Test
From COST Action FP0804: FORSYS
Methods and Dimensions
| Has temporal scale | Long term (strategic) |
|---|---|
| Has spatial context | Spatial with no neighbourhood interrelations |
| Has spatial scale | Forest level |
| Has objectives dimension | Multiple objectives |
| Has goods and services dimension | Market wood products |
| Has decision making dimension | More than one decision maker/stakeholder |
| Has risk/uncertainty analysis | no |
| Has advantages | AHP is a relatively simple and transparent method which is an advantage in participatory planning. |
| Has disadvantages | Using the standard AHP with pairwise comparisons of both criteria and alternatives may be cognitively demanding to the DM(s) with a larger number of criteria and alternatives. In turn, this may lead to inconsistency in preferences. |
| Has main contraints | The number of elements to be compared at each level should probably not exceed 4-5. |
| Has related method | Yes, using AHP in combination with other methods (regression, value functions, etc) may decrease the number of comparisons |
| Has method | Multi criteria decision analysis |
| Has submethods | Analytic Hierarchy Process (AHP) |
| Has detailed description of methods application in the DSS | In AHP, pairwise comparisons are made of criteria, and also of alternatives in terms of each criterion. The strenght of preference for one criteria/alternative over another is stated on a nine point ratio scale. Thus, each set of comparisons can be ordered in a n x n matrix. Weights for the criteria and alternatives are calculated by determining the eigenvector corresponding to the largest eigenvalue of each matrix (the so called eigenvalue technique).The overall priority of each alternative is then calculated by multiplying the criteria weight with the weight for the alternative with respect to the criteria in question. |
| Uses programming language | C++, C#, PHP, Visual Basic |
| Has reference | Nordström E.-M., Eriksson Ljusk O. & 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): 562-574. |
| Has related DSS | In this paper, no full DSS was used, Web-HIPRE was used for the AHP. Since then, AHP has been implemented in the Heureka PlanEval application. |
