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The Performance of Seaport Clusters - RePub - Erasmus Universiteit ...

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250<br />

<strong>The</strong> <strong>Performance</strong> <strong>of</strong> <strong>Seaport</strong> <strong>Clusters</strong><br />

In this thesis a method to delimit clusters is developed, based on two ‘boundaries’ <strong>of</strong> the<br />

cluster: the economic and spatial boundary. <strong>The</strong> method <strong>of</strong> delimitation consists <strong>of</strong> four<br />

iterative steps:<br />

1. Selection <strong>of</strong> a loosely defined specialization <strong>of</strong> the cluster and spatial scope <strong>of</strong> the cluster<br />

analysis, for instance ‘shipbuilding in the North <strong>of</strong> the Netherlands’.<br />

2. Identification <strong>of</strong> the set <strong>of</strong> ‘cluster activities’ based on an analysis <strong>of</strong> relations between<br />

activities with the use <strong>of</strong> input/output data, an analysis <strong>of</strong> the spatial concentration <strong>of</strong><br />

activities, an analysis <strong>of</strong> the structure and membership <strong>of</strong> business associations and an<br />

analysis <strong>of</strong> the composition <strong>of</strong> value chains.<br />

3. Identification <strong>of</strong> the relevant cluster region, based on a concentration analysis.<br />

Municipalities with a percentage <strong>of</strong> cluster firms above a certain minimum are included in<br />

the relevant region.<br />

4. Identification <strong>of</strong> the ‘cluster population’, consisting <strong>of</strong> firms involved in cluster activities<br />

and located in the relevant cluster region.<br />

Variables <strong>of</strong> cluster performance<br />

In this thesis it is argued that the value added created in the cluster is the best performance<br />

indicator. A growth <strong>of</strong> the added value over time shows a cluster is performing well. <strong>The</strong><br />

value added in a cluster changes as a result <strong>of</strong> two effects: an ‘incumbent performance’<br />

effect (changes <strong>of</strong> the value added generated by established firms) and a ‘population effect’<br />

(changes in the value added caused by a changing cluster population because <strong>of</strong> start-up,<br />

entry, exit, and bankruptcy).<br />

A widely accepted theory on relevant variables <strong>of</strong> cluster performance is lacking. In this<br />

thesis, four relevant schools are identified and insights from these schools are used to<br />

develop a sound analytical framework for analyzing cluster performance. <strong>The</strong> first school is<br />

termed ‘the Diamond School’ because the diamond framework (Porter, 1990) is center stage<br />

in this school. This framework encompasses a variety <strong>of</strong> insights relevant for the<br />

performance <strong>of</strong> clusters, but is not precise on variables that influence the performance <strong>of</strong> a<br />

cluster. <strong>The</strong> second school is ‘New Economic Geography’, with Krugman (1991) and Fujita<br />

et al (1999) as leading scholars. This school focuses on explaining the spatial concentration<br />

<strong>of</strong> economic activities.

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