Cluster Analysis

Cluster Analysis augments the SWOT to assist in identifying areas of the regional economy where comparative advantages exist and long-term growth through economic upgrading is most viable.

After the locational SWOT analysis is conducted and key sectors identified a cluster analysis is performed in order to better understand the business environment within which these focus sectors operate. The resulting regional cluster portfolio provides a mapping of the inherent strengths & weaknesses of a region, effectively outlining platform of comparative advantage for the region to compete from. 

Cluster Profiles as a Platform for Public-Private Collaboration

While there are groups of locations that aim to attract the same type of business activities, they tend to offer different combinations of assets; they are not just better or worse on one dimension that matters exclusively. This observation is core to what differentiates the cluster framework from other schools of thought that argue that there is one dimension of competitiveness that matters, with some locations succeeding and many others destined to fail.

Cluster analysis, on the other hand, considers the underlying dynamics and interconnections that enable certain regions to develop competitive advantages relevant to a specific set of economic activities. This means each region has its own distinct cluster portfolio(inherent strengths & weaknesses); giving each region a distinct platform to compete on. Through this lens we can see that clusters are both a reflection and a driver of the underlying competitiveness of a location.

The SEA Data Portal is designed to leverage these unique cluster profiles as a public-private platform for economic development.

Why perform a Cluster Analysis

Profile

Clusters are the building blocks of modern economies, providing key insights into the economic profile of a region.

Performance

Clusters help drive regional economic performance, from job growth to higher wages and innovation.

Policy

Clusters are a powerful tool for policy action and framework for economic development.

Companies

Clusters provide attractive opportunities for business investment, exports, site selection, and supply change assessment.

ABOUT CLUSTERS

Clusters are geographical concentrations of inter-connected enterprises and associated institutions that face common challenges and opportunities. They are both a reflection and a driver of the underlying competitiveness of a location.

3 Phases of a Cluster Mapping Effort

A cluster mapping effort proceeds in three main phases, with two steps each. 

Phase 1: First, decisions have to be made about the data to include and the cluster definitions to use.

Step 1: Data Audit

During this step initial assumptions about data availability need to be reviewed. The audit can generate more specific insights into the methods used for data generation by the original sources, including coverage, frequency, and types of indicators covered. Beyond data that can be linked directly to clusters, it is useful to identify data sources that are region-, industry, and even economy-wide.

Step 2: Cluster Definitions

Cluster mapping relies on the use of cluster definitions that are comprehensive, transparent, evidence based, and comparable across locations. For the cluster definitions there are two main options: Either to use the cluster definitions developed in the context of previous cluster mapping efforts or create a new set of definitions based on the data of the country in question. 

Phase 2: Next, data needs to be acquired and a cluster-specific dataset generated.

Step 3: Data Acquisition

The data sets identified as the source of the input data have to be acquired. There might be public data sets but in some countries commercial private data providers offer better data. An issue is whether the results of the analysis can be published in terms of cluster and region-specific data which can be problematic, especially when in small clusters data allows conclusions on individual firms.

Step 4: Cluster-Specific Data Set

The gathered data has to be aggregated towards cluster-level information for the target level of geography, using the cluster definitions derived in step 2 of phase 1. Note that this step has to be taken for every indicator that is covered, for example employment, wages, and establishments. This step leads to the core cluster mapping data set with a matrix structure.

Phase 3: Lastly, descriptive statistics are derived and a platform created to allow data access for key stakeholders.

Step 5: Descriptive Statistics Generation

The data can be used to create a core set of descriptive statistics and accompanying graphics to visualize the data. For the statistics on cluster presence it is necessary to operationalize the notion of a ‘strong cluster’, i.e. a group of related industries in which a location has reached critical mass. These descriptive statistics should include insights at the national, regional and cluster-specific level.

Step 6: Cluster Mapping Portal

In many cases it is useful to make the cluster mapping data set itself publicly available, not just a report on key descriptive statistics or overall findings. Such ‘open data’ portals have been launched in a number of countries, both to provide critical information to policy makers at the regionals level and to companies that are considering the attractiveness of different locations. 

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