1. S ystems Analysis Laboratory Helsinki University of Technology 1 Raimo P. Hämäläinen Jyri Mustajoki Systems Analysis Laboratory Helsinki University of Technology http://www.hut.fi/Units/Systems.Analysis A Java-applet for Value Tree and AHP Analysis Global Multicriteria Decision Support by Web-HIPRE www.hipre.hut.fi

2. S ystems Analysis Laboratory Helsinki University of Technology 2 Web-HIPRE = HIerarchical PREference analysis on the World Wide Web Successor of the the decision support software HIPRE 3+ Unlimited global access Opens up a new dimension in decision support Use by a Java-enabled browser The first interactive MCDM software on the Internet

3. S ystems Analysis Laboratory Helsinki University of Technology 3 www.decisionarium.hut.fi Group Collaboration Decision Making Computer Support CSCW Multicriteria Decision Analysis Internet Group Decision Making Web-HIPRE Opinion-Online Joint Gains GDSS, NSS DSS HIPRE 3+ WINPRE PRIME Solver

4. S ystems Analysis Laboratory Helsinki University of Technology 4 Computer-Supported Collaborative Decision Making Physical distance is no longer a barrier Internet provides an easy way to communicate and share information Individual models can be processed synchronously or asynchronously Group results easy to combine Global Platform for Individual and Group Decision Support

5. S ystems Analysis Laboratory Helsinki University of Technology 5 Starting Window

6. S ystems Analysis Laboratory Helsinki University of Technology 6 Completely mouse-driven structuring of the value tree This example: Selecting a cellular phone Web-HIPRE Main Window

7. S ystems Analysis Laboratory Helsinki University of Technology 7 Each element can be linked to a web-page Links can contain additional WWW-links, graphics, sound or video This can increase the quality of decision support dramatically On-line help also implemented by WWW-links WWW-links in Web-HIPRE

8. S ystems Analysis Laboratory Helsinki University of Technology 8 Web-HIPRE links can refer to any web-pages

9. S ystems Analysis Laboratory Helsinki University of Technology 9 Web-HIPRE links can refer to any web-pages

10. S ystems Analysis Laboratory Helsinki University of Technology 10 On-line help

11. S ystems Analysis Laboratory Helsinki University of Technology 11 Direct weighting, SMART, SWING SMARTER - rank based Pairwise Comparisons (AHP) Value Functions Any combinations of these Weighting Methods supported by Web-HIPRE

12. S ystems Analysis Laboratory Helsinki University of Technology 12 Note: Weights in this example are her personal opinions Direct Weighting

13. S ystems Analysis Laboratory Helsinki University of Technology 13 SMARTER uses rankings only SWING,SMART and SMARTER Methods

14. S ystems Analysis Laboratory Helsinki University of Technology 14 Continuous scale 1-9 Numerical, verbal or graphical approach Pairwise Comparison - AHP

15. S ystems Analysis Laboratory Helsinki University of Technology 15 Ratings of alternatives shown Any shape of the value function allowed Value Function

16. S ystems Analysis Laboratory Helsinki University of Technology 16 Combinations of methods allowed Each element can store all methods Selections shown by indicators Combined Use of Weighting Methods

17. S ystems Analysis Laboratory Helsinki University of Technology 17 Bar graphs or numerical values Bars divided by the contribution of each criterion Composite Priorities

18. S ystems Analysis Laboratory Helsinki University of Technology 18 Total weights of alternatives shown with respect to the weight of the criterion Sensitivitity Analysis

19. S ystems Analysis Laboratory Helsinki University of Technology 19 Group model is the weighted sum of individual decision makers’ composite priorities for the alternatives Group Decision Support

20. S ystems Analysis Laboratory Helsinki University of Technology 20 Individual value trees can be different Composite priorities of each group member - obtained from their individual models - shown in the definition phase Defining Group Members

21. S ystems Analysis Laboratory Helsinki University of Technology 21 Contribution of each group member indicated by segments Aggregate Group Priorities

22. S ystems Analysis Laboratory Helsinki University of Technology 22 Changes in the relative importance of decision makers can be analyzed Sensitivity analysis

23. S ystems Analysis Laboratory Helsinki University of Technology 23 Browser loads Web- HIPRE -applet, which operates in the memory of the local computer Nothing remains on the local computer after closing Web-HIPRE Models are saved on the server computer and operated via file server Web-HIPRE can also be installed locally Web-HIPRE Architecture

24. S ystems Analysis Laboratory Helsinki University of Technology 24 Models can be saved on the Web-HIPRE server to a public directory to your own password protected directory On the Internet use models cannot be saved on user’s local machine due to Java security reasons A local server can be installed to save models locally HIPRE 3+ models can be imported Model Handling in Web-HIPRE

25. S ystems Analysis Laboratory Helsinki University of Technology 25 Local use of Web-HIPRE Web-HIPRE can be installed on a local computer The file server is on the user’s computer  Models are saved locally Locally installed Web-HIPRE can also be used via the Internet or via Local Area Network (LAN) Organizations can install Web-HIPRE on their Intranet

26. S ystems Analysis Laboratory Helsinki University of Technology 26 Value prioritizations related to the regulation policy for Lake Päijänne Decision analysis interviews of stakeholders Open for public prioritizations Real Life Use of Web-HIPRE

27. S ystems Analysis Laboratory Helsinki University of Technology 27 www.paijanne.hut.fi Web-Page for the Lake Päijänne Case

28. S ystems Analysis Laboratory Helsinki University of Technology 28 www.hipre.hut.fi Model for cellular phone example: cellular.jmd Site will be open free of charge for academic use. Please, let us know your experiences: raimo@hut.fi, jyri.mustajoki@hut.fi The WWW-address of Web-HIPRE:

29. S ystems Analysis Laboratory Helsinki University of Technology 29 Edwards, W. and F.H. Barron, “SMARTS and SMARTER: Improved simple methods for multiattribute utility measurement”, Organizational Behavior and Human Decision Processes, 60, 1994, pp. 306-325. French, S., L. Simpson, E. Atherton, V. Belton, R. Dawes, W. Edwards, R.P. Hämäläinen, O. Larichev, F. Lootsma, A. Pearman and C. Vlek, “Problem Formulation for Multi-Criteria Decision Analysis: Report of a Workshop”, Journal of Multi-Criteria Decision Analysis, 7, 1998, pp. 242-262. Hämäläinen, R.P., “Computer Assisted Energy Policy Analysis in the Parliament of Finland,” Interfaces, 18(4), 1988, pp. 12-23. Hämäläinen, R.P. and H. Lauri, “HIPRE 3+ Decision Support Software vs. 3.13, User’s Guide”, Systems Analysis Laboratory, Helsinki University of Technology, 1993. Hämäläinen, R.P. and E. Kettunen, “On-Line Group Decision Support by HIPRE 3+ Group Link”, Proc. of the Third Int. Conference on Analytic Hierarchy Process, July 11-13, 1994, George Washington University, Washington D.C., pp. 547-557. Hämäläinen, R.P., E. Kettunen, M. Marttunen and H. Ehtamo, “Evaluating a framework for multi-stakeholder decision support in water resources management, Group Decision and Negotiation, 2000. (to appear) Marttunen, M. and R.P. Hämäläinen, “Decision Analysis Interviews in Environmental Impact Assessment,” European Journal of Operational Research, 87, 1995, pp. 551-563. Maxwell, D.T., “Decision Analysis: Aiding Insight V”, OR/MS Today, October 2000, pp. 28-35. Mustajoki, J. and R.P. Hämäläinen, “Web-HIPRE: Global decision support by value tre and AHP analysis”, INFOR, 38, 3, Aug. 2000. Related references

30. S ystems Analysis Laboratory Helsinki University of Technology 30 Pöyhönen, M. and R.P. Hämäläinen, “On the convergence of multiattribute weighting methods”, European Journal of Operational Research, 2001. (to appear) Pöyhönen, M., R.P. Hämäläinen and A. A. Salo, “An Experiment on the Numerical Modelling of Verbal Ratio Statements”, Journal of Multi-Criteria Decision Analysis, 6, 1997, pp. 1-10. Pöyhönen, M., H.C. Vrolijk, and R.P. Hämäläinen, “Behavioral and Procedural Consequences of Structural Variation in Value Trees”, European Journal of Operational Research, 2001. (to appear) Pöyhönen, M. and R.P. Hämäläinen, ‘Notes on the Weighting Biases in Value Trees’, Journal of Behavioral Decision Making, 11, 1998, pp. 139-150. Pöyhönen, M. and R.P. Hämäläinen, “There is hope in attribute weighting”, INFOR, 38, 3, Aug. 2000. Saaty, T.L., ‘The Analytic Hierarchy Process’, McGraw-Hill, Inc., 1980. Salo, A.A., “Interactive decision aiding for group decision support,” European Journal of Operational Research, 84, 1995, pp. 134-149. Salo, A.A. and R.P. Hämäläinen, “On the Measurement of Preferences in the Analytic Hierarchy Process” (and comments by V. Belton, E. Choo, T. Donegan, T. Gear, T. Saaty, B. Schoner, A. Stam, M. Weber, B. Wedley), Journal of Multi-Criteria Decision Analysis, 6, 1997, pp. 309-343. von Winterfeldt, D. and W. Edwards, ‘Decision Analysis and Behavioral Research’, Cambridge University Press, 1986. Related references