Voting Methods

  • Annika Kangas
  • Mikko Kurttila
  • Teppo Hujala
  • Kyle Eyvindson
  • Jyrki Kangas
Part of the Managing Forest Ecosystems book series (MAFE, volume 30)


For many participatory planning cases, the use of voting methods may be an effective approach. Voting methods have long traditions in making social choices – the main difference between group multi-criteria analysis and voting typically is that in voting the judgments are carried out holistically, without decomposing the problem to criteria. Because of the similarities behind group decision-making and voting, there are also several decision support tools that share properties from both these two approaches. In this chapter, we first present evaluation criteria for voting systems. After that, we describe many common voting schemes that could be utilised in forest planning. Finally, we present some decision support tools for multi-criteria planning based on voting theory such as multi-criteria approval and multi-criteria approval voting.


Democracy principles Criteria for voting schemes Approval voting Borda count Condorcet winner Multi-criteria approval Fuzzy voting Probability voting 


  1. Arrow, K. (1951). Social choice and individual values. New York: Wiley.Google Scholar
  2. Black, D. (1976). Partial justification of the Borda count. Public Choice, 28, 1–15.CrossRefGoogle Scholar
  3. Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukiàs, A., & Vincke, P. (2000). Evaluation and decision models – A critical perspective. Boston: Kluwer Academic Publishers.CrossRefGoogle Scholar
  4. Brams, S. T., & Fishburn, P. (1983). Approval voting. Boston: Birkhauser.Google Scholar
  5. Copeland, A. H. (1951). A ‘reasonable’ social welfare function, mimeographed. In Seminar on Applications of Mathematics to the Social Sciences, University of Michigan, Ann Arbor, MI.Google Scholar
  6. Cranor, L. F. (1996). Declared-strategy voting: An instrument for group decision making. Academic dissertation.
  7. de Borda, J.-C. (1781). Mathematical derivation of an election system. Isis, 44, 42–51. English translation by A. de Grazia (1953).Google Scholar
  8. de Condorcet, M. (1785). Essai sur l’application de l’analyse à la probabilité des décisions rendues à la pluralité des voix (Essay on the Application of the Analysis to the Probability of Majority Decisions). Paris: De l’Imprimerie royale.Google Scholar
  9. Felsenthal, D. S. (1989). On combining approval with disapproval voting. Behavioral Science, 34, 53–60.CrossRefGoogle Scholar
  10. Fraser, N. M., & Hauge, J. W. (1998). Multicriteria approval: Application of approval voting concepts to MCDM problems. Journal of Multi-Criteria Decision Analysis, 7, 263–272.CrossRefGoogle Scholar
  11. García-Lapresta, J. L., & Martínez-Panero, M. (2002). Borda count versus approval voting: A fuzzy approach. Public Choice, 112, 167–184.CrossRefGoogle Scholar
  12. Gerhlein, W. V., & Lepelley, D. (2001). The Condorcet efficiency of Borda Rule with anonymous voters. Mathematical Social Sciences, 41, 39–50.CrossRefGoogle Scholar
  13. Gibbard, A. (1973). Manipulation of voting schemes: A general result. Econometrica, 41, 587–601.CrossRefGoogle Scholar
  14. Heckelman, J. C. (2003). Probabilistic Borda rule voting. Social Choice and Welfare, 21, 455–468.CrossRefGoogle Scholar
  15. Hiltunen, V., Kangas, J., & Pykäläinen, J. (2008). Voting methods in strategic forest planning — Experiences from Metsähallitus. Forest Policy and Economics, 10, 117–127.CrossRefGoogle Scholar
  16. Hiltunen, V., Kurttila, M., Leskinen, P., Pasanen, K., & Pykäläinen, J. (2009). Mesta – Internet application for supporting discrete choice situations in strategic level participatory natural resources planning. Forest Policy and Economics, 11, 1–9.CrossRefGoogle Scholar
  17. Kacprzyk, J., Fedrizzi, M., & Nurmi, H. (1992). Group decision making and consensus under fuzzy preferences and fuzzy majority. Fuzzy Sets and Systems, 49, 21–31.CrossRefGoogle Scholar
  18. Kangas, A., Laukkanen, S., & Kangas, J. (2006a). Social choice theory and its applications in sustainable forest management – A review. Forest Policy and Economics, 9, 77–92.CrossRefGoogle Scholar
  19. Kangas, A., Kangas, J., & Laukkanen, S. (2006b). Fuzzy multicriteria approval method and its application to two forest planning problems. Forest Science, 52, 232–242.Google Scholar
  20. Kant, S., & Lee, S. (2004). A social choice approach to sustainable forest management: An analysis of multiple forest values in Northwestern Ontario. Forest Policy and Economics, 6, 215–227.CrossRefGoogle Scholar
  21. Kim, K. H., & Roush, R. W. (1980). Introduction to mathematical consensus theory. New York: Marcel Dekker.Google Scholar
  22. Laukkanen, S., Kangas, A., & Kangas, J. (2002). Applying voting theory in natural resource management: A case of multiple-criteria group decision support. Journal of Environmental Management, 64, 127–137.CrossRefPubMedGoogle Scholar
  23. Laukkanen, S., Palander, T., & Kangas, J. (2004). Applying voting theory in participatory decision support for sustainable timber-harvesting. Canadian Journal of Forest Research, 34, 1511–1524.CrossRefGoogle Scholar
  24. Laukkanen, S., Palander, T., Kangas, J., & Kangas, A. (2005). Evaluation of the multicriteria approval method for timber-harvesting group decision support. Silva Fennica, 39, 249–264.CrossRefGoogle Scholar
  25. Martin, W. E., Schields, D. J., Tolwinski, B., & Kent, B. (1996). An application of social choice theory to U.S.D.A. Forest Service decision making. Journal of Policy Modelling, 18, 603–621.CrossRefGoogle Scholar
  26. Mueller, D. C. (1989). Public choice II. New York: Cambridge University Press.Google Scholar
  27. Nurmi, H. (1987). Comparing voting systems. Dordrecht: D. Reidel Publishing Company.CrossRefGoogle Scholar
  28. Nurmi, H., Kacprzyk, J., & Fedrizzi, M. (1996). Probabilistic, fuzzy and rough concepts in social choice. European Journal of Operational Research, 95, 264–277.CrossRefGoogle Scholar
  29. Pasanen, K., Kurttila, M., Pykäläinen, J., Kangas, J., & Leskinen, P. (2005). Mesta – Non-industrial private forest landowners’ decision support for the evaluation of alternative forest plans over the Internet. International Journal of Information Technology and Decision Making, 4, 601–620.CrossRefGoogle Scholar
  30. Reynolds, A., & Reilly, B. (1997). The international IDEA handbook of electoral system design. Stockholm: International Institute for Democracy and Electoral Assistance.Google Scholar
  31. Riker, W. H. (1982). Liberalism against populism. Prospect Heights: Waweland Press, Inc.Google Scholar
  32. Saari, D. G. (1994). Geometry of voting (Studies in economic theory, Vol. 3). New York: Springer.Google Scholar
  33. Saari, D. G., & van Newnhizen, J. (1988). The problem of indeterminacy in approval, multiple and truncated voting systems. Public Choice, 59, 101–120.CrossRefGoogle Scholar
  34. Satterthwaite, M. A. (1975). Strategy-proofness and Arrow’s conditions: Existence and correspondence theorems for voting procedures and social welfare functions. Journal of Economic Theory, 10, 187–217.CrossRefGoogle Scholar
  35. Sen, A. K. (1997). On economic inequality. Oxford: Oxford University Press.Google Scholar
  36. Simpson, P. (1969). On defining areas of voter choice: Professor Tullock on Stable Voting. Quarterly Journal of Economics, 83, 478–490.CrossRefGoogle Scholar
  37. Vainikainen, N., Kangas, A., & Kangas, J. (2008). Empirical study on voting power in participatory forest planning. Journal of Environmental Management, 88, 173–180.CrossRefPubMedGoogle Scholar
  38. Yilmaz, M. R. (1999). Can we improve upon approval voting? European Journal of Political Economy, 15, 89–100.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Annika Kangas
    • 1
  • Mikko Kurttila
    • 2
  • Teppo Hujala
    • 3
  • Kyle Eyvindson
    • 4
  • Jyrki Kangas
    • 5
  1. 1.Economics and SocietyNatural Resources Institute Finland (Luke)JoensuuFinland
  2. 2.Bio-based Business and IndustryNatural Resources Institute Finland (Luke)JoensuuFinland
  3. 3.Bio-based Business and IndustryNatural Resources Institute Finland (Luke)HelsinkiFinland
  4. 4.Department of Forest SciencesUniversity of HelsinkiHelsinkiFinland
  5. 5.School of Forest SciencesUniversity of Eastern FinlandJoensuuFinland

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