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2.6 Specialisation indexes

2.6 Specialisation indexes
2.6 Specialisation indexes

The definition of priorities at national or regional level takes place within a series of activities and technology domains that are potentially competitive and able to generate new business in a global context faced with competition from other regions.

On the basis of the analysis of existing assets, comparative advantage and regional potential, regions should take into account key strengths and advantages of their technological and economic specialisation. Specialisation by definition has two contrasting aspects: one positive, indicating the areas where a country, a sector and/or a firm exhibits a stronger position than other countries, sectors and/or firms, and one negative, indicating, respectively, the areas of relative weakness. Consequently, technology or scientific specialisation in its positive sense inherently implies a concentration of capabilities on some areas of knowledge. Inversely, in its negative sense, it implies weak capabilities in other areas when compared to a point of reference. The very concept of specialisation, however, means that it is not conceivable that a country achieves specialisation positions across the whole broad spectrum of technologies, sciences and sectors.

In the literature, the measurement of specialisation originates in trade theory. Since then, a variety of specialisation indices have also been developed to capture the scientific and technological specialisation of a country or region, namely, the measurement of publications/citations and data regarding patenting.

The method for analysing regional specialisation produces technological and economic specialisation indexes for understanding the position of the regional technological and economic activities into global value chains, and uses an interactive dashboard for visualisation.

An example of the application of the method in the RIS3 development of regions can be found in Lithuania, which has used International Trade Centre UNCTAD/WTO – Trade Competitiveness Map which is used to benchmark national and sector trade performance. SCOPUS SCImago Journal and Country Rank tool are also frequently referenced for bibliometric analysis. The Centro region in Portugal has employed bibliometric analysis using a tool that analyses open access publications. Other regions (mostly Germany, Austria and Belgium) have made use of various national online statistical tools providing insights on patents and inventions.

Overview, key statistical analysis and qualitative assessment are the first methods used by all regions in Step 1 of the RIS3 process. Bibliometric analysis and benchmarking is used by regions in approximately half of the mapped RIS3. Collaboration and networking analysis and value chain analysis are only used in around one third of the mapped RIS3.

Description of the method

The definition of priorities at national or regional level takes place within a series of activities and technology domains that are potentially competitive and able to generate new business in a global context faced with competition from other regions.

On the basis of the analysis of existing assets, comparative advantage and regional potential, regions should take into account key strengths and advantages of their technological and economic specialisation. Specialisation by definition has two contrasting aspects: one positive, indicating the areas where a country, a sector and/or a firm exhibits a stronger position than other countries, sectors and/or firms, and one negative, indicating, respectively, the areas of relative weakness. Consequently, technology or scientific specialisation in its positive sense inherently implies a concentration of capabilities on some areas of knowledge. Inversely, in its negative sense, it implies weak capabilities in other areas when compared to a point of reference. The very concept of specialisation, however, means that it is not conceivable that a country achieves specialisation positions across the whole broad spectrum of technologies, sciences and sectors.

In the literature, the measurement of specialisation originates in trade theory. Since then, a variety of specialisation indices have also been developed to capture the scientific and technological specialisation of a country or region, namely, the measurement of publications/citations and data regarding patenting.

The method for analysing regional specialisation produces technological and economic specialisation indexes for understanding the position of the regional technological and economic activities into global value chains, and uses an interactive dashboard for visualisation.

An example of the application of the method in the RIS3 development of regions can be found in Lithuania, which has used International Trade Centre UNCTAD/WTO – Trade Competitiveness Map which is used to benchmark national and sector trade performance. SCOPUS SCImago Journal and Country Rank tool are also frequently referenced for bibliometric analysis. The Centro region in Portugal has employed bibliometric analysis using a tool that analyses open access publications. Other regions (mostly Germany, Austria and Belgium) have made use of various national online statistical tools providing insights on patents and inventions.

Overview, key statistical analysis and qualitative assessment are the first methods used by all regions in Step 1 of the RIS3 process. Bibliometric analysis and benchmarking is used by regions in approximately half of the mapped RIS3. Collaboration and networking analysis and value chain analysis are only used in around one third of the mapped RIS3.

Description of the method

Empirical research on international specialization patterns uses a wide array of statistical tools, ranging from simple descriptive indicators to complex econometric techniques.

Positioning in value chains, the OECD’s (2013) work on global value chains, in addition to the methods implemented by regions, suggests using other indicators of science, technology and economic specialisation for place-based growth. This includes longitudinal analyses and the comparison of patterns in scientific, technological and economic specialisation; and relative indicators that are important from a benchmarking perspective.

In this context, for the identification of the technological and economic specialisation of regions, three indicators will be described: the Activity Index (AI) for scientific activities (publications/citations), the Revealed Technological Advantage (RCA) for patents and the Revealed Comparative Advantage (RCA) for economic activities (trade/exports). Visualisation of indicators using an interactive dashboard will be also described.

Scientific Activity Index (AI) (note that this is developed separately under method 2.5 Science and technology profile and performance)

The index quantifies the academic performance of researchers, such as measuring the scientific performance based on the number of publications or the citation index (bibliometric indicators). Publication and citation counting techniques are tools used to illuminate and evaluate scientific activity, and can provide a comprehensive regional research profile.

Other scientific activity techniques are used for measuring the collaboration activities of researchers and community collaboration activities (e.g. co-authorship, co-partners in projects, and co-cited publications). At a regional level, publication and citation data are also patterns of research collaboration: they identify sub-fields that reflect specializations, assess and map research collaborations in terms of joint publication efforts, or assess the publication impact of institutions and their research fields. Affiliation and co-affiliation data from scientific publications can also be used to infer mobility patterns and to conduct diachronic network analyses to identify the mobility of people among locations over time.

At the regional level, data on the proportion of scholars that are “sent” or “received” can be also calculated by analysing the directionality of mobility events. The total number of scholars provides a capacity indicator for the region, which can be also used to calculate normalised shares both for sending and receiving regions/countries to demonstrate the flow of scholars between EU regions.

Revealed Technological Advantage (RCA)

The revealed technology advantage (RTA) index provides an indication of the relative specialisation of a given country in selected technological domains, and is based on patent applications filed under the Patent Cooperation Treaty. It is defined as a country’s share of patents in a particular technology field divided by the country’s share in all patent fields. The index is equal to zero when the country holds no patent in a given sector; is equal to 1 when the country’s share in the sector equals its share in all fields (no specialisation); and above 1 when a positive specialisation is observed. Patent counts are based on the priority date, the inventor’s residence and fractional counts.

There are two kinds of data related to patenting activities: (a) patenting activities of a country’s/region’s assignees, and (b) patent applications by a country’s/region’s inventors:

(a) Statistics on applicants allow for a more detailed and precise analysis of a country or region’s patenting than those based on inventor patent data. When analysing the patenting activity of assignees at the national level, proper allowance must be given for the structure of assignees, e.g. the size of assignees, their origin and field of operations; this is especially true when using European Patent Office (EPO)databases. It is the primary path in a significant number of technological specialisation studies, as it presents the “clearest” analysis of technological activities across countries, of individual firms and patent applicants within countries, and of the ambitions and participation of firms and individuals in international (or internal) technology markets.

(b) Data on inventor patents provide a better ‘‘picture’’ of the technological activities of developing countries than assignee patents. The advantage of studies based on inventor data is that a country’s inventors are more visible in the patenting process than a country’s assignees. A large number of these types of patent data allow calculations to be made, and the data to be more accurately analysed. However, the results drawn from inventor-based analysis are not as significant as the results and outcomes from an analysis of assignees data. This is because applicants companies and individuals are more interconnected with their country of origin than inventors.

For the study of the dynamics of patent development, two to three periods of three to five years (chosen from the comparable steady state period until the last available period in the database) can be analysed. This provides reliable data. At the same time it allows for smoothing and, to a certain degree, the elimination of random fluctuations in patenting dynamics.

Revealed Comparative Advantage (RCA)

RCA is an index used in international economics for calculating the relative advantage or disadvantage of a certain country or region in a certain class of goods or services as evidenced by trade flows. It is measured by the relative weight of a percentage of total export of commodities in a nation over the percentage of world exports in that commodity. The RCA is equal to the proportion of the country’s exports that are of the class under consideration (Eij / Eit) divided by the proportion of world exports that are of that class (Enj / Ent). A value of less than unit implies that the country has a revealed comparative disadvantage in the product. Similarly, if the index exceeds unity, the country is said to have a revealed comparative advantage in the product.

The concept of Revealed Comparative Advantage is similar to that of Economic Base Theory, which is the same calculation, but considers employment rather than exports. It most commonly refers to an index introduced by Béla Balassa. Measures of RCA have been used to help assess a country or region’s export potential. The RCA indicates whether a country is in the process of extending the products in which it has a trade potential, as opposed to situations in which the number of products that can be competitively exported is static. It can also provide useful information about potential trade prospects with new partners. Countries with similar RCA profiles are unlikely to have high bilateral trade intensities unless intra industry trade is involved. RCA measures, if estimated at high levels of product disaggregation, can focus attention on other nontraditional products that might be successfully exported.

Interactive Dashboard

A critical phase of the research process is the presentation of results. This is typically done in a variety of ways, including the use of tables and charts in reports and slide presentations. One of the more accessible and engaging means to present research results is through the use of online interactive dashboards with information about local specialisation profiles, past growth and future prospects.

“A dashboard is a visual display of the most important information needed to achieve one or more objectives which fits entirely on a single computer screen so it can be monitored at a glance.” It is also a customized, interactive display that is used to explore data. Dashboards can be connected to live data that are automatically updated in real-time, or based on a completed survey project or other finite datasets. For example, we can sort and rearrange data in an interactive grid, perform manipulations on the data to display only the information one is interested in, and display visual representations of the data in the dashboard to make the data easier to interpret.

In short, the method uses a collection of different visual elements — usually charts — arranged on a single web page, providing a summary of the most important results or findings related to a particular subject. The process for the creation of a dashboard is described in more detail in the implementation section.

Usability and impact

Indicators to measure specialisation in science, technology and exports may help policy-makers in identifying strengths, weaknesses, complementarities and mismatches with respect to scientific, technological, innovative and economic capabilities.

Longitudinal analyses of patterns in scientific, technological and economic specialisation and potential lags or interdependences between the different components can provide policy-makers with background information to assess the sustainability of traditionally strong sectors or, to consider providing public support to those areas where research capacity is strong but economically weak. Likewise, comparisons of technological and economic specialisation may show economically strong domains where technological activity is relatively weak or vice-versa. In such cases, policy-makers may want to consider whether stimulation for technological advancements or international collaborations would contribute to the sustainability of these sectors.

Relative indicators, such as the Activity Index (AI) for scientific activities, the Revealed Technological Advantage (RTA) for patents and the Revealed Comparative Advantage (RCA) for economic activities in exports, are used to avoid biases and to compare countries and regions on an “equal basis”. For example, relative specialisation indices integrate a comparison of profiles of a focal country/region to profiles of reference countries/regions. They can hence be used to answer questions like “where does a country (or region) stand in various sciences/technologies/economic domains, compared to other countries or regions”.

References contained in each patent application to previous relevant patents can provide information on the interrelatedness of various technological domains. In the same way, references contained in each patent application to research papers reporting results on which the invention is based, can be used to map the science – technology nexus. This can point to interesting opportunities for technology development and to gaps in the regional or national scientific profile. In addition, patents linked to universities and public research can help provide statistics regarding the role of universities in technological development (e.g. by compiling counts of the patents universities were granted, their forward citations, funded by a company or other source).

Techniques combining citation-linked and text-based approaches allow for the monitoring of the evolution of scientific and technological domains, and for the detection of new, emerging topics within existing fields. International and interregional collaborations in science and technology development can be mapped by studying co-authorship or co-inventorship patters between countries, regions and their respective institutions as articulated in the Triple Helix concept.

Required data

A selection of required data per specialisation field are listed below:

Scientific Activity (bibliometrics)

  • Data on the number of publications and citations on specific fields for indentifying the regional research profile
  • Measuring collaboration of researchers through joint publications
  • Affiliation data from scientific publication
  • Measuring collaboration of researchers through co-partnership in research projects
  • Data on co-cited publications
  • Data on publications of institutions in research fields
  • Data on scholars flow and mobility.

Revealed Technological Advantage (patents)

It is important for the design and interpretation of patent indicators to have value issues in mind. Major findings related to an approach that attempts to cast light on the value of patents by using patent information are mainly provided by bibliographic sources. Required patenting data at regional level are:

  • Data on the patents of a region’s assignees
  • Data on the patents of a region’s inventors
  • Share of patents in particular technology fields divided by the region’s share in all patent fields
  • Patents linked to universities and public research
  • Firms patent activities
  • Patent data to study the geographical properties of inventive processes—e.g. the role of local actors in regional or national innovation (universities, small companies, large companies, etc.), their interactions and the profile and impact of regional technological specialisation.
  • Patent data to investigate researcher mobility (across companies or countries), differences in researcher profiles across fields, and linkages across researchers and others).
  • Benchmarking patent data of a region with other regions at national or EU level in technological or sector fields.

Revealed Comparative Advantage (exports)

  • Data of a country’s/region’s exports of a commodity (or industry)
  • Data of a country’s/region’s total exports
  • Data of corresponding exports to a set of countries
  • Share of Product in Total Exports, i.e. the share of each export product (at a chosen level of disaggregation) in the country’s/region’s total exports.
  • Share of Market in Total Exports, i.e. the share of exports sold in each foreign country in the home country’s/region’s total exports.
  • Hirschman Herfindahl Index, i.e. the sum of squared shares of each product in total exports. A country/region with a perfectly diversified export portfolio will have an index close to zero, whereas a country which exports only one product will have a value of 1 (least diversified).

In addition to publications, patents and economic performance indicators, other data are relevant for assessing a country’s or a region’s STIE potential. Some examples include expenditures on innovation and research and development in specific sectors, the availability of human capital for certain scientific, technological and economic areas, the presence of IT-infrastructure in specific sectors, etc. On a national level, some sector specific datasets are available. Unfortunately, it is very difficult to find regional data that are sufficiently detailed in terms of relevant underlying fields, and that are comparable across different regions.

Relevant data sources

A selection of existing databases and tools relevant for the application of the method’s indexes are listed below:

Trade and Exports

  • EU Trade tool. A fully interactive web-based application for the visualisation of inter-regional trade flows and the analysis of regions’ competitive position of regions: http://s3platform.jrc.ec.europa.eu/s3-tools
  • Trade Centre UNCTAD/WTO. A trade Competitiveness Map that allows for benchmarking of national and sector trade performance: http://tradecompetitivenessmap.intracen.org/TP_EP_CI_HS4.aspx
  • OECD, Inter-Country Input-Output (ICIO) Tables. Presents matrices of inter-industrial flows of goods and services produced domestically and imported: https://www.oecd.org/sti/ind/input-outputtablesedition2015accesstodata.htm
  • The OECD ORBIS Database, for firm-level data: http://www.oecd-ilibrary.org/economics/the-oecd-orbis-database_5kmhds8mzj8w-en

Publications/Citations (Bibliometric analysis)

Bibliometrics includes several different measurement methods. Data sources and publication data are recorded in most databases, both nationally and internationally. For data sources in more detail please see method 2.5 Regional scientific production profile.

Patents

There are many tools and databases available for patents, and many of them are free to access. The website http://www.irossco.com/patentsearching.htm contains the links for all free patent databases. The website https://www.patentinspiration.com provides various analytics of patent data.

The most comprehensive and frequently used patent databases are provided by the European Patent Office (EPO), the United States Patents and Trademarks Office (USPTO), the Organisation for Economic Co-operation and Development (OECD), the Japan Patent Office (JPO), the World Intellectual Property Organization (WIPO), Questel Orbit, and Eurostat, although data from domestic patent offices are often analysed for supplementary purposes too. However, the most complete patent data are contained in the EPO Pat stat database. The United States Patent Classification can be used in studies based on USPTO patent data only.

Implementation roadmap

Step 1. Collection of data

In this step the collection of the needed data and existing indicators on the technological/scientific/economic specialisation of the region should be completed. In case that the existing indicators are not cover all the fields, development of new indicators is needed (see above required data).

Step 2. Indicator analysis

Analysis of indicators should cover three main dimensions: regional assets, linkages with the rest of the world and the position of the region in the global economy. For example, technology specialization (and specialization in general) is a relative measure and can be specified through two different comparisons:

  • A comparison between the relative weight of the reference variable (scientific knowledge, research, technology outputs, patents and/or productive areas) within the same country, e.g. specialization in ICT, biotech, electrical engineering etc.,
  • A comparison, respectively, between (for example) the above national technology specialization patterns to similar figures of third countries or areas.

Comparisons of specialisation indicators over time, changes in scientific, technological or economic specialisation should also be analysed. Some examples for indicator analyses are:

Analysis of Absolute and Relative specialisation

Analysis of the absolute positions of countries and regions on the indicators developed. Absolute specialisation indices give evidence on how the degree of specialisation of one specific area changes over time, regardless of the development of other areas. Absolute positions are also important since they signal a presence or lack of critical mass in the fields subject to prospective specialisation studies. A nation or a region can have a strong relative position in a certain area, though upon further inspection (and given the mathematical nature of the relative indicators) it may still lack a distinctive critical mass in that area.

Relative specialisation reveals a countries’/regions’ comparative advantages in relation to a reference group of countries/regions. The average economic structure of countries under study is taken as the benchmark for relative specialization measures. Specialization indices of this kind provide data on the dissimilarity in the technology composition of each region compared with the structure of the selected reference level.

Relational indicators’ analysis

Interesting insights can also result from the study of relations between scientific, technological and economic specialisations, which can be mapped using conversion tables. Relative indicators are important from a benchmarking and evolutionary perspective. Examples include two dimensional mappings of technological and economic specialisation indicators, or of scientific and economic specialisation that generate insights into the past, present and future endeavors. For example, it is questionable whether a historically important economic specialisation can be expected to last if scientific and technological strengths in underlying areas are absent. Similarly, strong scientific or technological positions that do not translate into economic performance raise policy questions regarding knowledge transfer.

Analysis in this field can also include concentration indices, measuring the weight of n more important sectors (n can take the value of 1, 3, 4, 6, etc) to the total relevant figure for a specific technology variable (e.g. R&D, patents). Alternatively an analysis of an index of technological specialisation that shows how much any particular country or region adapts its relative high to low tech products trade structure to changing patterns of world trade in high and low technology products or matching patent information with other information at the firm level, such as R&D, innovation, stock market value.

STEP 3. Create an Interactive Dashboard

This concerns the visualisation of data using open data Interactive Dashboard. The process to create an on-line interactive dashboard is the following:

  • Data upload
  • Data cleaning
  • Creation of variables
  • Cross tabs
  • Charts
  • Power Point export
  • Dashboard
  • Key findings

Figure 8 Implementation roadmap

Figure 8 Implementation roadmap

References
No References available