Published Date
Abstract
Nowadays, forests are often managed for multiple uses. Forests are expected to produce reasonable incomes while at the same time promoting nature conservation and amenity values. There are also other characteristics that make natural resources decisionmaking situations complex. For example, group decision making and public participation are often required. To help decision makers make good choices, information and analyses are needed on the decision situation, on alternative choices of action, and on the consequences of alternative choices as well as on the preferences among these consequences. Multiple Criteria Decision Support (MCDS) methods are decision analysis tools that have been developed for dealing with all that information in order to support complex decision making with multiple objectives. In this chapter, some MCDS methods that recently have been applied to forestry or other natural resources management planning problems, and have been found to be promising, will be presented. In addition, some forestry applications are briefly described, and experiences gained using MCDS methods in forest management are discussed. Of the MCDS approaches, a closer look is taken at the Analytic Hierarchy Process, outranking methods, voting approaches, and the Stochastic Multicriteria Acceptability Analysis, because of their potentials for application. Applications for practically all MCDS methods with different qualities can be found in the field of natural resources decision support. However, no single method is best for all the decision support processes. The tool to be used should be chosen to fit the situation at hand: i.e., planning-case-wise consideration is always needed in order to build up an appropriate decision support process.
References
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Volume 6 of the series Managing Forest Ecosystems pp 37-70
Title
Multiple Criteria Decision Support Methods in Forest Management
An overview and comparative analyses
- Author
- Jyrki Kangas
- , Annika Kangas
Abstract
Nowadays, forests are often managed for multiple uses. Forests are expected to produce reasonable incomes while at the same time promoting nature conservation and amenity values. There are also other characteristics that make natural resources decisionmaking situations complex. For example, group decision making and public participation are often required. To help decision makers make good choices, information and analyses are needed on the decision situation, on alternative choices of action, and on the consequences of alternative choices as well as on the preferences among these consequences. Multiple Criteria Decision Support (MCDS) methods are decision analysis tools that have been developed for dealing with all that information in order to support complex decision making with multiple objectives. In this chapter, some MCDS methods that recently have been applied to forestry or other natural resources management planning problems, and have been found to be promising, will be presented. In addition, some forestry applications are briefly described, and experiences gained using MCDS methods in forest management are discussed. Of the MCDS approaches, a closer look is taken at the Analytic Hierarchy Process, outranking methods, voting approaches, and the Stochastic Multicriteria Acceptability Analysis, because of their potentials for application. Applications for practically all MCDS methods with different qualities can be found in the field of natural resources decision support. However, no single method is best for all the decision support processes. The tool to be used should be chosen to fit the situation at hand: i.e., planning-case-wise consideration is always needed in order to build up an appropriate decision support process.
References
- Alho, J.M. and Kangas, J. 1997. Analysing uncertainties in experts’ opinions of forest plan performance. Forest Science 43: 521–528.
- Alho, J.M., Kangas, J. and Kolehmainen, O. 1996. Uncertainty in the expert predictions of the ecological consequences of forest plans. Applied Statistics 45: 1–14.CrossRef
- Alho, J.M., Kolehmainen, O. and Leskinen, P. 2001. Regression methods for pairwise data. In: Schmoldt, D., Kangas, J., Mendoza, G.M. & Pesonen, M. (Eds.). The Analytic Hierarchy Process in Natural Resources and Environmental Decision Making. Kluwer Academic Publishers, Managing Forest Ecosystems 3. Pp. 235–252.
- Arrow, K. 1951. Social choice and individual values. Wiley, New York.
- Bana e Costa, C.A. 1986. A multicriteria decision aid methodology to deal with conflicting situations on the weights. European Journal of Operational Research 26: 22–34.CrossRef
- Bana e Costa, C.A. 1988. A methodology for sensitivity analysis in three criteria problems: A case study in municipal management. European Journal of Operational Research 33: 159–173.CrossRef
- Barzilai, J. and Lootsma, F.A. 1997. Power relations and group aggregation in the multiplicative AHP and SMART. Journal of Multi-Criteria Decision Analysis 6: 155–165.CrossRef
- Bouyssou, D. 1992. Ranking methods based on valued preference relations: a characterization of the net flow method. European Journal of Operational Research 60: 61–67.CrossRef
- Bouyssou, D. and Perny, P. 1992. Ranking methods for valued preference relations: a characterization of a method based on leaving and entering flows. European Journal of Operational Research 61: 186–194.CrossRef
- Bradshaw, J. M. and Boose, J. H. 1990. Decision analysis techniques for knowledge acquisition: combining information and preferences using Aquinas and Axotl. International Journal of Man-Machine Studies 32: 121–186.CrossRef
- Brains, S.T. and Fishburn, P. 1983. Approval voting. Birkhauser, Boston.
- Brans, J.P., Vincke, Ph. and Mareschal, B. 1986. How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research 24: 228–238.CrossRef
- Charnetski, J.R. & Soland, R.M. 1978. Multiple-attribute decision making with partial information: the comparative hypervolume criterion. Naval Research Logistics Quarterly 25: 279–288.
- Cooper, W.W., Seiford, L.M. and Tone, K. 2000. Data Envelopment Analysis. A comprehensive text with models, applications, references and DEA-solver sotfware. Kluwer Academic Publishers. 318 p.
- Cranor, L.F. 1996. Declared-strategy voting: an instrument for group decision making. Academic dissertation. http://www.research.att.com/-lorrie/pubs/diss/diss.html
- Crawford, G. and Williams, C. 1985. A note on the analysis of subjective judgment matrices. Journal of Mathematical Psychology 29: 387–405.CrossRef
- d’Avignon, G.R. and Vincke, Ph. 1988. An outranking method under uncertainty. European Journal of Operational Research 36: 311–321.CrossRef
- De Jong, P. 1984. A statistical approach to Saaty’s scaling method for priorities. Journal of Mathematical Psychology 28: 467–478.CrossRef
- Edwards, W. 1971. Social utilities. Engineering Economist. Summer Symposium Series 6: 119–129. Edwards, W. and Barron, F.H. 1994. SMARTS and SMARTER: Improved simple methods for multiattribute utility measurement. Organizational Behavior and Human Decision Processes 60: 306–325.CrossRef
- Forman, E. H. 1987. Relative vs. absolute worth. Mathematical Modelling 9 (3–5): 195–202.CrossRef
- Fraser, N.M. and Hauge, J.W. 1998. Multicriteria approval: application of approval voting concepts to MCDM problems. Journal of Multi-Criteria Decision Analysis 7: 263–272.CrossRef
- Gershon, M. E. and Duckstein, L. 1983. Multiobjective approaches to river basin planning Journal of Water Resource Planning 109: 13–28.CrossRef
- Gibbard, A. 1973. Manipulation of voting schemes: a general result. Econometrica 41: 587–601.CrossRef
- Goumas, M. and Lygerou, V. 2000. An extension of the PROMETHEE method for decision making in fuzzy environment: ranking of alternative energy exploitation projects. European Journal of Operational Research. 123: 606–613.CrossRef
- Guariso, G. and Werthner, H. 1989. Environmental decision support systems. Ellis Horwood. Chichester. 240 p.
- Hammond, J.S., Keeney, R.L. and Raiffa, H. 1998. Even Swaps: A rational method for making trade-offs. Harward Business Review, March-April. Pp. 1–11.
- Hinloopen, E. and Nijkamp, P. 1982. Information systems in an uncertain planning environment - some methods. Working paper 82–117, International Institute for Applied Systems Analysis.
- Hobbs, M., Hytönen, L. and Kangas, J. 2001. Factors affecting the economic sustainability of the nonindustrial private forest enterprise: a comparison of stakeholder perceptions. In: Väyrynen, J. & Niskanen, A. (eds.). International Symposium on Economic Sustainablity of Small-scale Forestry. IUFRO Working Unit 3.08.00: Small-scale Forestry. 20–26 March, 2001, Joensuu, Finland. Abstracts. p. 60.
- Hokkanen, J., Landelma, R. and Salminen, P. 2000. Multicriteria decision support in a technology competition for cleaning polluted soil in Helsinki. Journal of Environmental Management 60: 339–348.CrossRef
- Hokkanen, J., Landelma, R., Miettinen, K. & Salminen, P. 1998. Determining the implementation order of a general plan by using a multicriteria method. Journal of Multi-Criteria Decision Analysis 7: 273–284.CrossRef
- Hokkanen, J. and Salminen, P. 1997a. Choosing a solid waste management system using multicriteria decision analysis. European Journal of Operational Research 98: 19–36.CrossRef
- Hokkanen, J. and Salminen, P. 1997b. Locating a waste treatment facility by multicriteria analysis. Journal of Multi-Criteria Decision Analysis 6: 175–184.CrossRef
- Hokkanen, J. and Salminen, P. 1997e. ELECTRE III and IV decision aids in an environmental problem. Journal of Multi-Criteria Decision Analysis 6: 215–226.CrossRef
- Hämäläinen, R. and Lauri, H. 1995. Hipre3+ Users Guide. Helsinki University of Technology. Systems analysis Laboratory.
- Kajanus, M. 2001. Strategy and innovation model for the entrepreneurial forest owner. University of Joensuu, Faculty of Forestry. 44 p + 4 app. Doctoral thesis.
- Kangas, A., Kangas, J. and Pykäläinen, J. 2001. Outranking methods as tools in strategic natural resources planning. Silva Fennica 35: 215–227.
- Kangas, J. 1992. Metsikön uudistamisketjun valinta - monitavoitteiseen hyötyteoriaan perustuva päätösanalyysimalli. Summary: Choosing the regeneration chain in a forest stand: A decision model based on multi-attribute utility theory. University of Joensuu. Publications in Sciences 24. 230 p. Doctoral thesis.
- Kangas, J. 1993. A multi-attribute preference model for evaluating the reforestation chain alternatives of a forest stand. Forest Ecology and Management 59: 271–288.CrossRef
- Kangas, J. 1999. The analytic hierarchy process (AHP): Standard version, forestry application and advances. In: Helles, F., Holten-Andersen, P. & Wichmann, L. (Eds.). Multiple Use of Forests and Other Natural Resources. Kluwer Academic Publishers, Forestry Sciences 61. Pp. 96–105.
- Kangas, J., Store, R., Leskinen, P. and Mehtätalo, L. 2000. Improving the quality of landscape ecological forest planning by utilizing advanced decision-support tools. Forest Ecology and Management 132: 157–171.CrossRef
- Kangas, J., Hytönen, L. and Loikkanen, T. 2001a. Integrating the AHP and HERO into the process of participative natural resources planning. In: Schmoldt, D., Kangas, J., Mendoza, G.M. & Pesonen, M. (Eds.). The Analytic Hierarchy Process in Natural Resources and Environmental Decision Making. Kluwer Academic Publishers, Managing Forest Ecosystems 3. Pp. 131–148.
- Kangas, J., Pesonen, M., Kurttila, M. & Kajanus, M. 2001b. A’WOT: Integrating the AHP with SWOT analysis. In: Dellman, K. (Ed.). Proceedings of the Sixth International Symposium on the Analytic Hierarchy Process ISAHP2001, August 2–4, 2001, Kursaal Bern, Switzerland. Pp. 189–198.
- Kangas, J., Pukkala, T. and Kangas, A.S. 2001e. HERO: Heuristic Optimisation for Multi-Criteria Forestry Decision Analysis. In: Schmoldt, D., Kangas, J., Mendoza, G.A. & Pesonen, M. (Eds.). The Analytic Hierarchy Process in Natural Resource and Environmental Decision Making. Kluwer Academic Publishers, Managing Forest Ecosystems 3. Pp. 51–65.
- Kangas, J., Hokkanen, J., Kangas, A., Landelma, J. & Salminen, P. 2002. Applying stochastic multicriteria acceptability analysis to forest ecosystem management with both cardinal and ordinal criteria. Manuscript.
- Keeney, R. L. 1988. Value-driven expert systems for decision support Decision Support Systems 4: 405–412.CrossRef
- Kim, K.H. and Roush, R.W. 1980. Introduction to mathematical consensus theory. New York, Marcel Dekker.
- Kurttila, M., Pesonen, M., Kangas, J. and Kajanus, M. 2000. Utilizing the analytical hierarchy process (AHP) in SWOT analysis–A hybrid method and its application to a forest-certification case. Forest Policy and Economics 1: 41–52.CrossRef
- Landelma, R., Hokkanen, J. and Salminen, P. 1998. SMAA–Stochastic multiobjective acceptability analysis. European Journal of Operational Research 106: 137–143.CrossRef
- Landelma, R. and Salminen, P. 2001. SMAA-2: Stochastic multicriteria acceptability analysis for group decision making. Operations Research 49 (3): 444–454.CrossRef
- Lakeman, E 1974. How democracies vote: a study of electoral systems. Faber & Faber, London, 4`h edition.
- Laukkanen, S., Kangas, A. and Kangas, J. 2002. Applying voting theory in natural resource management: a case of multiple-criteria group decision support. Journal of Environmental Management 64: 127137.
- Leclercq, J.P. 1984. Propositions d’extension de la notion de dominance en présence de relations d’ordre sur le pseudo-critères: MELCHIOR. Mathematical Social Sciences 8: 45–61.CrossRef
- Leskinen, P. 2001. Statistical methods for measuring preferences. University of Joensuu, Publications in Social Sciences 48. 111 p. Doctoral thesis.
- Leskinen, P. and Kangas, J. 1998. Analysing uncertainties of interval judgement data in multiple-criteria evaluation of forest plans. Silva Fennica 32: 363–372.
- Leung, L.C. and Cao, D. 2000. On consistency and ranking of alternatives in fuzzy AHP. European Journal of Operational Research. 124: 102–113.CrossRef
- Maystre, L.Y., Pictet, J. and Simos, J. 1994. Méthodes multicritères ELECTRE. Presses Polytechniques et Universitaires Romandes. Lausanne.
- Mendoza, G.A. and Prabhu, R. 2001. A fuzzy Analytic Hierarchy Process for assessing biodiversity conservation. In: Schmoldt, D., Kangas, J., Mendoza, G.A. & Pesonen, M. (Eds.). The Analytic Hierarchy Process in Natural Resource and Environmental Decision Making. Kluwer Academic Publishers, Managing Forest Ecosystems 3. Pp. 219–235.
- Miettinen, K. and Salminen, P. 1999. Decision-aid for discrete multiple criteria decision making problems with imprecise data. European Journal of Operational Research 119: 50–60.CrossRef
- Miettinen, K., Landelma, R. and Salminen, P. 1999. SMAA-O - Stochastic multicriteria acceptability analysis with ordinal criteria. University of Jyväskylä. Reports of the Department of Mathematical Information Technology Series B. Scientific Computing No. B 5.
- Mueller, D.C. 1989. Public choice IL Cambridge University Press, New York.
- Munda, G. 1995. Multicriteria evaluation in a fuzzy environment. Springer-Verlag, New York.CrossRef
- Nurmi, H. 1987. Comparing voting systems. D. Reidel Publishing Company, Dordrecht.
- O’Keefe, R. M. 1988. Artificial intelligence and the management science practitioner: expert systems and MS/OR methodology (Good News and Bad). Interfaces 18 (6): 105–113.CrossRef
- Ozernoy, V. M. 1992. Choosing the ‘best’ multiple criteria decision-making method. INFOR 30: 159–171.
- Pirlot, M. 1995. A characterization of ‘Min’ as a procedure for exploiting valued preference relations and related results. Journal of Multi-Criteria Decision Analysis 4: 37–56.CrossRef
- Pesonen, M., Ahola, J., Kurttila,M., Kajanus, M. and Kangas, J. 2001a. Applying A’WOT to Forest Industry Investement Strategies: Case Study of a Finnish Company in North America. In: Schmoldt, D., Kangas, J., Mendoza, G.A. & Pesonen, M. (Eds.). The Analytic Hierarchy Process in Natural Resource and Environmental Decision Making. Kluwer Academic Publishers, Managing Forest Ecosystems 3. Pp. 131–148.
- Pesonen, M., Kurttila, M., Kangas, J., Kajanus, M. and Heinonen, P. 2001b. Assessing the priorities among resource management strategies at the Finnish Forest and Park Service. To appear in Forest Science.
- Pukkala, T. 1993. Monikäytön suunnitteluohjelmisto MONSU. Ohjelmiston toiminta ja käyttö. Mimeograph. University of Joensuu, Faculty of Forestry. 42 p.
- Pukkala, T. and Kangas, J. 1993. A heuristic optimization method for forest planning and decision-making. Scandinavian Journal of Forest Research 8: 560–570.CrossRef
- Pykäläinen, J., Kangas, J. and Loikkanen, T. 1999. Interactive decision analysis in participatory strategic forest planning: experiences from State owned boreal forests. Journal of Forest Economics 5: 341–364.
- Raju, K.S. and Pillai, C.R.S. 1999a. Multicriteria decision making in performance evaluation of an irrigation system. European Journal of Operational Research 112: 479–488.CrossRef
- Raju, K.S. and Pillai, C.R.S. 1999b. Multicriteria decision making in river basin planning and development. European Journal of Operational Research 112: 249–257.CrossRef
- Reynolds, K.M. 2001. Prioritizing salmon habitat restoration with the AHP, SMART, and uncertain data. In: Schmoldt, D., Kangas, J., Mendoza, G.M. & Pesonen, M. (Eds.). The Analytic Hierarchy Process in Natural Resources and Environmental Decision Making. Kluwer Academic Publishers, Managing Forest Ecosystems 3. Pp. 199–218.
- Riker, W.H. 1982. Liberalism against populism. Waweland Press, Inc, Prospect Heights.
- Rietveld, P. and Ouwersloot, H. 1992. Ordinal data in multicriteria decision making, a stochastic dominance approach to siting nuvlear power plants. European Journal of Operational Research 56: 249–262.CrossRef
- Rogers, M. and Bruen, M. 1998a. A new system for weighting environmental criteria for use within ELECTRE III. European Journal of Operational Research 107: 552–563.CrossRef
- Rogers, M. and Bruen, M. 1998b. Choosing realistic values of indifference, preference and veto thresholds for use with environmental criteria within ELECTRE. European Journal of Operational Research 107: 542–551.CrossRef
- Roubens, M. 1980. Analyse et agrégation des préférences: modélisation, ajustement et résumé de données relationnelles. Revue Belge de Statistique, d’Informatique, et de Reserche Opérationelle 20: 36–67.
- Roy, B. 1968. Classement et choix en présence de points de vue multiples (la méthode ELECTRE). Revue Française d’Informatique et de Recherche Opérationnelle 8: 57–75.
- Roy, B. 1991. The outranking approach and the foundations of Electre methods. Theory and Decision 31: 49–73.CrossRef
- Saari, D.G. 1994. Geometry of voting, volume 3 of Studies in Economic Theory. Springer-Verlag, New York.
- Saaty, T.L. 1977. A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology 15: 234–281.CrossRef
- Saaty, T. L. 1980. The Analytic Hierarchy Process. McGraw-Hill, New York. 287 p.
- Saaty, T.L. 2001. Decision Making With Dependance And Feedback. The Analytic Network Process. 2°d edition. RWS Publications. 376 p.
- Salminen, P., Hokkanen, J. and Landelma, R. 1998. Comparing multicriteria methods in the context of environmental problems. European Journal of Operational Research 104: 485–496.CrossRef
- 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.CrossRef
- Schmoldt, D., Kangas, J., Mendoza, G.A. and Pesonen, M. (Eds.). 2001. The Analytic Hierarchy Process in Natural Resource and Environmental Decision Making. Kluwer Academic Publishers, Managing Forest Ecosystems 3. 305 p.
- Tarp, P. and Helles, F. 1995. Multi-criteria decision-making in forest management planning. Journal of Forest Economics 1: 273–306.
- Vincke, Ph. 1992. Multi-criteria decision aid. John Wiley & Sons. 154 p.
- von Winterfeldt, D. 1988. Expert systems and behavioral decision research. Decision Support Systems 4: 461–471.CrossRef
- von Winterfeldt, D. and Edwards, W. 1986. Decision analysis and behavioral research. Cambridge University Press. Cambridge. 604 p.
- Voogd, H. 1983. Multicriteria Evaluation for Urban and Regional Planning; Pion, London.
- Zanakis, S.H., Solomon, A., Wishart, N. and Dublish, S. 1998. Multi-attribute decision making. A simulation comparison of select methods. European Journal of Operational Research 107: 507–529.CrossRef
- Yu, W. 1992. Aide multicritère à la décision dans le cadre de la problématique du tri: méthodes et applications. PhD thesis, LAMSADE, Université Paris-Dauphine, Paris.
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