Industry Cluster Analysis

By: Hal  09-12-2011

Cluster theory suggests that competitive advantage derives not just from firm-based resources and capabilities, but also from the resources and capabilities located in the firm’s geographically proximate business environment.  Some empirical research on the impact of clustering has suggested that it can produce significant positive effects on rates of new firm formation and firm productivity, innovation, profitability, and growth.

Cluster analysis enables accurate and effective policy and management intervention.  An understanding of a cluster’s internal workings – components, structures, processes, routines and development pathways – is critical to support the development of a successful cluster. HAL has developed a framework, process, and tools for cluster analysis.


The HAL framework is illustrated in Figure 1.  It consists of two parts, Current Conditions and Current Performance.  Current Conditions consists of three constructs that measure the cluster’s supporting organizations, the competitive environment of customers and competitors, and the factors in the environment of the cluster that influence all of these actors (e.g. availability of HQP, business climate, etc.).

Figure 1: HAL Cluster Framework

Current Performance consists of three constructs that measure the cluster’s significance in terms of the number and size of core firms, the breadth of their responsibilities, and their reach to distant markets; interactions within the cluster and with the rest of the world; and the cluster’s dynamism in terms of innovativeness and growth.  The performance of the cluster as a whole is dependent on the success of the individual firms and moderated by the cluster factors, supporting organizations, and customers and competitors.  There is a temporal disconnect between Conditions and Performance in that current conditions impact future performance, and current performance is the result of past conditions. The framework is operationalized through specified indicators, as shown in Table 1.  These indicators have direct connections to an interview guide and survey used to collect information during the cluster analysis process.

Table 1: Cluster Constructs and Indicators





Current Conditions


Human Resources

Access to qualified personnel

Local sourcing of personnel


Quality of local transportation

Quality of distant transportation

Business Climate

Quality of local lifestyle

Relative costs

Relative regulations and barriers

Supporting Organizations

Innovation and Firm Support

Contribution of NRC

Contribution of other research organizations

Community Support

Government policies and programs

Community support organizations

Community champions


Local availability of materials and equipment

Local availability of business services

Local availability of capital

Competitive Environment

Local Activity

Distance of competitors

Distance of customers

Firm Capabilities

Business development capabilities

Product development capabilities

Current Performance


Critical Mass

Number of cluster firms

Number of spin-off firms

Size of cluster firms


Firm structure

Firm responsibilities


Export orientation



Internal awareness

External recognition


Local involvement

Internal linkages



R&D spending

Relative innovativeness

New product revenue


Number of new firms

Firm growth

The needs and concerns of cluster players will differ depending on the stage of development of the cluster, and cluster policies must evolve accordingly.  For example, in early stage clusters, salient issues include the development of specialized R&D infrastructure, the fostering of linkages, the development of firm capabilities, access to talent, and the elaboration of a shared vision.  In growing clusters, the emergence of new firms may alter the strategic alliances driving the cluster’s R&D activities, or may require new strategies to meet the increased demand for skilled labour and risk capital.  As the cluster firms expand their reach into national or continental markets, the availability of managerial talent with the skills needed to direct an enterprise of this increasing geographic scope can become a critical factor contributing to, or limiting, their growth potential.  The emergence of foreign competitors or competing technologies may also require an internal restructuring to increase efficiencies or a new investment in R&D capabilities.  This dynamism causes the cluster’s structure to change over time.


The cluster analysis process begins with a literature and document review of existing information regarding the state of the cluster.  Next, b ased on the review, and in consultation with core cluster stakeholders, the scope of the clusters is defined.  The scope is influenced by considerations of the cluster’s self-awareness (how do members of the cluster view themselves?), external recognition (how do others view the cluster?), and comparison (what definition will permit comparisons with similar clusters?).  Then, given this cluster scope, cluster members are identified using lists obtained from industry associations, economic development organizations, and other sources. Interviews are conducted with stakeholder representatives of each cluster, segmented as firms, research organizations, supporting organizations, and service providers.  The questions are structured according to the framework, and are open-ended, providing insight into the internal dynamics and workings of the cluster. A survey of cluster firms provides data for quantitative analysis that is not available from other sources.  Quantitative results for each indicator from the survey are used to determine a cluster’s strengths and weaknesses.  The ratings are based on what has been found to be important in many clusters across Canada and around the world.  However it must be understood that a cluster is the sum of its parts and that any indicator must be assessed in the context of the other elements of that cluster.  For this reason, care must be taken when comparing the performances of different clusters on any indicator.

A low indicator may or may not indicate a concern, depending on the circumstances of the cluster.  For example, Canadian clusters tend to perform poorly on measures related to local activity – measures of the proximity of important competitors and customers.  While the international literature stresses the importance of local competitors and customers, research has shown that Canadian clusters are almost never large enough to have significant local activity and rather depend to a greater extent on exports than do, for example, United States clusters.

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