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13 CONCLUSIONS FOR ANALYZING CLUSTERS This chapter is the first of three concluding chapters. This chapter discusses research findings of this study that can be generalized to clusters in general. As discussed in the empirical part, this should be regarded as ‘analytical generalization’ (not as empirical generalization). In the next chapter, conclusions specifically related to seaport clusters are discussed. The final chapter discusses implications for policy and management in seaport clusters. Some overlap between these chapters is unavoidable, since the same research findings can be relevant for clusters in general, for seaport clusters and for policy and management. All three chapters are finalized with a few suggestions for further research. 13.1 Constructing a cluster In this study a method to identify the ‘cluster population’ was developed. The cases show that this method is applicable when ‘economic census data’ are available at a sufficiently disaggregated level, both economically and geographically. Cluster activities have to be identified with the use of input-output data, an analysis of the structure of value chains, an analysis of the association structure and expert interviews. The relevant cluster region can be identified on the basis of a concentration analysis of these cluster activities. The cluster population, consisting of all organizations engaging in cluster activities and located in the relevant cluster region, can be identified with the use of a dataset in which all firms are classified in industries. This method does allow for a precise delimitation of the cluster and consequently a more precise analysis of the development of the cluster over time. 13.2 The theoretical framework The validity of the theoretical framework developed in the theoretical part (see Figure 18) is broadly confirmed in this research. A few additions to the framework that have resulted from the cases are discussed in the following paragraphs. The relevance of the four variables
192 The Performance of Seaport Clusters related to the structure of a cluster and the four variables related to the governance of the cluster is confirmed in this research. Figure 18: The theoretical framework Cluster structure (Dis)agglomeration forces Internal competition Cluster barriers Heterogeneity Cluster performance NPV of value added Cluster governance Intermediaries Trust Leader firms Collective action regimes Experts were asked to identify variables that were not addressed in the survey. They identified a number of variables, most importantly ‘distortions of the level playing field’, ‘trends in the shipping industry’ and ‘the transport policy of a country’ (state). These variables are relevant for the performance of port clusters. However, the framework deals exclusively with ‘cluster specific variables’ and these three variables are not cluster specific. Industry experts focus on the overall picture, but from a theoretical perspective a focus on cluster specific variables makes sense: without such a delimitation, an infinite number of variables can be identified and ‘everything is related to everything’. As far as cluster specific variables are concerned, the framework developed in this study proved to be a useful and complete ‘tool’ to analyze the performance of (port) clusters. The framework is an alternative for Porters well-known diamond framework and the adapted version of this diamond (Rugman et al, 1995). The most important differences between our framework and both alternatives are: • The distinction between structure and governance variables. In both alternatives, such a distinction is lacking. This distinction adds to the quality of the framework, in the sense that it is a shift away from the ‘mechanic’ explanation of the performance of a cluster
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PETER W. DE LANGEN The Performance
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The Performance of Seaport Clusters
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Preface v PREFACE My first publicat
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Preface vii The frequent question w
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x Emperical part: three cases of se
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1 INTRODUCTION Economists have alwa
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Chapter 1 - Introduction 3 1.2 Over
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Chapter 1 - Introduction 5 Second,
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2 CLUSTERS AS UNIT OF ANALYSIS In t
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Chapter 2 - Clusters as Unit of Ana
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20 The Performance of Seaport Clust
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22 Table 1: Four ways in which clus
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4 VARIABLES OF CLUSTER PERFORMANCE
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Chapter 4 - Variables of Cluster Pe
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5 CLUSTER STRUCTURE In this chapter
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Chapter 5 - Cluster Structure 41 Th
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Chapter 5 - Cluster Structure 43 ef
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Chapter 5 - Cluster Structure 45 Th
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Chapter 5 - Cluster Structure 47 fi
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Chapter 5 - Cluster Structure 49 va
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Chapter 5 - Cluster Structure 51 Ta
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54 6.1 Coordination in a cluster Th
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7 ANALYZING THE PERFORMANCE OF SEAP
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Chapter 7 - Analyzing the Performan
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8 CLUSTERING IN SEAPORTS In this ch
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Chapter 8 - Clustering in Seaports
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106 The Performance of Seaport Clus
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112 9.3.3 The presence of intermedi
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118 Figure 15: Optimal investment q
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10 STRUCTURE AND PERFORMANCE IN SEA
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Chapter 10 - Structure and Performa
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11 GOVERNANCE AND PERFORMANCE IN SE
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240 The weight of the variables of
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Appendix 2: Cluster Experts in the
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Appendix 2: Cluster Experts in the
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English Summary 249 The Performance
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English Summary 251 The third schoo
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English Summary 253 The empirical p
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English Summary 255 Internal compet
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English Summary 257 • The innovat
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262 Tabel S1: Het effect van de vie
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Curriculum Vitae 271 Curriculum vit
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The Performance of Seaport Clusters
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