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National Prosperity, Structural Holes and Sectoral Development

In a dynamic environment there should be a shift in focus from the already successful sectors to the sectors adjacent to the successful sectors. This policy shift will both strengthen the already successful sectors as well as lay the foundation for developing new successful sectors. Besides, the disruptive high-risk approach to industry policy (must also be pursued) is to focus on the links between already successful sectors in the economy. Firms that can innovate through the combination of knowledge domains not previously combined tend to increase the economic value of their portfolio of offerings. 

National prosperity has a high dependency on the ability to produce and export products and services that are highly competitive on the international market and to the extent the economy (or country) export more than its fair share of these products and services. The success of these products and services can come either by having highly competitive prices compared to similar offerings from elsewhere or, more desirably, through being able to offer something that nobody else can offer and thereby achieving non-price based competition, the sustaining of which requires inimitability.

It stands to reason that the deeper and broader the competence base of an economy the greater the portfolio of products and services the economy can produce. Hence, it is possible to observe the products and services that a given economy exports and if these have a smaller or larger global market share than is justified by the size of the economy (this is the underpinning of economic complexity) and from this deduce the competence portfolio of the economy.

The sectoral evolution of an economy can be viewed as a process of knowledge development and knowledge recombination. This means that the development of a sector is a function of both how much it invests in knowledge development (and how successful this investment is) and the availability and access to knowledge outside the sector that if combined with the knowledge inside the sector could provide new productive knowledge. Knowledge spillovers are more probable between sectors that are directly or indirectly linked. Directly linked sectors can be identified through supply-chain and value-chain type analysis on the firm level and input-output type analysis on the sector level. Indirectly linked sectors can be identified through competence communalities extracted from economic complexity analysis (these competence communalities are considered to exist if the likelihood of 2 products being exported together is larger than 50%).

Structural Holes

The ability to develop new productive knowledge (the ability to innovate) depends on access to existing competencies both within and outside the firm. The more complex the product or service, the higher the dependency on external competence and hence on the competence networks that the company have access to. A single company cannot innovate a complex product like a space re-entry vehicle or a complex service like real-time adaptive predictive maintenance service for a complex multi-technology product, and would have to depend on a network of competence partners.

These networks, if effective, would have an optimal size, enabling any network participant to reach any other network participant fast, would be made up of participants whose knowledge complement each other rather than substitute each other, and have participants with a willingness to share their knowledge with the other participants. In addition, the network needs to simultaneously minimise the route from any given network participant to any other network participants, and maximise the interaction between the different knowledge domains that exist within the network. This latter requirement lays the foundation for maximising the amount of productive knowledge that can be created within the network and hence that can benefit the firm. To stay competitive in a changing environment firms and sectors need to continuously adapt. This requires both absorptive capacity and access to knowledge not available within the firm or the sector itself.

Ideally the firm should sit as the sole point of connection between separate rich networks, each of which is complete in its own domain – this point is known as a structural hole. This would provide the firm with a competitive advantage as relates to creating new knowledge as the foundation for innovation by being the sole firm able to connect the knowledge from two or more separate knowledge domains. Hence for an economy, the most beneficial outcome is if sectors are in themselves covering the relevant competence domain well (i.e. are rich in knowledge) and are connected to many different sectors in its own as well as many other economies that are not in themselves interconnected. This would provide the original sector in the economy with an advantage in terms of connecting knowledge from several sectors outside the economy to enable innovations that can form a basis for successful (competitive) export and hence benefit the economy, something more difficult for the externally less well-connected sectors to do (see figure 1 for an illustration).

As a basis for a high potential for national value creation this requires:

  • A national economy with very many sectors i.e. a complex economy
  • That a high proportion of these domestic sectors contain the presently relevant competence for pursuing their activities as illustrated by them being successful in exporting their offerings by having a disproportionally international market share i.e. a revealed comparative advantage
  • That each of these domestic sectors has a high absorptive capacity for new knowledge. This means that these sectors have the capacity to make effective (productive) use of knowledge, ideas and technologies that become available through spillovers between firms, sectors and countries.
  • That each of these domestic sectors are connected to other sectors inside or outside the domestic economy that have a high level of competence in their specific domains
  • That each of the domestic or international sectors that the domestic sector is connected to is not in themselves connected to the other domestic or international sectors that the domestic sector is connected to.

Sectoral development as a basis for national prosperity

National prosperity can be increased by having existing successful sectors (firms) innovating by pushing the frontiers of existing knowledge domains; by developing sectors (and firms) adjacent (in the competence or supply-chain/value-chain sense) to existing successful sectors (firms); by forcing disruptive innovation resulting in new sectors (firms) or new activity domains through instigating collaboration and interaction between firms in sectors that, due to unrelated specialisation, would not normally collaborate or interact; and by redeploying existing competences linked to high complexity sectors that are in decline within the economy.

Success in all the above requires understanding the existing deep and spatially-specific knowledge domains. Thereby also enabling the identification of possible cross-overs between existing specialisations and the identification of adjacent knowledge domains (using the economic complexity approach).

  1. The role of policy makers in facilitating the redeployment of existing competencies linked to sectors in regional or economy wide decline is again substantial and imperative for both avoiding social problems with associated costs and regional and economy-wide prosperity. Examples of when this is critical is in e.g.
  2. The role of policy makers in forcing disruptive innovation resulting in new sectors through instigating collaboration and interaction between sectors that, due to unrelated specialisation, would not normally collaborate or interact is substantial and imperative for regional and economy-wide prosperity. There are several different scenarios for how this creation of new sectors may take place e.g.:
    • The unrelated knowledge domain of one sector is introduced to another sector leading to the receiving sector developing new offerings that are related to the existing offerings. An example could be the introduction of telematics and machine learning to the automotive industry leading to the development of autonomous vehicles.
    • The interaction of the unrelated knowledge domains of sectors result in offerings that are very weakly related to existing offerings from any of the sectors. An example of this is the combination of ICT, laser or electron beam technology, material science, powder metallurgy, mechatronics, etc. resulting in the emergence of the additive metallic manufacturing equipment sector (3D printer production). These interactions of unrelated knowledge domains can be driven by the emergence of new scientific or technological knowledge or by the emergence of new societal demands or challenges.
    • Policy makers will be required to draw on a combination of supply side, demand side and information provision tools to facilitate these types of outcomes.
  3. The role of policy makers in developing sectors linked (competency or supply-chain/value-chain wise) to existing successful sectors includes a mapping of what those sectors are. The easiest approach is to map the economic complexity of the spatial domain (region or country) to identifying sectors (competence domains) that are adjacent to existing sectors in which the spatial domain (region or country) already has a revealed comparative advantage. Once these sectors (having no unsurmountable barriers for development) are identified, they can be ranked based on their proximity (common knowledge/capabilities) to existing successful sectors and their contribution to raising the spatial domain’s (region’s or country’s) economic complexity. The highest ranked sectors can now be developed using a combination of traditional industry policy tools with a focus on the demand side (procurement, regulation and facilitated creation of agglomeration economic benefits) supported by some supply side tools (inward investment attraction, preferential loans and collaborative industry-research provider projects). It may be worth noting that for some regions the journey to high economic complexity may require progressing through many iterations of this process and hence may take a long time (10-30 years) – but unfortunately there are no shortcuts.
  4. The role of policy makers in contributing to already successful sectors pushing the frontiers of their underpinning knowledge domains and thereby achieving innovations that provide first-mover advantage on the market is limited. It may include encouraging and/or facilitating greater collaboration between firms and their customers, firms and their suppliers, and firms and relevant research providers. This argument holds both for successful sectors that have emerged through path dependency and through the other routes described – true by the mere fact that these sectors are already successful and hence have both the resources and competencies to pursue their own success. The primary role would be for policy makers to assist in introducing an impetus for change in these sectors when they are exposed to a market driven or technology driven challenge to their existence since these sectors, due to their path dependency and deep expertise tend to reject early signs of these threats (competence domain myopia) until it becomes too late to change.
  • Temporary valley of death periods for key sectors. This is observable in long lead-time, highly complex product domains with infrequent purchase e.g. defence value chains. Here the competence wants to be both developed and maintained and a common tool for this is paid study projects, paid for by the end customer (e.g. government) with performance requirements exceeding existing know performance boundaries.
  • Local decline of a sector that remains competitive in other economies e.g. the decline of the automotive industry in Australia. Here it is critical to identify the competences that is desirable to retain and those that are not – this depends on the specific competence and sectoral landscape of the economy. Once these competences are identified they can be introduced to new domains, which performance will increase as a consequence of accessing this competence. An example is the redeployment of LEAN competence from the declining automotive industry to the health care industry. The identified competences that are desirable to retain could also form the basis for new sectors in the economy that serve existing sectors with revealed comparative advantage e.g. the development of new sub-sectors in the Mining Equipment, Technology and Services industry applying LEAN production technologies to facilitate the migration of the mining industry (i.e. the client sectors) towards a higher level of automated production. Thereby both strengthening the existing revealed comparative advantage of the mining sector and facilitating its migration to a new value creating paradigm thereby reducing the risk for decline in this successful, and for the economy’s value creation, important sector.

Combining the discussion on structural holes with the discussion above leads to the conclusion that the highest strategic gains for regional prosperity stand to be had by enabling the interaction of unrelated knowledge domains from sectors (and firms) occupying structural holes. This logic applies on the micro-level of the individual firms, the meso-micro-level of firm clusters, the meso-level of sectors, and the macro-meso-level of sector clusters. These structural holes are frequently both created and filled by emerging sectors grounded in what is called General Purpose Technologies or Key Enabling Technologies like e.g. the emerging machine learning service and product providing sector.

Example of analysis and outcomes underpinning the sectoral policy focus that in turn underpin a Smart Specialisation Strategy

Smart Specialisation is an innovation policy concept that aims to boost regional innovation, contributing to growth and prosperity by helping and enabling regions to focus on their strengths and diversify from there. Smart Specialisation is based on partnerships between businesses, knowledge institutions, public and third sector entities and knowledge institutions.

“Smart specialisation strategy” means the national or regional innovation strategies which set priorities in order to build competitive advantage by developing and matching research and innovation strengths to business needs in order to address emerging opportunities and market developments in a coherent manner, while avoiding duplication and fragmentation of efforts; a smart specialisation strategy may take the form of, or be included in, a national or regional research and innovation (R&I) strategic policy framework or may form the basis of an industry policy Hence, the key objective of a smart specialisation strategy is to build on the knowledge base that currently exists. To this end, the policy targets certain activities with the potential to generate agglomeration economic benefits for firms and thus have a transformational effect, rather than simply promoting “scattered” innovation. Sector prioritisation then becomes a core element of smart specialisation policy. It is to be noted that a smart specialisation is more about de-selecting losers than picking winners.

Economic complexity analysis identifies knowledge capabilities of economies as demonstrated by the complexity of the products they export with comparative advantage. Additionally, existing knowledge capabilities are closely linked to future economic growth and consequently can be used as a measure of economic development. Economic complexity analysis can identify areas for development that are likely to succeed by assessing current capabilities, and can therefore be used as a highly effective tool for industry development policy and hence for a smart specialisation strategy. Below are three graphs extracted from the economic complexity analysis of South Australia to underpin the three policy foci:

In Figures 1-3 the above figures the y-axis shows the product-sector complexity ranking and the x-axis shows the share of adjacent competences present in the state. The higher the product-sector complexity ranking the more opportunities are present when new technologies (e.g. digital technologies) are introduced into the economy and the more opportunities arise from the presence of a sector in the economy the higher the complexity of that sector. In Figure 4 the x-axis is the same but the y-axis shows the improvement in overall complexity ranking that follows from developing the structural hole sector.

The share of adjacent competencies in the state have two implications: Firstly, the higher the share the easier to develop and grow the sector. Secondly, the higher the share the more collaborative firms in the product-sector tend to become. The low share illustrated in Figures 1-3 provides one indicator of why Australian firms tend to have a very low level of collaboration compared to other OECD economies.

Conclusion for policy makers 

Successful organisations tend to have a comprehensive understanding of the knowledge relevant to their domain of activity and can pursue a low risk strategy of capitalising on this knowledge by identifying and filling in gaps on the knowledge frontier, thereby achieving the foundation for first-mover advantage in their industry. This approach tends to generate a high level of novelty but does not seem to dramatically increase the economic value of the firm’s portfolio of offerings. This is a low-risk strategy as long as there is no disruption of the knowledge base nor any convergence between knowledge domains – some of which are unknown to the firm. Industry policy in this stable environment would be very limited and would focus on supporting already successful sectors. These sectors can be identified through an economic complexity analysis and illustrative results are shown in Figure 1.

In a dynamic environment there should be a shift in focus from the already successful sectors to the sectors adjacent to the successful sectors. This policy shift will both strengthen the already successful sectors as well as lay the foundation for developing new successful sectors. This can be articulated as the incremental low-risk approach to industry policy. These adjacent sectors can be identified through an economic complexity analysis and illustrative results are shown in Figure 2 and 3 respectively where the focus should be in strengthening the sectors shown in Figure 2 and developing a select few of those shown in Figure 3.

The disruptive high-risk approach to industry policy (which must also be pursued) is to focus on the links between already successful sectors in the economy. Firms that can innovate through the combination of knowledge domains not previously combined tend to increase the economic value of their portfolio of offerings. This requires policymakers to deploy policy tools that will facilitate collaboration and interaction between firms in sectors that, due to unrelated specialisation, would not normally collaborate or interact. This is doable since knowledge (technological) relatedness is a dynamic state that can be influenced. The more dynamic the competence and market demand environment the more important this approach to industry policy becomes (see results in Figure 4.)

As the dynamics of the competence and market demand environment increase the likelihood of some existing sectors experiencing terminal decline increase. It is normally not desirable to try to prolong the life of these sectors through expensive interventionist policies (it may instead be desirable to accelerate the demise of sectors in terminal decline through something that can be called an industrial euthanasia policy – not discussed here). In these situations, there are normally key competencies that exists in the declining sectors that are desirable to be maintained and redeployed within the economy. This redeployment of desirable competencies is normally more successful if the market forces are given a helping hand by policy makers – this due to issues around information asymmetry, search costs, absorptive capacity and managerial competencies in sectors primarily made up of SME’s (e.g. the METS sector in Australia) or in sectors with a myopic view on its competence need or hindered by a risk avoidance or not-invented-here culture (e.g. the health care sector).


Escrito por Prof. Göran Roos, South Australian Economic Development Board.


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