HELSINKI UNIVERSITY OF TECHNOLOGY Department of ... · use of this theory to help a single decision...
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HELSINKI UNIVERSITY OF TECHNOLOGY Department of Engineering Physics and Mathematics Ville Koskinen e-Learning and Teaching Mathematical Models of Negotiation Analysis Master’s thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Technology Espoo, 27.05.2003 Supervisor: Professor Raimo P. Hämäläinen Instructor: Professor Harri Ehtamo
Transcript of HELSINKI UNIVERSITY OF TECHNOLOGY Department of ... · use of this theory to help a single decision...
HELSINKI UNIVERSITY OF TECHNOLOGY Department of Engineering Physics and Mathematics
Ville Koskinen
e-Learning and Teaching Mathematical Models of Negotiation Analysis
Master’s thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Technology
Espoo, 27.05.2003
Supervisor: Professor Raimo P. Hämäläinen Instructor: Professor Harri Ehtamo
Preface
This work was carried out at the Systems Analysis Laboratory at the Helsinki University
of Technology (HUT). It is partially funded by OR-World EU project in which material
and techniques are developed and evaluated for web-based learning of management
science. The results of the work produced by the OR-World project team at HUT are
available at http://www.dm.hut.fi/ and the results specifically related to this thesis can be
found at http://www.negotiation.hut.fi/.
I wish to sincerely thank PROFESSOR HARRI EHTAMO, the instructor of this work, for
patient guidance and valuable and critical feedback during the development of the
material and this thesis. I am also grateful to my supervisor, PROFESSOR RAIMO P.
HÄMÄLÄINEN, for great visions and for the possibility to work within the project. I
appreciate whole OR-World team at HUT, especially MR. JAAKKO DIETRICH, for co-
operation and fruitful exchange of thoughts.
Finally, I wish to thank MAARIT, my wife and my co-worker, for supporting me at my
roughest times and my parents, ANNI and PENTTI, who deserve special appreciation for
giving me all their support throughout my life.
Kauniainen, May 2003
Ville P.J. Koskinen
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Table of Contents Preface.............................................................................................................................................iii
Acronyms ...................................................................................................................................... vi
1 Introduction ...........................................................................................................................1
1.1 Negotiation Analysis................................................................................................... 1
1.2 Objectives of the Work.............................................................................................. 2
2 e-Learning...............................................................................................................................4
2.1 Background .................................................................................................................. 4
2.2 Existing Material in the Negotiation Analysis Framework ................................... 5
2.3 Classification ................................................................................................................ 7
2.4 Challenges .................................................................................................................... 8
3 Implementation and Structure of e-Learning Material ................................................. 10
3.1 Implementation ......................................................................................................... 10
3.1.1 Creating and Delivering the Material ............................................................ 10
3.1.2 Multimedia Presentations................................................................................ 12
3.1.3 Tools for Interaction ....................................................................................... 12
3.2 Structure ..................................................................................................................... 13
3.2.1 Theory................................................................................................................ 14
3.2.2 Online Quizzes................................................................................................. 15
3.2.3 Cases .................................................................................................................. 15
3.2.4 Assignments...................................................................................................... 16
3.2.5 Video Clips........................................................................................................ 16
3.2.6 Learning Modules ............................................................................................ 17
4 Mathematical Models of Negotiation Analysis .............................................................. 18
4.1 Phases of the Negotiation Process ......................................................................... 18
4.2 Negotiation Analysis and e-Learning ..................................................................... 19
4.3 Game Theory............................................................................................................. 20
4.3.1 Prisoners’ Dilemma ......................................................................................... 21
4.3.2 The Problem of the Commons...................................................................... 23
4.4 Negotiation Analysis................................................................................................. 26
4.4.1 Utility Function Based Methods .................................................................... 27
4.4.2 Interactive Methods......................................................................................... 28
4.5 Jointly Improving Direction Method ..................................................................... 30
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5 Learning Module Description .......................................................................................... 33
5.1 Instructions ................................................................................................................ 33
5.2 Theory and Quizzes.................................................................................................. 34
5.3 Assignments and Case.............................................................................................. 36
6 Experiences of Use ............................................................................................................ 39
6.1 Student Evaluation.................................................................................................... 40
6.1.1 Online Questionnaire ...................................................................................... 40
6.1.2 Results................................................................................................................ 42
6.2 Quizzes and Assignments ........................................................................................ 47
7 Discussion ........................................................................................................................... 49
8 References ........................................................................................................................... 52
9 Web References.................................................................................................................. 59
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Acronyms
Acronym Explanation First referred on Page
AVI Audio Video Interleave 12
BATNA Best Alternative to a Negotiated Agreement 18
DTD Document Type Declaration 11
GIF Graphic Interchange Format 12
HTML Hypertext Markup Language 10
HUT Helsinki University of Technology 2
JSP Java Server Page 13
LMML Learning Markup Language 10
MCDA Multiple Criteria Decision Analysis 10
MCDM Multiple Criteria Decision Making 28
MIT Massachusetts Institute of Technology 4
MOLP Multiple Objective Linear Programming 28
NSS Negotiation Support System 2
PDF Portable Document File 10
SNT Single Negotiation Text 29
WYSIWYG What You See Is What You Get 12
XML Extensible Markup Language 10
XSL Extensible Style Sheet Language 11
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1 Introduction
Electronic media can act as a means to increase the level of co-operation, democracy and
citizens’ participation in decision making, and eventually to prevent conflicts. Applying
new techniques and technologies provides education. Hence, we envisage it as an
educational challenge to teach negotiation skills for the students of operations research
and for other persons involved in decision making in the modern society. Especially, it is
possible to develop these skills by means of e-learning, which can be closely integrated to
different forms of negotiation.
But what actually is e-learning? Basically, it means education that takes advantage of
electronic media offering new dimensions and possibilities. Particularly personal
computers (PCs) and the Internet have established a sound basis for e-learning because
their costs are nowadays relatively low and hence they have become a standard which
allows their widespread applications. Electronic media offer possibilities among others
for learning “any time, anywhere”, more extensive use of colorful graphics, animations,
voice and hypermedia than traditionally, and new ways of communication, such as e-mail,
on-line chat, newsgroups and video conferencing. Especially the new ways of
communication play a crucial role in the education and practice of negotiation.
1.1 Negotiation Analysis
By negotiation we mean an interactive process by which different parties try to reach
compromises and make an agreement. Negotiation science can be approached from
different directions including, political, behavioral and mathematical approaches, see, e.g.,
Fiorino (1995), Raiffa, Richardson and Metcalfe (2002) and Mumpower (1991).
According to Raiffa (1982) negotiation analysis has its roots in the early works of von
Neumann and Morgenstern (1944), who developed axioms describing the rationality of a
decision maker and introduced the concept of utility function. Decision analysis makes
use of this theory to help a single decision maker to make individual decisions (Belton
and Stewart, 2002; Raiffa, 1968). Decision problems involving multiple decision makers
can be analyzed, e.g., by game theory that deals with mathematical models of conflict and
co-operation between rational decision makers, see, e.g., Luce and Raiffa (1957) and
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Myerson (1997) for good textbooks on game theory. Negotiation analysis uses game
theory and decision analysis to develop methods for decision makers to make joint
decisions, see, e.g., Raiffa, Richardson and Metcalfe (2002) and Sebenius (1992). These
methods can be implemented as negotiation support systems (NSSs) to offer practical
negotiation tools.
There are many potential applications of negotiation analysis. Among others, it is a
promising tool for political and environmental decision making and electronic
commerce, also internationally (Susskind, Levy and Thomas-Larmer, 2000; Hämäläinen
et al., 2001; Kraus, 2001; Sebenius, 2001). Also, the potential applications of the web-
based NSSs have aroused discussion on e-democracy that focuses on deploying
electronic media to increase the level of citizens’ public participation, transparency of
decision making processes and eventually to improve the efficiency and effectiveness of
democracy, see, e.g., towards electronic democracy project1.
1.2 Objectives of the Work
There has been research on mathematical models of interactive negotiation at Systems
Analysis Laboratory, Helsinki University of Technology (HUT) in recent years see,
Ehtamo and Hämäläinen (2001) and the references in that paper. This research has
included not only mathematical models of negotiation but also work on NSSs that has
yielded the Joint Gains software2 being an implementation of an interactive negotiation
method. The Joint Gains is a tool for solving real-life multi player multi issue negotiation
problems allowing the players to negotiate interactively via the Internet even if they are
physically distributed. They only need to have a Java enabled web-browser, an access to
the Internet and agree on time when to negotiate.
Recently, there has been active work on applications of electronic media in teaching
negotiations, see, e.g., course at Concordia University3 and an e-learning program at
Harvard Business School4. These material offer facilities for “learning by doing” that is a
concept originating from the early works by Dewey (1910; 1938). Similarly, our e-learning
1 http://bayes.escet.urjc.es/ted/, referred 26.03.2003 2 http://www.jointgains.hut.fi/, referred 04.02.2003 3 http://mis.concordia.ca/projects/negocourse/nego_course/index.html, referred 04.02.2003 4 http://www.elearning.hbsp.org/, referred 04.02.2003
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material, which is produced as a part of ORWorld project (Suhl and Kassanke, 2000),
provides interactive and visual experiences for the students and lets them actively learn
by doing. We incorporate introductory theory sections complemented with relevant
references to the literature, case studies, quizzes and assignments. These elements are
complemented with multimedia presentations such as video clips, animations and
graphics where necessary. We take the Joint Gains to be an integral part of the learning
material and employ it as an educational instrument to provide facilities for interactive
and active learning.
The potential applications of negotiation analysis cover a variety of different disciplines.
Therefore, to serve the requirements of widest spectrum of learners we are challenged to
create material that can be tailored and used both as a whole but in parts too for different
needs. We aim to develop a modular material and a variety of learning elements to
support different didactical goals in different contexts. The modularity allows the users
of the material to construct their own wholes, or modules, of the material and possibly
include their own material in them too. The modules are intended for independent use
but they can be used as an additional or optional material in other courses as well.
The first phase of the development process involves constructing a material that can be
used as a part of a negotiation analysis course. We consider students of engineering as
primary users of the material. Also, the material can be applied when decision makers
and mediators are preparing for web-based participation in real-life negotiations so long
as the experiences of its use are accumulated.
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2 e-Learning
In this chapter, we discuss e-learning. First, we give an outlook to e-learning by defining it
and reviewing its evolution. Then we go through existing web resources in our negotiation
analysis framework. We also present a way to classify between different e-learning courses
and point out the challenges discussed in the e-learning literature.
2.1 Background
E-learning is typically defined as location and time independent learning making use of
computer and communication technologies to work with remote learning resources,
including coaches and other learners, see, Richards (2002) and a web site of Asynchronous
Learning Network organization5. We, however, consider that its computer aided side
should have greater emphasis than time and location independency. This is because an e-
learning course may also include some components requiring the students to be online at
the same time as Jolliffe, Ritter and Stevens (2001; Chapter 1) remind.
The nature of e-learning has changed during its evolution that was apparently initiated in
the early 1990’es when the computers and especially the Internet became rapidly more
and more popular. The most advanced teachers started creating course homepages that
contained course syllabus, bulletin boards, perhaps some learning material and links to
existing sources of interesting information. Nowadays, the use of electronic medium has
became a standard and there emerges all the time more and more new material and new
forms of e-learning in this continuum empowered by the continuously arising techniques.
There are many instances indicating that. For example, Massachusetts Institute of
Technology (MIT) has an MIT open courseware project6 aiming to bring systematically
information on each of its course to the web. Commercial software acting as e-learning
platforms for creating electronic courses has emerged. They include, e.g., WebCT and
Lotus BlackBoard; even traditional publishing companies are including electronic
5 http://www.aln.org/, referred 04.02.2003 6 http://ocw.mit.edu/index.html, referred 04.02.2003
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components in their services in co-ordination with the suppliers of the e-learning
platforms, see, e.g., Prentice Hall e-Learning7.
In this thesis, we adhere to e-learning on the course level, in which the didactical goals
are strictly defined. Nevertheless, there are also other notions of e-learning that are
closely related to our focus. For instance, a widely used approach in e-learning is the
collaboration via the web, which is sometimes referred to as cybercollaboration in the
literature. It employs the web as a tool for communication and offers facilities for group
work, brainstorming and interaction to transfer and transform knowledge between the
collaborating parties and generate new ideas. There are many experiences on this
approach and we suggest the reader to refer Dufner et al. (2002) and Sawhney et al.
(2002) as examples from the e-learning perspective.
Also, there are the virtual universities that are the most mature instances of e-learning
offering not only some courses but complete degrees online. Examples of these
universities are Canadian Virtual University8, British Open University9 and Korean
National Open University10 whose sizes are huge ranging from 150 000 to 350 000
students. The future scenarios of the higher education and universities are discussed, e.g.,
by Naquin (2002) in detail.
2.2 Existing Material in the Negotiation Analysis Framework
The negotiations are interactive processes between the negotiating parties and they can
be aided by applying electronic media to create NSSs. These systems are intended mainly
for solving real-life negotiation problems but besides it they can be used for educational
purposes, too. The students may apply them to solve imaginary negotiation problems by
having role-playing experiments as suggested, e.g., by Winham (2001). This lets the students
to simulate the negotiations and see how their actions affect the interactive negotiation
process and its final results. This cannot normally be accommodated in a traditional
course. Hence, negotiation analysis is a fruitful area for e-learning, simply because of its
interactive nature and practical essence.
7 http://cms.prenhall.com/coursecompass/, referred 04.02.2003 8 http://www.cvu-uvc.ca/, referred 04.02.2003 9 http://www.open.ac.uk/, referred 04.02.2003 10 http://www.knou.ac.kr/english/index.htm, referred 04.02.2003
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There are only a few e-learning courses on negotiation science. Köszegi and Kersten
(2003) have recently published the “Negotiations and e-negotiations: management and
support” course11. It consists of an electronic textbook presenting theory, some case
studies and role-playing assignments having a focus on basic concepts of economics,
game theory and social psychology. Our notions on e-learning of mathematical models of
negotiation analysis are somewhat similar to those presented by Köszegi and Kersten
even if our work has been carried out independently of them. For example, as Köszegi
and Kersten we also consider learning by doing very central concept and take advantage
of possibilities offered by electronic media to produce complete learning modules that
can be used in combination with face to face sessions or as independent wholes.
Nevertheless, when browsing their learning material one easily gets the impression of
studying a traditional textbook; whereas we have developed material looking more like a
“web-site”. Moreover, our approach includes the use of the Joint Gains software that is
completely available online any time from anywhere for real-life negotiations
incorporating cases defined by the negotiators or a third intervening party. Thus it is not
intended only for educational use as is the INSPIRE system (Kersten and Noronha,
1999) applied by Köszegi and Kersten in their e-learning course.
Harvard university press has published an e-learning program “Yes! The On-Line
Negotiator” based on the book by Fisher and Ury (1981). It is commercially available and
it contains slideshows summarizing the theory, presenting some case problems and
related quizzes12. That material is essentially a program and hence it does not constitute
complete whole but interactive facilities for training negotiation skills.
In the related field of game theory there are more educational resources available in the
Internet. For instance, a link collection13 provided by the Vanderbilt University contains a
number of links to existing material in the web. That material includes lecture notes,
textbooks, quizzes and tools illustrating the interactive nature of different games. It
should be emphasized, however, that those interactive tools are typically separate from
the e-learning courses that usually are only web-pages for delivering books and
assignments in electronic format.
11 http://mis.concordia.ca/projects/negocourse/nego_course/index.html , referred 04.02.2003 12 http://www.elearning.hbsp.org/, referred 04.02.2003 13 http://www.gametheory.net/ , referred 04.02.2003
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In the field of management science, or operations research as it is interchangeably called in
literature, there is also available a variety of e-learning material and experiences of their
use. For instance, OR-World, part of which our material is, and Vorms projects have
focused on assessing new techniques for education, see Kassanke and Steinacker (2001),
Suhl and Kassanke (2000) and Frank, Kassanke and Suhl (2002). Similar work has been
carried out at University of Strathclyde by the MENTOR project that aims to “improve the
effectiveness and the efficiency of teaching and learning OR/MS through the use of multimedia computer
based learning materials” (Thornbury et al., 1996). Those projects have reported that
electronic media has been successfully applied to offer multimedia presentations and
tools for interaction in teaching operations research. Also, International Federation of
Operations Research Societies (IFORS) has created tutOR learning modules14 and Institute for
Operations Research and the Management Sciences (INFORMS) has a learning center15, which
constitutes a set of links to existing educational resources in Internet. That material,
however, does not form an independent whole but rather a supplementary and
introductory material collection for existing courses.
2.3 Classification
The examples on the e-learning material in our framework show that there is a variety of
different approaches available. We can at least distinguish between independent e-
learning courses and traditional courses using supplementary electronic material. We
consider three different types of e-learning courses by following Richards (2002):
1. Internet is used for delivering information. The course has a homepage that
contains, for example, the course syllabus, bulletin board and possibly some
slideshows and a course book.
2. The course contains electronic components. Such a course may include
electronic entities for self-studying a certain topic replacing a lecture or
assignments.
3. The course is completely available electronically and it has an interactive focus.
14 http://www.tutor.ms.unimelb.edu.au/, referred 08.04.2003 15 http://www.anderson.ucla.edu/informs/SU/learning/, referred 08.04.2003
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Richards also presents that students’ physical vicinity needs to be taken into account in
the classification. Hence, she also differentiates distance learning from on-campus learning
being the basis of her study.
2.4 Challenges
The advantages of e-learning seem obvious. It can be self-paced, take place virtually any
time and anywhere, and it can provide possibilities for using multimedia and tools for
interaction. Nevertheless, when the evolution of e-learning is now getting saturated,
some criticism against it is emerging, see Aggraval and Legon (2003) and Wesley (2002).
Aggraval and Legon report that many universities such as MIT and Harvard have
concluded that e-learning cannot substitute traditional face to face learning and hence they
have abandoned some of their efforts in this area. Also, Dufner et al. (2002) have faced
similar problems due to the lack of face to face communication in cybercollaboration.
The lack of face to face communication is probably the most common and the most
discussed issue in e-learning literature because it hinders personal communication with
teachers and peer students reducing the possibility for social interaction, see, e.g., articles by
Wesley (2002) and Richards (2002). Hence, e-learning transforms the nature of
interaction or ruins it at the worst case. For instance, in a web course the students are
unable to interrupt the teacher and address supplementary questions focusing on unclear
issues or issues of special interest but they should rather search for new and additional
information actively by themselves. Hence, the lack of social interaction may cause the
students feel lonely and isolated. Wesley (2002) argues in his critical analysis of the
evolution of e-learning that this will eventually result to increase the efficiency of learning
rather than providing more room for creativity and innovation. Therefore, e-learning
may narrow the level of learning and produce undesirable results in some cases.
Another drawback in e-learning is that it may require new additional technical skills from
the students. This may produce technical problems causing overwhelming obstacles for
learning in the worst case. Especially students who are technofobic or unfamiliar with the
required techniques may face negative experiences. This is a problem particularly in
distance learning courses because the students are unable to meet personally their
teachers and ask for help as observed, e.g., by Richards (2002). If necessary, the students
may need to be coached to master some new technical skills at the beginning of the
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course, which should be avoided as it requires additional effort and motivation.
Therefore, the usability of the e-learning material should be taken into account carefully
in the material design and standardized graphical user interfaces should be used.
These observations settle challenges for the developers of e-learning courses and
material. The question is how to offer fruitful and pleasant learning experiences full of
new information with electronic techniques available without leaving the students lonely,
isolated and technofobic, if this is possible at all. The related challenges are mainly
technical but they also involve understanding of the learning processes. For instance, a
common misconception is that e-learning is only a transformation of existing textbooks
into electronic format and delivering them via the Internet (Hobbs, 2002) even if it has
been shown in many studies that reading printed books is easier than reading them on a
computer screen, see, e.g., Weitl et al. (2002). Hence, implementation of electronic media
must not be an intrinsic value but its suitability for education should be considered
carefully and reflected to the didactical goals in the design of the learning material.
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3 Implementation and Structure of e-Learning Material
We employ web techniques to produce an e-learning material that consists of text,
figures, multimedia and interactive tools that offer possibility for self-paced, location
independent and partly time independent learning. This chapter presents how that
material is implemented and what its main structure is. The structure of the learning
material is similar to the multiple criteria decision analysis (MCDA) e-learning material16.
3.1 Implementation
We address the question on how to create and deliver the material, which formats to use
in multimedia presentations and how to create tools for interaction from the technical
perspective. The aim is to choose the techniques such that the material can be created
with no great effort and it can be viewed by most common web browsers and other
common viewers in a user friendly manner. Hence, the technical skills required from the
students are minimal.
3.1.1 Creating and Delivering the Material
E-learning material is typically delivered in a variety of formats such as hypertext markup
language (HTML), portable document files (PDFs), MS Word documents and MS PowerPoint
slideshows. They can be viewed by only a certain viewer and hence they are more or less
unstructured, that is, their content is bound to the document and the format does not
make clear distinction between content, structure and visualization. This makes the
maintenance and reusability of the material difficult when dealing with large amount of
documents and hyperlinks. To overcome these problems the use of extensible markup
language (XML) has been studied in literature. It keeps content, structure and visualization
separate and it can be extended as its name suggests. One extension, which is intended
for producing a learning material, is learning markup language (LMML) developed by Süss,
Freitag and Brössler (1999).
16 http://www.mcda.hut.fi/, referred 01.04.2003
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The visualization of XML documents is defined separately by extensible style sheet language
(XSL) that can be used to generate, for instance, HTML and PDF documents from an
XML document. The structure of the XML is specified in document type declaration (DTD)
files. (Kassanke and Steinacker, 2001)
Due to its nature using XML requires a certain level of standardized structure of the
learning material (Suhl and Kassanke, 2000). For example, see Figure 1 below that
illustrates the XML structure specification of a case study which has been created by the
OR-World project team at HUT.
CASE
STRUCTURING
PROBLEM MODELLING
METHOD
Partition elements
Editing elements
Content elements
ANALYSIS Editing elements
SYNTHESIS
Content elements
Editing elements
Partition elements
Editing elementsPartition elements
Editing elements
Editing elements
Partition elements
CASE
STRUCTURING
PROBLEM MODELLING
METHOD
Partition elements
Editing elements
Content elements
ANALYSIS Editing elements
SYNTHESIS
Content elements
Editing elements
Partition elements
Editing elementsPartition elements
Editing elements
Editing elements
Partition elements
INPUT
Partition elements
Editing elements
INPUT
Partition elements
Editing elements
INPUT
Partition elements
Editing elements
INPUT
Partition elements
Editing elements
Partition elements
Editing elements
OUTPUT
Partition elements
Editing elements
OUTPUT
Figure 1 An example of a standardized structure of a case study
Each box in the Figure 1 is called an element and they describe the hierarchical structure
of the case element. For instance, the partition and editing elements at the lowest levels
of the structure divide each higher level element to sections, paragraphs and lists.
The problem of the standardized structures is that their usage may emerge inflexible and
thus there appears pressure to change the standard. Modifications to one standard result
a new one and hence a new XML extension. Another problem is that existing XML
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editors do not provide flexible WYSIWYG17 editing possibilities, see, e.g., Kantwerk’s
and Kassanke’s (2002) review. Therefore, we do not employ XML extensively but
concentrate on generating the material by using MS Office tools that allow simultaneous
design of content and its visualization. They also offer possibilities for converting the
material to HTML and PDF formats that are used for delivering the material for the
students.
3.1.2 Multimedia Presentations
Multimedia presentations can be delivered in a variety of different formats, e.g., MPG,
AVI, Macromedia Flash and GIF animations. To serve as many needs as possible, the
OR-World team at HUT decided to deliver multimedia presentations in three formats:
1. AVI with audio
2. AVI with no audio
3. GIF animations.
It is flexible to view the AVI files because they allow including audio, pausing, stopping,
rewinding or fast forwarding the presentations. Nevertheless, they need a media player to
be installed. Therefore, GIF animations are delivered, as well, because they can be viewed
by an ordinary web browser. Their usability is, however, poorer because they can only be
played and restarted and they may not contain audio. AVI files with no audio are
included in the material to serve the students who have slow internet connection
available and find the versions with audio too large.
These multimedia presentations are created with the Camtasia Screen Recorder that is an
application for recording the computer screen and dubbing audio on it.
3.1.3 Tools for Interaction
Java technologies offer a great variety of interactive functionality that can be applied in e-
learning and embedded in web browsers. Especially Java applets can be used to create
illustrative and interactive e-learning tools. Applets can be referred to as programs, but
the practical difference between them is that running an applet requires a web browser or
17 What you see is what you get
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a specific applet viewer. They are also independent of the computer platforms and hence
the students can use them regardless of their operating system.
It is possible to include functionality in the applets that allows many students to work
with a common tool via a server even if they are physically distributed all over the web.
For instance, Joint Gains negotiation support system is an applet implementing this
functionality.
Servlets and Java Server Pages (JSPs) are another type of Java-based techniques. They can be
used among others for creating web-forms that are filled and submitted to a server that
gives an appropriate response to the student and may store the submitted data. The
servlets and JSPs can be applied, for instance, to create online-questionnaires and online-
multiple choice questions being automatically graded. For technical description on
servlets, applets and their distributed usage see, e.g., Siyan et al. (1997, Chapters 8, 9, 16
and 18).
Java applets can, of course, be applied to create tools for communication among students
and between them and their instructor. Nevertheless, there are specific communication
methods as well that are independent of Java. They include different communication
forums such as, newsgroups, e-mail, chat and traditional telephone. Newsgroups are
intended for asynchronous group communication whereas chat is its synchronous
counterpart. E-mail and traditional phone calls are tools for private communication
between two persons and they are asynchronous and synchronous respectively.
3.2 Structure
The negotiation analysis site is conceptually divided into six main elements:
1. theory
2. online quizzes
3. cases
4. assignments
5. video clips
6. learning modules.
Each of them supports different learning objectives and presents the subject from different
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viewpoints. For example, Figure 2 presents the negotiation analysis learning material
front page. There is a frame on the left that the students can use for navigating among
those main elements whose purpose is explained below.
Figure 2 Negotiation analysis learning material front page
3.2.1 Theory
Theory can be compared to an ordinary introductory textbook but it is designed to be
on-screen readable, which is taken into account by considering two major challenges
presented by Weitl et al. (2002). The first challenge is that students’ perception tires out
when studying new information on the screen and the other one is the loss of overview,
which is due to low amount of information that can be shown on the screen at a time.
To cope with these challenges the theory is written in a format of a story telling about
two friends, Harold and William. This story is complemented with frequent headings and
introductory overview sections that point out its thread and the core concepts of the
theory.
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For instance, Weitl et al. (2002) have concluded that technical topics, such as pure
mathematics, are inconvenient to be studied through the web. Therefore, we include only
basic, high school level, mathematical definitions and analysis in the theory. Most of the
presentation is based on graphs and their interpretations. Further mathematical details
can be found from articles and textbooks given in further reading sections.
The theory is written in MS Word and delivered as HTML. The Word-document and its
PDF conversion are also available for printing.
3.2.2 Online Quizzes
Online quizzes are related to the theory and they contain multiple choice questions
regarding it. There is one quiz per each theory section. Their main purpose is to act as a
motivating self-evaluation tool and provide a variety of refreshing cognitive activities for
the students. They also summarize the core concepts of the theory and thus sharpen
students’ overview on the subject.
The students can access the quizzes, which are stored in Quiz Star18 server, by a web
browser and they are required to register themselves to the server, when using it for the
first time. After a student has filled a quiz and submitted it she gets immediately a
response pointing out the correct and incorrect answers. To find out the correct answers
the student should refer to the theory and try refilling and submitting the quiz.
The server gathers the submitted answers and their results are available for the creator of
the quiz. Thus the quizzes produce information on problems and misunderstandings that
the students may face during their learning process, which can be utilized in further
development of the material.
3.2.3 Cases
Cases are simple problems encountered in real life. They can be studied both as a
practical introduction to the theory concepts and as an example complementing the
theory. Theory and cases are independent entities that can be utilized separately or
18 http://quiz.4teachers.org/index.php3, referred 04.02.2003
15
together. Thus, the students can only read the theory part, familiarize themselves just
with the corresponding case example or study first the theory and search for more
practical insight form the cases.
Technically, it is very easy to add new cases and modify the old ones. Thus the cases can
serve as a customizable element of the learning material and they can be used to connect
the theory to students’ own personal context, which makes the adoption of new
knowledge more efficient.
The cases are delivered as MS PowerPoint slides and as GIF figures embedded in HTML
documents that are organized into a hierarchical structure by applying XML.
3.2.4 Assignments
Assignments can be seen as quizzes; for students, they offer refreshing activities and
provide a way to self-asses one’s skills. Nevertheless, they require deeper understanding
of the studied topic and more effort. Also, they are manually graded by an instructor.
There are two types of assignments: analytical and software assignments. The analytical
ones ask the students to apply mathematical tools that they have learned so far and to
familiarize themselves with the negotiation analytical methods as suggested by Meerts
(2001). In software assignments, the students learn by doing and solve practical
negotiation problems that involve role-playing experiments described in the cases, see
Winham (2001).
The assignments are available both as HTML and MS Word format for the students.
Those who are able to use MS Word can apply the assignment document as a report
template and fill their answers directly to it. The assignments contain also detailed
instructions so that the students need not to open a separate window for writing a report,
reading the assignment and the instructions.
3.2.5 Video Clips
Video clips are recordings that show how to work with software in detail. This is to
reduce the need for personal instruction and communication between the teacher and
16
students by e-mail or face to face directly. The clips are mainly intended to help the
students who are unfamiliar with computers and encourage them to start working with
the software assignment.
3.2.6 Learning Modules
Learning modules are collections of selected elements of the material and they form an
independent whole that corresponds to traditional few hours engineering lecture plus the
exercises.
The modules typically include the following: theory and case parts explaining the subject,
quiz and assignment parts in which the students can test and show their knowledge. A
module also presents the motivation, that is, an explanation concerning the purpose and
learning objectives of the module and detailed instructions on how to get through these
selected elements. The structure of the module follows closely the lines suggested by
Weitl et al. (2000).
The students are asked to fill an online evaluation that is intended to measure their
subjective experiences at the end of the module. The evaluations are accomplished with
the Opinions Online19 software, which is an online-platform for voting, surveys and group
decision developed at the Systems Analysis Laboratory.
19 http://www.opinions.hut.fi/ , referred 04.02.2003
17
4 Mathematical Models of Negotiation Analysis
This chapter presents why negotiation analysis is suitable for e-learning and provides a
brief overview on the content of the negotiation analysis e-learning material for interested
reader.
4.1 Phases of the Negotiation Process
We can distinguish at least five phases in negotiation process that can be aided by
mathematical modeling and electronic media, see, e.g., Kersten (1994):
1. Selection of the communication mode and arena
2. Setting agenda
3. Exploring the field
4. Narrowing the differences
5. Search for agreement
We briefly discuss these phases and their connection to negotiation analysis.
In the first phase, the negotiating parties are specified and they agree on the location where
the negotiation process may occur and choose the communication mode that can be
either physical or virtual. Virtual ones can be created by applying electronic tools offering
possibility for location and time independent communication. This phase may also
involve the parties to decide if any intervening third parties are used to help the negotiation
process because they may be hidden in some of the communication modes available. For
instance, Ehtamo and Hämäläinen (2001) and Kersten and Noronha (1997) have
described web-based NSSs that offer facilities for virtual communication and serve as
intervening software mediators.
The second and third phases, setting agenda and exploring the field, involve many
different sub-phases. The negotiating parties structure their problem and agree among
others on use of joint terminology, define the issues they negotiate about and formulate
the set of possible outcomes. The parties structure their preferences by identifying the
essential decision criteria to be able to assess different outcomes. Also, they can formulate
their best alternatives to a negotiated agreement (BATNA) that is the result for them that they
18
could achieve without negotiations (Fisher and Ury, 1981; see especially Chapter 6).
Basically, BATNA is an insurance that acts as a reference against which any outcome
should be compared to. It protects the parties from accepting unfavorable agreements
and from rejecting favorable ones. For a more complete description, especially for the
third phase, we recommend Hämäläinen et al. (2001), where it is applied in
environmental decision making context.
In the fourth phase, narrowing the differences, the negotiating parties create a set of
compromise outcomes for their problem and assess them. The parties exchange information
intensively and hence they learn the key issues of the negotiation and possibly emerging
sources of disagreement. The parties also see how their negotiation strategies act in
practice and they may end up changing them during the process. Even radical changes
may appear; for instance, they may turn into considering each other as co-operating
partners instead of competing opponents or vice versa.
In the final phase, the negotiating parties have already generated a number of
compromise outcomes and they search for an agreement. They may choose one of the
compromises as an agreement directly but they may also try to jointly improve some of
them if possible. In this case they choose the agreement among the improved ones.
Sebenius (1992) highlights the most essential elements of negotiation analysis mainly
following the earlier works of Keeney and Raiffa (1976), Fisher and Ury (1981) and
Raiffa (1982). These elements involve identifying the structure of the problem and
procedures for searching agreements. He defines negotiation analysis as a “technology for co-
operation” and he points out that negotiation analysis has its roots in game theory and decision
analysis. Hence, phases three, four and five can be aided by negotiation analysis but it also
offers a conceptual framework for phases one and two, see Raiffa (1982; especially
Chapter 1).
4.2 Negotiation Analysis and e-Learning
Different phases of the negotiation processes are interactive in nature. They are also
closely related to the practical cases encountered in real life that may excite even strong
emotions in the human minds. Hence, education of negotiation analysis can be made
more effective by taking advantage of the continuously emerging electronic media, as
19
discussed already in Chapter 2.3. This is simply due to interactive and practical
prescriptive nature of negotiation analysis.
The theory part of e-learning material, see Chapter 3.2.1, on negotiation analysis presents
an introduction to game theory and models in negotiation analysis by keeping non-
mathematical and mathematical sections separate. Here we represent the theory briefly in
the Chapters from 4.3 to 4.5 where the separation is not equally strict. Those sections are
mainly intended for interested reader to summarize the contents of the theory and to
represent the style of the theory. Nevertheless, they can be skipped, too, without losing
the thread of this thesis.
In the following, we assume that the reader is familiar with the basic concepts of decision
analysis and understands the concept of utility function that is a concept originally
presented by von Neumann and Morgenstern (1944). The fundamentals of utility theory
and decision analysis are explained in the e-learning material in a separate chapter for
non-advanced students.
4.3 Game Theory
Game theory section teaches the basic concepts in game theory that are presented by two
classical examples. They are relatively simple ones but rich enough to illustrate the
phenomena encountered in real life.
The first game, called the prisoners’ dilemma game, shows that the main solution concept in
game theory, the Nash equilibrium solution (Nash, 1951), gives both players a worse outcome
than they could achieve if they would have the possibility to co-operate. This problem is
originally contributed by Tucker in 1950 (see, e.g., Tucker’s memo, 1980) and it is
verbally presented by Luce and Raiffa (1957).
The other problem is called the problem of the commons, which is known at least since
philosopher David Hume (1739). In this game, a common property is being exhausted
because the Nash equilibrium produces worse outcome than the players could achieve by
co-operating as in the first game.
Good textbooks on game theory are, for instance, Luce and Raiffa (1957), Myerson
20
(1997) and Gibbons (1992).
4.3.1 Prisoners’ Dilemma
The story begins with a verbal presentation of the prisoners’ dilemma game:
Two suspects, Harold and William, are taken into custody and separated. The policeman accuses them of a crime but lacks sufficient evidence to convict them, unless at least one of them confesses. He explains the consequences following the two actions they could take: namely confessing the crime or not confessing it.
The policeman says: “If neither of you confess, then both will be convicted of a minor offence and sentenced to 1 month in jail. If you both confess, then I will sentence you to jail for 6 months. Finally, if only one of you confesses then he will be treated leniently and will be freed; while his confession is used as a witness against the other, who will be sentenced to 9 months in jail; 6 for the crime and 3 for obstructing the justice.”
In the theory section, this verbal description of the game is presented in a matrix form,
referred to as normal form game, as shown in Figure 3. It specifies the four possible
outcomes of the game that depend on the strategies chosen by the players, Harold and
William. They may choose either confess or not confess denoted by c and nc respectively.
The first number in each cell of the matrix refers to months in prison for Harold and the
latter is that for William. The negative sign is added to show that the players want to
maximize the numbers in the cell.
William does
not confess
William
confesses
Harold does
not confess
Harold
confesses
-9, 0
0, -9 -6, -6
-1, -1
Figure 3 The prisoners’ dilemma game as a normal form game
Let denote an arbitrary strategy for player i; i∈ {H,W}. H refers to Harold and W
refers to William. The set of all strategies available for player i is denoted by Sis
i and called
i’s strategy set. Hence, . By we denote player i’s utility or payoff function },{WH nccSS == iu
21
that specifies all possible payoffs for i for each strategy pair ( that might be
chosen by the players. The values of u can be read in the matrix in Figure 3.
), WH ss
i
s
W
H
ss
∀∀
, WPs
H ∈
The matrix shows that the best choice, or best response strategy, for William is c
independently of Harold’s decision. Similarly, Harold’s best choice is to play c. Hence,
both players want to confess and the strategy pair ),( cc is a self-evident solution to the
prisoners’ dilemma game. Consequently, both players will be sentenced to 6 months in
jail. This solution is called the Nash equilibrium solution of the game.
Mathematically speaking, the Nash equilibrium solution to the game above is a strategy
pair with the following property: the strategy is the best strategy for Harold,
provided that William chooses to play and vice versa, that is,
),( *W
*H ss *
Hs*W
.),(),(,),(),(
WW*HW
*W
*HW
H*WHH
*W
*HH
SssussuSssussu
∈≥∈≥
(4.1)
Hence, each player is willing to choose the strategy indicated by the solution provided the
other player also does so.
Note that there is an outcome in this game that would produce better payoff for both
players, namely -1,-1. Nevertheless, because of being rational and separated, the players
choose the Nash equilibrium solution and they cannot choose -1,-1. Thus, there is a
dilemma hidden in this game. The jointly preferred outcome -1,-1 is called Pareto optimal.
By definition, a strategy pair is Pareto optimal if any other strategy pair
gives a worse outcome for at least one of the players, that is,
)( HPs
),( WH ss
,,,),(),( WWHWHWH iSsSsssussu iPP
i ∀∈∀≥ (4.2)
where at least of the inequalities is strict. Therefore, also outcomes 0, -9 and -9, 0 are
Pareto optimal in the prisoners’ dilemma game. The Pareto optimal outcomes are
sometimes referred to as co-operative solutions because reaching them typically requires
co-operation, see Axelrod (1984).
The normal form game can also be represented in extensive form as a tree instead of a
matrix. The tree consists of decision nodes and terminal nodes and arcs connecting them.
22
Figure 4 presents the prisoners’ dilemma game as a tree. The topmost node of that tree
corresponds to Harold’s decision that is connected to William’s decision nodes. If
Harold chooses c then William’s node on the left is reached. Likewise, William’s node on
the right is reached if Harold chooses nc. Finally, depending on William’s choice one of
the terminal nodes is reached and, consequently, the game ends and the payoffs indicated
below the terminal nodes are received. Because William acts independently of Harold, he
does not know in which of his decision nodes he actually is. This is exhibited by
connecting the nodes with a vertical slashed line. Note that the players could be
interchanged in the game tree since the timing of the players’ decisions is irrelevant in
this case.
c nc
c nc c nc
Harold’s payoff: -6 0 -9 -1 William’s payoff: -6 -9 0 -1
Harold’s decision
William’s decision
William’s decision
Figure 4 The prisoners’ dilemma game in extensive form
4.3.2 The Problem of the Commons
The problem of the commons describes another type of game in which the players
choose their strategy from a continuous set. Hardin (1968) has given several socio-
economic interpretations for this problem and here we formulate it as follows:
It is spring. William and Harold are now released from jail and they both are going to graze goats in the summer on a common green. When the autumn arrives, they are going to sell their goats. Their problem is to decide how many goats they should graze.
The more a goat has grass the better it survives. If there are only a few goats on the green, adding one more does not harm the goats already grazing. But, if there are many goats, adding one more is harmful for all the goats and the value of a goat decreases remarkably.
To describe the game mathematically denote the number of goats for Harold by 0H ≥g
23
and for William by and assume that the goats are continuously divisible, i.e.,
and are real numbers instead of being integers only. The payoff function for Harold
is
0W ≥g Hg
Wg
[ ] HW )), gcPgu −=
Wg
.maxG≤
HWH( ggggP −−+
,(,(
HWHW
HWHH
gggguggggu
−−−−
W0 Gg ≤+
*Hg
Wg ′
)*Hg
WH( gg +
WH gg +
Hg
max) G=
()()
max
max
GG
==
max
HH ( g
G ≤
Hg≤
, *Wg
, where c is the cost of buying and caring for a goat.
Function P is the selling price of a goat per goat and it is function of the total number of
goats on the green, , that is denoted by G. William’s payoff function is similar to
that of Harold but with and interchanged.
)*W
Adding one more goat to the green harms the rest more if there are many goats than if
there were only a few goats on the green. This means a bigger drop for the selling price
per goat in the former case. Therefore, the function P(G), has negative first and second
derivative. Additionally, if G is greater than the carrying capacity of the green, denoted by
Gmax, the selling price of a goat is zero. Hence, we restrict ourselves to a set, where
0
For simplicity, suppose P to be a linear function of G and choose
W .
In this case the players’ payoff functions are
,),)
WW
HW
gcgc
−−
(4.3)
if . This is, in fact, a simple form of Cournot’s (1838) original model
of duopoly.
Figure 5 below presents some contours of the players’ payoff functions in ( -plane.
Along a contour a player’s payoff is constant and it can be shown that the inner contours
give greater payoff for the player. Hence, it can be easily verified that the point ( ,
where the players’ contours intersect perpendicularly, is the Nash equilibrium for this
game. If Harold decides to play , then William chooses his best response strategy and
maximizes his payoff on the slashed vertical line. He chooses , because for any other
choice, like , his payoff is smaller. Correspondingly, maximizes Harold’s payoff
on the slashed horizontal line corresponding to William’s choice and hence pair
satisfies (4.1) and it is the Nash equilibrium of the game.
), WH gg
*Hg , g
*Wg
*Hg
*Wg
(
24
Hg
Wg
Harold’s payoff contours
William’s payoff contours
*Hg
*Wg
Wg′
Hg
Wg
Harold’s payoff contours
William’s payoff contours
*Hg
*Wg
Wg′
Figure 5 Some contours of the players’ payoff functions and the Nash equilibrium for the problem
of the commons
We can describe the Pareto optimal outcomes for this game easily. Consider any point of
tangency of the players’ contours; one such point is illustrated in the Figure 6. Obviously,
there are no other points that would give a better payoff for both players and hence the
tangency point is Pareto optimal, by definition.
Hg
Wg
a Pareto optimal solution
joint tangent
Figure 6 A Pareto optimal solution
Figure 7 indicates that there are plenty of Pareto optimal points that are shown by the
line segment being referred to as Pareto frontier. The bolded part of the line segment
presents those Pareto optimal points that give better payoff for both players than the
Nash equilibrium.
25
Hg
Wg
Pareto frontier
Nash equilibrium
Figure 7 The Pareto frontier
It is commonly approved that in any bargaining or negotiation situation a solution should
desirably satisfy Pareto optimality (Mumpower, 1991). This is because it guarantees that
there exists no other outcome unanimously preferred by each player. Pareto optimality
alone does not, however, offer a unique solution but a set of efficient solutions that are
more or less preferable from a player’s viewpoint. The paradigm of choosing a fair Pareto
optimal solution for a game is addressed by axiomatic bargaining theory that is a field of
game theory. It consists of formulating axioms on how a solution for a set of games
should be selected and checking if the implied solutions seem appealing, see, e.g.,
Thomson and Lensberg (1989; especially Chapter 2).
Originally Nash (1950) introduced this axiomatic approach by presenting the Nash
bargaining solution, which is an outcome maximizing the product of utilities perceived by
the players, and the related axioms. Some of Nash’s axioms were criticized in the
literature and consequently several modifications were presented. The best known
variation of Nash bargaining solution, the Kalai-Smorodinsky solution, was contributed by
Kalai and Smorodinsky (1975). As game theory, axiomatic bargaining is descriptive in its
nature too and it does not either offer practical aid on how to reach the outcomes
implied by the axioms in practice. These axiomatic models are discussed in the e-learning
material a separate theory section in more detail.
4.4 Negotiation Analysis
Here we present a brief outlook on the methods in negotiation analysis for reaching
compromise outcomes and Pareto optimal agreements. We follow a classification
26
presented, e.g., by Ehtamo and Hämäläinen (2001) who consider two dimensions in their
article:
a) Whether the players’ utility functions are constructed as a whole or not.
b) Whether the players search for joint gains or make concessions.
In concession based methods, the players start the negotiation from separate positions
and narrow differences between them by giving subsequent offers and counteroffers for
each other. Once they reach each other the negotiation process terminates.
In the joint gains searching methods, the players start negotiation from a jointly accepted
position and search for new jointly preferred positions step-by-step until they are unable
to produce joint gain. The methods that do not require the construction of the players’
utility functions as a whole are called interactive. Hence, we can explicitly divide the
negotiation methods into four different modeling categories:
1. utility function and concession based methods
2. utility function based joint gains searching methods
3. interactive methods based on concession making
4. interactive methods searching joint gains
Note, however, that this classification is rough and it is an idealization of the types of
different methods as Ehtamo and Hämäläinen (2001) remark. Hence, it can be difficult
to classify different methods so sharply and eventually the negotiation procedures are
rather mixtures of these extreme types.
Many methods contain a third intervening party to help the negotiation process. One
type of intervener is a mediator that is a neutral party gathering some confidential
information from the players, making suggestions for them and assisting them to an
agreement. If the applied negotiation method is implemented as a computer software
system, the mediator can be a person using software to support the negotiation, but also
software alone can take the role of a mediator. In the latter case the players use the
supporting software by themselves.
4.4.1 Utility Function Based Methods
There is much literature dealing with the assessment of the utility functions. Keeney and
27
Raiffa (1976) and Clemen (1996) among others have shown how to construct an additive
utility function for a player. According to Raiffa (1982) a Pareto optimal solution can
then be found by maximizing a weighted sum of the players’ utility functions and the
Pareto frontier can be generated by systematically varying those weights. Once it has
been developed the players can choose the final agreement on the frontier, for instance,
through concession making. It is also possible to apply iterative processes along the
Pareto frontier to reach Nash- and Kalai-Smorodinsky bargaining solutions, see, e.g.,
Ehtamo, Ruusunen and Hämäläinen (1989).
There are hardly any utility function based methods searching joint gains according to
Teich, Wallenius and Wallenius (1994). Only Raiffa (1982) has presented some ideas but
he does not extend his analysis beyond the utility functions.
In general, there are only few practical applications based on the players’ individual utility
functions (Ehtamo and Hämäläinen, 2001). This is because they are not very easy to elicit
in general even if additive utility model described players’ preferences adequately. Hence,
the research of the interactive negotiation methods has been more extensive and closer
to practical applications.
4.4.2 Interactive Methods
There are several different types of interactive concession based methods, see review by
Teich, Wallenius and Wallenius (1994). A number of them are implementing multiple
criteria decision making (MCDM) methods and especially many of them are based on multiple
objective linear programming (MOLP) because of the underlying similarities between
negotiation and multiple criteria decision problems (Hipel, Radford and Fang, 1993). The
MOLP-based methods require that the players construct a crude linear approximation of
their utility functions that are then applied in concession making in a variety of ways. For
an example on such methods see an early paper by Korhonen et al. (1979).
There is a number of methods for searching joint gains interactively. For instance,
Korhonen et al. (1986) describe a method where joint gains is produced by asking
pairwise comparisons from the group of players as a whole. Ehtamo and Hämäläinen
(2001) also include in this class the constraint proposal method (Ehtamo et al., 1999) and
RAMONA-method (Teich et al., 1995) as its special case. The constraint proposal
28
methods are based on searching interactively the joint tangencies of the players’ utility
functions that determine the Pareto optimal outcomes, c.f., Figure 6.
One important class of interactive methods searching for joint gains are single negotiation
text (SNT) procedures. The concept of SNT was originally presented by Fisher and Ury
(1981) who applied it in the historic Camp David peace negotiations between Egypt and
Israel in 1978, see especially Raiffa (1982; Chapter 14). There were seven issues to be
decided upon and a U.S. team worked as an assisting mediator, who presented an initial
tentative agreement, called SNT-0, by putting initial suggestive values for the issues and
asked the players to criticize it. The U.S. team made it clear that this tentative agreement
was not intended to be the final one and not even close to it but a neutral starting
package instead. Based on the players’ criticism the U.S. team remodified the tentative
agreement iteratively and this way went through several SNTs until no joint
improvements were possible, see Figure 8. As a result, after twenty five tentative
agreements, the negotiation process terminated and the players concluded the peace. U.S.
president Jimmy Carter worked as the head of the U.S. team and his mediation was
qualified for the Nobel Peace Prize in 2002.
SNT-0
SNT-1 SNT-2
SNT-24
SNT-25
utility for Israel
utility forEgypt
feasible utility pairs
Figure 8 SNT-procedure producing joint gains in Camp David
The SNT procedure has been formalized mathematically in the literature by the jointly
improving direction method by Ehtamo, Verkama and Hämäläinen (1994; 1999), see Chapter
4.3, and directional search method by Teich et al. (1996). The initial tentative agreement,
whose choice may constitute a negotiation process itself, plays a crucial role in these
methods and its impact on the result of the negotiation has been discussed by Korhonen
29
et al. (1995).
4.5 Jointly Improving Direction Method
Here we present the jointly improving direction method (Ehtamo, Verkama and
Hämäläinen, 1999). We describe the method by using verbal and geometrical reasoning.
In the jointly improving direction method, the players negotiate interactively over
continuous issues and search step-by-step for joint gains under assistance of a mediator
until there is no room for joint improvements. The method can, however, be applied also
in the case where the utility functions are explicitly known. Here we only present the
main ideas of the interactive formulation of the method assuming that there are two
players, 1 and 2, negotiating about two issues, A and B, say time and money. The e-
learning material presents the method through an example where Harold and William
apply it to reach Pareto optimal outcomes for the problem of the commons.
There are three main phases that are repeated iteratively until no joint improvements can
be achieved:
1. The mediator helps the players to criticize a tentative agreement
2. The mediator generates a compromise direction
3. The mediator helps the players to find a jointly preferred outcome along the
compromise direction and based on them proposes a new tentative agreement
First, the players agree on an initial tentative agreement that will be jointly improved. It
can be the Nash equilibrium being the self-evident solution for a game or any other
reference point they choose, e.g., through concession making. Status quo can be a suitable
choice too if the underlying issues already have well-defined current values to be
modified in the negotiation.
When the negotiation process begins the mediator lets the players to criticize the
tentative agreement. He draws a small circle, or ellipse, centered at the initial tentative
agreement and takes some points on it. Asking a player to choose the point he prefers
most the mediator is able to draw a line segment from the tentative agreement through
the chosen point. This line segment defines a direction that is called player’s most preferred
30
direction, see Figure 9 below.
Which one of the points do you prefer most?
Player’s most preferred direction
Issue A
Issue B
Figure 9 Choosing the most preferred point on the circle and defining the player’s most preferred
direction
By definition, a direction is jointly improving if by taking any sufficiently small step along it
an outcome that is preferred by each player is reached. The mediator chooses one such
direction as a compromise direction and here we define it to be the one bisecting the angle
between the players’ most preferred directions, see Figure 10. This choice can be shown
to produce a jointly improving direction under rather mild mathematical assumptions
regarding the players’ underlying utility functions. Eventually, by taking a suitable final step
along the compromise direction the mediator is able to propose a jointly preferred
outcome for the players.
Player 1’s most preferred direction
Issue A
Issue BPlayer 2’s most preferred direction
Compromise direction
Figure 10 The bisecting compromise direction
The mediator chooses the final step length by asking the players to choose the distance
they would like to move along the compromise direction, that is, to choose their most
preferred outcome along the direction, and taking the minimum of them. Thus he reaches a
new point, which he proposes as a new tentative agreement. This choice guarantees that
31
the step is not too long and hence the proposal is jointly preferred. If one of the players
is not willing to take any move, the procedure terminates; otherwise the iterative process
continues and the new tentative agreement is being criticized.
Ehtamo, Verkama and Hämäläinen (1999) have mathematically shown that the method
converges to a Pareto optimal point under certain mathematical assumptions. It is also
possible to generalize the method to include many players and many issues, see Ehtamo,
Kettunen and Hämäläinen (2001) for details. The Joint Gains applet actually implements
the many player many issue case.
The method can also be applied for eliciting the Pareto frontier for a game. This provides
systematical variation of the reference points to produce a set of Pareto optimal
outcomes that can then be used to approximate the frontier, see Figure 11.
Pareto frontier
Issue A
Issue B
Figure 11 Developing the Pareto frontier by applying the method of improving directions
32
5 Learning Module Description
Currently, one learning module is implemented in the e-learning material. It is an
“introduction to game theory and negotiation” and it is intended to be completed in two
person groups to hinder the students feel lonely and isolated. The module consists of
four main parts: theory, quizzes, assignments and case. It implements the e-learning
material structure presented in Chapter 3, as “introduction to value tree analysis”
module20 in the MCDA e-learning site, and teaches the theory that is roughly described in
Chapter 4.
The learning module is intended for students that have some mathematical background
and it covers the mathematical parts of the theory and the assignments. Therefore, the
module is suitable among others for the students of operations research and engineering.
This chapter presents the module from the students’ viewpoint by describing, how the
students are supervised and how do they carry out the phases of the module.
5.1 Instructions
The students are given a link to a front page of the learning module21 presenting first a
brief overview on the different parts of the module. The theory part consists of three
sections teaching the basic concepts of game theory, negotiation analysis and the jointly
improving direction method. The assignment is divided into two parts, a and b. The
former is an analytical one that measures students’ understanding of the theory from the
mathematical perspective and the latter is a practical software assignment. It requires the
students to solve interactively a negotiation problem presented in the case description.
Eventually, after completing the assignments the students give feedback on the learning
module. A summary of results of a student evaluation is presented in Chapter 6.
20 http://www.mcda.hut.fi/value_tree/learning-modules/, referred 01.04.2003 21 http://www.negotiation.hut.fi/learning-modules/IntroToGTAndNego/, referred 04.02.2003
33
We emphasize the learning objectives for the student explicitly because the interaction
between an instructor and a student lacks of face to face communication. The aim is that
the students learn in this module the following:
• the basic elements in game theory
• what a negotiation problem is
• the principles of the jointly improving direction method to reach a Pareto point
in a negotiation game
• how to use the Joint Gains in negotiations
Finally, the instructions give a sequence of links that serve as a detailed supervision on
how to complete the module. Figure 12 below summarizes its parts and shows the order
in which the students are guided to carry out them. Besides the main parts, the Figure
includes the Joint Gains and some video clips illustrating its use, which the students
apply in the software assignment.
Theory
GameTheory
NegotiationAnalysis
Jointly ImprovingDirection Method
Quizzes
Quiz 1
Quiz 2
Quiz 3
Assign-ment a
Assign-ment b
Instructions
Questions
VideosVideo 1
Video 2Video 3Case
Case description
Question 1
Question 2
Joint Gains
Theory
GameTheory
NegotiationAnalysis
Jointly ImprovingDirection Method
Quizzes
Quiz 1
Quiz 2
Quiz 3
Assign-ment aAssign-ment a
Assign-ment bAssign-ment b
Instructions
Questions
VideosVideo 1
Video 2Video 3
VideosVideo 1
Video 2Video 3CaseCase
Case description
Question 1
Question 2
Joint GainsJoint Gains
Figure 12 Expected learning sequence in the module
5.2 Theory and Quizzes
The students are assumed to go through the theory section by section straightforwardly
34
and self-evaluate by quizzes what they have learnt between the sections. The sections are
divided into subsections each of which physically consists of one HTML-page. The table
of contents of the theory is presented for the students in a separate frame on the left side
of the body text to help the navigation and sharpen the overview, see Figure 13 for
illustration. The navigation frame can be hidden if necessary.
Figure 13 Illustration of the theory from the students’ point of view
When working with the quizzes the students interpret graphs and very simple negotiation
situations. See, for instance, Figure 14 depicting a part of the game theory quiz. The
game theory quiz contains games presented in matrix form and as graphs depicting the
players’ payoff contours. The students identify the Nash equilibrium and some Pareto
optimal outcomes for those games.
Negotiation analysis quiz deals with real-life negotiation situations, such as buyer and
seller giving subsequent offers and counteroffers for each other, and asks the students to
classify the applied negotiation methods in the framework of the theory. The students
35
also need to reconsider the definitions of mediator and reference point.
The questions regarding the jointly improving direction method are graphical in nature
too. They concentrate on the concept of jointly improving direction and on choosing the
most preferred outcome along a direction in a case where the players’ payoff contours
are explicitly known. The students also need to conclude whether it is possible to achieve
joint gains or not if the sum of the utilities perceived by the players is constant. Naturally,
it is impossible because in such a case the players are as if dividing a cake and hence gain
for one unavoidably means losses for the other.
Figure 14 An example of the game theory quiz
5.3 Assignments and Case
After completing the theory the students open an assignment document that serves as a
report template containing questions regarding the assignment and the related
instructions. They start dealing with the analytical assignment that involves analysis of
two different games. The first one is the battle of the sexes game (Luce and Raiffa, 1957) that
36
is given in normal form. It has two Nash equilibria and the students are asked to point
out both of them. They also represent the game in extensive form by adding the players,
their strategies and payoffs in a pattern of a game tree in the report template.
The other game is the problem of the commons, or its special case assuming the
approximation that results the simple form of Cournot’s duopoly model, c.f., Chapter
4.1.2 and especially Equation (4.3). The theory part shows how to find the Nash
equilibrium for it but only graphically and hence, the students compute it here
analytically. They also find one Pareto optimal solution by using the jointly improving
direction method when the players’ utility functions are explicitly known. The
equilibrium is used as a reference agreement in this example.
The assignment b deals with a case that represents a typical negotiation settlement in
trading between a buyer and a seller who negotiate about price and delivery time. The
students first familiarize themselves with the case description that presents the problem
and the preferences of the negotiating parties verbally. Figure 15 is an example presenting
a case slide depicting the buyer’s problem.
Figure 15 A case description slide
37
The students may start grasping with the assignment b after they have chosen their roles
and understood the preferences they represent. They solve the negotiation problem with
the jointly improving direction method interactively by applying the Joint Gains applet.
The report template contains instructions and links to video clips illustrating how to
work with the Joint Gains, that is, how to create a negotiation case, negotiate and view
the results.
The students are provided to start the negotiation from two different reference
agreements. They present the corresponding negotiation processes graphically, analyze
verbally the convergence of the method and explain why different outcomes were
reached when starting from different reference agreements. They also evaluate the
reasonability of the applied method and its implementation by assessing qualitatively
whether the successive tentative agreements seem jointly improving, and whether the
final agreements seem Pareto optimal, or not. Figure 16 below illustrates how the
students read the instructions, work with the Joint Gains and answer the questions
simultaneously.
Figure 16 The students use the Joint Gains and fill their answers to the report template
38
6 Experiences of Use
In this chapter, we present experiences of use of the “introduction to game theory and
negotiation” module described in Chapter 5. The module was used in November 2002 in
an advanced web course on mathematical modeling organized by the Virtual University
of Finland. The students were from different universities in Finland and they used an
A&O learning environment22 developed at the Tampere University of Technology for
communication and handing on their assignments. The course consisted of eleven
learning sessions, each of which included theory and related assignments corresponding to
lectures and exercises of one week in a traditional face to face engineering course.
Additionally, there was a final assignment to be completed. The students got feedback
regarding the assignments by e-mail and newsgroup facilities provided by the A&O
learning environment.
Our module was one of the learning sessions and there were 9 student groups, who
completed it, and each group consisted of one or two students. The construction of the
other sessions was different from that of ours. They consisted approximately of two
hours of video lectures, related slide shows and assignments.
To evaluate our module we follow a model presented by Kirkpatrick (1998) who divides
the levels of evaluation into four stages:
1. Students’ subjective reactions
2. Students’ objective learning
3. Changes to students’ behavior
4. Results to organizations in which students work
Students’ subjective reactions are measured by asking the students to fill out an online
questionnaire and we refer this stage to as student evaluation. The level of students’
objective learning is measured by the online quizzes and the assignments. The last two
stages, behavioral changes and the results to the organization, are not addressed here at
all. This is simply because we are not aiming to influence explicitly neither on the
students’ behavior nor any organization they are working within. Moreover, measuring
22 http://ao.tut.fi/, referred 04.02.2003
39
those stages would have provided observing the students and the organizations they
represent already before the learning session took place.
It needs to be emphasized that according to Jolliffe, Ritter and Stevens (2001) the student
evaluation must not to have too high level of visibility in the learning process and it must
not be threatening at all. Otherwise it may affect the students’ learning experience that
can cause bias in the results of the evaluation. Hence, we measure the students’ reactions
only right after they have completed the learning session and not during it even if the
former would provide richer feedback. To keep the evaluation non-threatening the
students can give their feedback anonymously.
Note that the experiences apply to the very first version of the module and are based on
low number of students offering no possibility for statistical analysis. Hence, the results
should be considered only as a rough overview providing guidelines for the future
development of the e-learning material.
6.1 Student Evaluation
The aim of the student evaluation is to measure how the students feel and not about
what they actually have learned. This means measuring their subjective feelings and
opinions about the functionality, effectiveness and quality of the learning module. This
subjective point of view is especially interesting because enthusiasm and positive feelings
obviously correlate positively with the level of learning.
6.1.1 Online Questionnaire
The applied online questionnaire contains multiple choice questions and some free form
questions that provide possibilities for writing down more detailed and accurate opinions
and thoughts. The questionnaire is intended to be as generic as possible to support its
reusability and hence the comparability of the opinions gathered in the forthcoming
evaluations. This comparability is also intended to cover comparisons between different
modules or even courses.
We divide the questions in the questionnaire into five main parts by partly adapting
student evaluation model by Jolliffe, Ritter and Stevens (2001):
40
1. Students’ background information
2. Technical issues
3. General opinions on e-learning
4. Opinions on the e-learning material
5. Concluding questions
The “Background information” part investigates the students’ personal profile that can
be used in classification of different types of students in the analysis of the results. We
ask their educational background, i.e., their university, department, years of study and
gender. Also, we ask their previous familiarity with browsing in the web and using e-mail
to understand if the level of technical knowledge affects the students’ perceptions.
The “Technical issues” part gathers information on technical problems the students
possibly face when completing the module. The problems with the learning material and
the software (Joint Gains) are kept separate. To understand the reasons for possibly
emerging problems we also ask which web-browser and computer platform they used
because they have often emerged to be sources of technical incompatibility problems.
The level of difficulties is measured on a subjective scale: none, some, minor, major and
overwhelming.
The “General opinions” part asks the students to list advantages and disadvantages they
see in e-learning and their earlier experience with web-based learning. These questions
serve as a barometer concerning the attitudes towards e-learning in the long run but they
also produce snapshot information that can be used when deciding how to develop the
material in the future.
The “Opinions on the e-learning material” part is the core of the questionnaire
investigating students’ subjective feelings about the module. First, as a kind of
background information concerning the module itself, we ask how familiar the students
were with the topic of the module, how long did it take to finish the module, whether
they worked with a pair or alone and whether they printed any material on paper or not.
The students assess how much they have learned and evaluate the usefulness of the
different elements of the module and the module as a whole. We also ask how easy it was
to navigate in the material, understand the assignment and the instructions.
41
As a conclusion, students’ willingness to work in similar learning environments and to
recommend their experiences for their fellow students is probed. To compare our format
to the format of video lectures we also ask which type did they prefer and how strongly.
The applied online questionnaire is available in its full detail in a module evaluation page
for reference23.
6.1.2 Results
Here we summarize the most interesting patterns of the results of the student evaluation.
The complete results are available in the module evaluation page23 together with the
questionnaire form.
The participating students were mainly graduate students in industrial engineering,
systems engineering, physics or other engineering. They considered themselves quite
experienced users of web and they had some familiarity with e-learning from the earlier
learning sessions of the web course. Hence, our experiences comprise of opinions of a
group of students who are not expected to be very technofobic and whose educational
background is relatively sound.
Figure 17 presents the results of the questions examining the students’ opinions about
the benefits and disadvantages of web-based learning at a general level. It can be seen
that most of the students considered “independence of location and timing” and the
“possibility for self-paced learning” as the main benefits in e-learning. Only a few of
them did see potential behind the other options included in the online questionnaire such
as “learning by doing” and “new ways to present information”. Hence, we can observe
that, from the students’ viewpoint, the main advantage offered by electronic media is the
possibility for learning “any time, anywhere”.
The students were relatively critical towards e-learning, c.f., Figure 17. Most of them
judged the “lack of communication with teacher” and the “lack of communication with
their peers” as the main drawbacks whereas none of them did find “lack of ways to
23 http://www.negotiation.hut.fi/learning-modules/IntroToGTAndNego/evaluation/evaluation.html, referred 04.02.2003
42
evaluate learning” as a problem. Some of the students also considered that “e-learning
requires self motivation” and found it as a problem. Indeed, this may be a problem but
mainly it is a counterbalance to the independency of physical location and timing and
hence it is hardly avoidable. These results propose that it is necessary to concentrate on
the forms of interaction and especially relations between face to face interaction and
electronic media when developing e-learning material. It is also important to focus on
robust implementation of electronic media and usability of the learning material as many
of the students found that “difficulties with technology” interfere e-learning.
Figure 17 Main benefits and disadvantages the students see in web-based learning in general
When judging the usefulness of our e-learning material the students found the theory
sections as the most useful element of the module, see Figure 18. For instance, the
students did not consider the quizzes too useful, which reflects their unpopularity. Only
four groups out of nine took even a look at the quizzes and only two groups answered
each of them. Hence, the results regarding the usefulness of the quizzes are insignificant
and suffer from the lack of interpretation in this case. The unpopularity of the quizzes is
explained by the fact that they were intended for self-evaluation, which was not
considered a problem by the students.
The usefulness of the video clips illustrating the use of the Joint Gains in the software
43
assignments was considered relatively low, too. This is likely because the written form
instructions regarding the software assignment were quite detailed and the students
reported understanding them relatively well, as results presented in Figure 19 show.
At this stage, when assessing the usefulness of the different elements of the module, it is
worth of realizing that the students were relatively skilled and they had earlier e-learning
experiences. When teaching more inexperienced students the evaluation would likely be
different. This is because inexperienced students feel themselves more technofobic and
lonely and hence, they will perceive the assisting role of the quizzes and the video clips
more important.
Figure 18 Usefulness of theory sections, video clips and quizzes
Figure 19 Understandability of the assignment and the instructions
44
Figure 20 Technical difficulties with the learning module
The students appeared to face some technical difficulties with the learning material and
the Joint Gains software, as shown in Figure 20. Nevertheless, they were not
overwhelming and some of the learning material related problems were due to
perturbations in the students’ own network, according to the free form feedback. Most
of the technical problems related to the software assignment are likely due to
incompatibility problems between the Joint Gains applet and the Java version installed in
student’s web browser. This type of problems are well known in the development of
web-based software; for more details and most up to date information, we suggest
interested reader to familiarize oneself with the technical documentation at the web site
of the Sun Microsystems developer services24.
The results of the concluding questions are mainly positive, c.f., Figure 21. It is strikingly
positive to realize that a clear majority of the students is willing to work in e-learning
environments similar to ours in the future. The students are somewhat hesitant when
their willingness to recommend their experiences for their fellow students is asked but
none of them is reluctant in this case. The results regarding the comparisons between the
video lectures and our format of e-learning were positive but neutral, too. In fact, only
one of the students prefers the video lectures to our format and virtually half of them are
24 http://developer.java.sun.com/, referred 28.04.2003
45
indifferent. Hence, we may conclude that our format of e-learning, which does not
intensively imitate the traditional lectured courses, gains support from the students and it
is worth of further development.
Figure 21 Students’ willingness to work in and recommend this type of e-learning format and its
comparison to video lectures
Systematical analysis and comparison between different subgroups of the students, such
as male and female, is not judicious in our case because the number of student responses
is such small. Nevertheless, we may highlight one interesting pattern in the results.
Namely, there seems to be a clear distinction between the judgments of the students who
printed material on paper and who did not. Namely, those two students, who gave the
worst score (2/5) on the usefulness of the theory sections, did not print anything on
paper. This is likely because the learning material is not completely on-screen readable
even if it was one of the goals in the material design. This kind of on-screen readability
problems conform to the experiences reported in e-learning literature, see, e.g., Weitl et
al. (2002). Hence, we can see that it is indeed necessary to offer possibilities for printing
out the material easily and that the foremost role of the Internet is to act as a tool for
material dissemination in case of the theory sections.
46
It is also worth of remarking that a more detailed quantitative analysis of the answers did
not verify that the level of appeared technical problems would have affected remarkably
students’ opinions and perceptions regarding the usefulness of the e-learning material.
This result is somewhat unexpected and it suggests that the technical difficulties faced by
the students were eventually relatively slight and hence they did not seriously affect the
students’ perceptions.
6.2 Quizzes and Assignments
The assignments and the quizzes provide information on the quality and validity of the
learning material by measuring the students’ skills objectively. Jolliffe, Ritter and Stevens
(2001) claim that especially multiple choice questions are suitable for this use because
their answers are unambiguous and hence easy to interpret. Nevertheless, they do neither
measure nor support deep understanding of the studied topic. In our case, the quizzes
correspond to those multiple choice questions and the assignments are for measuring the
deeper understanding. The quizzes are not addressed here at all because of their relatively
low level of popularity.
There were no systematical problems in understanding the theory based on the students’
answers. They did not need any personal guidance and they succeeded relatively well in
the analytical assignment and the software assignment, both of which are described in
more detail in Chapter 5.3.
The analytical assignment involved the students to analyze the battle of the sexes game
and the problem of the commons by applying mathematical tools they have learned so
far. The students transform the matrix form representation of the battle of the sexes
game to extensive form and find out its Nash equilibria. Here, each of the student groups
succeeded well and none of them had any deficiencies in their answers. The analysis of
the problem of the commons involved the students to find out its Nash equilibrium, too,
and to compute a Pareto optimal solution for that game by applying jointly improving
direction method when the players’ utility functions are explicitly known. This analysis
encountered a few problems but they were neither systematical nor severe.
The students faced more problems in the software assignment, where each group played
a role playing experiment with the Joint Gains. Seven groups out of nine had two
47
negotiation sessions and hence 14 negotiation sessions were performed in total. The
negotiation processes seemed to converge reasonably towards a Pareto optimal solution
only in case of three sessions. Those convergence problems caused confusion among the
students, who were partly unable to explain the reasons. Later, the analysis of the
negotiation processes of the sessions indicated that the students had entered irrational
answers in different phases of the negotiation process. This is likely due to the fact that
role playing is quite difficult (Hämäläinen et al., 2001) and that some of the students
negotiated alone by playing the roles of the both parties. To prevent this kind of
problems students should really work in two person groups as recommended in the
assignment instructions. Additionally, the software assignment should perhaps offer a
wider variety of practical cases among which the students’ might have chosen the one
closest to their personal context. This would prevent the students to have role playing
experiments by letting them to represent themselves in the negotiation.
48
7 Discussion
Based on the results of the student evaluation the students are willing to work in learning
environments similar to ours in the future and our format of e-learning compares with
video lectures. The students do not either resist the idea of recommending their learning
experiences for their fellow students. Moreover, the students were able to complete the
required assignments relatively well independently; they did not either need any personal
guidance of the human instructor or apply the newsgroup facilities for communication.
Hence, we have successfully created an e-learning material for teaching mathematical
models of negotiation analysis and the use of the Joint Gains software by employing the
Internet as a tool for interaction and material delivery.
The results of the student evaluation suggest that reading the theory on the computer
screen may be difficult because the students, who considered the theory useful, had
printed some material on paper. Therefore, the e-learning material is not completely on-
screen readable even if this was one of the design criteria. As an observation this is in a
harmony with earlier experiences reported in the literature and therefore we are not
anxious with this. It has also often been argued in the literature that mathematical topics
are unsuitable for e-learning. Based on our experiences we, however, doubt this. We
rather consider that the form of e-learning need to be tailored according to the
requirements of the studied topic and that the reported problems in e-learning basically
derive from the fact that reading electronic textbooks on-screen is difficult. Hence, the
theory sections, if delivered electronically, need to be designed so that they can be easily
printed and efficiently browsed especially if they contain complicated theoretical or
mathematical topics.
Hereby, we propose that electronic media is suitable for educational use but not alone as
it is. It still adds value for learning through offering capabilities for interaction,
visualization and material delivery. Hence, the research on e-learning should focus
extensively on providing interactive exercises and vivacious visualizations for the
students. Also, it should pay attention on structuring the material and integrating
traditional face to face class sessions and other learning elements, such as electronic
theory sections, traditional printed textbooks, cases, exercises, animations and video
clips, together as a whole in a learner friendly manner.
49
It was surprising to note that the students reported that they did not consider the lack of
self-evaluation as a problem in e-learning when grasping with our module. The most of
the students did not even try to answer the quizzes and they were able to work
independently. We see this indicating that the lack of social interaction was not a severe
problem in our experiment. Probably, this is partly because the students were allowed to
work with a fellow student as a group, which allows a chance for personal face to face
discussions hence preventing the learning to lose its social dimensions.
The students’ viewpoint is the most essential aspect when evaluating new ways of
education; this is what we have discussed so far. Nevertheless, teachers’ and developers’
viewpoint is worth of consideration as well because, in practice, it is impossible to offer
effective learning facilities for the students for anything. Based on our experiences we
consider that the development of e-learning material is time consuming. Especially,
creating new electronic theory sections and tools for interactive assignments requires
much effort. Hence, it would be easier to use existing theory sections delivered either
electronically or in format of traditional printed textbooks. Nevertheless, this was not
possible in our case because hardly any textbooks have been published about the
mathematical models of negotiation analysis except textbooks by Raiffa (1982) and
Raiffa, Richardson and Metcalfe (2002). After creating and implementing an e-learning
material its maintenance and future development should be easy and flexible, however.
The future shall show if this is true in our case and the invested effort pays back.
Online communication by e-mail with the students appeared to be relatively time
consuming, too. For instance, online feedback regarding the assignments had to be more
detailed and giving it was more inefficient than traditionally on a face to face basis. This
is because of the lack of social interaction that increases the eventuality of
misunderstandings and does not offer possibilities for focusing on the issues that are
basically unclear for the student.
In the future, our main aim is to have more experiences on the use of the e-learning
material also in the international context and thus gather even deeper insight on e-
learning of the mathematical models of negotiation analysis. To support the needs of a
variety of learners we should implement new learning modules and cases. Examples of
the future users of the material are economists, experts of e-business and persons
involved in environmental and political decision making. Also, later in the future,
50
diplomats could be possible users. This is because the methods in negotiation analysis are
especially suitable for international negotiations due to their analytical nature that may
help in relaxing possibly emerging cross-cultural tensions in a negotiation table, see, e.g.,
Sebenius (2001) and Kersten and Noronha (1999) for more details.
Economists’ point of view could be illustrated by creating a case presenting labor and
management negotiating employment contracts. A case on business to business
automated negotiations was interesting to complement the existing case to represent
negotiation analysis in the field of e-business. The environmental decision makers and
the politicians could be served by a case in which stakeholders with conflicting interests
negotiate a common policy of the management of natural resources. For example, this
could involve negotiation on the use and maintenance of a common water resource in
agriculture; see an article by Thoyer et al. (2001) for a concrete instance. As we can
imagine there is a variety of possible generic cases that could be implemented and served
for the different groups of students. Nonetheless, extensive creation of generic imaginary
cases should be avoided because a specifically tailored case need to be provided for
extremely application oriented learners.
The students, who are interested in mathematical modeling approach of the negotiations,
will be served by the existing module complemented with existing relevant literature.
Also, a variety of optional relatively simple case problems should be served for the
students to allow them to choose the most attractive one for the software assignment.
The students could be made even happier by making the use of the Joint Gains applet
can a bit more instructive and self-explaining as well. We could deepen the integration
between the instructions and the applet by establishing pedagogical structured wizards to
aid case creation and negotiation. This solution would also make the use of the applet
even easier and require lower level of expertise from the negotiating parties that are
specifically interested in its applications.
51
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