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Revista de
Administração
Contemporânea
Journal of Contemporary Administration e-ISSN: 1982-7849
1
Revista de Administração Contemporânea, v. 25, n. 2, e-190044, 2021 | doi.org/10.1590/1982-7849rac2021190044.en| e-ISSN 1982-7849 | rac.anpad.org.br
RESUMO
Contexto: nos últimos anos, estudos buscaram analisar de que forma os
processos de inteligência e de gestão do conhecimento são compreendidos
e aplicados no contexto da gestão pública, ambiente em que esses processos
aparecem como um ponto a ser explorado para potencializar a qualidade
decisória. Objetivo: analisar como os gestores públicos aplicam inteligência
e gestão do conhecimento visando a uma maior qualidade decisória.
Método: a partir de protocolo de pesquisa denido e validado, foram realizadas
entrevistas com dezessete gestores públicos do sul do Brasil. Para a análise,
foi aplicada a técnica de análise comparativa qualitativa utilizando conjuntos
fuzzy para identicar caminhos efetivos para tomada de decisão em Governo.
Resultados: os resultados indicam a importância da efetiva gestão de dados,
informações e conhecimentos para qualidade decisória de gestores públicos,
demonstrando que a pouca qualidade decisória está relacionada à ausência
ou à reduzida utilização de gestão do conhecimento e inteligência na gestão
pública. Conclusão: além de analisar condições e propor caminhos para levar
a uma maior qualidade na tomada de decisão dos gestores públicos, foi possível
contribuir para a temática de gestão do conhecimento e inteligência na gestão
pública, bem como beneciar o governo com caminhos a serem consolidados
e melhor explorados.
Palavras-chave: gestão pública; gestão do conhecimento; inteligência;
análise comparativa qualitativa; conjuntos fuzzy.
ABSTRACT
Context: in recent years, studies have sought to analyze how intelligence
and knowledge management processes are understood and applied in
the context of public management, environments in which processes
appear as a point to be explored to enhance decision-making quality.
Objective: to analyze how public managers apply intelligence and
knowledge management aiming at a higher decision quality. Method: based
on a dened and validated research protocol, interviews were conducted
with seventeen public managers in southern Brazil. For the analysis, the
qualitative comparative analysis technique using fuzzy sets was applied.
Results: the results suggest the importance of eective data, information,
and knowledge management for the decision-making quality of public
managers, demonstrating that the absence of decision-making quality is
directly related to the absence or little use of knowledge management and
intelligence elements in the public management. Conclusion: in addition
to analyzing conditions and proposing ways to lead to greater quality in
decision making by public managers, it was possible to contribute to the
theme of knowledge management and intelligence in public management,
as well as to benet the government with paths to be consolidated and
better explored.
Keywords: public management; knowledge management; intelligence;
qualitative comparative analysis; fuzzy sets.
Qualidade Decisória dos Gestores Públicos: Contribuições da Inteligência e
Gestão do Conhecimento
Decision-Making Quality of Public Managers:
Contributions from Intelligence and Knowledge
Management
1. Universidade Federal de Rio Grande do Sul, Escola de Administração, Porto Alegre, RS, Brazil.
2. Universidade de Lisboa, Instituto Superior de Economia e Gestão, Lisboa, Portugal.
JEL Code: D7, D8, H1.
Editor-in-chief: Wesley Mendes-Da-Silva (Fundação Getulio Vargas, EAESP, Brazil)
Reviewers: Amanda Cainelli (Universidade Federal do Rio Grande do Sul, EA, Brazil)
Natália Marroni Borges (Universidade Federal do Rio Grande do Sul, EA, Brazil)
Peer Review Report: The Peer Review Report is available at this
external URL
.
Received: April 23, 2019
Last version received: June 25, 2020
Accepted: June 25, 2020
# of invited reviewers until the decision:
Claudia Melati1
Raquel Janissek-Muniz1
Carla Maria Marques Curado2
1 2 3 4 5 6 7 8 9
1st round
2nd round
3rd round
4th round
5th round
Cite as: Melati, C., Janissek-Muniz, R., & Curado, C. M. M.
(2021). Decision-making quality of public managers:
Contributions from intelligence and knowledge management. Revista de Administração Contemporânea, 25(2),
e190044. https://doi.org/10.1590/1982-7849rac2021190044.en
Research Article
C. Melati, R. Janissek-Muniz, C. M. M. Curado
Decision-Making Quality of Public Managers: Contributions from Intelligence and
Knowledge Management
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INTRODUCTIONINTRODUCTION
The intensive use of information and
communication technology (ITC) in public
management led to a considerable increase in the
flow of data and information both from society to
governmental organizations and vice-versa. This context
demanded greater attention from public management
regarding the administration of information and
knowledge produced and used. According to the
Forrester Research, published in the journal Information
Week Government (Welsh, 2014), government agencies
must seek effective ways to use data to meet citizens’
expectations. In addition, service delivery must be
based on the unprecedented exponential volume of
data and consider the widespread mobile connectivity
(Scholl & Scholl, 2014; Gil-Garcia, Zhang, & Puron-
Cid, 2016).
Research shows that governments at different
levels are adopting tools and applications to improve
service delivery, increasing coordination, and quickly
responding to the rapid changes in the environment
(Gil-Garcia, Helbig, & Ojo, 2014; Paula & Rover,
2012; Ribeiro, Pereira, & Benedicto, 2013). One of
these management tools is the government’s intelligence
activity, which despite being in the early stages of
development, contributes to a new model of public
service delivery (Schedler, Guenduez, & Frischknecht,
2019).
The structure of the government’s intelligence
activity based on the use of data and information lead
to quality decision-making of public managers and
the development of new public policies. Cavalcante
(2018) suggests that the last decades’ economic, social,
and political-administrative transformations have
effectively enhanced a variety of restructuring processes,
improving service delivery and the functioning of the
Brazilian public sector.
A new form of thinking public management
entails goals such as the development of an agile
public administration regarding effectiveness in
service delivery and resolution of issues of government
and society, interdepartmental collaboration, and
the implementation of a creative mix of emerging
technologies for innovation in the public sector
(Eom, Choi, & Sung, 2016; Liu & Zheng, 2015).
New management processes, such as knowledge and
intelligence management, prove to be effective in
transforming data and information from the external
environment in relevant knowledge to quality decision-
making of public managers (Gil-Garcia et al., 2016;
Johnston & Hansen, 2011; Monavvarian & Kasaei,
2007; Shinoda, Maximiano, & Sbragia, 2015).
When adopting intelligence processes involving
activities of monitoring, observation, collection,
interpretation, creation of meaning, and dissemination
of data, organizations can select sensitive, useful, and
evidence-based information that contributes to assertive
decision-making (Gil-Garcia et al., 2016; Janissek-
Muniz & Blanck, 2014; Scholl & Scholl, 2014). In
turn, knowledge management (KM) refers to a series
of practices and techniques that organizations adopt
to create, share, and explore knowledge to achieve
organizational goals (Davenport, 1997; Nonaka &
Takeuchi, 2008; Arora, 2011; Jain & Jeppesen, 2013).
KM improves the capacity to carry out public
activities, with practices that increase the effectiveness of
public services, and enhance the communication among
the management levels (Wiig, 2002; Monavvarian
& Kasaei, 2007). These studies demonstrate the
importance of processes of knowledge and intelligence
management for quality decision-making (Alavi &
Leidner, 2001; Desouza, 2005; Hazlett, McAdam,
& Beggs, 2008; Johnston & Hansen, 2011; Linders,
Liao, & Wang, 2015; Shinoda et al., 2015). While
strategic intelligence activities prioritize looking at
the external environment and its relationship with the
organization, KM has an internal perspective, focusing
on the knowledge already existing in the organization
(Benedetti & Janissek-Muniz, 2009).
Although there are studies on both intelligence
and knowledge management in public management,
there is a gap in the literature regarding the association
between them. The Public Management Excellence
Model (or MEGP) (Ministério do Planejamento, 2016)
reinforces the importance of analyzing intelligence and
KM together. In the MEGP, the pillar ‘information
and knowledge’ supports the evaluation and processing
of data and facts of both the organization (internal)
and the environment (external), recognizing that the
data and facts of the environment are not under the
organization’s direct control, but may influence its
performance. In addition, Terra and Almeida (2008)
argue that the study of the concepts of KM and
intelligence, as well as the development of activities
related to processes, should be treated together. For
the authors, these elements should be aligned with the
organizational strategy, seeking synergies and optimal
allocation of resources and time.
Additionally, there are few reported efforts in
the literature (1) to leverage the use of social data to
build smart governments; (2) seeking the effective use
of data and information from citizens; (3) to analyze
C. Melati, R. Janissek-Muniz, C. M. M. Curado
Decision-Making Quality of Public Managers: Contributions from Intelligence and
Knowledge Management
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the dynamic interactions among stakeholders; and (4)
to influence and develop public policies (Bernardes,
Andrade, Novais, & Lopes, 2017; McBride, Aavik,
Lalvet, & Krimmer, 2018; Przeybilovicz, Cunha,
Macaya, & Alburquerque, 2018). In this sense, the
research question guiding this study is: Based on the
processes of intelligence and KM, what are the effective
paths to achieving quality decision-making of public
managers?
Thus, the objective of this study is to analyze
how public managers apply the processes of intelligence
and KM for quality decision-making. The study first
analyzes the issues related to intelligence and KM in
public management and then interviews seventeen
public managers. The data collected through the
interviews were analyzed using content analysis, and
later, to define paths, a qualitative comparative analysis
was applied.
This research contributes to expanding the
understanding of intelligence and KM in public
management, recognizing the utility of this combination
in a context of an unprecedented amount of data and
information, which need to be monitored, explored,
understood, transformed into knowledge, and converted
into actions to qualify the public managers’ decision-
making. As for its applicability, the study presents paths
for governments to explore and consolidate, leading to
better use of data and information from the context to
improve decision-making.
The structure of the article includes this
introduction to the theme, followed by a section
presenting the concepts of intelligence and KM and
their combination in the context of public management.
The next section discusses the methodology and
the techniques adopted, particularly the qualitative
comparative analysis, followed by the study’s results.
Finally, the article presents discussions, conclusions,
and directions for future research.
KNOWLEDGE MANAGEMENT AND KNOWLEDGE MANAGEMENT AND
INTELLIGENCE IN THE PUBLIC CONTEXTINTELLIGENCE IN THE PUBLIC CONTEXT
In the 1990s, the Brazilian government began a
process of modernizing public administration, focusing
on efficiency through reducing costs and applying a
result-oriented public activity, adopting managerial and
less bureaucratic assumptions (Abrucio, 1997; Batista,
2012; Klering, Porsse, & Ghadagnin, 2010; Paula,
2005; Pereira, 1996). According to Ribeiro, Pereira and
Benedicto (2013), public administration reforms have
contributed to improving political decision-making
capacity and to the decentralization of the state, with
the implementation of horizontal coordination and
modernization of human management potential. This
trend is based on building a more participatory, efficient,
and integrated public administration (Capobiango,
Nascimento, Silva, & Faroni, 2013; Paula, 2005; Secchi,
2009), providing better public management in service
delivery.
Rezende and Frey (2005), recognize the potential
of expanding the number and types of actors involved
in public management. For the authors, these new
directions of public administration and public policy
management require the mobilization of all knowledge
available in society to improve the administrative
performance and democratization of decision-making
processes. Studies also point out the importance of
acquiring data to be transformed into information and
knowledge to improve decision-making in the public
sector (Gil-Garcia, Pardo, & Aldama-Nalda, 2013;
Scholl & Scholl, 2014), since smart governments can
potentially feel and react to the environment based on
data relevant to decision-making (Gil-Garcia et al.,
2016).
Along the same vein, the Brazilian National
Program for Public Management and Bureaucratization
(known as Gespública) has sought, since the 2000s,
to support the development and implementation of
solutions that allow a continuous improvement in the
management of public organizations and their impacts
on citizens. Information and knowledge are presented
as a fundamental pillar to achieving one of the main
objectives of the program, which is the mobilization of
the Brazilian public administration toward result-driven
management (Ministério do Planejamento, 2016).
The process of intelligence in public management
is aligned with the objectives of administrative
modernization. It involves particular issues when
compared to the private sector. Several authors emphasize
the importance of continuous processes for monitoring
the environment and analyzing data and information
in government (Cepik, 1997, 2005; Desouza, 2005;
Johnston & Hansen, 2011; Linders et al., 2015). Issues
related to the effectiveness of public activity and the
delivery of quality public services, based on the use of
information from the environment, are characteristics
indicating the use of intelligence processes in public
management (Gil-Garcia et al., 2014; Scholl & Scholl,
2014).
According to Rezende (2012), intelligence in
public administration refers to the use of systematic,
personalized, and timely information and knowledge
for decision-making. It aims to help public managers
C. Melati, R. Janissek-Muniz, C. M. M. Curado
Decision-Making Quality of Public Managers: Contributions from Intelligence and
Knowledge Management
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deal with complexity and uncertainties through
coordination, continued involvement, access to open
data and shared information (Gil-Garcia et al., 2014;
Scholl & Scholl, 2014), in order to take advantage of
the population’s potentially latent skills and knowledge
(Johnston & Hansen, 2011).
The literature shows important dimensions of
the intelligence process in public management. First,
the support of top management by encouraging the
monitoring of the environment to capture relevant
data and information for the construction of more
efficient public administration (Gil-Garcia et al.,
2016). Second, the collaboration and participation of
people as recipients of data and information relevant
to the organization and obtained through monitoring
the environment (Gil-Garcia et al., 2016; Johnston &
Hansen, 2011; Paula & Rover, 2012). Finally, the use of
information and communication technology to collect
data from the external environment, as well as assisting
in data and information sharing among interested
parties (Paula & Rover, 2012; Scholl & Scholl, 2014).
However, it is not enough to obtain information
from the environment through intelligence processes.
All knowledge generated from the data and information
collected externally and that produced in the organization
must be subject to management (Tzortaki & Mihiotis,
2014). Therefore, the knowledge management (KM)
process is established based on the organization’s capacity
to gather, store, and transfer knowledge, providing
access to knowledge sources through mechanisms of
identification and information retrieval, in order to
apply such knowledge to the organization’s specific
needs (Alavi & Leidner, 2001).
According to Riege and Lindsay (2006), building
an effective government and developing knowledge-based
public policies require the adoption of management that
systematically and effectively captures, disseminates,
discloses, and applies organizational knowledge. The
public management must use practices and techniques
to create, share, and explore knowledge that can assist in
achieving organizational goals (Jain & Jeppesen, 2013).
In this sense, there is an effort by government agencies
to adopt KM practices to create innovative and complex
systems that connect people with relevant information
and knowledge to develop their activities (Riege &
Lindsay, 2006), considering that people’s knowledge
is a central value to an organization (Voronchuk &
Starineca, 2014).
The analysis of KM in the field of public
management suggests important dimensions to be
considered. Three of them stand out. First, the support
of top management for the creation, dissemination,
and storage of organizational knowledge, to develop
organizational policies oriented to learning and KM
(Hazlett et al., 2008; Lindner & Wald, 2011; Shinoda
et al., 2015).Second, the use of ICT as a facilitator in
the development of the KM process, since ICT allows to
quickly obtain, share, and store knowledge (Arora, 2011;
Dawes, Cresswell, & Pardo, 2009; Mao, Liu, Zhang, &
Deng, 2016; Schutte & Barkhuizen, 2015). Finally, the
dimension of human capital stands out as the leading
role of the KM process. Knowledge is created, obtained,
disseminated, and stored in the organization and
subsidizes decision-making, but the decisions are made
by people (Arora, 2011; Davenport, 1998; Monavvarian
& Kasaei, 2007; Voronchuk & Starineca, 2014; Wiig,
2002).
The analysis of the concepts of intelligence and
KM in government helps to establish some fundamental
factors that permeate both processes. For example, the
use of ICT and the role of people as primary agents
of such processes. In addition, the support of top
management and issues of culture and organizational
incentives appear as important factors in building an
organization that efficiently captures, transforms, and
manage information and knowledge.
The combination of the concepts of intelligence
and KM, considering the context of the public sector,
reveals that ICT, human capital (people), and the
support of top management are crucial factors in
the operationalization of the processes. In addition,
the government’s efficiency and effectiveness, and
quality decision-making of public managers, appear as
consequences of the effective use of intelligence and
KM mechanisms in the development of public activity.
Thus, intelligence processes are established from the
monitoring of the external environment for capturing
data and information relevant to the organization
(Janissek-Muniz, Lesca, & Freitas, 2006). KM seeks to
transform data and information from the environment
into knowledge to be shared, explored, and used in
decision-making (Gil-Garcia et al., 2013; Johnston &
Hansen, 2011; Wiig, 2002).
To resume the main points listed in the theoretical
analysis, Table 1 presents perspectives, authors, and basic
assumptions related to the processes of intelligence and
KM, focusing on the context of public management.
The studies presented in this literature review
allow inferring the relevance of intelligence and KM
processes for public management and the need for
continued research in this area. The intention is
to consolidate them as crucial processes for quality
decision-making of public managers.
C. Melati, R. Janissek-Muniz, C. M. M. Curado
Decision-Making Quality of Public Managers: Contributions from Intelligence and
Knowledge Management
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METHODOLOGYMETHODOLOGY
e methodology adopted to pursue the objective
of analyzing how public managers apply the processes of
intelligence and KM for quality decision-making consisted
of, rst, a literature review on intelligence and knowledge
management (KM) in the context of public management.
e review allowed identifying elements of both intelligence
and KM, establishing a research protocol. As for KM, the
elements observed were creating, transforming, structuring,
and sharing organizational knowledge. In the case of
intelligence, monitoring the environment and identifying,
organizing, and using data and information about the
environment stood out. e next step consisted of empirical
research, adopting a qualitative and exploratory approach.
e data collection method was semi-structured interviews,
and the analysis was carried out using content analysis and
qualitative comparative analysis (QCA).
Data collection
According to Myers (2013), qualitative researchers
claim that it is practically impossible to understand why
someone did something or why something happened in
an organization without talking to people about it. To
understand how public managers apply the processes
of intelligence and KM in the development of public
activity, the study chose to talk to people involved in
this task, using semi-structured interviews.
The study’s target audience was government
employees working as public managers, i.e., exercising
managerial activities in state secretaries linked to
the executive branch of one of the states in southern
Brazil. The interviewees were chosen for convenience,
proximity, and accessibility. During the interviews, the
participants were asked to recommend others who could
Table 1. eoretical perspectives.
Category eoretical assumptions Authors
Knowledge management
Knowledge management involves creating, storing, disseminating,
protecting, sharing, and using knowledge to maximize the eciency
of the organization. Knowledge is an asset that must undergo
ecient management and be constantly renewed to generate a
return and competitive advantage.
Alavi and Leidner (2001); Davenport (1997); Gaspar,
Santos, Donaire, Kuniyoshi and Prearo (2016); Gold,
Malhotra and Segars (2001); Nonaka (1994); Nonaka
and Konno (1998); Nonaka and Takeuchi (2008); Wiig
(1997, 2002).
Intelligence
e ability of organizations to collect, analyze, and disseminate data
and information (relevant to the development of their activities)
from the external environment, in advantage to their objectives and
strategies and reducing uncertainties in decision-making.
Andriotti, Freitas and Janissek-Muniz (2008);
Davenport (1998); Fachinelli, Glacomello, Rech and
Bertolini (2013); Janissek-Muniz et al. (2006); Janissek-
Muniz and Blanck (2014); Rios, Strauss, Janissek-Muniz
and Brodbeck (2011).
Convergence between
intelligence and KM in
public manage-ment
Support of top management as an organizational incentive for
the creation, sharing, and storage of organizational knowledge.
Creation of an organizational culture aimed at monitoring the
environment with the objective of capturing data and information.
e use of ICT favors the sharing of information and knowledge
among stakeholders, i.e., technology is a facilitator in capturing
data and information from the environment. Human capital has
a leading role in KM since people are the decision-makers who
use the knowledge created, obtained, disseminated, and stored
in the organization. It is crucial to take advantage of skills and
knowledge often latent in the crowd and seek people’s collaboration
and participation to increase eciency and eectiveness of public
activity. People are recipients of data and information from the
environment.
Dawes, Cresswell and Pardo (2009); Gil-Garcia et al.
(2013); Gil-Garcia et al. (2016); Hazlett, Mcadam and
Beggs (2008); Johnston and Hansen (2011); Lindner
and Wald (2011); Mao, Liu, Zhang and Deng (2016);
Shinoda, Maximiano and Sbragia (2015); Monavvarian
and Kasaei (2007); Paula and Rover (2012); Riege and
Lindsay (2006); Scholl and Scholl (2014); Voronchuk
and Starineca (2014); Wiig (1997, 2002).
Quality decision-making
of public managers
Contribution to the participation of citizens and organizations
in public management. Improving the quality of life through the
development of intellectual capital and increasing the number
of knowledge workers in society. Public managers’ decision-
making based on relevant data and information, improving public
administration: better service delivery, overcoming complex
challenges, agile public management, eective public policies, and
programs.
Gil-Garcia et al. (2013); Gil-Garcia et al. (2016);
Johnston and Hansen (2011); Monavvarian and Kasaei
(2007); Scholl and Scholl (2014); Wiig (2002).
Note. Source: elaborated by the authors.
C. Melati, R. Janissek-Muniz, C. M. M. Curado
Decision-Making Quality of Public Managers: Contributions from Intelligence and
Knowledge Management
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contribute to this research. The final number of semi-
structured interviews was defined by saturation.
The interviews were conducted between April and
May 2017, with seventeen participants. Fifteen (88%)
of them were male, eleven (65%) have been in the
public service for more than ten years, and twelve (71%)
received financial incentives (bonus for productivity) at
the agency where they work. Eleven (65%) had post-
degrees and worked in different relevant areas such as
inspection and collection, quality of public spending,
projects and system, public procurement. (Table 2).
Table 2. Interviewees’ prole.
Interviewee Length of service
(years) Gender Function in the
public agency Area of work Education
E1 10 M Manager Inspection and collection Post-degree
E2 25 M Manager Projects and systems Post-degree
E3 7 M Manager Quality of public spending Degree
E4 10 M Manager Budget planning Post-degree
E5 25 M Director Administrative management Master
E6 7 M Manager Financial planning and cash ow Post-degree
E7 23 M Manager Control of public debt Degree
E8 21 M Director Projects and systems Post-degree
E9 18 M Manager Personnel development Degree
E10 7 M Manager Financial planning Master
E11 25 M Director Quality and organizational development Master
E12 39 M Manager Institutional relations Degree
E13 38 M Director Public procurement Master
E14 6 M Manager Projects and systems Post-degree
E15 8 F Coordinator Legal advice Post-degree
E16 2 F Manager Personnel development Degree
E17 36 M Manager Planning and modernization Degree
Note. Source: elaborated by the authors.
C. Melati, R. Janissek-Muniz, C. M. M. Curado
Decision-Making Quality of Public Managers: Contributions from Intelligence and
Knowledge Management
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After data collection, the interviews were
transcribed, resulting in 92 pages of raw data. The
content was organized and structured, systematizing the
ideas and analyzing how public managers understand
and apply the processes of intelligence and KM for the
development of public activity, and for quality decision-
making. Afterwards, the referred data and information
were analyzed through the association of two techniques:
content analysis and qualitative comparative analysis
(QCA).
Data analysis
The techniques applied were content analysis
and fuzzy-set qualitative comparative analysis (QCA).
After the content analysis that identified and organized
the main elements portrayed in the interviews, some
conditions were established. The conditions were
calibrated to carry out the qualitative comparative
analysis. The procedures and analyzes are described in
this subsection.
Content analysis
The data analysis followed the steps described
in work by Bardin (2011). The content transcribed
was analyzed to identify categories. Table 3 presents
the categorization of data for content analysis, which
was based on the theoretical framework and the
understanding of public managers regarding intelligence
and knowledge management (KM), considering the
importance of these processes for the development of
public activity. In addition, it was possible to verify
convergent points of approximation of the concepts in
the public sectors and the perceived evolution in the
structuring of processes in the public sector according
to the view of the public managers interviewed.
Table 3. Categorization of information.
Raw data Category Sub-category eoretical framework
Transcription
of interviews
Knowledge
management
Knowledge management process
Alavi and Leidner (2001); Davenport (1997); Gaspar et al. (2016); Gold
et al. (2001); Nonaka (1994); Nonaka and Konno (1998); Nonaka and
Takeuchi (2008); Wiig (1997, 2002).
Knowledge creation
Knowledge use, storing, and
dissemination
Intelligence
Intelligence activities and teams
Andriotti et al. (2008); Davenport (1998); Fachinelli et al. (2013); Janissek-
Muniz et al. (2006); Janissek-Muniz e Blanck (2014); Rios et al. (2011).
Collection of data and
information
Analysis and use of data and
information
Dissemination of data and
information in the organization
Convergence
between intelligence
and KM in public
management
Support of top management
Gil-Garcia et al. (2013); Gil-Garcia et al. (2016); Hazlett et al. (2008);
Johnston and Hansen (2011); Lindner and Wald (2011); Monavvarian
and Kasaei (2007); Riege and Lindsay (2006); Scholl and Scholl (2014);
Shinoda et al. (2015); Wiig (2002).
Use of ICT
Alhamoudi (2015); Arora (2011); Dawes et al. (2009); Davenport (1998);
Gaspar et al. (2016); Gil-Garcia et al. (2013); Gil-Garcia et al. (2016); Gold
et al. (2001); Jain and Jeppesen (2013); Johnston and Hansen (2011); Mao
et al. (2016); Paula and Rover (2012); Pee and Kankanhalli (2016); Scholl
& Scholl, 2014; Schutte and Barkhuizen (2015); Wiig (2002).
Human capital
Arora (2011); Davenport (1998); Dawes et al. (2009); Gil-Garcia et al.
(2013); Gil-Garcia et al. (2016); Johnston and Hansen (2011); Mao et al.
(2016); Monavvarian and Kasaei (2007); Paula and Rover (2012); Scholl &
Scholl, 2014; Voronchuk e Starineca (2014); Wiig (1997, 2002).
Quality decision-
making of public
managers
-
Gil-Garcia et al. (2013); Gil-Garcia et al. (2016); Johnston and Hansen
(2011) Monavvarian and Kasaei (2007); Scholl and Scholl (2014); Wiig
(2002).
Note. Source: elaborated by the authors.
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Regarding the influence of the processes of
intelligence and KM in quality decision-making of public
managers, all seventeen interviewees listed the elements
‘data from the external environment’ and ‘information
and knowledge produced internally by the organization’
as of paramount importance and definitive for quality
decision-making, even if there were no intelligence
or KM processes structured in the organization. The
interviewees’ response corroborates the theory, both
regarding the knowledge sharing between the lower and
upper management and the search for relevant data and
information to qualify decision-making to overcome
complex public administration challenges (Wiig, 2002;
Johnston & Hansen, 2011; Gil-Garcia et al., 2013).
One of the interviewees mentioned the need
for faster, more consistent, and transparent decisions
(Riege & Lindsay, 2006), emphasizing that “if data
and information from the environment were not used,
decision-making processes would be dependent, perhaps
subjective, influenced by the capacity of a manager
to pressurize. Other [decisions] could not be as clear
[if not made based on data and information from the
environment].” Another issue that deserves attention
concerns the development of analytical capabilities
so that employees can process data and information
and move forward in evidence-based decision-making
(Malomo & Sena, 2017; Valle-Cruz & Sandoval-
Almazan, 2018). One interviewee considers there is
much to be improved regarding the concern over the
use of data and information for quality decision-making
about the development of public policies. According to
the interviewee, “a more structured process of knowledge
management is lacking, sometimes I need information
about something, and I need to call someone, so it is
restricted to interpersonal relationships.” Based on
the issues that emerged in the content analysis, when
the information was categorized, and in order to map
the causal configurations related to the processes of
intelligence and KM that could potentially lead to
quality decision-making of public managers, the study
adopted the fuzzy-set qualitative comparative analysis
technique, presented below.
Qualitative comparative analysis
The application of the fuzzy-set qualitative
comparative analysis (fsQCA) was considered adequate
in this case because it allows identifying causal
configurations that lead to the presence or absence
(represented by the symbol ~) of a given result, with
more than one solution for each given objective (Rihoux
& Ragin, 2009). The fsQCA offers, by inserting values
between 0 and 1, a closer perception of the situations
studied (Ragin, 2000).
The analysis identified which configurations of
causal conditions led to quality decision-making of
public managers, as well as the configurations that led to
the absence of the respective result. Each configuration
of the causal conditions and the associated result are
designated as a case (Fiss, 2007). The causal conditions
in the fsQCA are related to the dimensions considered
as relevant to the use of intelligence and KM processes
in the context of public management, based on the
theoretical framework and previous content analysis.
The conditions related to quality decision-
making of public managers are the use of knowledge
management processes (KM), intelligence (intel), and
the support of top management (topman), as well as the
influence of the length of service (length) and gender
of the respondent (gen). The dimensions related to the
use of ICT and the participation of people were not
analyzed because they showed, based on the theoretical
framework and content analysis, to be necessary in both
cases, with no need for incorporation in the study as a
way to bring a differential for research.
Calibration of conditions
QCA was developed to analyze configurations
of conventional Boolean sets. The approach analyzes
whether a given variable is part of a given set, through
the definition of crisp sets (sets of conditions that only
assume values 0 and 1). Crisp set qualitative comparative
analysis (csQCA) offers sets with simple data composed
of binary variables, coded as 1 for ‘present,’ and 0 for
‘absent’ (Rihoux & Ragin, 2009). The binary variable
in this study is the condition ‘gender.’
In addition to working with existing binary
variables in the conventional set approach, the fuzzy
set qualitative comparative analysis (fsQCA) considers
values between 0 and 1, not just ‘0’ or ‘1.’ The
fsQCA approach accepts alternative configurations of
conditions, equifinality, and asymmetry (Fiss, 2007),
Fuzzy sets offer a detailed and closer perception of
the situations studied (Ragin, 2000). According to the
author, the connection between theory and data analysis
is essential in social sciences, and fuzzy sets improve
such connection since they can be designed to fit and
‘fill in’ theoretical concepts.
Calibration is the process of classifying conditions
in each case, from ‘fully in’ (1.00) to ‘fully out’ (0.00),
and implies theoretical and empirical knowledge about
the variables (Ragin, 2005; 2008). In this study, binary
and calibrated categorical variables were adopted to allow
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the use of fsQCA. Each category was associated with
a significant set (full membership, point of maximum
ambiguity, and full non-membership). To calibrate the
fuzzy set data, a mechanical procedure (based on theory)
or a manual procedure (based on evidence) is used. This
study adopted a manual procedure to calibrate causal
conditions and results, based on the analysis of the
interviews conducted with public managers.
The process of intelligence and KM were analyzed
based on their various processes. Therefore, the variable
‘intelligence’ (intel) was considered as presenting
‘full membership’ when at least one of its processes
(monitoring of the environment, use of information, or
internal dissemination of data and information) resulted
in a given set. The same procedure was adopted for the
variable ‘knowledge management’ (KM), regarding
the type of membership to a given set observed in the
analysis of its processes (knowledge creation, knowledge
storage, knowledge use, or knowledge dissemination).
For the variables KM, intel, and support of
top management (topman), the calibration process
was established based on the definition of ‘levels of
importance’ of the respective processes and support: non-
important process/support (0.00); minimally important
process/support (0.25); moderately important process/
support (0.50); significantly important process/support
(0.75); totally important process/support (1.00). The
use of abbreviations for the variables helps to understand
and describe the causal configurations.
The variable ‘length of service’ (length) presents
several values and makes up a fuzzy set. Variables with
fuzzy values show the degree to which different cases
belong to a given set, evaluating different degrees of
association between being ‘fully in’ and ‘fully out.’
Such calibration is only possible with theoretical
and substantive knowledge, which is essential for the
specification of the three qualitative breakpoints: full
non-membership, point of maximum ambiguity, and full
membership (Ragin, 2005). Therefore full membership
adherence (0.90) was attributed for 39 years of public
service, full non-membership (0.10) was attributed for
two years of public service, and the point of maximum
ambiguity (0.50) for fourteen years of public service.
Gender (gen) is a binary variable. Regarding the
result ‘quality in decision-making of public managers,’
the calibration process was established by defining the
levels of importance: 0.00 (no quality); 0.25 (poor
quality); 0.50 (average quality); 0.75 (a lot of quality);
1.00 (total quality). Table 4 shows the cuts used in the
calibration for the causal conditions; the calibration
used in this study is presented for each condition.
Table 4. Calibration of conditions (variables).
Conditions and objective Calibration
Knowledge management (KM) (0.00; 0.25; 0.50; 0.75; 1.00)
Intelligence (intel) (0.00; 0.25; 0.50; 0.75; 1.00)
Support of top management (topman) (0.00; 0.25; 0.50; 0.75; 1.00)
Length of service (length) (39; 14; 2)
Gender (gen) Binary variable, 0 = Male; 1 = Female
Quality decision-making of public managers (quali) (0.00; 0.25; 0.50; 0.75; 1.00)
Note. Source: elaborated by the authors. Calibration is the process of classifying the conditions in each case, from ‘full in’ (1.00) to ‘full out’ (0.00). e process implies a
theoretical and empirical knowledge about the variables (Ragin, 2005; 2008).
Analysis of the necessary conditions
Causal conditions are assessed on their need
and sufficiency. The degree of need for the causal
condition indicates its relevance in the process of
achieving a particular result. The degree of sufficiency
demonstrates the extent to which the condition explains
the result obtained (Fiss, Sharapov, & Conqvist, 2013).
For Ragin (2000), needed conditions must present a
consistency value superior to 0.80. When addressing
the needed conditions for the result ‘quality decision-
making of public managers,’ the study found consistency
values superior to 0.90 for men (~gen), support from top
management (topman), knowledge management (KM),
and intelligence (intel), demonstrating the relevance
of these elements. As for the needed condition for the
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absence of the result ‘quality decision-making of public
managers,’ the findings that point to the absence of
support of management (~topman) and to the absence
of knowledge management (~KM) are representative,
presenting a consistency greater than 0.90.
Analysis of causal configurations
Following the best practices in the literature, the
intermediate solutions for the results of the sufficiency
analysis are reported. These solutions are not the most
(parsimonious) nor the least (complex) rigorous (Fiss,
2011; Ragin, 2008). The solutions are sets of causal
configurations of conditions that indicate the alternative
paths that lead to the analyzed result. Conditions may
be ‘core’ and ‘peripheral.’ The first are those conditions
present in both parsimonious and intermediate
solutions. Peripheral conditions are present only in
intermediate solutions (Ragin, 2000, 2008; Fiss, 2011;
Fiss et al., 2013). It is worth stressing that parsimonious
solutions have only the core conditions that are highly
linked to the result, while the intermediate ones are more
conservative and assume the more plausible simplified
hypotheses (Ragin, 2008).
Regarding quality decision-making of public
managers, the results of the sufficiency analysis show
an intermediate solution with a single configuration
with consistency superior to 0.80, complying with
the threshold suggested by Ragin (2008). Regarding
the absence of quality decision-making of public
managers, the intermediate solution shows three causal
configurations with consistency superior to 0.89, also
complying with the threshold established by Ragin
(2008) or Fiss (2011). Such a difference in the quantity
of causal configurations for quality decision-making of
public managers (and its absence) are important results
of the study.
The causal configurations presented in Table 5
show the core and peripheral conditions, both for the
result ‘quality decision-making of public managers’
(quali) and for the absence of this result (~quali).
Regarding quality decision-making of public managers,
the intermediate solution offers a single configuration.
As for its absence, the respective parsimonious solution
shows three intermediate causal configurations. Table
5 considers intel for intelligence, KM for knowledge
management, topman for support of top management,
gen for gender, and length for length of service.
Table 5. Causal congurations.
Causal conguration for quality decision-making of public managers
Causal condition Coverage Consistency
Conguration intel KM topmanst gen lenght Raw Unique
1 0,88 0,88 1,00
Global solution coverage: 0.88; Global solution consistency: 1.00
Causal congurations for the absence of quality decision-making of public managers
1 0,61 0,14 1,00
2 0,64 0,16 1,00
3 0,48 0,09 0,89
Global solution coverage: 0.86; Global solution consistency: 0.93
Note. Source: elaborated by the authors. Black circles (●) indicate the presence of the condition. Blank circles (◌) indicate the absence of the condition. Large circles indicate
core conditions. Small circles describe peripheral conditions. Blank cells indicate that the condition does not contribute to the result (presence or absence).
From the analysis of the configurations, it is
possible to infer that the fsQCA allows the variables to be
causally related in one configuration without necessarily
being related, or even inversely related, in other
configurations. There may be alternative configurations
of causal conditions for both the presence and the
absence of the expected result, and such configurations
reflect the three characteristics of fsQCA: (a) more than
one configuration of causal conditions leads to the
result and to its absence (alternative configurations of
causal conditions); (b) alternative causal configurations
can produce the same result (equifinality); (c) causal
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conditions of the result may differ from the causal
conditions of its absence (asymmetry).
Table 5 allows deducing that the fsQCA produced
only a causal configuration that leads to quality decision-
making of public managers. Such a configuration,
resulting from the intermediate solution, demonstrates
that the combination of processes of intelligence, KM,
support of top management, and the male manager lead
to quality decision-making of public managers. The
first two configurations regarding the absence of quality
decision-making of public managers are symmetrical to
the results obtained from the configuration for quality
decision-making of public managers. These results
are consistent with what was observed in the content
analysis. The combined application of the two data
analysis techniques — content analysis and QCA —
proved to be relevant for the development of the study,
complementing and validating the research. The results
obtained from the analysis of causal configurations are
aligned with the findings of the content analysis and the
inputs obtained from the literature, as discussed in the
following subsection.
Results validation
The evaluation of a qualitative content analysis
must consider its reliability and validity (Duriau, Reger,
& Pfarrer, 2007). Also, “the evaluation criteria for
qualitative and quantitative research must be different”
(Bryman & Bell, 2003, p. 411). For Guba and Lincoln
(2005), it is crucial to follow the principles of reliability
and authenticity — grounded in the constructivism
— in order to guarantee the validity of the analysis
following the principles of reliability and authenticity
borrowed from constructivism. Reliability encompasses
four criteria equivalent to those of quantitative research:
“credibility (which is parallel to internal validity),
transferability (which is parallel to external validity),
reliability (parallel to reliability), and confirmability
(parallel to objectivity)” (Bryman & Bell, 2003, p. 411).
For this study, the researchers digitally recorded
in audio and then transcribed, in full, 17 interviews.
The interviews allowed a full understanding of the
phenomenon researched, validating the literature
review. The initial analysis of the data collected
with the interviews started by identifying relevant
concepts and grouping them into categories (open
coding). Open coding involves examining, comparing,
conceptualizing, and categorizing data. The open coding
process generates concepts that can later be grouped
into categories (Bryman & Bell, 2003, p. 586). The
process was conducted by associating codes and creating
categories and relationships among them. A unique
classification was used for each code, which means that
the categories were mutually exclusive, as recommended
by Weber (1990), to restrict the categories to codes that
unmistakably reflect them, which maximizes validity.
Authenticity was guaranteed (Guba & Lincoln,
2005) based on the participation of several public
managers with different lengths of service, different
functions in the public agency, different areas of specialty,
and different genres. Thus, ontological authenticity was
provided, producing and offering public organizations
a model that clarifies the rationale for quality decision-
making of public managers. This contribution involves
the causal configuration for quality decision-making of
public managers and the causal configuration for the
absence of quality decision-making of public managers.
The validity of the content analysis was assessed
based on data saturation (Finfgeld-Connett, 2014). In
qualitative studies, sampling must be intentional. The
sampling method uses purposive sampling (or judgment,
selective, or subjective sampling), which is a non-
probabilistic sampling, where researchers rely on their
own judgment when choosing members of the population
to participate in their study. The interviews take place
until there is theoretical saturation, i.e., when there are
trivial inputs, and the phenomenon becomes repetitive
(Finfgeld-Connett, 2014). In this way, the sample size
depends on sufficient participation to reach theoretical
saturation. The theoretical saturation was reached after
the 17th interview (Glaser & Strauss, 1967).
The validity of the fsQCA was achieved by
confirming the configurations based on the data. An
example is a configuration for quality decision-making
of public managers found in the speech of interviewee
(I8): “The information and knowledge produced based
on data from the environment qualify decision-making.
These data influence because they bring additional,
complementary elements so that you can make a better
assessment of a particular scenario that involves decision-
making.” This result is in line with the literature, which
points out the importance of knowledge management
and the search for relevant data and information that
qualify decision-making to overcome complex challenges
in government (Gil-Garcia et al., 2013; Johnston &
Hansen, 2011; Wiig, 2002).
Likewise, it was possible to validate the causal
configurations for the absence of quality decision-making
of public managers. One example of these configurations
was observed with the interviewee I10, who stressed that
“many decisions end up having a political bias, and they
are not based on data, information, and knowledge,
which leads to the absence of quality decision-making.”
Interviewee I11 made comments in the same direction,
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saying that public managers sometimes acknowledge the
information to qualify a decision-making process, but
such information is not always used.
As for the third causal configuration, it is worth
mentioning that, for a male manager with little time in
public service, the processes of intelligence and KM are
insufficient to produce the result of quality decision-
making. This finding demonstrates a potential issue
to be further explored in the future since neither the
theoretical review nor the content analysis brought up
issues related to gender and length of service. Therefore,
the relationship between these characteristics and
the analyzed result probably include conditions not
evaluated in this study.
DISCUSSIONDISCUSSION
The literature review presented relevant aspects
regarding the use of intelligence and knowledge
management (KM) in the public sector. These aspects
allowed identifying issues related to the support of top
management, the use of ICT, and people’s participation
as elements that approximate the concepts of intelligence
and KM and public management. It is observed that the
association and application of the process of intelligence
and KM in public management aim, among other
aspects, to promote quality decision-making of public
managers.
The analysis of the data collected from interviews
with public managers shows that, in the public managers’
point of view, there are complementary aspects between
the concepts of intelligence and KM. The analysis also
allowed verifying the perception of public managers
regarding the importance of these processes (intelligence
and KM) in the public context, to examine the existence
of these processes in a structured form when it comes
to public management, and finally, identify paths that
prove to be effective for quality decision-making of
public managers. This objective is in line with the trend
toward a more participatory, efficient, integrated public
administration that provides better public management
in delivering services (Capobiango et al., 2013; Paula,
2005; Secchi, 2009). The public managers interviewed
recognize the importance of such processes for quality
decision-making.
The interviewees recognize the importance of
intelligence and KM processes for public management
but point to a lack of structured KM processes within
the public agencies where they work. The managers
identified some isolated experiences of using such
processes. However, knowledge, in general, is still
rooted in people and knowledge-sharing is based on
relationships among government employees, which must
be a dynamic of concern for public management (Eom et
al., 2016; Gil-Garcia et al., 2016; Johnston & Hansen,
2011; Riege & Lindsay, 2006; Scholl & Scholl, 2014).
Public management receives a large amount
of data and information from the environment, and,
according to the interviewees, there are not enough
staff to carry out the analysis of data and information
about minor demands or irregularities with little social
or financial impact on the state. This point demands
more attention from the top public management since
important insights may be withdrawn from these data to
design public policies.
The qualitative comparative analysis (QCA)
identified paths to quality decision-making of public
managers by using processes of intelligence and
knowledge management — or recognizing their absence.
Such analysis proved to be in line with the literature
and the content analysis, since the QCA indicated that
processes of intelligence and KM, together with the
other factors analyzed, lead to quality decision-making
of public managers.
The three causal configurations found for the
absence of quality decision-making of public managers
represent an opportunity for future studies exploring
the influence of gender and managers’ length of service.
The absence of length of service appears in two of the
three configurations that lead to the absence of quality
decision-making of public managers. However, the study
was unable to identify a cause for this phenomenon,
which may be related to either the lack of training or
the lack of tacit knowledge of the organization and
procedures, both acquired over time in the organization.
Additionally, future studies could examine the
possibility of existing conditions that were not addressed
in this study, and that may influence the quality decision-
making of public managers. Conditions such as training
and staff development can be an interesting path to
study. Finally, it is emphasized that the use of two data
analysis techniques, content analysis and QCA, proved
to be interesting for the development of qualitative
research. The techniques showed to complement and
validate each other.
FINAL CONSIDERATIONSFINAL CONSIDERATIONS
This study provides an original contribution
not addressed in the literature. It presents the causal
configurations that lead to quality decision-making of
public managers (as well as the causal configurations
that lead to the absence of such result) using elements of
C. Melati, R. Janissek-Muniz, C. M. M. Curado
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intelligence and knowledge management (KM) processes
in the context of Brazilian public management. The
findings suggest a path that leads to quality decision-
making of public managers and three others leading to
the absence of this result. These findings demonstrate the
importance of intelligence and KM for quality decision-
making in public administration, considering that data,
information, and knowledge subsidize public managers’
decision-making regarding service delivery and society’s
wellbeing.
The identification of paths leading to quality
decision-making of public managers allows suggesting
procedures to be adopted in governmental agencies
to increase the effectiveness in public management.
However, when identifying and following a path, it
is crucial to maintain the conditions to keep going in
the identified direction, at the same time as seeking
new paths that may be even more effective to achieve
the desired results. Knowing the paths that lead to the
absence of quality decision-making of public managers
represents an opportunity to avoid such configurations
in public organizations and not to incur inappropriate
decision-making.
This study brings a new way of analyzing
conditions and proposing a sufficient path leading to
quality decision-making of public managers. Future
studies may focus on the issue of the influence of gender
and length of service on quality decision-making of
public managers, since the results suggest that there may
be a relationship between gender and length of service
with aspects of trust, regardless of the use of structured
management processes.
Other directions for future research include a
comparative analysis between public agencies with
structured processes of intelligence and KM and those
that do not present such processes. This comparison
would possibly contribute to the analysis of determining
factors of success in the implementation and development
of processes of intelligence and KM to improve decision-
making. This study can also be replicated in the private
sector, examining large and small enterprises, family
and multinational companies, as well as non-profit
organizations.
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Authorship
Claudia Melati*
Universidade Federal do Rio Grande do Sul, Escola de
Administração
Rua Washington Luiz, nº 855, Centro Histórico, 90010-460,
Porto Alegre, RS, Brazil.
E-mail address: cmelati@yahoo.com.br
https://orcid.org/0000-0002-9369-0113
Raquel Janissek-Muniz
Universidade Federal do Rio Grande do Sul, Escola de
Administração
Rua Washington Luiz, nº 855, Centro Histórico, 90010-460,
Porto Alegre, RS, Brazil.
E-mail address: rjmuniz@ufrgs.br
https://orcid.org/0000-0002-0657-6559
Carla Maria Marques Curado
Universidade de Lisboa, Instituto Superior de Economia e Gestão.
Rua do Quelhas, nº 6, 1200-781, Lisboa, Portugal.
E-mail address: ccurado@iseg.ulisboa.pt
https://orcid.org/0000-0002-2608-8982
* Corresponding Author
Funding
ere are no funders to report for this article.
Conict of Interests
e authors have stated that there is no conict of interest.
Copyrights
RAC owns the copyright to this content.
Plagiarism Check
e RAC maintains the practice of submitting all documents
approved for publication to the plagiarism check, using
specic tools, e.g.: ienticate.
Authors' Contributions
1st author: conceptualization (equal); data curation (leader);
formal analysis (equal); investigation (leader); methodology
(equal); project administration (equal); supervision (equal);
visualization (equal); writing - original draft (leader); writing
- review and editing (equal).
2nd author: conceptualization (equal); data curation
(supporting); formal analysis (equal); investigation
(supporting); methodology (equal); project administration
(equal); supervision (equal); visualization (equal); writing
- original draft (supporting); writing - review and editing
(equal).
3rd author: conceptualization (equal); data curation
(supporting); formal analysis (equal); investigation
(support); methodology (equal); project administration
(equal); supervision (equal); visualization (equal); writing
- original draft (supporting); writing - review and editing
(equal).
Peer Review Method
is content was evaluated using the double-blind peer
review process. e disclosure of the reviewers' information
on the rst page, as well as the Peer Review Report, is made
only after concluding the evaluation process, and with the
voluntary consent of the respective reviewers and authors.
Data Availability
All data and materials were made publicly available through
the Mendeley platform and can be accessed at:
Melati, Claudia; Janissek-Muniz, Raquel;
Curado, Carla (2020), “Data for: "Decision-
making quality of public managers:
contributions from Intelligence and
Knowledge Management" published by
RAC - Revista de Administração
Contemporânea”, Mendeley Data, v3.
http://dx.doi.org/10.17632/j4jgpmnp7m.3
