APPLYING CASE-BASED REASONING FOR IDENTIFYING

THE NEGOTIATION PROFILE OF ELECTRONIC

NEGOTIATION SYSTEM USERS

Jakub Brzostowski

and Tomasz Wachowicz

Institute of Mathematics, Silesian University of Technology, ul. Kaszubska 23, 44-100 Gliwice, Poland

Department of Operations Research, University of Economics in Katowice, ul.1 Maja 50, 40-287 Katowice, Poland

Keywords: Negotiation profile, Conflict modes, Case-based reasoning, Electronic negotiation systems, Reputation

systems.

Abstract: In this paper we analyze the problem of identifying the negotiation profile of the electronic negotiation

system users. Usually such a profile is identified by means of the specific questionnaire (e.g. the Thomas-

Kilmann questionnaire), however it requires from the negotiator answering many troublesome questions

which is tiring and may lead to unreliable results. On the other hand many behavioural and psychological

studies confirm that there is a set of demographical and sociological characteristics that influence the human

general behaviour. Deriving from these studies we try to determine such a profile by analyzing the general

information provided by the pre-negotiation questionnaire the users fill while creating their negotiation

accounts. Having the historical data of Inspire negotiation system we try to find links between a set of the

data that describes the negotiators demographical features and their final negotiation profile using the notion

of Gilboa and Schmeidler case-based reasoning (CBR). To determine all the parameters required for the

case-based reasoning the statistical correspondence analysis on the set of the historical data is conducted in

advance. The results of CBR-based profile identification are also presented and discussed.

1 INTRODUCTION

The negotiation profile of a negotiator, as we see it,

is a set of negotiator's features, such as

cooperativeness, selfishness, assertiveness etc., that

describe negotiator’s behaviour in conflict

situations. It describes in fact a bargaining style of a

negotiator, which is a relatively stable, personality-

driven cluster of behaviours and reactions that arise

in negotiating encounters (Shell, 2001). This

bargaining style is, in turn, determined by

negotiator’s individual characteristics such as:

cultural (Adair and Brett, 2004) or demographical

(Jehn et al., 1997) ones or the visible personal

characteristics like age and gender (Kray and

Thompson, 2005). Some research confirm the

impact of these characteristics on the negotiation

process and outcomes (Sternberg and Dobson, 1987;

Thompson, 1990; Kersten et al., 2003) as well as the

impact of other factors, such as the motivation

styles, abilities or enduring dispositions (Elfenbein

et al., 2008). Thus it is important to be aware of

one’s negotiation profile, since it may influence the

negotiation process and the atmosphere of the

forthcoming negotiations. Having a particular

negotiation profile and using the corresponding

bargaining style makes the negotiators to be more or

less willing to use thus-or-such negotiation strategy

and tactics and consequently, to represent different

attitude towards the negotiation problem and to their

negotiation counterpart. Moreover, knowing the

counterpart’s negotiation profile may allow

negotiator preparing better to the forthcoming

negotiation, identifying their own strategies that fit

the counterpart’s position and style the best and

allow to influence them most efficiently to achieve

negotiator’s goals.

Negotiation profile can be identified twofold.

First approach is to use a psychometric instrument

based on the series of questions posed to the

negotiator and derive their negotiation profile by

analyzing different combinations of their answers.

Second approach is based on the extraction of the

levels of the profile’s features from the negotiation

thread by analyzing the communication process

between the parties. An example of the first

Brzostowski J. and Wachowicz T..

APPLYING CASE-BASED REASONING FOR IDENTIFYING THE NEGOTIATION PROFILE OF ELECTRONIC NEGOTIATION SYSTEM USERS.

DOI: 10.5220/0003755100480058

In Proceedings of the 1st International Conference on Operations Research and Enterprise Systems (ICORES-2012), pages 48-58

ISBN: 978-989-8425-97-3

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

approach is the Thomas-Kilmann conflict mode

instrument (TKI) proposed by Kilmann and Thomas

(1983). An application of such an instrument results

in levels of belonging of the negotiator to five

regions spanned on a plane with axes corresponding

to assertiveness and cooperativeness. The second

approach aims at measuring the degree of profile’s

features based on the types of responses given by a

negotiator during the process of exchanging

messages between two sides of the encounter (see

Brzostowski and Wachowicz, 2010). The type of

response, which may be positive, negative or

neutral, is scored with positive sign for positive

messages and negative sign for negative messages.

The scores also depend on the degree of importance

of a request and the degree of response satisfaction.

The problem with the first approach is that filling the

questionnaire and answering the series of question

may be time consuming, tiresome and discouraging

for the negotiator, while in the second approach

there is no knowledge allowing for building

negotiator's profile if the negotiator did not start any

encounter, yet.

In this paper we address a problem of identifying

the negotiation profile of the new electronic

negotiation system users with no negotiation history

behind them, but avoiding the specific psychometric

questionnaires (like the TKI ones). The main goal of

this paper is to prepare the formal mechanism that

would allow for eliciting the profile from the basic

descriptive information the user is giving while

registering to the system (creating an user account)

and filling the pre-negotiation questionnaire. To

solve this problem we propose to reason from the

case base that describes the historical negotiations

within which both the descriptive information of the

parties and their negotiation profiles were recorded.

It will allow us to conduct the case-based reasoning

(CBR) using the Gilboa and Schmeidler approach

(1995).

The paper has 6 more sections. The research

context that was the initial point for this paper is

presented in Section 2. Then, in Section 3 the

description of the case-based reasoning approach is

given. In Section 4, the set of historical data required

for the case-based reasoning is described, while in

Section 5 the application of CBR main ideas for

determining the negotiator’s bargaining profile

(based on the historical data) is shown. The issue of

determining the weight parameters required for case-

base reasoning is discussed in section 6. In section 7

the results of our approach are presented and

discussed. We conclude with some remarks on the

future work.

2 RESEARCH CONTEXT

The problem we have risen in the previous section is

a part of the research we are carrying out in order to

build a comprehensive electronic negotiation system

that would support its users throughout the whole

negotiation process, starting with the pre-negotiation

preparation and ending with the post-negotiation

optimization of the negotiated agreement

(Brzostowski and Wachowicz, 2009). The system,

called NegoManage, is designed to be a negotiating

platform that would allow negotiators to define the

negotiation problem, find the suitable counterpart

and negotiate the contract. NegoManage is a kind of

distributed system with the core deployed on the

Web and responsible for supporting communication

among the users and sharing the public information

about them (NegoManage Communication Unit).

There are also the satellite sub-systems responsible

for various functionalities such as the preference

elicitation subsystem, data visualization unit,

reputation subsystem, etc. Some of them are also

deployed on the Web, while the others need to be

installed on the users desktop computers. Such a

structure was chosen due to the security reasons.

Some information are strategic (like the negotiators

preferences) and should not be revealed to the

counterparts, therefore the subsystems responsible

for processing such information are deployed on the

users computers (NegoManage Individual Unit) and

there is no an external access to them from the level

of Web based units. The general architecture of the

system is presented in Figure 1.

Figure 1: The architecture of the NegoManage system.

One of the key elements of NegoManage system

is the reputation subsystem. According to the

definition of Howison (2009) the reputation in the

context of electronic interaction may described such

features of the systems and users as trustworthiness,

quality or any other characteristic specific to the

analyzed domain. NegoManage reputation

subsystem describes the negotiator’s profiles using

APPLYING CASE-BASED REASONING FOR IDENTIFYING THE NEGOTIATION PROFILE OF ELECTRONIC

NEGOTIATION SYSTEM USERS

two major negotiator’s characteristic: assertiveness

and cooperativeness, derived directly form the Dual

Concerns Model (Blake and Mouton, 1964). As

addressed in Section 1, such a profile could be

elicited by means of TKI and the Wharton-TKI

Bargaining Styles Grid (Shell, 2001) that allows to

recalculate TKI five-characteristic scores into the

two-dimension space of assertiveness and

cooperativeness. However, in NegoManage system

we aim to build the reputation system that reflect the

true negotiation profile the system user presents

during the subsequent encounters. We decided then

to determine the negotiators’ profiles based on the

analysis of messages exchanged between the players

in the process of negotiation. Deriving form the

Searle’s and Stile’s speech act taxonomies (Searle,

1969; Stiles, 1992) we proposed a new negotiation-

context depended speech act taxonomy (Brzostowski

and Wachowicz, 2010), based on which the

exchanged messages are classified and used later on

by the profiling mechanism. The mechanism, that

works according to formal algorithm, checks how

the message receiver is responding to the request of

message sender. Next, the mechanism determines

the degrees of the negotiator’s features (i.e.

assertiveness and cooperativeness). The final degree

of a feature is computed as an average degree of a

feature for multiple past negotiations. The

negotiation profile calculated this way is then

displayed by the reputation subsystem to all

NegoManage users and may be used by them for

browsing the most appropriate (from the behavioural

point of view) counterpart and for adequate

preparation of the negotiation strategy in the

forthcoming negotiations.

The only problem that occurs in our approach is

how to identify the initial negotiation profile of the

new system user, that did not conduct the

negotiation in NegoManage system yet. Since we

wanted to avoid using the TKI or similar solutions,

such as the Kraybill Conflict Style Inventory

(Kraybill, 2005) or Myers-Briggs Type Indicator

(Briggs and Myers, 1980), we decided to identify

such a profile based on the visible demographic

characteristics and psychological description of the

user that are available within their pre-negotiation

questionnaires. We assume then, having derived

from the results of behavioural research on

negotiation and the five-factor model (Mershon and

Gorsuch, 1988; Paunonen and Ashton, 2001;

Herrmann, 2004; Patton and Balakrishnan, 2010),

that there is any relation between some personal

characteristics of the negotiators and their

negotiation profiles. To find the relation and

describe it formally we will apply the case-based

reasoning (see Section 3). For such a reasoning the

historical data of the previous negotiation

experiment is needed that would provide all the

information required to build both the input and

output data. The case base we will use would be

comprised with the Inspire electronic negotiation

system data (see Section 4).

3 CASE-BASED REASONING

AND CASE-BASED PROBLEM

SOLVING

The idea of case-based problem solving is based on

the postulate that similar problems have similar

solutions (see Aamodt and Plaza, 1994; Gilboa and

Schmeidler, 1995). In the classical case-based

problem solving (Leake, 1996) we use the past

solutions of past problems to solve a new problem.

The idea of case-based problem solving is illustrated

in Figure 1.

The CBR mechanism retrieves from the case base

the relevant cases and adapts them to fit a new

problem. In the first stage of CBR features of the

current situation that are really relevant are

determined. In the next stage the CBR mechanism

retrieves from the most relevant prior cases or case.

Then the retrieved case or cases is adapted to fit the

new situation. After applying the solution suggested

by CBR the new case is stored in the case base.

Our application of the CBR concept differs from

the typical application. Instead of finding the

solution to a new problem we use the CBR concept

to predict the outcome of a new situation. We do not

consider the whole CBR cycle concerning the full

methodological framework of this approach

(Aamodt and Plaza, 1994). Instead, we focus on the

inference stage within the overall process of CBR. In

our particular application context we can consider a

decision problem of selecting the negotiation partner

with desired conflict resolution style. The decision

of selecting the negotiation partner is based on

similar encounters in the past. The concept of Case-

Based Decision Taking (Gilboa and Schmeidler,

1995) is used when each case may be split into three

components: the decision problem (situation), the act

that was chosen by the decision maker in this case

and the outcome received by the decision-maker.

The three abstract sets corresponding to these three

component may be introduced:

1. P - the set of decision problems. In our case

the decision problem is described by the

ICORES 2012 - 1st International Conference on Operations Research and Enterprise Systems

Figure 2: Leak's model of CBR accroding to (Leake, 1996).

demographic description of the negotiation

partner in the past negotiation.

2. A - the set of possible acts. The set of

potential negotiation partners. The act in this

case is a choice of one of those partners.

3. R – the set of conceivable results. The set of

resulting conflict resolution styles of the

chosen negotiator partner. In other words, it

is the description of encountered negotiation

behaviour of the chosen partner.

The product of these three sets gives us the set of

all possible cases

RAPC ×

. The given case

base M is a subset of the set C (

CM ⊂

4 INSPIRE’S CASE BASE

Inspire (Kersten and Noronha, 1999) is an online

system that has been used for years, mainly for

training and teaching negotiations (Paradis et al.,

2010). It supports negotiating parties in bilateral

negotiation process: pre-negotiation preparation,

actual conduct of negotiation and post-negotiation

phase. In the pre-negotiation phase the Inspire users

are asked to fill the questionnaire giving the basic

personal information about themselves and their

attitude towards the negotiation problem, process

and counterpart. Then they take the Thomas-

Kilmann test and have their bargaining style

identified this way. Inspires provides also its users

with the preference elicitation, that allow building

their own negotiation offers scoring systems. In the

actual negotiation phase the system supports the

communication between the parties, helps them to

evaluate negotiation offers and visualizes the

negotiation progress. In the post-negotiation phase

Inspire analyzes the compromise (if achieved) and

browses for its improvements using the notion of

Pareto-efficiency.

The case base required for our analysis is

comprised of the data collected by Inspire system

within the pre-negotiation phase. The base contains

the description of the users’ demographic and

personal features provided by the pre-negotiation

questionnaire and the TKI’s conflict style regions

(i.e. competing, collaborating, compromising,

avoiding and accommodating) identified by means

of TKI test. The set of users’ personal information

with the pre-defined resolution levels for the closed-

form questions are shown in Table 1.

APPLYING CASE-BASED REASONING FOR IDENTIFYING THE NEGOTIATION PROFILE OF ELECTRONIC

NEGOTIATION SYSTEM USERS

Table 1: The user’s personal characteristics recorded by Inspire system.

Description Options

Program of study (ed_field)

Arts and Fine Arts (1); Business & Management (2); Communication (3); Computer Science &

Information Technology (4); Education (5); Engineering (6); Health, Medical & Nursing (7);

Humanities (8); International Studies (9); Law & Criminal Justice (10); Mathematics & Statistics

(11); Psychology (12); Public Affairs, Administration (13); Social & Behavioural Sciences (14);

Others (15)

Level of stud (ed_level) High School (1), Undergraduate (2), Graduate (3)

Gender (gender) Female (1), Male (2)

Age group (age) 20 or less (1); 21-25 (2); 26-30 (3); 31-40 (4); 41-50 (5); 51 or more (6)

In which country was the user born? (c_born) Two letters UN symbol (numerical code)

In which country does the user currently reside?

(c_reside)

Two letters UN symbol

How long does the user reside in the country of

residence? (l_reside)

6 months or less (1); 6 months to 1 year (2); 1 year to 2 years (3); 2 years to 4 years (4); 4 years

to 7 years (5); 7 years or more (6)

First language (m_tongue) Name (numerical code)

Did the user participate in negotiation experiments

before? (p_before)

Yes (1); No (2)

Did the user use a decision support or negotiation

software before? (NSS)

Yes (1); No (2)

Did the user attend negotiation course/seminar before?

(course)

None (1); one (2); two or more (3)

How does the user rate her knowledge of negotiation?

(knowledge)

From novice (1) to expert (7)

How does the user rate her English proficiency?

(english)

From poor (1) to excellent (7)

In case-based decision theory each case consists of

two components: the situation and the outcome that

was experienced for this situation. For the

negotiation profile identification each case would

consist of demographic values as an input

(description of the situation) and the bargaining style

obtained as a result of TKI questionnaire as an

output (description of the outcome in terms of the

scores of the five regions of styles). The sample case

base input and output are shown in Table 2 and

Table 3.

Table 2: The case base (input) containing user description

in terms of demographic variables.

Vectors of input

age gen

der

c_r

esid

l_re

side

c_b

orn

m_t

ong

eng

lish

cou

rse

ed_

leve

kno

wle

dge

p_b

efor

ed_

fiel

2 2 1 3 16 1 6 2 3 1 2 1 2

2 1 1 6 1 1 6 1 2 1 2 2 2

2 2 1 6 1 1 5 1 2 1 2 1 2

1 2 1 6 1 1 7 2 2 1 5 2 2

3 2 1 6 1 1 4 1 2 1 4 1 2

Table 3: The case base (output) containing resulting

conflict mode regions descriptions.

Vectors of output

Competing Collaborating Compromising Avoiding Accomodating

4 3 10 7 4

5 2 9 7 5

6 6 9 5 2

9 3 10 2 4

4 5 10 6 3

5 APPLYING CBR FOR

IDENTIFYING THE

NEGOTIATORS BARGAINING

STYLE

The case-based prediction in our application aims at

estimating negotiator's conflict resolutions

(bargaining) style approach. Therefore as the

situations we have the negotiators demographic

features and as the outcome their conflict resolution

style descriptions. In other words, based on the

knowledge contained in the Inspire’s case base we

aim at predicting the conflict resolution styles based

ICORES 2012 - 1st International Conference on Operations Research and Enterprise Systems

on its demographic characteristics. In order to use

the case-based reasoning for identifying the profile

of any new negotiator we have to extract from the

case base the user demographic descriptions most

similar to the demographic descriptions of this new

negotiator (system user) first. Having selected these

descriptions we can estimate the bargaining style of

the new user by comparing the historical conflict

resolutions styles of the similar users in terms of

demographic characteristics.

Two questions arise here. First, how to form a

similarity metric for comparing the situations

(demographics descriptions) and second, how to

adjust the conflict resolutions style descriptions of

the similar negotiators to form a prediction about the

conflict resolution style of the assessed novice

negotiator.

Most of the demographic variables we use are

nominal, and therefore the similarity metric has to be

formed taking into account this feature. The

situation (the user demographics) is modelled here

as a vector of 12 variables. Since these variables are

nominal the similairty metric comparing the

situations x and y on each variable i should have a

simple form:

⎩

⎨

⎧

≠

yxS

),(

(1)

meaning that if two values of a demographic

variable are compared the similarity metric assings 1

to a pair of values if they are identical, and 0 if they

are different. It does not make sense to fuzzify the

metric since the varaible is nominal. The similarity

metric comparing vectors of 12 demographic

characteristics X = (x

, …, x

) and Y = (y

, …, y

)

is in turn of the following form:

∑

),(),(

iiii

yxSwYXS

(2)

As shown in the above formula, the similarity of

the demographic descriptions of two users is a

weighted sum of the similarity metrics, comparing

the situations on each coordinate of the demographic

user descriptions. The values

})12,,1{( K∈iw

are

the levels of importance of all demographic

variables. These values are determined using the

correspondence analysis, as we will show in Section

Having extracted the most similar cases from the

case base by means of the similarity metric S, we

may now adjust the conflict resolution styles

descriptions in the exctracted cases. This style is

described by five variables, namely: competing,

collaborating, compromising, avoiding and

accomodating. These variables are ordinal, which

allows us to use following procedure of adjustement.

Let us consider one variable which describes the

level of belonging to a particular conflict resolution

feature (for instance competing). Let us assume that

in the hypothetical situation we extracted from the

case base a set K of k most similar cases. In this

situation we have k cases in the form of the vectors

as follows:

),,,;,,,(

5211221

jjjjjj

cccddd KK .

(3)

where

},,1{ kj K

∈

d corresponds to the ith

demographic characteristic of the jth case

(

}12,,1{ K

∈

i ) and

c corresponds to the mth

bargaining style characteristic of the jth case

(

}5,,1{ K

∈

m ). The cases were exctracted from the

case base based on their similarity to the current

situation for which we want to estimate the conflict

resolution style and which we denote as

)

(

1221

dddD K= . The similarity degree of each

case j from the set K is determined by means of

formula (2) and is denoted by

s :

)

,( DDSs

= for each },,1{ kj K∈ .

(4)

Having the sequence of

s , describing the

similarities of the historical situations with the

current situation, we can estimate the value of

conflict resolution style variable for the current

situation using the concept of Gilboa and Schmeidler

(1995) case-based reasoning. According to the

Gilboa and Schmeidler ideas the estimation of the

bargaining style feature will be computed using the

following formula:

∑

(5)

In the formula (5) the estimation of a feature is

computed as the weighted sum of this feature in

historical situations. The more similar the historical

situation is to the current situation the higher the

contribution of the feature taken from historical

situation.

Let us assume, for example, that for the new

negotiator we have extracted from the case base

three the most similar cases with similarity degrees

as follows:

APPLYING CASE-BASED REASONING FOR IDENTIFYING THE NEGOTIATION PROFILE OF ELECTRONIC

NEGOTIATION SYSTEM USERS

7.085.095.0

321

=== sss

Furthermore, let us assume that the bargaining

style descriptions for these cases are as follows:

),4,10,3,8,5(),,,,(

=ccccc

),5,11,4,3,8(),,,,(

=ccccc

).3,7,10,5,2(),,,,(

=ccccc

We use formula (5) to estimate the style’s

features of the new negotiator. For instance, the

estimation of the competing feature (the first of five

bargaining style feature) is the following:

18.5

5.2

7.0285.0895.05

×+×+×

∑

As we can see in the above formula the first

feature levels (5, 8 and 2) are simply aggregated

with weights corresponding to the similarity degrees

of the current situation and the three historical

situations. The levels of the rest of the bargaining

style features are determined similarly.

The only problem that needs to be solved to used

the case-based reasoning proposed above is to find

the weights describing the levels of similarity,

required for formula (2). In the next section we will

present how these weights may be derived from the

case base using simple statistical tool – a

correspondence analysis.

6 CALCULATING THE LEVELS

OF IMPORTANCE OF THE

DEMOGRAPHIC VARIABLES

In order to determine the levels of importance of

particular demographic variables we perform a

correspondence analysis (see Hill, 1974; Benzecri,

1992). Correspondence analysis is a variant of

principal component analysis aimed primarily at

categorical data. The method allows analyzing the

data table (a contingency table) and leads to a kind

of visualization of the rows and columns of this table

in the form of a map. Then it allows interpreting

these distances and relative positions of the points

from the map. The analysis that usually precede the

three-step correspondence analysis algorithm is the

chi-square test that allows to verify what is the

relation (association) between the variables that

comprise the table, if any. In our approach, by using

the correspondence analysis we will measure the

level of association of a demographic variable with

the bargaining style and treat this measure as a level

of importance of the demographic variable. In other

words, the higher the association degree of the

demographic variable with the conflict resolution

style the more important the demographic variable

is. From the given case base we will compute the

association degree using the Yule’s phi-coefficient

(Φ) that derives from the chi-squared test. The

computation procedures is as follows.

In order to determine the Φ value we start with

the computation of contingency table as shown in

Table 4.

Table 4: The contingency table.

Categories

of variable X

Categories of variable Y

Sum of

rows

... Y

... n

... ... ... ... ... ...

... n

Sum of

columns

... n

In our particular application context the variable

X corresponds to one demographic variable (age, for

instance) and the variable Y corresponds to one of

the variables defining the bargaining style (for

instance the competing feature). The values n

correspond to the frequencies of occurrence of cases

derived from the database, falling into the ith

category of the first variable and jth category of the

second variable. While comparing the variable age

(X) with the competing feature (Y) we need to

analyze the 6 by 12 matrix, since there are 6

predefined categories of age recorder by Inspire

system and there is 12 possible levels of each

bargaining feature defined by TKI. Similar matrices

we build for each combination of the demographic

characteristic and the bargaining style feature.

Based on each contingency table we compute the

value of chi-square metric:

∑∑

−

hjhj

)

(

(6)

where

n and

are the empirical and theoretical

frequencies of the contingency table, respectively.

The theoretical frequencies

are determined from

the following formula:

ICORES 2012 - 1st International Conference on Operations Research and Enterprise Systems

(7)

The chi-square metric will be used now for

determining the strength of relationship between the

analyzed variables. One of such a measures is Yule’s

phi-coefficient (there are also other similar

measures, such as the Pearson's Contingency

Coefficient, T-Czuprow's convergence coefficient or

V-Cramer's coefficient) computed as follows:

=Φ .

(8)

As mentioned before we will treat the value of Φ

coefficient as a level of importance of the

demographic variable in the case-based reasoning

approach. For our particular Inspire’s case base we

obtain the values of phi-coefficients for pairs of

demographic variables and conflict bargaining

variables as shown in Table 5.

The last column of Table 5 is an average of the

Yule’s phi-coefficients for bargaining style variables

(it is normalized as well). As a result of this

computation we obtain levels of importance (w

) of

the demographic variables that may be used now to

initiate the weights in the formula (2) and conduct

the case-based reasoning for identification of the

negotiation profile of any new negotiator that wants

to use the negotiation support system like the

NegoManage one.

7 EXPERIMENTAL

EVALUATION

To evaluate the proposed approach we split the case

base into two parts. Our case base consists of 228

cases. The first part of the case base is the basis for

the reasoning process. The second part of the case

base consists of 25 cases. We use the second part of

the case base for testing the reasoning mechanism.

For each of the 25 cases in the second part of the

case base we estimate the conflict resolution style

description and compare it with the actual conflict

resolution style description. The comparison is done

by computing the distance between two vectors of

five conflict resolution style variables. As said

before the first vector describes the actual conflict

resolution style given in the testing part of the case

base, and the second vector describes the predicted

conflict resolution style. We perform the reasoning

on the level of similarity equal to 0.75. Table 6

shows the results of the reasoning.

As we can see in Table 2 the distances between

the actual and predicted outcomes are lower than the

max and min outcomes what indicates on good

performance of the CBR prediction mechanism. The

empty rows indicate that in the case base there was

no case that would be similar enough (on the level of

0.75) to the current situation

8 CONCLUSIONS

In this paper we proposed a novel approach for

Table 5: The Phi coefficients for different pairs of demographic variables and conflict resolution style variables.

Competing Collaborating Compromising Accomodating Avoiding Average

Normilized

)

age 0.46 0.49 0.39 0.4 0.49 0.45 0.07

gender 0.22 0.15 0.23 0.23 0.17 0.2 0.03

c_reside 1.05 1.12 1.23 0.94 1 1.07 0.17

l_reside 0.54 0.44 0.5 0.42 0.33 0.45 0.07

c_born 1.4 1.7 1.31 1.27 1.22 1.38 0.23

english 0.5 0.52 0.48 0.51 0.53 0.51 0.08

course 0.35 0.45 0.34 0.28 0.29 0.34 0.06

ed_level 0.22 0.24 0.27 0.22 0.24 0.24 0.04

NSS 0.19 0.24 0.15 0.24 0.17 0.2 0.03

knowledge 0.5 0.44 0.48 0.46 0.47 0.47 0.08

p_before 0.18 0.25 0.14 0.14 0.21 0.18 0.03

ed_field 0.71 0.67 0.6 0.62 0.62 0.64 0.1

APPLYING CASE-BASED REASONING FOR IDENTIFYING THE NEGOTIATION PROFILE OF ELECTRONIC

NEGOTIATION SYSTEM USERS

identifying the negotiation profile, i.e. the bargaining

style of a negotiator. Instead of eliciting such a

profile by means of a psychometric test, like it is

usually done in many negotiation situations, in our

approach we decided to use the historical

information about negotiation processes stored in the

INSPIRE system case base and, based on the results

of some research on the behavioural aspects of

negotiations, to derive the bargaining profile of the

negotiator from the analysis of their personal

characteristics. The case base we operated with

contained the knowledge about the demographic

characteristics of a negotiator and its conflict

resolution style determined by means of TKI. Then,

based on the postulate that similar demographics of

the player yields similar conflict resolution style

(which is the fundamental to the case base reasoning

approach) we derive the estimation of a conflict

resolution style (a profile) of a new negotiator. To

support our case-based mechanism with all the data

required we have also implemented the elements of

the correspondence analysis, that allows finding the

links between the analyzed variables that are

described by means of the weak scales (in our

experiment some of the personal features had been

described by means of ordinal- or nominal-scale

variables).

We believe the approach we proposed is more

user-friendly to the negotiator than the classic TKI

test (or the similar ones), since it does not enforce

them to fill the tiresome and difficult psychometric

questionnaires, but - what we are aware of - it needs

to be verified and tested on the significantly big

sample of the negotiators. The future work will

Table 6: Experimental evaluation of the CBR mechanism.

Case

Actual conflict resolution style Predicted resolution style Comparison

Competing Collaborating Compromising Avoiding Accomodating Competing Collaborating Compromising Avoiding Accomodating distance maximal minimal

1 9 5 8 3 3 6 5 9 5 4 0.1166 0.4333 0.4

2 9 5 8 2 4

3 3 4 12 3 5 4 4 9 5 4 0.1666 0.4333 0.4

4 2 3 8 9 8 6 5 9 5 4 0.25 0.45 0.3166

5 5 4 12 2 5 5 5 9 5 4 0.1333 0.4333 0.4

6 6 7 6 7 4 8 4 9 3 3 0.2166 0.4166 0.25

7 10 5 9 3 3 4 5 10 4 5 0.1666 0.4166 0.25

8 2 8 8 3 9 5 5 7 6 7 0.2 0.4166 0.25

9 1 4 8 5 10 5 5 8 5 6 0.15 0.4 0.3

10 6 6 10 4 2 5 5 8 6 5 0.15 0.4166 0.4

11 1 3 8 9 7 5 5 8 6 5 0.1833 0.4 0.35

12 12 6 6 2 2 6 4 8 6 4 0.2833 0.3833 0.3333

13 6 2 8 7 5 6 5 8 6 4 0.0833 0.4 0.3333

14 11 4 10 2 1 8 6 7 4 4 0.2166 0.3833 0.2333

15 6 4 8 5 7 5 5 8 6 5 0.8333 0.4166 0.3166

16 11 5 7 2 3 5 5 9 5 5 0.2166 0.4333 0.3833

17 3 3 11 8 3 6 5 9 5 4 0.1833 0.4333 0.4

18 8 8 7 1 4 5 4 7 6 6 0.2333 0.3888 0.3666

19 2 6 8 5 7 5 5 8 6 5 0.1166 0.4 0.3666

20 5 3 9 3 8 5 5 8 6 5 0.15 0.4 0.3833

21 7 2 10 5 4 6 5 9 5 4 0.0833 0.4333 0.4

22 3 6 7 6 8 4 7 7 7 5 0.1 0.4166 0.1

23 7 3 12 4 2

24 12 5 5 5 3

25 2 7 9 3 7 7 6 9 4 2 0.2 0.3833 0.25

ICORES 2012 - 1st International Conference on Operations Research and Enterprise Systems

focus then on the implementing our approach in the

NegoManage web-based core simultaneously with

the electronic TK test, which will allow to verify

whether the profiling mechanism that we built based

on the estimates from the case-based reasoning and

the correspondence analysis, is reliable enough and

may be used for eliciting the true negotiation profile

(i.e. the profile that is concordant with the results of

the TKI) of the new electronic negotiation system

user. After implementing our approach we also plan

to verify the results on the alternative psychological

research on negotiation (see Elfenbain et al., 2008),

which may modify the way we define the situation

in our case-based approach. It may appear that some

other psychological characteristic may (or should)

also be included in our analysis (such as the attitude

towards the problem, partner and process) that

would lead to the better estimation of the

negotiator’s profile.

Finally, we are aware of other alternative

methods that may be used in negotiators’ profiling,

that base on the classical statistical

clustering/classification approaches or apply AI

solutions like neural networks, and which we

rejected in our preliminary selection since they

usually requires metric data. Thus our future work

will also focus on analyzing the possible extensions

and modifications of these rejected methods that

could be used alternatively to our method and then

on comparing the clustering results they would lead

to with the results of our model.

ACKNOWLEDGEMENTS

We thank Gregory Kersten and the InterNeg

Research Centre Team for supporting us with the

Inspire database. This research is supported by the

grant of Polish Ministry of Science and Higher

Education (N N111 362337).

REFERENCES

Adair, W. L. and Brett, J. M. (2004). Culture and

negotiation processes. In Gelfand, M. J. and Brett J.

M. (Eds.), The Handbook of Negotiation and Culture

(pp. 158-176). Stanford: Stanford Business Books.

Aamodt, A. and Plaza, E. (1994). Case-based reasoning:

Foundational issues, methodological variations, and

system approaches. AI Communications, 7:, 39-59.

Benzecri, J. P. (1992). Correspondence analysis

handbook, New York: Marcel Dekker.

Blake, R. R. and Mouton, J. S. (1964). The managerial

grid. Houston: Gulf Publications.

Briggs, I. and Myers, P. B. (1980). Gifts Differing:

Understanding Personality Type. Mountain View:

Davies-Black Publishing.

Brzostowski, J. and Wachowicz, T. (2009). Conceptual

Model of eNS For Supporting Preference Elicitation

and Counterpart Analysis. In Kilgour, D.M. and Wang

Q. (Eds.), Proceedings of GDN 2009: An International

Conference on Group Decision and Negotiation (pp.

182-186). Waterloo: Wilfried Laurier University.

Brzostowski, J. and Wachowicz, T. (2010). Building

personality profile of negotiator for electronic

negotiations. In Trzaskalik, T. and Wachowicz, T.

(Eds.), Multiple Criteria Decision Making '09 (pp. 31-

46). Katowice: The Publisher of The University of

Economics in Katowice.

Elfenbein, H. A., Curhan, J. R., Eisenkraft, N., Shirako, A.

and Baccaro, L. (2008). Are some negotiators better

than others? Individual differences in bargaining

outcomes. Journal of Research in Personality, 42,

1463-1475.

Gilboa, I. and Schmeidler, D. (1995). Case-based decision

theory. The Quarterly Journal of Economics, 110(3),

605-639.

Herrmann, G. M. (2004). Haggling Spoken Here: Gender,

Class, and Style in US Garage Sale Bargaining.

Journal of Popular Culture, 38(1), 55-81.

Hill, M. O. (1974). Correspondence analysis: a neglected

multivariate method. Applied Statistics, 23, 340-354.

Howison, J. (2003). An Introduction to the Literature on

Online Reputation Systems for the MMAPPS project.

Retrieved July 27, 2011, from http://james.howison.

name/pubs/RepLitIntro.pdf

Jehn, K. A., Chadwick, C. and Thatcher, S. (1997). To

agree or not to agree: The effects of value congruence,

individual demographic dissimilarity, and conflict on

workgroup outcomes, International Journal of

Conflict Management, 8(4): 287-305.

Kersten, G. E. and Noronha, S. J. (1999). WWW-Based

Negotiation Support: Design, Implementation And

Use. Decision Support Systems, 25, 135-154.

Kersten, G. E., Koeszegi, S. and Vetschera, R. (2003). The

effects of culture in computer-mediated negotiations.

Journal of Information Technology Theory and

Application, 5(2), 1-28.

Kilmann, R. and Thomas, K. W. (1983). The Thomas-

Kilmann Conflict Mode Instrument.

Cleveland: The

Organizational Development Institute.

Kray, L. J. and Thompson, L. (2005). Gender stereotypes

and negotiation performance: An examination of

theory and research. Research in Organizational

Behavior, 26, 103-182.

Kraybill, R. (2005). Style Matters: The Kraybill Conflict

Style Inventory. Harrisonburg: Riverhouse ePress.

Leake, D. B. (1996). Case-Based Reasoning: Experiences,

Lessons & Future Directions. Menlo Park: AAAI

Press/MIT Press.

Mershon, B. and Gorsuch, R. L. (1988). Number of factors

in the personality sphere: does increase in factors

increase predictability of real-life criteria?. Journal of

Personality and Social Psychology, 55, 675–680

APPLYING CASE-BASED REASONING FOR IDENTIFYING THE NEGOTIATION PROFILE OF ELECTRONIC

NEGOTIATION SYSTEM USERS

Paradis, N., Gettinger, J., Lai, H., Surboeck, M. and

Wachowicz, T. (2010). E-Negotiations via Inspire 2.0:

The System, Users, Management and Projects. In: de

Vreede, G.J. (Ed.), Group Decision and Negotiations

2010. Proceedings (pp. 155-159). Omaha: The Center

for Collaboration Science, University of Nebraska at

Omaha.

Patton, C. and Balakrishnan, P. V. (2010). The impact of

expectation of future negotiation interaction on

bargaining processes and outcomes. Journal of

Business Research, 63(8), 809-816.

Paunonen, S. V. and Ashton, M. S. (2001). Big Five

factors and facets and the prediction of behavior.

Journal of Personality & Social Psychology, 81, 524-

539

Searle, J. R. (1969). Speech Acts: An Essay in the

Philosophy of Language. Cambridge: Cambridge

University Press.

Shell, G. R. (2001). Bargaining Styles and Negotiation:

The Thomas-Kilmann Conflict Mode Instrument in

Negotiation Training. Negotiation Journal, 17(2), 155-

174.

Sternberg, R. J. and Dobson, D. M. (1987). Resolving

interpersonal conflicts: An analysis of stylistic

consistency. Journal of Personality and Social

Psychology, 52, 794-812.

Stiles, W. B. (1992). Describing talk: a taxonomy of

verbal response modes. SAGE Publications.

Thompson, L. (1990). Negotiation behaviour and

outcomes: Empirical evidence and theoretical issues.

Psychological Bulletin, 108, 515-532.

ICORES 2012 - 1st International Conference on Operations Research and Enterprise Systems