Content uploaded by Thyago C. Nepomuceno
Author content
All content in this area was uploaded by Thyago C. Nepomuceno on Jan 05, 2019
Content may be subject to copyright.
Kybernetes
Modeling sequential bargains and personalities in democratic deliberation
systems: A NSS for social-efficient agreements
Thyago Celso Cavalcante Nepomuceno, Jadielson Alves de Moura, Ana Paula Cabral Seixas Costa,
Article information:
To cite this document:
Thyago Celso Cavalcante Nepomuceno, Jadielson Alves de Moura, Ana Paula Cabral Seixas Costa,
(2018) "Modeling sequential bargains and personalities in democratic deliberation systems: A NSS
for social-efficient agreements", Kybernetes, Vol. 47 Issue: 10, pp.1906-1923, https://doi.org/10.1108/
K-03-2018-0144
Permanent link to this document:
https://doi.org/10.1108/K-03-2018-0144
Downloaded on: 05 January 2019, At: 14:57 (PT)
References: this document contains references to 74 other documents.
To copy this document: permissions@emeraldinsight.com
The fulltext of this document has been downloaded 50 times since 2018*
Users who downloaded this article also downloaded:
(2018),"Developing a measurement instrument of knowledge management implementation in the
Iranian oil industry", Kybernetes, Vol. 47 Iss 10 pp. 1874-1905 <a href="https://doi.org/10.1108/
K-01-2018-0006">https://doi.org/10.1108/K-01-2018-0006</a>
(2018),"The rise of digital intelligence: challenges for public relations education and practices",
Kybernetes, Vol. 47 Iss 10 pp. 1924-1940 <a href="https://doi.org/10.1108/K-03-2018-0145">https://
doi.org/10.1108/K-03-2018-0145</a>
Access to this document was granted through an Emerald subscription provided by emerald-
srm:478307 []
For Authors
If you would like to write for this, or any other Emerald publication, then please use our Emerald
for Authors service information about how to choose which publication to write for and submission
guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information.
About Emerald www.emeraldinsight.com
Emerald is a global publisher linking research and practice to the benefit of society. The company
manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as
well as providing an extensive range of online products and additional customer resources and
services.
Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the
Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for
digital archive preservation.
*Related content and download information correct at time of download.
Downloaded by UFPE At 14:57 05 January 2019 (PT)
Modeling sequential bargains and
personalities in democratic
deliberation systems
A NSS for social-efficient agreements
Thyago Celso Cavalcante Nepomuceno
Department of Production Engineering, Universidade Federal de Pernambuco,
Recife, Brazil and Department of Computer, Control and Management
Engineering Antonio Ruberti (DIAG), Sapienza University of Rome,
Rome, Italy, and
Jadielson Alves de Moura and Ana Paula Cabral Seixas Costa
Department of Production Engineering, Universidade Federal de Pernambuco,
Recife, Brazil
Abstract
Purpose –This paper aims to introduce a negotiation support system (NSS) with a theoretical modeling
that considers the aspects of human personality and negotiator’s behavior to assist the decision-making of
public managers and stakeholders in democratic bargaining processesand support social-efficient outcomes.
Design/methodology/approach –A game theoretical modeling of public participatory negotiations
characterized by complete and perfect information is explored with the inclusion of personality aspects and
negotiation styles. The importance of the negotiation knowledge disclosure in the sequential bargains of
participative budgeting is highlighted by an experiment with 162 state-owned companies’managers and
graduate students to present the contribution of the system’s applicability.
Findings –A considerable number of Pareto-efficient deliberation agreements are obtained with few
interactions when the negotiation strategies and the personality aspects of opponents and stakeholders are
freely available (a symmetry in the public negotiation knowledge). In addition to the set of Pareto-efficient
agreements, those with the best social outcome (i.e. that maximize the group satisfaction despite individual
losses) are observed when the informational tool for personality and negotiation style inference is enabled.
Originality/value –Many scholars argue for Pareto-efficient allocation instead of equal divisions of
resources within participative democracies and public governance. This work provides a new system with an
empirical application and theoretical modeling which may support those arguments based on the nonverbal
negotiation aspects.
Keywords Decision making, Game theory, Negotiation support systems, Participatory democracy,
Personality and cognition
Paper type Research paper
1. Introduction
Participatory democracies emphasize the deliberative decisions on the involvement of
constituents. This form of democracy provides better decision-making processes by
delegating responsibilities of public settlements to local people with greater understanding
of the present reality than rulers and gives space for a greater ownership of state-sponsored
operations, as they are co-authors in the creation of the public policy (Bane, 2010;Cohen and
K
47,10
1906
Kybernetes
Vol. 47 No. 10, 2018
pp. 1906-1923
© Emerald Publishing Limited
0368-492X
DOI 10.1108/K-03-2018-0144
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0368-492X.htm
Downloaded by UFPE At 14:57 05 January 2019 (PT)
Fung, 2004;Fung and Wright, 2003). Bula and Espejo (2012) argues for a cybernetic
understanding of the organizational structures and governance to let people the chance of
represent their desires, reduce power imbalances and influence their destinies. A desirable
democratic system to produce such outcome, under the arguments of Espejo (2000), requires
the self-construction process where stakeholders are complete aware of their reality,
purpose, personal desires, interests and collective value to steer interaction toward better
social agreements.
Such nonverbal negotiation aspects root on the formation of constituents’profile and
personality, which may not be easily accessed to design organizational policies and trace
external boundaries with their environment. Especially considering negotiations with public
interest such as government acquisitions, public procurement, outsourcing and bidding
processes, the traditional tools for conflict management may undermine social gains by not
considering those aspects for approaching deliberations with the public administration.
Participative budgeting is one form of these public negotiations that requires a deep
knowledge over the environment and nonverbal negotiation aspects to derive efficient social
outcomes. Brownell (1982) defines participative (or participatory) budgeting as an
accountability mechanism in which ordinary individuals are involved in and have influence
on how part of a public budget, that directly affects their lives, must be allocated
(Mahlendorf et al., 2015). According to Célérier and Cuenca Botey (2015), this mechanism can
produce an emancipatory perspective and substantial social change by eradicating
corruption and improve the life conditions of the most needed (see similar constructs in
Sintomer et al.,2012).
Participatory budgeting practices were originally implemented in the city of Porto Alegre,
Brazil, and served as a pioneer model for many Latin America cities, such as Rosário
(Argentina), Recife (Brazil), Montevideo (Uruguay), Belo Horizonte and Atibaia (Brazil), and
expanded worldwide in cities, such as Chicago, NY (US), Toronto (Canada), Barcelona (Spain),
Paris and Saint-Denis (France). According to Sintomer et al. (2010) and Gomez et al. (2016),more
than 1,500 municipalities across the globe have forms of participative deliberations systems
based on Porto Alegre’s model. This participatory decision-making on public resources has
presented positive implications to outstanding difficulties particular to Latin–American social
and organizational contexts, such as living conditions and infant mortality (Gonçalves, 2014),
poverty, education and access to sanitation (Campbell, et al. 2017) and energy justice
(Capaccioli, et al. 2017;Jenkins, 2018). As the popular participation in the definition of
government policies is often characterized by public discussions and negotiations, the mutual
understanding of goals and desires is critical to achieve good social prospects.
From the assumption that democracy is the right of all citizens to participate in deciding
their present and future (Bula and Espejo, 2011), some negotiation support systems (NSSs)
have been seeking to devote technological manners to promote conflict resolution, develop
and improve methodologies to facilitate the participative budget management (Benyoucef
and Verrons, 2008;Gomez et al., 2013). By definition, NSSs compose a special category of
group support systems designed to support the activities of two or more negotiating parties
to reach an agreement via computerized systems that integrate information and
communication technologies through electronic media (Bichler et al.,2003;Delaney et al.,
1997;Lee et al.,2007). These NSSs, beside supporting the execution of negotiations, can
guide online activities (Kersten, 2004), facilitate communication, structure and organize
processes’information related to the negotiation (Gettinger et al.,2012), being characterized
by the ability to enable people from different placesand time zones to communicate by using
computational resources (Kersten and Noronha, 1999).
Democratic
deliberation
systems
1907
Downloaded by UFPE At 14:57 05 January 2019 (PT)
Besides supporting traditional online negotiation, NSSs have a wide range of
applications among e-democracy (French, 2007), group decision (Nakaoka et al.,2009;
Tavana and Kennedy, 2006) and budget management (Wolfe and Murthy, 2005). Each type
of application may vary with regard negotiation goals; when they focus on a dispute
compromise, i.e. “win-lose”negotiations, they are identified as distributive negotiations
(Weigand et al.,2003). Otherwise, when the negotiations seek to create a solution that
satisfies all negotiators, i.e. “win-win”negotiations, they are identified as integrative
negotiations. Although recognizing the benefits of using the NSS to secure the functional
success of democratic deliberations, to the best of our knowledge, no further research have
explored the influences of nonverbal characteristics to mitigate the lack of face-to-face
interaction and help to achieve a Pareto-efficient outcome, defined as the allocation where it
is impossible to make someone better off without making someone else worse off (Mock,
2011). This concept has an extreme importance in the discussion of system thinking for
political governance and people interactions, as Pareto-efficient results are often preferable
to equal measures of social outcome (Barr, 2012). The budget game (present in the third
section of this work) has settings that exemplify this assertion.
Nonverbal information about personality traits and negotiation style can help rulers and
constituents to adjust their tactics within negotiations of public interest, according to their self-
personal information and a mutual understanding of other parties’personality and tactics
(Gilkey and Greenhalgh, 1986). Because the negotiators are the most complex and flexible part
of the communication system (DeRosa et al., 2004), the information on their preferences and
negotiation behavior tends to improve the communication process, as well as the outcome (Yiu
and Lee, 2011). Here, we offer the development of a Web NSS that besides incorporating
traditional tools of a NSS, also integrates personality and negotiation information to improve
the communication process during the negotiation to obtain better social outcomes in
democratic deliberation systems, more precisely, in participative budgeting systems.
This work contributes to the discussion of negotiations within participatory democracy
deliberations initially through the conceptualization of sequential bargains under complete
and perfect information, modeled to include the personality traits and negotiation style of
constituents. Though these aspects combining emotions and strategies are crucial to
determine the outcome of a negotiation process, to the best of our knowledge, they have not
been modeled in a game theoretical approach, especially considering the context of
participatory democracies. As main result from the methodological modeling, it will be
argued that when the information on the personality and negotiation characteristics of the
participants are available, Pareto-efficient agreements may be obtained from the public
disputes with few interactions among the parties. The second contribution is the
development of a Web-based NSS following the traditional NSS approach (Lim, 2000;Lee
et al., 2007) with conceptual models to help the implementation and validation of those
aspects of the negotiation knowledge. By the end of this analysis, we want to present an
experiment involving 162 managers of state-owned companies and graduate students of
Latin America countries to demonstrate the system contribution to the negotiation process
and to the efficient (participative) allocation on public budgeting.
2. Methodology
This section is devoted to the theoretical understanding of the structure observed in
sequential bargain negotiations with complete and perfect information under limited and
complete negotiation knowledge, in special, devoted to bargains of public budgeting in
participative democracies, and to the methodological proposal of a NSS which may facilitate
the bargain process by reaching a Pareto-efficient solution with few interactions. The
K
47,10
1908
Downloaded by UFPE At 14:57 05 January 2019 (PT)
following model in this section will consider two decision-makers and a government
disputing a specific budget which the outcome depends on a set of rational assumptions that
is expected from the social behavior. The concept of rationality is defined by the appropriate
response to the elicited event, which is relative to what different individuals consider as a
normal behavior (Yolles, 2006). According to Hebert Simon’s theory of bounded rationality
(Simon, 1947,1955,1956), the decision-making in real (not-simulated) environments is
characterized by the difficulty to anticipate prospects of actions, limited knowledge on the
opponents’strategies and human behavior, incomplete information and human constraints
on computational capacities and to access the information available. In addition, the
individual operates in a social environment which affects his/her decision-making and the
results can hardly be prescript (Cristofaro, 2017).
Those concepts found support in the economics and cognitive psychology of the prospect
theory (Tversky and Kahneman, 1973) in the perception of risk (Slovic, 1987) and by
evolutionary game theorists (Aumann, 1997;Smith, 1982) which assumes that players do not
predict the consequences of their actions accurately. When it concerns the personality traits and
negotiation style within bargaining processes of public deliberation systems, such aspects in
the theory of bounded rationality have not be given the appropriate attention. Therefore, the
game theory of sequential bargain in this work is characterized by complete and perfect
information on the payoffs, but adapted to three instances of negotiation knowledge:
asymmetry in the negotiation knowledge where the player has private information of his/her
opponent’s personality and negotiation style, asymmetry in the negotiation knowledge where
the opponent has private information of the considered player’s personality and negotiation
style and mutual negotiation knowledge where both has access to personality traits and
negotiation style of his/her counterpart. In this structure, the mutual knowledge assumes
considerable advantage for the social outcome.ANSSisproposedattheendofthissectionto
include such mutual knowledge information to support more precise bargain decisions.
2.1 Sequential bargains with asymmetric and mutual negotiation knowledge
Assume the following negotiation where two community agents (players) bargain for a certain
amount of money which must be administrated in their infrastructure. This sort of negotiation
is the heart of the participatory democracy where ordinary individuals decide how to allocate
public budget in their community needs. In some extent, similar characteristic of this process
can be observed within the structure of classical economic games in the literature, such as the
Gibbons (1992) descriptions, Rubinstein (1982) and Sobel and Takahashi (1983) sequential
bargaining models and Von Stackelberg (1934) model of duopoly. Some recent game
approaches have similar characteristics with the present modeling (Brangewitz and Gamp,
2013;Bolton and Karagözo
glu, 2016;Geraskin, 2017;Nepomuceno and Costa, 2014;Santos
et al.,2017;Wu and Wang, 2017) The negotiation will be characterized as a dynamic
negotiation of complete and perfect information, which means that not only each negotiator has
the complete information on the payoff function of his/her counterpart, but also the entire
history behind the negotiation so far (strategies adopted, interactions, moves and choices) is of
common knowledge (Gibbons, 1992).Thetimingofthebargaingoesasfollows:
T
0
. The nature (in this case represented by the government) shares a certain amount
of budget “M”with the interest players “A”and “B”by suggesting some initial (un)
proportional allocation. Be (a’,b’) the shares of the budget belonging to A, B.
T
1
. Community A observes the initial proposal and chooses to either keep it or reject
it with a new offer (a’’,b’’) from the feasible set F(a’’,b’’)#M. If both communities
accept this proposal, the negotiation ends with the payoff (a’’,b’’).
Democratic
deliberation
systems
1909
Downloaded by UFPE At 14:57 05 January 2019 (PT)
T
1
. Community B observes the initial proposal and chooses to either keep it or reject
it with a new offer (a’’’,b’’’) from the feasible set F(a’’’,b’’’)#M. If both communities
accept this proposal, the negotiation ends with the payoff (a’’’,b’’’).
T
2
. If exists, the counterpart of the proposer in T1, say “A”, observes the second
offer from “B”and chooses to either keep it or reject it with a new offer (a’’’’,b’’’’)
from the feasible set F(a’’’’,b’’’’)#M. If community B accepts the proposal, the
negotiation ends with the payoff (a’’’’,b’’’’). Otherwise, B makes a new offer and the
game continues indefinitely until an agreement is reached.
Note that (T
1
) may occur simultaneously (any player may choose the sequence of the
game at first). Assume the existence of an average offer O
i
e
F(a, b) #Minwhich
players (i= 1, 2) are leaned to approximate, e.g. an equal division in the monetary
resource, and that changes in this value are influenced by their negotiation style “
h
”
and personality trait “ȹ”parameters. Let us denote the marginal change in the proposal
O
i
by
g
i
=O
i
(
h
,ȹ), and
g
0ithe estimative made by the player j (j = 1, 2) in regard to
what he believes to be the real parameter of marginal change
g
for the player i,sothat
a=
g
A
O
A
and b =
g
B
O
B
. In addition, in the real-world transactions it is plausible to
assume that the Oichanges with variable returns to scale, i.e.
g
increasing and
decreasing are not necessarily as linear function of parameters
h
,and
w
.Letw>1and
k>1 denote the exponents of this marginal change for A and B, respectively. If A
rejects the initial proposal, the decision is summarized to maximize their utility by a
choice of a(and consequently b) such that:
max uA
0#a#M
a;b
ðÞ
¼max
g
w
AOA
0#a#M
¼MÔB(1)
And similarly:
max uB
0#b#M
b;a
ðÞ
¼max
g
k
BOB
0#b#M
¼MÔA(2)
As the offers Ô
B
and Ô
A
are unknown parameters for Aand B, respectively, they become
estimative of the real O
B
and O
A
parameters based on the perception of their opponents’
personality and negotiation style, and equations (1) and (2) turns to:
max uA
0#a#M
a;b
ðÞ
¼max
g
w
AOA
0#a#M
¼M
g
0k
BOB(3)
and
max uB
0#b#M
b;a
ðÞ
¼max
g
k
BOB
0#b#M
¼M
g
0w
AOA(4)
Bknows the payoff function of Adepends on B’s decision, as much as Aknows the payoff
function of Bdepends on A’s. As this negotiation is characterized by a dynamic game of
complete and perfect information, substituting (3) in (4), Bfaces the following decision-
making:
K
47,10
1910
Downloaded by UFPE At 14:57 05 January 2019 (PT)
max uB
0#b#M
b;a
ðÞ
¼max
g
k
BOB
0#b#M
¼M
g
0w
A
M
g
0k
BOB
g
w
A
!
¼
g
k
BOB
¼M
g
0w
A
g
w
A
!
Mþ
g
0w
A
g
w
A
!
g
0k
BOB(5)
Equation (5) states that the rational offer which community Bmust choose in this
negotiation setting depends on more unknown parameters than they would liketo have. The
decision is laid upon his personality and negotiation profile (
g
k
BÞ;the personality and
negotiation profile of his opponent (
g
w
AÞ, what Bbelieves to be his opponent negotiation and
personality profile (
g
0w
AÞ, and what Bbelieves to be his negotiation and personality profile in
the eyes of his opponent (
g
0k
BÞ. In real-world negotiations, characterized by complete and
perfect information, assuming rational decision-makers, it takes time and many interactions
for each negotiator to estimate those parameters, and sometime the agreement is far from a
social optimum. As Ahas similar payoff function, the same dilemma is applied for their
decision making as well. When the information which depends on the marginal change
g
is
disclosed, and considering Bas the agent of evaluation, three situations can be delegated
from the economic equation (5).
First scenario: Asymmetric negotiation knowledge where B has private information on the
negotiation style “
h
”and personality trait “ȹ”parameters of their opponent (
g
0w
A¼
g
w
A):
maxuB
0#b#M
b;a
ðÞ
¼
g
k
BOB¼M
g
0w
A
g
w
A
!
Mþ
g
0w
A
g
w
A
!
g
0k
BOB
¼M
g
w
A
g
w
A
!
Mþ
g
w
A
g
w
A
!
g
0k
BOB¼MMþ
g
0k
BOB
;
g
k
BOB¼
g
0k
BOB
The decision of Bis summarized to choose a marginal change in his proposal such that:
g
k
B¼
g
0k
B(6)
When Bhas complete and perfect information of the negotiation process, and knows his
opponent’s profile, i.e. personality style, negotiation bias, trends, emotions and how he/she is
to behave given the proper incentives, Bmay anticipate forward choices and lead the
negotiation to a point where Abelieves is B’s marginal change (optimal) offer. Ceteris
paribus, the same solution is verified for A.
Second scenario: Asymmetric negotiation knowledge where A has private information
on the negotiation style “
h
”and personality trait “ȹ”parameters of their opponent
(
g
0k
B¼
g
k
B):
maxuB
0#b#M
b;a
ðÞ
¼
g
k
BOB¼M
g
0w
A
g
w
A
!
Mþ
g
0w
A
g
w
A
!
g
0k
BOB
The first order condition for this particular problem is:
Democratic
deliberation
systems
1911
Downloaded by UFPE At 14:57 05 January 2019 (PT)
@u
@
g
k
B
¼k
g
0w
A
g
w
A
!
g
k1
BOBk
g
k1
BOB¼0 Dividing both terms by kOBresults
:k
g
0w
A
g
w
A
!
g
k1
BOBk
g
k1
BOB¼
g
0w
A
g
w
A
!
g
k1
B
g
k1
B
;
g
k1
B
g
0w
g
w1
!
¼0 (7)
When Ahas the private knowledge on the negotiation behavior and personality of B,Amay
lead the negotiation to a point where the optimal choice of Beither 0 (zero) with
g
k1
B=0,in
which case Breceives no share of the disputed money M,orleadBto attempt to estimate the
behavior of A, represented by what Bbelieves to be the marginal changes in the offer as
function of Apersonality and negotiation style
g
0w
A, as close as possible to the real
parameter
g
w
A, which may result
g
0w
A
g
w
A
1
’
g
w
A
g
w
A
1¼11¼0.Ceteris paribus, the
same solution is verified for A. As every two-part negotiation exhibits a counterpart
representing the asymmetric knowledge, the optimal solution for both players is limited to
estimate unknown parameters such as the economic equation (5), which despite demanding
time, may not guarantee equilibrium with a Pareto-efficient agreement. Another additional
concern is the possibility of players misrepresenting their desires, which may lead the
negotiation to even greater expected time to closure and small expected payoffs.
Third Scenario: Mutual Negotiation Knowledge where A and B have prior knowledge on
the negotiation style “
h
”and personality trait “ȹ”parameters of their opponent (
g
0w
A¼
g
w
A
and
g
0k
B¼
g
k
B).
Assuming both players has mutual information in regard to the opponents’personality
and negotiation style, and assuming both players knows their opponent has the same
information with regards their own profile, none will have enough incentives todeviate from
their optimal offer and the possibility of misrepresentation is minimized by the mutual
knowledge of behaviors (i.e. mutual knowledge that the other part would be deviating from
his/her optimal):
max uB
0#b#M
b;a
ðÞ
¼
g
k
BOB¼M
g
0w
A
g
w
A
!
Mþ
g
0w
A
g
w
A
!
g
0k
BOB
¼M
g
w
A
g
w
A
!
Mþ
g
w
A
g
w
A
!
g
*k
BOB¼MMþ
g
*k
BOB
;
g
k
BOB¼
g
*k
BOB
Notice that
g
*k
BOBis no longer what Abelieves to be theoptimal offer forB(
g
0k
BOB), instead
this is what Aknows is the optimal offer for B. The decision of Bis summarized to choose a
marginal change in his proposal such that they would not deviate from the optimal:
g
k
B¼
g
*k
B(8)
Which is assumed to produce Pareto’s social efficient outcome with few interactions in the
negotiation process.
K
47,10
1912
Downloaded by UFPE At 14:57 05 January 2019 (PT)
2.2 The negplace system
The NegPlace System is a Web-based NSS developed to integrate the personality and
negotiation style of users and guide the negotiation process by using a web environment.
This NSS offers technological resources for an enjoyableexperience in the online negotiation
process. The program is available for all operating systems and devices connected to the
internet with a web browser. Such characteristic makes the NegPlace a portable and scalable
system, which enable a complete negotiation environment anytime and anywhere.
Some components have been developed to facilitate the communication process, among
which are the tools for individual profile, problem manager, negotiation manager, offer
sender and informational tool. Most of these components are found in traditional NSS
(Kersten and Lo, 2003;Kersten and Noronha, 1999;Schoop et al., 2003;Tavana and Kennedy,
2006), with exception the informational tool that have been designed for the negotiation
knowledge inference. This component is responsible to capture, process and exhibit the
information of the personality traits and negotiation styles of participants during the
negotiation. Users are invited to respond two questionnaires, one with 44 and the other
containing 30 items, to elicitate the personality and negotiation dimensions.
Some studies have used the functionalities of NegPlace to approach social or
organizational problems (Moura and Cabral, 2014;Moura and Costa,2015, 2018)or
integrating these negotiation problems with neuroscience mechanisms (Moura et al.,2016).
Nevertheless, any type of negotiation can be conducted in the platform because of its
flexibility and adaptability to support from single-pair to group decision negotiation. Two
psychological models have been used for informational tool to capture and process the
personality traits and negotiation styles information. The Big Five (BF) (Goldberg, 1990)
model has the function of capturing the personality traits by using a survey with 44 items
which classifies the user in five dimensions of personality (Goldberg, 1993). Each dimension
represents a set of characteristics from the respondent’s personality in terms of extraversion,
agreeableness, conscientiousness, neuroticism and openness (John and Srivastava, 1999).
Negotiation studies have recognized the usefulness of the BF model in their negotiation
process in attempting to find relationships between its dimensions and the negotiation
features (Antonioni, 1998;Barry and Friedman, 1998;Curhan et al.,2006;Wood and Bell,
2008).
The second psychological model traces the negotiation styles, known as Thomas–
Kilmann Conflict Mode Instrument (TKI) (Thomas and Kilmann, 1974). Applied as conflict
management instrument, the TKI can easily be expanded to negotiation context, since
negotiation are deemed as means of resolving conflict situations (Bazerman et al.,2000).
This model has two basic conflict dimensions based on assertiveness and cooperativeness
levels, which can be divided in five conflict modes: competing, collaborating, compromising,
accommodating and avoiding. The pooling in the conflict modes characterizes conflict
management or negotiation style of a specific person based on a questionnaire with 30 items
(Consulting Psychologies Press, 2002). The TKI has been widely approached in negotiation
studies, either online or face-to-face negotiations, mainly with the purpose to shed a light on
how conflict behavior adopted by negotiators can influences the negotiation process and
results (Ames, 2008;Nelson et al., 2015,2016;Shell, 2001).
The informational tool is present in the pre-negotiation and negotiation phases. A
module with an informational screen presents information on the personality traits and
negotiation styles from the opponents and themselves in textual and graphic ways
(Figure 1). All relevant information provided by negotiators is summarized in a short
description with graphs related to the dimension of the personality traits and a spider chart
with the dimensions of the negotiation styles. Each chart axis represents a dimension, being
Democratic
deliberation
systems
1913
Downloaded by UFPE At 14:57 05 January 2019 (PT)
its level or intensity measured in a ten-point scale. The more distant from the center, the
greater will be the level or intensity. At the top of informational tool screen, some personality
recommendations are present as an overview on the five dimensions of the personality
traits. According to the BF model, each dimension has specific characteristics, which
depends on measured levels.
3. The participatory budgeting game
The experiment consists a dynamic negotiation of complete and perfect information in
which three parts, the public administration representative (P), the neighborhood A
community leader (A) and neighborhood B community leader (B) bargain a municipal
budget for public works. In all, 162 individuals took part the experiment composing a total
of 54 negotiations: 95 males (58.6 per cent) and 67 females (41.4 per cent). All from Latin
American countries (Brazil mostly, Venezuela, Colombia and Ecuador), ages ranging from
21 to 46 years old (mean age approximately 28 years old), composed by undergraduate
students of business, information technology and management engineering, some graduate
students of industrial and management engineering, managers of financial firms, water and
electricity distribution companies, bank employees, sworn officers, managers of public
safety secretaries and police stations, water and sewage companies and industrial
supervisors.
Initially, the participants were randomly divided into two groups of negotiation: one
group enabled for informational tool usage (i.e. access on the opponent’s negotiation profile
and personality traits) and the other group with informational tool disabled. In the
negotiation case, there is a budget limited to R$1,500,000 (Brazilian reais) and a state law
enforces the city administration to invest no less than 80 per cent of the amount in projects
according to the neighborhood’s needs. Each neighborhood leader has information about the
other’s projects and cost and a sense of their priorities. If there is no agreement, the amount
will be used for next year’s budget and the negotiation interaction goes from a distributive
Figure 1.
Informational tool
screen with
personality traits and
negotiation styles
K
47,10
1914
Downloaded by UFPE At 14:57 05 January 2019 (PT)
to integrative relation among the parts. The public works each neighborhood requires, their
cost and priority are presented in Table I.
It is essential for the public administration to meet high and very high priorities,
rather than higher values first, and it is assumed that the public administration slightly
prefer to save financial resources than to invest in medium or low priority projects.
Figure 2 presents the timing of the negotiation as an extensive form game: first, the
public administration representative chooses an xp, offer to community A and yp offer
to community B from the feasible set 1,200,000 <F(x,y,z)#1,500,000; both the leaders
of A and B observes the public administration offer and decide whether to accept or
reject the proposal –if both accepts, the negotiation ends with payoffs (xp, yp, zp) to
community A, B and public administration, respectively; if one part accepts, e.g.
community A, and the other rejects, the rejecter (community B) is invited to propose a
better offer for each part, which might result (xb, yb, zb) if both the public
administration and the community A accepts; if no one accepts the public administrator
offer, both are invited to propose offers simultaneously, and the negotiation goes on
until a three part agreement is signed.
The public administration primarily aims to maximize the utilities of both the voter
from community A (u
A
(x,y,z)) and B (u
B
(x,y,z)) and save some share of the budget “z”
whenever possible. The payoff function for the public administration is defined as a
decision:
Table I.
The budget game:
projects, cost and
priorities for each
neighborhood
Neighborhood Project Cost Priority
A 1 Community daycare R$500,000 Very high
2 Road paving R$250,000 High
3 Fairground square R$250,000 Medium
4 Community city gym R$150,000 Low
B 5 Health center R$550,000 Very high
6 Road paving R$350,000 High
7 Multi-sports court R$150,000 Medium
8 Community library R$101,000 Low
Figure 2.
Extensive form
budgeting game
under complete
information
A P B
reject accept (xp, yp, zp) accept reject
B P A
reject accept (xa, ya, za) accept accept (xb, yb, zb) accept reject
P A B P
… … … …
Democratic
deliberation
systems
1915
Downloaded by UFPE At 14:57 05 January 2019 (PT)
max uP
0#xþy#M
x;y;z
ðÞ
¼max uA
0#x#M
x;y;z
ðÞ
þmax uB
0#y#M
x;y;z
ðÞ
þ
g
s
Pz(9)
where:
max uA
0#x#M
x;y;z
ðÞ
¼px
ðÞ
max
g
w
Ax
0#x#M
¼1500000
g
0k
By
g
0s
Pz(10)
and
max uB
0#y#M
x;y;z
ðÞ
¼py
ðÞ
max
g
k
By
0#y#M
¼1500000
g
0w
Ax
g
00s
Pz(11)
The functions p(x) and p(y) represent constant weight to consider the priority levels of the
projects, i.e. the value of the money. For instance, if Community Daycare has very high
priority (p(daycare) = 4) valued at R$500,000, the value (in utility) for community A to obtain
this project must be 500,000*4 = 2,000,000. Nevertheless, the scale of which the priority may
vary is not defined in the experiment, i.e. it is up to each negotiator perception to evaluate
how much worth very high, high, low and very low priorities are. The marginal change in
the public administration saving share is represented by
g
s
Pand (
g
0s
Pz,
g
00s
Pz) are
estimates of this marginal change made by Aand B, respectively. Using the Negplace tool
for personality and negotiation styles inference, the parameters
g
0w
A,
g
0k
By;
g
0s
Pzand
g
00s
Pz
become common knowledge. After the first proposal made by the public administration at
T0, the decision of A is summarized to:
max
g
w
Ax
0#x#M
¼1500000
g
k
B
1500000
g
*w
Ax
g
s
Pz
g
k
B
!
g
s
Pz
¼1500000 1500000 þ
g
*w
Axþ
g
s
Pz
g
s
Pz;
g
w
Ax¼
g
*w
Ax(12)
Similar to the theoretical model derived by equation (8), the same results are applied for the
player B. At each step in the negotiation process, the agents face the same problem, and
the role of the public administration is to intervene in the participative bargain whenever the
result is distant from the social optimum. The social optimum results are discriminated in
the Pareto-efficient agreements of Table II. The First Best outcome is the best individual
option for each negotiation member, e.g. the best overall outcome for A is to obtain the
public administration to execute all of their projects, a total amount of R$1,150,000. As it is
Table II.
Pareto social-efficient
agreements to each
neighborhood and
the public
administration
A B Public adm. First best (A, B, P) Social payoff
1, 2, 3 and 4 R$1,150,000 6 R$350,000 R$1,500,00 (1, 7, 6) 14
1, 2 and 3 R$1,000,000 6 and 7 R$500,000 R$1,500,00 (2, 6, 6) 14
1, 2 and 4 R$900,000 5 R$550,000 R$1,450,00 (3, 5, 2) 10
1 and 2 R$750,000 5 R$550,000 R$1,300,00 (4, 5, 1) 10
1 and 2 R$750,000 5 and 7 R$700,000 R$1,450,00 (4, 4, 2) 10
1 and 4 R$650,000 5, 7, 8 R$801,000 R$1,451,00 (5, 3, 7) 15
1 R$500,000 5 and 6 R$900,000 R$1,400,00 (6, 2, 4) 12
2 and 3 R$500,000 5 and 6 R$900,000 R$1,400,00 (7, 2, 5) 14
2 R$250,000 5, 6, 7 and 8 R$1,151,000 R$1401,00 (8, 1, 3) 12
K
47,10
1916
Downloaded by UFPE At 14:57 05 January 2019 (PT)
still possible to make both B and the public administration better off by carrying outproject
6 with high priority, the outcome (1, 2, 3, 4) = R$1,150,000 would not be Pareto-efficient if the
project 6 (1, 2, 3, 4, 6) = R$1,500,000 is not attached in Table II in lieu of the former result.
Note the distributive nature of A-B negotiation: while the outcome (1, 2, 3, 4, 6) still remains
the first best to A, it is just the seventh best result for B because there will be a plenty of
other combinations with better individual outcomes for B. In addition, there is an integrative
nature in A–P and B–P interactions once each part gets mutual benefits by using resource in
high and very high priority projects.
The Social Payoff scores in the last column are defined as the sum of the Fist Best
payoffs. Therefore, smaller Social Payoff agreements are preferable for being closer to the
First Best results of the negotiators. From the set of Pareto-efficient possibilities, we find
three outcomes that present the best Social Payoff “10”: (1, 2, 4, 5) = R$1,450,000;
(1, 2, 5) = R$1,300,000; and (1, 2, 5, 7) = R$1,450,000. Any Pareto-efficient agreement
besides the social optimum (i.e. agreements that maximize the group utility, regardless
individual payoffs), is possible, which means that once reached, it will be impossible to
improve the social outcome with no additional loss for another part. For instance, if the
players find themselves in the sixth agreement with social payoff “15”wanting to obtain
the best social outcome “10”, B would have to give up at least one project, being worse off.
Likewise, it is not possible any other improvement in the social payoff “15”without
making at least one part worse off.
As a matter of course, non-Pareto-efficient outcomes are possible, such as an agreement
[(2, 3, 4), (5, 7, 8)] = R$1451,00, which could result a First Best (6, 3, 7) and Social Payoff = 16.
In this situation, one could suggest the player A to change his initial configuration (2, 3, 4) to
(1, 4), which should improve his wellbeing and the social payoff (1,4, 5, 7, 8) = 15, without
jeopardize any other result. Other inefficient (non-Pareto) agreements may exist, such as A
(3, 4) and B(7, 8) = R$1,251, with no priorities met and damage for the public administration
prestige, which may be originated from a misinterpretation of the game or lack of interest
from the participants in the experiment, i.e. lack of interest to achieve better offers, rather
than an irrational behavior of individuals.
4. Results
Table III summarizes the results. The usage of the opponent’s negotiation profile and
personality traits informational tool enabled by the Negplace system allowed the negotiation
to pursue an agreement that in addition to be Pareto-efficient is also (for the majority of
participants) the best social outcome possible. From 162 participants, 93 users had the
information concerning the others’personality dimensions and negotiation style available,
90 agreements were Pareto-efficient (60 of them reached an agreement with the best social
payoff) and 3 outcomes were not Pareto-efficient. On the other hand, 69 users had the
negotiation knowledge and personality of their counterparts disabled, which resulted in 57
Pareto-efficient agreements (30 choices on the best Pareto social payoff) and 12 players
signed non-Pareto-efficient agreements. With respect to the number of interactions, the
average number of negotiation phases (offers and counter-offers) to reach a Pareto-efficient
agreement with the negotiation profile and personality traits information tool enabled were
lower (about 5.9 interactions) than with the same tool disabled (about 8.48 interactions to
reach an agreement).
The last column has this information summed up as percentages. About 82.6 per cent of
participants reached out Pareto-efficient outcomes with the personality and negotiation style
tool disabled, compared to about 96.8 per cent with the tool enabled. Some larger difference
is observed when one of the best social payoffs is considered [agreement (1, 2, 5, and 7)]:
Democratic
deliberation
systems
1917
Downloaded by UFPE At 14:57 05 January 2019 (PT)
64.53 per cent with personality and style enabled to 43.48 per cent disabled. It can be
identified a pattern from the negotiators to pursue a budget division that besides efficient be
close to equality in both number of projects and priorities. The complete knowledge of the
participants on the negotiation parameters of their opponents presents positive results
considering the average budget management and priorities. The group with enabled
negotiation knowledge had an average budget amount equal to R$1442.0318 with an
average of three priority projects per agreement (2.9032 priority projects). On the other hand,
the group of participants with the negotiation knowledge disabled had average budget
amount equal R$1452.4989 with an average of twopriority projects per agreement, i.e.in the
second group they spend more and receives less.
To determine whether this difference with regard to the two groups of users are
statistically significant, we perform unpaired Welch’s Student’st-test, a type of statistical
test important when two population with different sample sizes are assumed to present
unequal variances. The p-value statistic equals 0.011568, which rejects the null
hypothesis in favor of the alternative hypothesis that the means of the groups of users are
not equal, pointing to a significant negotiation improvement when each part knows their
opponent’s personality and negotiation style (Table IV).
5. Conclusion
The approach and the conceptual design of the NegPlace offer a new point of view
concerning the use of nonverbal negotiation knowledge during the bargaining process
supported by NSS. Through the lens of bargaining theory, the Pareto-efficient collective
Table III.
Participatory
budgeting game
table of results
Informational tool Pareto-efficient agreements Cost Negotiators (%)
Enabled 1, 2, 3, 4 and 6 R$1,500,00 –
1, 2, 3, 6 and 7 R$1,500,00 3.22
1, 2, 4 and 5 R$1,450,00 –
1, 2 and 5 R$1,300,00 –
1, 2, 5 and 7 R$1,450,00 64.53
1, 4, 5, 7, and 8 R$1,451,00 9.68
1, 5 and 6 R$1,400,00 –
2, 3, 5 and 6 R$1,400,00 19.35
2, 5, 6, 7 and 8 R$1401,00 –
Non-Pareto efficient outcomes –3.22
Disabled 1, 2, 3, 4 and 6 R$1,500,00 4.35
1, 2, 3, 6 and 7 R$1,500,00 13.05
1, 2, 4 and 5 R$1,450,00 –
1, 2 and 5 R$1,300,00 –
1, 2, 5 and 7 R$1,450,00 43.48
1, 4, 5, 7, and 8 R$1,451,00 8.69
1, 5 and 6 R$1,400,00 –
2, 3, 5 and 6 R$1,400,00 8.69
2, 5, 6, 7 and 8 R$1401,00 4.35
Non-Pareto efficient outcomes –17.39
Table IV.
Unpaired Welch’s
hypothesis test first
group: 93; second
group: 69
Groups Mean SD p-value Conclusion
Enabled 1442.032 22.51 0.0115681 Reject the null hypothesis H
0
(equal mean distribution)Disabled 1452.435 27.60
K
47,10
1918
Downloaded by UFPE At 14:57 05 January 2019 (PT)
agreement, i.e. the agreement in which one cannot improve his/her well-being (payoff)
without making another part worse-off, can be achieved more precisely when the
characteristics of the negotiators personality and strategies (negotiation style) are common
knowledge. This concept, despite being crucial for a collaborative governance of public
resources which emphasizes the participation and control of constituents, has not been given
the proper attention. The Negplace system brings those concepts and information through
assessments of personality based on the MBTI and TKI models, which may guarantee the
efficiency of democratic participative agreements.
In addition to Pareto-efficient agreements, the information about one’spersonalityand
negotiation style may provide enough argument to discredit threats or accurate non-
credible strategies. Suppose that the leader of neighborhood A threatens to end the
negotiation if neighborhood B leader does not give up one of their First Best in exchange
to a fairer outcome. The player B may rationally reason this situation as a credible threat,
and since to obtain something is better than ending the negotiation with nothing, a non-
Pareto agreement would be signed. With a mutual understanding of personalities,
aspirations, strategies and desires, the budget management interaction may result in a
better payoff for all stakeholders and prevent this worst outcome to arise given a lack of
personality trait consideration.
The results of the proposed experiment considering a public budget sequential
bargain negotiation support such achievements. The accessibility which the inputs
provided by the MBTI and TKI models in the NegPlace, in addition to avoid non-Pareto-
efficient outcomes, points to agreements where the best social result is possible by a
mutual understanding of interest and desires. About 64 per cent of negotiations under
this setting have reached such prospects. Therefore, the system can address the
personality and negotiation information styles to mitigate the discomfort of many face-to-
face interactions, which are common in this kind of negotiation procedure and produce
better agreements. Much remains under discussion; nevertheless, the purpose of
improving the negotiator satisfaction with a clearer communication process and mutual
personality understanding might lead to a different negotiation perspective of democratic
participative deliberations.
References
Ames, D.R. (2008), “Assertiveness expectancies: how hard people push depends on the consequences
they predict”,Journal of Personality and Social Psychology, Vol. 95 No. 6, pp. 1541-1557.
Antonioni, D. (1998), “Relationship between the big five personality factors and conflict management
styles”,International Journal of Conflict Management, Vol. 9 No. 4, pp. 336-355.
Aumann, R.J. (1997), “Rationality and bounded rationality”,Games and Economic Behavior, Vol. 21
Nos 1/2, pp. 2-14.
Bane, M. (2010), “From clients to participants? Alternative local governments and the limitations of
participatory democracy in the neoliberal era, Saquisilí, Ecuador”,Democratic Paths and Trends,
Emerald Group Publishing, Bingley, pp. 111-128.
Barr, N. (2012), “The relevance of efficiency to different theories of society”,Economics of the Welfare
State, 5th ed., Oxford University Press, Oxford, p. 46, ISBN: 978-0-19-929781-8.
Barry, B. and Friedman, R.A. (1998), “Bargainer characteristics in distributive and integrative
negotiation”,Journal of Personality and Social Psychology, Vol. 74 No. 2, pp. 345-359.
Bazerman, M.H., Curhan, J.R., Moore, D.A. and Valley, K.L. (2000), “Negotiation”,Annual Review of
Psychology, Vol. 51 No. 1, pp. 279-314.
Democratic
deliberation
systems
1919
Downloaded by UFPE At 14:57 05 January 2019 (PT)
Benyoucef, M. and Verrons, M.H. (2008), “Configurable e-negotiation systems for large scale and
transparent decision making”,Group Decision and Negotiation, Vol. 17 No. 3, pp. 211-224.
Bichler, M., Kersten, G. and Strecker, S. (2003), “Towards a structured design of electronic
negotiations”,Group Decision and Negotiation, Vol. 12 No. 4, pp. 311-335.
Bolton,G.E.andKaragözo
glu, E. (2016), “On the influence of hard leverage in a soft leverage bargaining game:
the importance of credible claims”,Games and Economic Behavior, Vol. 99, pp. 164-179.
Brangewitz, S. and Gamp, J.P. (2013), “Asymmetric nash bargaining solutions and competitive
payoffs”,Economics Letters, Vol. 121 No. 2, pp. 224-227.
Brownell, P. (1982), “Participation in the budgeting process: when it works and when it doesn’t”,
Journal of Accounting Literature, Vol. 1, pp. 124-153.
Bula, G. and Espejo, R. (2011), “Governance and inclusive democracy”,Proceedings of 2011 IEEE
International Conference on Grey Systems and Intelligent Services, GSIS’11 –Joint with the 15th
WOSC International Congress on Cybernetics and Systems, pp. 905-909.
Bula, G. and Espejo, R. (2012), “Governance and inclusive democracy”,Kybernetes, Vol. 41 Nos 3/4,
pp. 339-347.
Campbell, M., Craig, P. and Escobar, O. (2017), “Participatory budgeting and health and wellbeing: a
systematic scoping review of evaluations and outcomes”,The Lancet, Vol. 390, p. S30.
Capaccioli, A., Poderi, G., Bettega, M. and D’Andrea, V. (2017), “Exploring participatory energy
budgeting as a policy instrument to foster energy justice”,Energy Policy.
Célérier, L. and Cuenca Botey, L.E. (2015), “Participatory budgeting at a community level in Porto
Alegre: a bourdieusian interpretation”,Accounting, Auditing & Accountability Journal, Vol. 28
No. 5, pp. 739-772.
Cristofaro, M. (2017), “Herbert Simon’s bounded rationality: its historical evolution in management and
cross-fertilizing contribution”,Journal of Management History, Vol. 23 No. 2.
Cohen, J. and Fung, A. (2004), “Radical democracy”,Swiss Political Science Review, Vol. 10, pp. 169-179.
Consulting Psychologies Press (2002), Thomas-Kilmann Conflict Inventory, Consulting Psychologies
Press, Palo Alto, CA.
Curhan, J.R., Elfenbein, H.A. and Xu, H. (2006), “What do people value when they negotiate? Mapping
the domain of subjective value in negotiation”,Journal of Personality and Social Psychology,
Vol. 91 No. 3, pp. 493-512.
Delaney, M.M., Foroughi, A. and Perkins, W.C. (1997), “An empirical study of the efficacy of a computerized
negotiation support system (NSS)”,Decision Support Systems, Vol. 20 No. 3, pp. 185-197.
DeRosa, D.M., Hantula, D.A., Kock, N. and D’Arcy, J. (2004), “Trust and leadership in virtual teamwork:
a media naturalness perspective”,Human Resource Management, Vol. 43 Nos 2/3, pp. 219-232.
Espejo, R. (2000), “Self-construction of desirable social systems”,Kybernetes, Vol. 29 Nos 7/8,
pp. 949-963.
French, S. (2007), “Web-enabled strategic GDSS, e-democracy and arrow’s theorem: a Bayesian
perspective”,Decision Support Systems, Vol. 43 No. 4, pp. 1476-1484.
Fung, A. and Wright, E.O. (2003), “Thinking about empowered participatory governance”, in Fung, A.
and Wright, E.O. (Eds), Deepening Democracy: Institutional Innovations in Empowered
Participatory Governance, Verso, New York, NY.
Geraskin, M. (2017), “Game-theoretic analysis of Stackelberg oligopoly with arbitrary rank reflexive
behavior of agents”,Kybernetes, Vol. 46 No. 6.
Gettinger, J., Koeszegi, S.T. and Schoop, M. (2012), “Shall we dance? The effect of information
presentations on negotiation processes and outcomes”,Decision Support Systems,Vol.53
No. 1, pp. 161-174.
Gibbons, R. (1992), Game Theory for Applied Economists, Princeton University Press, Princeton.
K
47,10
1920
Downloaded by UFPE At 14:57 05 January 2019 (PT)
Gilkey, R.W. and Greenhalgh, L. (1986), “The role of personality in successful negotiating”,Negotiation
Journal, Vol. 2 No. 3, pp. 245-256.
Goldberg, L.R. (1990), “An alternative ‘description of personality’: the big-five factor structure”,Journal
of Personality and Social Psychology, Vol. 59 No. 6, pp. 1216-1229.
Goldberg, L.R. (1993), “The structure of phenotypic personality traits”,American Psychologist, Vol. 48
No. 1, pp. 26-34.
Gomez, J., Insua, D.R. and Alfaro, C. (2016), “A participatory budget model under uncertainty”,
European Journal of Operational Research, Vol. 249 No. 1, pp. 351-358.
Gomez, J., Insua, D.R., Lavin, J.M. and Alfaro, C. (2013), “On deciding how to decide: designing
participatory budget processes”,European Journal of Operational Research, Vol. 229 No. 3,
pp. 743-750.
Gonçalves, S. (2014), “The effects of participatory budgeting on municipal expenditures and infant
mortality in Brazil”,World Development, Vol. 53, pp. 94-110.
Jenkins, K. (2018), “Setting energy justice apart from the crowd: lessons from environmental and
climate justice”,Energy Research & Social Science, Vol. 39, pp. 117-121.
John, O.P. and Srivastava, S. (1999), “The big-five trait taxonomy: history, measurement, and
theoretical perspectives”, in Pervin, L.A. and John, O.P. (Eds), Handbook of Personality: Theory
and Research, 2nd ed., Guilford Press, New York, NY, pp. 102-138.
Kersten, G.E. (2004), “E-negotiation systems’: interaction of people and technologies to resolve
conflicts”, InterNeg Research Papers, pp. 5-6.
Kersten, G.E. and Lo, G. (2003), “Aspire: an integrated negotiation support system and software
agents for e-business negotiation”,International Journal of Internet and Enterprise
Management, Vol. 1 No. 3, p. 293.
Kersten, G.E. and Noronha, S.J. (1999), “WWW-based negotiation support: design, implementation, and
use”,Decision Support Systems, Vol. 25 No. 2, pp. 135-154.
Lee, K.C., Kang, I. and Kim, J.S. (2007), “Exploring the user interface of negotiation support
systems from the user acceptance perspective”,Computers in Human Behavior,Vol.23
No. 1, pp. 220-239.
Lim, J. (2000), “An experimental investigation of the impact of NSS and proximity on negotiation
outcomes”,Behaviour & Information Technology, Vol. 19 No.5, pp. 329-338.
Mahlendorf, M.D., Schäffer, U. and Skiba, O. (2015), “Antecedents of participative budgeting-a review
of empirical evidence”,Advances in Management Accounting, Emerald Group Publishing,
Bingley, pp. 1-27.
Mock, W.B. (2011), “Pareto optimality”,Encyclopedia of Global Justice, Springer, Dordrecht,
pp. 808-809.
Moura, J.A. and Cabral, A.P.S. (2014), “Incorporating personal style into a Negotiation Support System”,
Proceedings of the Joint International Conference of the INFORMS GDN, pp. 95-99.
Moura, J.A. and Costa, A.P.C.S. (2015), “NegPlace platform a web negotiation support system that
incorporates negotiators styles and personalities”,The 15th International Conference on
Group Decision & Negotiation Letters,Warsaw School of Economics Press,Warsaw,
pp. 1-413.
Moura, J.A. and Costa, A.P.C.S. (2018), “Personality traits and negotiation style effects on negotiators:
perceptions in a web-based negotiation”,Journal of Organizational and End User Computing,
Vol. 30 No. 2.
Moura, J.A., Daher, S.F.D. and Costa, A.P.C.S. (2016), “Investigating relations between
psychophysiological measures and negotiation style in a negotiation support system
context”,16th International Conference on Group Decision and Negotiation, INFORMS GDN
2016,Bellingham.
Democratic
deliberation
systems
1921
Downloaded by UFPE At 14:57 05 January 2019 (PT)
Nakaoka, I., Matsumura, M., Kushida, J.I. and Kamei, K. (2009), “A proposal of group decision support
system for kansei commodity purchase using som and its applications”,International Journal of
Innovative Computing, Information and Control, Vol. 5 No. 12, pp. 4915-4926.
Nelson, N., Bronstein, I., Shacham, R. and Ben-Ari, R. (2015), “The power to oblige: power, gender,
negotiation behaviors, and their consequences”,Negotiation and Conflict Management Research,
Vol. 8 No. 1, pp. 1-24.
Nelson, N., Shacham, R. and Ben-ari, R. (2016), “Trait negotiation resilience: a measurable construct
of resilience in challenging mixed-interest interactions”,Personality and Individual
Differences, Vol. 88, pp. 209-218.
Nepomuceno, T.C.C. and Costa, A.P.C.S. (2014), “A principal-agent approach for the crowding-out effect
in information technology outsourcing contracts under asymetric information”, Anais do XLVI
Simp
osio Brasileiro de Pesquisa Operacional, Salvador/BA.
Rubinstein, A. (1982), “Perfect equilibrium in a bargaining model”,Econometrica: Journal of the
Econometric Society, Vol. 50 No. 1, pp. 97-109.
Santos, H., Cristino, C. and Bruno, G. (2017), “Extended warranty: an approach via Stackelberg game”,
Russian Management Journal, Vol. 15 No. 4, pp. 425-440.
Schoop, M., Jertila, A. and List, T. (2003), “Egoisst: a negotiation support system for electronic
business-to-business negotiations in e-commerce”,Data & Knowledge Engineering,Vol.47
No. 3, pp. 371-401.
Shell, G.R. (2001), “Bargaining styles and negotiation: the Thomas-Kilmann conflict mode instrument in
negotiation training”,Negotiation Journal, Vol. 17 No. 2, pp. 155-174.
Simon, H.A. (1947), Administrative Behavior, 1st ed., Free Press, New York, NY.
Simon, H.A. (1955), “A behavioral model of rational choice”,The Quarterly Journal of Economics,
Vol. 69 No. 1, pp. 99-118.
Simon, H.A. (1956), “Rational choice and the structure of the environment”,Psychological Review, Vol. 63
No. 2, pp. 129-138.
Sintomer, Y., Herzberg, C., Allegretti, G. and Rocke, A. (2010), “Learning from the south: participatory
budgeting worldwide - an invitation to global cooperation”, InWEnt gGmbH, Bonn –Capacity
Building International, Germany/Service Agency Communities in One World.
Sintomer, Y., Herzberg, C., Röcke, A. and Allegretti, G. (2012), “Transnational models of citizen
participation: the case of participatory budgeting”,Journal of Public Deliberation, Vol. 8 No. 2.
Slovic, P. (1987), “Perception of risk”,Science, Vol. 236 No. 4799, pp. 280-285.
Smith, M.J. (1982), Evolution and The Theory of Games, Cambridge University Press, Cambridge.
Sobel, J. and Takahashi, I. (1983), “A multistage model of bargaining”,The Review of Economic Studies,
Vol. 50 No. 3, pp. 411-426.
Tavana, M. and Kennedy, D.T. (2006), “N-site: a distributed consensus building and negotiation
support system”,International Journal of Information Technology & Decision Making,Vol.5
No. 1, pp. 123-154.
Thomas, K.W. and Kilmann, R.H. (1974), Thomas-Kilmann Conflict Mode Instrument, Xicom, Tuxedo,
New York, NY.
Tversky, A. and Kahneman, D. (1973), “Availability: a heuristic for judging frequency and probability”,
Cognitive Psychology, Vol. 5 No. 2, pp. 207-232.
Yolles, M. (2006), Organizations as Complex Systems: An Introduction to Knowledge Cybernetics,
Information Age Publishing, Charlotte, NC, pp. 261-262.
Von Stackelberg, H. (1934), Marktform und gleichgewicht, J. springer, Vienna.
Weigand, H., De Moor, A., Schoop, M. and Dignum, F. (2003), “B2B negotiation support: the need for a
communication perspective”,Group Decision and Negotiation, Vol. 12 No. 1, pp. 3-29.
K
47,10
1922
Downloaded by UFPE At 14:57 05 January 2019 (PT)
Wolfe, C.J. and Murthy, U.S. (2005), “Negotiation support systems in budget negotiations: an
experimental analysis”,Journal of Management Information Systems, Vol. 22 No. 3, pp. 351-381.
Wood, V.F. and Bell, P.a. (2008), “Predicting interpersonal conflict resolution styles from personality
characteristics”,Personality and Individual Differences, Vol. 45 No. 2, pp. 126-131.
Wu, S. and Wang, D. (2017), “The influence of local government decision-making competition on
enterprise innovation investment under information asymmetry and multiple risk appetite
type”,Kybernetes, Vol. 46 No. 5.
Yiu, T.W. and Lee, H.K. (2011), “How do personality traits affect construction dispute negotiation?
Study of big five personality model”,Journal of Construction Engineering and Management,
Vol. 137 No. 3, pp. 169-178.
Corresponding author
Thyago Celso Cavalcante Nepomuceno can be contacted at: nepomuceno@dis.uniroma1.it
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
Or contact us for further details: permissions@emeraldinsight.com
Democratic
deliberation
systems
1923
Downloaded by UFPE At 14:57 05 January 2019 (PT)
