Published Feb 28, 2018
Aregai Tecle Gustavo Perez-Verdin


A very important aspect of natural resources management is determining optimal budget allocation to satisfy the needs and aspirations of multiple stakeholders. This is especially the case in developing countries like Mexico where budgetary funds are in short supply. There has been an increasing debate in Durango, Mexico, for example, about determining the most efficient way of allocating a budget for multi-purpose forest management. The debate has been triggered by a growing number of interests and stakeholders, which in addition to optimal timber production, have the desire to improve environmental conditions, water resource development, range and other non-timber resources production, and to provide better amenity values and expanded recreational opportunities. CONAFOR (COmisión NAcionale FORestal), the Mexican agency in charge of allocating funds to promote sustainable forest resources development, has been implementing four national programs: developments of forest resources, tree plantations, non-timber products, and water resources.  In addition to these programs, the forest resources management decision-making process involves four interest groups and six management objectives independently connected in a hierarchical framework.  Accordingly, the most suitable multi-objective/multi-criterion decision-making (MODM/MCDM) technique for optimal allocation of scarce budgetary funds among the four natural resources development programs is the Analytic Hierarchy Process (AHP).  The two programs that receive the most funds are forest resources development and water resources/ environmental services development.  In this way, the AHP can be used to optimally distribute scarce financial resources among competing programs to improve regional economic development and better satisfy the needs of various interest groups.


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Multiobjective forest management, CONAFOR, forest budget allocation, Mexican community forestry, utility model, ejido

Alcorn, J.B. and Toledo, V.M. (1998). Resilient resource management in Mexico's forest ecosystems: the contribution of property rights. In F. Berkes and C. Folke (Eds), Linking social and ecological systems: management practices and social mechanisms for building resilience (216-249). Cambridge, U.K: Cambridge University Press.

Alonso, J.A., and Lamata, M.T. (2006). Consistency in the Analytic Hierarchy Process: A new approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 14(4). Doi: 10-1142/S0218488506004126.

Ananda, J. and Herath, G. (2009). A critical review of multi-criteria decision making methods with special references to forest management and planning. Ecological economics, 68(10), 2535-2548. Doi:

Ansah, R.H., Sorooshian, S. and Bin Mustafa, S. (2015). Analytic Hierarchy Process decision making algorithm. Global Journal of Pure and Applied Mathematics, 11(4) 2015. http///

Balteiro, L.D., and Romero, C. (2008). Making forestry decisions with multiple criteria: A review and assessment. Forest Ecology and Management, 255(2008), 3222-3241. Doi:

Balteiro, L.D., Gonzalez-Pachon, J. and Romero, C. (2009). Forest management with multiple criteria and multiple stakeholders: An application to two public forests in Spain. Scandinavian Journal of Forest Research, 24(1), 87-93. Doi:

Balteiro, L.D. Romero, C. (2001). Combined use of goal programming and the Analytic Hierarchy Process in forest management. In D.L. Schmoldt, J. Kangas, G.A. Mendoza, and M. Pesonen (Eds), The Analytic Hierarchy Process in Natural Resource and Environmental Decision-Making (81-95). Norwell, MA : Kluwer Academic Publishers. Doi:

Bradford, J.B and D’Amato, A.W. (2012). Recognizing trade-offs in multiple-objective land management. Frontiers in Ecology and the Environment, 10(4), 210-216. Doi: 10.1890/110031. Doi: 10.1890/110031

Cheng, E.W.L., and Li, H. (2004). Contractor selection using the Analytic Network Process. Construction Management and Economics, 2004(22), 1021-1032. Doi:

Chiou, C.W., Chen, C.C. and Chiou, S.C. (2009). A decision-making model of budget allocation for the restoration of traditional settlement buildings. International Conference on Management and Service Science on 20-22 Sept. 2009 in Wuhan, China. Doi: 10.1109/ICMSS.2009.5303265

Duckstein, L. and A. Tecle. (1993a). Multiobjective Analysis in Water Resources: Part II - A New Typology of MCDM Techniques. In: Marco, Harboe and Salas (eds.), Stochastic Hydrology and its Use in Engineering. Kluwer Academic Publishers, Dordrecht, The Netherlands. pp. 333-344. Doi:

Duckstein, L., and Tecle, A. (1993b). Multiobjective analysis in water resources: Part I – Numerical versus non-numerical and discrete versus continuous alternatives. In: Marco, Harboe and Salas (Eds.), Stochastic Hydrology and its Use in Engineering (319-332). Dordrecht, The Netherlands: Kluwer Academic Publishers. Doi:

Duckstein, L. and Tecle, A. (2002). Multicriterion analysis in water resources management. In H.H.G. Savenije and A.Y. Hoeksta (Eds.), Water resources management, Encyclopedia of life support systems (EOLSS), Oxford, UK: UNESCO, EOLSS Publishers. Doi:

Duke, J.M., and Aull-Hyde, R. (2002). Identifying public preferences for land preservation using the Analytic Hierarchy Process. Ecological Economics, 42, 131-145. Doi:

Ford, R.M., Anderson, N,M, Nitschke, C., Bennet, L.T. and Williams, K.J.H. (2017). Psychological values and cues as a basis for developing socially relevant criteria and indicators for forest management. Forest Policy and Economics, 78(2017), 141-150. Doi:

Forman, E. and , Peniwati, K. (1998). Aggregating individual judgments and priorities with the Analytic Hierarchy Process. European Journal of Operational Research, 108(1),165-169. Doi:

Groselj, P., Hodges, D.G. and Stirn, L.Z. (2016). Participatory and multi-criteria analysis for forest (ecosystem) management: A case study of Pohorje, Slovenia. Forest Policy and Economics, 71(2016), 80–86. Doi:

Hajkowicz, S., and Higgins. A. (2006). A comparison of multiple criteria analysis techniques for water resource management. European Journal of Operational Research, 184(2008), 255–265. Doi:

Hossain, S.M. Y., and Robak. E.W. (2010). A forest management process to incorporate multiple objectives: a framework for systematic public input. Forests, 1, 99-113. Doi: 10.3390/f1030099

Ishizaka, A., and Labib. A. (2011). Review of the main developments in the Analytic Hierarchy Process. Expert Systems with Applications, 38(11), 14336–14345. Doi:

Jenkins, T. (2005). Multi-objective forest planning. Forestry, 78(4),457-458. Doi:
Kangas, J. (1992). Multiple-use planning of forest resources by using the Analytic Hierarchy Process. Scandinavian Journal of Forest Research, 7, 259-268. Doi:

Kangas, J. (1994). An approach to public participation in strategic forest management planning. Forest Ecology and Management, 70, 75-88. Doi:

Kangas, J. (1999). The Analytic Hierarchy Process (AHP): Standard version, forestry applications and advances. In F. Helles, P. Holten-Andersen, and L. Wichmann (Eds), Multiple use of forests and other natural resources (96-105). Norwell, MA: Kluwer Academic Publishers. Doi:

Kangas, J., Kangas, A., Leskinen, P. and Pykalainen, J. (2001). MCDM methods in strategic planning of forestry on state-owned lands in Finland: applications and experiences. Journal of Multi-Criteria Decision Analysis, 10(5), 257-271. Doi: 10.1002/mcda.306

Krcmar, E, Van Kooten, G.C., Vertinsky, I. (2005). Managing forest and marginal agricultural land for multiple trade-offs: compromising on economic, carbon and structural diversity objectives. Ecological Modelling, 185(2), 451-468. Doi:

Leskinen, P. (2000). Measurement scales and scale independence in the Analytic Hierarchy Process. Journal of Multicriteria Decision Analysis, 9(4), 163. Doi: 10.1002/1099-1360(200007)9:4<163::AID-MCDA274>3.0.CO;2-L

Macharis, C., Springael, J., De Brucker, K. and Verbeke, A. (2004). Promethee and AHP: The design of operational synergies in multicriteria analysis. Strengthening Promethee with ideas of AHP. European Journal of Operational Research, 153, 307?317. Doi:

Mardani, A., Jusoh, A., Nor, K., Khalifah, Z., Zakwan, N. & Valipour, A. (2015). Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014. Economic Research-Ekonomska Istraživanja, 28(1), 516-571. Doi: https:/doi/full/10.1080/ 1331677X.2015.1075139.

Mendoza, G., and Prabhu, R. (2000). Multiple criteria decision making approaches to assessing forest sustainability using criteria and indicators: A case study. Forest Ecology and Management, 131(1-3), 107-126. Doi:

Moseley, K.R., Ford, W.M., Edwards, J.W. and Strager, M.P. (2009). A multi-criteria decision making approach for management indicator species selection on the Monongahela National forest, West Virginia. USDA Forest Service Northern Research Station, Research Paper NRS-12. Doi:

Napoli, G., and Schilleci, F. (2014). Application of an Analytic Network Process in the planning process: The case of an urban transformation in Palermo (Italy). A conference paper. Doi: 10.1007/978-3-319-09150-1_22.

Nilsson, H., Nordstrom, E.M. and Ohman, K. (2016). Decision support for participatory forest planning using AHP and TOPSIS. Forests, 7(5), 100. Doi: 10.3390/f7050100.

Niemela, J., J. Young, D. Alard, M. Askasibar, K. Henle, R. Johnson, M. Kurttila, T.B. Larsson, S. Matouch, P. Nowicki, R. Paiva, L. Portoghesi, R. Smilders, A. Stevenson, U. Tartes, and A. Watt. (2005). Identifying, managing and monitoring conflicts between forest biodiversity conservation and other human interests in Europe. Forest Policy and Economics, 7(2005), 877-890. Doi:

Nordstrom, E.V. (2010). Integrating multiple criteria decision analysis into participatory forest planning. A doctoral thesis for the Department of Forest Resources Management, Swedish University of Agricultural Sciences, Umea, Sweden. Doi:

Ozdemir, Y., Basligil, H. and Karaca, M. (2011). Aircraft selection using analytic network process: A case for Turkish Airlines. Proceedings of the World Congress on Engineering, II, London, U.K.

Perez-Verdin G., Navar-Chaidez, J.J., Kim, Y-S and Silva-Flores, R. (2011). Valuing watershed services in Mexico's temperate forests. Modern Economy, 2(5),769-779. Doi: 10.4236/me.2011.25085

Pérez-Verdín, G., Hernández-Díaz, J.C., Márquez-Linares, M.A. and Tecle, A. (2009). Aplicación de técnicas multicriterio en el manejo integral forestal en Durango, México. Madera y bosques, 15(1), 1405-0471. Doi:

Phua, M.H., and Minowa, M. (2005). A GIS- based multi-criteria decision making approach to forest conservation planning at a landscape scale: A case study in the Kinabalu area, Sabah, Malaysia. Landscape and Urban Planning, 71(2-4), 207-222. Doi:

Poff, B., Tecle, A. Neary, D.G. and Geils, B. (2010). Compromise programming in forest management. Journal of the Arizona-Nevada Academy of Science, 42(1), 44-60. Doi:

Poff, B., Tecle, A. Neary, D. and Geiles, B. (2012). Spatio-temporal multi-objective decision making in forest management., In C. Van Riper III, M. Villarreal, C. van Riper, and M. Johnson (Eds.), The Colorado Plateau V: Research, environmental planning, and management for collaborative conservation (121-129). Tuscon, AZ: The University of Arizona Press. Doi: 10.2307/j.ctt183pc7f

Proctor, W. (2005). Valuing forest resources using multi-criteria decision analysis and stakeholder participation. In. Michael Getzner, M., C. Spash, and S. Stagl (Eds.), Developing alternatives for valuing nature: Part II: Taking multiple criteria into account. London, UK: Routledge.

Rhoda, R. and Burton, T. (2010). Geo-Mexico: the geography and dynamics of modern Mexico. Canada: Sombrero Books.

Saaty, T.L. (2017). The Analytic Network Process. Download from at 0:40+0430 on Wednesday April 26, 2017.

Saaty, T. L. (2010). Principia Mathematica Decernendi: Mathematical Principles of Decision Making. Pittsburgh, PA: RWS Publications. ISBN 978-1-888603-10-1.

Saaty, T. L. (2008a). Measurement and its generalization in decision making: Why pairwise comparisons are central in mathematics for the measurement of intangible factors - The Analytic Hierarchy/Network Process. RACSAM (Review of the Royal Spanish Academy of Sciences, Series A, Mathematics), 102 (2), 251–318. Doi:

Saaty, T. L. (2008b). Decision making with the Analytic Hierarchy Process. International Journal Services Sciences, 1(1), 83-98. Doi: 10.1504/IJSSCI.2008.017590

Saaty, T.L. (2003). Decision-making with the AHP: Why is the principal eigenvector necessary. European Journal of Operational Research, 145(1), 85-91. Doi:

Saaty, T. L. (2001). Fundamentals of the Analytic Hierarchy Process. In D.L Schmoldt, J. Kangas, G.A. Mendoza, and M. Pesonen (Eds), The Analytic Hierarchy Process in natural resource and environmental decision making (15-35). Norwell, MA: Kluwer Academic Publishers. Doi:

Saaty, T.L. (1998). Ranking by eigenvector versus other methods in the Analytic Hierarchy Process. Applied Mathematics Letters, 11(4),121-125. Doi:

Saaty, T.L. (1997). That is not the Analytic Hierarchy Process: what the AHP is and what it is not. Journal of Multi-Criteria Decision Analysis, 6(6), 324-335. Doi: 10.1002/(SICI)1099-1360(199711)6:6<324::AID-MCDA167>3.0.CO;2-Q

Saaty, T.L. (1990). How to make a decision: The Analytic Hierarchy Process. European Journal of Operational Research, 48, 9-26. Doi:

Saaty, T. L. (1988). Multicriteria decision making: The Analytic Hierarchy Process. Pittsburgh, PA: RWS Publications.

Saaty, T. L. (1980). The Analytic Hierarchy Process. Planning priority setting, resource allocation. New York, NY: McGraw-Hill Inc. Doi:

Saaty, T.L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15, 234-281. Doi:

Saaty, T. L.. and Vargas, L.G. (2006). Decision making with the Analytic Network Process: Economic, political, social and technological applications with benefits, opportunities, costs and risks. New York: Springer.

Saaty, T. and Vargas, L.G. (1982). The logic of priorities. Boston: Kluwer-Nijhoff. Doi:

Sadeghi, M., Rashidzadeh, M.A. and Soukhakian, M.A. (2012). Using Analytic Network Process in a group decision-making for supplier selection. Informatica, 23(4), 621-643.

Schmoldt, D.L., Kangas, J. and Mendoza, G.A. (2001a). Basic principles of decision making in natural resources and the environment. In D.L Schmoldt, J. Kangas, G.A. Mendoza, and M. Pesonen (Eds),The Analytic Hierarchy Process in natural resource and environmental decision making (1-13). Dordrecht, The Netherlands: Kluwer Academic Publishers. Doi:

Schmoldt, D.L., Kangas, J. and Mendoza, G.A. and Pesonen, M. (2001b). Strategic and tactical planning for managing national park resources. In Schmoldt et al. (Eds.), The Analytic Hierarchy Process in Natural Resource and Environmental Decision-Making (67-79) Dordrecht, The Netherlands : Kluwer Academic Publishers. Doi:

Semarnat. (2000). Strategic forest program 2025. (Secretaria de Medio Ambiente y Recursos Naturales). Available at ENG/pdf/19.pdf (last time visited June 7, 2004).

Špor?i?, M. (2012). Application of multi-criteria methods in natural resources management - A focus on forestry: Chapter 22. In Jorge Martin Garcia and Julio Javier Diez (Eds.), Sustainable forest management - Current research. Casero, Doi: 10.5772/23667

Špor?i?, M., Landeki?, M. Lovri?, M. Bogdan, S. and Šegoti?, K. (2010). Multi-criteria decision-making in forestry - methods and experiences. Sumarski List, 134(5-6), 275-284.

Tecle, A. (2007). Sustainable natural resources management in an era of global climate change. Forum on Public Policy, 3(4), 443-454.

Tecle, A. (1992). Selecting a multicriterion decision making technique for watershed resources management. Water Resources Bulletin, 28(1), 129-140. Doi: 10.1111/j.1752-1688.1992.tb03159.x

Tecle, A., and Duckstein, L. (1994). Concepts of multicriterion decision- making, Chapter 3. In H.P. Nachtnebel (Ed.), Decision support system in water resources management (33-62) Paris, France: UNESCO Press.

Tecle, A., and Jibrin, S. (2012). Incorporating fuzzy logic and stochastic processes in multiobjective forest management. Hydrology and Water Resources in Arizona and the Southwest, 41, 41-45.

Tecle, A., Shrestha, B. and Duckstein, L. (1998). Multiobjective decision support system for multiresource forest management. Group Decision and Negotiation, 7, 23-40. Doi:

Tecle, A., Szidarovszky, F. and Duckstein, L. (1995). Conflict analysis in multi-resource forest management with multiple decision-makers. Nature & Resources, 31(3), 8-17.

Thangamani, G. (2012). Technology selection for product innovation using Analytic Network Process (ANP) - A ccase study. International Journal of Innovation, Management and Technology. 3(5), 560-565. Doi: 10.7763/IMT.2012.V3.298.

Triantaphyllou, E. (2000). Multi-criteria decision making methods: A comparative study. Boston, MA: Springer. Doi:

Tversky, A., and Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211,453-458. Doi: 10.1126/science.7455683

Vaidya, O.S., and Kumar. S. (2006). Analytic Hierarchy Process: an overview of applications. European Journal of Operational Research, 169(1), 1-29. Doi:

White, S.W., and Bordoloi, S.K. (2015). A review of DEA-based resource and cost allocation models: Implications for services. International Journal of Service and Operations Management, 20(1). 86-101. Doi: 10.1504/IJSOM.2015.065973

Zahedi, F. (1987). A utility approach to the Analytic Hierarchy Process. Mathematical Modeling, 9, 387-395. Doi:

Zanakis, S.H., Mandakovic, T., Gupta, S.K., Sahay, S. and Hong, S. (1995). A review of program evaluation and fund allocation methods within the service and government sectors. Socio-Economic Planning Sciences, 29(1), 59-79. Doi: