Decision making model in forest road network management

  • Srđan H. Dimić University of Defence in Belgrade, Military academy, Department of Logistics
  • Srđan D. Ljubojević University of Defence in Belgrade, Military academy, Department of Logistics
Keywords: Forest road network, decision making, strategy, FDA’WOT model, fuzzy Delphi, fuzzy SWOT, AHP,

Abstract


Forest resource exploitation and the achievement of full forest potential depend on the density and quality of the forest road network. The forest road network has to fulfill multiple functions; it thus has strategic importance in forest management. When planning the forest road network development, decision makers have to consider various technological, economic, social, and environmental factors. A comprehensive and functional approach is needed. A hybrid methodological framework for the formulation of guidelines, within which the strategy for the development of the state-owned forest road network should be defined, is presented in this paper. A fuzzy modification of the A'WOT method is proposed. The model, named FDA’WOT model, is based on an idea to provide a conceptual framework for strategic option selection by combining the fuzzy Delphi technique, the fuzzy SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) and the Analytical Hierarchical Process (AHP). The FDA’WOT model overcomes the problems of a classical SWOT analysis related to the vagueness and uncertainties in assessment of the character, impact and relative importance of strategic factors. It is a frame for a multicriteria approach in decision making which allows analytical prioritization of alternative strategic options and selection of an optimal one. The proposed model is applied to a case study of the strategy selection for the forest road network development in the Republic of Serbia. The presented results have shown that the FDA'WOT model can successfully create conditions for sustainable strategy formulation.

 

References

Bojadziev, G., & Bojadziev, M. 2007. Fuzzy Logic for Business, Finance and Management.Singapore: Hackensack. NJ: Word Scientific, pp.71-72.

Carbone, F., & Savelli, S. 2009. Forestry programmes and the contribution of the forestry research community to the Italy experience. Forest Policy and Economics, 11(7), pp.508-515. Available at: https://doi.org/10.1016/j.forpol.2009.06.001.

Danilović, M., & Stojnić, D. 2014. Assessment of the state of a forest road network as a basis for making a program of forest management unit opening. Bulletin of the Faculty of Forestry, 110, pp.59-71. Available at: https://doi.org/10.2298/gsf1410059d.

Diaz-Balteiro, L., & Romero, C. 2008. Making forestry decisions with multiple criteria: A review and an assessment. Forest Ecology and Management, 255(8-9), pp.3222-3241. Available at: https://doi.org/10.1016/j.foreco.2008.01.038.

Dimić, S., Pamučar, D., Ljubojević, S., & Đorović, B. 2016. Strategic Transport Management Models—The Case Study of an Oil Industry. Sustainability, 8(9), p.954. Available at: https://doi.org/10.3390/su8090954.

Dwivedi, P., & Alavalapati, J.R.R. 2009. Stakeholders’ perceptions on forest biomass-based bioenergy development in the southern US. Energy Policy, 37(5), pp.1999-2007. Available at: https://doi.org/10.1016/j.enpol.2009.02.004.

Gerasimov, Y., Senko, S., & Karjalainen, T. 2013. Nordic Forest Energy Solutions in the Republic of Karelia. Forests, 4(4), pp.945-967. Available at: https://doi.org/10.3390/f4040945.

Ghazinoory, S., Zadeh, A.E., & Memariani, A. 2007. Fuzzy SWOT analysis. Journal of Intelligent and Fuzzy Systems, 18(1), pp.99-108.

Hayati, E., Majnounian, B., Abdi, E., Sessions, J., & Makhdoum, M. 2013. An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation. Environmental Monitoring and Assessment, 185(2), pp.1767-1776. Available at: https://doi.org/10.1007/s10661-012-2666-1.

Hoang, H.T.N., Hoshino, S., & Hashimoto, S. 2015. Forest stewardship council certificate for a group of planters in Vietnam: SWOT analysis and implications. Journal of Forest Research, 20(1), pp.35-42. Available at: https://doi.org/10.1007/s10310-014-0472-z.

Hynynen, J., Salminen, H., Ahtikoski, A., Huuskonen, S., Ojansuu, R., Siipilehto, J., . . . Eerikäinen, K. 2015. Long-term impacts of forest management on biomass supply and forest resource development: a scenario analysis for Finland. European Journal of Forest Research, 134(3), pp.415-431. Available at: https://doi.org/10.1007/s10342-014-0860-0.

Hynynen, J., Salminen, H., Huuskonen, S., Ahtikoski, A., Ojansuu, R., Siipilehto, J., . . . Eerikainen, K. 2014. Scenario analysis for the biomass supply potential and the future development of Finnish forest resources. Working Papers of the Finnish Forest Research Institute, 302, ISBN 978-951-40-2487-0.

Jalilova, G., Khadka, C., & Vacik, H. 2012. Developing criteria and indicators for evaluating sustainable forest management: A case study in Kyrgyzstan. Forest Policy and Economics, 21, pp.32-43. Available at: https://doi.org/10.1016/j.forpol.2012.01.010.

Jarský, V., Sarvašová, Z., Dobšinská, Z., Ventrubová, K., & Sarvaš, M. 2014. Public support for forestry from EU funds – Cases of Czech Republic and Slovak Republic. Journal of Forest Economics, 20(4), pp.380-395. Available at: https://doi.org/10.1016/j.jfe.2014.10.004.

Kajanus, M., Leskinen, P., Kurttila, M., & Kangas, J. 2012. Making use of MCDS methods in SWOT analysis—Lessons learnt in strategic natural resources management. Forest Policy and Economics, 20, pp.1-9. Available at: https://doi.org/10.1016/j.forpol.2012.03.005.

Kangas, J., Pesonen, M., Kurttila, M., & Kajanus, M. 2001. A'WOT: Integrating the AHP with SWOT Analysis. In Proceedings of the 6th International Symposium on the Analytic Hierarchy Process - ISAHP 2001.Bern,Switzerland, pp.189-198.

Kurttila, M., Pesonen, M., Kangas, J., & Kajanus, M. 2000. Utilizing the analytic hierarchy process (AHP) in SWOT analysis — a hybrid method and its application to a forest-certification case. Forest Policy and Economics, 1(1), pp.41-52. Available at: https://doi.org/10.1016/s1389-9341(99)00004-0.

Ljubojević, S., Dimić, S., & Luković, N. 2014. An analytical approach to defining strategic options in a case of developing multimodal transport in the Army of Serbia. Vojnotehnički glasnik / Military Technical Coourier, 62(2), pp.74-95. Available at: https://doi.org/10.5937/vojtehg62-2068.

Meddour-Sahar, O. 2015. Wildfires in Algeria: problems and challenges. iForest - Biogeosciences and Forestry, 8(6), pp.818-826. Available at: https://doi.org/10.3832/ifor1279-007.

Mendoza, G.A., & Prabhu, R. 2004. Fuzzy methods for assessing criteria and indicators of sustainable forest management. Ecological Indicators, 3(4), pp.227-236. Available at: https://doi.org/10.1016/j.ecolind.2003.08.001.

-Ministry of Agriculture, Forestry and Water Management of the Republic of Serbia, Directorate for Forests. 2006. Strategija razvoja šumarstva Republike Srbije. Belgrade: Ministry of Agriculture, Forestry and Water Management of the Republic of Serbia (in Serbian).

Ochoa-Gaona, S., Kampichler, C., de Jong, B.H.J., Hernández, S., Geissen, V., & Huerta, E. 2010. A multi-criterion index for the evaluation of local tropical forest conditions in Mexico. Forest Ecology and Management, 260(5), pp.618-627. Available at: https://doi.org/10.1016/j.foreco.2010.05.018.

Pellegrini, M., Grigolato, S., & Cavalli, R. 2013. Spatial Multi-Criteria Decision Process to Define Maintenance Priorities of Forest Road Network: an Application in the Italian Alpine Region. Croatian Journal of Forest Engineering, 34(1), pp.31-42.

Rauch, P. 2007. SWOT analyses and SWOT strategy formulation for forest owner cooperations in Austria. European Journal of Forest Research, 126(3), pp.413-420. Available at: https://doi.org/10.1007/s10342-006-0162-2.

Saaty, T.L. 1980. The Analytic Hierarchy Process.New York: McGraw-Hill.

Saaty, T.L. 1977. A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), pp.234-281. Available at: https://doi.org/10.1016/0022-2496(77)90033-5.

Stainback, G.A., Masozera, M., Mukuralinda, A., & Dwivedi, P. 2012. Smallholder Agroforestry in Rwanda: A SWOT-AHP Analysis. Small-scale Forestry, 11(3), pp.285-300. Available at: https://doi.org/10.1007/s11842-011-9184-9.

-Statistical Office of the Republic of Serbia. 2015. Šumarstvo u Republici Srbiji, 2014.Bilten, 596/2015.Belgrade: Statistical Office of the Republic of Serbia (in Serbian).

Triantakonstantis, D.P., Kalivas, D.P., & Kollias, V.J. 2013. Autologistic regression and multicriteria evaluation models for the prediction of forest expansion. New Forests, 44(2), pp.163-181. Available at: https://doi.org/10.1007/s11056-012-9308-x.

Zadnik Stirn, L. 2006. Integrating the fuzzy analytic hierarchy process with dynamic programming approach for determining the optimal forest management decisions. Ecological Modelling, 194(1-3), pp.296-305. Available at: https://doi.org/10.1016/j.ecolmodel.2005.10.023.

Winkel, G., & Sotirov, M. 2011. An obituary for national forest programmes? Analyzing and learning from the strategic use of “new modes of governance” in Germany and Bulgaria. Forest Policy and Economics, 13(2), pp.143-154. Available at: https://doi.org/10.1016/j.forpol.2010.06.005.

Zadeh, L.A. 1965. Fuzzy sets. Information and Control, 8(3), pp.338-353. Available at: https://doi.org/10.1016/s0019-9958(65)90241-x.

Zarekar, A., Vahidi, H., Zamani, K.B., Ghorbani, S., & Jafari, H. 2012. Forest Fire Hazard Mapping Using Fuzzy AHP and GIS study area: Gilan province of Iran. International Journal on Technical and Physical Problems of Engineering, 12(4), pp.47-55.

Published
2019/01/08
Section
Review Papers