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Regional Competitiveness Analysis: Process and Measurement
The emphasis on regional
competitiveness has gradually gained lately in strength and scope. From the
first EU Reports on competitiveness
which signalled worrying trends relative to the competitive advantages in both
global and local contexts to the present strategic guidelines of the Community which
makes the competitiveness of regions a priority theme, the topic has come to
hold the centre stage at the European policy-making level. The renewed Lisbon
Agenda requires that 'the Union
must mobilise all appropriate national and Community resources - including
cohesion policy' and makes clear that greater ownership of
the
The development sources are regionally divided in a strong relation to the local abilities to put at good use certain common determining factors of the entrepreneurial initiative. Various regional developments are accounted for by an emerging entrepreneurship potential, independently of certain geographical cliché or of any deterministic nature.
The emergence of new perspectives in creating competitive advantages at national level clearly emphasizes the role of local factors and economic initiative in the general economic development of a country through conceptual constructions such as industrial clusters or districts, innovation networks or competence centres. However, at the same time there is a reduced offer of empirical analysis which examines the relation between economic initiative and local economical development systematically (OECD 2003: p. 10; p. 13).
The regional environment is shaped by three important groups of influences on entrepreneurship, namely factors specific to the macro-climate, micro-climate factors and factors specific to each person. The enterprise macro-climate is characterized by indicators which reflect such aspects as regional infrastructure, regional cultural level, economic situation, or political systems. All these factors however receive different interpretations and therefore the micro-climate factors of the entrepreneur's 'world' are represented by this infinite variety of ways of perceiving the surrounding reality. Thus, the reactions, the vision, the strategy, the action manner, the efficiency and of course the success are mostly the result of micro-climate factors beneficial for the enterprise initiative. Another category of factors specific to the entrepreneur includes age, gender, social status, education level; these factors can describe the intensity of the latent enterprise initiative or the evolution of the already manifested one.
The theoretical background increasingly combines the macro aspects of industrial policy with the regional ones of the economics of agglomerations. The EU experts wonder in a report of the European Commission (2002) if cluster policy is not a way of reaching the EU landmark objective of becoming the most competitive region in the world at the horizon of 2010. The same study offers details that are less common for standard economic texts: the initiatives dedicated to generating new businesses were equally divided between medium and big urban localities, and rural ones and small towns (European Commission 2002: p. 21). This is prima facie evidence regarding the existence of some conditions for the development related rather to the economy of the region than to some inherently better influences, of historical, psychological or any other nature.
Beyond the academic preoccupation, it can be distinguished a reorientation of the public attention towards this kind of problems. For example, if the annual competitiveness reports of the European Union (EU) focused at the beginning only on the comparison between EU and its advanced peers, the last reports reveal a need of extending the analysis regarding the implications of the competitive policies to a national level.[1] This particularly means that regional competitiveness plays a new, enhanced role through its emphasis on regions that enjoy the biggest increases of competitiveness. At the same time, the regional level of analysis also crosses the national borders by drawing attention to the way the productive capacities are reallocated in the widened European area especially because of the increase of the industrial production in those fields where important economies of scale (internal or external) can be achieved.
This material proposes first a review of the theoretical aspects of regional competitiveness in order to enlighten the factors and analytical approaches usually deemed relevant to determine which factors of local development affect success or lead to failure. The second section offers a first glimpse on the entrepreneurial potential of the Romanian regions. Finally, in the third section, several indicators of measurement are discussed for their significance in producing reasoned policy recommendations.
I Process
Irrespective of definitions, competitiveness is normally linked to such tangible outcomes as continued productivity growth, high real wages and standards of living, and vibrant processes of innovation. Conditions that are necessary for the study of national competitiveness are likely to be common to regional-level analyses, although in this latter case the usual constraints - membership of a currency union, factor mobility, barriers to trade, absorption of macroeconomic shocks - are indefinitely relaxed. At the same time, the reciprocal relationship should also be considered especially in connection to the cooperative behaviour on the international level.
If a definition is nonetheless required, regional competitiveness may be defined as the ability of a region and, therefore, of its public authorities, to retain its local businesses and skills base and to attract foreign investment (CSR and the SME). Its competitive characteristics are accordingly based, albeit not exhaustively, on:
- Infrastructure quality
- The general quality of the environment
- The quality of the region's research and innovation centres
- The ability to retain and attract skilled manpower
- Taxation
- Workforce cost and quality
The normal analytical framework uses concepts from
However, the economists are well aware that growth and competitiveness more often than not are not part of a positive correlation implying that more growth is equivalent to improved competitiveness. It is for this reason that an analysis of the unfolding developments should be carefully considered against the theoretical background. In this sense, the EU adds valuable clarifications to the understanding of the objectives of any competitiveness initiative: 'The aim of the new regional competitiveness and employment objective is to anticipate and promote economic change by improving the competitiveness and attractiveness of EU regions.' (Commission 2005: p. 90)
There is a clearly defined tendency (Commission 2003: p. 131) to link the concept of regional competitiveness to those circumstances of economic activities conducive to clustering in a limited number of places and within clearly defined boundaries. Clusters are generally associated with better economic performance:
l
Financial
services in
l
Fashion in
l
Entertainment
in
l
Chemicals
in
l Movie production in Buftea area
The insights from the new economic geography offer the basics of the economics of agglomerations (clustering):
l Agglomeration of economic activities is dependent on the force of dispersion and the force of concentration
l At very high trade costs, industries will be forced to develop locally
l At very low costs, necessary inputs can be delivered to wherever the factor costs are lowest
l The agglomerations reinforce the comparative attraction of regional economies
Observations of various instances of regional development reveal that non-codified knowledge plays a salient role in laying the foundations of any form of local/regional economy. This tacit form of knowledge is 'sticky' because it borrows from local patterns of development and consequently it is best transmitted via face-to-face interaction. Geographical proximity matters because social capital - the standard representation of tacit knowledge as factor of production - uniquely configures a region in terms of its intrinsic conditions for competitive upgrade.
The breadth of regional advantage is twofold:
Figure 1. Capital and mobility
The Cluster - Standard definition and characteristics
Clusters are geographic concentrations of interconnected companies, specialized suppliers, service providers, firms in related industries, and associated institutions (for example, universities, standards agencies, and trade associations) in particular fields that compete but also cooperate. (Porter) From this definition results that a typical representation of agglomerative economies is described simultaneously by
l Spatially concentrated economic activities
l Critical mass of economic actors
l Specialized economic actors
l Multiple actors, which addresses several a bundle of markets
l Competition and cooperation strategies involving the participants
l Adaptation over time among the various actors that are interlinked through the cluster.
Regional competitive success is built on such factors as:
l Clusters and Productivity
Access to Specialized Inputs and Employees
Access to Information
Complementarities
Access to Institutions and Public Goods
Incentives and Performance Measurement
l Clusters and Innovation
New buyer needs
New technological, operating, or delivery possibilities
Capacity to act rapidly on these insights
l Clusters and New Business Formation
Barriers to entry
are lower than elsewhere
Better information about opportunities
Firms easily perceive gaps in products, services, or suppliers to fill
A lower risk premium on capital
A significant local market
Barriers to exit can also be lower
l Competition and cooperation within clusters
Vertical
relationships (those with buyers and suppliers)
Sharing
information that can contribute to new product and process developments or to
allow gains through better coordination of activities
Horizontal
relationships (those with direct competitors)
Tradeoff
between access to greater resources versus the potential for loss of
proprietary information or the creation of stronger competitors
Table 1. Activities that are regarded as being of some importance or of importance for coordinating activities among the firms in the clusters
|
R&D |
Basic research Applied research |
|
Production |
Production Bundling of products and services from several firms |
|
Inputs |
Joint purchase of raw materials, components Joint purchase/carrying out of service functions |
|
Training |
Management training Other education or training Technological survey |
|
Marketing and sales |
Market research Joint branding Joint selling activities |
|
Logistics |
Joint warehousing Joint transportation |
|
Government relations |
Lobbying government Coordinating public-private investments |
Cluster analysis must become part of competitive assessments, along with company and industry analysis.
The appropriate question for firms is not whether to compete or cooperate, but rather on what dimensions to compete and on what dimensions to cooperate.
Private sector roles in cluster upgrading can be found in all parts of the diamond.
Pitfalls on the way to regional development
1) Sclerotic industrial agglomerations
l In the eighteenth century, Sheffield (
In the late nineteenth century, Sheffield was overtaken by its long term
rival,
Seki (
In the early 1990s, there were approximately 300 cutlery firms in
2) The low end of high tech - the technological threshold
Table 2. Examples of regional clusters (S= Science based; T= Traditional)
|
Country |
Cluster name |
|
|
Technology
Cluster in |
|
|
Chemical
Industry, |
|
|
Industrial
District of |
|
|
The Dublin Software Cluster (S); The Dairy processing Industry (T) |
|
|
Biomedical cluster in Emilia-Romagna (S)¸ Eye-glass cluster in Belluno County (T) |
|
|
The
Cluster of Machine-Tools in the Basque Country (S); Shoe Manufacturing in the
|
|
|
Cambridgeshire (High-tech) (S); British Motor Sport Industry, Oxfordshire/ Northamptonshire (T) |
Source: European Commission, 2002
Policy initiatives
Analytical framework (
1. Causes of growth. Why do some regions grow faster than others? What are the primary initiating factors responsible, and through what processes do these causes operate? What is the role of interregional trade, migration, and investment in the spread of development from one region to another?
2. Structure. How does regional economic structure relate to growth? What kinds of structure are conducive to growth, or the reverse? What structural changes are associated with growth?
3. Convergence. Why is convergence so much in evidence? Is it universal and inevitable, or is it subject to reversals?
4. Control over regional development. Can regional development be substantially guided by policy? If so, what are defensible objectives and appropriate policies?
On overview of the European policy initiatives is provided by Table A1 in Annex.
Specific initiatives:
Taking account of specific geographic situations
Certain territories experience
Competitiveness handicaps that are hard to overcome
General initiatives:
Developing regional innovation structures, based on region-specific priorities, needs, circumstances and preferences that vary depending on the period of time and the region in question
Stakeholders industry and trade, universities, technical universities, research institutes
Policy actions: industry-specific education and training programmes, to familiarise people in the use of new work methods and tools; to ensure the availability of competent workforce while considering the regions' changing economic structures, the provision of entrepreneurship training, from primary school to university, to promote the development of services and markets that support entrepreneurship, to adapt technologies and procedures that can change existing production structures and enhance overall productivity.
II Entrepreneurial potential of the Romanian regions
This section attempts to glance through the workings of the real economy with the help of some empirical evidence on the Romanian economy. Against that background, a methodology to link development to entrepreneurship is proposed and subsequently discussed. Given the limitations, the dataset has been selected with respect to the longest possible list of economic and social-cultural aspects which by and large correspond to the macro- and micro-climate of influences on entrepreneurship. A set of thirty-three indicators[2] has been processed for all 42 regional administrative counties / units with the help of the statistical software SPSS, using the cluster method. This cluster method is based on a specific algorithm for an optimum grouping of the counties depending on the similarities and differences between the selected indicators. The programme groups similar counties based on the selected indicators while the particular cases presenting specific properties much different from the other cases, appear separately.
The 'cluster' number or the number of similar areas (counties) has been set to eight. This option is sustained by the argument that there are as many development regions, and by analogy there can be observed how the counties fare in this statistical investigation as opposed to their administrative location. On the other hand, other types of divisions which were experimented, for example in groups of 2, 4, or 6, frequently led to many groups represented by only one county that made the analysis highly irrelevant.
The conclusions include observations on various iterations depending on different combinations of the chosen indicators, but a special significance has been given to the combination that gets together the whole set. Particular references are made only to this latter case. The results are given in Table A2 and Figures A1 and A2 in the appendix. The findings attempt to reveal local areas of development (counties) with a developed entrepreneurial spirit, those that possess such potential and those with a poor situation and contrast these more nuanced results with the familiar image of, say, discrepancies between the advanced West and the poor East.
There should be first noted that the
processed data reveal several 'isolated' countries/areas-Bucuresti,
Arges,
More interestingly, the forming of a
cluster of counties with very good performance levels-Brasov, Timis,
Cluj, Iasi, Bihor, Bacau, Galati, Prahova, Mures, Dolj (Table
A2, second row)-is suggestive of a remarkably even distribution of
entrepreneurial activity throughout the country. According to the logic of this
methodology, these counties show the highest level of the enterprise
development. Two observations arise in this context. First, this group features
a sub-cluster consisting of
There are still other several counties with
a manifest good potential for enterprise development, but in their case
adequate support programmes are needed. For counties like
A notable implication of the analysis consists in the strength of the interdependence between the economic factors and the social-cultural ones within a region. Generally, it may be noticed that counties with a good economic milieu also present a favourable social-cultural situation; the relation goes the other way around too.
These estimates reache results that are similar to conclusions of reports touching on the same topic (e.g. UNDP 2004). It nevertheless advances the discussion by finding similarities over a mixed set of influences on entrepreneurship across Romanian regions. The conclusions come in two areas of interest.
Firstly, the results underpin a view on enterprise dynamics that may be reasonably divided in three areas of development. There is first a group that shows a favourable climate for enterprise initiatives, from business performance to market networks and supporting social infrastructure. There are then counties satisfactorily positioned to outgrow their present medium-level enterprise development level. They certainly have strong advantages that must be further pursued, but at the same time favourable conditions must be created for the diversification of the regional enterprise initiatives. Through inadequate policies, these areas with potential can be forced towards involution as well, and it is precisely for this reason that this case requires special attention. Finally, the remaining counties expose such a large range of unsuccessful achievements that makes them unattractive for business development.
Secondly, it is somehow part of the intellectual tradition the fact that regional development should be understood in terms of different business habits, favouring 'mentalities', in general, inherently better conditions in certain regions as opposed to others. This investigation acknowledges indeed different practices with regard to regional business initiatives, but the abilities for the establishment of some thriving economic activities find a favourable environment for manifestation in any region. The variety of local conditions and capabilities forms a particular development fabric which should be put to good use through public policies and business strategies.
III Measurement
This section deals with how to measure regional competitiveness and its main determinants. Although there is no universally accepted definition of regional competitiveness, this concept is intended to measure the level of economic success displayed by regions. This is usually done by constructing a set of indicators and then comparing them, across regions, in order to quantify the level of success each region has achieved. The usefulness of this exercise is to see whether the factors underlying success can be applied elsewhere, notably in regions that perform more poorly.
Although both theoretical and empirical work have generated a series of indexes that assess a region's competitiveness, a few issues need to be addressed first, namely:
What are the determinants for regional development?
Which indicators are most appropiate to describe the level of regional development?
What do these indicators imply for the direction of causation
To what extent data availability allows regional analyses in comparable terms.
As a general rule, competitiveness is determnined by productivity, defined as a the output value per units of input, with which a region employs its human, capital and natural resources. In turn, productivity sets a region's standard of living as reflected by wage level, returns on capital and human resources. In fact the link between productivity and 'per capita' GDP is quite strong. This can be seen by breaking down the 'per capita' GDP indicator into a series of component factors:
(Productivity) * (Work-Leisure choice) * (Employment Rate) * (Demographic Factor)
Thus, one of the most common regional indicator used in practice to measure a region's economic success is the GDP per capita. In the expression above productivity is defined as GDP/hours worked. In contrast to the other way of measuring productivity, GDP/employee, the GDP/hours worked indicator has the advantage of measuring more accurate the labour effort, an important consideration when particular sector activities require different profiles of work intensity.
A variety of general factors affecting competitiveness are suggested by the literature (see Figure 1.3). For instance, neoclassical theory stresses out the importance of physical and human capital assuming that technological influences are exogenous. To remedy the ad hoc assumption of exogenous technological influences, the growth theory endogenised technology within the system, suggesting that the accumulation of knowledge could generate increasing returns - as brought about, for instance, by human capital accumulation.
Another stream of economic theory has attempted to explain regional competitiveness using the geographical concentration approach.
Figure 2. Regional Competitiveness Theories
The Neoclassical View Initial Conditions Level of Investment Human Capital Technology Driven Growth Theory Endogenous Technological
Advance Externalities Regional
Competitiveness GDP/Employee GDP/Hours Worked Economic Geography / Trade Theory Agglomeration Effects Urbanisation Transport Costs Economies of Scale Sectoral Specialisation Knowledge-Based Factors - input measures (human
capital, R&D infrastructure, investment in R&D, number of
researchers) -
output measures (patents, process and product innovation) Cost Competitiveness Unit Labour Cost Price of public input Ratio of prices tradeable/nontradeable
Source: Adapted from the European Competitiveness Report, 2003.
Cost competitiveness is another way through which regional competitiveness can be assessed. Economic theories that focus on cost are Ricardo's comparative advantage or Heckesher-Ohlin's trade thory. The unit labour costs (ULC) is a more direct way of measuring how expensive is production in a given region. ULC is defined as the ratio of labour costs per unit of output. Here, the former includes both the gross wage as well as indirect costs per employee. Thus, higher ULC implies a loss of competitiveness. This rises when the increase in labour costs is higher than productivity increases.
Obviously, different theories would require the usage of different indicators. However, in practice, a number of indicators could have similar informational content. Therefore the challenge is to select the most relevant indicators that would hold the highest explanatory power in assessing a region's competitiveness. The most common used indicators are listed below[3]:
Gross Value Added (GVA). It gives an indication of the value of economic activity in the region. It usually allocates the incomes received by employees to where they work. Often, the GVA/head figure is reported.
Gross Disposable Household Income. It measures the income received by households and implicitly, living standards.
Labour Productivity. This is computed as GVA/workforce job and could be assessed within different sectors of the regional economy ie industry, services, etc.
Investment by domestic and foreign firms. It expresses the potential future output growth of the region as it represents addition to the region's capital stock. A common proxy for investment is the net capital expenditure made by firms.
The Value of Exports. This is dependendent of the size of the regional economy. In the long run it is solely the increase in export value that ensures the expansion of the regional economy.
Average Earnings. This indicator measures the marginal product of labour and it is usually expressed as hourly earnings. Often it distinguishes gender pay, overtime and full time pay.
Employment and Unemployment Rates. These quantify the region's workforce participation rate.
Business Registration and Survival Rates. One indicator of business formation is the number of new VAT registrations each year as a percentage of firms registered for VAT at the end of that year. The survival rate reflects the number of firms - as given by the VAT registrations - still in business after a certain number of years[4].
Entrepreneurship. The indicator aims at measuring the contribution made by entrepreneurs to the regional economy.
Knowledge could be measured as the skills of the workforce, such as education levels or spending on education, or through measures such as R&D expenditure. The latter can, in principle be computed for three sectors - government, business, and higher education establishments - although in practice data availability constraints makes the choice of total R&D expenditure preferable in orderer to ensure reasonable coverage across space and time.
Innovation can be proxied by the R&D expenditure, expressed as above. Another way to measure innovation is by the percentage of firms that report co-operation agreements on innovation activities.
The stock of human capital can be proxied by the working population - by age structure if necessary - personnel employed in R&D, employment in high-tech sectors, total number of students and those involved in tertiary education.
Transport Infrastructure. This indicator could have many subcomponents but the relevant ones are the mode of transport to work and the average speed on roads.
Industrial property and office rental costs.
There are other factors - as suggested by theory - which can have an effect on competitiveness but for which there is no quantifiable approximation. For instance, much of government policy falls under this category, as do indicators measuring the extent of venture capital activity, business registration rates, and the presence of high-tech clusters. However, such features can be examined to see whether they are present in the characteristics of those regions which display them. In addition other factors such as the sectoral structure, investment or the degree of spillover effects are important when assessing a region's competitveness. Empirically, the most prosperous regions have high share in market services, usually, over 70%, but success tend to depend on the type of market service which dominates. For instance, tourism services are not associated with particularly high productivity levels. Investment measures the change in capital stock of a region's economy and is an important indicator of future output performance.
While indicators are useful in assessing a region competitiveness, most of the times these are computed in isolation. Creating a composite index at the local or regional level - that would comprise information contained in a number of different single indicators - would be a step forward. To date, there a number of organisations that compute such indices, a review of which is presented below:
The World Economic Forum (WEF) Index - Global Competitiveness Report 1999. This is one of the most complex attempts to date to construct a composite competitiveness index. It has been devised with inputs from Porter (1999). The index is based on quantitative and qulitativ data classified into eight groups with a weight of 75% for the former. Furthermore, the WEF Index assigns the following weights to each of the eight groups classification indices as follows: openess, finance, government and labour 1/6 each, infrastructure and technology 1/9 each, management and institutions 1/18 each. The weights are chosen through regression analysis looking at the correlation coefficient with the per capita economic growth.
The 3-factor model (Huggins, 2003) is a composite index which incorporates data available at local, regional and national level. The index is based on three components, inputs, output and outcomes. The variables used to construct the composite index - and their associated weights in brackets - are:
a) business density measured as the number of firms per capita (0.111). This is a measure of the potential future development of new firms.
b) proportion of knowledge-based businesses measured as the share of knowledge-businesses in total businesses (0.111).
c) GDP per capita, measures the historical impact of competitiveness (0.333)
d) average earnings, with high earnings being usually an indicator of high competitiveness (0.166)
e) economic activity rates which is a measure of how human capital is employed in a region (0.111)
f) unemployment (0.166)
Huggins (1999) calculates such a UK Competitiveness Index for all
regions of the
United Nations Industrial Development Organisation (UNIDO). UNIDO produces a scorecard which is comprised of two rankings[5]: 1) A competitive industrial performance index on the basis of four factors and 2) A ranking of economies by the five drivers of industrial performance, namely: knowledge, inward openness, financial system, governance and the political system. All these five factors are obtained through multivariate analysis from an intial set of 29 relevant indicators. Out of the five indicators, knowledge is by far the most important one and comprises of variables which are highly correlated with the creation, diffusion and use of knowledge such as R&D and innovation or quality mangement and education. The inward openess has indicators pertaining to import trade and inward FDI. The financial system indicator refers to aspects such as market capitalisation, country risk and access to credit.
The Development Report Card produced by the Corporation for Enterprise Development, which generates three indices:
a) Performance Index which measures the following: employment, earnings and job quality, equity (with respect to income), quality of life, resource efficiency and a number of trend indicators which measure changes in a set of variables.
b) Business Vitality Index which comprises of indicators reflecting cometitiveness of existing businesses, entreprenurial energy, and trend indicators
c) Development Capacity Index which includes information relating to human, fiancial and infrastracture resources, innovation assets, amenity resources and trend indicators.
The grades are computed as follows:
Raw data are collected for all the 68 measures contained in the indicators above[7].
Each state is individually ranked from 1 (best) to 50 (worst) in every measure based upon the raw data obtained.
To calculate both the index and subindex scores, the relevant measure rankings for each state are added together. Again, the scores are ranked from 1 to 50.
States that rank from 1-10 earn 'A's, those ranking from 11-20 earn 'B's, states that rank from 21-35 earn 'C's, those that rank from 36-45 earn 'D's and states ranking from 46-50 earn 'F's.
When a tie occurs, each state receives the same rank and the next best performing state is ranked as if the tie had not occurred. For example, if two states have the best score, each receives a '1' ranking and the next state is ranked '3'.
References
Bergman, Edward M. and Edward J. Feser, Industrial and Regional Clusters: Concepts and Comparative Applications, West Virginia University's Regional Research Institute, Electronic version, [https://www.rri.wvu.edu/WebBook/Bergman-Feser/contents.htm][26.10.2006]
Commission of the European Communities, 'Cohesion Policy in Support of Growth and
Jobs: Community Strategic Guidelines, 2007-2013', Com (2005) 0299,
Commission of the European Communities,
'European Competitiveness Report 2003', Commission Staff Working
Document, SEC(2003)1299,
Commission of the European Communities, 'Final Report of the Expert Group on
Commission of the European Communities, 'Regional Clusters in
''CSR in the SME and Regional Competitiveness' Working Group : Introduction'
[https://ec.europa.eu/enterprise/csr/documents/mainstreaming/ms_sme_topic1_discussion_en.pdf] [26.10.2006]
Department of Trade and Industry (DTI), Regional Competitiveness & State of the Regions, URN 06/259, July 2006.
Hoover, Edgar M. and Frank Giarratani, An Introduction to Regional Economics, 3rd Edition, West Virginia University's Regional Research Institute, Electronic version, 1999 [https://www.rri.wvu.edu/WebBook/Giarratani/hoover.htm] [Oct. 2006]
Huggins, Robert, Creating a
OECD, Entrepreneurship and Local Economic Development, Paris, 2003.
'Towards a New Regional Policy in 2007', Report adopted by the CPMR Political Bureau, Kastoria (Greece), 21 January 2000 [https://ec.europa.eu/regional_policy/debate/document/futur/organ/crpm_kastoria_jan00_en.pdf] [26.10.2006]
United Nations
Development Programme (UNDP) (2004), 2003-2004 National Human Development Report.
United Nations Industrial Development Organisation (UNIDO). Capability building for catching-up. Historical, empirical and policy dimensions, Industrial Development Report 2005
West Finland Alliance (WFA), 'European Union's Regional and Structural Policies after 2006 Regional Points of View', 24.4.2003
Annex. Tabel A1 Experiente nationale vest-europene privind initiativele de dezvoltare a aglomerarilor competitive
|
Tara |
Istoric |
Initiative selectate |
Criterii / Metode folosite pentru identificarea aglomerarilor |
|
Austria |
Sunt recunoscute un numar de aproape 50 de initiative, din care aproape 2/3 au aparut si au fost sprijinite la nivel federal. Guvernul incepe in 1998 un efort concertat de crestere a exporturilor prin promovarea aglomerarilor. Proiectul este organizat de Ministerul de Finante si Ministerul Economiei prin canalizarea de fonduri catre Camera de Camert (aflata in proprietatea statului) pentru institutionalizarea aglomerarilor. Obiectivele legate de export vizau in special concentrarea resurselor de marketing si vanzari prin activitati precum reprezentare colectiva la manifestari expozitionale, studii de piata pentru debuseele de export, activitati de influenta guvernamentala. Manifestarile regionale se evidentiaza puternic in Austria Superioara (Upper Austria) si Austria Inferioara (Lower Austria). Instrumentele de sustinere folosite sunt mai ales de natura ne-financiara si se concretizeaza in imbunatatirea circuitului informational, a cooperarii intre firme si institute de cercetare si dezvoltare, pregatirea fortei de munca si servicii comune de marketing si export. |
Austrian Food Cluster Automotive Cluster Vienna Ecological Construction Cluster Lower Austria Timber Cluster Lower Austria |
1) Orientarea relatiilor de afaceri pe orizontala si verticala. 2) Estimarea competitivitatii internationale. |
|
|
|
|
|
|
Belgia |
Politicile specifice urmeaza un traseu separat in cele doua regiuni importante, flamanda si valona. Regiunea flamanda initiaza astfel de politici in 1994. In iunie 2001, se creeaza un instrument specific, "Cooperare Flamanda pentru Inovare". Procesul este organizat in doua etape: (1) Acreditarea aglomerarii din partea Guvernului Flamand. Costurile operationale ale institutiei sunt subventionate; (2) Acces la masuri de sprijin care pot lua forma consultantei, granturi si imprimuturi pentru proiecte de inovare si cercetare-dezvoltare. In Regiunea Valona sunt promovate doua initiative complementare: Contrat d.Avenir pour la Wallonie, dedicata domeniului economic, si Promethée Programme, dedicata tehnologiilor. |
Digital Signal Processing Valley (DSP) Walloon Aeronautical Cluster (EWA) |
Intreprinderi si/sau institutii regionale care in mod voluntar, dar activ se grupeaza pentru a crea sinergii in domenii precum cercetare-dezvoltare, inovare, calificare, productie, comercializare. |
|
|
|
|
|
|
Danemarca |
Ministerul Afacerilor Economice are rolul de conducator in initierea programelor, in timp ce implementarea lor se face prin participarea guvernelor regionale. Atentia acordata dezvoltarii aglomerarilor a aparut necesara in contextul formularii noi noi politici industriale care sa identifice centre de competenta nationale si regionale. Un Raport din 2001 identifica 29 de aglomerari, din care 16 cu acoperire nationala, iar 13 de tip regional. Intr-o etapa ulterioara, au fost pregatite masuri de sprijin al dezvoltarii institutionale, tinand cont de particularitatile fiecarei aglomerari. |
Medicon Valley NorCom Wireless Communication Cluster |
Interviuri adresate unui numar de 75 de experti suplimentate de indicatori cantitativi privind mediul de afaceri si specializarea de export. |
|
|
|
|
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Finlanda |
Interesul a vizat cu prioritate coagularea resurselor la nivel local, regional si national pentru dezvoltarea unor domenii de competenta competitive pe plan international. Programele au fost aplicate in perioada 1994-1998 si au ajutat la formarea si consolidarea legaturilor de cooperare intre diferiti actori regionali. Pe langa sprijinul specific acordat unui numar important de intreprinderi mici si mijlocii, rezultatele notabile se refera la creearea Centrelor de Expertiza, 14 la nivel regional si 2 in retea nationala. Activitatea lor are loc prin cooperarea dintre industrie, guverne locale, alte autoritati publice, centre tehnologice, universitati si institute de cercetare. Responsabilitatea gestionarii acestor organizatii revine de regula centrelor tehnologice. Institutionalizarea aglomerarilor are loc prin proceduri de licitatii bazate pe criterii precum standarde internationale inalte, aordari inovative, impactul potential al masurilor propuse si organizare eficienta. |
Finnish Forest Cluster Programme Wood Wisdom Global Village (TLX) |
Legaturi inter-industriale intre 68 de ramuri suplimentate de date privind exporturile si investitiile. |
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Franta |
Agentia guvernamentala de planificare spatiala - DATAR Délégation à l'Aménagement du Territoire et à l'ActionRégionale- si-a asumat rolul de a dezvolta o politica a Sistemelor Productive Locale (SPL). In 1999, apare primul studiu comandat de DATAR care facea publica o harta a aglomerarilor regionale. In 2001, apar alte cateva studii similare efectuate de firme de consultanta (Bernard Reverdy Consultants; Michel Le Duc Consultants). Politica SPL se bazeaza pe cateva coordonate de baza si anume: 1) incurajarea cooperarii intre firmele componente ale aglomerarii; 2) incurajarea cooperarii dintre firme si institutiile de educatie si cercetare regionale; 3) formarea unor politici de dezvoltare locale prin comunicarea institutionala dintre autoritatile publice si organizatiile locale. Politica SPL a luat nastere prin doua tipuri de initiative. Pe de o parte, prin licitatii succesive in 1998 si 1999, au fost selectate 96 de proiecte din 202, care au devenit oficial SPL. Pe de alta parte, ca urmare a institutionalizarii, aglomerarile recunoscute au avut posibilitatea sa solicite fonduri publice pentru realizarea programelor. La initiativa districtului industrial din Vallée de l'Arve, a fost creata in 1997 o federasie nationala a aglomerarilor franceze sub titulatura Club des districts industriels français (CDIF). Principalul obiectiv este de a crea o retea a SPL pentru diseminarea bunelor practici, promovarea know-how, precum si stabilirea unei interfete cu institutiile franceze si europene. |
Cluster des 'bio produits' (Rhône-Alpes) Cluster des Loisirs Numeriques (Rhône-Alpes) Cluster du Neige (Rhône-Alpes) MedInSoft Cluster (Provence) |
Sistemele de productie locale sunt caracterizate prin (i) o concentrare locala a intreprinderilor mici si mijlocii, (ii) apartanenta acestor intreprinderi la cateva ramuri sau activitati, (iii) firmele se afla in stare de cooperare si concurenta, (iv) regiunea cuprinde activitati inrudite precum servicii de afaceri sau cercetare-dezvoltare, si (v) existenta unei "culturi" comune organizatiilor din acea zona. |
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Germania |
Autoritatea federala nu a fost implicata mult timp in proiecte specifice. Se remarca totusi activitatea Ministerului Federal pentru Educatie si Cercetare in programe de cercetare, investitii pentru infrastructura si fonduri de capital pentru infiintarea unor noi firme. In 1996, lanseaza BioRegiocontest in 1996, prin care organiza o competitie intre cele mai avansate regiuni cu potential competitiv la scara internationala. S-au remarcat trei regiuni din partea vestica - BioRegion Rheinland, BioRegion Rhein-Neckar-Dreieck si BioRegion München - si una din fosta regiune comunista - BioRegion Jena. Politica aglomerarilor este in mare parte o componenta a politicilor regionale. Exista o varietate de initiative regionale concentrate pe dezvoltarea aglomerarilor. Proiectul REKON isi propune schimbarea structurala in regiunea Rinului de Nord-Westphalia. Aglomerarile institutionalizate folosesc in comun aceeasi structura manageriala, pentru ca dupa un timp sa revina la auto-gestiune. Masurile sunt concetrate pe nevoile locale. In regiunea Ruhr, proiectul vizeza firmele active in domeniul constructiilor si mestesugurilor cu obiectivul de a inlocui modul traditional de productie "auto-suficienta" a firmelor locale prin cooperare in dezvoltarea unor noi produse si intrarea pe noi piete. Managementul unei aglomerari este responsabil pentru consultanta manageriala, dezvoltarea si implementarea proiectelor de cooperare. |
Automotive Saarland it.saarland BioRegio München |
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Italia |
Adoptarea legilor 317/1991 si 598/1994 au permis initierea unor politici industriale orientate catre sisteme de productie locale si districte industriale. Aceste politici vizeaza in principal dezvoltarea centrelor si structurilor intermediare de cercetare, experimentare, proiecte pilot, programe de calificare, modernizarea productiei si consultanta tehnica pentru inteprinderile mici si mijlocii. Obiectivul final este cresterea nivelului tehnologic si capabilitatii inovative la aceste firme. Implementarea masurilor are loc prin conectarea politicilor nationale cu initiativele regionale si locale. Rezultatele pot lua forma parcurilor stiintifice, centrelor pentru incurajarea inovatiei, centrelor sectoriale pentru transfer tehnologic si a asistentei tehnice generale la nivel local. In general, aceste "centre" sunt promovate si conduse in comun de regiuni, institutii de finantare regionale, camere de comert, impreuna cu firme si asociatii profesionale. |
Managements & Buildings South Tyrol Cluster IT & Software Engineering Bolzano Cluster Quality Butchers of South Tyrol |
Districtele industriale sunt sisteme locale de munca care (i) au o pondere mai mare decat media a lucratorilor in industria de prelucrare, (ii) sunt specilizare in sectorul de prelucrare, si (iii) au o concentrare de lucratori in intreprinderile mici si mijlocii. |
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Olanda |
Politica aglomerarilor urmareste cooperarea tehnologica in vederea imbunatatirii competitivitatii si inovativitatii firmelor prin trei functii de baza (1) crearea unor conditii cadru favorabile pentru industrie si servicii in general, (2) realizarea unor functii de broker prin alaturarea ofertei si cererii si furnizarea informatiei strategice, si (3) intelegerea rolului guvernului ca un consumator pretentios si sofisticat care furnzeaza nevoi sociale. Sunt folosite doua instrumente principale. Primul consta in crearea conditiilor favorabile prin aplicare unor politici specifice. Al doilea consta in actiunea de tip broker. Ministerul Afacerilor Economice incearca sa stimuleze aglomerarile prin furnizarea de informatii privind oportunitatile si posibilitatile de concentrare a activitatii, organizarea dialogului si contactului dintre participantii potentiali, coordonarea procesului de concentrare, introducerea unoi noi contacte, retele si instrumente financiare. Mai mult de 10 initiative au luat nastere prin implicarea directa a acestui Minister. |
Genomics Katalyse ECP.nl |
Aglomerarile din activitati economice inrudite sunt identificate prin conexiunile dintre principalii furnizori de bunuri si servicii si principalii consumatori. Metoda este formata din (i) legaturi inter-industriale intre 214 grupari industriale, si (ii) analize de tip "produce si foloseste" pentru 650 categorii de produs si 260 categorii de activitati economice. |
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Norvegia |
Primul instrument de politica dedicata aglomerarilor a fost introdus in 1998 sub forma unui program experimental de 4 ani numit REGINN (Regional Innovation System). Obiectivul programului era de a stimula cooperarea intre firme din diferite sectoare si organizatiile de cercetare si de invatamant locale in vederea atingerii unei capabilitati inovationale sporite. Initiativa si fondurile destinate programului REGINN erau de natura publica. Accesul in cadrul proiectului era destinat celor 19 regiuni si s-a facut prin intermediul unei pre-calificari in baza analizelor inovatiei regionale si a propunerilor pentru proiecte concrete de inovatie. Proiectele se desfasurau la nivel regional prin gestiunea, de regula, a unui institut de cercetare regional. Exemple de initiative includ dezvoltarea unei noi tehnologii, metode de organizatie. |
The maritime cluster The Norwegian oil and gas cluster |
Aglomerarile regionale indeplinesc urmatoarele criterii: (i) piata muncii este reprezentata la nivel regional, (ii) regiunea ese specializata in cel putin unul din 39 sectoare industriale (cu un coeficient al locatiei egal sau mai mare de 3.0), si (iii) sectoarele specializate trebuie sa includa cel putin 200 de locuri de munca si 10 firme din regiune. |
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Portugalia |
Autoritatile portugheze au comandat lui Michael Porter un studiu care sa puna in evidenta dezvoltarea competitivitatii internationale a industriilor prin evidentierea sectoarelor care aveau o cota de export comparativ mare. Una dintre implicatiile acestei cercetari a fost definirea unei strategii nationale pentru dezvoltarea unora din industriile de export in aglomerari. Una din initiativele adiacente este Programul Integrat de Sprijin al Inovatiei (PROINOV) al carui punct focal il constituie inovatia si aglomerarea prin dezvoltarea initiativelor plecand de la un grup industrial definit. Printre actiunile incurajate se numara colaborarea intre firme, intre acestea si asociatiile de afaceri, instituttiile de educatie, de cercetare si financiare. |
Footwear cluster Metallic moulds (Leiria) |
Sectoare industriale cu specializare de export (caracterizate prin avantaje comparative). |
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Spain |
Initiativele sunt aproape exclusiv de competenta guvernelor regionale. In mod proeminent, se remarca experientele din Galitia, Tara Basca si Catalonia. In 1991, regiunea Basca punea in aplicare instrumente de politica dedicate stimularii gruparilor economice particulare (aglomerari) care apartineau de sectorale industriale importante ale regiunii, considerate in perspectiva curenta si viitoare. Institutionalizarea a cuprins mai mult de 10 sectoare. Sprijinul public era canalizat prin asistenta financiara destinata sa acopere partial costurile activitatilor specifice aglomerarii, precum calificare, circulatia informatiei, cooperare cu centre tehnologice. |
Catalonia Pharmaceutical cluster Consumer Electronic in Catalonia Knitwear Cluster in Anoia, Catalonia Galician Automotive Industry (CEAGA) |
Sistemele de productie locale au fost identificate prin concentrarea locala a intreprinderilor mici si mijlocii, care apartin catorva industrii, aflate adesea in relatii de colaborare prin relatii de aprovizionare. Agentii locali se definesc de asemenea si prin agrearea unui set comun de valori si norme culturale. |
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Suedia |
Principalul obiectiv al programelor nationale consta in consolidarea politicilor de dezvoltare regionala si industriala mai ales prin incurajarea sistemelor de inovatie. Un astfel de program a fost conceput pentru perioada 2002 - 2004. Stimularea aglomerarilor este vazuta ca o strategie pentru facilitarea transformarii industriale si dezvoltarea capacitatii companiilor suedeze de a concura global. Programul destinat aglomerarilor cuprinde cateva puncte de referinta: (i) masurile au la baza analize; (ii) identificarea oportunitatilor si amenintarilor in dezvoltarea industriala cu privire la functionarea eficienta a sistemelor de inovatie si a aglomerarilor; (iii) este acordat sprijin pentru verificarea calitatii, operationalizarea cercetarii dezvoltarii si crearii de retele in cadrul aglomerarilor. Aglomerarea va fi conectata la acorduri regionale privind cresterea economica intre regiuni si guvern. |
Fiber Optic Valley Future Position X (Gävle) Game- and Film Factory (Umea-Skelleftea) Heavy Vehicles (Kronoberg) IGIS (Innovative Geografic Information System) |
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Marea Britanie |
Departamentul de Comert si Industrie (www.dti.gov.uk) publica in 1998 o Carte Alba a Competitivitatii intitulata "Our Competitive Future: Building the Knowledge Driven Economy", efort care numara printre implicatii angajamentul administratiei britanice de a investiga conceptul aglomerarii. In noiembrie 1999, sunt anuntate doua initiative. Prima se referea la infiintarea unui Grup de Initiativa a Politicii Aglomerarii, care avea in componenta lui membrii ai guvernului, agentiilor de dezvoltare regionala, guvernelor locale, universitati, sectorul privat, experti. Grupul urmarea sa identifice barierele in calea dezvoltarii aglomerarilor si sa conceapa solutii de politica adecvate. A doua initiativa se referea la un proiect de cercetare de creionare a hartii concentrarilor existente. Rezultatul avea sa fie publicat in 2001 sub titlul de 'Business Clusters in the UK - a First Assessment'. In Scotia, Tara Galilor si Irlanda de Nord politica este implementata, respectiv, de ScottishEnterprise, Adunarea Galeza si de catre Departamentul pentru Firme,, Comert si Investitii. In partea scotiana, efervescenta initiativelor publice este foarte bine pusa in evidenta. Prin Scottish Enterprise Network (SE) a fost impusa ca prioritate incurajarea aglomerarilor in economia scotiana. Au luat fiinta in consecinta patru aglomerari pilot, in industriile petrol si gaze, semiconductori, alimentara si biotehnologie. Toate cele patru pun in aplicare planuri de actiune de transformare industriala pentru urmatorii 5 pana la 10 ani. |
Clothing & Textiles Cluster, East Midlands Humber Seafood Cluster Project Medilink East Northwest Automotive Alliance Scottish Energy Industry Scottish Enterprise Life Scottish Food & Drink |
Etape de parcurs: (i) identificarea "varfurilor regionale", de ex. sectoare care au un coeficient al locatiei peste 1,25 si/sau peste 0,2 % din forta de munca regionala, (ii) gruparea sectoarelor astfel identificate in aglomerari, si (iii) interviuri extensive cu reprezentanti ai aglomerarilor, agentiilor regionale, institutelor de cercetare pentru a clarifica in ce masura aglomerarea de "varfuri regionale" reprezinta intr-adevar agomerari (competitive). |
Observatory 2002, 24-25, Porter 1998, The Competitiviness Institute
Table A2 Characteristics of Romanian clusters
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County cluster composition |
Common characteristics |
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Bucuresti (B) |
Highly positive levels of indicators on all influences under investigation, except for the criminality rate |
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Galato (GL), Prahova (PH), Dolj (DJ), Timis
(TM), Bihor (BH), Cluj (CJ), |
High density of population High rate of unemployment High level of education Large number of employees Low salaries |
Large number of companies, but relatively few when divided by the number of inhabitants Interest for research-development area Very low intensity of sports activities, largely concentrated in few big cities Adequate sanitary infrastructure Good level of budgetary revenues |
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Dense population High level of employment Relatively low levels of unemployment High level of education Large number of employees, mainly in construction, tourism, transportation, estate transactions and other services Relatively high salaries |
Very high levels of turnover and investments Relatively high number of libraries Intense sports activities Poor quality of health infrastructure Modest levels of research-development Medium criminality rate Very good level of budgetary revenues |
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Arges (AG) |
Low level of unemployment High level of educated people Large number of employees in industrial activities Small number of employees in construction Relatively low salaries Very high levels of turnover and investments |
High spending on research-development High number of libraries Intense sports activities Very good quality of health infrastructure Medium business density |
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Gorj (GJ), Hunedoara (HD), Ilfov (IF) |
Dense population Relatively high unemployment, low employment Poor education Large number of employees in research-development Few libraries |
High criminality rate Low number of companies Relatively high levels of turnover and investments (on a per capita basis) Developed sanitary infrastructure Good level of budgetary revenues |
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Botosani (BT), Neamt (NT), Vaslui (VS), Buzau (BZ), Dambovita (DB), Teleorman (TR), Olt (OT), Valcea (VL), Arad (AR), Maramures (MM), Alba (AB), Mures (MS), |
Relatively low level of density of population Very low level of employment High unemployment Average level of education Small number of employees Lowest levels of salaries Below average number of companies Modest turnover |
Few investments Low interest for research development Few libraries Modest sports activities Modest sanitary infrastructure Low level of budgetary revenues Average criminality rate |
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Mehedinti (MH) |
Low level of research development Average levels of turnover and investments |
Very few employees in tourism and catering Relatively intense activity in construction |
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Caras-Severin (CS),
Bistrita-Nasaud (BN), |
Extremely low levels of indicators on all influences under investigation |
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Source: Processed data and statistics from INS (2005)
Figure A1 Map of clusters of entrepreneurial activity in
Source: Processed data. A lighter colour means a less favourable scoring on the selected indicators for the particular cluster. The complete datasheets are available from the author on request.
Figure A2 Map of clusters of entrepreneurial activity in
LOCKM, POC, R-SOM, NMS, CSMNL, ULAICCS, CA, IB, CTACD, TVBL, R-CRIM, CAPLOC, IBPLOC, CTACDLOC See text (section II) for definitions.
Source: Processed data. A lighter colour means a less favourable scoring on the selected indicators for the particular cluster. The complete datasheets are available from the author on request.
The full set of reports on competitiveness can be found at https://ec.europa.eu/enterprise/enterprise_policy/competitiveness/
Inhabitants per square kilometre -LOCKM, Active employed population -POC, Unemployment rate -R-SOM, School population within the pre-school education -PSPRS, School population within the superior education -PSSUP, Average number of the employees -NMS, Average number of the employees within industry -NMSI, Average number of the employees within constructions -NMSCNS, Average number of the employees within commerce -NMSCOM, Average number of the employees within hotels and restaurants -NMSHR, Average number of the employees within transport, storing and communications -NMSTDC, Average number of the employees within financial services -NMSIF, Average number of the employees within real estate transactions and other services -NMSTIAS, Average nominal monthly net salary -CSMNL, Active local units within industry, constructions, commerce and other services - ULAICCS, Turnover -CA, Gross investments -IB, Employees within the development research activity per 1000 civil employed persons -SACD, Total expenses in the development research activity -CTACD, Total number of libraries -NTB, Identified sportsmen -SL, Number of hospitals -NS, Number of beds in hospitals -NPS, Criminality rate (crimes investigated by police per 10000 inhabitants) -R-CRIM, Total income to the local budget -TVBL, Turnover per inhabitant -CAPLOC, Gross investments per inhabitant -IBPLOC, ULAICCS per inhabitant -ULAPLOC, CTACD per inhabitant -CTACDLOC, SL reported to the number of inhabitants -SLLOC, NS reported to the volume of the population -NSPITLOC, NPS reported to the volume of the population -NPSLOC, TVBL per inhabitant -TVBLPLOC.
The rankings are at the national level. However, data availability allows these indices to be computed at regional level as well.
The analysis captures the idea that a complex data set can be reduced to a smaller number of uncorelated composite variables, each reflecting a specific dimension of the dataset's total variance.
Each of the indicators mentioned above has more sub-indicators, a
number of which totals 68. A complete definition of those is given on the
CFED's website www.cfed.org. The indices are
computed for the
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