Proceedings of the 8th International Conference on Intellectual ...

Rita Babiliūtė and Kęstutis Kriščiūnas
marine engineering. Wong et al. (2009) notes that <strong>the</strong> above-mentioned knowledge-intensive clusters
are regarded as <strong>the</strong> engines <strong>of</strong> growth at <strong>the</strong> national level, what provides legitimacy for <strong>the</strong> state
support. The success <strong>of</strong> top-down approach largely depends on <strong>the</strong> degree <strong>of</strong> trust that government
institutions manage to induce into <strong>the</strong> upcoming cluster initiative. It means that <strong>the</strong> actors in <strong>the</strong>
system (firms, research bodies, academia, etc.) should already possess quite strong institutional trust.
It does not deny <strong>the</strong> importance <strong>of</strong> personal trust in <strong>the</strong> specific leaders <strong>of</strong> governing bodies, however,
<strong>the</strong> overall trust in institutional environment remains <strong>of</strong> paramount importance. The emergence <strong>of</strong>
successful state initiated clusters is hardly possible when its key actors have no trust in institutional
system.
Most <strong>of</strong> <strong>the</strong> sustainably successful industrial clusters, however, emerge as <strong>the</strong> bottom-up initiatives,
where <strong>the</strong> role <strong>of</strong> <strong>the</strong> state is quite modest. Fromhold-Eisebith and Eisebith (2005) note that <strong>the</strong>
bottom-up approach refers to <strong>the</strong> dynamic aspect <strong>of</strong> <strong>the</strong> cluster, when actors decide to cooperate in
order to draw on certain collective advantages. Usually this process is naturally evolved, when
organizations/entrepreneurs share common experience while at <strong>the</strong> same time developing personal
trust that facilitates business transactions etc. Thus, <strong>the</strong> decision to participate in cluster is determined
by <strong>the</strong> economic rationale <strong>of</strong> participating organizations ra<strong>the</strong>r than some visionary government
initiative. Again it does not deny <strong>the</strong> potential importance <strong>of</strong> institutional trust; however, in <strong>the</strong> case <strong>of</strong>
naturally emerged clusters, <strong>the</strong> individual business logics and inter-personal relations (quite <strong>of</strong>ten,
based on trust in pr<strong>of</strong>essional competence) played key role. For example, in some classical industrial
clusters, such as Silicon Valley, <strong>the</strong> institutional environment had a trigger effect on cluster
development (e.g. Pentagon financing to military radio-electronics research at Stanford or venture
funds found in <strong>the</strong> region), but <strong>the</strong> very fabric <strong>of</strong> cluster was and remains highly dependent on
entrepreneurial initiatives and pr<strong>of</strong>essional inter-personal relations “on <strong>the</strong> shopfloor” level. It is <strong>the</strong>
case when an appropriate institutional environment supports <strong>the</strong> productive inter-personal
interactions.
Trust and <strong>the</strong> type <strong>of</strong> knowledge in industrial cluster
The relative importance <strong>of</strong> inter-personal vs. institutional trust within <strong>the</strong> cluster may depend on <strong>the</strong>
type <strong>of</strong> knowledge that is subject to inter-organizational interaction, which at <strong>the</strong> same time is <strong>of</strong>ten
related to <strong>the</strong> nature <strong>of</strong> <strong>the</strong> specific industry. In this context, Laestadius (1998) makes a distinction
between syn<strong>the</strong>tic and analytical knowledge.
The analytical knowledge prevails in <strong>the</strong> areas, such as biotechnologies, ICT or genetics (<strong>of</strong>ten
referred to as radical innovations), and <strong>the</strong> explicit, codified knowledge is <strong>of</strong>ten <strong>the</strong> main subject to
inter-organizational interaction. The firms maintain both formal and informal relations with R&D
institutions and university research centres (e.g. <strong>the</strong> case <strong>of</strong> Silicon Valley). Therefore, a high degree
<strong>of</strong> institutional trust is important in such kind <strong>of</strong> relations.
The syn<strong>the</strong>tic knowledge, on <strong>the</strong> o<strong>the</strong>r hand, prevails in <strong>the</strong> more traditional industries and leads to
incremental ra<strong>the</strong>r than radical innovations. The industrial knowledge is less codified and less explicit,
<strong>the</strong>re is less formal R&D involvement in inter-organizational relations, while many (incremental)
innovations happen by applying existing knowledge or looking for new combinations <strong>of</strong> “existing
pieces” via trial and error. The relations among actors are thus less <strong>of</strong> an institutional, but more <strong>of</strong> an
inter-personal nature in such type <strong>of</strong> environment.
Along similar lines, Cooke et al. (2004) distinguishes between two types <strong>of</strong> regional innovation
systems (RIS): institutional RIS and entrepreneurial RIS and claims that <strong>the</strong>y differ by a different
degree <strong>of</strong> institutional involvement. The institutional systems are more oriented to science, while
entrepreneurial systems more focus on applied research.
For example, <strong>the</strong> innovative clusters <strong>of</strong> “third Italy” fall into <strong>the</strong> category <strong>of</strong> entrepreneurial systems
and are characterized by <strong>the</strong> predominance <strong>of</strong> strong personal ties. Han et al. (2008) claim that
informal channels held by entrepreneurs play <strong>the</strong> crucial role in <strong>the</strong> process <strong>of</strong> trust building as it
facilitates <strong>the</strong> transfer <strong>of</strong> knowledge around <strong>the</strong> cluster. Ano<strong>the</strong>r relevant aspect is <strong>the</strong> impact <strong>of</strong>
informal collaboration and extensive contact networks that might be <strong>the</strong> precondition for <strong>the</strong>
knowledge communities to emerge. As Preissl and Solimene (2003) highlight, <strong>the</strong> informal information
exchanged within a cluster leads to a quick diffusion <strong>of</strong> new ideas and to dynamic innovation paths,
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