Advertisement

Collaborative Management of Ecosystem Services in Natural Parks Based on AHP and PROMETHEE

  • Marina SeguraEmail author
  • Concepción Maroto
  • Valerie Belton
  • Concepción Ginestar
  • Inmaculada Marqués
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 274)

Abstract

Management of protected areas has been focusing on conservation and recreation. Nevertheless, current governance trends include other ecosystem services from social and economic perspectives by involving stakeholders. The objectives of this chapter are to select and prioritize projects, as well as to develop new indicators based on the main functions of ecosystems to classify the territory inside protected areas. Both purposes take into account the provided ecosystem services and the stakeholders’ preferences in order to implement a collaborative decision making tool in a forest Natural Park.

When applying AHP in order to elicit people’s preferences, it is important to have a graphic tool, which allows answering pair comparisons easily, obtaining the inconsistency index online and facilitating the revision of their answers. This case study provides a friendly implementation with macros in Excel, which enables the users to elicit and then revise their judgments if their inconsistency index is not acceptable, increasing by a lot the percentage of consistent surveys. The Excel application aggregates judgments from a group of people by the geometric mean in order to derive priorities for collaborative management. Although PROMETHEE is applied by using D-Sight software, we provide its implementation in Excel for illustrative purposes. This outranking approach enables us to select and prioritize projects and generates indicators to classify areas of the territory according to their main ecosystem services. These indicators are shown in graphs, which are simple to understand, providing relevant information for collaborative management of Natural Parks.

References

  1. Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200, 198–215.  https://doi.org/10.1016/j.ejor.2009.01.021.CrossRefGoogle Scholar
  2. Brans, J. P., & Mareschal, B. (2005). PROMETHEE methods, chapter 5. In J. Figuera, S. Greco, & M. Ehrgott (Eds.), Multiple criteria decision analysis, State of the art surveys (pp. 163–195). New York, NY: Springer.CrossRefGoogle Scholar
  3. Chai, J. Y., Liu, J. N., & Ngai, E. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40, 3872–3885.CrossRefGoogle Scholar
  4. de Almeida, A., Cavalcante, C. R., Alencar, M. H., Ferreira, R., de Almeida-Filho, A., & Vitelli, T. (2015). Multicriteria and multiobjective models for risk, decision analysis reliability and maintenance, International series in operations research & management science. Cham: Springer.CrossRefGoogle Scholar
  5. De Brucker, K., Macharis, C., & Verbeke, A. (2013). Multi-criteria analysis and the resolution of sustainable development dilemmas: A stakeholder management approach. European Journal of Operational Research, 224(1), 122–131.  https://doi.org/10.1016/j.ejor.2012.02.021.CrossRefGoogle Scholar
  6. D-Sight. (2013). http://www.d-sight.com
  7. Expert Choice Comparion Core. (2013). www.expertchoice.com
  8. Fontana, V., Radtke, A., Bossi Fedrigotti, V., Tappeiner, U., Tasser, E., Zerbe, S., & Buchholz, T. (2013). Comparing land-use alternatives: Using the ecosystem services concept to define a multi-criteria decision analysis. Ecological Economics, 93, 128–136.  https://doi.org/10.1016/j.ecolecon. 2013.05.007.CrossRefGoogle Scholar
  9. González-Pachón, J., & Romero, C. (2004). A method for dealing with inconsistencies in pairwise comparisons. European Journal of Operational Research, 158(2), 351–361.CrossRefGoogle Scholar
  10. González-Pachón, J., & Romero, C. (2007). Inferring consensus weights from pairwise comparison matrices without suitable properties. Annals of Operational Research, 154(1), 123–132.CrossRefGoogle Scholar
  11. Hillier, F. S., & Hillier, M. S., (2011). Introduction to management science. A modelling and case studies approach with spreadsheets (4th ed.). Burr Ridge, IL: McGraw-Hill.CrossRefGoogle Scholar
  12. Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202, 16–24.CrossRefGoogle Scholar
  13. Ishizaka, A., & Labib, A. (2011). Review of the main developments in the analytic hierarchy process. Expert Systems with Applications, 38, 14336–14345.CrossRefGoogle Scholar
  14. Macharis, C., Turcksin, L., & Lebeau, K. (2012). Multi Actor Multi Criteria Analysis (MAMCA) as a tool to support sustainable decisions: State of use. Decision Support Systems, 54, 610–620.  https://doi.org/10.1016/j.dss.2012.08.008.CrossRefGoogle Scholar
  15. Maroto, C., Alcaraz, J., Ginestar, C., & Segura, M. (2014). Operations research in business administration and management. Universitat Politécnica de Valencia.Google Scholar
  16. Maroto, C., Segura, M., Ginestar, C., Uriol, J., & Segura, B. (2013). Sustainable forest management in a Mediterranean region: Social preferences. Forest Systems, 22(3), 546–558.  https://doi.org/10.5424/fs/2013223-4135.CrossRefGoogle Scholar
  17. Marqués-Pérez, I., Segura, B., & Maroto, C. (2014). Evaluating the functionality of agricultural systems: Social preferences for multifunctional peri-urban agriculture. The “Huerta de Valencia” as case study. Spanish Journal of Agricultural Research, 12(4), 889–901.  https://doi.org/10.5424/sjar/2014124-6061.CrossRefGoogle Scholar
  18. Martinez-Harms, M. J., Bryan, B. A., Balvanera, P., Law, E. A., Rhodes, J. R., Possingham, H. P., & Wilson, K. A. (2015). Making decisions for managing ecosystem services. Biological Conservation, 184, 229–238.  https://doi.org/10.1016/j.biocon.2015.01.024.CrossRefGoogle Scholar
  19. Mendoza, G. A., & 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.  https://doi.org/10.1016/j.foreco.2006.03.023.CrossRefGoogle Scholar
  20. Millennium Ecosystem Assessment. (2003). MA conceptual framework. In Ecosystems and human well-being: A framework for assessment (pp. 25–36). Island Press. Retrieved from http://www.millenniumassessment.org/documents/document.765.aspx.pdf
  21. Powell, S. G., & Baker, R. K. (2016). Business analytics: The art of modeling with spreadsheets (5th ed.). New York: Wiley.Google Scholar
  22. Saaty, T. L. (2006). Fundamentals of decision making and priority theory with the analytic hierarchy process (p. 478). Pittsburgh, USA: RWS Publications.Google Scholar
  23. Saaty, T. L., & Islam, R. (2015). Hierarchon Vol. 2: A dictionary of AHP hierarchies (p. 320). Pittsburgh: RWS Publications.Google Scholar
  24. Saaty, T. L., & Peniwati, K. (2008). Group decision making: Drawing out and reconciling differences (p. 385). Pittsburgh, USA: RWS Publications.Google Scholar
  25. Saaty, T. L., & Vargas, L. G. (2001). Models, methods, concepts & applications of the analytic hierarchy process (p. 333). Boston: Kluwer Academic.CrossRefGoogle Scholar
  26. Segura, M., & Maroto, C. (2017). A multiple criteria supplier segmentation using outranking and value function methods. Expert Systems with Applications, 69, 87–100.  https://doi.org/10.1016//j.eswa.2016.10.031.CrossRefGoogle Scholar
  27. Segura, M., Maroto, C., Belton, V., & Ginestar, C. (2015). A new collaborative methodology for assessment and management of ecosystem services. Forests, 6(5), 1696–1720.CrossRefGoogle Scholar
  28. Segura, M., Ray, D., & Maroto, C. (2014). Decision support systems for forest management: A comparative analysis and assessment. Computers and Electronics in Agriculture, 101, 55–67.CrossRefGoogle Scholar
  29. Xu, Z. (2000). On consistency of the weighted geometric mean complex judgement matrix in AHP. European Journal of Operational Research, 126, 683–687.  https://doi.org/10.1016/S0377-2217(99)00082-X CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Marina Segura
    • 1
    Email author
  • Concepción Maroto
    • 1
  • Valerie Belton
    • 2
  • Concepción Ginestar
    • 1
  • Inmaculada Marqués
    • 3
  1. 1.Department of Applied Statistics and Operations Research, and QualityUniversitat Politècnica de ValènciaValenciaSpain
  2. 2.Department Management ScienceUniversity of StrathclydeGlasgowUK
  3. 3.Department of Economic and Social ScienceUniversitat Politècnica de ValènciaValenciaSpain

Personalised recommendations