How to measure IC in clusters: empirical evidence
| Pages | 354-380 |
| DOI | https://doi.org/10.1108/14691930610681456 |
| Date | 01 July 2006 |
| Published date | 01 July 2006 |
| Author | Jose Luis Hervas Oliver,Juan Ignacio Dalmau Porta |
| Subject Matter | Accounting & finance,HR & organizational behaviour,Information & knowledge management |
How to measure IC in clusters:
empirical evidence
Jose Luis Hervas Oliver and Juan Ignacio Dalmau Porta
Polytechnic University of Valencia, Valencia, Spain
Abstract
Purpose – The purpose of this paper is to provide a strategic framework and tool to measure and
value intellectual capital (IC) in regional clusters.
Design/methodology/approach – A theoretical cluster strategic framework is presented and
cluster fundamentals are discussed for proper model development. Design methodology was used to
construct a model which achieves the aforementioned purpose.
Findings – The paper provides a comprehensive model to describe, map, measure and value IC on
clusters and systematically control the IC evolution.
Research limitations – Thesystem provided is not an exhaustive use of all the available measures.
A more comprehensive practical application on several clusters would be necessary to validate and
readapt the model.
Practical implications – A very useful tool of information and practical assessment for IC is
provided to cluster agents and policymakers to establish proper strategic initiatives. New ideas about
IC measurement in clusters are provided to academia.
Originality/value – So far, no IC cluster model has been designed. This paper fulfils an IC
measurement model to help individuals involved in clusters, such as mangers, policymakers, etc.
Keywords Intellectualcapital, Cluster analysis, Value chain,Strategic management,
Socio-economicregions, Modelling
Paper type Research paper
Introduction
Clusters are geographic concentrations of interconnected companies and institutio ns in
a particular field (Porter, 1998, p. 78). Industrial districts, as the Italian ones (in Piore
and Sabel, 1984; Pyke and Sengenberger, 1992) are located firms embedded in an
interdependent production process, belonging to interrelated industries and attac hed to
a local community delimited by the diary workplace distance (Sforzi, 1990), as a
specific case of cluster definition[1]. Clusters are a worldwide phenomenon that appear
in Japan (Friedman, 1988), the USA (Scott, 1991), Germany (Herrigel, 1996) and
Netherlands, Finland or Sweden (CEC, 2002), among other countries. Regional
scientists (Brusco, 1986; Bellandi, 1989; Becattini, 1990, 1997; Maillat, 1989) among
others, have highlighted cluster benefits or externalities which have also been
supported in a set of empirical work (Hervas, 2004; Decarolis and Deeds, 1999; McEvily
and Zaheer, 1999) among others.
On the other hand, intellectual capital (IC) research has mainly focuse d on
individual companies rather than on macro-level units such as regions or nations
(Bontis, 2004), to the extent that there are just few works concerned about IC on nations
The current issue and full text archive of this journal is available at
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The authors are really thankful to Dr Jose Maria Viedma, who encouraged them to produce this
article, and to two anonymous referees for their helpful and useful comments.
JIC
7,3
354
Received 17 June 2005
Revised 17 July 2005
Accepted 17 August 2005
Journal of Intellectual Capital
Vol. 7 No. 3, 2006
pp. 354-380
qEmerald Group Publishing Limited
1469-1930
DOI 10.1108/14691930610681456
(Malhotra, 2003; Bontis, 2004; Pasher, 1999; Rembe, 1999; and Edvinsson and Malone,
1997), supra-nations (Andriessen and Stam, 2005) and regions and cities (Viedma, 1999,
2002, 2003; Martins and Viedma, 2004). Moreover, the academia has abandoned the
meso-level, with no IC works focused on regional clusters[2], gap research which
presents and opportunity to scholars and constitutes the purpose of this study. As a
consequence, this article’s objective consists of developing a cluster conceptual
framework and a model to obtain a useful tool to analyze, measure and value the IC
originated within clusters.
Then, why is cluster phenomenon important? Theoretically, the cluster benefits or
externalities are reflected in the following ideas (Porter, 1998, p. 80):
Clusters affect competition in three broad ways: first, by increasing the productivity of
companies based in the area; second, by driving the direction and pace of innovation, which
underpins future productivity growth; and third, by stimulating the formation of new
business, which expands and strengthens the cluster itself. A cluster allows each member to
benefit as if it had greater scale or as if I had joined with others formally – without requiring
it to sacrifice its flexibility.
Building regional clusters is perceived by some practitioners and scholars as the way
to compete globally (Robert Huggins Associates, 2002; Lagendijk, 2000, p. 165;
Commission of the European Communities, 2002; The Competitiveness Institute, 2005 ).
Similarly, the Commission of the European Communities (CEC, hereinafter) (CEC, 2004,
pp. 20-1) enhance clusters benefits by recognizing that clusters drive technology
transfer and innovation. The CEC (2005, p. 23) also reflects the cluster importance by
addressing explicitly in the Integrated Guideline No 15 to achieve the European
strategy known as the Lisbon Agenda[3] that “Member states should focus on ... the
creation and development of regional or local clusters” (CEC, 2005, p. 23).
Nevertheless, why should IC scholars be interested in cluster economies? The reason
is pretty clear: competitive advantage could reside as much in the location as in an
individual firm (Porter, 1990, 1991; Budd and Hirmis, 2004) and thus IC building
competitive advantage for the future relies on both levels. Hence, IC community
interest may also yield in the assumption that the economic externalities bundled in the
cluster are claimed to be knowledge accumulations (Florida, 2002; Storper and
Venables, 2002) or sticky[4] knowledge (Lagendijk, 2000, p. 165) which constitutes
available IC sources at the meso-economic level for located firms which have not been
addressed by IC scholars rather focused on the macro and micro-economic levels.
Moreover, there is empirical evidence that clusters constituted an internal reg ional
element able to explain success and IC in regions (Robert Huggins Associates, 2002).
One of the reasons to focus on clusters, a part from the evidence remarked above
about IC and clusters, is the regional heterogeneity and complexity which does not
permit to focus on indirect mechanisms such as agglomeration economies which may
explain IC drivers within regions. Regions may contain a wide range of industries
involved in different business and at different strategic and market stages. As a
consequence, focus may be diffused and the scope, for an IC model, not well determined
and highlighted. As Budd and Hirmis (2004, p. 1026) explained regions’ competition is
between regional competences and not regional competitiveness per se. In our opinion,
the cluster concept focuses much more on this regional competences scope rather than
the region as a whole and can also be more useful to analyze regional competitiveness
through agglomeration economies in certain industries. Let’s illustrate this idea with a
How to measure
IC in clusters
355
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