A Gestão do Conhecimento holística: análise de
aderência do modelo de Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns model

The Holistic Knowledge Management: adherence
analysis of the Moscoso-Zea, Luján-Mora,
Cáceres and Schweimanns
model

Fábio Corrêa

https://orcid.org/0000-0002-2346-0187

Doutor em
Sistemas de Informação e Gestão do Conhecimento. Professor Universidade FUMEC
– Brasil. [email-masked]

Dárlinton Barbosa Feres Carvalho

https://orcid.org/0000-0003-3844-0178

Doutor em Informática. Professor
Universidade Federal de São João del-Rei (UFSJ) –
Brasil. [email-masked]

Renata de Souza França

https://orcid.org/0000-0002-3809-0975

Doutora em Sistemas de Informação e Gestão
do Conhecimento. Professora Universidade do Estado de Minas Gerais (UEMG) –
Brasil. [email-masked]

Jurema Suely de Araújo Nery Ribeiro

https://orcid.org/0000-0002-6465-6020

do Conhecimento. Professora Universidade FUMEC – Brasil. [email-masked]

ABSTRACT

The holistic paradigm has been
pointed out for many years as an approach to be considered in the development
of Knowledge Management (KM) frameworks. The Moscoso-Zea,
Luján-Mora, Cáceres and Schweimanns model is a recently developed KM framework,
which cited studies that preach Holistic Knowledge Management (HKM). The
purpose of this research is to analyze the adherence of the framework to the
HKM in order to discern if the management proposed by
this framework has been considered following the holistic paradigm. The
analysis is developed employing mixed methodological procedures, which makes
use of qualitative content analysis and the quantitative approach. The results
show that the analyzed framework only partially adheres to HKM, revealing the
need to develop new frameworks that consider all dimensions together, such as
are presented here. This research contributes by weaving a view that adjusts KM
to the holistic paradigm and by proposing a method to enable the analysis of KM
frameworks using a holistic approach. The analysis of other frameworks,
considering the procedures adopted in this study, is a suggestion for future
research. Thus, other studies may consider the findings of this research for
the development of structures that encompass KM in its entirety within the
organizational scope.

Keywords: Knowledge management; Holistic paradigm; Holistic
knowledge management; Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns; Content analysis.

RESUMO

O paradigma
holístico tem sido apontado há anos como uma abordagem a ser considerada no
desenvolvimento de frameworks de
Gestão do Conhecimento (GC). O modelo Moscoso-Zea, Luján-Mora, Cáceres e Schweimanns
é uma estrutura de GC desenvolvida recentemente, que citou estudos que demarcam
a Gestão do Conhecimento Holística (HKM). O objetivo desta pesquisa é analisar
a aderência desse framework ao HKM a
fim de discernir se a gestão proposta por esse foi considerada mediante ao
paradigma holístico. A análise é desenvolvida por meio de procedimentos
metodológicos mistos, que se valem da Análise de Conteúdo qualitativa e da
abordagem quantitativa. Os resultados mostram que o framework analisado adere parcialmente ao HKM, revelando a
necessidade de desenvolver novos modelos que considerem todas as dimensões dessa
gestão em conjunto. Esta pesquisa contribui ao tecer uma visão que ajusta a GC ao
paradigma holístico e ao propor um método que permite a análise de frameworks mediante a essa perspectiva.
A análise de outros modelos, considerando os procedimentos adotados neste
estudo, é uma sugestão para pesquisas futuras. Assim, outros estudos podem
considerar os achados desta pesquisa para o desenvolvimento de estruturas que
englobem a GC em sua totalidade no âmbito organizacional.

Palavras-chave:
Gestão do conhecimento; Paradigma holístico; Gestão do conhecimento
holística; Moscoso-Zea, Luján-Mora,
Cáceres e Schweimanns; Análise de conteúdo.

Recebido
em 09/12/2020.  Aprovado em 20/02/2021.
Avaliado pelo sistema double blind peer review. Publicado conforme normas da APA

https://doi.org/10.22279/navus.2021.v11.p01-12.1492

1 INTRODUCTION

Knowledge Management (KM) is an emerging field
grounded in research and practice (Bolisani & Handzic, 2015; Scholl, Konig,
Meyer & Heisig, 2004). The research evolves upon
scientific studies considering several perspectives, e.g. (Al-Rasheed &
Berri, 2017; O'Brien, 2017; Serna, Bachiller &
Serna, 2017), which are therefore put into practice in different contexts, such
as enterprise information systems (Oztemel & Arslankaya, 2012), government (Tuamsuk,
Phabu & Vongprasert,
2013), health (Mutuwa & Maiga,
2014; Rojas, Bermudez & Morales, 2013; Sánchez & Dante, 2016) and
education (Bem, Coelho & Dandolini,
2016; Farías, Mercado & González, 2016).

The bond between theoretical research and
organizational practice is established through the development of KM
frameworks. A framework is a schematic representation of reality that aims to
demonstrate the main elements of KM and its interfaces (Heisig,
2009; Wai, Hong & Din, 2011). Some of these elements are people, processes,
and technology (Farías, Mercado & González, 2016;
Sánchez & Dante, 2016). Nevertheless, the rising number of created KM
frameworks is already expressive, thus, fostering the need for research aimed
at understanding the features regarding the plurality of these proposals.

The studies conducted by Holsapple
and Joshi (1999), Rubenstein-Montano, Liebowitz, Buchwalter,
McCawa, Newman and Rebeck
(2001), Heisig (2009) and Fteimi
(2015) analyzed together a total of 270 KM frameworks. The results highlight
that KM demands a broad and unifying framework (Holsapple
& Joshi, 1999; Rubenstein-Montano, Liebowitz, Buchwalter,
McCawa, Newman & Rebeck,
2001) since KM's goal is to implement a holistic approach (Heisig,
2009) that comprehends the elements of this joint management (Fteimi, 2015). Thus, these studies point out the need to
promote the development of KM frameworks from the perspective of the holistic
paradigm.

The KM research background presented by Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns (2016)
cite the research presented by Heisig (2009). As
mentioned before, Heisig (2009) points out the need
to develop holistic KM frameworks. It is also worth mentioning that this framework
is a recent proposal, published in 2016, which leads to the likelihood of
making an incremental development within the state-of-art field of KM. Thus,
both theoretical orientation and temporality instigate the analysis of this
framework based on the holistic KM.

In this context, this research is guided by the
objective of analyzing the adherence of the Moscoso-Zea
framework, Luján-Mora, Cáceres
and Schweimanns (2016) to holistic KM. This analysis
contributes by a) investigating whether the authors have fully minded the
upshots presented by Holsapple and Joshi (1999),
Rubenstein-Montano, Liebowitz, Buchwalter, McCawa, Newman and Rebeck (2001),
Heisig (2009) and Fteimi
(2015); b) reveal how much - in percentile - a recent framework adheres to the
holistic KM paradigm; and c) present a method to enable the analysis of
frameworks before the standings of holistic KM.

Since Holsapple and
Joshi (1999), Rubenstein-Montano, Liebowitz, Buchwalter,
McCawa, Newman and Rebeck
(2001), Heisig (2009) and Fteimi
(2015) did not outline what frames holistic KM, the following section of this
paper describes a theoretical view that fits these perspectives. Therefore, the
methodology is presented to be used for the analysis of the Moscoso-Zea,
Luján-Mora, Cáceres and Schweimanns (2016) to KM framework. In sequence, the
framework is analyzed, and the results are presented. Finally, the conclusion
of this analysis is presented, followed by the bibliographical references used
in this paper.

2 The
Holistic Knowledge Management and its dimensions

According to Thomas Kuhn (2012), a paradigm
consists of a standard of instruments at the disposal of science to address its
problems. The Newtonian-Cartesian paradigm, also called the reductionist
paradigm, was proposed by René Descartes (1596-1650) and Isaac Newton
(1642-1727) and is still the predominant paradigm used in the sciences (Weil,
1991; Capra, 1996; Crema, 2015). This paradigm requires that a phenomenon, or
object of study, must be segmented into parts. Therefore, the parts must be
analyzed and understood in isolation, leading to an understanding of the
phenomenon in its totality (Vergara, 1993; Ferreira, Cardoso, Corrêa & França, 2009). This
allows the research to divide the entire phenomenon into its separate parts in
search of an understanding of the event’s whole (Crema, 1991).

The reductionist approach to science is applied
in several fields. For instance, modularization, as proposed by structured
programming in Computer Science, consists of attacking the problem and dividing
it into parts (tasks) to better develop a solution (Wirth, 1986). The MergeSort ordering algorithm employs the divide-to-conquer
approach and inherently promotes the division of a problem into sub-problems,
for subsequent resolution of these sub-problems in order to
combine their results to achieve the whole goal: the solution of the original
problem (Cormen, Leiserson,
Rivest & Stein, 1990; Ziviani, 2014).

In Administration, organizations are segmented
into parts, such as organizational charts, roles, and specific profiles. People
develop activities, related to their positions and the organizational sector (i.e. parts) to which they belong, guiding the company (i.e.
whole) to the accomplishment of their objectives (Ferreira, Cardoso, Corrêa, & França, 2009). KM,
which contemplates knowledge in the organizational context and presents several
aspects, among them information technology (Skyrme
& Amidon, 1997; Wong & Aspinwall, 2005; Sedighi
& Zand, 2012; Kumar, Singh & Haleem, 2015),
operates in a fragmented business context and also
assumes the traits of this paradigm. The KM adjusts hard aspects (coding,
interface mediated by information technology) and soft (personalization,
personal interface) and splits them into dimensions such as organizational
culture (Al-Mabrouk, 2006; Lin & Lin, 2006; Gai & Xu, 2009; Valmohammadi, 2010), strategy (Skyrme
& Amidon, 1997; Al-Mabrouk, 2006; Lin & Lin, 2006; Gai & Xu, 2009)
and processes (Skyrme & Amidon, 1997; Serna, Bachiller & Serna, 2017; Wong & Aspinwall, 2005; Zieba & Zieba, 2014), to name
a few.

However, researchers (Weil, 1991; Capra, 1996; Flach & Behrens, 2008; Maciel
& Silva, 2008; Crema, 2015; Pereira, 2018) point out that the reductionist
paradigm is insufficient to deal with contemporary and future problems, since
these are more intricate than in the past, such as during the time of Descartes
and Newton. The reason is that understanding the isolated parts allows one to
understand the full object of study, but not the object in its entirety because
the connections between the parts also constitute part of the whole. Thus, the
holistic paradigm appears as a better approach for current science inquiries.

The holistic paradigm states that the parts -
fragmentation is admitted - must be analyzed together for the next connections
to be well-preserved (Vergara, 1993; Capra, 1996). Thus, it becomes possible to
understand the phenomenon in its completeness, since the connections between
the parts also constitute the whole and form the integral, the total, the holos of the phenomenon (Pereira, 2018). While reductionism
allows us to understand the full object of study, holism promotes the
comprehension of the whole object of study in its absolute completeness, since
the connections between the parts are considered within this paradigm (Crema,
2015).

In the scope of KM, the holistic paradigm
announces that this management must consider its dimensions (parts) together.
Emphatically, Heisig (2009, p. 16) pointed out:
“Isolated efforts [...] which only address one KM activity [...] and only one
critical success factor like ‘information technology’ are considered
insufficient. Moreover, the goal of KM is to implement a holistic approach
towards the management of organisational knowledge”.
In other terms, it consists of KM frameworks that address “[…] different
elements of KM, which should be considered together” (Fteimi,
2015, p. 5).

Establishing the dimensions of holistic KM is a
problem that has been tackled by many researchers since the 1970s. The Critical
Success Factors perspective is handy to delineate these dimensions, being
employed by most of the studies found in the literature. According to Rockart (1979), Critical Success Factors are areas of the
organization that drive it toward successful organizational performance. These
are the dimensions (i.e. areas) critical to KM's
success.

Accordingly, if a dimension is critical to the
success of organizational KM, then it is a part of the whole of its management.
All critical dimensions to KM's success together make up the whole of holistic
KM (Fteimi, 2015). To identify such dimensions, we
carried out a systematic review of the literature on the SCOPUS database, using
the terms “knowledge management” and “critical success factors”. Of the 48
studies returned, 8 were publications unavailable for download, 1 was a
duplicate study, and 24 do not theoretically support the presented Critical
Success Factors. Another 3 publications were added to the corpus of analysis
because the remaining 15 studies frequently cite them. The 18 publications,
dating from 1997 to 2015, were investigated resulting in 13 critical dimensions
to the success of KM, which according to Fteimi
(2015) should be considered together, namely:

Strategy: consists of the organization's current vision for its long-term goals
and objectives (Davenport, De Long & Beers, 1998). Regarding this, the KM
should be aligned with the organizational strategy and clarified to members of
the organization. As for alignment, the KM strategy should support the strategic
objectives of the company through a value proposition (Al-Mabrouk, 2006), even
though the value cannot be directly calculated (Skyrme
& Amidon, 1997). Furthermore, the KM strategy should be clarified so that
the members of the company understand their purpose and support KM towards
achieving their organization's strategy (Wong, 2005; Lin & Lin, 2006; Gai
& Xu, 2009);

Leadership and support
of senior management: leaders and top management act as
a mainstay which supports KM's proposal (Wong, 2005). Thus, they should support
KM by words, acts, and examples of the organization’s intention to its members
(Gai & Xu, 2009; Valmohammadi, 2010; Wai, Hong
& Din, 2011). They should understand the concept of KM, homogenize its
message and encourage its activities (Zieba & Zieba, 2014), as well as provide financial, moral, time and
targeting of necessary knowledge to be managed (Davenport, De Long & Beers,
1998; Al-Mabrouk, 2006; Arif & Shalhoub, 2014; Kumar, Singh & Haleem, 2015);

KM team: results in a team of professionals to promote KM in the organization
(Davenport, De Long & Beers, 1998). These have specific roles (Wong &
Aspinwall, 2005; Valmohammadi, 2010), as Chief
Knowledge Officer (Davenport, De Long & Beers, 1998), and responsibilities
(Arif & Shalhoub, 2014)
like establishing knowledge processes (Lin & Lin, 2006), coordinating,
managing (Gai & Xu, 2009) and defining the direction to be reached by the
KM proposal (Wong, 2005);

Resources (financial,
human, material and time): any business initiative needs resources (Lin & Lin, 2006). Within
KM, financial resources are needed to obtain specific technological systems (Abbaszadeh, Ebrahimi & Fotouhi,
2010; Al-Mabrouk, 2006) and to maintain the KM team (Wong, 2005). Also, a site
for installation (Kumar, Singh & Haleem, 2015), materials, such as
computers and other physical items and infrastructure (Sedighi
& Zand, 2012), time for people to share their
knowledge and other activities regarding this matter (Al-Mabrouk, 2006) are
also required for the success of KM initiatives;

Processes and
activities: they are the core of KM (Sedighi & Zand, 2012) for
directing members of what to do with knowledge (Abbaszadeh,
Ebrahimi & Fotouhi, 2010). Some examples, such as
identification, storage, sharing and creation of knowledge are adopted in
frameworks (Wong, 2005; Anggia, Sensuse,
Sucahyo & Rohajawati,
2013) and have characteristics, usually non-linear (Valmohammadi,
2010; Sedighi & Zand,
2012). These should be integrated into the daily flow of work to be performed
by individuals (Gai & Xu, 2009; Abbaszadeh,
Ebrahimi & Fotouhi, 2010);

Human resources
management: the management of human resources
is vital for KM since it acts together with knowledge holders (Valmohammadi, 2010; Sedighi &
Zand, 2012). Thus, the processes of recruitment (Wong
& Aspinwall, 2005; Wong, 2005), development (Wong, 2005; Kumar, Singh &
Haleem, 2015) and retention (Wong, 2005) of employees act as a pillar for KM (Abbaszadeh, Ebrahimi & Fotouhi,
2010), as they provide the company with individuals who possess knowledge
relevant to organizational purposes;

Training and education: KM's vocabulary disengages from the
conventional, for instance, making a distinction amongst data, information, and
knowledge (Davenport, De Long & Beers, 1998). Thus, employees should be educated
to standardize concepts (Akhavan, Jafari & Fathian 2006; Al-Mabrouk, 2006), lexicon, message, roles to
be performed by the KM team (Wong, 2005) and their purpose in this management
(Davenport, De Long & Beers, 1998). Employees should be trained with the
required skills to develop their activities (Anggia, Sensuse, Sucahyo & Rohajawati, 2013), such as handling knowledge-driven tools
(Abbaszadeh, Ebrahimi & Fotouhi,
2010) and preparing a promising field for them to participate in KM (Sedighi & Zand, 2012) effectively;

Motivation: consists of the establishment of rewards for employees to engage and
practice KM (Al-Mabrouk, 2006; Lin & Lin, 2006), which is a challenge
(Davenport, De Long & Beers, 1998). Such incentives may consider rewards (Valmohammadi, 2010) through awards (Davenport, De Long
& Beers, 1998), recognition for sharing good ideas, as done in Buckman
Laboratories (Davenport, De Long & Beers, 1998; Wong & Aspinwall,
2005), or valuation of the individual through career paths (Zieba
& Zieba, 2014);

Teamwork: consists of the gathering of two or more individuals, who influence
themselves and interact (Wai, Hong & Din, 2011) and cooperate for a common
purpose. Teamwork raises the potential of KM processes and activities (Sedighi & Zand, 2012) and  it is a fruitful
way to create, share, (Wai, Hong & Din, 2011) and exchange knowledge by
promoting the development of organizational knowledge (Akhavan,
Jafari & Fathian, 2006). It is worth noting that
KM does not eradicate individual work, but recognizes the potential of the
union of individuals through common goals (Sedighi
& Zand, 2012);

Culture: it is composed of parameters for values, norms and social customs that
shape the way people behave (Al-Mabrouk, 2006). Within the KM, a desirable
culture should foster knowledge sharing (Davenport, De Long & Beers, 1998)
and admission of error (Wong, 2005) in order to create
a degree of trust between individuals (Gai & Xu, 2009; Valmohammadi,
2010). This culture tends to establish a collaborative environment (Lin &
Lin, 2006) for the appraisal, creation, sharing, and application of knowledge
in the organizational scope (Al-Mabrouk, 2006);

Information technology: by the technical aspect, technology is a means by which explicit
knowledge tends to be stored (Wong & Aspinwall, 2005) and shared in the
organization (Anggia, Sensuse,
Sucahyo & Rohajawati,
2013), by the use of a database, intranet (Sedighi & Zand, 2012) and
internet (Kumar, Singh & Haleem, 2015). This social aspect, including
technology, such as video conferencing and telephones, acts as an element of
connection between individuals for the sake of tacit knowledge (Skyrme & Amidon, 1997; Wong & Aspinwall, 2005; Sedighi & Zand, 2012; Kumar,
Singh & Haleem, 2015). However, this dimension must be understood as a
means to KM and not as a definitive solution (Abbaszadeh,
Ebrahimi & Fotouhi, 2010; Valmohammadi,
2010);

Measurement: measuring is required in order to assess the
fulfillment of objectives and gauge the progress of KM (Valmohammadi,
2010; Kumar, Singh & Haleem, 2015). It comprises establishing measurable
goals for further measurement (Lin & Lin, 2006), usually defined by
financial indicators or metrics, as well as acceptable non-financial
measurements (Gai & Xu, 2009) due to the intangibility of knowledge. Some
measurements make use of organizational diagnoses (Akhavan,
Jafari & Fathian, 2006) and the valuation of
knowledge. Regarding the latter kind of measurement, notable efforts are being
employed by the field of study called intellectual capital (Al-Mabrouk, 2006; Sedighi & Zand, 2012);

Pilot Project: this regards the introduction of KM in a smaller organizational scope in order to obtain lessons learned and best practices,
aiming at the extension on a broader business scope (Skyrme
& Amidon, 1997; Akhavan, Jafari & Fathian 2006). The initiatives made by Microsoft, Hewlett-Packard and BP Exploration (oil segment), according
to Akhavan, Jafari, and Fathian
(2006), used pilot programs that, after testing at a smaller scale, enabled the
deployment of the KM to the full organizational scope.

Therefore, the previously consolidated
dimensions constitute the critical parts to the success of holistic KM that
should be considered together in a KM framework. These dimensions are addressed
in the analyses of Moscoso-Zea, Luján-Mora,
Cáceres and, Schweimanns
(2016). The methodological procedures used in this examination are presented in
the following section.

3 METHOD

In order to examine of the Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns framework (2016), Content Analysis (Bardin,
1997) is employed. Content Analysis allows a scientific production to be
examined in order to make inferences and quantify
elements identified in the text. In this method, the first step is to define a
registration unit, which is the element to be investigated by the examination
of the scientific production. In this research, the registration units are the
dimensions of the holistic KM (HKM), presented in the previous section.

The application of this method has two phases.
In the first one, the article with the Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns (2016) framework definition is read as a whole,
aiming to identify the presence or absence of HKM dimensions. By using a
qualitative interpretive approach, the subjectivity of the researcher is
admitted (Creswell, 2014). However, for the results to be trustworthy, direct
citations are used as a way to allow the reader to
understand the inferences made. Thus, the application of the method emphasizes
the methodological rigor indicated by Flick (2014), which allows for checking
of the results.

In sequence, we identified the dimensions of
the HKM in the framework, and these are analyzed by the quantitative approach
(Creswell, 2014). This approach is based on the use of mathematical techniques.
In this research, the HKM dimensions are quantified as a percentile in order to show the degree of adhesion of this framework to
HKM. Thus, this result reveals its adherence to the HKM perspective, pointed
out as required to be considered in the development of KM frameworks.

In summary, the Moscoso-Zea,
Luján-Mora, Cáceres and Schweimanns (2016) framework is examined using a
Qualitative Content Analysis, in order to identify the
existence or absence of the HKM dimensions. Subsequently, these dimensions are
quantified to obtain the percentage of adhesion of this framework to HKM. Thus,
these procedures - interpretive reading and percentile calculations,
respectively - are manual in nature.

The justification for the analysis of this
framework is based on two related aspects, theoretical orientation
and temporality. The theoretical orientation is based on the
fact that Moscoso-Zea, Luján-Mora,
Cáceres and Schweimanns
(2016) cite Heisig (2009) in their proposed
framework. Heisig (2009) points out the need to
develop HKM frameworks. Furthermore, the KM framework development is based on
Enterprise Architecture (EA), in which the authors state “EA addresses the need
to manage increasing complexity and deal with continuous change by providing a
holistic view of the organization, including their organizational components
and their relations” Moscoso-Zea, Luján-Mora,
Cáceres & Schweimanns,
2016), p. 245, authors' underlining).
Therefore, it is plausible to infer that Moscoso-Zea,
Luján-Mora, Cáceres and Schweimanns (2016) are guided by this feat. As for
temporality, this framework was published in 2016, which refers to the
possibility that it presents an evolution concerning what has already been done
in the KM field. Thus, both theoretical orientation and temporality instigate
the analysis of this framework before the HKM.

Besides, it is worth noting that the results,
coming from the analysis of this framework, are not intended to grant credit or
discredit to it. It is only sought to understand if new frameworks of KM have
been tackling the need to approach this research field from the perspective of
the holistic paradigm, pointed out as essential for success in KM.

4 ANALYSIS AND RESULTS

Moscoso-Zea, Luján-Mora, Cáceres
and Schweimanns (2016) assert that the frameworks, considering  their
proposal,  “[…] have not been well
explained in terms of how to implement them in practice to cover all KM
dimensions” (Moscoso-Zea, Luján-Mora,
Cáceres & Schweimanns,
2016, p. 244). By this statement the authors are
attempting to “[…] present a KM framework which can be used in practice to
capture, use and transfer knowledge” (Moscoso-Zea, Luján-Mora, Cáceres & Schweimanns, 2016, p. 245), claiming it as a proposal that
might serve as a guide for organizations.

The researchers' framework addresses the types
of tacit and implicit knowledge along with the dimensions of people (1),
processes (2) and technology (3). Explicit knowledge is one that can be formulated,
documented and reproduced; while “Implicit knowledge
also known as tacit knowledge is knowledge that is difficult to document or
formulate, and is normally associated with human knowledge” (Moscoso-Zea, Luján-Mora, Cáceres & Schweimanns, 2016,
p. 247, authors' underlining), treating implicit knowledge as tantamount to
tacit, thus diverging from the perspective of Nickols (2000) e Grant (2007).

The people dimension (1) clarifies that
individuals are the knowledge holders and the mainstay of KM. The authors'
framework is careful to “[…] capture and to transfer knowledge from people in
organizations” (Moscoso-Zea, Luján-Mora,
Cáceres & Schweimanns,
2016, p. 246). The process dimension (2) reflects on how people perform their
activities in the organization and merge with technology because it is a way
that supports individuals in their tasks (Moscoso-Zea,
Luján-Mora, Cáceres & Schweimanns, 2016).

The technology dimension (3) consists of the
Enterprise Architecture (EA) and Business Intelligence (BI) elements. The
authors point out that EA aims to optimize organizational processes and support
business strategy, adopting the following definition: “EA is defined as ‘a
coherent set of principles, methods and models that are used in the design,
realization and maintenance of an enterprise’s business architecture,
organizational structure, information architecture and technology architecture
with respect to the corporate strategy” (Moscoso-Zea,
Luján-Mora, Cáceres & Schweimanns, 2016, p. 244). BI is understood as

[…] the conversion of organizations resources to knowledge. It is the
data mining and the integration of information from corporate data warehouses
to produce large amounts of information needed for effective decision
making process and for planning strategically to achieve a competitive
advantage in its industry. (Moscoso-Zea, Luján-Mora, Cáceres & Schweimanns, 2016, p. 244-245)

By means of the conjunction of these dimensions
and types of knowledge, Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns (2016) argue that their framework “[…] details
how a KM implementation should be done in order to capture explicit and
implicit knowledge” (Moscoso-Zea, Luján-Mora,
Cáceres & Schweimanns,
2016, p. 244) by printing a procedural order to be followed to achieve the
above. The KM processes set to the framework, adhering to the dimension
"Processes and activities" of holistic KM, are at the core of KM (Sedighi & Zand, 2012) because
they state what can be done with knowledge (Abbaszadeh,
Ebrahimi & Fotouhi, 2010). In the Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns (2016)
model, such processes are production (a), collection (b), presentation (c) and
use (d) of knowledge.

Implicit knowledge is produced (a) by the
people who conduct the organization's processes. The production of knowledge
(a) is not described by Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns (2016) in order to
demonstrate how such knowledge is created, as done in the proposal of Nonaka
and Takeuchi (1995), which deals with the process of knowledge creation and
presents tools for its operationalization. Thus, the analyzed framework assumes
that knowledge is produced by people and serves as input to the next step: collection
step.

This knowledge is collected (b) by BI
technology and EA. Mosctheoso-Zea, Luján-Mora, Cáceres and Schweimanns (2016) do not clarify how this collection
happens, because since the technological devices capture the tacit knowledge,
people must articulate it somehow in order to be
processed by the BI tools and EA. As in the production process (a), the
collection process (b) is obscure in the framework. Regardless, the framework
model’s description implies two methods of knowledge collection: technological
tools can extract information from other technological systems or receive them
through manual input made by people.

In both situations, there would be a knowledge
externalization process involved. In the former, the individual would have to
articulate his knowledge in a format to be inputted into the system manually.
In the latter, the same should be done, but in another system. Thus, the
technological integration enables collection of the knowledge, stored as
information, by the BI tool, for example. Briefly, the processes of production
(a) and collection (b) are not prescribed and do not indicate, in their
description, actions that could be done to create or capture knowledge.

The core of the Moscoso-Zea,
Luján-Mora, Cáceres and Schweimanns (2016) framework is the technology dimension
(3). Since technology is a medium whereby explicit knowledge tend to be stored
(Wong & Aspinwall, 2005) and shared in the organization (Anggia, Sensuse, Sucahyo & Rohajawati, 2013), through the use of a database, intranet (Sedighi
& Zand, 2012) and internet (Kumar, Singh &
Haleem, 2015), regarding the technical aspect, the framework adheres to the
"Information technology" dimension of HKM.

Once knowledge is captured (b), it is processed
by the BI and EA. Both tend to allow for knowledge discovery in databases. BI
employs the Extraction, Transformation, and Loading (ETL) process in order to extract data from other systems, treat it and
upload it to a data center for analysis. In EA, a scanned document can be
captured by this tool and translated into outlines that "[…] describe
organizational structures (people), business processes, applications
and technological infrastructure" (Moscoso-Zea, Luján-Mora, Cáceres & Schweimanns, 2016, p. 247).

Thus, technology, through the
use of BI and EA tools, nurtures the diagramming of explicit knowledge
for its visualization in different perspectives. In order to
visualize this knowledge, Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns (2016) emphasize that a technological system of
KM can be useful in this sense. The use of BI, EA, and a KM technology system
converges with the combination process of the Nonaka and Takeuchi (1995) SECI
framework; however, Moscoso-Zea, Luján-Mora,
Cáceres and Schweimanns
(2016) do not present an association of the process of these technologies with
the SECI combination phase.

After transformation of the data processed by
technological means, the presentation (c) of this knowledge can be visualized
through reports and panels, in an explicit format. So, this knowledge can be
used (d) by the people and processes of the organization as support in the
decision making, for instance, restarting the iterative cycle of the framework
(Moscoso-Zea, Luján-Mora, Cáceres & Schweimanns, 2016).

Moscoso-Zea, Luján-Mora, Cáceres
and Schweimanns state that their framework “[…]
details how a KM implementation should be done in order to capture explicit and
implicit knowledge” (Moscoso-Zea, Luján-Mora,
Cáceres & Schweimanns,
2016, p. 244, authors' underlining). This clarification is not presented
transparently, since the production process (a) of the tacit knowledge by the
people, as well as their collection (b) by the technology, are obscure in the
analyzed framework. The framework presentation mainly discusses the role of
technology in information processing for the discovery of knowledge and through
the processes of the framework. It assumes that explicit knowledge is present
in all phases, being derived from the tacit knowledge, which is not directly
addressed in the study.

The authors conclude that “[…] the use of BI
and EA tools bridges the gap of capturing all the knowledge dimensions” (Moscoso-Zea, Luján-Mora, Cáceres & Schweimanns, 2016,
p. 248), with the dimensions of people, processes, and technology. This
statement is rather comprehensive. From the technological point of view, one
can even raise this as a hypothesis to be investigated, but on the KM side, in
which people, processes, strategies, among other dimensions are considered,
this statement presents itself as premature.

Finally, the Moscoso-Zea,
Luján-Mora, Cáceres and Schweimanns (2016) model results in a strictly
technologically focused approach that orchestrates and describes how BI and EA
technologies can be useful for the discovery of knowledge. In synthesis, the
framework presents the following holistic KM dimensions:

Strategy: no;

Leadership and support
of senior management: not specified;

KM team: not specified;

Resources (financial,
human, material and time): not specified;

Processes and
activities: yes. Production, collection,
presentation and use;

Human resources
management: not specified;

Training and education: not specified;

Motivation: not specified;

Teamwork: not specified;

Culture: not specified;

Information technology: yes. Framework core;

Measurement: not specified;

Pilot Project: not specified.

As shown previously, the Moscoso-Zea
framework, Luján-Mora, Cáceres
and Schweimanns (2016) has a technological focus.
However, the authors point out that the model addresses all dimensions of
knowledge and provides a holistic view, including its organizational components
and relationships. What can be seen is that the framework presented tends to
address the whole of the Information technology dimension, but not the whole of
KM, made up of 13 dimensions, which includes technology.

From this point of view, the presented holistic
perspective is grounded on the technological aspect, missing better treatment
of the other dimensions critical to the success of holistic KM. A consequence
of this approach is failing to achieve corporate objectives. For instance, the
strategy alignment regarding the organizational with the KM (Skyrme & Amidon, 1997; Al-Mabrouk, 2006) is imperative
to let the KM support the corporate goals. Besides, this alignment must be
clarified to the staff (Wong, 2005; Lin & Lin, 2006; Gai & Xu, 2009),
so the KM objectives can be achieved and, consequently, those of the
organization.

Furthermore, the leadership and support of
senior management act as a means of sustaining KM (Wong, 2005), through
resources such as financial, moral, time and strategic knowledge targeting to
be managed (Davenport, De Long & Beers, 1998; Al-Mabrouk, 2006; Arif & Shalhoub, 2014; Kumar,
Singh & Haleem, 2015). Thus, the dimensions “Leadership and support of
senior management” and “Strategy” constitute vital dimensions for the success
of KM. Neglecting a proper treatment for them leaves the KM incomplete,
regarding the precepts of the HKM, not contemplating all the critical
dimensions for the success of this form of management.

Considering the analysis conducted on the Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns (2016),
the above-weighted dimensions are presented in Fig. 1, which expresses the
adhesion of the framework to the dimensions of the holistic KM established by
this research. The presence of a dimension places it on scale 1 (outer edge) of
the graph, and its absence marks it on the scale 0 (center).

Figure 1. Adherence of the Moscoso-Zea,
Luján-Mora, Cáceres and Schweimanns framework (2016) to the holistic Knowledge
Management.

Source: The authors.

Therefore, the Moscoso-Zea,
Luján-Mora, Cáceres and Schweimanns (2016) framework includes the dimensions
"Processes and activities" and "Information technology,"
denoting that 15.4% (2 of the total of 13 dimensions) adhere to the holistic KM
framework, according to the presented characterizations in this paper.

5 CONCLUSION

This research was conducted with the intent to
analyze the adherence of the Moscoso-Zea, Luján-Mora, Cáceres and Schweimanns framework (2016) to the holistic KM. First, the
theoretical fit of KM in relation to the holistic paradigm was developed in order to characterize this form of management and to
highlight the dimensions to be contemplated in a framework based on this
paradigm. Through mixed methodological procedures, which made use of the
qualitative content analysis and the quantitative approach, the degree of
adhesion of the framework to holistic KM was assessed.

As a result, the analyzed framework adheres in
15.4% to the dimensions of holistic KM. This result announces that the holistic
framework gap has not yet been filled. However, this result is not conclusive
in this announcement, since there is a need for
analysis of other frameworks for a more consistent finding. At this point, this
research contributes from three perspectives.

The first, to investigate whether the academy
has been accepting the conclusions of studies that point to the holistic
paradigm as necessary to the development of KM frameworks. In this perspective,
we find the need for continuity of research that intends to develop
comprehensive frameworks that together consider all the dimensions of holistic
KM presented in this research. Although the analyzed framework took into account a holistic view in its development, the
theoretical background focused on technology only enabled the development of a
comprehensive solution to a part of the whole according to a broader
perspective of HKM such as presented in this research.

The second contribution is related to the
percentage view of how much the framework adheres to KM's holistic paradigm. In
this perspective, the proponents of the framework, dating from 2016, as well as
other researchers, can take care that their proposals are positioned more
solidly on these KM dimensions.

The third contribution is the presentation of a
method to promote the analysis of frameworks considering the imperative of
holistic KM. In this perspective, other researchers can make analyzes,
considering the methods presented in this research, in order
to reveal a broader perspective of how well KM has been developed for a
holistic approach. Thus, the analysis of other frameworks is a suggestion for
future research.

It is worth noting again that there is no
attempt, from this research, to grant merit or demerit to the framework. Developing
a framework is a challenge since there are several organizational aspects to be
considered in the knowledge-oriented negotiations. Therefore, the proposition
of a framework already stands as a contribution. However, it is necessary to
contemplate knowledge in its whole, this being a difficult requirement for
successful KM in the various contexts of its application.

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