Systems Analysis Laboratory Helsinki University of Technology An e-Learning module on Negotiation Analysis Harri Ehtamo Raimo P Hämäläinen Ville Koskinen Systems Analysis Laboratory Helsinki University of Technology

Systems Analysis Laboratory Helsinki University of Technology SAL e-learning resources in decision making Value Tree AnalysisGroup Decisions and Voting Uncertainty & RiskNegotiation Analysis

Systems Analysis Laboratory Helsinki University of Technology Negotiation analysis learning module  Material on mathematical models of negotiation analysis  Modular structure  Focus on learning by doing  Use of interactive web-based negotiation support software, Joint Gains  Negotiating parties can be in different locations

Systems Analysis Laboratory Helsinki University of Technology To whom 1. University students  Understand basic negotiation analysis models  Practical experience in analytical negotiation support 2. Real negotiators or their assistants  Familiarize with the mathematical modeling approach  Understanding and structuring of game settings  Role-playing in surrogate negotiations

Systems Analysis Laboratory Helsinki University of Technology Need for negotiation support  Political and environmental decision making  Management of natural resources  Negotiations on discharge limits  International conflict resolution  Labor – management negotiations  etc.  E-commerce applications  Buyer – seller negotiations on price, delivery time, quantity, etc.

Systems Analysis Laboratory Helsinki University of Technology  E-learning course at Concordia University (G. Kersten)  Electronic textbook, cases  Interactive negotiation assignments  Use of INSPIRE software  Focus on  economics  game theory  social psychology E-negotiation sites

Systems Analysis Laboratory Helsinki University of Technology  “Yes! The On-Line Negotiator” Harvard Business School  Cases and related quizzes on principled negotiation  Game theory sites, e.g. by A. Roth  Interactive Java applets, electronic textbooks  Decision analysis  Decision analysis society  e-Learning modules at SAL e-Learning resources for negotiations

Systems Analysis Laboratory Helsinki University of Technology

Systems Analysis Laboratory Helsinki University of Technology System architecture Client Web browser HUT SAL server Software: Web-HIRPE Prime Decisions Joint Gains Opinions Online (voting version) HUT SAL server Software: Web-HIRPE Prime Decisions Joint Gains Opinions Online (voting version) Self Assessment & Grading Quiz Star Q&A Tool set Self Assessment & Grading Quiz Star Q&A Tool set

Systems Analysis Laboratory Helsinki University of Technology Value Tree Analysis Learning paths and modules Learning path: guided route through the learning material Learning module: represents 2-4 h of traditional lectures and exercises Assignments Theory Videos Cases Quizze s Learning Paths Evaluation Introduction to game theory and negotiation Module 3 Module 2

Systems Analysis Laboratory Helsinki University of Technology Value Tree Analysis Modular structure Theory HTML pages Case slide shows video clips Assignments online quizzes software tasks report templates Evaluation Opinions Online Web software Joint Gains video clips Assignments Theory Videos Cases Quizz es Learning Paths Evaluation Introduction to game theory and nego Module 3 Module 2

Systems Analysis Laboratory Helsinki University of Technology Ways of use  Different e-learning resources on the web can be used to produce larger learning entities  Material can be linked  Embedding e-learning modules into traditional courses: e.g. on environmental decision making or international affairs, e- commerce

Systems Analysis Laboratory Helsinki University of Technology  Basic concepts  Game theory  Mathematical models of negotiation analysis  Examples  Prisoners’ dilemma  Problem of commons  Buyer – seller negotiations  Joint Gains web software Material

Systems Analysis Laboratory Helsinki University of Technology Value Tree Analysis Theory  Main concepts in brief Introduction Multiple criteria decision making Game theory Axiomatic bargaining Negotiation analysis Jointly improving direction method Systems Analysis Laboratory Helsinki University of Technology

Systems Analysis Laboratory Helsinki University of Technology Value Tree Analysis Evaluation Cases Assignments Theory Intro MCDA Game Theory Axiomatic Bargaining Buyer – Seller Negotiations definition of a negotiation problem solving a negotiation problem interactively use of the Joint Gains software Problem of Commons solving a negotiation problem by value functions Buyer – Seller Negotiations definition of a negotiation problem solving a negotiation problem interactively use of the Joint Gains software Problem of Commons solving a negotiation problem by value functions

Systems Analysis Laboratory Helsinki University of Technology

Systems Analysis Laboratory Helsinki University of Technology Value Tree Analysis Assignments Quizzes 4-6 questions per theory section the student is asked to interpret graphs Quizzes 4-6 questions per theory section the student is asked to interpret graphs Software assignments negotiations with the Joint Gains learning by doing

Systems Analysis Laboratory Helsinki University of Technology Value Tree Analysis Video clips Videos illustrating the use of Joint Gains: Creating a negotiation case Negotiating with Joint Gains Viewing the results

Systems Analysis Laboratory Helsinki University of Technology Report templates for assignments Detailed instructions Available as MS Word document and HTML Detailed instructions Available as MS Word document and HTML

Systems Analysis Laboratory Helsinki University of Technology Introduction to game theory and negotiation learning module

Systems Analysis Laboratory Helsinki University of Technology The Jointly Improving Directions Method  Ehtamo, Verkama and Hämäläinen (1999, 2001)  The procedure generates step-by-step new jointly preferred points from an initial point  Interactive method for reaching Pareto points

Systems Analysis Laboratory Helsinki University of Technology Joint Gains software  Implements the Jointly Improving Directions Method  2 to N negotiating parties  2 to M continuous decision variables  Linear inequality constraints on variables  Administrator can create cases online  Parties can be distributed on the web

Systems Analysis Laboratory Helsinki University of Technology Joint Gains negotiation process 1)Identification of the most preferred directions 2)Determination of the compromise direction 3)Identification of the most preferred points in the compromise direction 4)Determination of the new intermediate point How to interactively identify parties’ most preferred  directions?  points on the compromise direction?

Systems Analysis Laboratory Helsinki University of Technology A contour of party’s utility function Improving directions for a party Party’s most preferred direction most preferred direction is the gradient of the utility function Issue A Issue B Intermediate point

Systems Analysis Laboratory Helsinki University of Technology Set of jointly improving directions Jointly improving directions Improving directions for party 2 Improving directions for party 1 Issue A Issue B

Systems Analysis Laboratory Helsinki University of Technology Compromise direction The compromise direction bisects the angle between the parties’ most preferred directions Issue A Issue B

Systems Analysis Laboratory Helsinki University of Technology Producing joint gains The method terminates at a Pareto point where the most preferred directions are opposite Issue A Issue B

Systems Analysis Laboratory Helsinki University of Technology Process generates Pareto points Utility of party 1 Utility of party 2 Pareto frontier

Systems Analysis Laboratory Helsinki University of Technology Joint Gains system architecture Case Administrator Party N Party 2 Party 1 World Wide Web... WWW Browser Mediator software SERVER

Systems Analysis Laboratory Helsinki University of Technology Joint Gains case creation

Systems Analysis Laboratory Helsinki University of Technology Joint Gains session creation

Systems Analysis Laboratory Helsinki University of Technology Joint Gains negotiations Online chat

Systems Analysis Laboratory Helsinki University of Technology Joint Gains negotiations Preference elicitation Viewing the results

Systems Analysis Laboratory Helsinki University of Technology Experiences  Introduction to game theory and negotiation analysis learning module  One of 11 learning sessions in an advanced web course on mathematical modeling  Students worked unassisted in different universities in Finland in one or two person groups  9 groups and 13 students

Systems Analysis Laboratory Helsinki University of Technology

Systems Analysis Laboratory Helsinki University of Technology

Systems Analysis Laboratory Helsinki University of Technology Summary of student evaluations  Enjoyed the session even if the module requires advanced skills  Generally did not need any personal guidance  Difficulties in the role-playing task in the assignment  Assistance of an instructor would have helped

Systems Analysis Laboratory Helsinki University of Technology Supporting real negotiations ?  Researchers or assistants can learn by role- playing in surrogate negotiations  Suitability of the Joint Gains approach for generating a set of Pareto points ?  Negotiators use the Joint Gains in facilitated / assisted sessions  Environmental policy problems  Lake-River regulation policy problem (Hämäläinen et al. 2001)  E-commerce  Is it of help to generate Pareto points ?

Systems Analysis Laboratory Helsinki University of Technology SAL e-learning resources   Decision making resources at Systems Analysis Laboratory  Links to student evaluations   e-Learning in Multiple Criteria Decision Analysis   e-Learning in Negotiation Analysis   Decision support tools and resources at Systems Analysis Laboratory USE IS FREE !

Systems Analysis Laboratory Helsinki University of Technology References Ehtamo, H. and R.P. Hämäläinen (2001). “Interactive Multiple-Criteria Methods for Reaching Pareto Optimal Agreements in Negotiations”. Group Decision and Negotiation, Vol. 10, Ehtamo, H., E. Kettunen and R.P. Hämäläinen (2001). “Searching for Joint Gains in Multi-Party Negotiations”. European Journal of Operational Research, Vol. 130, No. 1, Ehtamo, H., M. Verkama and R.P. Hämäläinen (1999). “How to Select Fair Improving Directions in a Negotiation Model over Continuous Issues”. IEEE Transactions on Systems Man and Cybernetics – Part C: Applications and Reviews, Vol. 29, Hämäläinen, R.P. and J. Dietrich (2002). Introduction to Value Tree Analysis: e-Learning Module. Systems Analysis Laboratory, Helsinki University of Technology, modules/. Hämäläinen, R.P., E. Kettunen, M. Marttunen and H. Ehtamo (2001). “Evaluating a Framework for Multi-Stakeholder Decision Support in Water Resources Management”. Group Decision and Negotiation, Vol. 10,

Systems Analysis Laboratory Helsinki University of Technology Web sites Kersten, G. (2002). “Negotiations and e-Negotiations: Management and Support”. Concordia University. (referred ) Roth,A. (1995). “Game Theory and Experimental Economics Web Site”. Harvard University. (referred )