A rational approach to identify and cluster intangible assets. A relational perspective of the strategic capital

Date12 October 2015
Pages809-834
DOIhttps://doi.org/10.1108/JIC-06-2015-0050
Published date12 October 2015
AuthorFranco M. Battagello,Michele Grimaldi,Livio Cricelli
Subject MatterInformation & knowledge management,Knowledge management
A rational approach to identify
and cluster intangible assets
A relational perspective of the
strategic capital
Franco M. Battagello
Department of Enterprise Engineering,
University of Rome Tor Vergata, Rome, Italy
Michele Grimaldi
DIMSAT, University of Cassino and Southern Lazio, Cassino (FR), Italy, and
Livio Cricelli
DICEM, University of Cassino and Southern Lazio, Cassino (FR), Italy
Abstract
Purpose This study is intended to work out a bottleneck in the comprehension of the relational
nexus which links the set of key strategic resources (SRs) of a company, represented by the uncertain
recognition and the ambiguous clustering of their intangible components. The purpose of this paper is
to provide a candidate solution for a rational appraisal of the inventory of the knowledge-based
resources held by a company, which synergically form its Intellectual Capital (IC).
Design/methodology/approach This goal is achieved by the means of a qualitative/quantitative
approach composed of sequential phases, intended to: atomize the value domain of the firm into its
basic building blocks; gauge their mutual interactions and impacts; re-aggregate those involved
entities accordingly; cluster them into a collection of identified and validated Intangible Assets (IAs).
Never giving any direct judgment on the IAs themselves (whose extension can be fuzzy or unknown).
But on the impacts between the value drivers they are built on.
Findings The proposed procedure, step-by-step illustrated by means of a numerical simulation, out
of the amorphous mass of the SRs, returns an analytic picture of its composing elements keeping track
of their intertwined connections and mutual influence. Consequently, allowing the comprehension of
the actual framing and of the relational positioning and magnitude of such entities.
Practical implications This risk-mitigated rational identification of IAs allows the analyst to
target a proper evaluation technique on them. And the management of the company to mindfully
allocate/leverageon them to improve businessperformance and strategyalignment. The implementation
returns some analytic tools which render a diagnostic snapshot of the composing elements of the IC,
increasing the awareness of such entities and allowing internal/external benchmarking.
Originality/value The suggestedmethodology mitigatesthe risk of discretionality inthe definition of
the perimeter of each target-entity, by avoidingany direct biased judgment on them. So that each asset
gets unambiguously identified within a network-logic and the interlinkedportfolio of knowledge-based
resources can be assessed and managed in an rational and traceable way.
Keywords Clustering, Intellectual capital, Business valuation, Intangible assets portfolio,
Relational benchmarking, Strategic capital
Paper type Research paper
1. Introduction
Every company in the world is characterized by a unique blend of resources and, at the
same time, by the peculiar way it exploits them as a whole. Indeed, through their proper
allocation, deployment and management, each company achieves its business goals in
alignment with the traced strategy so that they are actually utilized as the key to create
Journal of Intellectual Capital
Vol. 16 No. 4, 2015
pp. 809-834
©Emerald Group Publis hing Limited
1469-1930
DOI 10.1108/JIC-06-2015-0050
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1469-1930.htm
809
Perspective of
the strategic
capital
value and gain competitive advantage. Such entwined collections of strategic resources
(SRs), once put in use, represent a proxy of companiesdistinctiveness, as highlighted
by the resource-based view (RBV) (Penrose, 1959; Wernerfelt, 1984). Furthermore, the
knowledge-based view (KBV) (Grant, 1996) considered critical for competitiveness
a sub-set of SRs, characterized by knowledge-nature and knowledge-processes. From a
resource standpoint, the KBV identified the Intangible Assets (IAs) as the main
knowledge-basedsource of value creation and performance. It is due to the intrinsic
value of the knowledge substratum that they embody and vehicle throughout the value
system of the organization, that such resources can play a starring role among the SRs
for gaining competitive advantage (Itami, 1987; Roos et al., 1997).
Nevertheless, it is also true that each set each blend of resources physiologically
comes with different mut ual relations among its co mponents. And differen t
implications about the way each company creates value through them (Starovic and
Marr, 2003). Therefore, their proper appraisal is a critical crucial, actually point for
their subsequent successful management, since it should be capable of appreciating
their interlinked relations.
And, what is more, the issues around any consistent valuation of IAs find their
origin in a previous logic step: in their propaedeutic identification that should be
unambiguous and rational and in their proper framing within the very fabric of the
organization. When it comes to their assessment, a great benefit could be represented
by the fact of avoiding the use of preset definitionsfor each target IA. This is because,
regardless of their possible comparable names, they could represent something even
extremely different among each company in which they are nurtured. The multiplicity
of interrelations among them and the role they play (in concert with all the other
key-resources), for a specific company operating in a specific business, make a sensible
difference in defining their essence. Therefore, if any auditing/assessmen t process of
the IAs starts with such out-of-focus assumptions deriving from the use of generic
definitions, it is quite subsequent that the entire appraisal will be jeopardized. The risk
is to obtain biased and distorted findings, caused by overlaps/mismatches, under/over
esteems, redundancies/omissions.Therefore not because of thechoice of an inappropriate
evaluation technique, but simply because of an inaccurate targeting of the entities to be
assessed, upstream (Brugger, 1989; Collis, 1994).
Traditional approaches that can be found both in literature and in practice appreciate
the IAs always considering them as previously definedconstructs, using logic categories
which are formed and labeled before the assessment-process itself. Therefore using some
ex machinacriterion, detached from any real-case specificity. Furthermore, they hardly
factor adequately the knowledge dynamics which first originated and now link them
(Estivill-Castro, 2002; Choong, 2008; Ferenhof et al., 2015). This could provoke a major
chain-effect error: when starting a new assessment, the analyst just takes the intangible
entity to be estimated for granted, never questioning about its real nature and the mutual
relations it builds with other intangibles. The common use of preset categories reflects a
common top-down wise thinking, but which just leads to a common risk: if there is any
mis-recognition error on the entities to be studied at the very beginning of the analysis, this
will be inherited to the conclusions and unavoidably affect them.
Would not it be worthier using an unbiased identification solution for such resources
in the first place? A qualitative/quantitative one, that allows even the tracking of their
clustering, in order to secure, at least, from the risk deriving from the use of preset
categorizations. Furthermore, a reliable candidate solution should be also built around
some less fuzzy criteria, than outlining the shape of such intangible aggregates from
810
JIC
16,4

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