vassev, and M. Hinchey, Eds., vol. 144, pp. 156–170, Springer International Publishing, 2014. View at Google Scholar · View at Scopus
  339. A. Drogoul, N. Q. Huynh, and Q. C. Truong, “Coupling environmental, social and economic models to understand land-use change dynamics in the mekong delta,” Frontiers in Environmental Science, vol. 4, 2016. View at Publisher · View at Google Scholar
  340. A. Caiani, A. Russo, A. Palestrini, and M. Gallegati, Economics with Heterogeneous Interacting Agents: A Practical Guide to Agent-Based Modeling, Springer, 2016.
  341. R. A. Kelly et al., “Selecting among five common modelling approaches for integrated environmental assessment and management,” Environ. Model. Softw, vol. 47, pp. 159–181, 2013. View at Google Scholar
  342. B. de Vries, “Interacting with complex systems: models and games for a sustainable economy,” 2017, http://dspace.library.uu.nl/handle/1874/203530.
  343. P. J. Schoemaker and C. A. van der Heijden, “Integrating scenarios into strategic planning at Royal Dutch/Shell,” Planning Review, vol. 20, no. 3, pp. 41–46, 1992. View at Publisher · View at Google Scholar