Decision and Negotiation Support in Multi-Stakeholder Development of Lake Regulation Policy

1. Decision and Negotiation Support in Multi-Stakeholder Development of Lake Regulation Policy - Report on the testing phase Raimo P. Hämäläinen1, Eero Kettunen1, Mika Marttunen2, and Harri Ehtamo1 1 Systems Analysis Laboratory, Helsinki University of Technology 2Finnish Environment Institute http://www.hut.fi/Units/Systems.Analysis/

2. The Framework 1. Structuring the problem 2. Identifying Pareto-optimal alternatives 3. Seeking group consensus 4. Seeking public acceptance • Objective to provide support for the whole decision process

3. Information Technology Dynamic policy alternatives: ISMO - Interactive analysis of dynamic water regulation Strategies by Multicriteria Optimization Problem Structuring - comparison of policy alternatives: HIPRE 3+ Web-HIPRE

4. Public - acceptance: Opinion Online - Web-based survey and voting Pareto-optimal policies: Joint Gains - Generating efficient alternatives (in testing with simplefied goals) Group-consensus: HIPRE Grouplink (Interval AHP model) WINPRE - Workbench for Interval Preference Programming (Interval AHP, SMART/SWING)

5. Development of Water Level Management Policy in Lake Päijänne • Illustrative reference case • Regulation policy defined by annual water level goals • Stakeholders with conflicting objectives • Hydro power producers, fishermen, farmers, ... • First phase of true testing • Role playing experiments

6. 10 40 0 30 50 20 km LAKE PÄIJÄNNE LAKES RUOTSALAINEN AND KONNIVESI LAKE PYHÄJÄRVI RIVER KYMIJOKI

7. Need for modeling and decision support • Dynamic system • No intuitive solutions - impacts are functions of decision variables • Interactive analysis of impacts • Multiple criteria • Many stakeholder groups

9. Water level Water level Outflow Outflow Utopia solution Realistic solution

10. Structuring the Problem • Iterative value tree analysis • Hierarchical structuring and prioritization • Decision criteria • Learning the ranges by initial prioritizations with temporary alternatives • Stakeholder grouping • Decision variables defining regulation policy • Target water levels at April 1st and September 1st

11. Value tree analysis by Web-HIPRE

12. Method of Improving Directions • Ehtamo, Kettunen and Hämäläinen (1998) • Interactive method for identification of efficient alternatives - Joint Gains software • Subjects are onlygiven simple comparison tasks: “Which one of these alternatives do you prefer most?” or “Which one of these two alternatives do you prefer, A or B?”

13. Pareto-efficiency in group settings Inefficient alternative: Alternatives preferred to x by DM1 Alternatives preferred to x by DM2 x Efficient alternative:

14. Approximating DM’s utility function’s gradient direction x2 Most preferred alternative on the circle Approximation at x x x1

15. Calculation of jointly improving direction • Required preference information: DMs’ utility functions’ gradient directions • Solution of a nonlinear direction finding optimization problem • Special case with two DMs: bisecting direction

16. Iteration step • DMs select most preferred points in this direction • New iteration point: nearest x2 DM1 DM2 DM1 Jointly improving direction x DM2 x1

17. x2 Efficient frontier x1 Generation of efficient frontier from different initial points

18. Joint Gains DM interface Subject 1: “environmentalist” Joint Gains- Negotiation Support System Subject 5: “power company” Joint Gains DM interface Joint Gains Mediator Joint Gains DM interface Subject 4: “farmer” Local area network questions replies Joint Gains DM interface Joint Gains DM interface Subject 3: “fisherman” Subject 2: “summer resident”

19. Interfaces for comparison tasks Scanning alternatives or Answer a series of pairwise comparison questions B A A etc. B

20. Proposal for jointly preferred alternative Y X

21. Role Playing Experiments • Roles (fisherman, environmentalist, summer resident, farmer, power company) and objectives (e.g., high and diverse catch, natural reproduction) given • 2 or 3 subjects in 9 test groups Questions of interest: • Subjects’ opinion about the tasks • Consistency of statements • Convergence speed

22. initial and intermediate points stopping point Mediation processes for 2 DM groups Roles: Environmentalist & Farmer Fisherman & Environmentalist Fisherman & Summer resident

23. initial and intermediate points stopping point Mediation processes for 2 DM groups Roles: Fisherman & Environmentalist Power company & Environmentalist Fisherman & Power company

24. initial and intermediate points stopping point Mediation processes for 2 and 3 DM groups Roles: Fisherman & Farmer Summer resident & Environmentalist Farmer, Power company & Summer resident

25. Role playing experiments - observations • Subjects found the stated questions easy to reply with both elicitation methods • Statements and results were consistent with the given role objectives • Experiment suggests a high speed of convergence • Low degree of conflict (similar objectives) Þ same nearby points reached from different initial points

26. Seeking Group Consensus • Select and evaluate a representative set of efficient alternatives by interval value tree analysis • Objective to reach consensus • Tools for consensus seeking • HIPRE 3+ Group Link • WINPRE - Workbench for Interactive Preference Programming

27. HIPRE Group Link Individual AHP prioritizations (HIPRE) Combination of prioritizations (Group Link) Interval preference model (WINPRE) View from interval preference model for three DMs: Recreation Recreation Landscape Landscape Biodiversity Biodiversity DM1 DM2 DM3 DM2 DM3 DM1 DM2 DM1 DM3

28. WINPRE - Workbench for Interactive Preference Programming (AHP mode) Group priorities embedded in the interval statements

29. Conclusion • Framework for supporting complex decision processes • An evolutionary learning process • Shown to be feasible by role playing experiments • Real application • Testing of methods and tools • Biases related to elicitation procedure tested • Important testing phase often neglected • Allows improvements before final process

30. References WWW-sites Systems Analysis Laboratory Activity Report: http://www.hut.fi/Units/SAL/Research/. WINPRE - Workbench for Interactive Preference Programming v. 1.0, Computer software, Systems Analysis Laboratory, Helsinki University of Technology. Downloadable at http://www.hut.fi/Units/SAL/Downloadables/. Web-HIPRE - Java-applet for Value Tree and AHP Analysis, Computer software, Systems Analysis Laboratory, Helsinki University of Technology (http://www.hipre.hut.fi). The Päijänne regulation policy project: (http://leino.hut.fi/päijänne.htm) References Ehtamo, H., R. P. Hämäläinen, P. Heiskanen, J. Teich, M. Verkama, and S. Zionts (1998), “Generating Pareto Solutions in Two-Party Negotiations by Adjusting Artificial Constraints,” Manuscript, Systems Analysis Laboratory, Helsinki University of Technology. Downloadable at http://www.hut.fi/Units/SAL/Publications/. Ehtamo, H., E. Kettunen, and R. P. Hämäläinen (1998), “Searching for Joint Gains in Multi-Party Negotiations,” Manuscript, Systems Analysis Laboratory, Helsinki University of Technology. Downloadable at http://www.hut.fi/Units/SAL/Publications/. R.P. Hämäläinen, E. Kettunen, M. Marttunen and H. Ehtamo: An approach to decision and negotiation support in multi-stakeholder development of lake regulation policy. Manuscript, Systems Analysis Laboratory, Helsinki University of Technology. Downloadable at http://www.hut.fi/Units/SAL/Publications/.

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