Fuzzy Analytical Hierarchy Process Evaluation of Stakeholder Groups Involvement in Forest Management Situations
Abstract
Decision-makers frequently face numerous complex, unforeseen, and irreversible problems when choosing forest management for a given situation. In these kinds of circumstances, a multitude of stakeholders or interest groups may be involved, and it may be necessary to consider a variety of criteria. In a case study of Prespa Park, we employed an approach that integrates the Fuzzy Analytical Hierarchy Process (FAHP), extended goal programming (ExtGoalProg), and "Saaty-type" surveys to rank five forest management scenarios selected through a participatory process. We also looked at three techniques for normalizing stakeholder preferences to see if they affected FAHP scenario rankings. The study was based on different empirical analyses and conducted in three parts. The first part involved identifying the key stakeholders involved in the process, establishing the "stakeholders' panel," dividing it into four "interest groups," and creating a "study/professional panel." The next step involved the identification of five alternative forest management scenarios and their associated criteria. The second part involved applying the FAHP-ExtGoalProg approach, which combines FAHP and ExtGoalProg, to rank the scenarios. In the third part of this study, we looked at how the ExtGoalProg, geometric mean, and weighted arithmetic mean techniques compared when it came to combining the preferences of different stakeholders into a single preference for all five forest management scenarios. The techniques produced varying scenario rankings, indicating that stakeholders should consult and consider the situation before selecting the optimal normalization technique to prevent bias or misleading results. The suggested approach is suitable for addressing comparable issues in forestry and environmental management.
References
[1] Adem Esmail, B., and Geneletti, D. 2018. Multi‐criteria decision analysis for nature conservation: a review of 20 years of applications. Methods in Ecology and Evolution, 9(1): 42–53. DOI: https://doi.org/10.1111/2041-210X.12899
[2] Adger, N., Arnell, N., and Tompkins, E. 2005. Successful adaptation to climate change across scales. Global Environmental Change, 15: 77–86. DOI: https://doi.org/10.1016/j.gloenvcha.2004.12.005
[3] Ahmed, F., and Kilic, K. 2019. Fuzzy Analytic Hierarchy Process: A performance analysis of various algorithms. Fuzzy Sets and Systems, 362: 110–128. DOI: https://doi.org/10.1016/j.fss.2018.08.009
[4] Ananda, J, and Herath, G. 2008. Multi-attribute preference modelling and regional land-use planning. Ecological Economics, 65: 325–335. DOI: https://doi.org/10.1016/j.ecolecon.2007.06.024
[5] Ananda, J., and Herath, G. 2009. A critical review of multi-criteria decision-making methods with special reference to forest management and planning. Ecological Economics, 68(10): 2535–2548. DOI:https://doi.org/10.1016/j.ecolecon.2009.05.010
[6] Balest, J., Hrib, M., Dobšnská, Z., and Paletto, A. 2016. Analysis of the effective stakeholders’ involvement in the development of National Forest Programmes in Europe. International Forest Review, 18: 13–28. DOI:https://doi.org/10.1505/146554816818206122
[7] Bolte, J.P., Hulse, D.W., Gregory, S.V., and Smith, C. 2006. Modeling Biocomplexity: Actors, Landscapes and Alternative Futures. Environmental Modelling and Software, 22: 570–579. DOI:http://dx.doi.org/10.1016/j.envsoft.2005.12.033
[8] Borges, J.G., et al. 2017. A multiple criteria approach for negotiating ecosystem services supply targets and forest owners’ programs. Forest Science, 63(1): 49–61. DOI: https://doi.org/10.5849/FS-2016-035
[9] Brody, S.D. 2016. Ecosystem Planning in Florida: solving Regional Problems through Local Decision-making. London: Routledge, 230 pp. DOI: https://doi.org/10.4324/9781315578750
[10] Bruña-García, X., and Marey-Pérez, M. 2018. Participative forest planning: How to obtain knowledge. Forest Systems, 27: 1–11. DOI: https://doi.org/10.5424/fs/2018271-11380
[11] Burton, P., and Mustelin, J. 2013. Planning for climate change: Is greater public participation the key to success? Urban Policy and Research, 31(4): 399–415. DOI: https://doi.org/10.1080/08111146.2013.778196
[12] Carmona, G., Varela-Ortega, C., and Bromley, J. 2013. Participatory modelling to support decision making in water management under uncertainty: two comparative case studies in the Guadiana river basin. Spain. Journal of Environmental Management, 128: 400–412. DOI: https://doi.org/10.1016/j.jenvman.2013.05.019
[13] Catsadorakis, G., and Malakou, M. 1997. Conservation and management issues of Prespa National Park. Hydrobiologia, 351: 175–196.
[14] Cegan, J.C., Filion, A.M., Keisler, J.M., and Linkov, I. 2017. Trends and applications of multicriteria decision analysis in environmental sciences: literature review. Environment System Decision, 37(2): 123–133. DOI:https://doi.org/10.1007/s10669-017-9642-9
[15] Chan, H.K., Sun, X., and Chung, S.H. 2019. When should fuzzy analytic hierarchy process be used instead of analytic hierarchy process? Decision Support Systems, 125: 113114. DOI:https://doi.org/10.1016/j.dss.2019.113114
[16] Clamote Rodrigues, D., and Fischborn, M. 2016. Solutions in Focus: Transboundary Protected Area Solutions. Switzerland: IUCN, Gland, 34 pp.
[17] Cortina, C., and Boggia, A. 2014. Development of policies for Natura 2000 sites: a multicriteria approach to support decision makers. Journal of Environment Management, 141: 138–145. DOI:https://doi.org/10.1016/j.jenvman.2014.02.039
[18] Davis, L.S., Johnson, K.N., Bettinger, P., and Howard, T.E. 2001. Forest management: To sustain ecological, economic, and social value (4th ed.). Long Grove, IL: Waveland Press, Inc., 804 pp.
[19] De Castro, M., and Urios, V. 2017. A critical review of multi-criteria decision making in protected areas. Economia Agraria y Recursos Naturales, 16(2): 89–109. DOI: 10.7201/earn.2016.02.04
[20] Diaz-Balteiro, L., Alfranca, O., González-Pachón, J., and Romero, C. 2016. Ranking of industrial forest plantations in terms of sustainability: a multicriteria approach. Journal of Environment Management, 180: 123–132. DOI: https://doi.org/10.1016/j.jenvman.2016.05.022
[21] Diaz-Balteiro, L., and Romero, C. 2008. Making forestry decisions with multiple criteria: A review and an assessment. Forest Ecology and Management, 255(8-9): 3222–3241. DOI:https://doi.org/10.1016/j.foreco.2008.01.038
[22] Diaz-Balteiro, L., González-Pachón, J., and Romero, C. 2017. Measuring systems sustainability with multi-criteria methods: a critical review. European Journal of Operational Research, 258(2): 607–616. DOI:https://doi.org/10.1016/j.ejor.2016.08.075
[23] Ezquerro, M., Pardos, M., and Diaz-Balteiro, L. 2016. Operational research techniques used for addressing biodiversity objectives into forest management: an overview. Forests, 7(10): 229. DOI:https://doi.org/10.3390/f7100229
[24] Focacci, M., et al. 2017. Integrating Stakeholders' Preferences in Participatory Forest Planning: A Pairwise Comparison Approach from Southern Italy. International Forestry Review, 19(4): 413–422. DOI:https://doi.org/10.1505/146554817822272349
[25] Frantzeskaki, N., et al. 2019. Nature-based solutions for urban climate change adaptation: Linking science, policy, and practice communities for evidence-based decision-making. Bioscience, 69(6): 455–466. DOI:https://doi.org/10.1093/biosci/biz042
[26] Fremuth, W., and Shumka, S. 2013. Management Plan of the Prespa National Park in Albania (2014–2024). Tirana, Albania: NewPolitics, 159 pp.
[27] Garfi, M, Martí, L., Bonoli, A, and Tondelli, S. 2011. Multi-criteria analysis for improving strategic environmental assessment of water programmes. A case study in semi-arid region of Brazil. Environmental Management, 92: 665–675. DOI: 10.1016/j.jenvman.2010.10.007
[28] González-Pachón, J., and Romero, C. 2007. Inferring consensus weights from pairwise comparison matrices without suitable properties. Annals of Operations Research, 154: 123–32. DOI: 10.1007/s10479-007-0182-4
[29] González-Pachón, J., and Romero, C. 2010. Goal programming: From constrained regression to bounded rationality theories. In: Zopounidis C., and Pardalos P.M. (Eds.), Handbook of multicriteria analysis. New York: Springer, pp. 311–328.
[30] Grazhdani, D. 2016. Assessing the variables affecting on the rate of solid waste generation and recycling: An empirical analysis in Prespa Park. Waste management, 48: 3–13. DOI:https://doi.org/10.1016/j.wasman.2015.09.028
[31] Grazhdani, D. 2024a. Results of two non-market valuation methods used to estimate recreational fishing in the Lakes Prespa watershed. Journal of Environment Management and Tourism, 15(1): 52–68. DOI:https://doi.org/10.14505/jemt.v15.1(73).05
[32] Grazhdani, D. 2024b. An Approach to Assessing Farm-Scale Adaptation to Climate Change: The Case Study of Prespa Park. Journal of Environmental Management and Tourism, 15(2): 231–247. DOI:https://doi.org/10.14505/jemt.v15.2(74).01
[33] Grazhdani, D. 2010. How to Plan a Sustainable Forestry Management When Environmental Goals Conflict with Existing Practices in National Prespa Park. In Proceedings of International BALWOIS Conference, 25–29 May 2010, Ohrid, Republic of Macedonia, pp. 1–7.
[34] Grazhdani, D. 2014. Integrating ecosystem services into assessment of different management options in a protected area: a deliberate multi-criteria decision analysis approach. Bulgarian Journal of Agricultural Sciences, 20(6), 1311–1319.
[35] Grazhdani, D. 2015. Contingent valuation of residents' attitudes and willingness to pay for non-point source pollution control: A case study in AL–Prespa, southeastern Albania. Environment Management, 56(1): 81–93. DOI: 10.1007/s00267-015-0480-6
[36] Grazhdani, D. 2023. An Approach for Managing Landscapes for a Variety of Ecosystem Services in Prespa Lakes Watershed. Hydrobiology, 2(1): 134–149. DOI: https://doi.org/10.3390/hydrobiology2010008
[37] Grošelj, P., Hodges, G.D., and Stirn, Z.L. 2016. Participatory and multi-criteria analysis for forest (ecosystem) management: A case study of Pohorje, Slovenia. Forest Policy and Economics, 71: 80–86. DOI:http://dx.doi.org/10.1016/j.forpol.2015.05.006
[38] Gunduz, M., and Alfar, M. 2019. Integration of innovation through analytical hierarchy process (AHP) in project management and planning. Technological and Economic Development of Economy, 25(2): 258–276. DOI: 10.3846/tede.2019.8063
[39] Hiltunen, V., Kangas, J., and Pykäläinen, J. 2008. Voting methods in strategic forest planning - Experiences from Metsähallitus. Forest Policy and Economics, 10(3): 117–127. DOI:https://doi.org/10.1016/j.forpol.2007.06.002
[40] Holder, C.D. 2016. Multiscale forest governance structures within a transboundary bio sphere reserve in Central America. World Dev. Perspect., 3: 22–24. DOI: https://doi.org/10.1016/j.wdp.2016.11.005
[41] Ignizio, J.P., and Romero, C. 2003. Goal programming. In: Hossein B, Ed. Encyclopedia of information systems. New York: Elsevier, pp. 489–500.
[42] Kabisch, N. et al. 2016. Nature-based solutions to climate change mitigation and adaptation in urban areas: Perspectives on indicators, knowledge gaps, barriers, and opportunities for action. Ecology and Society, 21(2): 39. DOI: 10.1007/978-3-319-56091-5_1
[43] Kangas A., Kangas J., and Laukkanen, S. 2006. Fuzzy multicriteria approval method and its application to two forest planning problems. Forest Science, 52: 232–242. DOI:https://doi.org/10.1093/forestscience/52.3.232
[44] Kangas, J. 1994. An approach to public participation in strategies forest management planning. Forest ecology and management, 70(1–3): 75–88. DOI: https://doi.org/10.1016/0378-1127(94)90076-0
[45] Kangas, J., and Kangas, A. 2005. Multiple criteria decision support in forest management—The approach, methods applied and experiences gained. Forest Ecology and Management, 207: 133–143. DOI:https://doi.org/10.1016/j.foreco.2004.10.023
[46] Kangas, J., Kangas, A., Leskinen, P., and Pykäläinen, J. 2002. 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: https://doi.org/10.1002/mcda.306
[47] Karjalainen, T., et al. 2003. Scenario Analysis of the Impacts of Forest Management and Climate Change on the European Forest Sector Carbon Budget. Forest Policy and Economics, 5(2): 141–155. DOI:https://doi.org/10.1016/S1389-9341(03)00021-2
[48] Khadka, C., Hujalab, T., Wolfslehnera, B., and Vacik, H. 2013. Problem Structuring in Participatory Forest Planning. Forest Policy and Economics, 26: 1–11. DOI: https://doi.org/10.1016/j.forpol.2012.09.008
[49] Krcmar, E., and van Kooten, G.C. 2008. Economic Development Prospects of Forest-Dependent Communities: Analyzing Trade-Offs Using a Compromise-Fuzzy Programming Framework. American Journal of Agricultural Economics, 90(4): 1103–1117. DOI: 10.1111/j.1467-8276.2008.01149.x
[50] Laukkanen, S., Palander, T., and Kangas, J. 2004. Applying voting theory in participatory decision support for sustainable timber harvesting. Canadian Journal of Forest Research, 34(7): 1511–1524. DOI:10.1139/x04-044
[51] Lemos, M. C., and Agrawal, A. 2006. Environmental governance. Annual Review of Environment and Resources, 31: 297–325. DOI: https://ssrn.com/abstract=1081963
[52] Maroto, C., et al. 2013. Sustainable Forest Management in a Mediterranean region: social preferences. Forest Systems, 22(3): 546–558. DOI: https://doi.org/10.5424/fs/2013223-04135
[53] Marques, M., Oliveira, M., and Borges, J.G. 2020. An approach to assess actors’ preferences and social learning to enhance participatory forest management planning. Trees, Forests and People, 2. DOI:https://doi.org/10.1016/j.tfp.2020.100026
[54] Matevski, V., et al. 2010. Notes on phytosociology of Juniperus excelsa in Macedonia (Southern Balkan Peninsula). Hacquetia, 9/1: 93-97. DOI: https://doi.org/10.2478/v10028-010-0005-z
[55] Mattsson, B.J., et al. 2019. Evaluating a collaborative decision-analytic approach to inform conservation decision-making in transboundary regions. Land Use Policy, 83. DOI: 10.1016/j. landusepol.2019.01.040
[56] Mendoza, G.A., and Martins, H. 2006. Multi-criteria decision analysis in natural resource management: A critical review of methods and new modelling paradigms. Forest Ecology and Management, 230(1-3): 1–22. DOI: https://doi.org/10.1016/j.foreco.2006.03.023
[57] Mermet, L., and Farcy, C. 2011. Contexts and concepts of forest planning in a diverse and contradictory world. Forest Policy and Economics, 13: 361–365. DOI: https://doi.org/10.1016/j.forpol.2011.03.006
[58] Munda, G. 2004. Social multi-criteria evaluation: Methodological foundations and operational consequences. European Journal of Operational Research, 158: 662–677. DOI: http://dx.doi.org/10.1016/S0377-2217(03)00369-2
[59] Nesshöver, C., et al. 2017. The science, policy and practice of nature-based solutions: An interdisciplinary perspective. Science of Total Environment, 579: 1215–1227. DOI: 10.1016/j.scitotenv.2016.11.106
[60] Nilsson, H., Nordström, E-M, and Öhman, K. 2016. Decision Support for Participatory Forest Planning Using AHP and TOPSIS. Forests, 7(5): 100. DOI: https://doi.org/10.3390/f7050100
[61] Nordström, E.-M., Eriksson, O.L, and Öhman, K. 2010. Integrating multiple criteria decision analysis in participatory forest planning: Experience from a case study in northern Sweden. Forest Policy and Economics, 12(8): 562–74. DOI: https://doi.org/10.1016/j.forpol.2010.07.006
[62] Nordström, E.-M., Öhman, K., and Eriksson, O.L. 2012. Approaches for Aggregating Preferences in Participatory Forest Planning - An Experimental Study. The Open Forest Science Journal, 5: 23–32. DOI:10.2174/1874398601205010023
[63] Ortiz-Urbina, E.J., González-Pachón, J., and Diaz-Balteiro, L. 2019. Decision-making in forestry: a review of the hybridisation of multiple criteria and group decision-making methods. Forests, 10(5): 375. DOI:https://doi.org/10.3390/f10050375
[64] Pérez-Rodríguez, F., and Rojo-Alboreca, A. 2017. The triangle assessment method: a new procedure for eliciting expert judgement. Expert Syst. Appl., 72: 139–150. DOI: https://doi.org/10.1016/j.eswa.2016.11.021
[65] Prell, C., Hubacek, K., and Reed, M. 2009. Stakeholder analysis and social network analysis in natural resource management. Society and Natural Resources, 22: 501–518. DOI:https://doi.org/10.1080/08941920802199202
[66] Rauschmayer, F., and Wittmer, H. 2006. Evaluating deliberative and analytical methods for the resolution of environmental conflicts. Land Use Policy, 23(1): 108–122. DOI:https://doi.org/10.1016/j.landusepol.2004.08.011
[67] Renn, O., and Schweizer, P.J. 2009. Inclusive risk governance: Concepts and application to environmental policy making. Environmental Policy and Governance, 19(3): 174–185. DOI: https://doi.org/10.1002/eet.507
[68] Rossi, F.J., Carter, D.R., Alavalapati, J.R.R., and Nowak, J.T. 2011. Assessing landowner preferences for forest management practices to prevent the southern pine beetle: an attribute-based choice experiment approach. Forest Policy and Economics, 13 (4): 234–241. DOI: https://doi.org/10.1016/j.forpol.2011.01.001
[69] Saarikoski, H., Mustajoki, J., and Marttunen, M. 2013. Participatory multi-criteria assessment as ‘opening up’ vs. ‘closing down’ of policy discourses: a case of old-growth forest conflict in Finnish Upper Lapland. Land Use Policy, 32: 329–336. DOI: https://doi.org/10.1016/j.landusepol.2012.11.003
[70] Saaty, R.W. 1987. The analytic hierarchy process—What it is and how it is used. Mathematical modelling, 9(3-5): 161–176. DOI: https://doi.org/10.1016/0270-0255(87)90473-8
[71] Saaty, T.L. 1990. How to make a decision: the analytic hierarchy process. European Journal of Operational Research, 48: 9–26. DOI: http://dx.doi.org/10.1016/0377-2217(90)90057-I
[72] Saaty, T.L. 1980. The analytic hierarchy process. New York: McGraw-Hill, 287 pp.
[73] Saaty, T.L. 2008. Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1): 83–98. DOI: 10.1504/IJSSCI.2008.017590
[74] Sánchez-Lozano, J.M., and Bernal-Conesa, J.A. 2017. Environmental management of Natura 2000 network areas through the combination of Geographic Information Systems (GIS) with Multi-Criteria Decision Making (MCDM) methods. Case study in south-eastern Spain. Land Use Policy, 63: 86–97. DOI:https://doi.org/10.1016/j.landusepol. 2017.01.021
[75] Sarvašová, Z., Dobšinská, Z., and Šálka, J. 2014. Public participation in sustainable forestry: The case of forest planning in Slovakia. IForest, 7: 414–422. DOI: https://doi.org/10.3832/ifor1174-007
[76] Scholl, A., Manthey, L., Helm, R., and Steiner, M. 2005. Solving multi-attribute design problems with analytic hierarchy process and conjoint analysis: An empirical comparison. European Journal of Operational Research, 164(3): 760–777. DOI: 10.1016/j.ejor.2004.01.026
[77] Sheppard, S.R.J., and Meitner, M. 2005. Using multi-criteria analysis and visualization for sustainable forest management planning with stakeholder groups. Forest Ecology and Management, 207(1-2): 171–187. DOI:https://doi.org/10.1016/j.foreco.2004.10.032
[78] Srdjevic, Z., Lakicevic, M., and Srdjevic, B. 2013. Approach of decision making based on the analytic hierarchy process for urban landscape management. Environment Management, 51: 777–785. DOI:10.1007/s00267-012-9990-7
[79] Thirumalaivasan, D., Karmegam, M., and Venugopal, K. 2003. AHP-DRASTIC: Software for specific aquifer vulnerability assessment using Drastic model and GIS. Environmental Modelling Software, 18: 645–656. DOI:10.1016/S1364-8152(03)00051-3
[80] Torfi, F., Farahani, R.Z., and Rezapour, S. 2010. Fuzzy AHP to determine the relative weights of evaluation criteria and Fuzzy TOPSIS to rank the alternatives. Applied Soft Computing, 10: 520–528. DOI:https://doi.org/10.1016/j.asoc.2009.08.021
[81] Uhde, B., Hahn, W.A., Griess, V.C., and Knoke, T. 2015. Hybrid MCDA methods to integrate multiple ecosystem services in forest management planning: a critical review. Environment Management, 56 (2): 373–388. DOI: 10.1007/s00267-015-0503-3
[82] Valasiuk, S., et al. 2018. Is forest landscape restoration socially desirable? A discrete choice experiment applied to the Scandinavian transboundary Fulufjället National Park Area. Restoration Ecology, 26 (2): 370–380. DOI: https://doi.org/10.1111/rec.12563
[83] Vrahnakis, M.G. Fotiadis, and Kazoglou, Y. 2011. Registration, Assessment and Geographical Represantation of the Range and Forest Habitat Types of the Natura 2000 Sites Prespa National Park (Ethnikos Drymos Prespn - GR 1340001) and Mt. Varnountas (Ori Varnountas GR 1340003) and Adjacent Areas. Final Report. Society for the Protection of Prespa.
[84] Wamsler, C. et al. 2020. Beyond participation: When citizen engagement leads to undesirable outcomes for nature-based solutions and climate change adaptation. Climatic Change, 158(2): 235–254. DOI:https://doi.org/10.1007/s10584-019-02557-9
[85] Wamsler, C., and Raggers, S. 2018. Principles for supporting city–citizen commoning for climate adaptation: From adaptation governance to sustainable transformation. Environmental Science and Policy, 85: 81–89. DOI:https://doi.org/10.1016/j.envsci.2018.03.021
[86] Zadeh, L.A. 1965. Information and control. Fuzzy Sets, 8: 338–353. DOI: http://dx.doi.org/10.1016/S0019-9958(65)90241-X
[87] ExpertChoice, Decision Support Software. 2002. Available at: http://expertchoice.com/about-us/our-decision-making-methodology/
[2] Adger, N., Arnell, N., and Tompkins, E. 2005. Successful adaptation to climate change across scales. Global Environmental Change, 15: 77–86. DOI: https://doi.org/10.1016/j.gloenvcha.2004.12.005
[3] Ahmed, F., and Kilic, K. 2019. Fuzzy Analytic Hierarchy Process: A performance analysis of various algorithms. Fuzzy Sets and Systems, 362: 110–128. DOI: https://doi.org/10.1016/j.fss.2018.08.009
[4] Ananda, J, and Herath, G. 2008. Multi-attribute preference modelling and regional land-use planning. Ecological Economics, 65: 325–335. DOI: https://doi.org/10.1016/j.ecolecon.2007.06.024
[5] Ananda, J., and Herath, G. 2009. A critical review of multi-criteria decision-making methods with special reference to forest management and planning. Ecological Economics, 68(10): 2535–2548. DOI:https://doi.org/10.1016/j.ecolecon.2009.05.010
[6] Balest, J., Hrib, M., Dobšnská, Z., and Paletto, A. 2016. Analysis of the effective stakeholders’ involvement in the development of National Forest Programmes in Europe. International Forest Review, 18: 13–28. DOI:https://doi.org/10.1505/146554816818206122
[7] Bolte, J.P., Hulse, D.W., Gregory, S.V., and Smith, C. 2006. Modeling Biocomplexity: Actors, Landscapes and Alternative Futures. Environmental Modelling and Software, 22: 570–579. DOI:http://dx.doi.org/10.1016/j.envsoft.2005.12.033
[8] Borges, J.G., et al. 2017. A multiple criteria approach for negotiating ecosystem services supply targets and forest owners’ programs. Forest Science, 63(1): 49–61. DOI: https://doi.org/10.5849/FS-2016-035
[9] Brody, S.D. 2016. Ecosystem Planning in Florida: solving Regional Problems through Local Decision-making. London: Routledge, 230 pp. DOI: https://doi.org/10.4324/9781315578750
[10] Bruña-García, X., and Marey-Pérez, M. 2018. Participative forest planning: How to obtain knowledge. Forest Systems, 27: 1–11. DOI: https://doi.org/10.5424/fs/2018271-11380
[11] Burton, P., and Mustelin, J. 2013. Planning for climate change: Is greater public participation the key to success? Urban Policy and Research, 31(4): 399–415. DOI: https://doi.org/10.1080/08111146.2013.778196
[12] Carmona, G., Varela-Ortega, C., and Bromley, J. 2013. Participatory modelling to support decision making in water management under uncertainty: two comparative case studies in the Guadiana river basin. Spain. Journal of Environmental Management, 128: 400–412. DOI: https://doi.org/10.1016/j.jenvman.2013.05.019
[13] Catsadorakis, G., and Malakou, M. 1997. Conservation and management issues of Prespa National Park. Hydrobiologia, 351: 175–196.
[14] Cegan, J.C., Filion, A.M., Keisler, J.M., and Linkov, I. 2017. Trends and applications of multicriteria decision analysis in environmental sciences: literature review. Environment System Decision, 37(2): 123–133. DOI:https://doi.org/10.1007/s10669-017-9642-9
[15] Chan, H.K., Sun, X., and Chung, S.H. 2019. When should fuzzy analytic hierarchy process be used instead of analytic hierarchy process? Decision Support Systems, 125: 113114. DOI:https://doi.org/10.1016/j.dss.2019.113114
[16] Clamote Rodrigues, D., and Fischborn, M. 2016. Solutions in Focus: Transboundary Protected Area Solutions. Switzerland: IUCN, Gland, 34 pp.
[17] Cortina, C., and Boggia, A. 2014. Development of policies for Natura 2000 sites: a multicriteria approach to support decision makers. Journal of Environment Management, 141: 138–145. DOI:https://doi.org/10.1016/j.jenvman.2014.02.039
[18] Davis, L.S., Johnson, K.N., Bettinger, P., and Howard, T.E. 2001. Forest management: To sustain ecological, economic, and social value (4th ed.). Long Grove, IL: Waveland Press, Inc., 804 pp.
[19] De Castro, M., and Urios, V. 2017. A critical review of multi-criteria decision making in protected areas. Economia Agraria y Recursos Naturales, 16(2): 89–109. DOI: 10.7201/earn.2016.02.04
[20] Diaz-Balteiro, L., Alfranca, O., González-Pachón, J., and Romero, C. 2016. Ranking of industrial forest plantations in terms of sustainability: a multicriteria approach. Journal of Environment Management, 180: 123–132. DOI: https://doi.org/10.1016/j.jenvman.2016.05.022
[21] Diaz-Balteiro, L., and Romero, C. 2008. Making forestry decisions with multiple criteria: A review and an assessment. Forest Ecology and Management, 255(8-9): 3222–3241. DOI:https://doi.org/10.1016/j.foreco.2008.01.038
[22] Diaz-Balteiro, L., González-Pachón, J., and Romero, C. 2017. Measuring systems sustainability with multi-criteria methods: a critical review. European Journal of Operational Research, 258(2): 607–616. DOI:https://doi.org/10.1016/j.ejor.2016.08.075
[23] Ezquerro, M., Pardos, M., and Diaz-Balteiro, L. 2016. Operational research techniques used for addressing biodiversity objectives into forest management: an overview. Forests, 7(10): 229. DOI:https://doi.org/10.3390/f7100229
[24] Focacci, M., et al. 2017. Integrating Stakeholders' Preferences in Participatory Forest Planning: A Pairwise Comparison Approach from Southern Italy. International Forestry Review, 19(4): 413–422. DOI:https://doi.org/10.1505/146554817822272349
[25] Frantzeskaki, N., et al. 2019. Nature-based solutions for urban climate change adaptation: Linking science, policy, and practice communities for evidence-based decision-making. Bioscience, 69(6): 455–466. DOI:https://doi.org/10.1093/biosci/biz042
[26] Fremuth, W., and Shumka, S. 2013. Management Plan of the Prespa National Park in Albania (2014–2024). Tirana, Albania: NewPolitics, 159 pp.
[27] Garfi, M, Martí, L., Bonoli, A, and Tondelli, S. 2011. Multi-criteria analysis for improving strategic environmental assessment of water programmes. A case study in semi-arid region of Brazil. Environmental Management, 92: 665–675. DOI: 10.1016/j.jenvman.2010.10.007
[28] González-Pachón, J., and Romero, C. 2007. Inferring consensus weights from pairwise comparison matrices without suitable properties. Annals of Operations Research, 154: 123–32. DOI: 10.1007/s10479-007-0182-4
[29] González-Pachón, J., and Romero, C. 2010. Goal programming: From constrained regression to bounded rationality theories. In: Zopounidis C., and Pardalos P.M. (Eds.), Handbook of multicriteria analysis. New York: Springer, pp. 311–328.
[30] Grazhdani, D. 2016. Assessing the variables affecting on the rate of solid waste generation and recycling: An empirical analysis in Prespa Park. Waste management, 48: 3–13. DOI:https://doi.org/10.1016/j.wasman.2015.09.028
[31] Grazhdani, D. 2024a. Results of two non-market valuation methods used to estimate recreational fishing in the Lakes Prespa watershed. Journal of Environment Management and Tourism, 15(1): 52–68. DOI:https://doi.org/10.14505/jemt.v15.1(73).05
[32] Grazhdani, D. 2024b. An Approach to Assessing Farm-Scale Adaptation to Climate Change: The Case Study of Prespa Park. Journal of Environmental Management and Tourism, 15(2): 231–247. DOI:https://doi.org/10.14505/jemt.v15.2(74).01
[33] Grazhdani, D. 2010. How to Plan a Sustainable Forestry Management When Environmental Goals Conflict with Existing Practices in National Prespa Park. In Proceedings of International BALWOIS Conference, 25–29 May 2010, Ohrid, Republic of Macedonia, pp. 1–7.
[34] Grazhdani, D. 2014. Integrating ecosystem services into assessment of different management options in a protected area: a deliberate multi-criteria decision analysis approach. Bulgarian Journal of Agricultural Sciences, 20(6), 1311–1319.
[35] Grazhdani, D. 2015. Contingent valuation of residents' attitudes and willingness to pay for non-point source pollution control: A case study in AL–Prespa, southeastern Albania. Environment Management, 56(1): 81–93. DOI: 10.1007/s00267-015-0480-6
[36] Grazhdani, D. 2023. An Approach for Managing Landscapes for a Variety of Ecosystem Services in Prespa Lakes Watershed. Hydrobiology, 2(1): 134–149. DOI: https://doi.org/10.3390/hydrobiology2010008
[37] Grošelj, P., Hodges, G.D., and Stirn, Z.L. 2016. Participatory and multi-criteria analysis for forest (ecosystem) management: A case study of Pohorje, Slovenia. Forest Policy and Economics, 71: 80–86. DOI:http://dx.doi.org/10.1016/j.forpol.2015.05.006
[38] Gunduz, M., and Alfar, M. 2019. Integration of innovation through analytical hierarchy process (AHP) in project management and planning. Technological and Economic Development of Economy, 25(2): 258–276. DOI: 10.3846/tede.2019.8063
[39] Hiltunen, V., Kangas, J., and Pykäläinen, J. 2008. Voting methods in strategic forest planning - Experiences from Metsähallitus. Forest Policy and Economics, 10(3): 117–127. DOI:https://doi.org/10.1016/j.forpol.2007.06.002
[40] Holder, C.D. 2016. Multiscale forest governance structures within a transboundary bio sphere reserve in Central America. World Dev. Perspect., 3: 22–24. DOI: https://doi.org/10.1016/j.wdp.2016.11.005
[41] Ignizio, J.P., and Romero, C. 2003. Goal programming. In: Hossein B, Ed. Encyclopedia of information systems. New York: Elsevier, pp. 489–500.
[42] Kabisch, N. et al. 2016. Nature-based solutions to climate change mitigation and adaptation in urban areas: Perspectives on indicators, knowledge gaps, barriers, and opportunities for action. Ecology and Society, 21(2): 39. DOI: 10.1007/978-3-319-56091-5_1
[43] Kangas A., Kangas J., and Laukkanen, S. 2006. Fuzzy multicriteria approval method and its application to two forest planning problems. Forest Science, 52: 232–242. DOI:https://doi.org/10.1093/forestscience/52.3.232
[44] Kangas, J. 1994. An approach to public participation in strategies forest management planning. Forest ecology and management, 70(1–3): 75–88. DOI: https://doi.org/10.1016/0378-1127(94)90076-0
[45] Kangas, J., and Kangas, A. 2005. Multiple criteria decision support in forest management—The approach, methods applied and experiences gained. Forest Ecology and Management, 207: 133–143. DOI:https://doi.org/10.1016/j.foreco.2004.10.023
[46] Kangas, J., Kangas, A., Leskinen, P., and Pykäläinen, J. 2002. 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: https://doi.org/10.1002/mcda.306
[47] Karjalainen, T., et al. 2003. Scenario Analysis of the Impacts of Forest Management and Climate Change on the European Forest Sector Carbon Budget. Forest Policy and Economics, 5(2): 141–155. DOI:https://doi.org/10.1016/S1389-9341(03)00021-2
[48] Khadka, C., Hujalab, T., Wolfslehnera, B., and Vacik, H. 2013. Problem Structuring in Participatory Forest Planning. Forest Policy and Economics, 26: 1–11. DOI: https://doi.org/10.1016/j.forpol.2012.09.008
[49] Krcmar, E., and van Kooten, G.C. 2008. Economic Development Prospects of Forest-Dependent Communities: Analyzing Trade-Offs Using a Compromise-Fuzzy Programming Framework. American Journal of Agricultural Economics, 90(4): 1103–1117. DOI: 10.1111/j.1467-8276.2008.01149.x
[50] Laukkanen, S., Palander, T., and Kangas, J. 2004. Applying voting theory in participatory decision support for sustainable timber harvesting. Canadian Journal of Forest Research, 34(7): 1511–1524. DOI:10.1139/x04-044
[51] Lemos, M. C., and Agrawal, A. 2006. Environmental governance. Annual Review of Environment and Resources, 31: 297–325. DOI: https://ssrn.com/abstract=1081963
[52] Maroto, C., et al. 2013. Sustainable Forest Management in a Mediterranean region: social preferences. Forest Systems, 22(3): 546–558. DOI: https://doi.org/10.5424/fs/2013223-04135
[53] Marques, M., Oliveira, M., and Borges, J.G. 2020. An approach to assess actors’ preferences and social learning to enhance participatory forest management planning. Trees, Forests and People, 2. DOI:https://doi.org/10.1016/j.tfp.2020.100026
[54] Matevski, V., et al. 2010. Notes on phytosociology of Juniperus excelsa in Macedonia (Southern Balkan Peninsula). Hacquetia, 9/1: 93-97. DOI: https://doi.org/10.2478/v10028-010-0005-z
[55] Mattsson, B.J., et al. 2019. Evaluating a collaborative decision-analytic approach to inform conservation decision-making in transboundary regions. Land Use Policy, 83. DOI: 10.1016/j. landusepol.2019.01.040
[56] Mendoza, G.A., and Martins, H. 2006. Multi-criteria decision analysis in natural resource management: A critical review of methods and new modelling paradigms. Forest Ecology and Management, 230(1-3): 1–22. DOI: https://doi.org/10.1016/j.foreco.2006.03.023
[57] Mermet, L., and Farcy, C. 2011. Contexts and concepts of forest planning in a diverse and contradictory world. Forest Policy and Economics, 13: 361–365. DOI: https://doi.org/10.1016/j.forpol.2011.03.006
[58] Munda, G. 2004. Social multi-criteria evaluation: Methodological foundations and operational consequences. European Journal of Operational Research, 158: 662–677. DOI: http://dx.doi.org/10.1016/S0377-2217(03)00369-2
[59] Nesshöver, C., et al. 2017. The science, policy and practice of nature-based solutions: An interdisciplinary perspective. Science of Total Environment, 579: 1215–1227. DOI: 10.1016/j.scitotenv.2016.11.106
[60] Nilsson, H., Nordström, E-M, and Öhman, K. 2016. Decision Support for Participatory Forest Planning Using AHP and TOPSIS. Forests, 7(5): 100. DOI: https://doi.org/10.3390/f7050100
[61] Nordström, E.-M., Eriksson, O.L, and Öhman, K. 2010. Integrating multiple criteria decision analysis in participatory forest planning: Experience from a case study in northern Sweden. Forest Policy and Economics, 12(8): 562–74. DOI: https://doi.org/10.1016/j.forpol.2010.07.006
[62] Nordström, E.-M., Öhman, K., and Eriksson, O.L. 2012. Approaches for Aggregating Preferences in Participatory Forest Planning - An Experimental Study. The Open Forest Science Journal, 5: 23–32. DOI:10.2174/1874398601205010023
[63] Ortiz-Urbina, E.J., González-Pachón, J., and Diaz-Balteiro, L. 2019. Decision-making in forestry: a review of the hybridisation of multiple criteria and group decision-making methods. Forests, 10(5): 375. DOI:https://doi.org/10.3390/f10050375
[64] Pérez-Rodríguez, F., and Rojo-Alboreca, A. 2017. The triangle assessment method: a new procedure for eliciting expert judgement. Expert Syst. Appl., 72: 139–150. DOI: https://doi.org/10.1016/j.eswa.2016.11.021
[65] Prell, C., Hubacek, K., and Reed, M. 2009. Stakeholder analysis and social network analysis in natural resource management. Society and Natural Resources, 22: 501–518. DOI:https://doi.org/10.1080/08941920802199202
[66] Rauschmayer, F., and Wittmer, H. 2006. Evaluating deliberative and analytical methods for the resolution of environmental conflicts. Land Use Policy, 23(1): 108–122. DOI:https://doi.org/10.1016/j.landusepol.2004.08.011
[67] Renn, O., and Schweizer, P.J. 2009. Inclusive risk governance: Concepts and application to environmental policy making. Environmental Policy and Governance, 19(3): 174–185. DOI: https://doi.org/10.1002/eet.507
[68] Rossi, F.J., Carter, D.R., Alavalapati, J.R.R., and Nowak, J.T. 2011. Assessing landowner preferences for forest management practices to prevent the southern pine beetle: an attribute-based choice experiment approach. Forest Policy and Economics, 13 (4): 234–241. DOI: https://doi.org/10.1016/j.forpol.2011.01.001
[69] Saarikoski, H., Mustajoki, J., and Marttunen, M. 2013. Participatory multi-criteria assessment as ‘opening up’ vs. ‘closing down’ of policy discourses: a case of old-growth forest conflict in Finnish Upper Lapland. Land Use Policy, 32: 329–336. DOI: https://doi.org/10.1016/j.landusepol.2012.11.003
[70] Saaty, R.W. 1987. The analytic hierarchy process—What it is and how it is used. Mathematical modelling, 9(3-5): 161–176. DOI: https://doi.org/10.1016/0270-0255(87)90473-8
[71] Saaty, T.L. 1990. How to make a decision: the analytic hierarchy process. European Journal of Operational Research, 48: 9–26. DOI: http://dx.doi.org/10.1016/0377-2217(90)90057-I
[72] Saaty, T.L. 1980. The analytic hierarchy process. New York: McGraw-Hill, 287 pp.
[73] Saaty, T.L. 2008. Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1): 83–98. DOI: 10.1504/IJSSCI.2008.017590
[74] Sánchez-Lozano, J.M., and Bernal-Conesa, J.A. 2017. Environmental management of Natura 2000 network areas through the combination of Geographic Information Systems (GIS) with Multi-Criteria Decision Making (MCDM) methods. Case study in south-eastern Spain. Land Use Policy, 63: 86–97. DOI:https://doi.org/10.1016/j.landusepol. 2017.01.021
[75] Sarvašová, Z., Dobšinská, Z., and Šálka, J. 2014. Public participation in sustainable forestry: The case of forest planning in Slovakia. IForest, 7: 414–422. DOI: https://doi.org/10.3832/ifor1174-007
[76] Scholl, A., Manthey, L., Helm, R., and Steiner, M. 2005. Solving multi-attribute design problems with analytic hierarchy process and conjoint analysis: An empirical comparison. European Journal of Operational Research, 164(3): 760–777. DOI: 10.1016/j.ejor.2004.01.026
[77] Sheppard, S.R.J., and Meitner, M. 2005. Using multi-criteria analysis and visualization for sustainable forest management planning with stakeholder groups. Forest Ecology and Management, 207(1-2): 171–187. DOI:https://doi.org/10.1016/j.foreco.2004.10.032
[78] Srdjevic, Z., Lakicevic, M., and Srdjevic, B. 2013. Approach of decision making based on the analytic hierarchy process for urban landscape management. Environment Management, 51: 777–785. DOI:10.1007/s00267-012-9990-7
[79] Thirumalaivasan, D., Karmegam, M., and Venugopal, K. 2003. AHP-DRASTIC: Software for specific aquifer vulnerability assessment using Drastic model and GIS. Environmental Modelling Software, 18: 645–656. DOI:10.1016/S1364-8152(03)00051-3
[80] Torfi, F., Farahani, R.Z., and Rezapour, S. 2010. Fuzzy AHP to determine the relative weights of evaluation criteria and Fuzzy TOPSIS to rank the alternatives. Applied Soft Computing, 10: 520–528. DOI:https://doi.org/10.1016/j.asoc.2009.08.021
[81] Uhde, B., Hahn, W.A., Griess, V.C., and Knoke, T. 2015. Hybrid MCDA methods to integrate multiple ecosystem services in forest management planning: a critical review. Environment Management, 56 (2): 373–388. DOI: 10.1007/s00267-015-0503-3
[82] Valasiuk, S., et al. 2018. Is forest landscape restoration socially desirable? A discrete choice experiment applied to the Scandinavian transboundary Fulufjället National Park Area. Restoration Ecology, 26 (2): 370–380. DOI: https://doi.org/10.1111/rec.12563
[83] Vrahnakis, M.G. Fotiadis, and Kazoglou, Y. 2011. Registration, Assessment and Geographical Represantation of the Range and Forest Habitat Types of the Natura 2000 Sites Prespa National Park (Ethnikos Drymos Prespn - GR 1340001) and Mt. Varnountas (Ori Varnountas GR 1340003) and Adjacent Areas. Final Report. Society for the Protection of Prespa.
[84] Wamsler, C. et al. 2020. Beyond participation: When citizen engagement leads to undesirable outcomes for nature-based solutions and climate change adaptation. Climatic Change, 158(2): 235–254. DOI:https://doi.org/10.1007/s10584-019-02557-9
[85] Wamsler, C., and Raggers, S. 2018. Principles for supporting city–citizen commoning for climate adaptation: From adaptation governance to sustainable transformation. Environmental Science and Policy, 85: 81–89. DOI:https://doi.org/10.1016/j.envsci.2018.03.021
[86] Zadeh, L.A. 1965. Information and control. Fuzzy Sets, 8: 338–353. DOI: http://dx.doi.org/10.1016/S0019-9958(65)90241-X
[87] ExpertChoice, Decision Support Software. 2002. Available at: http://expertchoice.com/about-us/our-decision-making-methodology/
Published
2024-08-30
How to Cite
GRAZHDANI, Dorina.
Fuzzy Analytical Hierarchy Process Evaluation of Stakeholder Groups Involvement in Forest Management Situations.
Journal of Environmental Management and Tourism, [S.l.], v. 15, n. 3, p. 435 - 448, aug. 2024.
ISSN 2068-7729.
Available at: <https://journals.aserspublishing.eu/jemt/article/view/8552>. Date accessed: 25 oct. 2024.
doi: https://doi.org/10.14505/jemt.v15.3(75).02.
Section
Article
Copyright© 2024 The Author(s). Published by ASERS Publishing 2024. This is an open access article distributed under the terms of CC-BY 4.0 license.