An eLearning module on Negotiation Analysis www negotiation

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

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

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-negotiation sites § 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 Systems Analysis Laboratory Helsinki University of Technology

e-Learning resources for negotiations § “Yes! The On-Line Negotiator” Harvard Business School § Cases and related quizzes on principled negotiation § Game theory sites, e. g. by A. Roth http: //www. economics. harvard. edu/~aroth/alroth. html § Interactive Java applets, electronic textbooks § Decision analysis society http: //decision-analysis. society. informs. org § e-Learning modules at SAL http: //www. dm. hut. fi § Systems Analysis Laboratory Helsinki University of Technology

Systems Analysis Laboratory Helsinki University of Technology

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

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 Learning Theory Cases Quizze Paths s Videos Assignments Evaluation Introduction to game theory and negotiation Module 2 Module 3 Systems Analysis Laboratory Helsinki University of Technology

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

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

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

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

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

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 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 Systems Analysis Laboratory Helsinki University of Technology and HTML

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 § § Identification of the most preferred directions Determination of the compromise direction Identification of the most preferred points in the compromise direction 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

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

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

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

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

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

Joint Gains system architecture Case Administrator WWW Browser SERVER Mediator software eb W e id W ld r Wo WWW Browser. . . Party 1 Systems Analysis Laboratory Helsinki University of Technology Party 2 Party N

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 roleplaying 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 § www. dm. hut. fi § § § www. mcda. hut. fi § § e-Learning in Multiple Criteria Decision Analysis www. negotiation. hut. fi § § Decision making resources at Systems Analysis Laboratory Links to student evaluations e-Learning in Negotiation Analysis www. decisionarium. hut. fi § 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, 475 -491. 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, 54 -69. 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, 26 -33. Hämäläinen, R. P. and J. Dietrich (2002). Introduction to Value Tree Analysis: e-Learning Module. Systems Analysis Laboratory, Helsinki University of Technology, http: //www. mcda. hut. fi/value_tree/learningmodules/. 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, 331 -353. Systems Analysis Laboratory Helsinki University of Technology

Web sites Kersten, G. (2002). “Negotiations and e-Negotiations: Management and Support”. Concordia University. (referred 24. 09. 2003) http: //mis. concordia. ca/projects/negocourse/nego_course/index. html Roth, A. (1995). “Game Theory and Experimental Economics Web Site”. Harvard University. (referred 24. 09. 2003) http: //www. economics. harvard. edu/~aroth/alroth. html Systems Analysis Laboratory Helsinki University of Technology