Transcript No Slide Title

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
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
 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
Learning
Theory Cases Quizz
Paths
Modular structure
Theory
• HTML
pages
Case
• slide shows
• video clips
Systems Analysis Laboratory
Helsinki University of Technology
Web
software
• Joint Gains
• video clips
VideosAssignments
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, ecommerce
Systems Analysis Laboratory
Helsinki University of Technology
Material
 Basic concepts
 Game theory
 Mathematical models of negotiation analysis
 Examples
 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
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
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
WWW Browser
WWW Browser
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
 Decision making resources at Systems Analysis Laboratory
 Links to student evaluations
 www.mcda.hut.fi
 e-Learning in Multiple Criteria Decision Analysis
 www.negotiation.hut.fi
 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