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  1. Aiding Decisions, Negotiating and Collecting Opinions on the Web D E C I S I O N A R I U M www.decisionarium.hut.fi Raimo P. Hämäläinen Systems Analysis Laboratory Helsinki University of Technology www.raimo.hut.fi JMCDA, Vol. 12 , No. 2-3, 2003, pp. 101-110. v. 3.2006

  2. Systems Analysis Laboratory Updated 25.10.2004 D E C I S I O N A R I U M g l o b a l s p a c e f o r d e c i s i o n s u p p o r t group decision making multicriteria decision analysis group collaboration decision making GDSS, NSS Joint Gains multi-party negotiation support with the method of improving directions RICH Decisions rank inclusion in criteria hierarchies CSCW DSS Opinions-Online Windows software for decision analysis with imprecise ratio statements platform for global participation, voting, surveys, and group decisions internet PRIME Decisions computer support WINPRE preference programming, PAIRS Web-HIPRE Smart-Swaps value tree and AHP based decision support web-sites www.decisionarium.hut.fi www.dm.hut.fi www.hipre.hut.fi www.jointgains.hut.fi www.opinions.hut.fi www.smart-swaps.hut.fi www.rich.hut.fi PRIME Decisions and WINPRE downloadable at www.sal.hut.fi/Downloadables selected publications J. Mustajoki, R.P. Hämäläinen and A. Salo: Decision support by interval SMART/SWING – Incorporating imprecision in the SMART and SWING methods, Decision Sciences, 2005. H. Ehtamo, R.P. Hämäläinen and V. Koskinen: An e-learning module on negotiation analysis, Proc. of HICSS-37, 2004. J. Mustajoki and R.P. Hämäläinen, Making the even swaps method even easier, Manuscript, 2004. R.P. Hämäläinen, Decisionarium - Aiding decisions, negotiating and collecting opinions on the Web, J. Multi-Crit. Dec. Anal., 2003. H. Ehtamo, E. Kettunen and R.P. Hämäläinen: Searching for joint gains in multi-party negotiations, Eur. J. Oper. Res., 2001. J. Gustafsson, A. Salo and T. Gustafsson: PRIME Decisions - An interactive tool for value tree analysis, Lecture Notes in Economics and Mathematical Systems, 2001. J. Mustajoki and R.P. Hämäläinen: Web-HIPRE - Global decision support by value tree and AHP analysis, INFOR, 2000. elimination of criteria and alternatives by even swaps

  3. Mission of Decisionarium Provide resources for decision and negotiation support and advance the real and correct use of MCDA History: HIPRE 3+ in 1992 MAVT/AHP for DOS systems Today: e-learning modules provide help to learn the methods and global access to the software also fornon OR/MS people

  4. Opinions-Online (www.opinions.hut.fi) • Platform for global participation, voting, surveys, and group decisions Web-HIPRE (www.hipre.hut.fi) • Value tree based decision analysis and support WINPRE andPRIME Decisions (for Windows) • Interval AHP, interval SMART/SWING and PRIME methods RICH Decisions (www.rich.hut.fi) • Preference programming in MAVT Smart-Swaps (www.smart-swaps.hut.fi) • Multicriteria decision support with the even swaps method Joint Gains (www.jointgains.hut.fi) • Negotiation support with the method of improving directions

  5. New Methodological Features • Possibility to compare different weighting and rating methods • AHP/MAVT and different scales • Preference programming in MAVT and in the Even Swaps procedure • Jointly improving direction method for negotiations

  6. eLearning Decision Making www.dm.hut.fi SAL eLearning sites: Multiple Criteria Decision Analysis www.mcda.hut.fi Decision Making Under Uncertainty Negotiation Analysis www.negotiation.hut.fi

  7. Opinions-OnlinePlatform for Global Participation, Voting, Surveys and Group Decisions www.opinions.hut.fi www.opinions-online.com Design: Raimo P. Hämäläinen Programming: Reijo Kalenius Systems Analysis Laboratory Helsinki University of Technology http://www.sal.hut.fi

  8. Surveys on the web • Fast, easy and cheap • Hyperlinks to background information • Easy access to results • Results can be analyzed on-line • Access control: registration, e-mail list, domain, password

  9. Creating a new session • Browser-based generation of new sessions • Fast and simple • Templates available

  10. Possible questions • Survey section Multiple/single choice • Best/worst • Ranking • Rating • Approval voting • Written comments

  11. Viewing the results • In real-time • By selected fields • Questionwise public or restricted access • Barometer • Direct links to results

  12. Approval voting • The user is asked to pick the alternatives that he/she can approve • Often better than a simple “choose best” question when trying to reach a consensus

  13. Advanced voting ruleswww.opinion.vote.hut.fi • Condorcet criteria • Copeland’s methods, Dodgson’s method, Maximin method • Borda count • Nanson’s method, University method • Black’s method • Plurality voting • Coombs’ method, Hare system, Bishop method

  14. Examples of use • Teledemocracy – interactive citizens’ participation • Group decision making • Brainstorming • Course evaluation in universities and schools • Marketing research • Organisational surveys and barometers

  15. Global Multicriteria Decision Support by Web-HIPREA Java-applet for Value Tree and AHP Analysis www.hipre.hut.fi Raimo P. Hämäläinen Jyri Mustajoki Systems Analysis Laboratory Helsinki University of Technology http://www.sal.hut.fi

  16. Web-HIPRE links can refer to any web-pages

  17. Direct Weighting Note: Weights in this example are her personal opinions

  18. SWING,SMART and SMARTER Methods • SMARTER uses rankings only

  19. Pairwise Comparison - AHP • Continuous scale 1-9 • Numerical, verbal or graphical approach

  20. Value Function • Ratings of alternatives shown • Any shape of the value function allowed

  21. Composite Priorities • Bar graphs or numerical values • Bars divided by the contribution of each criterion

  22. Group Decision Support • Group model is the weighted sum of individual decision makers’ composite priorities for the alternatives

  23. Defining Group Members • Individual value trees can be different • Composite priorities of each group member • - obtained from their individual models • - shown in the definition phase

  24. Aggregate Group Priorities • Contribution of each group member indicated by segments

  25. Sensitivity analysis • Changes in the relative importance of decision makers can be analyzed

  26. Future challenges • Web makes MCDA tools available to everybody - • Should everybody use them? • It is the responsibility of the multicriteria decision • analysis community to: • Learn and teach the use different weighting methods • Focus on the praxis and avoidance of behavioural biases • Develop and identify “best practice” procedures

  27. Sources of biases and problems

  28. Visits to Web-HIPRE

  29. Visitors’ top-level domains

  30. Visitors’ first-level domains

  31. Visits through sites linking to Web-HIPRE

  32. Literature Mustajoki, J. and Hämäläinen, R.P.: Web-HIPRE: Global decision support by value tree and AHP analysis, INFOR, Vol. 38, No. 3, 2000, pp. 208-220. Hämäläinen, R.P.: Reversing the perspective on the applications of decision analysis, Decision Analysis, Vol. 1, No. 1, pp. 26-31. Mustajoki, J., Hämäläinen, R.P. and Marttunen, M.: Participatory multicriteria decision support with Web-HIPRE: A case of lake regulation policy. Environmental Modelling & Software, Vol. 19, No. 6, 2004, pp. 537-547. Pöyhönen, M. and Hämäläinen, R.P.: There is hope in attribute weighting, INFOR, Vol. 38, No. 3, 2000, pp. 272-282. Pöyhönen, M. and Hämäläinen, R.P.: On the Convergence of Multiattribute Weighting Methods, European Journal of Operational Research, Vol. 129, No. 3, 2001, pp. 569-585. Pöyhönen, M., Vrolijk, H.C.J. and Hämäläinen, R.P.: Behavioral and Procedural Consequences of Structural Variation in Value Trees, European Journal of Operational Research, Vol. 134, No. 1, 2001, pp. 218-227.

  33. New Theory: Preference programming Analysis with incompletepreference statements (intervals): ”...attribute is at least 2 times as but no more than 3 times as important as...” Windows software • WINPRE – Workbench for Interactive Preference Programming Interval AHP, interval SMART/SWING and PAIRS • PRIME-Preference Ratios in Multiattribute Evaluation Method Incomplete preference statements Web software • RICH Decisions – Rank Inclusion in Criteria Hierarchies

  34. Preference Programming – The PAIRS method • Imprecise statements with intervals on • Attribute weight ratios (e.g. 1/2w1/ w2 3)  Feasible region for the weights • Alternatives’ ratings (e.g. 0.6  v1(x1)  0.8)  Intervals for the overall values • Lower bound for the overall value of x: • Upper bound correspondingly

  35. Interval statements define a feasible region S for the weights

  36. Uses of interval models New generalized AHP and SMART/SWING methods DM can also reply with intervals instead of exact point estimates – a new way to accommodate uncertainty Interval sensitivity analysis Variations allowed in several model parameters simultaneously - worst case analysis Group decision making All members´ opinions embedded in intervals = a joint common group model

  37. Interval SMART/SWING • A as reference - A given 10 points • Point intervals given to the other attributes: • 5-20 points to attribute B • 10-30 points to attribute C • Weight ratio between B and C not explicitly given by the DM

  38. WINPRE Software

  39. PRIME Decisions Software

  40. Literature – Methodology Salo, A. and Hämäläinen, R.P.: Preference assessment by imprecise ratio statements, Operations Research, Vol. 40, No. 6, 1992, pp. 1053-1061. Salo, A. and Hämäläinen, R.P.: Preference programming through approximate ratio comparisons, European Journal of Operational Research, Vol. 82, No. 3, 1995, pp. 458-475. Salo, A. and Hämäläinen, R.P.: Preference ratios in multiattribute evaluation (PRIME) – Elicitation and decision procedures under incomplete information, IEEE Transactions on Systems, Man and Cybernetics – Part A: Systems and Humans, Vol. 31, No. 6, 2001, pp. 533-545. Salo, A. and Hämäläinen, R.P.: Preference Programming. (Manuscript) Downloadable at http://www.sal.hut.fi/Publications/pdf-files/msal03b.pdf Mustajoki, J., Hämäläinen, R.P. and Salo, A.: Decision Support by Interval SMART/SWING - Incorporating Imprecision in the SMART and SWING Methods, Decision Sciences, Vol. 36, No.2, 2005, pp. 317-339.

  41. Literature – Tools and applications Gustafsson, J., Salo, A. and Gustafsson, T.: PRIME Decisions - An Interactive Tool for Value Tree Analysis, Lecture Notes in Economics and Mathematical Systems, M. Köksalan and S. Zionts (eds.), 507, 2001, pp. 165-176. Hämäläinen, R.P., Salo, A. and Pöysti, K.: Observations about consensus seeking in a multiple criteria environment, Proc. of the Twenty-Fifth Hawaii International Conference on Systems Sciences, Hawaii, Vol. IV, January 1992, pp. 190-198. Hämäläinen, R.P. and Pöyhönen, M.: On-line group decision support by preference programming in traffic planning, Group Decision and Negotiation, Vol. 5, 1996, pp. 485-500. Liesiö, J., Mild, P. and Salo, A.: Preference Programming for Robust Portfolio Modeling and Project Selection, European Journal of Operational Research (to appear) Mustajoki, J., Hämäläinen, R.P. and Lindstedt, M.R.K.: Using intervals for Global Sensitivity and Worst Case Analyses in Multiattribute Value Trees, European Journal of Operational Research. (to appear)

  42. RICH Decisions www.rich.hut.fi Design: Ahti Salo and Antti Punkka Programming: Juuso Liesiö Systems Analysis Laboratory Helsinki University of Technology http://www.sal.hut.fi

  43. The RICH Method Based on: Incomplete ordinal information about the relative importance of attributes • ”environmental aspects belongs to the three most important attributes” or • ”either cost or environmental aspects is the most important attribute”

  44. Score Elicitation • Upper and lower bounds for the scores • Type or use the scroll bar

  45. Weight Elicitation The user specifies sets of attributes and corresponding sets of rankings. Here attributes distance to harbour and distance to office are the two most important ones. The table displays the possible rankings.

  46. Dominance Structure and Decision Rules

  47. Literature Salo, A. and Punkka, A.: Rank Inclusion in Criteria Hierarchies, European Journal of Operational Research, Vol. 163, No. 2, 2005, pp. 338-356. Salo, A. and Hämäläinen, R.P.: Preference ratios in multiattribute evaluation (PRIME) – Elicitation and decision procedures under incomplete information, IEEE Transactions on Systems, Man and Cybernetics – Part A: Systems and Humans, Vol. 31, No. 6, 2001, pp. 533-545. Salo A. and Hämäläinen, R.P.: Preference Programming. (manuscript) Ojanen, O., Makkonen, S. and Salo, A.: A Multi-Criteria Framework for the Selection of Risk Analysis Methods at Energy Utilities. International Journal of Risk Assessment and Management, Vol. 5, No. 1, 2005, pp. 16-35. Punkka, A. and Salo, A.: RICHER: Preference Programming with Incomplete Ordinal Information. (submitted manuscript) Salo, A. and Liesiö, J.: A Case Study in Participatory Priority-Setting for a Scandinavian Research Program, International Journal of Information Technology & Decision Making. (to appear)

  48. Smart-SwapsSmart Choices with the Even Swaps Method www.smart-swaps.hut.fi Design: Raimo P. Hämäläinen and Jyri Mustajoki Programming: Pauli Alanaatu Systems Analysis Laboratory Helsinki University of Technology http://www.sal.hut.fi

  49. Smart Choices • An iterative process to support multicriteria decision making • Uses theeven swaps method to make trade-offs (Harvard Business School Press, Boston, MA, 1999)

  50. Even Swaps • Carry out even swaps that make Alternatives dominated (attribute-wise) • There is another alternative, which is equal or better than this in every attribute, and better at least in one attribute Attributes irrelevant • Each alternative has the same value on this attribute  These can be eliminated • Process continues until one alternative, i.e. the best one, remains