Journal of Competitiveness

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Journal of

Competitiveness

A Comparative Analysis o the Competitiveness o theReadymade Garment Industry Clusters in Delhi, Dhaka and

ColomboChoe, KyeongAe; Nazem, Nurul Islam; Roberts, Brian H.; Samarappuli, Nihal;

Singh, Rajveer

Determinants o Competitiveness: A Study o the IndianAuto-component Industry

Joshi, Deepikaa; Rathore, Ajay Pal Singh; Sharma, Dipti

Multidimensional Networks: Te Changing Character and

Framework o Inter-rm CollaborationPloder, Michael; Steiner, Michael

When Policy Goes Cluster: Refecting the European way(s)Rehfeld, Dieter

From Industrial Clusters to Global Knowledge HubsReve, Torger

Also eaturingArticles rom the IFC India City Competitiveness Report 2010

Papers and ideas presented at the13th CI Global Competitiveness Conerence 2010

January 2011, Volume 1, Issue 1



Arturo, CondoProessor o Competitiveness andStrategy INCAE, Costa Rica

Dharwadkar, RaviProessor o ManagementMartin J. Whitman School o Manage-ment, USA

Doyle, EleanorSenior Lecturer in EconomicsUniversity College Cork, Ireland

Dufll, DavidDeputy DeanRobert Kennedy College, Switzerland

Elazar, BerkovitchDeanArison School o Business, Israel

Hergnyan, Manuk

Proessor, Strategic ManagementYerevan State University, Armenia

Kapoor, AmitProessor o Strategy and IndustrialEconomicsManagement Development Institute,India

Kini, RameshProessor o Automation and Com-puter Science DepartmentKazakh British echnical University,Kazakhstan

Lall, AshishAssociate ProessorLee Kuan Yew School o Public Policy,Singapore

Mishra, Abhishek Proessor o Business Policy andStrategy Indian Institute o Management-

Ahmedabad, India

Prasad, AjitProessor o Strategy International Management Institute,India

Role, RobertProessor o International BusinessMoore School o Business, USA

Steinbock, DanResearch Director o InternationalResearch

India, China & America Institute,USA

Unger, MichaelAssociate proessor o managementand international businessSellinger School o Business andManagement

Balaji, G.Senior Director, Fidelity BusinessServices India

Batra, Anurag MD and Editor-in-Chie, Exchange4-Media Group

Doyle, Christopher

MD, Dynamic Results IndiaFormer Country Manager, India,Economist Intelligence Unit

Fowcs-Williams, IorCEO, Cluster Navigators

Jakhu, Ram S.Associate Proessor, Institute o Airand Space Law, McGill University

Kapoor, AmitHonorary Chairman, Institute orCompetitiveness

Proessor o Strategy and IndustrialEconomics, MDI

Ketels, ChristianPrincipal Associate, Institute or Strat-egy and Competitiveness, HarvardBusiness School

Muneer, M.Leading management consultant andauthor

Verma, Sanjay Executive Managing Director, South

Asia, Cushman & Wakeeld

Editorial Board Advisory Board, Institute for Competitiveness

enhancing prosperity



January 2011 Journal o Competitiveness 1

Journal of Competitiveness



January 2011Journal o Competitiveness2




Dear Readers,Competitiveness is a very important word, especially or countries like India that are transorming

rapidly and have the immense opportunity to prioritize productivity and inclusiveness in their growthstrategy.

But the truth is that it’s not a very well-known word. Outside o the lecture halls and academic journalsand perhaps select boardrooms, it’s an alien term or—not just the ‘lay’ person—but even entrepreneurs,policy makers and senior executives.

The Journal o Competitiveness brought out by the Institute or Competitiveness is an attempt to ad-dress various aspects o the subject, rom both academic and non-academic perspectives.

This issue gives you the best o the 13th TCI Global Competitiveness Conerence 2010, presentingve papers in their entirety. The papers, rom researchers and cluster experts across the world, ocus onthe scenario in South Asia and the priorities or India’s clusters—particularly in the readymade garmentand automobile industry. Additionally, the papers look at developing knowledge hubs, the ramework ointer-rm collaboration, and lessons or shaping policies or clusters. Excerpts rom the papers and ideaspresented at the 13th TCI Global Competitiveness Conerence 2010 are also included.

The journal also includes articles rom the India City Competitiveness Report 2010, which is beingreleased by the Institute or Competitiveness during this conerence. These articles look at various aspectso how cities in India could improve their competitiveness in areas like governance, transportation, brand-ing and attracting investment.

It is our sincere hope that the ideas presented in the Journal o Competitiveness reach a wide andrelevant audience o decision makers in corporations, as well as policy makers.

To submit your papers or double-blind review, email [email protected].

Editor’s notE







A CompArAtivE AnAlysis of thE CompEtitivEnEss of thErEAdymAdE GArmEnt industry ClustErs in dElhi, dhAkAAnd Colombo1

Choe, KyeongAe2

Nazem, Nurul Islam3

Roberts, Brian H.4

Samarappuli, Nihal5

Singh, Rajveer 6

The Asian Development Bank has recently com-pleted a project on City Cluster Economic Devel-opment (CCED) in South Asia, which examinedthe competitiveness o cities and industry clustersin Bangladesh, India and Sri Lanka. Part o theresearch involved an analysis o readymade gar-ment industry clusters in Delhi, Dhaka and Co-lombo. This paper describes new methodology

techniques or analyzing the competitiveness oclusters, using a modication o the Porter Dia-mond Model. The study measures 39 attributeso competitiveness aecting the perormance anddevelopment o three RMG industry clusters. The

1 The views expressed in this paper are those o the authors and do not refect a position or are binding on the ADB and AusAID that

supported the CCED project in South Asia

2 Urban Development Division, South Asia Department Asian Development Bank, Manila

3 Centre or Urban Studies, Dhaka, Bangladesh

4 University o Canberra, Australia

5 Board o Investment o Sri Lanka, Colombo6 Apex Clusters, Delhi, India

paper, which is a part o the CCED research proj-ect, has involved one o the most in-depth analysesconducted in the competitiveness industry clustersin South Asia. The analytical methodology provedto be useul or strategizing identied strategicopportunities or interventions by the governmentand cluster stakeholders to enhance the competi-tiveness o the readymade garment industries in

the three countries.

Keywords: Readymade garment industry, Competi-tiveness, Industry clusters, Bangladesh, India, SriLanka

ABSTRACT




introduCtionThe readymade garment (RMG) industry is one othe world’s largest industries. Global production ogarments in 2009 exceeded 17 million tons, withexports worth more than US$ 300 billion. The

RMG industry is labor-intensive and a very largegenerator o employment globally. Most o the la-bor orce is women, who work in large actoriesor micro enterprises or very low wages. Asiancountries dominate the production o textiles andRMGs. The industry is a major source o exportincome or countries like Bangladesh, China, India,Indonesia and Sri Lanka. It is a highly competitiveindustry, driven by keeping labor, transportation,materials and utility costs low. Industry margins atthe actory foor production level are low; so thatrms engaged in manuacturing and retail o cloth-ing and apparel products are constantly seekingways to keep costs down to maintain a competitivebusiness edge.

The high dependence countries like Bangladeshand Sri Lanka have on textile and RMG exportsmakes them especially vulnerable to changes in ex-change rates, raw material costs, technology im-provements and buyer markets. The recent globalnancial crisis has had a signicant impact on the

RMG industry, causing cut backs in production andthe loss o a large number o jobs in many coun-tries. There is growing concern by western con-sumers also about the environmental impacts andlabor conditions in ootwear, clothing and textileactories in developing countries. These actors areputting pressure on manuacturers o garments andtextiles to change the way RMG products are pro-duced to tailor or the changing demands o exportmarkets in the uture.

The growing pressure on rms and small busi-nesses in the RMG industry to enhance their Com-petitiveness to maintain market share is leadingmany countries to explore ways that governmentsand business can work more closely together to re-duce transaction costs. Business, in particular, islooking constantly or ways to reduce transactionscosts. Most do this by ocusing on achieving greatereciencies within internal production and distri-bution systems—especially along internal supply

chains. However, rms are less able to reduce ex-ternal transaction costs o commonly-shared a-cilities and services, such as water and transportacilities.

For more than two decades governments and

business have been ocused on ways to improvecompetitive advantage in cities and regions. Mucho Michael Porter’s work since the Competitive-ness o Nations (Porter, 1990) was published hasocused on ways to enhance the competitivenesso business in cities and regions (Porter, 2000).This has led to a growing interest by governmentsand business on ways to oster the development oindustry clusters, which are seen as a way to en-hance the Competitiveness o local economies andincrease production. Clusters developed by rivalrms and suppliers collocating and collaboratingon ways to reduce external transaction costs, in-novate and develop new business opportunities andmarkets that support the development o new busi-ness and investment in local economies and thegrowth o exports.

The initial ocus on the development o clusterssought to examine ways rms can pursue and cre-ate competitive advantage. However, over time,there has been a signicant shit rom the initial

ocus on competitive advantage (which ocused onimproving organizational eciencies) to collabora-tive advantage (Tapscott and Williams, 2006). Thisdevelopment o industry clusters as a way to en-hance the competitiveness o local economies leadto an interest and new ideas on how to use clus-tering as a means o reducing external transactioncosts to business and government. The new ocus onclusters involves rival rms and suppliers and gov-ernments cooperating and collaborating on ways

to reduce external rather than internal transactioncosts, innovate, and develop new business opportu-nities and markets.

The Asian Development Bank has recently com-pleted a project on City Cluster Economic Devel-opment (CCED) in South Asia (Roberts and Choe,(orthcoming 2010)). CCED involves a seven stepprocess that is used to evaluate the competitivenesso cities and industry clusters, and to develop plansor investment in projects and programs to develop




a plan to build-up strategic architecture (Hameland Prahalad, 1994, Roberts and Stimson, 1998),which is used to support the development and moreecient operation o local economies. Part o theCCED research project involved an analysis o the

RMG industry clusters in Delhi, Dhaka and Co-lombo. Strategic architecture includes endowedresources, human capital, business dynamics andenabling environments. The competitiveness othese things is important to the development o lo-cal economies and clusters.

An important element o strategic architectureis the creation o catalysts. These take dierentorms including networks, civic entrepreneurs, a-cilities and incentives. Catalysts are responsible ordriving business eort, innovation and investment

attraction in local economies and clusters. Onceprojects and programs needed to develop strategicarchitecture to support clusters have been identi-ed, there is need to establish a cluster develop-ment pathway and mechanisms to build criticalelements o strategic architecture. This includesthe nancial mechanisms and organizational gov-ernance arrangements to deliver on these.

The paper commences with a brie descriptiono the methodology used or cluster analysis de-

veloped by the CCED project, and provides someinsights on the policy implications this has had onthe development o clusters. A comparative analy-sis o 13 key Competitiveness indicators derivedrom a measure o the 39 competitiveness attri-butes in the RMG industry clusters in Colombo,Delhi and Dhaka is presented. The results showsignicant dierences between the competitive at-tributes or each cluster. An explanation is givenor some o these dierences. The ndings haveenabled the identication o strategic opportuni-

ties or interventions by government and clusterstakeholders to improve the competitiveness andperormance o the readymade garment industriesin each country. The research has involved oneo the most in-depth analyses ever undertaken tocompare the competitiveness o three RMG indus-try clusters in South Asia. Some o the insightsgained rom the comparison study are presentedin the conclusion to the paper.

mEthodoloGy usEd to EvAl-uAtE thE CompEtitivEnEssof rGm ClustErsMany techniques have been developed to study and

analyze the structure o clusters. Marshall (1929,1920) and Weber (1929) studied spatial agglom-eration o economic activities in national econo-mies during the early 20th century. One o the ear-liest studies on clusters was o the New York hotelindustry in the 1890s, which demonstrated thebenets and spin-os o competitive businessesco-locating (Baum and Haveman, 1997, Weber,1929). Co-location o hotels led to the local devel-opment o smaller service businesses, restaurants,bars and shops that serviced hotel customers. Thesynergy created by the mix o land-use activitiesenhanced competition between suppliers, and ex-panded the range and choice o accommodationservices.

Porter Model o Cluster Analysis

Michael Porter (1980) began to explore techniquesto map and analyze industrial structures and com-petitors, and using the inormation derived romhis research on strategies rms use to achieve

a competitive advantage. This research revealedour orces driving industrial competitiveness—potential entrants, buyers, suppliers and industrycompetitors. This resulted in the concept o inter-nal and external environmental analysis. In Por-ter’s model, environment dealt exclusively withthe economic and business environment given hisrealization that the study o rms and industrieswas insucient to explain competitive advantage.This led to urther research on the competitivenesso global industries (Porter 1985) and o nations

(Porter 1990).Porter’s Competitive Advantage o Nations

(1990) introduces his diamond model o competi-tiveness. The model has the ollowing our broaddrivers that shape the environment in which rmsand regions compete or business:n actor conditions, which include the skills, re-sources, technology, and inrastructure necessary tocreate competition in a given industry or cluster;




n demand conditions, which include the nature olocal and overseas demand or industry productsand services;n related and supporting industries, where thepresence or absence o suppliers and distributors

in support o industry sectors or clusters will deter-mine competitiveness;n rm strategy, structure, and rivalry, which re-late to conditions in a nation governing how com-panies are created, organized, and managed andthe nature o domestic rivalry.

Porter identied two other important actorsthat aect competitive advantage o rms: chanceand the role o government. Chance relates toevents or occurrences that have little to do witha country’s circumstances, but can be infuenced

by individuals, such as the decision by Bill gatesto locate Microsot’s in Seattle. Governments canhave signicant role in aiding competitive advan-tage, especially through public policies which areavorable to investment and prot perormance.Porter identies the importance o clustering com-petitive industries to create rivalry and stimulateinnovation.

Porter (1990) has had an important infuenceon strategic thinking or business and economic

development. While his early work was extensive-ly concerned with the competitiveness o nations,many o the case studies provide an insight into thecompetitiveness o regions. Other researchers haveused Porter’s model to analyze the competitiveadvantage o regions or manuacturing (O’malleyand Egeraa, 2000), trade services (Daly and Rob-erts, 1998), lm (Assmo, 2005), ood (Neven andDröge, 2001), and education (Curran, 2001). Stillother researchers have developed new qualitativeand quantitative methods or exploring and evalu-

ating the competitiveness o clusters in cities andregions (Enright et al, 1996, Brown, 1996). In-deed, the study o industry clusters has become adiscipline in itsel.

Cluster Structure and Supply Chain Mapping

Cluster mapping, seeks to translate statistical dataand inormation gained rom the above types oanalysis into a map the structure and supply chains

o a cluster. These cluster maps can be very com-plex. The intent o cluster mapping is to identiysignicant spatial concentrations o employmentand business activities, nancial and related trans-actions that occur between businesses and support

industries in the same locality. The process beginsby assessing the spatial concentration o industriesby SIC category input-output (I/O) analysis. A goodexample o this technique was used by Feser andBergman’s (2000) to study clusters in the NorthCarolina economy. Cluster mapping also uses loca-tion quotient (LQ) analysis to identiy the level oconcentration or intensity o business activities ina location. I/O tables help dene the transactionrelationships between dierent types o industriesin a cluster supply chain.

Certain types o rms make up the core o acluster. Core industries might include several oodprocessing actories which orm the core o a oodcluster or a steel mill or a metals cluster. LQs orthese industries are likely to be high. Other rms lo-cate close to and service the cluster’s core rms. InPorter’s (1990) model, these are the suppliers or re-lated supporting industries. Where LQs or non-coreindustries are relatively high, greater than 5, thiscould indicate a relatively mature and large cluster.

Cluster maps also provide useul spatial plan-ning inormation about the scale and the mag-nitude o agglomeration occurring in a cluster.Spatial plans can be designed to encourage theco-location o supporting industries and improvelogistics acilities needed to transport goods andservices and other products to and rom the cluster,or within a metropolitan region where a cluster ispoly-centered; that is, not conned to one area othe city. The mapping provides important inorma-tion or more detailed analysis o how the cluster

unctions, and the competitiveness o the dierentactors that support its operation and development.Once analysts have mapped a cluster, the next stepis to analyze the competitiveness o pertinent clus-ter elements.

Cluster Attribute Competitive Analysis

Porter’s (1990) Diamond Model is one o the mostwidely used techniques or cluster analysis. It in-




volves analysts working with industry ocus groupsto score the relative strengths o the attributeso competitiveness within a cluster. The DiamondModel has its weaknesses in that it does not providea spatial dimension to cluster analysis, but it has

provided a useul ramework or strategic thinkingabout local economic development and has beenwidely applied in many countries to analyze clus-ters. The model can be used to identiy and analyzethe interaction o actors that underlie local com-petitiveness and to ormulate strategy or regionaleconomic and industry cluster development basedon identied elements o competitive advantage.

The CCED methodology used to conduct thecluster analysis o the RMG industry in Colombo,Delhi and Dhaka, seeks to measure 39 attributes

o competitiveness that are grouped under the vedriving actors in the Porter model: actor condi-tions; demand conditions; related and supportingindustries; rm strategy, structure, and rivalry;and the role o government. The chance actor isremoved as it is not easy to measure as a actor ocompetitiveness. Table 1 shows 13 primary attri-butes o cluster competitiveness related to the vedriver actors measured as part o the research.These are an aggregation o the 39 indicators un-

dertaken or simplicity o presentation in the pa-per. The 39 attributes o competitiveness are as-sociated with six elements o strategic architectureexplained earlier that support the development oregional economies and clusters. Using an ordinalranking semi-qualitative scoring method based onnumeral scale o 0–5 (see Table 1) it is possibleto measure the relative competitiveness o each at-tribute. The scoring o attributes is done using amodied Delhi technique (Bordecki, 1984) wherean industry ocus group comprising 10-15 business

leaders and other knowledgeable experts (all to-gether known as a cluster working group) score thecurrent and estimated uture level o competitive-ness needed or each o the 39 attributes to make acluster competitive.

The scores recorded or each attribute by theindustry cluster ocus group assessors are summedand averaged. Following discussion by the groupmembers, scores may be adjusted until a nal

agreed score or the Competitiveness attribute isagreed upon. The scores or all the attributes areaveraged to arrive at an overall Competitivenessscore or the cluster. An average attribute competi-tiveness score greater than 3.75 suggests combined

attributes supporting the cluster are very strong,well-developed and internationally competitive; ascore around 3.00 suggests a relatively strong, na-tionally competitive cluster; while a score between2.5 indicates a small, emerging, sub-nationalstrength cluster. A score o 2 or less suggests thatthe cluster is relatively weak and only competingor business in local markets or is a newly emerg-ing cluster.

Cluster Competitiveness Defciency (Gap)

AnalysisThe second part o the competitiveness analysis isto assess competitiveness gaps o attributes; thatis, the dierence between the current and uturelevel o competitiveness attributes necessary todevelop the elements o strategic architecture sup-porting the development o the cluster competitive.Where there are signicant dierences or gaps, or

Competitiveness ElementsO Cluster

Indicators CompetitivenessScore 0-5

Factor Conditions

Labor 4 3.1Inrastructure 4 3.75Resources 3 2Social Environment 2 2.75

Demand Conditions

Markets 2 3.2

New Products 2 3.8Business Environment 4 2.3Firm Strategy StructureAnd

RivalryStructure 2 4Collaboration 5 4.1Technology Orientation 1 4

Related SupportingIndustries

Supply Chains 3 3.5Value Adding 2 3.8Government

Enabling Environment 5 3.9

Source: Roberts And Choe, (Forthcoming 2010)

Table 1: Attributes O Competitiveness Related ToFive Factors In The Porter Diamond Model




Table 2 Sample o Competitive Attributes o Clusters Using Porter’s Diamond Model

Demand Conditions Current StatusFuture Competitiveness

RequirementsGap Actions

Markets

Expanding Domestic And Local

Markets

2.75 3.75 - 1 Sucient Market Intelligence

Expanding Export Markets 2 4 - 2 Collaborative Marketing

New Products

Demand Expansion Capacity ForNew Products

2 4 - 2 New Technologies

Responsiveness To Change AndInnovativeness

2 3 - 1 Change Anagement

Source: Roberts And Choe, (Forthcoming 2010)

example a actor o 2, this suggests there may beneed or strong intervention by government and in-dustry stakeholders to lit the level o the selectedattributes o competitiveness to raise the overallcompetitiveness and economic perormance o the

cluster.Table 2 shows an example o how two primarycompetitive attributes o the cluster might be as-sessed. For example, a growing cluster seekingto expand into national or international marketsmight score 2.75 on overall current competitive-ness, but it would need to lit its overall index scoreto 3.00 to succeed nationally and 3.75 internation-ally. The cluster’s competitiveness index would needto improve by 0.25, or 9%, to become a successulnational cluster, and 1 or 36% to be internationally

competitive. Actions to strengthen weak competi-tiveness attributes would need to be identied. Pos-sible actions or enhancing the competitiveness omarketing and new products attributes are shownin the nal column o the table. The analysis mayalso include reerences to other sources o inorma-tion that may be relevant to the analysis.

The competitiveness deciency-gap analysisprovides a qualitative measure o the strengths andweaknesses o attributes o strategic architecture,

as well as potential threats and opportunities ac-ing the development o a cluster. The value o theanalysis is that it enables a cluster working groupresponsible or preparing a plan to develop a clus-

ter to identiy possible projects and programs thatshould be considered in a cluster development busi-ness plan and action plan.

AnAlysis of rmG industriEs

in Colombo, dElhi AnddhAkAUsing the above techniques, the CCED investiga-tion teams in each country began a detailed analy-sis o nine industry clusters in Colombo, Delhi andDhaka. The RMG industry was a common clusterinvestigated in each country. The ollowing pres-ents a summary o the competitiveness analysisconducted or the three RMG clusters.

Colombo RMG ClustersRMG and textiles is Sri Lanka’s largest export sectorgenerating US$3.2 billion in exports in 2009, equiv-alent to 46% o the country’s total export earnings.Most RMG are exported to Europe and the UnitedStates. The Colombo Metropolitan Region (CMR) isthe centre o the RMG industry in Sri Lanka and is aworld-class RMG manuacturing cluster. The clusterprovides direct employment or more than 300,000people (33% o manuacturing sector employment)

and indirect employment or a 1 million people. Di-rect oreign investment in the RMG industry at theend o 2007 exceeded US$ 700 million, o which theCMR accounted or US$ 280 million.




Current Conditions The RMG cluster in the CMR has a signicantpresence o manuacturing units engaged in coreindustries. The core o the cluster has more than500 apparel manuacturers. The cluster is backed

by a proactive industry association, the Joint Ap-parel Association Forum, made up o representa-tives rom key stakeholders in the industry. TheCMR also has a good network o transportation in-rastructure supported by export and logistics com-panies. The CMR RMG cluster has well establishedorward and horizontal supplier rms producingtextiles and garment accessories such as buttons,elastic, labels and packaging materials. However,the highest value-added components, includingequipment suppliers, designers and retailers, are

largely absent. Figure 1 presents the apparel clus-ter map constructed by the RMG industry ocusgroup or the CCED project.

Mapping the RMG supply chain was undertak-en and provide an important understanding o theclusters production systems, the value-adding ele-ments associated with this and the linkages to othersupporting industries and services. The textile andapparel industry’s supply chain shows that the in-dustry cluster has extensive backward linkages that

have a strong multiplier eect on employment andproduction. Figure 2 presents the apparel cluster

map constructed by the RMG industry ocus groupor the CCED project.

The emerging IT cluster in the CMR has im-proved the supply chain management and localnancial institutional capacity supporting the clus-

ter. Much o the equipment necessary or produc-ing garments is imported mostly rom Germanyand Italy. The demand or this equipment is notsucient to encourage manuacturing o machin-ery under license to replace the need or importso machinery. The cluster is supported by a smallnumber o exporting and logistics companies alongwith relatively good supporting inrastructure suchas transportation and utility rms. Universities andvocational schools with design and production cur-ricula support the cluster, but as oreign retailers

design most products, and more than 85% o out-put is exported, Sri Lanka has ew designers andretailers. As a result, the cluster has not been ableto gain access to international media, promotionand advertising, including ashion shows. This hasa signicant negative impact on the cluster’s abil-ity to move toward higher value-added activities.

Competitiveness Analysis of the Apparel Clus-

ter in Colombo

Figure 2 shows the analysis o the competitive-ness actors in the apparel industry cluster usingthe Porter Diamond Model and scaling systems

described above. These actorswere identied by a cluster ocusgroup or the ve driving ac-tors (See Figure 3). The clusteris positioned in the right market,including high-end products, butmany o the activities associatedwith the cluster are low value-

added activities such as cut-and-make garments. Thus, the clustereectively participates in only10% o the value chain process.The challenge is to shit into highvalue-added activities such asdesign, marketing and sales. Thisis dicult because o the globalstructure o the RMG industry

Industry

Fig 1 Apparel Industry Cluster Map, CMR

Source: (ADB, 2010) IT = inormation technology.




Highly competent

workforce

Good quality

telecommunication

services

Good Quality of raw

materials

Good workplace conditions

High cost of Electricity

Poor quality of

infrastructure logistics

Poor education/training

facilities

Poor quality of living

conditions for workforce

International repute as a

reliable supplier of quality

products

High level of business ethics

(‘Garments without Guilt’)

Emphasis on change

Small domestic market

Narrow Export base

Undue competition due to lack

of preferential market access

Slow responsiveness and

innovativeness to change

Lack of demand expansion

capacity for new products

Lack of readiness to face risks

Less emphasis/success on

product branding (brand

management)

350 + existing firms competing without

Government protection

Presence of reputed international firms

Presence of strong business associations

(JAAF)

Proactive at National / International level

Involvement in CSR activities

Low level of knowledge sharing

Low level of Technology application in firms

Usage of automated design / software

Emerging accessories cluster

Lack of business development

services

Low response time and low quality of

local support services

Firms inability to exploit value

adding potential

Gover nment – Policy &

Suppor t

Lack of long-term plans for apparel

industry development

Lack of government support for

industry development (eg. R&D)

Lack of enforcement of business

regulations (VAT refunds)

Relatively rigid labour regulations

Not enough marketing of the

industry

Fig 2 Apparel Industry Cluster Analyses

R&D = research and development.

Source: ADB, 2010

where these activities tend to be dominated by de-sign houses and global corporation.

Figure 3 shows the assessment o the ve driv-ers o competitiveness in the Colombo RMG clus-ter. Factor and demand conditions are relatively

strong, as is rm strategy and rivalry and relatedsupporting industries; however, government supportis weak. The overall competitiveness o the cluster is2.68, which is below 3.25 considered necessary toremain competitive in international markets. Whilethe RMG industry is growing, it appears to be los-ing market share to its competitors especially romChina and other SE Asian countries.

Delhi RMG Cluster

More than 600,000 people are employed in the

Delhi garment and textile industries. The New DelhiNational Capital Region (NCR) has one o the larg-est concentrations o RMG industry employmentin India. The NCR produces 40% o India’s ready-made garment exports and is the leading RMGcluster in the country. Most o the garment rms inthe NCR are located in the Okhla Industrial Area,in the southeast part o New Delhi. The industrialarea is responsible or 40% o RMG manuactured

goods in the NCR. More than 4,000 actories arelocated in this industrial area, which is one o thelargest in the country. The other major productioncenter in NCR is in Gurgaon, in the southwest.

Current Conditions The RMG cluster is very dependent on export or-ders or its development. The cluster accounts or16% o total apparel exports rom India. There areabout 50 large export houses situated in Okhla thatare responsible or most o the clusters exports.With the presence o international brands, exportsgo primarily to the European Union countries, Can-ada and the United States. Exports are mainly o-cused on clothing and discount chain markets, andnot high-priced garments. The key eatures o the

cluster include the ollowing: (i) rms ace dicul-ties in accessing supplier services, education andtraining acilities, and product improvement ser-vices and in building brands; (ii) stakeholders havelow levels o awareness o policy matters, govern-ment issues, and export procedures; and (iii) rmstend to use traditional, outdated practices and havelow social capital and a lack o expertise that couldhelp units solve production-related problems.




Competitiveness Analysis of

the Delhi RMG Cluster An assessment o the competi-tiveness o the cluster was under-taken by an industry ocus group

using the CCED techniques de-scribed earlier. The ollowingbriefy describes the analysis othe drivers o competitiveness us-ing the Porter model. The resultso the analysis are shown in g-ure 4. The strengths o the clus-ter include a trained workorce,good supporting clusters andpreerential access to the Euro-pean Union market. Weaknesses

include the low levels o brandingand marketing. Signicant entre-preneurial activity is apparent in this small but rap-idly growing sector, but moving the whole clusterin this direction will require higher levels o coor-dination between education institutions, rms andthe government. The conditions prevailing in thiscluster are poor and their competitiveness scoresrange rom 1.25 to 3.66. O the 39 competitivenessattributes, 72% have an average score o less than

2.5 (scores o 3 are necessary or a driver or at-tribute to be considered nationally competitive). Tocompete at the international level, the conditions inRMG cluster needs to be improved to at least 3.75to make the cluster more competitive.

The ollowing describes briefy the analysis o thedrivers o Competitiveness using the Porter model.

Factor ConditionsProduction resources or the RMG industry includeraw materials suppliers, machinery tools suppliers,

abric processors, and packing materials suppliers.Suppliers in the cluster are close to their marketsand the SMEs in the cluster have easy and cost-eective access to a wide range o services. Criti-cal to the growth and development o the clusterhas been the availability o cheap labor due to themigrant population rom Bihar and Uttar Pradesh.These workers gain entry to the trade by workingin actories with little ormal training. The NCR

has a number o established education and ICT in-stitutions that act as a catalyst or enriching thecluster’s human capital base. This has had a posi-tive spin-o to the region, but the impact on theRMG industry has been less than other sectors othe economy.

The cluster rms have access to railways, roadsand airports, including an international container

at the Okhla industrial area; however, the conditiono inrastructure and reliability o utility servicesis poor. Internal public transport acilities are notavailable, which makes it dicult or workers toget to and rom places o work. The condition owater supply, solid waste management and electric-ity supply is poor, but the latter has improved some-what, but urther improvement is needed to ensurean uninterrupted 24-hour power supply to rms inthe cluster. This has a disruptive impact on produc-tion costs and eciencies. In many cases, actoriesare duplicating public services in order to maintainproduction. This represents signicant sunk coststo businesses or the provision o services that areused when supply o water or electricity is disrupt-ed or not available.

Demand ConditionsThe RMG cluster is solely dependent on orders ormanuacturing. The cluster accounts or 16% o to-

Fig 3: Analysis o the Competitiveness o the RMG Cluster, Colombo

Source: ADB, 2010




Fig 4: Analysis o the Competitiveness o the RMG Cluster, Okhla,

Delhi

Source: NIUA, 2010

tal apparel exports rom India. There are about 50large export houses situated in Okhla, which are

responsible or most o the clusters exports. Withthe presence o international brands, exports goprimarily to the European Union countries, Canadaand the United States. Exports are mainly ocusedon clothing and discount chain markets, and nothigh-priced garments.

Related and Supporting IndustriesSupplementary industries and activities that sup-port the RMG cluster include: merchants; traders;

manuacturers o abric, thread, buttons, and t-tings; processing units; buying houses; exporters;abricators; machine embroiderers; and machin-ery suppliers. The supply chain structure is welldeveloped, with a very large number o micro en-terprises. The industry experiences a problem ohigh rejection rates, indicating a quality assuranceproblem within the supply chain network. The cur-rent situation in the RMG cluster is that ew o thecompetitiveness attributes are good or excellent.

Firm Strategy and RivalryMost garment manuacturing units in the clus-ter are small and amily-owned, with the ownerand other amily members taking on the roles omanager, purchaser, marketer, negotiator, qual-ity controller and nance controller. As a result,ew proessionally-qualied people are recruitedto those roles with the exception o a ew peoplewith diplomas holders in merchandising. However,

large rms and export housesdo recruit technically- and com-mercially-qualied employees orproduction, inventory control anddesign work. There is need or a

wide range o support programsinvolving education and training.The key eatures o the cluster

that emerged rom the evalua-tion included the ollowing: (i)rms ace diculties in access-ing supplier services, educationand training acilities, and prod-uct improvement services and in

building brands; (ii) stakeholders have low levelso awareness o policy matters, government issues

and export procedures; and (iii) rms tend to usetraditional, outdated practices and have low socialcapital and a lack o expertise that could help unitssolve production-related problems.

The cluster’s strength lies in production fexibil-ity, opportunities to expand the domestic marketand capacity to expand into new products. Low in-vestment, entry barrier requirements, easy and costeective access to a wide range o services, abun-dant availability o raw materials and easy avail-

ability o cheap labor need to be harnessed in theright manner to open up markets at all levels, andgive a air share o reward to all the stakeholders.

Dhaka RMG Industry

The RMG industry in Dhaka has been the lead-ing export sector industry in Bangladesh or morethan 15 years. In 2007 there were almost 4,500registered (and many unregistered) garment ac-tories in Bangladesh, employing about 2.4 millionpeople. More than 1.2 million people are employed

in the industry in Dhaka. More than 60% o ac-tories were located in Dhaka, 8% in Narayanganjand 17% in Gajipur (BGMEA 2008). The gar-ments industry in Bangladesh is mostly export-oriented. The geographical concentration o ac-tories in these districts gave them advantages interms o access to skilled labor, lower transpor-tation and other business transaction costs. Thissector has gained comparative advantage due to




the large pool o low cost labor and low transpor-tation costs due to co-location o industrial estab-lishments and some supporting government poli-cies. The government o Bangladesh has identiedthis sector as one o the ‘thrust sectors’ o growth

o the economy and has provided signicant sup-port to its development.

Current Conditions The development o the RMG industry in Bangla-desh is encouraged and supported by the govern-ment since the mid-1980s. The backward link-age supply industries grew rapidly in response toa demand or material and abricated products.Many o this lower order supply chain industriesbecame scattered around the region because sup-

pliers could not aord rents on properties close tothe main producers and the very low prot marginsin micro or amily-run enterprises. As a result, thesupply chain distribution structure became widelydispersed, and this resulted in ineciencies andhigh local transaction costs in the industry sector.

Many o the actory buildings in the city centreare multi-storey and not well designed to accom-modate expansion or ensure ecient production.Many o the supporting industries are located closeto the main production houses; however, the inten-

sity o development in these areas has added to thetrac congestion problem and over taxed many othe utility services. It is or this reason that manyactories that have undergone expansion have re-located to areas where there is more land or ex-pansion and vertical (same level) integration intoproduction systems. Despite these disadvantages,many have well-established amily businesses thathave expanded operations elsewhere in the region,and continue to maintain premises in the inner city,partly because o the availability o skilled work-

orce that continues to reside in this area.

Cluster Structure Map Figure 5 is a map showing the structure o the RMGindustry cluster in DCR. The ve core industries thatmake up the cluster are textiles, knitwear, woolen

Fig 5: Forward-Backward Linkage Map Showing the Structure o the Dhaka RMG Cluster

Source: (CUS, 2010)




textiles, jute textiles and handlooms. The backwardand orward linkages supporting the industry clus-ter are government on policy and strategy matters,as well as utility services, industry association andinterest groups, education establishments, labor

unions, national market and international R&D/ design linkages. Many components o the clustersare poorly developed, inecient or missing. As aresult, the cluster is not unctioning eciently andthis will continue to undermine its competitivenessin the ace o competition rom other Asian RMGcenters especially China.

There are many problems associated with theoperations o the RMG industry cluster. Most largerms have purchased backup utility systems (powergeneration, water supply, steam supply and ETP) to

overcome continuous disruptions to public agencyprovision o services. The large labor orce andmid-level technical/management sta are oten notsuciently skilled to take on greater responsibili-ties or are technologically literate. There is a heavyreliance upon oreign skilled man power to do tasksthat could easily be done by trained Bangladeshis,provided there were acilities to do so. While tele-communication have improved, transport services,congestion and logistics management are becom-

ing worse, thereby adding to the transaction costso business. Quality assurance on many projectsis weak, leading to high rejection rates on exportproducts.

Supply Chain Mapping Figure 6 shows the nature o the vertical supplychain or the textile and RMG Industry in DCR.There are over nine stages in the supply chain orsome products produced by rms in the cluster.

Each stage oers opportunity to add value toproducts, especially by horizontal integration odesign and marketing services. Mapping the RMGsupply chain was important in aiding industry un-derstanding o the production systems operatingwithin the cluster, the value-adding elements othe cluster and the linkages to supporting supplyindustries and services. The textile and apparelindustry’s supply chain has extensive backwardlinkages that have a strong multiplier eect onemployment and raw material supply.

Overall Competitiveness Figure 7 shows the overall completeness o the vedriving actors aecting the competitiveness o thecluster. Overall, the competitiveness o the cluster isweak and in need o improvement. Demand condi-tions are most avorable in the cluster, as most othe products are low-priced exports destined or dis-count or lower-priced stores in developed economies.The weakest position is government support. Much

o this has to do with the need or industry reormsand removal o many unnecessary restrictions on theoperations o the industry, and in the provision oessential inrastructure and services. Factor condi-

Fiber

NaturalFibers:1 .Cotton2.JuteFibers

ManMade

Fibers

SyntheticFibers

1 .Wool

2.Silk

Ginning

Spinning

Dyeing

Yarn

Knitting

Weaving

Cloth

Ready madeGarments

Export

LocalMarket

Lining,Button,Zipandotheraccessories

Fig 6: Nine Stages o Supply Chain or Textile and Readymade Garments Industry, Dhaka

Source: Authors (orthcoming 2010)




tions, rm strategy and rivalry and supporting in-dustries are not internationally competitive.

Factor ConditionsParticipants in the initial industry stakeholder meet-ing or the RMG industry cluster identied a numbero labor problems that were aecting the eective-ness and eciency o the sector. There is lack oadequate education and training acilities and insu-

cient skilled manpower to improve the competitive-ness and perormance o the RMG sector. The onlyspecialized education institution serving the sectoris the College o Textile Engineering and Technology.Some educational institutions oer degree coursesor ashion technology, merchandising, supply chainmanagement, etc., but the greatest need is or edu-cation and training acilities to upgrade technicalskills and quality enhancement programs. This is asignicant actor aecting the poor foor quality o

nished goods and high rejection rates in the RMGindustry in DCR.Utility services supporting the RMG industry

were identied as being poor and unreliable. TheDCR LGUs also need to improve the delivery andquality o utility services, especially in areas wherethe concentration o industrial units is high. Indus-try ocus group participants also identied problemswith proximity and access to raw materials. Thisindicates the need or government and industry to

work together to make a greater eort to improvethe quantity and quality o raw materials supply anddelivery systems to support the bottom-end o thesupply chain.

Conditions or employees working in RMG acto-ries are generally poor, due to low wages, high rentsand overcrowded housing, along with poor access tobasic health and social services. Work place saetyand health conditions in actories are poor and, in

some cases, dangerous. These actors impact onworkplace productivity and stoppages due to acci-dents. Many o these costs are considered externali-ties and not the responsibility o business; however,they have a signicant impact on the overall produc-tivity o the sector.

Demand ConditionsMarket conditions or the RMG industry are highlycompetitive or exporting rms, but the domestic

market is very weak. There is the realization bymany companies that international markets are go-ing to become more dicult to access and that ex-pansion into the domestic markets will be importanti the industry is to grow. However, the capacity othe domestic market to expand is constrained, asmost o the population has little excess disposableincome to spend on clothing. However, demand elas-ticity or cheap cloth is low, thus, making the sectorless vulnerable to international business risk associ-

Fig 7: Analysis o the Competitiveness Drivers o the RMG Cluster, Dhaka





ated with raw material prices. The market will haveto be developed or budget and a ew niche productlines o clothes and dress wear. The capacity o thesector to develop new products is relatively weak, asis the capacity to respond to change and innovate.

The ability to develop new products and change pro-duction line processes will be important i the clusteris to maintain and develop its export market shareand develop domestic market opportunities.

The dynamics o the business environment is rela-tively strong and quality and reliability o product ishigh, because rms have to compete in internationalmarkets. Entrepreneurs in this sector are generallyacross the need or post sales and product support,as this is important or quality assurance and prod-uct reputation in dealing with oreign buyers. The

RMG sector in Bangladesh seems capable o dealingwith international business risks, but still needs toimprove the level o business ethics and risk man-agement. Despite the current global recession, theRMG sector in Bangladesh shows a moderate level ogrowth, which suggests they are experienced enoughto deal with the problems this has created globallyor the industry. Demand elasticity or cheap cloth islow, thus, making the cluster less vulnerable to inter-national business risk associated with rapid fuctua-

tions in raw material prices. A signicant demandactor that will aect the industry in uture will bethe pressure place upon the industries to be morecarbon neutral. This will be a major challenge orthe RMG industry, as it will signicantly aect costs,and likely put a downward pressure on wages.

Firm Strategy and RivalryThe RMG industry is dominated by local rms. Thereare ew joint ventures or oreign rms engaged inthe in the Dhaka RGM cluster. Foreign rm inter-

ests tend to Taiwanese and Korean. There is need orthe industry to expand its engagement with oreignrms to speed up the rate o technology transer, toadopt more modern management practices and touse the purchasing power o oreign rms to gainaccess to new and expanded markets. There is needalso to improve the fexibility and integration oproduction systems. While many rms are entre-preneurial, there is rigidity to change and most do

not have the capital to invest in new technologiesor way to respond to rapidly changing market de-mands. Investment in the textile and clothing sectorcould generate more wealth or the country, but thegovernment will need to take steps to reorm oreign

investment policy and taris i it wants to attractoreign investment and modernize productions sys-tems in the sector.

The practice o knowledge sharing and collabora-tion within the rms is new or most businesses op-erating in the RMG industry sector in Bangladesh.So is the level o technological diusion along supplychains. The industry, as a whole, has not realizedthat collaboration is necessary to take advantage oeconomies o scale, and to overcome the treats rommore capital-intensive production systems that are

driving down production costs in other parts o Asia.Firms could share the experience o knowledge onmarket condition or new technology. Initiatives toencourage the practice o knowledge sharing will bean important step in enhancing a more collabora-tive approach to competition and production in thesector.

Finally, the uptake o modern technology in theRMG sector is not high. Bangladesh has an abun-dance o unskilled labor, and many rms are pre-

pared to orce down labor costs in order to remaincompetitive. Many rms don’t realize that orcingdown labor costs oten leads to lower productiv-ity. Higher salaries, up-skilling o workers and theintroduction o more modern technologies lead toincreased productivity and higher returns on capi-tal. The application o new technologies has beenrustrated by labor laws and practices that preventthe adoption o new technologies. The slow uptakein new technology is a signicant constraint on thedevelopment and competitiveness o the sector.

Related and Supporting IndustriesThe research ound many rms were not satisedwith the perormance o supporting services, espe-cially government services that are very slow andprone to rent seeking. Modern industries are in-creasingly dependent on high quality inormation,regulation, nancial and legal services to maintaincompetitiveness. These support services are weak or




are lacking in the cluster, and it is one o the mostsignicant constraints on its development.

The value adding potential in the sector is high,but opportunities to expand and develop supply chainindustries are undermined by poor knowledge, lack

o government policy and support or innovation,research and development. Most rms do not knowhow to value add, sticking to traditional productionsystems and practices that are rapidly becoming out-dated. Education programs to encourage innovationand risk management o product development arenecessary.

GovernmentFirms in the clothing & textile sector expect a loto support rom the government. This is partly be-

cause industrialization in Bangladesh began undersocialist policies that tended to protect and supportrms rom competition. There is no coherent policyor supporting the development o the RMG clusterat this time. Private sector investment in R&D isnegligible. The RMG industry is the ‘thrust sector’or the economy, and they do get some tax benetsupport rom the government; however, there is theneed or long-term business development policy, in-stitutional reorms, tax breaks or R&D and venturecapital ormation and low interest loans that arenecessary to enhance the perormance o the sector.The government must also take a leading role in thedevelopment o strategic public inrastructure, suchindustrial estate and inrastructure development,and land banking to ensure the industry can growand develop sustainably.

CompArison of thE Com-pEtitivEnEss of rmG Clus-tErs in dhAkA, ColomboAnd dElhiAn analysis o the attributes and drivers o com-petitiveness or the three RMG clusters was under-taken to identiy dierences between the industriesin the three countries. The results o the data col-lected are shown in table 3 and analysis o the re-sults summarized in the ollowing discussion.

Competitive Analysis o RMG Clusters

Table 3 shows the scores or 39 current and utureattributes o competitiveness or the RMG indus-try clusters in Colombo, Delhi and Dhaka. Figure8 shows the 39 competitive attributes or the ve

drivers aggregated to 13 key or primary attributes.There are signicant dierences between the com-petitiveness o attributes in the three clusters. Thecomparative analysis suggests that the Colombocluster overall is the most competitive o the threeclusters. This is because it is more specialized andtargets the higher value end o the global consum-er market. However, the cluster has a number oweaknesses that need support i it is to enhance itscompetitive position and develop. All three clus-ters are acing strong competition rom Southeast

Asian producers and will not be in a position tostrengthen their competitive position by relying onadvantage through economies o scale in the uture.To develop, it will have to identiy how to add valuealong the supply chains.

Several weak competitiveness attributes arecommon to all the clusters studied. Overall supportrom government is weak, compared to other Asiancountries. Value adding, development o markets,access to resources and access to skilled labor are

common actors undermining the competitivenesso the cluster. The condition in Colombo in thesocial and business environments, collaboration,technology orientation, inrastructure and supplychains is much stronger than in the other clusters.The Colombo cluster appears to have a much stron-ger willingness o rms to collaborate, althoughthis might be because the rms in the clusters ishaving to pitch themselves.

The market ocus o all the clusters is exports,primarily to generate oreign exchange earnings.While leading rms in the clusters are aware o thepotential o developing domestic markets, inecien-cies in the production chain process o the clustermean that prot margins and the potential to addvalue and expand demand in the domestic markethave not been attractive. Firms in Dhaka, especially,are reluctant to share inormation and knowledge toimprove cross-industry learning that could supportinnovation. Social capital in the cluster is strong be-




cause o the long history and associations betweenlocal producers and suppliers in areas with a strongphysical concentration o similar types o businesses.As a result, opportunities or the clusters to supportendogenous growth is being hampered.

Government support or cluster development inall three countries is generally weak, especially theunwillingness o governments to streamline businessapproval processes, increase resources or educa-tion and training, and incentives to upgrade tech-nologies that will enhance business perormanceand lead to more sustainable industry development.Governments are also reluctant to address the seri-ous environmental problems associated with manyo these clusters. Most clusters enjoy some strategicadvantage by being located close to sources o rawmaterials that are reliable in terms o supply ando reasonably good quality; however, there is still ahigh import component, especially or synthetic gar-ments, which weakens the competitiveness o the re-source attribute. Competition in global markets hasraised awareness o the need or improved qualityassurance, production sustainability and businessethics. Without such improvements, cluster rmsnd securing international contracts dicult.

Two sets o competitive attributes require themost support. The rst set is related to support-ing industries, especially strengthening the deliveryand quality o local business support services, iden-tiying opportunities to add value to supply chains,

and sharing this knowledge with other businessesin the cluster. Enhancing the competitiveness othese attributes associated with actor conditionswill require ormal and inormal disseminationo knowledge though the development o trainingacilities, networks and partnerships and industryassociations.

The second signicant set o attributes re-quiring support relates to government services.Government support or clusters is limited in allthree countries. Approval systems or businessdevelopment are bureaucratic, which deters in-vestors and new entrants into the cluster. Busi-ness and environmental regulations are complexand not enorced. Governments’ ailure to addressenvironmental problems aects public health andemployees’ productivity. Government support orR&D is limited, undermining clusters’ capacityto raise productivity and production along supplychain systems.

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

Labour

Infrastructure

Resources

SocialEnvironment

Markets

NewProductsBusiness

EnvironmentStructure

Collaboration

TechnologyOrientation

SupplyChains

ValueAdding

Government

ApparelClusterColombo

Okhla&NoidaReadymadeGarmentsDelhiRMGIndustryDhaka

FIRMSTRATEGYSTRUCTUREANDRIVALRY

RELATEDSUPPORTINGINDUSTRIES

DEMANDCONDITIONS

FACTORCONDITIONS

Fig 8: Comparison o the 13 Primary Competitive Attributes or the Three RMG Clusters





A p p a r e l C l u s t e r

C o l o m b o

O k h l a & N o i d a

R e a d y m a d e G a r m e n t s

D e l h i

R M G I n d u s t r y D h a k a

A p p a r e a l C l u s t e r

C o l o m b o



D e l h i


A p p a r e l C l u s t e r

C o l o m b o



D e l h i


FACTORCONDITIONS 3.02 2.13 2.10 4.71 4.51 3.82 1.69 2.38 1.72

Labour

Availabilityof SkilledLabour 3.20 2.11 2.10 4.80 4.22 4.00 1.60 2.11 1.90

ManagementSkills 3.20 2.50 1.80 5.00 4.72 3.90 1.80 2.22 2.10

EfficiencyandProductivityof Labour 3.00 2.22 2.40 4.80 4.44 3.80 1.80 2.22 1.40

EducationandTrainingfacilities 2.80 3.11 1.00 5.00 4.66 3.60 2.20 1.55 2.60

Infrastructure

Qualityof InfrastructureServices(logistics) 2.80 2.11 2.20 4.80 4.61 4.10 2.00 2.50 1.90

Qualityof InfrastructureServices(utilities) 3.00 2.34 1.80 4.40 4.61 3.80 1.40 2.27 2.00

Costof Services 3.20 1.50 2.20 4.80 4.50 3.40 1.60 3.00 1.20

Qualityof TelecommunicationServices 3.80 1.11 2.70 4.60 4.77 3.90 0.80 3.66 1.20

Resources

Proximity torawmaterial 2.20 2.14 2.20 4.20 4.42 4.10 2.00 2.28 1.90

Costof localrawmaterialsvisimports 2.40 1.93 2.40 5.00 4.57 3.70 2.60 2.64 1.30

Qualityof

raw

materials 3.40 2.50 3.10 4.60 4.62 4.30 1.20 2.12 1.20

SocialEnvironment

Qualityof livingenvironmentforworkforce 2.40 2.28 1.10 4.40 4.05 3.10 2.00 1.77 2.00

Workplaceconditions 3.80 1.83 2.30 4.80 4.38 4.00 1.00 2.55 1.70

DEMANDCONDITIONS 2.71 2.40 2.31 4.29 5.18 3.53 1.57 2.78 1.21

MarketsExpandingdomesticandlocalmarkets 1.40 1.37 1.00 3.20 4.31 3.00 1.80 2.94 2.00

Expandingexportmarkets 2.20 2.28 3.20 4.40 4.66 4.20 2.20 2.38 1.00

NewProductsdemandexpansioncapacityfornewproducts 2.00 1.56 2.00 3.80 4.33 3.60 1.80 2.77 1.60

Responsivenessandinnovativenesstochange 2.80 1.94 2.00 4.80 4.44 3.40 2.00 2.50 1.40

BusinessEnvironment

Quality&reliabilityof productorservice 3.60 2.38 2.80 4.80 4.88 3.10 1.20 2.50 0.30

Productsustainablyawarenessandsupport 3.20 2.37 2.70 4.40 4.37 3.60 1.20 2.00 0.90

Strongbusinessethics 3.80 2.55 2.50 4.60 4.77 3.80 0.80 2.22 1.30

Readinesstofacerisk 2.33 4.50 2.17

FIRMSTRATEGYSTRUCTUREANDRIVALRY 3.00 2.26 1.81 4.48 4.26 3.46 1.48 2.00 1.65

StructureExtentof foreignand jointventurefirmpresence 2.80 2.32 1.60 3.80 3.75 3.30 1.00 1.43 1.70

Flexibilityof productionsystems 2.60 1.29 1.90 4.40 4.12 3.50 1.80 2.83 1.60

Collaboration

Strongindustryfirmcollaboration 2.80 2.62 1.40 4.20 4.12 3.20 1.40 1.50 1.80

Sharedindustryknowledgecapitaldevelopment 2.40 2.65 1.60 5.00 4.31 3.40 2.60 1.66 1.80

Strongsocialcapitalandbusinessnetworks 3.60 2.45 2.30 5.00 4.33 3.80 1.40 1.88 1.50

Nationalorinternationalleadership 3.40 2.55 2.30 4.80 4.38 3.70 1.40 1.83 1.40

Civicentrepreneurshipandcommunity engagement 3.60 2.05 1.30 4.40 4 .27 3 .30 0.80 2 .22 2 .00


Highlevelof technology applicationinfirms 2.80 2.16 2.10 4.20 4.77 3.50 1.40 2.61 1.40

RELATEDSUPPORTINGINDUSTRIES 2.80 2.43 1.98 4.92 4.63 3.98 2.12 2.20 2.00

SupplyChainsStrengthof localbusinesssupportservices 2.80 2.41 1.80 4.80 4.66 3.90 2.00 2.25 2.10

Responsivenessof localsupportservices 2.80 2.20 1.80 5.00 4.62 4.00 2.20 2.42 2.20

Qualityof localsupportservices 3.20 2.61 1.90 5.00 4.75 4.00 1.80 2.14 2.10

ValueAdding

Potentialtoaddvaluetosupplychains 2.80 2.50 2.40 5.00 4.62 3.80 2.20 2.12 1.40

Businessawarenessof valueaddingpotential 2.40 2.44 2.00 4.80 4.50 4.20 2.40 2.06 2.20

GOVERNMENT 1.72 2.71 1.44 5.00 4.50 3.66 3.28 1.80 2.22

Governmentsupportforclusterdevelopment 2.20 2.82 0.90 5.00 4.50 3.80 2.80 1.68 2.90

Streamlinedbusinessapprovalsystems 1.40 2.37 1.50 5.00 4.37 3.50 3.60 2.00 2.00

Supportforsustainableindustrydevelopment 1.80 2.12 1.60 5.00 4.43 4.00 3.20 2.31 2.40

Enforcement of businessregulations 2.00 2.81 2.20 5.00 4.56 3.60 3.00 1.75 1.40

SupportforR&D 1.20 3.41 1.00 5.00 4.66 3.40 3.80 1.25 2.40

Average 2.68 2.21 1.92 4.52 4.36 3.59 1.84 2.15 1.67

CurrentCompetitiveP os ition Nec es sar yCompetitive GapAnalysis

Table 3 Competitiveness Attributes or RMG Industry Clusters in Colombo, Delhi and Dhaka




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1.00

1.50

2.00

2.50

3.00

3.50Labour

Infrastructure

Resources

SocialEnvironment

Markets

NewProductsBusiness

EnvironmentStructure

Collaboration


SupplyChains

ValueAdding

Government

ApparelClusterColombo

Okhla&NoidaReadymadeGarmentsDelhi

RMGIndustryDhaka

DEMANDCONDITIONS

FACTORCONDITIONS

FIRMSTRATEGYSTRUCTUREANDRIVALRY

RELATEDSUPPORTINGINDUSTRIES

Fig 9 Competitive Gap Analysis 13 Primary Competitive Attributes in the Three Clusters


Competitiveness Gap Analysis in the Three

Clusters

Figures 9 show the competitive gap or conditionsor the 13 primary attributes o competitivenessin the three clusters using aggregated data de-

rived rom table 3. There are signicant dier-ences between the competitiveness gaps or the13 primary attributes in each cluster. The gapanalysis measures the dierence between the per-ceived actual and necessary level o competitive-ness considered necessary to a level or nationalor international competitiveness. For the threeclusters, 18 attributes have an average competi-

tive deciency score gap o 2 or more considerednecessary to support the desired level o competi-tiveness. Nineteen attributes had scores between2 and 1.5 or the desired level o competitivenessimprovement. The deciency gap analysis is a use-ul means o identiying priorities or strengthen-ing the competitiveness attributes supporting thedevelopment o a cluster.

The gaps in the competitive attributes or ac-tor conditions occur mainly in the area o humanresource development. The clusters have an abun-dant supply o unskilled labor, but all were expe-riencing a high level o skills loss through migra-

tion. Currently, the clusters do not have enoughcapacity to meet the demand or skilled laborand management, which are essential to improveoverall productivity and perormance. Educationand training acilities to meet the ongoing and

expanding demand or proessional and technicalskills and competencies needed to support the nineclusters are in short supply. Foreign enterprisesin some clusters are recruiting internationalsta because o the shortage o local skills. Skillshortages are undermining rms’ ability to buildstrong, competitive management and productioncapabilities.

The lack o government support and inrastruc-ture is a problem or the development o all theindustry clusters studied, although the situation isnot as bad as or the prior issues, as a signicant

proportion o leading rms in the clusters are lo-cated in planned industrial areas and districts, andinrastructure and utility services are generallybetter in these locations than in inner city areas.The costs o services, especially water, electricityand telecommunications, are high because o sys-tem losses and thet that aect production costs,and hence the competitiveness, o many rms. Poortelecommunications services combined with low




levels o computer literacy oten mean that con-tracts are lost, many to clusters in Southeast Asiancountries where these services are much more reli-able. The proximity to materials used in productionis a competitive advantage or the clusters studied,

but poor logistics are causing delivery delays anddamage, aecting just-in-time and perishable oodbusinesses in particular.

Many larger rms in the RMG clusters realizethat appropriate residential accommodation is es-sential to attract and maintain skilled workers. Itis also important to ensure healthy and productiveworkorces. When planning and developing specialenterprise zones and industrial estates, govern-ments have ailed to provide or workers’ housingneeds.

Demand condition deciencies were the lacko capacity to expand export markets and developdomestic markets, rms’ slow responsiveness tochanges in market demand, and lack o innovationto respond to demand or new products. The clus-ters tend to suer rom inertia, which reduces theoverall dynamics o business in the cluster.

prioritiEs for fostErinG

ClustEr dEvElopmEnt inrmG industriEsThe goal o the CCED approach seeks to identiybankable projects that are attractive to investorsand prioritize investment areas to maximize theeconomic impact o development in cities in Asia.Government support is important or the develop-ment o clusters, because many projects involvingmajor inrastructure, acilities and capacity-build-ing programs entail high initial risks, which private

investors nd unacceptable. For many projects theeconomic returns to the community and businessare high, but the nancial returns to investors arenot acceptable. In such cases, CCED analysis canprovide better inormation o “where to investrst” to have clusters develop more eciently andto generate job opportunities or the local residents.Governments have a key role to play in sharing risksor guaranteeing cash fow during the initial stages

o a project intended to support the development oa cluster. This is common or public–private part-nership projects, where governments need to takea leading role in supporting cluster developmentprojects to overcome risks beore private sector

partner(s) become engaged.Many o the investments in the action plans orclusters developed or the three clusters are tar-geted at enhancing government support and indus-try services, as these were shown to be particularlyweak in all three countries. Most priority projectsselected are needed to reduce the external transac-tion costs associated with the operations o rmsinvolved in the cluster. Many projects involve pub-lic sector investment, as engaging businesses ininvestment projects helps to improve municipal in-

rastructure and services, the capacity o logisticssupport systems, R&D, education and training, andreorming business regulations. These are mattersbest undertaken by governments, but stakeholders’interests must be considered when addressing theseissues. In many cases, business can oer solutionsand be engaged in the delivery o public services,provided it is protable and expedient or them todo so.

Priority areas to support the development o

RMG clusters in the three countries include:n improving knowledge management and interna-tional marketing intelligencen applying ICT technologies to improve ecien-cies in the clustersn providing training acilities and programs toenhance the knowledge and skills o cluster work-orcesn improving the delivery o utilities, especiallywater supply, waste management, electricity, andtelecommunications servicesn enhancing support or R&D, particularly to os-ter innovation and the development o new productsand servicesn streamlining approval and permitting processesby providing one-stop shop acilities and e-gover-nance systemsn developing business networks and associationsto oster the dissemination o knowledge and or-mal and inormal (tacit) learning




n Developing special initiatives such as an ap-parel city in Colombo, regional garment centersin Dhaka, and national garment institutes in Delhiand Dhaka

ConClusionThe CCED analysis o the RMG industries in Co-lombo, Delhi and Dhaka has added a new dimen-sion to analyzing the competitiveness o clusters inAsian cities. There is growing interest in Bangla-desh, India and Sri Lanka on the role clusters couldplay in supporting local economic development andattracting oreign investment. The developmentand testing o CCED analytical methodology in thethree countries has involved a signicant learning

process, along with experimentation not commonlyassociated with this type o research undertaken bydevelopment banks. The process has provided in-sights into improved project design o developmentbank projects, but it took much longer than antici-pated to achieve results, the data collection provedproblematic, and the acilitating o industry ocusgroups to share inormation and collaborating inthe qualitative research involved a great deal otrust building and education beore good coopera-tion between industry stakeholders and the govern-

ment was achieved.CCED analytical methodology uses many

techniques well -established in regional econom-ics research and practices to analyze and pre-pare strategies or local economic development.The CCED is one o the rst kinds o research incompetitiveness and cluster areas where it com-bines spatial agglomeration or practical urbandevelopment perspectives. The process has dem-onstrated that when combined with limited quali-

tative data, qualitative techniques can generateinormation and insights that provide valuableunderstanding insights into what shapes the de-velopment o local economies and identies thecompetitive strengths as well as weaknesses inexisting strategic architecture.

The RMG industry is a highly competitive in-dustry. In Asia it is a labor-intensive industry,which employs millions o mainly low-skilled andlow-paid emale workers. In most cases the indus-

tries are only engaged in the primary productionstage o manuacturing and export, which providesew opportunities or RMG clusters to signicantlyclimb up the supply chain and add value to localproduction systems. With the expansion o domes-

tic markets, there is signicant potential o theRMG industry clusters to expand both the horizon-tal and vertical supply chains in the industry. Todo this they must create much more competitivestrategic architecture.

Factor conditions o competitiveness in all threeRMG clusters are relatively weak, especially govern-ment support. The enabling environments to supportcluster development in all three cities need to be sub-stantially improved. The unnecessary high levels obureaucracy in governance and regulations systems,

rent seeking and the lack o government support andknow-how to develop the RMG industries in Colom-bo, Delhi and Dhaka is holding back the developmento the industry and undermining its competitiveness.Greater support or clustering by local and nationalgovernment could help to overcome some the prob-lems in inrastructure and skills shortages througha range o partnerships with the private sectors andthe ostering o strong industry cluster organiza-tions. By ostering a more collaborative approach

to cluster development to overcome some o theseproblems, it should be possible to reduce transac-tions cost to business and make these cities moreattractive places or investors in the uture.

The investigation into the RMG clusters has ledto important discoveries that could help policy de-cision making by governments, businesses, and in-vestors to acilitate opportunities to support the de-velopment o clusters. CCED analysis has enhancedwell-established research techniques by enabling amore detailed exploration into the competitiveness

o cities and industry clusters than has been pos-sible beore. Finally, the CCED study o the RMGclusters has led to a better understanding o thenature and economic importance o the three RMGclusters in the three cities in which the studies wereconducted, and how industry and government canwork collaboratively to develop pathways that canlead to the achievement o more sustainable devel-opment outcomes or these clusters in the uture.




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2 Assmo, P. (2005) Creative Clusters - Ideas And

Realities For Cluster Growth: The Example OFilm In Vast In The Region O Vastra, Gota-land, Sweden. In Karlsson, C., Johansson, B.& Stough, R. G. (Eds.) Industrial Clusters And

Inter-Firm Networks. Cheltenham, Edward El-gar Publishing Ltd.

3 Baum, J. A. C. & Haveman, H. A. (1997) LoveThy Neighbor? Dierentiation And Agglomera-tion In The Manhattan Hotel IndUstry: 1898-1990. Administrative Science Quarterly, 42.

4 Bordecki, M. J. (1984) A Delphi Approach,

New York, N.Y. University.5 Brown, R. F. (1996) Industry Clusters: A New

Approach To Economic Development In Re-

gional Australia, Canberra, Agps.6 Curran, P. J. (2001) Competition In Uk Higher

Education: Applying Porter’s Diamond ModelTo Geography Departments. Studies In Higher

Education, 26, 223 - 251.7 Cus (2010) City Cluster Economic Develop-

ment: Bangladesh Case Study, Manila, Asian

Development Bank.8 Daly, M. T. & Roberts, B. H. (1998) Applica-tion O Porter’s Diamond Model To EvaluateThe Competitiveness O Tradeable Services InA Regional Economy: A Case Study O TropicalNorth Queensland, Australia. Western Regional

Science Association: Thirty-Seventh Annual

Meeting. Monterey, Caliornia.9 Enright, M., Scott, E. & West, J. (1996) Hong

Kong’s Competitiveness, Hong Kong, OxordUniversity Press.

10 Feser, E. J. & Bergman, E. M. (2000) NationalIndustry Cluster Templates: A Framework ForApplied RegionaL Clusters. Regional Studies,34, 1-19.

11 Hamel, G. & Prahalad, C. (1994) Competing

For The Future: Breakthrough Strategies For

Seizing Control Of Your Industry And Creating

The Markets Of Tomorrow, New York, Har-vard University Press.

12 Marshall, A. (1920) Industry And Trade, Lon-don, Mcmillian.

13 Neven, D. & Dröge, C. L. M. (2001) A Diamond

For The Poor? Assessing Porter’s DiamondModel For The Analysis O Agro-Food ClustersIn The Developing Countries. Michigan StateUniversity.

14 Niua (2010) City Cluster Economic Develop-

ment: Innovative Interventions South Asia NewDelhi, Institute For Urban Aairs.

15 O’malley, E. & Egeraa, C. V. (2000) IndustryClusters And Irish Indigenous Manuacturing:Limits O The Porter View. The Economic And

Social Review, 31, 55-79.

16 Porter, M. E. (1980) Competitive Strategy:

Techniques For Analyzing Industries And Com-

petitors, New York, Free Press.17 Porter, M. E. (1985) Competitive Advantage:

Creating And Sustaining Superior Performance, New York, Free Press.

18 Porter, M. E. (1990) The Competitive Advan-

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And Economic Development: Local Clusters

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ment In South Asia, Manila, Asain DevelopmentBank.

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Industries. Chicago, Il, University O ChicagoPress.




dEtErminAnts of CompEtitivEnEss: A study of thE indiAnAuto-ComponEnt industry

Joshi, Deepikaa1

Rathore, Ajay Pal Singh2

Sharma, Dipti3

In the present era o global competition, competi-tiveness is the key word to success. Industries arecompeting in their respective domains to establishthe global benchmarking standards. Here deter-mining the critical success actors is an importanttask. In the context o the Indian auto-componentindustry, this paper is an attempt to identiy, in-tegrate and analyze the actors responsible or

1 Department o Management Studies, Malaviya National Institute o Technology Jaipur, India

2 Department o Mechanical Engineering, Malaviya National Institute o Technology Jaipur, India

3 Department o Humanities & Social Science, Malaviya National Institute o Technology Jaipur, India

its competitiveness. Further, this evaluation willassist in recognizing the critical actors o suc-cess to win a place in the global auto-componentindustry.

Keywords: Competitiveness, Determinants o com-petitiveness, Automotive industry, Auto-componentindustry

ABSTRACT




introduCtionUnparalleled intensication o the worldwidemarket has created a erce competition amongstvarious sectors and nations across the globe. Pres-ently, when most o the nations are acing turbulent

growth rates, the ocus is shited to those sectorso economy that promise accelerated growth. TheIndian automotive industry is one such sector hav-ing tremendous potential or uture growth. Today,domestic rms have already realized the marketopportunities and are trying hard to excel withintheir domains. In this scenario, competitiveness isthe universally-accepted ormula or growth [29].However, leaprogging o the Indian automotive in-dustry has made it a part o the global supply chainactivity. To become competitive, rms or industriesneed to nd and act upon critical actors to success.This not only helps in mitigating local competition,but also builds up national competitiveness.

The Indian auto-component sector that initiallystarted with the development o small and mediumscale enterprises is now gaining recognition as a‘global quality player’. The global attractivenessand success o this sector depends on some signi-cant actors. These actors directly or indirectly a-ect the perormance o a rm or an industry. Thus,

it merits extraordinary attention o practitionersand researchers. The present study is primarily o-cused on analyzing the competitiveness o the In-dian automotive industry. Secondly, it identies thecritical success actors or protable developmento the Indian auto-component sector.

rEviEW of litErAturEIn the present era o globalization and industrial-ization, competitiveness is achieving a positive ap-

preciation. Over a period o time, it has becomethe name o game i.e. “be competitive and win”.This has made competitiveness synonymous withsuccess. Various researchers have expressed it indierent ways; or K. Momaya [22] it is a useulindicator o the long-term socio-economic healtho a country. For scholars with a resource-basedviewpoint, it is distinctive competence availablein any given organization [5] [6] [11] [14] [16]

[19] [31] [33]; or scholars having a knowledge-based viewpoint, competence is creation o orga-nizational knowledge that is proprietary to rm(Nonaka and Spender, 1992); and or scholars witha competence-based viewpoint, it is resources and

capabilities that are dicult to imitate [17]. Thus,productivity comes rom capability, which in turncomes rom resources and knowledge.

The wide-ranging concept o competitiveness isbuilt across three dierent levels o competitive-ness i.e. rm, industry and nation. At the nationallevel, competitiveness is synonymous to productiv-ity o the nation [15] [21] [27] thus augmentingits trade and export perormance [30] to achievehigh and rising standard o living [20] [34]. Essen-tially, it is not the nations that directly compete in

the global marketplace, competition actually arisesat the industry and rm level [22] [28]. Moreprecisely, rms o an industry struggle to buildup industrial competitiveness that ultimately aug-ments national competitiveness. For this reason,national competitiveness is oten considered as themacro actor while the individual competitivenesso various industries and rms is counted as micro-actors.

The study o various models and rameworks

related with ascertaining competitiveness has un-veiled the important act that competitiveness is acollection o discrete variables that are oten iden-tied as determinants o competitiveness or indica-tors o competitiveness. The diamond approach tointernational competitiveness [27] has identiedour actors or national competitiveness: (a) ac-tor conditions, (b) demand conditions, (c) relatedand supporting industries, and (d) rms’ strategy,structure and rivalry. Caves [9] has identied veactors responsible or inter-industry dierences:

(a) competitive conditions, (b) organizational ac-tors, (c) structural heterogeneity, (d) dynamic dis-turbances and (e) regulation. K. Momaya and A.Ambastha [4] [22] have discussed dierent aspectso industry level competitiveness: (a) assets, (b)processes and (c) perormance. Thus, competitive-ness is a multidimensional concept [24]. However,the determinants o competitiveness at all threedierent levels are not exclusively separated. This




can be attributed to the mutual impact they have oneach other. The actors aecting national competi-tiveness are also considered as determinants o theperormance o industries and rms. On the otherhand, the ability o rms and industries is oten

translated into the position that a nation’s economyholds on a global platorm.Assessing national competitiveness is a complex

task. Nevertheless, it can always be measured withreerence to the competitiveness o the nation’s in-dustries [7] [8] [22]. The dimensions o any givensector’s/nation’s perormance oten depend upona large number o variables and sub-variables at-tached to it. Even the most authenticated reportslike Global Competitiveness Report and WorldCompetitiveness Yearbook have ranked the coun-

tries on the basis o various pillars and indicators.These pillars and indicators are basically variablesor units used or measuring competitiveness. How-ever, the actors (variables) governing competitive-ness at the industry level are highly sector-specic,and vary rom sector to sector.

Various public policies adopted by the govern-ment are aimed at restructuring the present posi-tion o industry sectors [22]. This initiates openborder practices and creates a single platorm or

exchange o goods and services. Thus, competitive-ness or the trade sector depends on open trade orno protection or subsidies [8] and internationaltrade agreements [7] [22]. This increases exportsrom a country thereby allowing increased infowo oreign currency. Government-protected poli-cies speciy the level o FDI and FII received bythe industry as a whole [7]. This however requiresa developed inrastructure in the orm o industrialclusters [7] [28]. Thereby it brings in subsidies,incentives and SEZs by government and industry-

specic agencies. Moreover, the never-ending R&Dactivities are central to technological innovations[7] [13] [22], though it can also be achieved byin-house automation, design knowledge and skills[10] [23]. For heavy-technology-oriented business-es like manuacturing, investment in R&D activitiesis the major source o positive cash fows. Theseactivities aects new product development, short-ens lead time as well as cycle time [32] and nally

results in the realization o prots, revenue growth,and market capitalization. It is also supported bythe concept o quality, which is highly subjectivein nature. But quality standards and accreditationsare universal perormance indicators. Following

these standards usually indicates the rm-specicdegree o product quality [7] [10] [22] [23]. Forsectors that are involved in mass production likethe auto-component industry, labor productivity isthe key indicator o eciency [7]. Simultaneouslyit requires eectiveness too. Failure to attain laborproductivity renders production a costly aair. Thismay increase the overall cost o doing business. Fi-nally it can increase the price o products or ser-vices [10] [22]. For labor-intensive industries, theworld’s best economies are competing on unit labor

cost [3] [12].According to the supply chain research commu-

nity, any given rm is a set o management pro-cesses. These processes are interlinked with eachother. Any uncertainty at the rst stage o orecast-ing the demand and supply situation can distort thesubsequent processes [10]. Moreover, satisyingthe customer is the ultimate aim o any businessactivity. In business-to-business (B2B) markets itoten depends upon satisying the other’s business

needs. Proper scheduling techniques and reducingthe requency o machine breakdowns leads to per-ect delivery [10]. Here inormation always playsa very important role [10]. I shared properly andwholly among suppliers, buyers and the ultimateconsumers, it can be a good source o competitive-ness or the industry as a whole.

rEsEArCh mEthodoloGy/ ApproAChThe review o literature presented in the previoussection is aimed at highlighting the importanceo competitiveness. Factors that decide the com-petitiveness o the manuacturing sector are alsoput orth. Further, in the next section a secondarymethod o data collection is used or collecting therequired inormation. Statistical data rom variousorganizations o national repute like CRISIL, So-ciety o Indian Automobile Manuacturers (SIAM),










has increased more than two times in the past veyears. This has supported the increase in produc-tion and exports o components in India. Both,production and exports have shown a growth onearly 6% in 2009, whereas imports have showna growth o 31%. This is an indicator o the hugerequirement o auto-components or India-basedmanuacturers. It is a matter o concern or thelocally-producing rms as they are losing domes-tic opportunities to oreign-based manuacturersand hence increasing the outfow o Indian cur-rency to the global market.

As o today, the growth in the auto-componentsector has reached such a position that variousmultinational companies like Mercedes, GeneralMotors, Ford, Daewoo, Honda and Volkswagenhave already set up their international purchasing

oces (IPOs) in India to source or their global op-erations. This has urther complemented the growthrate o the Indian auto-component industry. Today,the Indian auto-component industry has become apart o the global supply chain activity and hencerequires special attention o practitioners and re-searchers or its urther development.

drivErs of CompEtitivE-nEssThe accelerated growth o the Indian automotivesector is determined by some critical success ac-tors. These actors are the entities and variablesinvolved throughout the business process, i.e. right

100,000.0

200,000.0

300,000.0

400,000.0

500,000.0

600,000.0

700,000.0

800,000.0

2002-03 2003-04 2004-05 2005-06 2006-07 2007-08

Years

R s . M i l l i o n

Total organised sector SSI sector

Fig 4: Individual Contribution o Small Scale In-dustries (SSIs) & Organized Sector

Data Source: CRISIL Research, ACMA (Reer Table 5)

Table 5: Individual Contribution O Small Scale Industries (Ssis) And Organized Sector

(Rs. Million)

Type 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08

Total organizedsector 196,425.9 235,928.0 298,105.5 409,054.8 522,637.5 558,142.2

SSI sector 58,927.8 70,472.0 89,044.5 122,185.2 156,112.5 166,717.8

Total 255,353.6 306,400.0 387,150.0 531,240.0 678,750.0 724,860.0

Data Source: CRISIL Research, Automotive Component Manuacturers Association (ACMA)

rom procurement o raw materials to delivery onished goods. The degree o eectiveness and e-ciency o these actors truly determines the per-ormance o the Indian automotive industry as awhole. For the ease o study, they are classied asdirect and indirect actors.

The elements o competitiveness actually orm aparadigm. The directly-involved entities are a mem-ber o the auto-component supply chain activity andthe indirectly-involved entities carry out supportiveunctions. Moreover, the directly-involved variablesare the rms’ strategies on which an organization




has direct control to achieve competence. Indirect-ly-involved variables are mainly industry-specicactors. A graphical depiction o the interrelation-ship among these actors is presented in gure 5.The combined eect o these actors actually deter-mines competitiveness. For the auto-component in-dustry, which has mass production and supply, costcompetitiveness and perect delivery are the majorcriteria or success, which in turn comes rom theseentities and variables. Here, 1 and 2 represent thedirectly-involved variables.

Customers drive competition in the industry bycreating demand. Stipulated demand or robust andreliable auto parts by automobile manuacturershas orced OEMs to compete considering technol-ogy as a success actor. Today, Indian manuactur-ers are ully capable enough o producing hi-tech

components like electronic uel injectors and metalintensive components used in orging, stamping andcasting, etc. For example, Bharat Forge Limitedrom India has a leading position in steel and alu-minum orging across the world. However, with thegrowing trend o alliances and ventures, the statuso technology as a actor is now that o an orderqualier instead o an order winner. In this context,success stories o Maruti Udyod Limited and Suzu-

ki o Japan, and that o Steering Systems and SonaKoyo o Japan are o utmost signicance. Boththese ventures were made or technology acquisi-tion or continuous production improvement. To-day, large numbers o companies are building theirproduct consortia and competitiveness because oeasy mode to technology transer. Though Indiais still on its learning curve as ar as technologyand R&D are concerned, it has helped developingin-house R&D and design and development (D&D)acilities. Scorpio rom Mahindra and Mahindra,Indica and Indigo rom Tata Motors and Pulsarrom Bajaj Auto’s are all indigenously-designedvehicles. Today, Indian rms are designing aterreceiving orders rom manuacturers. Firms likeSundram Fasteners have well equipped CAD/CAMlabs or testing and designing o auto components.

The developed Indian sotware industry is a greatsource o help to the industry’s R&D activities. Asthe cost o component designing in India is one-twelth o that in the US and UK, the manuactur-ers like Volkswagen, Mercedes, Nissan and manymore are starting their component production inIndia. Undoubtedly, intensication o the globalautomotive industry has created competitive rival-ry, but simultaneously it has orced rms to design

OEMsTier 1

Tier 2

Automobile

AssemblersCustomer

Cost

Delivery1

2

1

2

1

2

Competitive Rivalry

Demand pattern

Financial Institutions

Third Party Logistics

Research Firms

Agencies

Fig 5: Entities and Variables Involved in Auto-component Business Activity

Directly-involved entities Tier 1& Tier 2 suppliers, OEMs, auto assemblers,ultimate customers

Indirectly-involved entities Banks and nancial institutions, third-party logistics, research

rms, government and non-government agenciesDirectly-involved variables Technology, human skills, resources, fexibility, qualityIndirectly-involved variables Competitive rivalry, demand pattern




globally competitive business strategies to leveragemarket opportunities.

Government initiatives and policies alwaysact as acilitators or industrial development. InIndia, The Department o Heavy Industry is the

main agency or promoting the growth and de-velopment o the automotive sector. In order topush advancement in the auto sector, the depart-ment has undertaken several measures, like theAuto Policy in 2002, time-bound implementationo the Auto Mission Plan 2006-16, setting up theNational Manuacturing Competitiveness Counciland Investment Commission or enhancing themanuacturing competitiveness, and the NationalAutomotive Testing and R&D Inrastructure Proj-ect (NATRiP) at a total cost o $388.5 between

central and state governments to aid world-classautomotive saety, emission and perormancestandards. Moreover, the government has allowed100% oreign equity investment and reduced theduties and taxes on raw material purchase to5-7.5% rom the earlier 10%. This has also givenan opportunity to multinationals to start theirproduction units in India. Apart rom setting upSEZs, the government is ostering cluster orma-tion at the regional level, whereby manuactur-

ers located in proximity to OEMs synergize eachothers prot. Major clusters o in the country arepresent in Delhi, Gurgaon, Faridabad, Manesar(North), Mumbai, Pune, Nashik, Aurangabad(West), Chennai, Bangalore, Hosur (South) In-dore (Central India) and Jamshedpur (East). Thisallows easy sharing o commonalities and comple-mentariness. The ormation o nodal associationslike ACMA and SIAM has structured the industryor its long-term protable development. Current-ly, ACMA represents 479 component manuactur-

ers and SIAM represents 39 leading vehicle andvehicular manuacturers in India. These agenciesact as a catalyst and interact with internationalexperts or the development o the sector.

The auto-component sector is a mass produc-tion industry. The advantageous position o thecountry with regards to low cost skilled workorcewith multilingual capability is promoting exportso labor-intensive work. For example, Indian rms

are incurring just $6 per day as compared to 33.6in Brazil. This accounts or 9.3% o the total costo component production in India. Even ater com-paratively lower productivity, a components manu-acturer enjoys a cost advantage o 2-30%. More-

over, the decreasing cost o raw materials is one othe key actors responsible or development o thecomponent and ancillary industry. Raw material ac-counts or 57% o the total cost o auto-componentproduction compared to 61% in 2007 (IMaCS).The huge popularity o cost advantage has madeIndia a global auto-component manuacturing hub.German automaker Volkswagen is initiating com-ponent sourcing rom India or its Russian and Eu-ropean plants. Carlos Ghosn o Nissan said that “II have to ght the battle on low cost, I am going to

do it (with a base) in India.” Thus, cost competenceis ampliying the potential gains o the Indian auto-component manuacturing industry.

Driven by the need o export markets, qualityawareness has increased since the last decade. In-dian rms have improved product quality by imbib-ing world-class quality standards like TS 16949,GS 9000, ISO 9000 and OHSAS 18001. The de-ects have been reduced to 100 parts per million(ppm) in 2009 rom 500 ppm in 2007. Eleven In-

dian auto-component manuacturers have won theprestigious Deming Award and teen have wonthe Total Productive Maintenance (TPM) Awardsin 2009. To attain high operational eciency, In-dian suppliers are embracing modern shop foorpractices like Six-Sigma, Kaizen, TQM, TPM,lean manuacturing, etc. Moreover, the adoptiono world-class manuacturing practices, educatingmanagers and shop foor workers has made Indiancomponent manuacturing a quality-oriented indus-try. It has also acilitated the fexible production

system thereby making the perect delivery systemor rms.

The growth o rubber, aluminum and steel produc-tion as well as development o the power sector andbusiness inrastructure acilities within the countryhas also strengthened the ancillary and componentproduction. However, the linkage between universi-ties and manuacturers is still missing. These link-ages, i developed properly with IITs, NITs and IIMs




can help in technical as well as business planning ac-tivities or the enhancement o the auto-componentsector as a whole.

Various socio-economic actors that contributetowards high growth in the Indian automobile sec-

tor are rising per capita income, alling age o rst-car users, shorter replacement cycles, rising duelincome amilies, new technology (which is loweringcost o ownership), low car penetration in the coun-try and easily-available nancing options. This issurging the demand o components and ancillariestoo. Various initiatives at the national and industrylevel have made this sector a rising sector in theIndian economy.

Besides, the strategic handling o competitivepressure has also helped national and multinational

rms to overcome local as well as global challeng-es. Building industry competitiveness ultimatelypaves the way towards development o nation asa whole.

ConClusionIndian is one among the astest-growing economieso the world. Herein, the country’s developing auto-component industry plays a vital role. Nevertheless,there are some actors critical to the success o de-

veloping the Indian auto-component industry. De-tailed review o literature is done to identiy theseactors and named them determinants o competi-tiveness. Findings revealed that technology, R&Dcapabilities, D&D capabilities, developing statuso allied industries, low cost advantage associatedwith the country, ollowing global quality normsand developing the socio-economic status o thecountry’s population are some o the critical suc-cess actors to the Indian auto-component indus-

try. However, government policies, nodal agencies,escalating demand condition, intensiying competi-tive rivalry and large number o choices availableto the ultimate customer derive the industry com-petition as a whole. The study also discovered oneact that cost and delivery are the core competenceo the auto component and ancillary industry. Anyimprovement in the eectiveness o the aoresaidactors will have a strong multiplier eect on theauto-parts sector. Moreover, the well-implemented

national strategies will advocate the growth o in-dividual auto-component manuacturers and nallythe country as a whole.

The current research paper is entirely limitedto secondary data obtained rom various publica-

tions o authorized sources. The above cited successactors are required to be tested and validated inauto component rms or generalizing the researchstudies. This leaves scope or urther research too.

Reerences

1 ‘Automotive Mission Plan (Amp) 2006-2016’(2006), Ministry O Heavy Industries And Pub-lic Enterprises, Government O India.

2 Auto Policy 2002, Ministry O Heavy IndustriesAnd Public Enterprises, Government O India.

3 Ark, Bart Van, Erumban, Abdul Azeez, Chen,Vivian, Kumar, Utsav, (2008) ‘The Cost Com-petitiveness O Manuacturing In China AndIndia: An Industry And Regional Perspective’,Indian Council For Research On InternationalEconomic Relations, Working Paper No. 228

4 Ambastha Ajitabh And K. MOmaya (2004)‘Competitiveness O Firms: Review O Theory,Frameworks, And Models’, Singapore Manage-ment Review, Vol. 26, No 1, Pp 45-61

5 Barney, J.B. (1986b) ‘Organization Culture:Can It Be A Source O Sustained CompetitiveAdvantage’, Academy O Management Review,11 (July), Pp 656-665

6 Barney, J.B. (1991) ‘Firm Resources And Sus-tained Competitive Advantage’, Journal OManagement, Vol 17, Pp 99-120

7 Biggeri Luigi, ‘New Challenges In MeasurementO Competitiveness In Economic Globalization’,Document I/8

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multidimEnsionAl nEtWorks: thE ChAnGinG ChArACtErAnd frAmEWork of intEr-firm CollAborAtion

Ploder, Michael1

Steiner, Michael2

The paper explores the orm and content o eco-nomic interaction o rms based on various con-cepts o agglomeration and social networks. It usesa case study o the machinery sector in the regiono Styria as empirical background.

Starting with types o clustering—the model opure agglomeration, the industrial-complex modeland the social-network model—the paper arguesthat given geographical agglomerations allow di-erent types o networks and dierent patterns

o behavior, and thus dierent orms o learning,knowledge sharing and knowledge creation.

Some “stylized acts” in support o this perspec-tive are derived rom an analysis o a regional net-work. This network comprises more-or-less individu-

1 Joanneum Research

2 University O Graz

alistic open systems consisting o several areas ooverlap. Physical linkages between these networksare rather weak, but intersections based on coopera-tive R&D and R&D inrastructure, qualication andinormal exchanges are clearly evident, and seem todominate rom a regional perspective. Despite evi-dent sectoral concentrations, direct links to the pre-vailing science base appear more signicant as bind-ing actors than long-term supplier networks. Theserelationships are interpreted in terms o their need

or proximity, their durability and above all their di-rection o knowledge dependency.

Keywords: Agglomeration, Knowledge Transer,Social Networks, Evolutionary Economics

ABSTRACT




introduCtionWhile we are well aware that it is probably im-possible to provide one single theory o clustersand their networks, there is nevertheless a certainconsensus that several elements o specic theories

may help us understand their orms and unctions.They, thus, oer a certain unity o approach inidentiying the important elements that are neededor explaining the changing character o the inno-vation process.

Recent debate has begun to ocus more on howar, and in which ways, clusters oster knowledgecreation and organizational learning, and has em-phasized the organic-evolutionary dimension ocluster-based industrial agglomerations. Knowl-edge has been recognized as a major source ocompetitive advantage in an increasingly integrat-ed world economy (Dosi and Malerba 1996, Grant1996, Foss 1999, Nonaka et al 2000).

The most successul regions are perceived to bethose where rms display innovative capacity, i.e.rms are able to adapt to a rapidly-changing mar-ketplace and stay one step ahead o competitors.

The emphasis o cluster interpretation haschanged rom an analysis o orces o agglomera-tion to the various orms and contents o organiza-

tional learning and knowledge exchange—the orig-inal concentration on clusters as mere geographicconcentrations o sectors and rms has been trans-ormed into a search or institutions or knowledgemanagement and organizational learning empha-sizing the organic-evolutionary dimension.

Growth o the knowledge base depends on in-tended and unintended individual processing oexperiences, i.e. ‘learning’, while the interpreta-tion, transer and use o experiences is infuenced

by interaction between individuals and betweenorganizations (Cohen/Levinthal 1989, Ander-sen 1995, Hartmann 2006). These insights haveshited the emphasis rom material links to theimmaterial knowledge fows within clusters, andhave pointed to the need or connectivity betweendierent agents concerning knowledge creationand diusion.

This has then led to urther questions concern-ing the degree to which clusters are to be regarded

as non-market devices by which rms may seekto coordinate their activities with other rms andknowledge-generating institutions. Ongoing learn-ing processes between rms and within clustersstress the importance o institutional arrangements

or the generation o knowledge and learning net-works that are not available in markets (Maskell/ Malmberg 1999). As the necessary knowledge maylie outside a rm’s traditional core competence,inter-rm alliances and networks are widely recog-nized as an important organization orm o innova-tive activity (Gay/Dousset 2005).

In this paper, we again emphasize the ideas oagglomeration and knowledge exchange, and dis-cuss to what extent this approach has specic re-gional or spatial dimensions, while ocusing on the

necessity and orms o proximity, especially withrespect to knowledge exchange.

By means o network analysis we then developsome “stylized acts” or the various dimensions ointeraction within a given network o medium-techrms in Styria, one o the nine provinces (regions)o Austria. The nal section is used to interpret thendings.

GEoGrAphiCAl AGGlomErA-

tion And loCAl nEtWorksSince Marshall (1890/1920), Weber (1929) andHoover (1948), many authors have dealt with thephenomenon o geographical agglomeration. In thediscussions o clusters, networks and agglomera-tions, and particularly in those relating to indus-trial districts and agglomerations, there are cer-tain common traits, and requently terms are onlyweakly dierentiated.

The basic idea o geographical agglomeration

was brought up by Marshall (1890/1920) and thethree sources o economies o agglomeration hementions—input sharing, labor market pooling andknowledge spillovers—correspond with the core-elements o the current cluster-concept, at least inthat orm in which it has been discussed since theearly nineties in industrial countries. A more re-cent attempt to distinguish various cluster ormshas been made by Belussi (2006) by contrasting




geographical agglomeration and active clustering(as policy- or rm-driven strategy).

While implicitly ocusing on geographical ag-glomeration and economies o agglomeration, westress here a dimension o externalities beyond

the tangible dimension o direct co-operation. Onextending the basic idea o economies o agglom-eration, we see that externalities are widely en-orced by inormal and non-economic dimensions.Amin and Thrit (1995) use the term “institutionalthickness” to address the existence o a support-ing environment beyond rms (institutionalizedco-operations and networks). Geographic agglom-eration (and concentrated versus dispersed locationpatterns) set a ramework or economic interactionand (material and immaterial) linkages between

economic actors.The existence o a cluster doesn’t necessarily

imply the coexistence o all dening characteris-tics o a geographical agglomeration. On the otherhand, a geographical agglomeration may also existin the absence o a cluster or network.

While the existence o a pure geographical ag-glomeration (e.g. a city) avors the development oclusters; growing networks and clusters can alsocause the emergence o a geographical agglom-

eration, as was the case perhaps in Silicon Valleyin Caliornia. Myrdal’s (1957) idea o cumulativecausation corresponds with a dynamic view o a co-evolutionary development o economies o agglom-eration and growing clusters (without yet ormal-izing interdependency as was done by Kaldor, 1972and Dixon and Thirlwall, 1975).

In other words, additional local linkages and re-lations strengthen tendencies o concentration andagglomeration. Networks and clusters are possiblemeans o overcoming constraints o exchange with-

in and between geographical agglomerations, andalso acilitate the denition and deense o rules oexclusion, as already pointed out by Marshall.

Yet, what is still an open question is the micro-perspective. Economies o agglomeration and di-mensions o interaction could be selective in re-spect o the actors, since they regulate the extentto which the latter are able to participate or gainrom externalities: e.g. with respect to exchange o

physical goods versus R&D, or labor market poolsor blue collar workers or engineers.

In addition to direct physical exchange, inputsharing and common labor market pools, system-atic knowledge exchange and knowledge spillovers

have gained considerably importance as an argu-ment or geographical concentrations o activities.A requently used argument is that the collabora-tive nature o innovation processes has reinorcedtendencies toward geographical clustering becauseo the advantages o locating in close proximity toother rms in specialized and related industries(Storper, 1995, 1997). Transaction costs such astransportation costs and spatial communicationcosts in particular, reinorce the relationship be-tween individual environment and the development

o embedded social networks (Granovetter 1994).Firms establish a variety o types o interactions

and relationships, each o them having dierentimpacts on the knowledge generation and diusionprocess. Mariotti and Delbridge (2001) speak othe necessity or rms—in the ace o knowledgeambiguity, o knowledge-related barriers, o tacit-ness and complexity o knowledge—to engage inthe management o a portolio o ties.

Organizations are thereore likely to engage in

inter-organizational relations that show a varietyo types o ties:They can have quite dierent dimensions and

can be dened according to the character o socialrelations between actors, the regulation o the re-lationship, requency o use, length and duration othe relationship, and also o course in terms o thenature o the inormation exchange itsel (Mari-otti/ Delbridge 2001, 13). It is also important todistinguish between both content (i.e. the type orelation) and the orm (i.e. the social structure o

relations), as has been outlined by Powell/Smith-Doerr (1994).

One additional question which needs to be ad-dressed in this context concerns the legitimacy oa pure micro-level, individual rm approach inanalysing the incentives or clustering.

Individuals and rms alone are, rom an eco-nomic point o view, not capable o delivering su-cient amounts and varieties o knowledge. We are




conronted here with one o “the most troublesomeissues in the social sciences …” (Felin/Foss 2006,1) – the question o the adequate level and unit oanalysis. The question o whether the individual orsocial collectives (rms, networks, regions …) have

explanatory primacy is o course part o an old de-bate in economics, sociology and the philosophyo science and is oten now dealt with under theheading o “methodological individualism” versus“methodological collectivism” (Hayek 1945, Pop-per 1957, Coleman 1964, Douglas 1986).

Further potential or conceptual dierentiationrelates to the orms, channels and mechanismso knowledge exchange. As this exchange occursthrough interaction, the structure o the interac-tion infuences the extent o knowledge diusion

(Gay/Dousset 2005). This coincides within the viewthat “spatialities and temporalities are not neutralrames, but constitutive elements o socioeconomictransormation” (Colletis-Wahl et al 2008, p.22).

The cross-sectoral dimension o knowledge spill-overs is also a source o contention in the literature.Following Marshall (1890) and Arrow (1962),knowledge is predominantly industry-specic.Knowledge spillovers may thereore arise betweenrms within the same industry. Jacobs (1969), on

the other hand, mentioned the signicant act thatknowledge may spill over between complementaryrather than similar industries.

The signicance o geographical agglomerationand networking is strongly determined by the par-ticular sector (industry) and the leading technol-ogy. There seems to be a clear agreement in therecent literature about cross-sectional dierencesin agglomeration orces: As has been emphasizedby Botazzi et al (2001, 2003) and also Gordon/ McCann (2000, 2005), huge inter-sectoral dier-

ences in spatial agglomeration outcomes can beidentied.

Following Gordon/ McCann (2000) agglom-eration economies appear particularly relevant in“scale-intensive sectors” - hinting at the orms ohierarchical agglomeration discussed above - andin “supplier-dominated sectors”. Conversely, theyappear the least relevant in “science-based” sec-tors. The importance o agglomeration depends

closely on the prevailing sectoral and technologicalpattern.

The ollowing argumentation takes up two ap-proaches to dierentiating typologies and ocuseson the dierent dimensions o agglomeration and

clustering viewed as helpul guidelines in the dis-cussion o the network observed in Styria and inanswering the key-questions o the empirical analy-sis. An attempt is also made to combine, and di-erentiate, the “agglomeration” approach with theadditional insights mentioned above.

Gordon and McCann (2000: 15) dene anddiscuss three theoretical approaches or industrialclustering that refect dierent (more or less ideal-ized) perspectives on agglomeration—the model opure agglomeration, the industrial-complex model

and the social-network model.n The phenomenon o economies o agglomerationas an intrinsic motive or clustering, in the sense ospatial concentration o economic activity, is attrib-uted more or less exclusively to the traditional ideao Marshallian industrial districts. Following in theootsteps o Thünen in the eld o location econom-ics, and Smith’s idea o division o labor, the modelo pure agglomeration, which in the tradition oMarshall is based on a local pool o specialized la-

bor, on the increased local provision o non-tradedinput specic to an industry, and on technologicalspillovers may contribute to an “evolving localizedenvironment o learning” (Gordon/McCann 2000,517). The Marshallian approach was quickly devel-oped and extended by Hoover (1948) by distinguish-ing between localization economies and urbaniza-tion economies. Following Marshall (1890/1920),positive externalities o agglomerations are denedby regional non-traded inputs, knowledge and in-ormation spillovers, and a local pool o skilled

labor. From the perspective o knowledge fowsand learning processes avored by agglomeration,such externalities occur more or less unheard andunseen. Knowledge exchange and learning occursunconsciously via transer o human or materialresources. The most important point seems to bethat the approach is not bound to the idea o directsupply-relationships among the bulk o actors in-volved. Following the traditional idea o Marshal-




lian industrial districts, interaction is primarily ledby the needs o industrial production.n A second group o approaches pooled by Gor-don/McCann (2000: 517) under the term o in-dustrial complex models systematically tried to

justiy spatial concentration by the quantica-tion and minimization o spatial transaction costs(refecting the origins o the approach, primar-ily transportation costs). The industrial complexmodel is associated with cumulative learningrom sources inside the industry, non-transerableexperience, the role o leading rms and powerasymmetries (Iammarino, McCann 2005). Al-though the implicit concealment o (unplanned)economies o agglomeration didn’t mean that theywere not relevant. Attention nevertheless shited

to innovation as an interactive process involvingthe sharing and the exchange o dierent ormso knowledge between actors (Lawson and Lorenz1999)—knowledge and competence as developedinteractively and within subgroups o a regionaleconomy (Freeman 1979, Lundvall 2002). Thecritique here has been concerned with the questiono whether this interaction is an outcome o (neo-classical) rational behavior or the result o a more‘associative-relational’ mode o organization, or

what has been termed ‘associative governance’,leading to the creation o clubs, orums, consor-tia and other institutional schemes o partnership(Cooke 1998; Cooke and Morgan, 1998). Thereare elements o knowledge sharing in the sensethat adopting the perspective o specic clustersrepresents a quasi-monopoly or the internaliza-tion o the benets o innovation created withinthe (more or less) “closed club”.n The social-network model as the third type—relying on trust and social embeddedness as the

dominant link between the cluster rms (andthereore not on deliberate economic decisionsbased on the minimization o dierent transactioncosts)—also avors the exchange o knowledge.However, such exchange is here based on stronginterpersonal relationships that transcend rmboundaries and allow or diverse orms o knowl-edge sharing. Following Iammarino and McCann(2005), traditional and recent approaches o

social networks may be dierentiated. The tra-ditional approach corresponds to the ‘Marshall-stimulated’ industrial districts where knowledgeis mainly codied and oriented to process in-novation transerred by personal contacts, and

social and political lobbying. While in the tra-ditional approach the network seems to be basedon geographical proximity rooted in historicalexperience, the new approach o social networksseems to be based on relational and organization-al proximity. The links between actors are thenstronger the more they are based on elements osocial embeddedness: norms, sets o common as-sumptions, habits ormed by culture, history, ando course, but not necessarily, spatial proximity.They orm social capital that avors the explicit

and implicit sharing o knowledge. New physicaltechnologies and innovations do not just happen,they need social technologies as pathways to co-ordinate human action.

As Iammarino and McCann (2005) mention,much o the discussion in the literature is basedon ideal types, whereas in reality all spatial clus-ters and industrial agglomerations will containmore or ewer o the above characteristics, ur-thermore, clusters may mutate rom one typol-

ogy to another. From another perspective, this isalso outlined by Rychen/Zimmermann (2008, p.768): the concept o cluster “usually consideredas a spatial concentration o industrial and tech-nological activities” has to be enriched and “it ismore important to understand how and why rmsbuild links and how the structure o links will givesense (or not) to the co-location o actors.” It isthereore important to incorporate the dimensiono collaboration—the basic conception o rms isa “network-driven economic strategy built on col-

laboration among the participants” (Reid et.al.2008, p.2).

The ollowing section is dedicated to interpret-ing the case network investigated in the light o theapproaches discussed above. The suppositions thatcontext, typology and signicance o geographicalagglomerations and embedded networks change,seems to be clearly refected in the case o the ma-chinery sector in the region o Styria.




thE EmpiriCAl AnAlysis:A QuAlitAtivE ApproAChbAsEd on soCiAl nEtWork AnAlysisThe empirical analysis starts with an analysis orelevant regional data and expert interviews andthen continues with a case study analysis o the re-lations o engineering rms in Styria.

Interaction in the observed network

Network analysis is a well established method inthe social sciences. Recently, the method has alsobeen applied to the analysis o production clusters(Krätke 2002), innovative activity and knowledgeexchange (Giuliani 2005), and alliance or R&Dnetworks (Gay/Dousset 2005).

Social network analysis is a helpul tool or dis-cussing the structure o networks as it allows themapping and measuring o the relationships (com-munication and transaction) between dierent ac-tors, i.e., the existence, context and portolio o re-lations between actors in a regional network. It isa method or revealing relations between dierentactors. Such relations are phenomena that cannotbe reduced to the properties o individual actors or

rms themselves and thus need to be interpreted asproperties o systems than o individual actors.

The Empirical Database The present network analysis is based on an em-pirical sample o rms identied by a snowball-ing method o sampling in cluster and networkinvestigation. This corresponds with the relationalapproach and is developed by means o the reer-ences to actors as revealed by previous respondents(Frank 1979, Scott 2000). 1

Our starting point was a large system supplier inthe automobile sector located in the region o Styr-ia/Austria. The snowball method produced rmsbelonging to dierent sub-sectors o the manuac-turing sector and related supply-chain and innova-

tion-strategies. Starting with the initial rm, thesample was developed. Following a citation path oregional suppliers (production or commercializa-tion o goods and services) and o regional partnersin the eld o research and development (coopera-

tive R&D and related activities and exchange, thedatabase or the subsequent network analysis wasextended to 23 rms, o which 18 are producers(with dierent positions in the supply-chain suchas system-suppliers, component suppliers and toll-manuacturers). The remaining ve are technicalbusiness services. Additionally nine R&D institu-tions (universities, co-operative R&D institutions)are included. The inormation and data collectedare based on extensive qualitative interviews andsupported by a quantitative survey concerning spe-

cic data.

Indicators of Interaction Qualitative indicators revealing individual strate-gies o innovation are helpul discussing individualstrategies and their aggregation at the networklevel. They are selectively used here to nd—vianetwork analysis—the structural eatures o thenetwork o 32 actors. The selected indicators othe relations cultivated by the organizations coverthree dimensions o interaction: direct delivery re-lations, R&D, and technological innovation in acompetitive and a pre-competitive context.

(DELIV): The rms were questioned concern-ing direct delivery relations (goods or services) toclients, suppliers or partners (in the case o syn-ergetic product bundles).2 The direct delivery ogoods and services is not reduced to the materialdimension as it also covers questions o innovationin inormation management or capacity-extendinginvestments.

(PRE-COMP): The dimension o interaction inthe context o pre-competitive R&D was also ana-lyzed. Pre-competitive research and developmentaims to extend the product spectrum, as well asintroduce new processes and alternative materi-

1 The assumption is that the segment o the network that orms the sample is representative o the whole network. More exact knowl-edge o present population and relevant relationships is obviously necessary. However, results rom an earlier investigation support

the accuracy o the present sample technique.




als. It includes undamental research, which is anactivity designed to broaden scientic and tech-nical knowledge not necessarily linked to indus-trial or commercial objectives, as well as indus-trial research, i.e. research aimed at developing

or improving new or existing products, processesor services in so ar as it is also not directly con-nected with a client tender, oer or an existingbusiness relation.

(COMP): Competitive research and develop-ment and innovation processes are short- andmedium-term oriented and mostly associated withdirect expectations o return or with a direct tenderor oer etc., which is in contrast to pre-competitiveR&D that is long-term oriented.

Structure of Network and Network Density Following the socio-centric approach, the densityo a network is given by the ratio o relations real-ized to the total number o potentially maximumpossible relations. We dichotomized the relationsin that we only dierentiated between existenceand non-existence o a relation between two actors[0; 1], and thereore disregarded the intensity othe relations (in our case the requency o interac-tion) surveyed. This enabled us to avoid the prob-lems typically associated with the measuremento the intensity o evaluated graphs (Scott 2000).Network density yields inormation on the generalstructure o the network as a whole.

One o the core eatures o an actor identied innetwork analysis is its centrality. Using the concepto centrality (in dierent orms) we gain insights intothe specic eatures o the interaction o the actorsin the network and their specic position and/or em-

beddedness in the network. While density ocuses onthe properties and general structure o the networkas a whole, centrality tries to capture the position oindividual actors or groups o actors within the net-work. This is again based on the relations revealed

by the actors, where the relations are valued ordinar-ily in terms o requency o interaction. The poten-tial centrality o an actor is determined by a broadrange o industry or sector-specic actors (Cohenet al 2000), by capacity and individual motivation(Bayona et al 2001, Theter 2002). A high centralityis positively associated with multiple possibilities orreceiving and generating knowledge.

Keeping in mind that interregional and interna-tional relations exist and may be o major priority,e.g. direct delivery relations, the analysis below o-

cuses on regional interaction. Table 1 presents thedensity measure or the three dimensions o rela-tions between the actors.

Direct delivery relations have the weakest den-sity. Although the datasets have been dichotomizedand thereore relations with a very low requencyo interaction have been “up-graded”, the densityo the network o direct delivery relations is lowerthan the density o knowledge-intensive and inno-vation-related interaction. Regional input-output

relations were reduced in order to ocus attentionmore on international markets.While competitive R&D and innovation process-

es, especially in the case o domestic system suppli-ers, are partially similar in density to direct deliv-

2 The dimension o supply-chain networks is a unction o verti-

cal integration and division o labor in an industry. The auto-mobile and aerospace industries are avorites in supply chain

networks and relations. They are, however, special cases as

middle or high volumes o products, with a relatively highnumber o individual parts, are produced by specied rou-

tines. Regional clients in other areas o the machinery sector

and their limited lot or customized orders place constraints

on medium- and long-term planning, automation and growth.This approach was not used that extensively in the machinery

sector. Given the importance o the systems subcontracted by

assemblers, a clear strategic goal o these rms is working

with a smaller number o large suppliers.

3 Even in the case o a network o 32 actors with a relatively

low density the number o cross-cutting relations is relatively

conusing, even more so with a network density o 0.223.

RelationalDimensions

Density

(Deliv) Direct Delivery Relations 0.068

(Pre-Comp)Interaction In The Con-

text O Pre-CompetitiveR&D

0.143

(Comp)Interaction In The

Context O CompetitiveR&D And

0.074

Table 1 Density o Observed Dimensions o Net-

working




ery relations, the regional density o the network inpre-competitive R&D is much higher. While R&Dinstitutions are o negligible signicance in respecto direct delivery relations, the network is based toa considerable degree on relations with cooperative

R&D institutions.The relational data can be used to provide agraphical representation o the transaction networkor the organizations observed. While network dia-grams oer a traditional and basic methodology orormalizing network analysis, and are a very helpulmean o interpretation and discussion, clarity suersgreatly as the number o actors observed increases.3

A quite useul method o graphical represen-tation, which is implemented in most sotwarepackages, ollows the approach o Kamada-Kawai

(1989) spring embedding algorithm. This is nowemployed below.

Figure 1 gives an overview o all relations re-corded, and combines the three dimensions dis-cussed above. It also takes into account the valu-ation o the relations in terms o requency ointeraction. The shape o actors (nodes) corresponds

with the dierent types o organizations. The sizeo the nodes corresponds with the size o the orga-nization, and the length o lines corresponds withthe distance between the actors observed.

A urther interesting dimension o networkanalysis is ‘coreness’, which ollows the idea ocore and periphery. Here we use the concept o thek-core (Seidman 1983, Scott 2000). A k-core isa sub-graph in which each actor is adjacent to atleast k other actors in the sub-graph. That is, orall nodes in the sub-graph minimum the number

o the actors’ direct relations within the sub-graphis k (in our case eight). K-core analysis comple-ments the measurement o density, since the lat-ter is not able to refect structural eatures o thenetwork. The k-core is an area o relatively highcohesion. As can be seen at rst glance, we candierentiate between those actors in the core othe network (colored black) and those actors moreor less on the periphery o the network (coloredwhite). The diagram reveals the high density o

the realized relations calculated in the previousparagraphs. In the k-core o the diagram, we nda group o institutions that seem to interact mul-tilaterally. In the “core” o the network, we ndR&D institutions, large system suppliers and tollmanuacturers (surace-treatment, heating etc.),which maintain multiple, but weak relations, witha broad range o regional clients.

Spotting a Leading Firm in the Network

Here we now ocus on a specic rm, ss 20 in the

total network. This is a highly specialized manuac-turer o measuring equipment or science and indus-try. This success is based on the direct applicationand transer o scientic knowledge gained in themeasurement o physical or chemical phenomena.

The rm is highly vertically integrated and isembedded in smaller networks ollowing niche strat-egies. The partners o the rm in direct delivery(component and toll-manuacturers) and its part-

systems supplier

component supplier

toll manufacturer

technical business services

R&D- institutions

systems supplier

component supplier

toll manufacturer

technical business services

R&D- institutions

Source: Present Authors

Fig 1: Network o Firms and KnowledgeGenerating Institutions




ners in competitive and pre-competitive researchand development (key clients, highly specializedbusiness services, universities) are not identical.

On the delivery side, the observed rm interactswith component suppliers in the eld o die cast-

ing, spray casting, plastics processing, electronics,sheet metal orming, and manuacturing o highperormance glasses.

Originally, the rm was a pure converter, produc-er and specialist in marketing. This division o laborhas changed since the 1980s. A well-established co-operative base allows access to university partnersand to an independent research laboratory that pro-vides exclusive, science-driven R&D. The rm enjoysa relatively high in-degree centrality in respect o di-rect deliveries. The out-degree centrality o the rm

in the region, with respect to deliveries, is consider-ably low bowing to the high export intensity.

A high share o the turnover is reinvested inR&D activities, 10% or intramural R&D and anadditional 10% o the turnover or external R&D.The degree centralities in respect o R&D (pre-competitive and competitive) are higher than orthe average o the leading rms in the network. Thecore competences o the rm are based on combin-ing and applying ndings rom basic research, in

precision engineering and electronics.While radical innovations and market noveltiesmostly emanate rom R&D or client-partners, in-cremental improvements are promoted by internalR&D. R&D and production and marketing o newproducts are concentrated within the region.

As the rm is not located in the core o vehiclemanuacturing, but in the interace with other sectorssuch as manuacturing o plastic products or mea-surement techniques, it has a relatively high value orbetweenness centrality. The ndings or this typical

rm serve to strengthen the thesis that rms actingin market niches, demanding highly specialized coop-eration, tend towards long-term cooperation.

The Historical Background and Changing Role

o Geographic Agglomeration in the Medium-

Technology Sector in Styria

The majority o the observed rms have been in theregion or more than ten years. The current situa-

tion and recent developments cannot thereore beadequately analyzed without considering the his-torical background and structural change o re-gional industry over the last ew decades.

In the late 1960s and 1970s, the networks in

the medium-technology sector were dominated bylarge state-owned rms that were highly verticallyintegrated and had lost their headquarter unctionsto Vienna. While supply-side linkages to the regionstill existed, agglomeration took a very limited tra-ditional orm. In most cases, planning, R&D andmarketing/distribution unctions, i.e. those unc-tions responsible or the monitoring o marketsand technology, had been lost. Clearly, observablelock-in eects had led to agglomeration becominga mere by-product o path-dependence with none

o the advantages o agglomeration mentioned byBotazzi et al (2001).

Against the background o a history o out-ward dependence and nationalized standardizedmass production, the traditional indicators usedto measure the strength o social networks hadbecome very weak. According to Iammarino andMcCann (2005), social networks exhibit the ol-lowing characteristics—knowledge is largelycodied and mature and mainly oriented to pro-

cess innovation, transmitted essentially by way opersonal contacts, and there is extensive socialand political lobbying, backward and orwardlinkages. As ar as social networks still existed(e.g. in the machinery and the automobile sector),they became a ruitul base or the restructuringo the 1990s.

During the developments o the last ew de-cades, the typology o agglomeration and the roleo networks have changed considerably. Many largerms were re-privatized and down-sized at the end

o the 1980s. Firms, thus, needed to learn to col-laborate and develop their potential or innovationas a strategic resource. This entailed abrupt, andlong overdue, change rom a Fordist to a more fex-ible mode o production.

A massive structural change took place, begin-ning in the 1990s, especially in sectors related tosteel production, such as mechanical and automo-tive engineering. High degrees o diversication




and broad unspecied clienteles were replaced bya ocus on market niches and technological spe-cialization, while higher lot sizes enabled highercross-unctional integration and raised fexibilityby leaving scope or automation. Technological up-

grading (including the introduction o quality andmeasuring standards) also opened doors to a newclientele. This was accompanied by extending otheir responsibilities or tool making and sourcingcapabilities, and also by shiting the responsibilityor quality and price rom clients to suppliers. In-novations in these sectors were infuenced by ap-plications o specialized knowledge in the eld omaterials, tooling and processing techniques, orby the need to solve very specic problems in themachinery sector, on the supply side, hierarchical,

spatially localized relations were developed. Thesehave been ormed around the elite R&D-intensiveand export-oriented large rms.

Human Resources and the Regional Labor

Market

A typical characteristic o agglomerations, in thesense o the model o pure agglomeration mentionedby Gordon and McCann (2005), and also ollowingBotazzi et al (2001)—namely, a more or less com-mon labor market pool—was not observed.

For the investigated component supplier rms(here in more-or-less rural and isolated areas) itis still the case that they operate with reerence tovery local labor markets, binding traditions and alow mobility o employees. Small- and medium-sizedsupplier rms exhibit amily-based traditional struc-tures, sometimes over generations. Concerning thequalication structure, there are deep dierencesbetween original equipment manuacturers (OEMs)or system-suppliers with R&D units on the one hand,

and basic technology providers, extended work-benches or third-party subcontractors on the other.

This is true or both lower- as well as high-skilledworkers, where employee turnover is normally amore-or-less accepted instrument o knowledgetranser and networking among rms. Because othe immobility o the local labor orce and the re-stricted capacity o the regional labor market, mosto these rms were able to retain the key-personnel

and competences and the regionally integrative po-tential o their personnel. Yet, by the same token,this implies only little mobility o qualied person-nel coming rom Europe (or language reasons,predominately rom Germany). Also due to ocial

restrictions, labor infow rom the new EU membercountries remains limited.

Discriminative Capabilities and Heteroge-

neous Strategies in the Case o R&D and In-

novation

As already mentioned, leading rms do not play adominant role on the demand side. The broad rangeo material input-output linkages is directed out-ward and direct material linkages on the regionallevel (corresponding to the industrial complex mod-

el mentioned by Gordon/McCann) are considerablyweak. In act, the opposite seems to be true. Inthe case o large rms, agglomeration phenomenabased on knowledge complementarities (Botazzi etal 2001) seem to be clearly evident.

The R&D capacities o the observed rms werehighly varied. Nearly hal o the investigated rms(mostly SMEs) do not employ permanent R&Dsta. The leading rms have intensied R&D ac-tivities and ormal co-operation with knowledge-generating institutions since the mid-1990s.Especially in the case o pre-competitive R&D, co-operative publicly-supported projects or participa-tion in cooperative R&D institutions has gainedan increasing role as a policy measure during thelast decade.

In respect o knowledge-driven activities, ele-ments o agglomeration phenomena based on knowl-edge complementarities were observed (ollowingBotazzi et al 2001). These were also in line with theexclusivity characteristics suggested by the industrial

complex model (Gordon and McCann 2005). Thelarge R&D intensive rms observed here constantlyseek orms o regional pre-competitive R&D coop-eration. This may result in the ormation o “Clubs”

5 The Competence Centre Program was introduced in 1998.

Competence centers are co-nanced by the regional govern-

ment, the national government and the active partners. A

considerable part o co-operation involves third parties (pre-erably SMEs).




(Gordon and McCann 2005, Cooke 2000) o closerinteraction especially in respect o R&D, or in somecases cooperative R&D institutions. While materialinput-output linkages are spreading widely, and areoutward oriented, the R&D-oriented sphere is con-

centrated on the local context and to a large extentsupported by intensive direct and indirect social in-teraction (inormal exchange, contacts in the localtechnical community). During the past ew years,in terms o innovation, rms already active in R&Dhave undergone a shit rom being demand-pull-driv-en (responding to market demands) to technology-push-driven (rms have become proactive in theirsearch or new technologies and USPs). This has in-creased the motivation to be integrated in the region-al (technical) science community. The main spheres

o economies o agglomeration have shited consider-ably during the last ew decades. The newly identiedresearch ‘Clubs’ in publicly-supported R&D projectsare able to utilize economies o agglomeration pri-marily concentrated in the eld o R&D and science.

As long as natural spillovers are high and com-petitive conficts are manageable (e.g. in the caseo material sciences), larger rms accept weakerpartners, and/or smaller rms, and are willing tointegrate them into their activities. Low spillovers

and a higher market orientation avor more re-strained, sometimes exclusive, behavior rom thestronger side. This corresponds with the ndingsin the literature or partner selection in R&D coop-erations (Atallah 2005).

This orm o agglomeration, partially takingplace beyond ormal networks, also correspondswith the idea o a new type o social network men-tioned by Iammarino and McCann (2005). Firmsengaging in cooperative pre-competitive R&D andknowledge generation appeared to seek suitable

equal partners.The qualitative interviews strengthened the no-

tion that rms attempt to generate a portolio ocooperative partners, which consciously combinesspecialization and fexibility. In terms o knowl-edge generation and exchange, the geographic di-mension is relevant as long as the actors are ableto utilize knowledge potential. While larger rmswith noticeable R&D capacities are able to utilize

international contacts in research and developmentactivities, smaller low- or medium-tech rms stickto the region and to their regional partners. Small-er rms are conronted with a sel-reinorcing com-bination o low R&D capability on the one hand,

and limited market demand on the other.In agreement with the concept o absorptive ca-pacity, it was ound that rms with low R&D andinnovation potential (mainly component suppliers,where innovation is predominately directed by in-vestment) ound it dicult to build up and retainadequate relations with knowledge-generating or-ganizations. The medium-tech component suppli-ers observed here, proved to be unable to maintaincontinuous relationships with knowledge-generat-ing institutions. They were not capable o dening,

setting up and managing relevant projects. Theselow and medium-tech rms did, however, partiallyutilize opportunities to establish long-term contactswith individual public or semi-public R&D institu-tions (dealing with basic technologies mostly mate-rial sciences). They also tried to gain rom possiblespillovers rom per appropriate events or inormalinquiries. Here, partner behavior in direct deliveryand in competitive and pre-competitive researchand development, as ar as existent, is not identi-

cal. While cooperative R&D and knowledge gener-ation o regional SMEs are relatively seldom, andsupply-chain relations are dominated by extra re-gional linkages, low- and medium-tech SMEs gainrom knowledge-sharing in respect o quality man-agement, inormation management and promotiono the location by ormal cluster organizations.

In addition, two interesting long-term partner-ships between small knowledge-intensive technicalbusiness services and large systems and componentsuppliers were observed, in the network analyzed

here, and were based on long-term trust and inor-mal exchange.

ConClusionGeographic agglomerations, on the one hand, andnetworks and clusters on the other have to be in-terpreted as interdependent phenomena. The roleso clusters, networks and geographical agglomera-tion are subject to considerable co-evolution. Di-




erent approaches concerning orms, channels andmechanisms o knowledge exchange oer dierentconclusions with respect to the signicance o geo-graphical agglomeration in knowledge exchange.

In the case study analysis, dierent dimensions

o interaction can be observed. There are network-ing-dimensions o material, supply-oriented trans-actions, and networking-dimensions o knowledgesharing. The rst belongs to the process o divisiono labor dealing with the exchange o goods andservices, the second with knowledge. The main di-erences reside in the orm o interaction and inthe impact o interaction. The spheres o physicalinteraction (subcontracting relations) dier consid-erably rom the spheres o knowledge-intensive andR&D-driven interactions. They are dierent in re-

spect o actors involved, spatial extension, and thussignicance o geographic agglomeration.

The observed network is, in its regional dimen-sion, dominated by knowledge-intensive relations.The qualitative evidence gathered by numerous in-depth interviews reveals that the highest number ointeractions was reached in pre-competitive R&Dknowledge exchange and that immaterial dimen-sions dominate the material ones. The (industrial)rms do have extensive supplier relations, but only

to a very limited extent within the region and withinthe network. There is no automatic parallelism ointeractions. This does not necessarily exclude au-tomatic spillover o knowledge connected with sup-plier relations, but it does emphasize that higherintensities o knowledge exchange, as indicated bythe revealed orms o interaction are actively cho-sen and not a mere by-product. Knowledge-orientedrelations within the network are regionally concen-trated to a large degree. Proximity per se is not su-cient to generate knowledge between rms. The

diusion o knowledge within clusters is highly se-lective and strongly depends on the position o rmswithin networks and their absorptive capacity. Localuniversities and cooperative R&D institutions have adominating role and assume gate keeper unctions,especially in pre-competitive research. Firms witha relatively high R&D capacity also take up such arole, thus indicating the necessity o a well-devel-oped internal knowledge base. The dominating role

o the newly-ounded cooperative R&D institutions(competence centers) can be taken as an indicationthat this kind o network relation is rather new andthat the pattern o interaction has a temporary char-acter, and depends on the existence o specic kinds

o knowledge-generating institutions.In the Styrian case, the main dimensions oeconomies o agglomeration have changed consid-erably during the last ew decades. The portolio ointeractions and the meaning o agglomeration orthe observed rms cannot be reduced to specic di-mensions taken as given or not. To this extent thatthey are determined by rm capabilities and rmbehavior, not all dimensions o agglomeration, andthus economies o agglomeration, are accessible orall agents. While small- and medium-sized rms

partially gain rom economies o agglomerationin the eld o basic technologies such as materialsciences or tool making, large rms concentratedpre-competitive research in the region in order togain rom economies o agglomeration in the eldo science and R&D.

These agglomeration eects still seem to be con-centrated around certain insider ‘clubs’. A consid-erable number o rms investigated are not able toparticipate and gain rom economies o agglomera-

tion. While there is a long tradition o pro-activecluster and network promotion in Styria, sectoraldiversity (i.e. a low critical mass o actors) andrelatively low absorption capacity serve to hamperthe potential gains rom economies o agglomera-tion or a considerable share o SMEs.

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WhEn poliCy GoEs ClustEr: rEflECtinG thE EuropEAnWAy(s)1

Rehfeld, Dieter 2

1 In times o network and knowledge society, all research is embedded in collective structures. Thanks to Saskia Dankwart and AnitaPöltl or all support rom additional research to language washing. Thanks to Judith Testriep or a lot o discussion and ideas.

2 Institute or Work and Technology/University o Applied Science, Gelsenkirchen

introduCtionIt is obvious that cluster activities are dierentaround the world. In simple words, while Ameri-canactivities are rst o all business-driven, Europeanactivities are oten policy-driven (Ketels 2003). In

Europe, the European Union and structural undshave become ew o the driving orces in earlycluster-related initiatives. Cluster policy ollowedwith best practice in cluster initia-tives could bestudied. Despite success stories about cluster initia-tives, there are dierent ways o implementing thecluster approach in policy in Europe. Regional andnational governments ol-lowed their own way de-pending on the specic cultural and political pathsand the economic base. No wonder the cluster ap-

proach became more and more “uzzy” (Marcusen1999) in the course o success.Meanwhile, management studies as well as re-

search in economics and economic geography didcontribute to a deeper understanding o the struc-tures and processes o cluster development (Asheim/ Cooke/Martin 2006). There is a dierence, though,between how clusters develop and work in a suc-cessul way on the one hand, and how to initiateor infuence an evolutionary proc-ess (Boschma/ Frenken 2005) like this by political strategies and

instruments on the other. The second question re-quires deeper understanding o political processesbecause it is well-known that policy ollows rulesand conventions that are dierent rom economicones.

In order to ll this gap, this paper is about clus-ter policy rom a political science point o view. Itstarts with a brie outline o the context o clusterdevelopment, and then it discusses why the clusterapproach became so dominant in all elds o eco-

nomic policy. Going on, it attempts to work out whathappens when an economic success story becomesthe ocus o political pro-grams. The key argumentin this context is that the dierences within clusterpolicy in Europe can be explained by the specicnational or sub-national strategic traditions andcultures in eco-nomic policy. Despite those dier-ences, there are some key problems that result romdierent logics in policy and economy, and can bestudied as dilemmas that can be rebalanced, butnever solved by cluster policy. Nevertheless, cluster

policies have innovative impacts on political strate-gies or two reasons. Firstly, a cluster policy takesplace in the context o multi-level policy and thismeans that dierent political levels infuence eachother. Secondly, a cluster policy implies new modeso governance or at least a recombination o givenmodes o governance. In so ar, cluster policy hasan experimental dimension. Finally, some conclu-sions are presented about the challenges needed toimprove cluster policy.

To avoid misunderstandings it is best to startwith some key denitions. In this paper clusterresp. cluster development means the autonomousand evolutionary economic processes that aredriven by the benets o spatial density and re-




gional concentration. Cluster initiative reers tobottom-up, in most cases locally-driven, activitieso sel-organization o private (and oten pub-lic)actors that aim at ostering or strengthening thelocal clusters. Cluster policy reers to strategic ap-

proaches o central state activities that promote andsupport the implementation o cluster initiatives bya broad range o instruments that start with sup-porting sel-organization and end with more-or-lesstop-down planning instruments.

thE ContEXt of ClustEr dE-vElopmEntClusters are not really new in economy. The stud-ies o Alred Marshal in the late 19th century are

a point o reerence in most cluster studies, butspatial inequalities and regional concentration hadbeen broadly discussed in economic studies in thiscentury (Scheuplin 2006). This is not the place totell the story o cluster studies in the last decades.There are good reasons to assume that clus-tershave been an important aspect in the spatial divi-sion o labor in the course o the 20th cen-tury,too. For instance, the automotive industry has beenclustered at a very early stage o the developmento this value chain. In Germany, the clusters thatcan be studied today had been established in the1930s (Reheld 1999). Nevertheless, we can as-sume that in the course o mass production, stan-dardization o the value chain, internationalizationand global diusion o pro-duction technology, thelocal environment lost strategic importance in busi-ness strategies and in academic studies as well.

When the end o standardized mass productionbecame inevitable, the spatially dierentiated pat-terns o spatial division o labor came back on the

global maps. Piore/Sabel (1984) worked out theimportance o regional networking or the rise omore fexible production systems and in regionalstudies (c. the retrospective view in Cooke 2009)successul regional innovation sys-tems (the “holytrinity” o regional studies reers to Third Italy,Silicon Valley and Baden-Württemberg). In theend, it was Porter’s research on the competitiveadvantage o nations (1990) that gave the decisive

impulse to pay more attention to cluster develop-ment in policy as well.

In brie, there are our trends that are importantin order to understand the new interest in clus-ters.These trends are societal, but they all have in com-

mon a specic ocus on the regional level, they areoverlapping, and are strongly related to the clusterapproach (see gure 1).

Firstly, in the course o the last two or threedecades, there was a undamental change in com-pany culture (Boltanski/Chiapello 2003, Castells1996) driven by dierent actors:

n Companies became more embedded in valuechains than years beore (this means, there is a newbalance between market relations and network re-lations).n They aced rising insecurity caused by changesin innovation speed and complexity (net-works arehelpul in reducing several o these insecurities).n Rising integration o technology, production andservice unction requires more internal and exter-nal cooperation, and a related absorption capacity

o companies’ organization.n Globalization requires a deep understanding othe specic impacts o dierent markets and theinteraction o dierent cultures.

This change went rom a more-or-less lonesomerider culture to a network culture that infu-encedand partially changed the whole companies’ cul-ture, and did not start in clusters. In com-parisonto ormer decades, this change raised companies’

Fig 1: The Context o the Rise o the Cluster Ap-proach

Search of new

policy strategies

Decentralization

Regionalization

Global shifts:

New role of regions in a

global spatial division

of labor

Rise of the

network economy

"Entgrenzung"

Cluster

Approach




awareness o the region and encouraged compa-nies’ embeddedness in clusters.

Secondly, hand-in-hand with the rise o thenetwork economy, the spatial division o labor ischanging. The balance between national, state

and local or regional areas is rebalancing (Sas-sen 2008, Reheld 2009). From a business point oview, regions became more important than the na-tional environment. Even i this is studied by dier-ent concepts (agglomeration, cluster, met-ropolitanareas, or world cities), there is a strong ocus onthe reasons and impacts o spatial con-centrationon business activities.

Thirdly, in Europe the last decades became thehigh-time o regionalization and decentralization(Hooghe/Marks/Schakel 2010). Nearly all Eu-

ropean countries started a reorganization o thepolitical institutions that was driven by the ideao decentralization—more than a new division oresponsibilities between the dierent political andadministrative levels. It reers to the search o newmodes o governance, especially to public-private-partnerships, to activating instruments and tolearning processes (Benz et al 2010).

Summing up, the new spatial division o laborand the rise o the network economy go hand in hand

and related decentralization and regionalization inthe political-administrative system gave space ornew activities that corresponded with this econom-ic change. Clusters are o importance in all threeaspects. We can suggest that ourthly they work asthe missing link that gives policy the chance to re-organize institutional and strategic terms, and acethe economic change in a more successul way. Thenext section will discuss why the cluster approachnot only became an economic success story, but asel-enorcing process in policy as well.

thE risE of ClustEr poliCy Cluster policy is a late comer on the cluster agenda,though there are dierences. Austria and Finlandare pioneers, France and the German ederal stateBaden-Württemberg hesitated or a long time,the Middle and Eastern European countries aresomewhere in-between, and Turkey is just start-ing. Lower Austria, Grenoble resp. Rhone-Alpes in

France and Tampere in Finland unctioned as earlybirds. West-Midlands in the UK, Wolsburg andDortmund in Germany and Catalonia in Spain weresome o the most prominent ollowers.

Today, nobody really knows how many cluster

initiatives are active in Europe. The EuropeanCluster Organization Directory (2010) lists 1205cluster organizations in 216 regions, but there arelots o initiatives—like the privately-unded initia-tives not listed in public documents—that are miss-ing in this list.

The key impulse or cluster policy came romtwo sides. On one hand, successul cluster initia-tives had been established bottom-up. On the other,international activities contributed to the dissemi-nation o the cluster approach. The World Bank

conerence in Mexico in 1997, the insti-tutional-ization o The Competitiveness Institute (TCI), theCluster White Book (2003) and the Cluster GreenBook (2004) are some o the milestones in interna-tional cluster discussion.

In the European Union, cluster policy becamea strategic key issue in the context o the LisbonStrategy. Program lines like PAXIS, ProInno, In-nova or KIS aimed at organizing and disseminat-ing: good praxis, supporting networks between Eu-

ropean clusters in order to organize shared learningand to improve capacity building in emerging clus-ters and EC-policy moves towards strengtheningworld-class clusters (EC 2008).

Broadly speaking, national states and ederalstates have been the last actors in the eld o clus-ter activities. The dynamics o ormer activitieswere such that the central or ederal state becameinvolved in the process. There are our reasonswhy the cluster approach became so prominent inpolicy.

In strategic terms, the cluster approach lled agap in economic policy. The idea o a support driv-en macro-economic policy that became the leadingidea in the 1980s and 1990s, in combina-tion withthe hope o rising service industries that compen-sate the rising weakness in productive industries,became outdated with the crisis o the new econo-my around the turn o the century. The cluster ap-proach gave the ideas to ll both gaps: to reinvent




meso-economic policy combin-ing regional and sec-tor issues, and to renew the interest in productiveindustries in a uture-oriented way.

In institutional terms, cluster policy is a chal-lenge or the traditional institutional setting in

Europe. Departments o dierent ministries hadbeen complementary with industrial associationsthat oten represented a sector and not a valuechain. Regional activities had been ocused on asmall local level with strong administrative bor-ders. Bottom-up cluster initiatives showed that itis possible to overcome those institutional limitsand cluster policy hopes to renew the institutionalsetting or economic policy.

In instrumental terms, the uzzy charactero the cluster approach makes this approach t

in dierent philosophies in economic policy. Yound versions o cluster policy that are based onhard incentive and planning on one end and ver-sions that try to activate private actors on theother, an aspect that will be discussed in moredetail in the ollowing section.

The embedding in national philosophies onhow to drive economic policy especially explainsthe variations o cluster policy in Europe. Nev-ertheless, there are three basic assumptions in all

vari-ations o cluster policy (see g. 2). This isnot the place to discuss the reliability o thoseassump-tions because they are handled as quasi-

Fig 2: Key Ideas o the Intervention Model o Cluster Policy

© 2007 IAT – own illustration

Cluster-

management

FP1 FP2 FP3

Cluster-

politik

externe Rahmenbedingungen

Cluster

ClustereffekteKoordination

Innovation t0

I n n o v

a t i o n

t 1

Spill-over-Effekte

Cluster-

management

FP1 FP2 FP3FP1 FP2 FP3FP1 FP2 FP3

Cluster-

politik

externe Rahmenbedingungen

Cluster

externe Rahmenbedingungenexterne Rahmenbedingungen

Cluster Cluster

ClustereffekteClustereffekteKoordination

Innovation t0

I n n o v

a t i o n

t 1

Spill-over-Effekte

realities in cluster policy and in so ar they are asocial act (Durkheim 1961):n Clusters are more the innovative spatial andunctional core in a knowledge-based global econ-omy.n

The potential o clusters is high and can bemobilized. The expected synergetic eects espe-cially promise a new dynamic in competence andinnovation.n Policy has the knowledge and the strategic ca-pacity to make the potentials work in a dynamicand sel-enorcing way.

Following these key ideas the basic model ointervention entails the ollowing aspects (g.2):n There is a need or deciding what clusters

(where and who) promise good results when theyget political support.n The dierent elds o economic policy (labormarket policy, technology and innovation policy,regional policy, inrastructure policy) have to becoordinated.n The implementation needs strong cluster ini-tiatives that are based on a commitment rom thecompanies.n I this process works, it helps to improve the

development o the cluster in a synergetic waythat brings out spill-over eects that work as in-novative drivers in the national econ-omy.

From a political pointo view, this approach isnear to the task to squarethe circle and can bestudied by the dilemmaapproach (Prud’homme/ Dankbaar 2007):n Policy, especially in

European welare stateshas strong legitimatingrom equality and co-her-ence. Cluster policy needsto select and ocus on thestrong actors (“strength-en the strength”).n The dierent elds oeconomic policy are em-




bedded in very specic institutional con-texts andnetworks, and there is a lot o doubt about thechances o coordination.n Implementation needs bottom-up activities,but there is no guarantee that the interest o

those activities matches the top-down interest ocluster policy.n Cluster initiatives, even well-running ones, areonly one aspect in a broad range o actors thatinfuence cluster development. So ar, evaluationailed when they tried to isolate the impact oeconomic policy and evaluation has always beenbased on plausibility and indi-rect indicators.

The consequence is not that cluster policy hasno chance, but that we have to be careul when wediscuss the expected results.

Map 1: Biotech Regions in Germany

BMBF 2005

hAndlinG dilEmmAs inClustEr poliCy: tAsks AndillustrAtionsThis chapter aims to discuss the way policy handles

the dilemmas that have been discussed in chapterthree. The rst dilemma is to select promising clus-ters, which means the question o who and what.Discussing this aspect we have to keep in mind thatclusters are selective by denition in at least twoways.

First, in regional terms, clusters base on con-centration. The higher the concentration o relatedvariety (Boschma/Frenken 2005) o economic ac-tivities (including research, education, qualica-tion and so on), the more dense the interaction (in-ternal as well as external) and higher the chanceo dynamic cluster eects. Thereore, cluster policy

in ideal terms has to ocus on a smallgroup o promising clusters. To illus-trate this dilemma, the case o the Ger-man biotechnology cluster is o inter-est. The idea was great. Germany was alate-comer in biotechnology. It was lag-ging behind in the 1970s and 1980s,but in the late 1990ies the situation got

better. There are dierent reasons orthe rising dynamic. It had to do withthe rising presence o international ven-ture capital companies in Germany, andwith innovation in measurement andanalytic meth-ods and equipment. Fur-ther, all activities o sector ormationspeed up: proessions in education bynew curricula, dierent airs, buildingo an business association (biotechnol-ogy had been em-bedded in the chemi-cal companies association beore) andso on.

The most cited reason or take-o isthe success o the bio-regio-competitivecall that was initi-ated and organizedby the German Ministry o Researchand Technology in the second hal o the1990s. This competitive call is o specialinterest in our context because it aimed




BrandenburgNorth-Rhine-Westphalia

Bavaria

Biotechnology Biotechnology Biotechnology

Aerospace Aerospace

Media/IT ITC ITC

Media

Creativeindustries

Automotive Automotive Automotive

Energy

economy

Energy economy

Oil/Bio energy Energy research

Geo Science

Wood industry

Plastics Plastics

Logistics Logistics Logistics

Optic Nano-Micro Nano

Paper industry

Railway Railway

Food industries Food Industries Food Industries

Tourism

EnvironmentalTechnologies



Health Care Medical Technologies

Medical Research

Mechanicalengineering

Mechatronic/Robotic/ Production Systems

Chemistry Chemistry

Financial services

at strength-ening the most innovative and best or-ganized biotech-regions. Regions had been asked towork out cooperative development strategies includ-ing crucial issues like venture capital, public ap-provals, university-company ties or specialized in-

rastructure. Due to the aims o the competitive call,the three leading bio-technology regions (Rhineland,Mittlerer Neckar, and Munich) were pointed out aswinners and one East-German Region (Jena) wasput in as a support region be-cause o its specialcompetence in biotech equipment.

Thus ar, the story looked good i we think aboutcluster building. Unortunately, soon it became ob-

vious that the losers did not accept the result. Upto twenty regions were involved in the com-petitivecall and most o them had the eeling that they dida good job, has high potential, and they build up ashared vision. They tried to nd new ways to get

unded, and because Germany is a strong ederalpolitical system, most o them applied or und-ing by their ederal state govern-ment. The ederalstates programs, additional programs by the Ger-man Ministry o Research and Technology and sev-eral ways o European unding were available andhelped nearly all regions to stay in the game.

At the end o the day, there are around 30 biore-gions in Germany that claim to be or to becomebiotech clusters (see map 1).

Germany has nearly 600 biotech companies

and each biotech region counts or 20 companieson an average. A lot o these regions are missinglocal venture capital unds and some o them haveno laboratory inrastructure. The dilemma is thatthe process was highly successul in activating lo-cal actors, but the local actors became so strong inlobbying or public unding that at the end, publicresources became more disperse and were not con-centrated on the most promising re-gions.

Secondly, in unctional or sector terms, one key

result o Porter’s (1990) study is that no countryhas the resources to establish globally successulclusters in a broad range o sectors. Concentra-tion or ocusing is needed. The problem is thatthere is high insecurity about industrial sectorsthat will be the driving orces in the uture. Inthis case again, the German example illustratesthat the practice is more driven by the ear tomiss an interesting chance than by selective deci-sion. Figure 3 summarizes the cluster activitieso three German ederal states—Bavaria, North-

Rhine-Westphalia and Brandenburg. We can seethat despite some dierences in wording and lo-cal spe-cializations, the elds o cluster policy arevery similar.

Maybe the approach in Brandenburg is moreoriented towards productive industries, the North-Rhine-Westphalian and the Bavarian one have astronger ocus on new technologies, but the di-er-ences are not really strong. Policy makers in charge

Fig 3: Fields o Cluster Policy in Three GermanFederal States




o cluster policy are aware o this problem withoutany doubt. In all three countries, there is a broadconsensus that 15 or 18 clusters are too much, butbecause it is dicult to select without knowing theuture the key strategy is to wait or evaluation. It

is too early to discuss the results because the evalu-ations are in a very emerging state, but whateverthe result is the dilemma remains—in all sectorscluster policy intends to acti-vate sel organizationand when you have done this it is very hard or poli-

ticians to stop the und-ing even when the resultsare not the expected ones.

As pointed out, there is need o coordination odierent elds o policy (this part bases on (c. orthis chapter Muth/Reheld 2007, Reheld/Terstiep

2007, Terstriep (2006)). There is a long hope thatregionalization will bring out more solutions andcoordinated processes. The problem is that clus-ter policy on a central level is oten embedded intraditional philosophies and contexts. In most Ger-man ederal states, the roots o cluster policy arein the eld o regional policy. The consequence wasthat clusters got unding in regions that were lag-ging behind in average eco-nomic perormance or

Fig 4: Cluster Policy and Cluster Initiatives Compared

Brandenburg

NRW

Czech Rep.

Austria

BavariaFinland

France

Switzerland

FundingBottom-up

dezentral

Bottom-up

Top-down

zentral

S t r a t e g y

Top-down

in regions that aced heavy sector restructuring.This means that those regions had weak potentialsin clustering. At the same time, and without anycoordination, the central state ocused strongly ontechnology-driven clusters. With the shit in Eu-

ropean structural policy towards Lisbon strategy,the ramework changed and today cluster policybecomes linked with technology policy.

In contrast, in Finland, cluster policy had astrong start in the context o Finnish technology

and innovation policy. Today, there is a shit tostrategy centers that are driven by the most im-portant Finnish industrial value chains. In France,we nd a combination o traditional planning ap-proaches rooted in the 1950s, in ongoing decen-

tralization strategies and in a strong technologydriven ocus. In Switzerland, cluster initiativesare bottom-up driven in most cases and centralpolicy is in its emerging phase. In the German ed-eral state Brandenburg, cluster policy was part othe regional policy but the instruments (incentiveson the one hand, network projects on the other)started in dierent contexts and now they have theproblem o coordination. In the Czech Republic,




you nd the combination o central- and state-driven planning strategies and market-driven in-struments.

These are only ew examples. They illustratethat cluster policy is oten embedded in national

traditions and the related elds o economic policy.It shows that it is ar rom coordinating di-erentelds o economic policy, and labor market policyhas very ew links with cluster policy (maybe Swe-den is a case where this coordination with labormarket policy works).

Third, and this has links with the argumentsabove, there is a dilemma between bottom-up andtop-down approaches, in other words, betweencluster policy and cluster initiatives. Figure 4shows the position o cluster policy in selected

countries resp. ederal states along the top-downbottom-up axis “unding” and “strategy”. Morecluster unding and strategy are bottom-up drivenand cluster policy is only supporting, but moststrategies in cluster policy have a strong top-downimpact and they aim at activating sel-organiza-tion. The problem comes to lie when new activi-ties in cluster policy meets long-standing bottom-up initiatives. This is the case in most Germanederal states, in certain French regions and in

some parts o the Czech Republic. The dilemma isthat i policy wants to initiate sel-organization, ithas to risk that the priorities o the societal actorsare dierent rom the central state priorities.

ClustEr poliCy As multi-lEvEl poliCy: fiElds forEXpErimEnts And lEArninGCluster policy is a multilevel policy. Such a multi-level policy is characterized by the ollowing ea-tures (c. contributions in Tömmel (ed.) 2007, Benzet al. (ed.) 2007):n Complex institutional and actor patternsn Boarders between the levels and the actors arenot clearly dened, so responsibilities are not al-ways clearly attributedn No actor is able to achieve the desired goal onhis own, actors are interdependentn Aim and implementation are acted out in an in-

terplay between public and private actors, and aremainly about sel-regulation and not about classi-cal state interventionn Which is why steering techniques that do (andcan) not all back on authoritative instruments can

be ound.I we ollow the political science discussion aboutnew patterns o governance, especially in the Europe-an Union, there seems to be reasons or doubt aboutthe success o cluster policy, since it is assumed thatmultilevel policy only works i the “shadow o hier-archy” is given in the back-ground, i.e., i the statehas the possibility to all back to other authoritativeinstruments i sel-organization does not work.

However, this is precisely what is not possiblewith cluster policy, as without the active (and in-

creasingly also nancial) participation o the ad-dressees, such a policy is not realistic. In orderto become aware o the demands made on clusterpolicy, it is useul to keep in mind the key task.

Cluster policy wants to encourage sel-organi-zation, usually through an initial unding with di-gressive public participation. At the same time,cluster policy aims towards the provision o col-lec-tive goods that have not been provided by privateactors so ar (i this was not the case, cluster policy

would not be necessary). Consequently, it is notsolely about the activation o potentials that havebeen latent so ar, but also about a change in cor-porate behavior. It is no longer the lonesome ridercompany that is requested but the socially respon-sible and economically net-worked entrepreneur. Itshould be noted that this is a development within aspecic policy eld, but that such a collective ad-justment o corporate action opposes diametricallycompetition law, which acts on the assumption oisolated actors only mediated through the market

and puts di-rect communication under the suspi-cion o not permissible agreements.

The dilemmas cluster policy has to balance arediverse. Thereore, cluster policy can only be suc-cessul, i it proves to be adaptive with regard toits strategies and instruments. Elements o such anadaptive process can in act be seen. There seemsto be a division o labor within the Euro-pean mul-tilevel system.




On the European level, the eld or experimentscan be ound. In the mentioned program areas(PAXIS, INNOVA and PRO INNO, KIS), experi-ences rom established cluster management activi-ties are concentrated, new tools and instruments

are tested, standards or the proessionali-zation ocluster management are elaborated and, last butnot least, the inormation basis or a comparabilityand evaluation o cluster development is built.

The multiplicators are consultancies integratedinto the activities, networks o cluster managers,institutions o advanced training and big interna-tional conerences. Even i the landscape o clus-termanagement in Europe is still very heterogeneous,certain standards with regard to proes-sionalismhave been accepted that cannot be ignored in thelong run.

Cluster policy o central states, respectively oederal states in ederalist states, still has to ndits own place. I we take key categories o the gov-

ernance discussion (steering through market, hier-archy and networks) as a point o reerence, almostall possible elds are covered in this triangle (g.5). The proceedings o states (respectively ederalstates) with extreme restructuring prob-lems (e.g.in Eastern and Central European states or Bran-denburg) or o states with a strong planning tradi-tion like France are infuenced the most by classicalsteering. Here, the challenge is to line the central

Fig 5: Modes o Governance in Cluster Policy

© 2007 IAT – own illustration

Network

Hierarchy

centralplanningl

award activation

self-organization

bundling

formation

corporatism

Market

implementation

„venture capital“„

state impulses with the initiation o societal sel-organization.

At the other end, and this is oten disregarded,there are activities o regional sel-organization ocompanies that do not depend on public unding, o-

ten don’t even want to because they want to achievetheir goals independent rom political requirementsand public attention.

In between, there are all sorts o hybridorms—initial nancing aimed at a societal sel-organization that later will be sel-supportingor the promotion o extraordinary cluster proj-ects won through promotional competition—stillclosely linked to markets and networks. The bun-dling or ormation o national resources throughan intensive technological co-operation or a co-

operation comparable to classical corporatismbetween state, unions and companies are linkedcloser to public interests. It is precisely these ac-tivities that stand to ace the challenge, not tointerconnect too closely but to stay open to theoutside and thereore to new impulses.

In a certain way, such dierent models will al-ways be ound, depending on the economic startingposition, the readiness o social actors to partici-pate in the provision o collective goods or na-tional

political-administrative steering philosophies andregulation systems. However, all these dierent ap-proaches have in something in common—startingrom a certain point in time they all rely on theactive participation o those addressees. This is es-pecially true or the participation o companies.

Regardless o the starting point, cluster policywill have to solve the distribution problems men-tioned beore in a dierent way because clearorecasts o uture economic developments are notpossible. The most promising way at the moment

seems to be to orm cluster policy in accor-dancewith the promotion o venture capital.n At rst, it is reasonable to promote broadly, alsokeeping in mind that not all promoted pro-jects willbe successul.n Next, it is important to connect the promotionto clearly dened (nancial as well as material)goals and to organize a orm o support in order toachieve those goals.




n Finally, at a certain point in time it is to be de-cided where projects can now run by themselvesand have the desired societal use, where urthersupport is needed because the achievement o thedesired goals take longer than oreseen and where

public activities have to be termi-nated.I this reerence to sel-organization is miss-ing, the bottom-up developed cluster managementactivities and central state activities will confict.In the worst case, not only public resources arewasted because o a lack o eectiveness, but theautonomous processes o cluster development arealso thwarted, i public resources are distributedwidely as the above discussed example o Germanbiotechnology shows.

strEnGths And WEAknEss-Es of ClustEr poliCy in Eu-ropEThe European Union bases on the idea to combineregional diversity and coherence in a ruitul anddynamic way. The cluster approach oers a strongstrategic rame to bring this idea to lie. Due toregional diversity, in structural as well as culturalterms, clusters and cluster initiatives are very dis-

tinct rom region to region, rom value chain tovalue chain. Facing this situation, cluster policy canbe studied regarding the way it balances dilemmas.First o all, on one hand, the di-lemma allows re-gional distinctive ways o cluster development andcluster initiatives; and on the other, the dilemmamakes it possible to work out general quality stan-dards and success criteria. Without this balance, thecluster approach becomes more uzzy and runs therisk o losing the potential o cluster development.

The problem is that cluster policy needs newconcepts and strategies and that there is a highinse-curity about the results that can be expectedin a realistic way. So ar, cluster policy is highlyex-perimental and needs strong learning process-es. This is, by no means, sel-evident because, aspointed out, cluster policy always runs the risk obecoming embedded in traditional paths o singleelds o economic policy. Nevertheless, there is agood chance o policy innovation or three reasons:

n Cluster policy needs to combine dierent modeso governance and in the course o im-plementa-tion; there is the chance to refect promising waysand to adapt policy.n Cluster policy is a multi level policy, and in best

case the level work in complementary way.n Cluster policy is very dierent on the local orregional level and cluster managers need to act onan international level (otherwise they risk to causelock-in eects), as this oers the opportunity toshare experiences and to learn rom each other.

This cannot solve all the dilemmas mentionedin the chapters above. Is it realistic to expect thatcluster policy in strong regions is so successul thatall regions benet by spill-over eects in the longrun? Do weak regions have a realistic chance to

strengthen their economic perormance when theyocus on cluster, especially in those value chainswith a long standing spatial division o labor? Isthere a realistic chance to overcome the traditionalboundaries o administrative insti-tutions? What isneeded to avoid a destructive clash between bot-tom-up and top-down activities?

The key idea behind this paper is that the clus-ter approach has a high potential to strengtheneconomic perormance in regions as well as in

Europe. The danger is that the cluster approachbecomes diused and that cluster policy becomesmore vague and, in consequence, the potential othe cluster approach becomes wasted.

Focusing on cluster policy, it is urgent to discussour challenges.

First, i it is true that clusters are selective andthat it makes no sense to try to develop clustersin each region, we need urther strategic conceptsor those regions that have no promising startingpoints to develop clusters. A cluster is one way to

strengthen the innovative perormance o re-gions,but we need dierent ways to work out “innovativespaces” (Reheld 2006). This includes the questionin which way these regions can make good use okey ideas o the cluster approach, like networking,linking local-global chains, improving competence,organizing collective learn process and so on.

Second, we need a deeper understanding o howcluster policy is positioned in the trends o global




change. A lot o uture trends are highly decentral-ized. Sustainable strategies or new health conceptsare basic challenges to improve quality o lie in allregions and it is not helpul to dis-cuss these chal-lenges rom a cluster point o view. No region is

autonomous in a global world and access to globalknowledge, and the competence to make good useo it, is crucial or the uture o all regions again.Global migration brings out more geographical fuidor borderless spaces and innovative, as well as, -nancial fows transer geographically-xed regions.Clusters are nods in all trends or they have the po-tential to work as nods like this and cluster policyhas to avoid to x on a given geographical level.

Third, we need evaluation concepts that areaware o the complex aspects o cluster policy. In

certain terms it will be very successul when clusterpolicy contributes to reorganize the institu-tionalsetting o economic policy, when it succeeds incombing private activities and public re-sources orwhen it helps to make institutions more fexible. Soar, evaluation concepts are ocus-ing on indicators,hard ones as well as weak ones (see the exampleson the homepage o Scottish Enterprise), but, inorder to evaluate cluster policy, we need an under-standing o the underlying intervention concept and

the related strategy.Fourth, doing this we cannot expect perect so-lutions, but dierent ways to balance dilemmas.Good practice always is good practice in a speciccontext o space and time. Clusters develop in anevolutionary way and cluster policy has to do thesame thing. Cluster policy in this way, has to keepin mind that it is public policy and thereore, it hasto stand or more than the economic evolutionaryway. It has to ocus on public goods and benets,and when it does so successully, there is a chance

or a ruitul co-evaluation between public and pri-vate interests.

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from industriAl ClustErs to GlobAl knoWlEdGE hubs

Reve, Torger 1

Knowledge-intensive industries are increasingly lo-cated in global knowledge hubs, which are charac-terized by a high density o interrelated knowledgerms operating globally. Examples include Bostonin lie sciences, Silicon Valley in inormation andcommunication technology, and Houston in oil andgas. Typically, such global knowledge hubs emergerom well-reputed universities and private researchlabs, but they also include a wide array o com-mercial actors and a competent venture capitalmarket. Successul global knowledge hubs are ableto attract knowledge unctions rom major multi-nationals in the industry. Together with universi-ties and their related research labs this creates anadvanced, specialized job market attracting talentand knowledge workers on a global scale.

Global knowledge hubs emerge rom industrialclusters or geographical agglomerations o relatedrms, thus such knowledge hubs are highly pathdependent, not easily lending themselves to indus-trial development policies. While industrial clus-ters typically center around large manuacturingor service rms and their network o suppliers,knowledge hubs are more diverse in their compo-sition, placing universities and R&D institutionsat the center. As the density and interactions o

1 BI Norwegian School o Management, Norway

ABSTRACT

knowledge organizations increase, the result is vi-brant innovation competition and high commercial-ization o innovation, given the active presence ocompetent venture capitalists and investors.

Some o these knowledge hubs take global lead-ership positions, such as Boston in lie sciences andSilicon Valley in inormation technology, but theyare constantly challenged by other knowledge hubssuch as San Francisco and San Diego in biotech,and Bangalore and Hyderabad in sotware and ITservices. Despite the prevalence o modern commu-nication technology, geographical proximity mat-ters even in high-tech industries.

In the current paper, the global knowledge hubconcept is extended to the global maritime indus-try, as illustrated by the Norwegian and Singapor-

ean maritime clusters, and policy measures areproposed to transorm these maritime clusters toglobal maritime knowledge hubs or super clusters.

The global knowledge hub concept is presentedas a new industrial paradigm with important im-plications or knowledge-based industrial develop-ment and industrial policy making.

Keywords: Knowledge hub, Maritime clusters, Nor-way, Singapore, Knowledge-based industries




introduCtionIn classical writings o microeconomics and orga-nization theory, the rm is viewed as an autono-mous unit acing actor and product markets. Ba-sically, the rm is conceptualized as a production

unction or an input-output system transormingraw materials and other input actors into nishedproducts and services to be sold to customers in acompetitive market. The rm is basically seen as amanuacturing unit, represented by a typical valuechain—rom inbound logistics through operations,outbound logistics, marketing and sales and ater-sales service (Porter 1985).

In the writings on industrial marketing, dis-tribution and logistics, the rm is seen to be parto an industrial network, ocusing on supplier anddistributor relationships, and the eld o inter-or-ganizational research came to power (Stern & Reve1980, Håkansson & Snehota 1995). The sameholds true in strategy where research on strategicalliances has been strong or many years (Lunnan& Haugland 2008).

Rather than studying inter-organizational rela-tions in terms o buyer-seller dyads (Stern & Reve1980) or simple industrial networks (Håkansson& Snehota 1995), many researchers in the elds

o economic geography (Asheim 2000) and indus-trial development, most notably Proessor MichaelPorter (1990) at Harvard Business School, havestudied industrial agglomerations at given loca-tions. The main terms used are industrial districtsor industrial clusters, which have been dened as“a geographically proximate group o intercon-nected companies, suppliers, service providers andassociated institutions in a particular eld, linkedby externalities o various kinds,” (Porter 2003).

Let us take the auto industry as an example andsee how it can be studied using various industriallenses.

In the rst paradigm, business as manuacturing,the auto industry is studied by analyzing major in-dustrial actors such as GM, VW or Toyota as acto-ries. The roots go back to scientic management andFordism. The analytical model applied is typically avalue chain (Stabell & Fjeldstad 1998), and the goalis to optimize productivity and value creation.

In the second paradigm, business as industrialclusters, the auto industry is studied as a networko car manuacturers, auto part suppliers, serviceproviders and car dealers, particularly as the in-dustry centers rom various key locations such as

Detroit, Stuttgart or Osaka. The major manuac-turing rms are placed at the core o the indus-trial cluster, while the other industrial actors arereerred to as related and supporting rms. Thisalso included universities and other knowledge pro-viders. The model has been made world amous byMichael Porter (1990), and empirical studies areprevalent.

Industrial clusters represent superior locationsdue to lower transaction costs o operations, and theexistence o knowledge externalities and network

eects. Knowledge externalities arise rom sharingo knowledge and rom utilization o a common,specialized inrastructure. Thus, industrial clustersnot only require a critical mass o rms at all levelso the value chain, but there also have to be closeinteractions between the industrial actors withinthe cluster. The result is accelerated learning andhigher rates o innovation and commercialization,and there seems to be clear scale eects (Krugman1991). Thus, major industrial clusters tend to be

growing, while minor industrial clusters tend to bereduced as rms consolidate and co-locate.On a global scale, a hierarchy o industrial

clusters in any particular industry can typically beobserved. The rst tier consists o a ew key indus-trial locations, like what we observe in the auto-mobile industry; with Japan, Germany and UnitedStates being the three major auto industry loca-tions. These are oten reerred to as global clusters.Global clusters have the highest concentration orms and control the ull range o industrial knowl-

edge required within the given industry. This is alsowhere major R&D and new product developmenttakes place.

The second tier clusters can be ound in runner-up auto manuacturing countries like Korea, Chinaand India. These are new industrial clusters or re-gional clusters challenging the existing global clus-ters. Many previously strong regional actors in theauto industry (e.g., Skoda, Saab and Volvo) were




rst taken over by the major global players (e.g.,VW, GM and Ford). Recently, new auto actors romemerging economies are taking over old car manu-acturers, e.g., Tata taking over Jaguar and Volvogetting new Chinese owners.

The third tier o automobile clusters has a con-centration o more specialized suppliers and ser-vice providers to the auto industry, such as the autoparts manuacturers o many European and Asiancountries. These specialized clusters are builtaround more specialized industrial knowledge, andthe supplier clusters are highly dependent on theirglobal customers. The vertical inter-organizationalrelations are governed by strong contractual ar-rangements tying these clusters to the main actorsin the global clusters.

The ourth tier o automobile clusters simplyconsists o standalone auto assembly or auto partsplants located in countries with avorable actorconditions, such as Brazil, Mexico, Poland andThailand. We may reer to these clusters as trans-plant clusters. In transplant clusters, industrialknowledge generation is limited, and transplantclusters tend to be local in nature. Most o the or-eign direct investments in emerging economies areo this kind.

Finally, there are raw material producers thatcould be anywhere where actor conditions are a-vorable. Sometimes, these producers orm com-modity clusters, as we see in many countries thatare strong in natural resource industries.

In this paper, I will study the industrial clusterstructure in knowledge-intensive industries. Exam-ples o such industries are lie sciences, biotech, in-ormation and communication technology, althoughmost industries today are highly knowledge-inten-sive in some sense or another. Thus, the argument

in this paper is that studies o knowledge-intensiveindustries are transerable to many other indus-tries, such as the maritime industry, which is myempirical ocus in the second part o the article.

Finally, in applying these concepts to the mari-time industry, I will introduce the concept o globalknowledge hubs. Thus, the third industrial para-digm discussed is industries as global knowledgehubs. This concept has substantial implications or

industrial development and suggests more radicalknowledge-based industrial policies.

thE EmErGEnCE of knoWl-EdGE hubsSome o the most amous industrial clusters can beound in knowledge-intensive industries. I we studythe development o Silicon Valley (Saxenian 1994),it started with the development o the semi-conduc-tor industry and computer manuacturing. Keyactors at this stage were companies like Fairchildand Intel in semi-conductors, and Hewlett Packardand Apple in computers. Over time, the dynamicschanged into communication technology, producingsuch key players as Cisco in network technology,

and Yahoo and Google in internet search technol-ogy. Behind the rapid development o the IT indus-try in Silicon Valley was leading edge research anddevelopment, most notable at Stanord Universityand related R&D acilities.

What characterized the Silicon Valley IT clus-ter was the high amount o entrepreneurship re-sulting in thousands o startup rms within anypossible knowledge niche o the industry. Thetransition o startups into commercial successulrms was ueled by a dynamic venture capital in-dustry, providing competent capital to new entre-preneurs. Venture capitalists speeded up the selec-tion processes, both in terms o killing ventureswith low commercial potential and by providingample unding to ventures with high growth com-mercial potential. Entrepreneurs, who were otenyoung university graduates or ormer employeeso some o the major IT rms in the Valley, hadthe opportunities to transorm their knowledge in-vestments into stocks or cash, and many became

serial entrepreneurs, setting up new IT, sotwareor service companies in many locations around theworld. The Bangalore IT cluster in India is a wellknown example, and a company such as Inosyshas its roots in Silicon Valley.

Empirical studies o knowledge-intensive clus-ters like Silicon Valley reveal dense networks oknowledge linkages and rapid transer o knowl-edge workers among the key actors in the cluster




(Saxenian 1994, Stuart 2000). The major uni-versities (Stanord, Berkeley and San Jose) andtheir associated research labs became major link-ing pins in the knowledge network. The importantrole o public research organizations should be

noted (Whittington et al., 2008). New technologyand new commercial concepts came out o closecooperation between universities, labs and majorIT companies that were all located close to eachother. The waterholes in the Silicon Valley becameamous or rapid exchange o new ideas. The driv-ing orce was innovation competition, and the re-wards or commercial success were substantial. Itall peaked during the dot.com era, but the SiliconValley still kept up its reputation as one o theglobal new venture hubs, not only in inormation

and communication technology, but in many newknowledge industries, including lie sciences andbiotech that we now turn to.

An even more amazing story o the rapid growtho a new knowledge-intensive industry is the emer-gence o the Boston lie science industry. The pat-tern o development in Boston is even clearer thanin the Silicon Valley case, and recently, excellentresearch data has been presented or the develop-ment o the Boston and San Francisco lie science

industries (Whittington et al. 2008).The new lie science industry developed romscientic advances in biotechnology, and the de-velopment took place at the three major researchuniversities in Boston: MIT, Harvard and BostonUniversity with their associated university hospi-tals. As these universities were international lead-ers in lie sciences, educating the most capable,new knowledge workers, doctors and scientists,major commercial actors in lie science, includingmajor biotech and pharmaceutical companies rom

around the world, set up their labs and test acili-ties in the Boston area. The idea was to be close tothe rapid scientic development and to be amongthe early adaptors o new technologies into com-mercial products and services. At the same time,many entrepreneurs trained in lie sciences sawopportunities or themselves, and a large wave obiotech startups emerged. Again, the driver wasthe venture capital industry. This industry does not

have its main hub in New York like the rest o theUS nancial industry, and is more concentrated incities like San Francisco, Boston and San Diego.

These cities also happen to have the highest con-centration o rms in the new knowledge-intensive

industries, such as lie sciences. Recently, GenomeTechnology (2008) placed Boston/Cambridge, MAway ahead o all other biotech locations in the world,ollowed by the San Francisco Bay area and San Di-ego.

The recent empirical study o the developmento the Boston and San Francisco lie science in-dustries, 1988-1999 reerred to above, not onlydemonstrates the importance o critical mass oco-located knowledge companies, but it shows theimportance o close linkages between the same

knowledge actors (Whittington et al 2008). At theearly stage o development o the lie science clus-ter in Boston, 1988, 114 organizations had 201observed ormal ties, while in the more maturestage o cluster development, 1999, 740 organi-zations had 1559 observed ormal ties. Formalties include research partnerships, licensing agree-ments, nancial investments and manuacturingand marketing contracts. O the 740 organizations,212 were dedicated biotechnology rms, 96 were

public research organizations (which also includeuniversities, university research hospitals and in-dependent research institutes), and 240 were capi-tal venture rms. Public R&D institutions play apivotal role in knowledge generation, while venturecapital rms play a similar pivotal role in venturecommercialization. In sum, these actors not onlyorm a strong industrial cluster, they orm a globalknowledge hub.

What characterizes a global knowledge hubis a strong core o public research organizations

(PROs), mainly universities and independent re-search institutes, interacting closely with the R&Dunits o major commercial actors in the industry.In the biotech industry, this means the labs and de-velopment units o dedicated biotechnology rms(DBFs) and the many pharmaceutical, chemicaland healthcare companies. When a knowledgehub reaches a certain critical mass, we see thatmost o the global actors in the industry establish




centers o excellence in the same geographical lo-cation. This is done to be an integral part o theadvanced learning and innovation milieu, takingadvantage o learning by interaction and diusiono knowledge (Sorensen & Fleming 2004), and o

learning by hiring (Song, Almeida & Wu 2003). Asthe knowledge hub also contains major world-classuniversities oering specialized graduate programsand high quality doctoral programs, young talentsrom around the world seek the same knowledgehubs. This again creates a dynamic, high-talent la-bor market that gives rise to network externalitiesthat benet all the actors in the hub.

The second layer o rms in a global knowledgehub consists o a competent venture capital indus-try that increases commercialization opportunities

by unding ideas that come out o the universitiesand labs at the same location. The venture capitalindustry covers all stages o the innovation and en-trepreneurship process—rom early stage businessangles and seed capital rms, to hard core venturecapital rms going in at various stages o develop-ment beore the most successul ventures reach theIPO stage and are quoted on the stock exchange.There is, o course, extensive takeover activity tak-ing place during the venturing process, where large

companies take over promising startups or spinos.In both cases, new ideas are turned into commer-cial success, giving entrepreneurs strong economicincentives to continue to innovate. The heroes aretopnotch scientists and serial entrepreneurs thatbecome rich in the process.

The third layer in global knowledge hubs con-sists o the large array o technological and com-mercial actors that turn science and technologyinto products and services. This is where largenumbers o small and medium-sized rms in the

knowledge industry grow up, and this is wherelarge multinationals, like Genentech and Novartis,try to play dominating roles. Mergers and acquisi-tions are requent and sometimes major in nature,e.g., Japanese Takeda Pharmaceuticals taking overCambridge-based Millennium Pharmaceuticals in2007 or $8.8 billion.

As in regular industrial clusters, there are numer-ous suppliers, intermediaries and service providers

that have an active supporting role in the knowledgehub. Actually, such rms, in particular, brokers andconsultants, are very important in knowledge diu-sion. This is the same network mechanism that is vi-tal in open innovation (Chesbrough 2003)—creating

social capital that acilitates innovation and com-mercialization. Global knowledge hubs are dierentrom research hubs where universities and R&D labsexist in splendid isolation rom business and venturecapital demands. In knowledge hubs, investors con-stantly chase ideas and vice versa.

Within global knowledge hubs, there is a smallworld o scientists and commercial actors (Fleminget al 2007) that are world experts within their ar-eas o specialization. Small worlds are character-ized by intensive inormation exchange and shared

values, reducing communication barriers to almostzero, although the membership o small worlds isoten culturally diverse. The two overriding valuesare the drive to succeed scientically and the driveto succeed commercially.

Another important eature o global knowledgehubs is that they typically consist o several smallworlds that are in intense internal rivalry. The scien-tic rivalry between Harvard and MIT is well known,and in the biotech case, key biotech rms tend to be-

long to either one o the two spheres. Under suchcompetitive circumstances, there is no time to rest onyour laurels, and innovation competition is erce.

What we nd in studying knowledge hubs, isthat governmental agencies may also play an im-portant role, partly in terms o unding variousR&D initiatives and also by setting industry stan-dards and new regulatory regimes. In the Bostonbiotech hub, 24 dierent governmental agencieshad located there in 1999, and they were all ac-tive members o the knowledge hub. Thus, the role

o private-public partnerships in innovation milieusseems to be a major driver, although the roles maydier across nations.

The global knowledge hub o the biotech indus-try in Boston is beautiully illustrated by clustermap in colors developed by Whittington (2007)in her doctoral research. Here, the distributiono the main components in Boston biotech inven-tions, 1976–2002, is illustrated by mapping the




ormal inter-organizational ties between universi-ties (21%), biotech rms (38%), public researchorganizations (26%) and cross-sector (16%). Thenumber o actors and their ormal ties is incrediblyhigh. In addition, there are many inormal linkages

and networks that are hard to capture in this typeo quantitative network research.

In order to capture the structure o a globalknowledge hub like the Boston lie science clus-ter, I would place the universities and the publicresearch institutions at the core o the hub. In theBoston biotech case, you may well put the our“Research One” universities in Boston in the mid-dle (Harvard, MIT , Boston and Tuts), along withresearch hospitals like Massachusetts General and

research institutes like Dana Farber Cancer Centerand Whitehead Institute o Biomedical Research.Its geographical center is at Kendall Square, Cam-bridge, Mass which is also the home o MIT. Re-cently, major international pharmaceutical rmslike Pzer and Novartis have located their R&Dacilities at Kendall Square.

The knowledge plus orientation o American re-search universities (Mowery et al. 2004) includeearly movement o university graduates into com-

mercial rms, consulting relationships betweenaculty and companies, licensing o university tech-nologies, industry gits supporting university re-search and student training, aculty entrepreneur-ship ounding new companies, aculty involvement

on scientic advisory boards, and ormal contrac-tual partnerships to pursue joint R&D, product orprototype development and clinical tests.

I we look at the innovation output in terms opatents in the biotech cluster in Boston, two-thirdso the 900 biotech patents registered in Bostonbetween 1976 and 1998 came rom a university,while one-thirds came orm biotech companies. Itis air to say that there are seamless relationshipsbetween universities and private business. The re-

sult is that much o published academic researchnow comes out o the R&D units o corporations,while many new commercial ventures come outo universities. This orms the core o the globalknowledge hubs.

What makes the core o R&D and innovation sosuccessul, in global knowledge hubs like Boston, isthe network o venture capital rms and investorssurrounding the universities and public researchinstitutions. This is a substantial economic orce

Distribution of Scientific Clusters

Main Component, Boston

Inventors 1976-2002

Color Legend

Reds: University (21%)All other

colors: Biotech (38%)Light

Grey: PRO (26%)Black: Cross-

sector (16%)

Fig 1: Boston Biotech Knowledge Hub Linkages




unding the majority o the commercialization ac-tivity in the knowledge hub, and oering powerulincentives to those who succeed by taking an in-vention or innovation into the commercial stages.Venture capital markets discount uture earnings

into the present, thus oering venture capital tostartup rms whose earnings are uncertain utureprospects. Only major corporations are able to dothe same, e.g., by corporate unding o internalventures. The role o government money is limited,except in the unding o basic research and in largedeense contracts.

The next layer o actors in global knowledgehubs is the whole array o commercial rms,covering the various stages o development, test-ing, manuacturing, marketing and services that

constitute the majority o value creation in mostindustries. In knowledge-intensive industries, therole o manuacturing is much more limited than inmore traditional industries, while product develop-ment, marketing and service represent the substan-

tial part o value creation. The ocus is on R&D,commercialization and marketing. The analyticalmodel is one o value shops or value networks (Sta-bell & Fjeldstad 1998). Finally, there are numeroussuppliers and service providers serving the knowl-

edge rms.The structure o the global knowledge hub in thebiotech industry in Boston can be illustrated as inFigure 2.

At the core o the global knowledge hub are thePROs such as universities and private R&D institu-tions. These interact closely with venture capitaland other competent investors that know the indus-try well.

The knowledge-capital core is surrounded by anumber o DBFs that breed on the ideas developed

at the universities, working closely not only withPROs, but also with large multinationals rom thepharmaceutical and chemical industries (PHAR).

The development o an ecient biotech knowl-edge hub also requires well unctioning healthcareorganizations (HCO), which in this sector repre-sents both a resource and an important market.The role o university research hospitals is critical.Finally, there is a large abric o specialized andsupporting knowledge services (SSS) serving and

developing the knowledge hub. This is the layertypically creating most jobs.Network externalities can also be better real-

ized i eective institutions or collaboration (IFCs)exist. These organizations also have a brandingrole or the global knowledge hub. Finally, the roleo new standards and eective government regula-tions (REG) is critical in turning emerging indus-tries into growth industries.

I we compare the knowledge hub concept withtraditional industrial cluster maps, we can note

the inversion rom having the major manuactur-ing companies at the core, to having the researchand innovation at the core. The basic premise isthat new business emerges rom knowledge andmarket needs. This also changes the role o capitaland investors whose role is to match the two. Theknowledge dynamics primarily come rom R&Dand small knowledge based rms rather than rommanuacturing and large multinationals. Universi-

LegendPRO Public Research OrganizationsVC Venture CapitalDBF Dedicated Biotech FirmsPHAR Pharmaceutical IndustryHCO Health Care OrganizationsSSS Specialized Supporting

ServicesIFC Institutions for CollaborationREG Regulatory Regime

REG

IFCSSS

HCO

PHAR

DBF

VC

PRO

Fig 2: Boston Biotech Global Knowledge Hub

Structure




ties and R&D institutes become industrial actorsthat are sometimes even more important than ma-jor business corporations. Thus, close knowledgeinteractions between academia and private busi-ness are vital in any knowledge hub.

GlobAl mAritimE knoWl-EdGE hubsThe maritime industry has been extensively studiedin industrial cluster terms (Reve et al. 1992, 2001,Jakobsen 2003, 2004). On the one hand, the mari-time industry, such as ship building and shipping,represents relative traditional industries, not typi-cally thought o as knowledge-intensive industries.On the other hand, a large part o the maritime in-dustry runs purely on the knowledge-serving globaltransportation markets. Shipping has no other re-source base than the people owning and operatingthe ships. Ship building in high-cost countries canonly survive i it is able to innovate technologically.The remaining parts o the maritime cluster aretechnical and commercial services, rom the mostadvanced knowledge services to simple operationalsupport.

The most complete maritime clusters can be

ound in Norway, Japan and China, but Greece(shipping), Korea (ship building) and Singapore(port) are also strong maritime clusters, along withseveral other EU countries.

The Norwegian maritime cluster can be illus-trated by Figure 3 (c., Reve et al. 2001:196).

The core o the Norwegian maritime cluster isthe shipping companies providing seaborne trans-portation services worldwide. The Norwegian mar-itime cluster can be traced back to about a 1000years back when the Vikings ruled the Northernshores. The Norwegian maritime cluster has beenhighly innovative, particularly when it comes tonew ship designs, advanced ship equipment, mari-time IT and new commercial concepts. Interest-ingly enough, ship owners rom a country withless than 1/1000 o the world population controlabout 1/10 o world shipping. Norway is also hometo some o the largest global actors in shipping -nance, ship brokers, marine insurance, ship classi-

cation services and maritime law. The North Seaoshore oil industry has developed rom much othe same maritime knowledge base, making Nor-wegian companies world leading in new advancedsectors such as oshore oil drilling, foating oil and

gas production and subsea technology. Thus, theNorwegian maritime cluster is becoming a knowl-edge-intensive industry, thriving on innovation andwith the ability to commercialize maritime activi-ties on a global basis.

Given the large concentration o maritime ac-tors in Norway, its knowledge intensity and the

dense network o interactions within the industry,the Norwegian maritime cluster (c. Figure 3) canbe re-conceptualized as a global knowledge hub.The maritime knowledge hub model, as it appliesto the Norwegian maritime cluster, is presented inFigure 4.

At the core o the knowledge hub is research andinnovation. This not only includes universities andpublic research organizations, but also to a largeextent what takes place o R&D among the com-mercial actors in the industry. Much o this R&D

activity takes place outside the labs, in interactionsamong the various maritime actors, customers,suppliers and consultants.

Unlike the Boston and Silicon Valley cases, thenext circle in the knowledge hub model does notmainly consist o venture capital, but includes ahost o private capital and investors, ranging romrisk capitalists, private equity and large commer-cial investors with a long history o investments

UPGRADING INTERNATIONALIZATION

Shipping

brokers

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Ports and

terminals

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ship equip-ment

MaritimeR&D

Specializedship yards

Maritimeeducation

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design

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Shipping

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Efficient

fisheries

Environmental

standards

Maritimpolicies

Offshore

oil and gasindustry

Logisticssystems

Humanresource

services

Shippingclassification

services

SHIPPING

Fig 3: The Norwegian Maritime Cluster




in the shipping industry. The ability to und largemaritime projects, e.g., in the global oil and gas rigindustry, is astounding.

In the third circle o the knowledge hub modelwe nd the critical mass o maritime actors thatmake up the majority o the maritime industry,such as shipping, ship industry, oshore industryand maritime services. These our sectors have beendescribed in detail in the maritime cluster studies,and the main challenge is to nd out whether they

interact closely enough to create network exter-nalities that are so important to dynamic industrialclusters (Orvedal 2002).

Finally, I have added our external orces thatwill shape the maritime industry in the years tocome. These include the global battle or talentand technology (Florida 2005), and the overallorces o economics and environment. The econom-ics have to do with world trade and global trans-portation markets, which in turn closely depend onupturns and downturns in the world economy. The

recent global nancial crisis illustrates the point.Oil prices play a particularly strong role, especiallyor a country like Norway. which is also a major oiland gas producer. Environment has more and moreto do with climate, primarily the emission o CO2,which o course, is also produced by carbon energyusage in the maritime industry.

The knowledge hub model applied to the Nor-wegian maritime industry, has two main purposes.

First, it can serve as a de-scriptive model to guideempirical research o themaritime industry, e.g., howstrong is the research and in-

novation core, and how closedo the various maritime ac-tors interact. In particular, itis important to nd out howclosely the maritime indus-try interacts with PROs, andhow well academia meets theuture knowledge needs othe maritime industry.

Second, the maritimeknowledge hub model is a

normative model that can guide industrial actionand industrial policy toward the maritime cluster.Thus, in order or Norway to succeed as a lead-ing maritime nation when acing keen competitionrom aggressive maritime nations in Asia, Norwayneeds to strengthen its strategic core o maritimeknowledge generation and dissemination. Thismeans strengthening maritime R&D, maritime ed-ucation, and maritime innovation milieus, includ-ing investing in leading edge maritime knowledge

at universities. It also includes plans or creatingthe largest and most advanced research and testingacilities or ocean technology, reerred to as theOcean Space Center.

In act, the concept o Norway as a globalmaritime knowledge hub was pioneered by OsloMaritime Network in an eort to strengthen theattractiveness o Oslo as a location or globalshipping operations. In May 2008, the GlobalMaritime Knowledge Hub Initiative was launchedin order to make Norway a global knowledge hub

or maritime research, innovation and educationat all levels.

Initially, the Norwegian maritime industry und-ed 10 new maritime proessorships (or researchchairs) at Norwegian University o Science andTechnology (NTNU) in Trondheim and BI Norwe-gian School o Management in Oslo. NTNU alreadyhad a Center o Excellence in maritime research—Centre or Ships and Ocean Structures (CESCO),

Shipping

Maritime

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industry

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industry

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Fig 4: The Norwegian Maritime Knowledge Hub




while BI had developed a Global Executive MBAprogram or shipping, oshore and nance, in co-operation with Nanyang Technological University(NTU) in Singapore.

Two years later (in April 2010), there are close

to 20 new privately-unded maritime proessorshipsin place at our dierent universities and maritimecolleges in Norway, and a similar number o proes-sorships and maritime research centers are undernegotiations. Proposals or a large national researchprogram, called Maritime 21, have been put or-ward by the Norwegian maritime industry, ocusingon demanding maritime operations, ocean technolo-gy, environmental technology and arctic technology,as well as on new business models or the maritimeindustry. Plans and designs or the Ocean Space

Center in Trondheim have materialized.

sinGAporE And norWAy CompArEdSingapore has much o the same role in the mari-time industry in Asia that Norway has in Europe,although its strategic base is dierent. Singaporederives much o its maritime power rom its port,strategically located on the major sea route between

East Asia, Middle East and Europe. In addition,Singapore has become a major location or ship-ping and maritime service compa-nies, including many Norwegiancompanies. Singapore also hasa competitive oshore industry,with leading shipbuilding compa-nies specializing in drilling rigsand foating production vessels.What characterizes Singaporeis its aggressive industrial policytoward attracting internationalknowledge-based companies, par-ticularly in the maritime industry.Singapore has concentrated itsmaritime policies, including own-ership and operations o its ports,into one single government agency,Maritime & Port Authority (MPA)o Singapore.

Although Singapore wants to become one o thehigh-tech players o Asia, ocusing on such knowl-edge-based industries as IT and biotech, MinisterMentor Lee Kuan Yew recently put things more inperspective, “Biotechnology and pharmaceuticals

are ‘sexy and glamorous’ industries, but the mari-time sector is basic to Singapore’s development.Thus, Singapore wants to move rom being a majorhub port to becoming an international maritimecenter with a ull suite o services.” (The StraitsTimes, Sep. 26, 2007).

The international maritime center idea cor-responds closely to a global maritime cluster, butit has relatively little emphasis on the knowledgecontent required in order to succeed. Thus, it isalso possible to re-conceptualize the international

maritime center o Singapore to a global maritimeknowledge hub, c., Figure 5. The gure comesout o the work o the 3rd Maritime R&D Advi-sory Panel o Maritime & Port Authority (MPA) oSingapore, where the author was one o the inter-national members.

Research, innovation and education have beenplaced at the core o the global maritime knowl-edge hub o Singapore, surrounded by a networko venture capital and competent investors. Again,

there are our major industrial sectors constitutingthe majority o the corporate content o the mari-

INVESTORS

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MARITIMEMARITIME

SERVICESSERVICES

OFFSHOREOFFSHORE

& MARINE& MARINE

ENGINEERINGENGINEERING

SHIPPINGSHIPPINGRESEARCH

INNOVATION

EDUCATION

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A L

E C O N O

M Y

G L O B A L

E N V I R O N M E N T

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A L

P O P U

L A T I O

N

G L O

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S

A Global Maritime Knowledge Hub shall propel the

Singapore Maritime Cluster

Fig 5: The Singaporean Maritime Knowledge Hub




time knowledge hub. In Singapore these sectorsare port, shipping, oshore & marine engineeringand maritime services. It all started with the stra-tegic location at the Malacca Strait, and it is airto say that the port is still the major driver o the

Singapore maritime industry. More and more ship-ping companies are placing their global or Asianheadquarters in Singapore due to avorable taxrates and a good inrastructure. This in turn haslead to an infux o many maritime service com-panies. Oshore and marine engineering consistso two major ship builders ocusing on oshorestructures, expanding into global oshore markets.Singapore is also a major port or bunkering andrepairs, and there are also major oil terminals anda petrochemical industry that are important or the

maritime industry.Singapore lags behind Norway, Japan, Korea

and China when it comes to maritime R&D, butthe two major universities, Nanyang TechnologicalUniversity (NTU) and National University o Sin-gapore (NUS) have started activities in maritimeresearch and development, as well as launchingseveral maritime educational programs, initiatedby MPA. Both in maritime research and maritimeeducation, MPA has been instrumental in setting

up strategic alliances with Norway. MPA has es-tablished a Maritime R&D Fund o S$ 400 million,and A*Star (Singapore’s Research Foundation)has initiated R&D programs, building internationalR&D bridges, e.g. with Norway.

knoWlEdGE-bAsEd indus-triAl dEvElopmEnt poli-CiEsGlobal knowledge hubs are rare, and even the moreknowledge-intensive industries have room or morethan two or three global knowledge hubs. Bostonand San Francisco Bay are examples in the bio-tech industry. Thus, becoming a global knowledgehub or a specic industry is more a long term goalthan a reality or most regions.

What is common is to nd more specializedglobal knowledge hubs. In the maritime industry,Norway, Singapore, Japan and China are candi-

dates to become global maritime knowledge hubs.Greece already has such a position when it comesto shipping, while Korea has a strong position inship building. London has a global knowledge hubposition when it comes to the nancial aspects

o shipping, while Rotterdam and Hamburg havestrong maritime hub positions as ports and mari-time services.

The same type o specialization can be observedwithin countries. In Norway, shipping is concentrat-ed in Oslo and Bergen, while the ship industry (shipdesign, shipbuilding and ship equipment) is mainlylocated on the northwestern coastline o Norway.What distinguished industrial clusters rom globalknowledge hubs is the reliance on research anddevelopment, its emphasis on innovation and com-

mercialization, and its global reach.Most ship yards around the world do little or no

research and development. They simply build ac-cording to spec, and the competitive edge is to bethe cheapest. The more advanced end o the ship-building industry invest in long term technologi-cal innovation, working closely with major clients,suppliers and public research organizations. Theknowledge intensity can be measured by the knowl-edge composition o the workorce (percent o

workorce with PhD and MSc), the relative amountspent or R&D (as percent o sales), the numbero knowledge alliances, the number o patents ob-tained, etc. These measures can be calculated orindividual companies, but more importantly suchmeasures apply to the industrial cluster in a givenregion.

The underlying rationale is that industries inregions compete not only in terms o productiv-ity and low cost, but also in terms o innovationand knowledge content. For high cost locations

like Norway and Singapore in the maritime in-dustry, competing on innovation is simply a must.This can be done by attracting a critical mass omaritime actors that spend substantial amountso resources on R&D and who interact closely tocreate knowledge externalities that benet all theactors in the knowledge hub. The battle is otentimes over the location o centers o excellencethat the multinationals set up in several countries.




Such global knowledge hubs also attract the besttalents, both in the educational phase and in theindustrial practice phase, creating a highly at-tractive labor market and large opportunities orentrepreneurship. This gives a special role or the

research universities, but also or more vocationaland technical colleges, educating the specializedworkorce needed in a particular industry. Moreand more such knowledge hubs are able to attracttalent and companies rom many countries, some-times even globally. A key requirement again isthe availability o competent risk capital.

The implications o the knowledge hub model orindustrial policies have not been ully spelt out yet.What we see is that common tax subsidies are re-placed by more ocused knowledge-based policies.

Examples include developing world class universi-ties, specialized research institutes, labs and testacilities, along with the hard and sot inrastruc-ture required to attract knowledge-based compa-nies and highly educated sta on a global scale.What governments need to consider, are strongerincentives or R&D and innovation, better knowl-edge inrastructure, easier immigration rules, andimproved venture capital markets. Oten it is amatter o making it simpler to locate companies

and easier to do business. This is not simply a ques-tion o policies and regulations, but it also has astrong cultural component. Florida (2005) reersto this as tolerance and acceptance or diversityand a multi-cultural population. Many totalitar-ian countries, e.g., in the Middle East, have seri-ous problems in meeting the cultural dimensions oknowledge development. Stability, security, a cleanenvironment and good quality o lie can also give aregion a competitive edge.

It is not new to rerame industrial policy into

innovation policy (e.g., OECD 2008). The knowl-edge hub model, however, puts the main emphasison knowledge policies, putting schools, universities,R&D, innovation and entrepreneurship at the cen-ter stage, rather than considering these knowledgeunctions as support services to corporations. Thisis very clear when you study new and emergingknowledge industries, such as biotech and nano-tech industries. These industries were created in

research labs, and new commercial actors emergedrom the new knowledge base. On the other hand,this was also how most other industries were origi-nally created. Take a traditional and mature indus-try like the ertilizer industry and the establish-

ment o Norsk Hydro, now Yara. Norsk Hydro wasestablished based on a new technology inventedby a research scientist, William Birkeland, whoconvinced a venture capitalist, Sam Eyde, to putmoney behind the idea o taking nitrogen out o theair by using electricity generated by a water all atRjukan, Norway. Today, Yara is the world’s largestertilizer producer, manuacturing and operatingglobally.

One o the main theses in this paper is that in-dustrial development mainly comes rom innovative

industrial environments, here called global knowl-edge hubs, where specialized and basic knowledgemeets demanding markets with a drive to commer-cialize. Universities, public research organizations,venture capital and competent investors have par-ticularly critical roles in such knowledge hubs.

Global knowledge hubs are path dependent andculturally bound, but there are also examples o hownew knowledge hubs have been created by cluster-based policies ocusing knowledge and network de-

velopment. The catalogue o cluster-based policiesneeded to stimulate the growth o global knowledgehubs is still not complete, and more work needs tobe done to understand all the mechanisms inherentin knowledge-based industrial development.

Another thesis in this paper is that the develop-ment o knowledge-intensive industries is basical-ly similar to the development o other industries.Such a thesis asks or new comparative research.Based on the premise that knowledge orces aresimilar across industries, the maritime industry

has been analyzed in largely the same terms as thebiotech industry. In both industries, we nd glob-al knowledge hubs that take lead roles in shapingthese industries. Boston and San Francisco Bayhave such roles in the biotech industry, while Nor-way and Singapore may well take similar globalknowledge hub roles in the maritime industry. Themajor common competitor in the maritime indus-try is China, as in so many other industries. Used




normatively, the global knowledge hub modelpoints to knowledge-based industrial policies thatare dierent rom what is typically implementedin industrial development.

ConClusionThis paper argues or a new knowledge-based para-digm or understanding industrial development.Rather than understanding the rm as manuactur-ing or seeing rms as part o industrial clusters, in-dustries can be analyzed as knowledge hubs. Globalknowledge hubs have world class universities andpublic research organizations at their core, andare in close interaction with venture capitalists andcompetent investors. From this knowledge core, ex-

tensive industrial development can take place, as il-lustrated by the development o the Boston biotechindustry.

Based on the premise that most industries arebecoming knowledge-based, and that knowledgedynamics are basically the same across industries,the global knowledge hub model was applied to theNorwegian and Singaporean maritime industry.Both countries are in a strategic position to shapethe uture development o the maritime industry,but this requires substantial knowledge invest-ments and closer interactions between the actorsin the industry and between private industry andacademia.

The global knowledge hub model can be appliedboth as a descriptive model o industrial develop-ment or as a normative model or industrial de-velopment policies. Both approaches ask or newcomparative empirical research.

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from thE indiA City CompEtitivEnEss

rEport 2010




CitiEs, CompEtitivEnEss, And EConomiC dEvElopmEnt:untAnGlinG thE linkAGEs

Dr. Christian Ketels, member of the Harvard Business School faculty at Professor Michael E. Por-

ter’s Institute for Strategy and Competitiveness and Member of the Advisory Board, Institute for

Competitiveness emphasizes the need for Indian cities to have a clear competitive agenda in order

for the nation to achieve higher competitiveness.

More advanced economies are more urbanized economies. As the interest in economic geographyhas increased, this empirical act has been more widely acknowledged. The 2010 World De-velopment Report provided signicant evidence on how cities and dierent levels o economic

activity across space thereore have to become a more important aspect o the policy dialogue on develop-ment.

In less-developed economies, the growth o cities and the increasing level o urbanization are largely arefection o the widespread weaknesses that exist in economic conditions. With inrastructure, education,and many other aspects o competitiveness weakly developed in rural regions, cities tend to be the onlyplaces where companies and individuals nd opportunities or successul economic activity. The growth ocities is thus more a refection o the development challenges that exist elsewhere in these economies, notso much a sign o true improvements. In act, the rise o mega-cities in many developing economies cre-ates many problems o their own, as these huge agglomerations struggle to provide public services to anexploding number o citizens. This is why in developing economies the rise o cities is seen as an inevitablepart o development, but also as a policy challenge—it creates the need or policies that enable cities tocope with the massive demands that are placed on them. It also creates the need or policies that enablecitizens in rural regions to develop their own economic opportunities. The challenge is to avoid a political

schism between metropolitan and rural regions that would threaten to halt urbanization and thus hurtdevelopment.

In advanced economies, cities are able to play a radically dierent role. With both rural and metro-politan regions providing at least the basic level o competitiveness, the choice o where to locate speciceconomic activities becomes an issue o relative productivity and cost levels. This allows cities to attractactivities that are usually more skill-intensive and where there are strong local knowledge spill-overs whilerural regions attract more capital-intensive or labor-cost sensitive activities in standardized productionprocesses. Cities turn out to be the places where dierent types o proximity benets can reinorce eachother—specialization in specic clusters can occur as well as cross-cluster agglomeration o generaltypes o activities. This mixture is especially important or innovation. High-skilled people are attractedto places that provide variety and interesting contrasts. Ideas are born where dierent intellectual tradi-tions and approaches meet. But to evaluate whether these ideas have any market potential, and to thentranslate them into protable products and services, a specialized cluster o related and supporting activi-ties is needed.

From the competitiveness perspective, the policy imperative or cities as well as or rural regions isessentially the same, independent o the stage o economic development—develop the competitiveness othe local economy in order to achieve higher levels o company productivity and thus support higher levelso prosperity. The specics steps that are needed, however, dier signicantly based on the type o localityand the level o economic sophistication it has reached. What is true in both more- and less-developedeconomies is the need to ocus on the specic role that an individual region can play. This requires or




cities and or the rural regions around them to cooperate closely. It is crucial to enable less-advancedmanuacturing activities to be placed in rural regions in the vicinity o the cities, especially in developingeconomies. The city can provide the advanced services and management unctions, the rural regions theland and lower cost labor. This division o labor can relie pressure on the city’s inrastructure and createeconomic opportunities outside o the large agglomerations.

In the past, cities—also in India—have tried to manage their growth by creating articial limits. Inmany cases, this approach has ailed and made living conditions worse. Mumbai, or example, limits theheight o buildings, which has reduced space use and orced people to live arther and arther away romthe city center. This has created increasing pressure on an already struggling transportation system. Rentcontrol has urther reduced the incentives or land owners to re-invest in housing stock. Mumbai hascontinued to grow nevertheless, but the city is less ecient in providing even basic services in terms ohousing and inrastructure than it could be. What is needed is a dierent policy approach that ocuses onbetter public services and land use inside the city, while creating real economic opportunities outside othe city as well. There are no magic solutions. But there is a need to move away rom the ailed approacho dealing only with the consequences o increasing urbanization. Instead, there needs to be a competitive-ness-oriented policy approach that changes the economic undamentals o where people live and work.

Many o the policy choices that have to be made in order to enable a balanced development o citiesand rural regions require the action o all levels o government—national, state and local. But thereis an increasing realization that cities are not helpless, and in act control many policy tools in landplanning, inrastructure investments, and the implementation o general policies set at higher levels ogeography. Cities need to have a clear competitiveness agenda. Without cities that push or competi-tiveness, it is hard to see how a nation like India can make any sustained progress in its overall questor higher competitiveness.




GroWinG With ClustErs

Dr. Amit Kapoor, Professor of Strategy and Industrial Economics, Management Development Insti-

tute (MDI) and Honorary Chairman, Institute for Competitiveness explains how clusters can trans-

form and add value to the competitive landscape of a city.

Cities and townships are the vantage point or the growth and development o states. The WorldBank has released a status report “Reshaping Economic Geography” on the world economic re-gions and emphasized on urbanization, territorial development and international integration or a

country to grow economically. Thus ar, India has ocused on creating industrialization, but its accidentalconfuence with urbanization and clusters has provided the governance with a tool or enabling industrial-ization in lieu o creating it. Close to 36% o the population in Maharashtra and 45% in Goa live in urbanareas and their annual growth rates are 9 and 10%, respectively. Urban centers allow or concentratedeconomic activity and specialization and hence, cluster ormation comes more naturally. The ocus o this

article is to highlight the importance o clusters and drive location advantages to convert to economicbenets.

Sriperumbudur, a lackluster village near Chennai with no history o industrialization is the largestelectronic hub in India. The Alappuzha coir cluster, the leather cluster in Chennai, the diamond industryin Surat, the petroleum cluster in Bombay, the cotton yarn industry in Ahmedabad and numerous otherexamples indicate the prerequisite presence o a cluster or the industry and the region to prosper. Thediamond cluster contributes 17.22% o the world export o non-industrial diamonds and iron ore and con-centrates contribute 14.20%. Close to 65% o India’s exports stem rom clusters. Industrialization couldnever reach pinnacles o international integration without cluster ormation and industry specialization.

Clusters perorm a unction as basic as bringing the worker and the machinery together to manuac-

ture. Downstream and backstream industries, educational support, nancial institutions and other serviceproviders prop up together linked by complementarities and commonalities. Clusters create the impetusor innovations and competitiveness and acilitate commercialization. Easy access to raw material andlabor, rapid diusion o technological innovations and incentives against rivals enable newer lines oproducts and opportunities to get readily developed and absorbed in the market stream. Thus, the rstchallenge that the governance aces or industrialization is the ormation o clusters.

Urban agglomerates possess the actors required or a cluster to develop. With Nashik, Mumbai, Pune,Nagpur and other centers o economic activity within the state, Maharashtra contributes approximately15% o the national GDP. Another striking example o the eect o urbanization is Delhi; despite a smallsize and population, this city-state contributes about 3% o the GDP. Sriperumbudur could develop intoan electronic hub due to its proximity to Chennai (Bombay High and Alappuzha near Mumbai and Cochin,

respectively). These regions had the resources but the means to process them came rom their neighbors.Inrastructure and human expertise available due to their proximity to relatively developed cities enabledthe regions to specialize and their industry to grow.

Location development cannot, however, be carried out oblivious o the inherent advantages o the loca-tion. Chandigarh as a tech hub ailed as they could neither cater to the demand o engineers and the likeor the industry nor support the infow o migrants who lled the job vacancies. The misconception wasthat only a high-tech industry would lead to growth, but there is no such thing as a high-tech industry.Companies in the same domain can be seen operating with dierent quotients o technological prowess.Agriculture can be done with sophisticated machinery and give high returns. Location development must




be in consideration with the local resources.Another major barrier in cluster ormations and urbanization is the creation o unsustainable urban

agglomerates. Bengaluru and Gurgaon emerged with great promises parallel to that o the Silicon Valleyand Singapore, but the decrepit state o their inrastructure tells a dierent tale. Economic policy shouldreinorce the established and the emerging clusters; however, regulations need to be careully laid out.

The Indian economic geography is waiting to be mapped. However, urbanization remains a challengeor India with more than 70% o its population alling under the rural category. India reels under theburden o income disparities and economic backwardness and urbanization would encourage industrialclusters to create the much-needed income and employment opportunities. A cluster-based regime wouldopen the doors or competitive advantage to lead the entourage towards growth and progress and unlockumpteen avenues or states and regions to create an agglomeration o prosperity.




Good urbAn GovErnAnCE:An impErAtivE for EQuitAblE GroWth

Gordon Feller, CEO of Urban Age Institute, succinctly describes how improving governance—at

the central, regional and local levels—is now a critical part of the agenda for urban economic

growth and social development worldwide.

Good urban governance means inclusion and representation o all groups in the urban society, aswell as accountability, integrity and transparency o government actions. Capable urban manage-ment means the capacity to ulll public responsibilities with knowledge, skills, resources and

transparent procedures. There isn’t a single model that could t the complex process o local capacitybuilding in all countries across the region; the ultimate success is determined by national policies and

local leaders’ willingness and ability to carry out their mandates. The World Bank provides technical as-sistance and advisory services to assist in public administration reorms and capacity building at the levelo local governments.

Firstly, we need a good denition to guide our thinking: governance is the science o decision-making.The concept o governance reers to the complex set o values, norms, processes and institutions by whichsociety manages its development and resolves confict, ormally and inormally. It involves the state, butalso the civil society at the local, national, regional and global levels.

Good governance implies eective political institutions and the responsible use o political power andmanagement o public resources by the state. Essentially, it is about the interaction between democracy,social welare and the rule o law. Good governance, thus, extends beyond the public sector to include allother actors rom the private sector and society. Good governance is guided by human rights and by the

principles o the rule o law and democracy, such as equal political participation or all. Particular atten-tion is devoted to the needs o the weaker members o society.

In the United Nations’ Millennium Declaration, the international community reached a consensus thatgood governance is not only an aim in itsel, but also a key actor in attaining human development and insuccessul poverty reduction and peace-building.

Some o the most important work now underway on good urban governance covers the promotiono democracy and rule o law. Human rights play a particular role in this context, especially women’srights. Eective works in the eld o law and justice means ghting corruption and promoting theresponsible use o public nances. It means supporting smart and eective government and adminis-trative reorms, the decentralization and regionalization o state power, and the development o local

and municipal government. In doing so, it implies the promotion o locally appropriate approaches; itnot only cooperates with government institutions, but it must also promote and strengthen civil-societyactors.

Decentralization is crucial to the whole process o creating better, smarter and cleaner urban gov-ernance. Citizens, companies and associations approach the state requesting an enormous diversity oservices; the law must regulate which o these the state is required to perorm. It is also necessary todene the tasks to be undertaken at each government level—central government, regional authorities orlocal administrative units. Decentralized governmental structures work closer to the grassroots and aremore cost-ecient and fexible. However, local authorities and regions are not able to solve all o soci-ety’s problems. An important criterion or dealing with the question o governmental organization is the




‘subsidiarity’ principle. This says that tasks should be perormed wherever possible at the closest level ocompetence appropriate to the given situation.

Many countries want to exploit the advantages oered by an expedient allocation o tasks within thegovernment administration. This requires regulating decision-making responsibilities and earmarking su-cient resources or implementation.

Many governments and parliaments are in the process o dening these tasks. For which services andcorresponding inrastructure measures is the state itsel responsible? Which tasks can it entrust to oth-ers? How does it plan and nance these? Which government levels should perorm which tasks? Shouldresponsibility lie with the central government, or a regional or local authority? Who decides on the qualityo services, and how? And who monitors the actors?

In order to nd technically and needs-appropriate solutions, a growing number o government actorsare ocusing on perorming the tasks allocated to them—what competencies do the local authorities needin order to promote local development? How can the support measures be organized so as to producesustainable results? This also means involving representatives rom the regions and municipalities, civilsociety and the private sector in these decisions on reorm.

Cities with good governance have a greater potential to create and support good living conditions.

These cities have a better chance to oer their inhabitants a more equitable share in economic growth,access to inrastructure and services, and participation in political decision-making. Accompanying theseopportunities, however, are growing demands on the capacities o municipal institutions. As national-levelpublic unding dwindles or cities, public resources must be stretched to meet the needs o the growingnumbers o urban dwellers. This is one o the central challenges o our time.




smArtEr indiA

Transportation bottlenecks increase business costs considerably in Indian cities. Dr. Amit Kapoor,

Professor of Strategy and Industrial Economics, Management Development Institute (MDI) and

Honorary Chairman, Institute for Competitiveness and Susan Zielinski, Managing Director of SMART

(Sustainable Mobility & Accessibility Research & Transformation, a project of UMTRI, the University of Michigan Transportation Research Institute and TCAUP, the Taubman College of Architecture and

Urban Planning, in Ann Arbor) tell us how innovations in information technology can pose some

solutions.

India reels under the burden o congestion and trac. While urbanization traces a new path or theIndian populace to race and prosper, the pace o the Indian economy is slowed down due to its grosslyinadequate inrastructure. The implications o the rise in urban population on urban transportation

and subsequently on business require urgent attention. The current state o transportation leaves vast gaps

between demand and supply, and uture projections indicate we are nowhere near closing those gaps.Precious time is wasted waiting in trac jams and at signals. The woeully inadequate public transportsystem, and the insucient routes and roads available are the prime reasons or the hours-long traccongestion that most people in metropolitans have learnt to live with. The number o cars and privatetransport are on the rise as towns and urban areas expand, and the provision o inrastructure to supportthe infux is insucient to create conditions or the smooth fow o all orms o trac.

The problem is not small, and the subsequent consequences cannot be ignored. The cost o doingbusiness rises as employers need to get their employees to work. Hours are wasted managing the tracsituation in place o working productively. What’s more, the health and welare o all urban dwellers arecompromised with the rise in pollution, not to mention the longer-term threat o climate change. The dualeconomy means dierent modes o transportation are suited to needs dierentiated by variance in income,

in turn creating a bigger mess on the roads i the system is not properly integrated and optimized (whichis usually the case).

In a nutshell, there is no space let and the urban areas are only attracting more people. As such theneed-o-the-hour is not just a more uel-ecient technology (that will actually continue eating up thatspace), but rather a more multi-aceted, human-oriented, integrated system that connects and optimizesall modes and services in an innovative and cost-eective way. The transportation problem has too ar-reaching an impact on land use, urban sprawl, pollution and climate change, inrastructure, and saety tobe ignored or reasoned only in the wake o congestion on the roads.

Fortunately, some exciting options are emerging, that may just meet urgent transportation needs andresult in business opportunity and urban competitiveness at the same time. Much as our present telecom-

munication network has evolved to include and connect iPods, PDAs, laptops, desktops and cell phones,SMART’s innovative approach integrates the various IT technologies with a wide range o transportationmodes, services, designs and inrastructure to create an urban portolio that permits an easy, convenient,door-to-door trip. Only a step outside the house would link the traveler to ‘New Mobility Hubs’ or placesthat connect a whole range o transport modes and amenities, day-care centers, satellite oces, caes,shops and entertainment, all linked or inormation and are payment through a cell phone, PDA or in-ormation kiosk (or those who cannot aord a cell phone). The inormation is relayed in real time on thearrival, departure or availability o transport modes and services including inormation on restaurants,shops and services, maps, etc. The system works to oer smooth transition between various modes o




transport and to use the inormation on scheduling and options to plan the most appropriate path or jour-ney. It also works to oer new “last mile” services that provide on-demand transer rom the hub to theront door. A person needs to just pick a waiting car or train or hop on to the next bus cutting delays tothe minimum. Imagine getting inormation about the waiting carpool to reach the nearest metro stationjust in time to leave in the ongoing train, only to be dropped to the oce or may be the airport, all within

a single, eortless and non-stop journey. All the modes o transport are streamlined to orm a single net-work to transport people with smoothness, eciency and speed.SMART (Sustainable Mobility and Accessibility Research and Transormation) is an initiative o the

University o Michigan that began in collaboration with Ford Motor Company around 2005 to address thetransportation challenge in global cities as the world rapidly urbanizes. (In 2007, 50% o the world livedin city regions. In the next 20 years that gure will climb to 2/3 o the planet). The exciting co-beneto addressing the urban transport challenge is that companies and entrepreneurs that work together torespond to the need or sustainable, integrated, multi-modal urban transportation stand to tap rapidlyemerging (and sizable) ‘New Mobility’ markets.

In this spirit, SMART and Ford have engaged a myriad o industry partners related to the uture otransportation (New Mobility) to support a comprehensive entrepreneurial and business base. The initia-

tive promises to change the way cities comprehend urban transport. Public-private partnerships can makeroom or public-private innovation where business is involved rom the outset in understanding and co-dening the problem, and then oering solutions that support the public good and stimulate new businessopportunities at the same time.

Apart rom addressing urban congestion, this approach has the potential to provide an ideal opportu-nity or businesses and entrepreneurs to develop integrated New Mobility systems building on the Ford-SMART collaboration. The question remains however, on how companies will envision the India-specicneeds and opportunities and uses o New Mobility Hub Networks and how they might create an intricateweb o technology and transport to simpliy the current complications o the urban agglomeration andoer an almost perect (and cost-eective, business-positive) solution.




hAbitAts At risk:ChAllEnGEs of urbAn GovErnAnCE in indiA

Raj Liberhan, Director India Habitat Centre, warns of impending disaster unless a realistic needs

assessment of the infrastructure needs of Indian cities is made. Ultimately, pressure from the citi-

zens, who seek a better quality of life, will be the ultimate motivation and test for city governments

and managers.

Humans have used nature’s assets since time immemorial in the belie that these resources hadalways been around and would be so orever. The implicit view was ‘use what you need and donot worry about regeneration or replacement’. The niteness, however, o nature’s lie-sustaining

treasures like water, energy, ossil uels and orests has come home in a pointed manner to policymakersand consumers alike, and is pushing us to rapidly nd substitutes, supplements and replacements.

The stark reality acing us and demanding answers is that nature’s assets need to be secured and onlythen can human security be ensured. The two are closely interlinked, though our perspective solely romthe prism o human security distorts the solutions we seek. This anthropogenic ocus leads to a lopsidedinvestment o time and money and consequential unsatisactory outcomes.

Urban habitats in South Asia (a region that gave us the immaculately planned towns o the Indus val-ley Civilization thousands o years ago), and indeed in much o the developing world, are ast becomingvulnerable to multiple hazards. Mega cities, in particular, are crucibles o hazards. Smaller cities tooare deteriorating at an alarming rate and there is not even a modicum o concern in evidence, much lessan eort to ameliorate the situation. Water availability is an issue and its quality an even greater issue.Energy concerns, both o availability and access, plague every city, big or small. Sanitation and wastemanagement strategies are beginning to be talked o only or mega cities. In the rest, disposal o waste

generally implies throw-what-you-do-not-need-in-any-vacant-site. Similarly, sanitation in small and me-dium towns is virtually non-existent. The cumulative impact o the needs o burgeoning urban populationsis depleting physical resources, and given the absence o a perspective plan or managing our cities, thereis no regeneration o sources o supply.

The big question is—will our cities survive? Or is there certain inevitability about the degradation ocity inrastructure and civic amenities that no organization or planning process can address as the vol-umes to be serviced are huge? In this context, questions about the sustainability and survival o the cityand its population acquire great urgency. I we couple this with the inadequacy o the solution providersone could argue not much time is let beore the inadequacies swamp any chance o a solution.

There is no doubt that the state is making eorts to provide or capital investments in inrastructureand services at the city level as well as undertaking urban reorms (the Jawaharlal Nehru National UrbanRenewal Mission is an important example). However, the current state o civic inrastructure is a sorrytale and the challenges are enormous.

For the capital city o Delhi alone, as per Pro. Kumon, with the number o agencies in charge o thecapital’s water supply, sanitation, health services and pollution control, it could be reasonably assumedthat the city enjoys an enviable standard o cleanliness and health. Nothing could be urther rom thetruth. Let us look at a ew telling statistics or solid waste, water and energy as illustrative examples.

About 6000 tons o solid waste was generated daily in Delhi during 2004, up rom 1960 tons in 1981.According to the 1997 White Paper on Pollution in Delhi, this gure is expected to increase to about12,750 tons per day by 2015 (http://www.envor.nic.in/divisions/cpoll/delpolln.html). Per capita waste




generated ranges rom 150-600 grams daily, depending on economic status. This includes waste romhouseholds, industries and medical establishments. In addition, the two thermal power plants burningcoal produce 6500 tons o fyash daily. Out o this, only 65% gets collected per day by the MunicipalCorporation o Delhi and another 10-12% by other agencies (http://www.teri.res.in/teriin/camps/delhi.htm#waste). What happens to the rest? Where does it go?

For the country as a whole, solid waste generated daily per person has increased rom about 295 gramsin 1947 to 490 grams in 1997 and is expected to urther increase to 945 grams by 2047 (http://www.devalt.org/newsletter/eb04/o_1.htm). The estimated land required or disposing such huge amountswould be humongous.

With respect to water pollution even though Delhi constitutes only 2% o the catchment o the Ya-muna basin, yet the area contributes about 80% o the pollution load (White Paper, op. cit.). There are16 drains that discharge treated and untreated waste water/sewage o Delhi into the Yamuna river. Themunicipal sector is the main source o water pollution in terms o volume. In 1997, about 1900 mld owastewater was discharged rom the municipal sector (up rom 960 mld in 1977) and 320 mld rom theindustrial sector. Though the installed capacity or treatment was 1,270 mld, the treatment quality was/ is not up to the desired level o secondary treatment. Thus, a substantial quantity o untreated sewage and

partially-treated sewage is discharged into the Yamuna every day. The Najagarh drain contributes 60%o total wastewater, and 45% o the total BOD load being discharged rom Delhi into the Yamuna.

With respect to groundwater as well, 75% o the samples taken rom hand pumps were ound untor human consumption. Delhi does not have enough clean water: as against the present demand o 800MGD only 650 MGD potable water is available (http://www.delhijalboard.nic.in/djbdocs/r_w_harvesting/ harvesting1.htm).

The gap between demand and supply is partly being met by extraction o groundwater through wells,tube wells and deep-bore hand pumps. It is estimated that water quality and availability problems willbecome acute in the near uture because resh water sources will decrease, and the city will be orced touse brackish and saline water.

Finally, we take a brie look at the energy scenario. The power situation is grave. At a general levelit can be said that India’s economic growth will continue to be hampered because o power supply con-straints. What does this bode or India’s cities? The stories and statistics o shortages can be repeatedacross the length and breadth o the country.

Yet our urban centers are growing by the day. What we need is an analysis o our cities’ strength anddecits on ve undamental parameters that will determine their survival and growth or extinction. Theseare water, energy, transport, sanitation and waste management. In our view, these are absolutely criticaland unless development in these areas keeps pace with demographic trends, the resultant disaster is goingto happen sooner than later.

We need realistic surveys and needs assessment o our cities on a given set o indicators, make an as-sessment o current pace o investments and the levels needed, technology supplements and strategies to

keep ahead o the volumes that will impact our cities. In the process, we also need to take a hard look atstructures o governance and their capacity to address the challenges o the ve undamental actors orcity survival and growth.

It is clear that placing the management o cities on the roadmap to sustainable development will re-quire interventions on many ronts. Innovations are required to reduce inputs per unit o output (resourcemanagement eciency), restrict consumption o services (eciency in service delivery), and augmenta-tion o input fows (resource mobilization). Further, to assess the visible risks, alternative scenarios needto be worked out, or example:nBusiness-as-usual, i no changes take place on demographic and related ronts




nFeasible interventions that control demographic and related parametersnInnovative approaches with respect to city management processes

Some questions/issues

For initiating this process, several critical issues have to be addressed and a demand-driven strategydesigned to be implemented over a give time rame. Some illustrative issues or challenges that need im-

mediate attention are:nWhat have been the deciencies in managing the growth o cities?nWhat local innovations and policies are required to manage the rate o slum ormation?nWhat are the most eective interventions to assist the urban poor—slum upgrading, slum relocation

or other types o interventions?nWhat are the three most critical tasks to bring back a sae and hygienic city environment—waste

management, water management, slum management, trac management, energy management?nWhy has the present set o interventions not worked—bad planning and policies, inecient manage-

ment, weak inormation base on the problems and on people’s aspirations?nIs there a hope or our choking cities and what should be the roadmap or them to reemerge not only

as centers o sustainable growth, but as attractive destinations or healthy living?Documentation can be the starting point o a dialogue or the citizens to demand provisioning o al-

locations in a given time rame and to create benchmarks or every city so that the citizen can demandperormance o their city managers and representatives. The ultimate equation o environmental securitycreating the ambience o individual security will get created as a benchmark and the initiative can be ex-tended to other cities. This will serve as a citizen’s mandate or civic governance that in turn can impactthe attitude and agenda o the political executive, irrespective o party aliation.




WAlkAbility: thE CritiCAl urbAn pArAdiGm

Sanjeev Sanyal, Founder & President of the Sustainable Planet Institute advocates urban planners

to include walkability into the DNA of Indian cities as a simple, yet radical step, towards increased

sustainability and social inclusion.

When China began to reorm its economy in 1978, it had an urbanization rate o barely 18%(roughly equivalent to India in 1950). Thirty years later, the proportion is estimated at around55%! We have every reason to believe that India will experience something similar in the next

three decades. Within teen years, states like Tamil Nadu, Maharashtra and possibly Gujarat and Punjabwill have an urban majority. By 2040-45, we can expect the country to have an overall urban majority.This raises the problem o accommodating another 350-400 million people in our cities. Indian citiesalready struggle to serve the existing urban population, how will they deal with this deluge? In particu-lar, how do we ensure that these cities are environmentally sustainable at a time when climate change is

becoming a major global issue.O course, environmental sustainability is not the only actor to consider. Cities have to be economi-

cally- and socially-sustainable as well. This is true or existing cities as well as the many new cities thatIndia will build in the next hal century. So we need to think o an urban paradigm that combines eco-logical concern with inclusive growth. Furthermore, it must be a paradigm that applies equally to smallmoussil towns like Purulia and Jorhat as well as mega-cities like Mumbai and Delhi. Finally, it must besimple to understand, easy to apply on a mass scale and fexible enough to adapt to local conditions. Isthere a way to combine all this?

Need to think systemically

Growing awareness about climate change has recently ocused a great deal o attention on “green build-ings” as the uture o urbanism. A plethora o “green codes” have been initiated including LEED, GRIHAand so on. My discussions with leading architects suggest that these codes typically give us energy savingso around 15% (higher savings are possible but they involve sharply higher costs). This is a useul saving,but it is hardly a major strategic intervention.

The problem with so-called green codes is that they exclusively ocus on maximizing an individualbuilding whereas the real gains come rom overall urban orm. Is the city dense or sprawled? Do peoplelive in apartments or ree-standing houses? Is the city designed or public transport? For instance, energyuse drops by over 30% just by moving people rom houses to apartments even i we ignored the greencodes. In other words, India needs to think more about the overall scheme. Given the scale o the impend-ing shit in population, we urgently need to think o simple and universal paradigms that can be replicated

on a mass scale across the country.

Walking: The ultimate orm o public transport

The history o every city is ultimately dened by the nature o its transportation network. London isdened by its underground rail network, Manhattan by its street-grid (and its underground rail), Los An-geles by the highway network, Paris by its avenues and wide side-walks, and so on. This is critical to boththeir evolution as well as their urban experience. This is also true o Indian cities. Mumbai developed tworailway corridors built in the nineteen-century while Delhi is the result o a car-based design (cars hadjust appeared when Lutyens was designing New Delhi). Once the transportation network has been xed,the DNA o the city is very dicult to change. This means that our quest or environmentally and socio-




economically sustainable urban orm must start with the transportation network. Given our concern withenvironmental impact and social inclusion, it must be some orm o public transport—but what?

Any discussion o public transport ends up being a debate about buses and trains. Oddly, the simplestand most widely used orm o public transport is walking (and its sister mode, cycling). A 2008 studyo 30 Indian cities showed that almost 40% o all trips in urban India involved no motorized vehicles

at all—28% walked and 11% cycled. The proportion was sharply higher in smaller towns as distanceswere usually small and the roads less congested. However, in bigger cities, the proportion o people usingconventional public transport was high, and consequently commuters walked the last mile. For instance,in cities with more than 8 million population: 22% walked all the way, 8% used cycles and 44% usedpublic transport. This adds up to 74% o people who rely on non-motorized transport or at least part othe commute.

Not only is walking a democratic orm o transportation, it is clearly ecologically-riendly, healthy, en-hances social interaction and gives the city a personality. Moreover, social interaction and street lie haveenormous economic value as this is what makes cities dynamic and creative. This is why the core o all theworld’s great cities is consciously walkable—central London, Paris, Manhattan, Singapore and so on.

Note that walkability and public transport must be embedded in the urban DNA as soon as possible

because it is very dicult to retrospectively change urban orm. Take or instance, Atlanta and Barcelona.Atlanta has a metro network o 74km while Barcelona has one o 99km. These may seem comparable butper capita CO2 emissions or Atlanta are ten times that o Barcelona. The dierence is mostly explainedby Barcelona being compact while its American rival is spread out. As a result, less than 4% o Atlanta’spopulation lives within a reasonable walking distance o a metro station compared to 60% or Barcelona.I Atlanta now tried to give its citizens the same accessibility, it would have to build 2800 new metro sta-tions and 3400km o new tracks!

Despite this overwhelming evidence, very little thought is given to pedestrians in Indian urban plan-ning. A brand new city like Gurgaon does not have any network o sidewalks at all! Note that it is not justa matter o building sidewalks. Walkability is about making it possible or the average citizen to be able

to lead his/her lie by relying largely on walking or day-to-day activities. This requires a whole gamuto urban design requirements like density, mix-use, street lie, pedestrian crossings, tree-shade, public-spaces and so on. All these parameters are important in their own right, but walkability is a simple wayto encapsulate this philosophy o urban planning. This is why I strongly eel that walkability is the singlemost important urban design paradigm that must be adopted while thinking o India’s urban uture.

“Trac and Transportation Policies and Strategies in Urban areas in India”, Wilbur Smith Associ-ates (sponsored by Ministry o Urban Development), 2008.

World Development Report 2009, The World Bank.




brAndinG A City from Within

Madhav Raman, Partner at Anagram Architects and Anupam Yog, Director with Mirabilis Advisory

take a look Delhi’s inherent urbanism, its urban identity and experience and at the interstitial ele-

ments within Delhi that could be used to build a brand for the city, from within.

Urban experience

“A single exhaustive denition eludes a city’s “urban experience”—which can also be interpreted as acity’s brand. Nevertheless, it could perhaps be described as a woven composite, mainly dened by its builtcharacter, its urban identity and the behavior o its residents.”

Built character: The evolution, conservation and renewal o the built character o a city is governed byplanning norms, building controls and urban policy, which are the traditional instruments o urban plan-ning and urban design. The built character makes the most immediate spatial and visual impact o thecity’s “hardware” on the psyche o its residents. Through its deliberate control and careul manipulation,

a physical sense o “place” may be created within dierent precincts o the city. It is even possible to cre-ate “urban icons”, spaces that induce a sense o belonging through their distinct and unique singularity.

Urban identity: However, “place-making” is truly the work o the citizens o a city. Certain urbancontexts o the city strike a deep chord with its residents. Even though they may be unremarkable archi-tecturally, the chord resonates with the citizenry so strongly that a collective identity gets invested in these“places”. The “places” then move beyond the realm o physical symbolism and become iconic within theminds o the residents, contributing immeasurably to their urban identity. Quite oten, this is less throughphysical engineering, but due more to the nurturing o numerous inherent characteristics such as historic-ity, accessibility, multi-vocal qualities and inclusive nature.

Urban behavior: Multi-vocal urban contexts carry unique meaning to each individual; their simultane-

ous inclusiveness allows people to openly engage with them both individually and collectively. Such spacesand contexts within a city have a deeply reciprocal relationship with the urban behavior o the residents,the manner in which they view and engage with their city, and with each other. The urban behavior o acity replicates itsel in recognizable patterns at multiple scales.

Interstitial urbanism

“As emerging cities hurtle along the path o rapid urbanization, many issues that pertain to urban experi-ence all outside the purview o ormal tracks o urban planning and policy.”

Urban experience evolves over many years o habitation in a settlement and has deep cultural andsocio-economic roots. Its very nature makes it impossible to describe, and thereore analyze, in purelystatistical terms. Yet, it adds immeasurable value to the city. It enhances the livability o the city and

increases its ability to attract and absorb human capital. In short, it vitalizes a city, encouraging a senseo belonging amongst residents and widening their engagement with the city and with each other. Thishelps empower segments o urban society whose means are limited and who seem to have a reduced stakein the city. It increases the adoption and utilization o the city’s inrastructure and spaces through cultur-ally congruent means. Other aspects o healthy urban behavior such as syncretism, tolerance, a socialconscience and a liberal outlook are intrinsically linked to a vibrant urban experience.

The urgency or development in emerging cities puts a strong emphasis on global models o inrastruc-ture development and technological advancement. Yet, this oten results in eroding the intangible qualityo urban experience. Moreover, the pace o development requently allows inadequate time and space or




the city to adopt new physical inrastructure and spaces, and inuse them with its inherent urban charac-ter. Crucially, the rapid introduction o new physical assets to the city renders older, oten more vibrantassets, redundant, deunct or underutilized. Their reinterpretation and regeneration may help in creatingtimeless, relevant socio-cultural anchors that are vital or cities experiencing vast change over a relativelyshort period o time.

What are these core assets that hold the key to revealing a city’s identity or character? What is thenature o their potential to add value to the urban living condition? In what manner could these be tappedor reinvented to create more inclusiveness? How can these assets empower residents, and result in socio-ecologically aware liestyles?

Branding Delhi

Let us evaluate the possibilities o building Brand Delhi by looking within.Redundancies enroute: Within Delhi’s grade separators, interchanges and rotaries, pockets o redun-

dant spaces and suraces such as fyover sots, trac islands, medians and roundabouts exist. Sucheatures are permanent components to our cityscape. While they are constantly on view (to commutersor example), there is scant engagement with the city. Can these spaces do more than merely channelize

trac?Deunct urban hardware: As Delhi acquires new inrastructure and buildings, old structures, “hard-

ware” and edices are abandoned, get under-utilized, or become superfuous. Many o these have signi-cant urban value due to their age, iconic status or location. Could they be innovatively leveraged?

Water conduits: From the natural drainage systems (nullahs) to sewers, water supply pipelines to watertankers, various conduits and channels o water scour Delhi. How can their value as existing networks bebetter used by the city?

Green reserves: Delhi’s Ridge Forests were a contiguous belt that ensconced the ormal city just a ewdecades ago. Rapid agglomeration has reduced these to green enclaves o various sizes. While it is impera-tive that these are protected and allowed to thrive, it is equally important or them to be part o Delhi lie.What orm o engagement should this be?

Urban villages & historic settlements: Delhi’s many “original” settlements and rural enclaves give aunique favor to the city, but seem to be at odds with development policies. Being outside the ambit o ur-ban controls, they remain excluded rom the abric o the city. Could these settlements potentially enhancethe inclusiveness o the city and become vibrant contributors to Delhi’s urban experience?

Wholesale markets and street commerce: Delhi’s urban culture, like that o most other old cities acrossIndia, is very deeply linked to the commerce o the street. This is the essence o Indian city lie and Delhihas its own special relationship with what is now termed as the “inormal tertiary sector”. Similarly itswholesale markets, some o which have existed or many centuries, are signicant cultural anchors. Canthese seedbeds o interstitial urbanism be revived?

This is a radically dierent way o looking at building a contemporary city brand. Eventually, however,

in the context o India, and perhaps elsewhere too, it is important to look within to build a city brand thatnds resonance and has the ability to endure.




An ElEvEnth intErmission

Sam Miller, journalist and author of ‘Delhi: Adventures in a Megacity’, recounts his experience of

crafting and then running his beloved Delhi on SimCity from the year 1900 till the present day. His

frustrations as Mayor of Delhi in the game mirror the tremendous complexities of real-life urban

planning and management, both disciplines increasingly critical to the growth trajectories of cities across the world and areas where Indian cities like Delhi urgently need expertise and intervention

today.

The year 1999 was one o the worst in Delhi’s history. Air pollution reached record levels, there weredaily power cuts and water shortages, rioters took to the streets, a tornado struck the south o thecity, there were huge res in the largest industrial area; a plague o locusts descended on Delhi’s

suburbs, space junk landed in the city center and the Yamuna turned into a raging whirlpool. The popula-tion halved in the course o the year, with people feeing to the neighboring countryside, and the city went

bankrupt. Delhi’s long-standing mayor, Shyam Mitra, leaned back, stared at his computer screen, and elthe had no option but to resign. Or he could go back to his previous saved version o SimCity, when Delhiwas still a fourishing metropolis.

Until my son introduced me to SimCity, I thought all computer games were about killing or winning,or both. In SimCity you can’t win, and no one ever dies (even during an earthquake). Instead, you buildyour own ‘simulated’ city, call it what you want, become its mayor and see how successul you are at run-ning it. As the clock o history ticks by, at your chosen speed, on the toolbar at the bottom o the screen,your city grows and shrinks. People (‘Sims’) migrate to your city when it’s an attractive place to live andwork in. And they leave i they don’t like it, perhaps because you haven’t built enough schools or there aretoo many power cuts, or because it’s too boring. I became a secret addict. It’s unexpectedly realistic, andbecause there is a serious side to it—like a beginners’ course in urban planning—I elt able to pretendthat I was hard at work.

SimCity has a number o pre-installed cities—real and invented—including London, Los Angeles andan all too plausible Dullsville. But there’s not a single city rom the developing world. So, no Delhi. I eltit was time or me to have a shot at running this city that had become my home. First, I had to recreatethe terrain o Delhi on an empty greeneld site, careully sculpting, with mouse-and-toolbar, the contourso my virtual city. Delhi would not be Delhi without the Ridge and the Yamuna, and I was able, god-like,to raise and sink the land to create the ancient topography o Delhi on my computer screen. I then had toskip the next ew millions o years o Delhi history, since the game automatically gave me a ormal start-date o Jan 1, 1900.

I hurriedly created Old Delhi rst, with a central street, just like Chandni Chowk, as its main east-west

axis. I careully placed homes, actories and shops around Old Delhi in a way that mimicked the real cityat the start o the twentieth century. I could lay out the streets as I wished, and had a choice betweenresidential, commercial and industrial buildings o low, medium or high density. The population began togrow. I laid railway lines, created landll sites, built hospitals and schools. The architecture o the build-ing was very Western, so compromises were necessary. For the Red Fort I had to make do with a Disney-style Cinderella’s castle; a lighthouse became the Qutub Minar, surrounded (this was the early 1900s) bya small village. The only nod to India in the entire pre-packaged SimCity game is the Taj Mahal, which,quite appropriately, I was able to place on the site o its precursor and inspiration, Humayun’s Tomb.

In 1920, I began building British New Delhi. The avenues o India’s new capital were laid out accord-




ing to the plans o Lutyens and Baker, with the Arc de Triomphe and the White House proving suitablesubstitutes or India Gate and the Viceregal (now Presidential) Palace. I moved on quickly to the concen-tric circles o Connaught Place. The city’s population continued to grow slowly. The new parts o the citywere too low-density, I was told by Constance Lee, one o a series o virtual advisers.

I soon came upon the ‘disaster’ menu, a drop-down list that allowed me to summon up a wide range

o catastrophes. And so, at the click o a mouse, I was able to replicate the great North Delhi tornado o1978. Similarly, the Partition riots o 1947, the anti-Sikh riots o 1984, the anti-Muslim riots o 1992all took place (this time without serious casualties) on the streets o SimDelhi.

However, the SimCity computer model was not working like the real Delhi in a number o telling ways.Sims are a lot more ussy, or spoilt, than the people o Delhi. By the late 1990s my city only had a popula-tion o just over hal a million, a twentieth o the size o the real Delhi. I the roads aren’t kept in perectcondition, or there are a ew power-cuts, Sims leave the city in droves. They began demanding a Metro asearly as the 1920s, and would not put up with what were, by Delhi standards, rather low levels o pollu-tion. Sims won’t move into homes without an underground 24-hour water supply.

As mayor o Delhi, I became more and more rustrated, and began to run out o money. Most o thecity’s income came rom taxes, and its residents kept moving out i I raised tax rates. In early 1999, an

old electricity generating station became overloaded, and blew up. I didn’t have enough money to buy anew one, and all the other electricity plants tripped. Suddenly Delhi had no power, not even enough towork the water pumping stations—and my lovingly created city had no water either. In the real Delhi, poorpeople would have used handpumps and wells, the rich would have used water tankers and generators. ButDelhi just collapsed. A sel-destructive anger, born o impotence, overtook me. I pressed every disasterbutton, and went to get a beer rom the ridge. My city was black with the carcasses o deserted buildingsby the time I returned a ew minutes later. In two SimCity years, the population had dropped to almostnothing. I realized that I hadn’t destroyed the city quite as quickly as the British had ollowing the 1857uprising, or as Mohammad Tughlaq had in 1327; but I had come pretty close. Delhi was dead.

I searched out my son, and told him my tale o woe. And he told me a secret. He taught me about cheat

codes. Most computer games have them, he told me with a slightly patronizing air, as i I were the child.‘With SimCity, you just need to type in the special code, and everything is ree.’ He reverted to my olderstored version o SimDelhi rom 1993, held down our keys at once, (Ctrl-Alt-Shit-C) and up jumpeda little dialogue box. He typed ‘I am weak” and suddenly I had unlimited credit. Everything was ree.Another cheat code “nerdz rool’ converted all my old industrial buildings into hi-tech ICT businesses. Ibegan to create the perect Delhi, my version o Amir Khusro’s heaven on earth.

Like Delhi’s city planners o the nineteen-sixties and seventies, I was able to ignore reality. They justpretended it was a middle-sized city without major inrastructure problems. I could just print money, andbuy any solution I wanted. I did still try to keep the city authentic. So the Metro appeared in 2002, andan earthquake shook the city in 2005. Lots o sporting acilities sprang up across the city in time or theCommonwealth Games o 2010, by which time the Metro had spread across all o Delhi; there were still

more sports stadia or the 2020 Olympics, and I was delighted when my city became an international hubor space travel in 2045.

As the population continued to grow, I elt pleased with mysel, despite the double articiality o a citythat exists only on a computer hard drive and in which construction costs are zero. But it did raise thesame issues, which remain at the heart o Delhi’s modern dilemma. I had chosen population growth as myindicator o success; recognizing that improved services mean more migrants, which puts greater pressureon services. I these services can be improved, the city’s population would, well, spiral.

SimCity has a limited number o pixels, or land squares, on which I can ‘grow’ my city. And in theend I ran out o space, with a population o just over two million. There are no geographical limits—no




mountains and no coastline—to the expansion o the real Delhi; it could, or better or worse, continue togrow in every direction, and it may once again become the most populous city in the world.

Outside the Console

Agreed, this is just a video game. But this “game” puts orth some serious considerations or all o us.While we are busy ranking our mega cities, SimCity, by not having any Indian cities as an option, lands

a blow to our ego. One might contend that it is a western game and hence it might have been created tocater to a similar audience. That is very sound logic, especially since it had no cities rom the developingworld. Well, to the competitive Indian that is still an insult: it is okay to ignore the rest o the developingworld, but they must have chosen some Indian cities to represent the emerging world!

The policymakers do not have it easy. Even inside the console, creating and maintaining a city turnedout to be a tough task. As the author discovers, coping with the population growth alongside the growthin the diverse demands o the people is overwhelming even in a virtual world. By how much this dicultycompounds in the real world is a matter o debate, what is a certainty is that the diculty does com-pound.

Unlike Miller, our mayors do not have ‘special codes’; hence everything is not ree! That’s the real

world or you. Hence, it is not possible to create everything perectly like in SimCity. However, unlikeSims, real Delhi-ites do not think luxurious amenities as being mandatory beore choosing a city to live.So we don’t really need to build Delhi to perection, and can still be rest assured that it will continue togrow. The end result, just as in the video game, we have ourselves a situation where the population spiralsand Delhi continues to grow until it reaches its boundary, like in the game, or a point o sel-destruction.

In a strange way, the simulation augurs the need o careul planning or Delhi—and any big city inIndia or that matter—as we concentrate on making our cities productive, competitive and livable. Itcalls or detailed vision and implementation o decisive regulations pertaining to advancement o inra-structure, population control, environmental sustainability, etc., rom the policy makers. Thus, while ourmayors ence away to make their respective cities as competitive as possible as business destinations, theymay are better i they heed this SimCity able!




fdi, CitiEs And CompEtitivEnEss

Sandeep Mann, COO, Remorphing writes about how cities can leverage their competitive position

to attract investment and what a long path Indian cities need to tread to really interest investors.

Anand Mahindra once stated that any region aspiring or a healthy incremental capital output ratio(ICOR) o 4, with the usual growth rate o 8%, needed reinvestments to the tune o 32%. Unor-tunately, no region has savings matching this gure, usually capping savings at 5-20%. Naturally,

this decit has to be plugged with oreign investment. All regions have to chase higher and more sus-tainable planes o prosperity; alling in line with a Nietzsche kind o directive to emerge as ‘exceptionalregions’ with ‘exceptional inhabitants’. Though the competitiveness o any region can be measured in di-erent ways, the enhancement o all such levels would always be uelled by urther investments.

The Gandhian thought that work remains so long as there is a tear in any eye is contemporarily

matched by initiatives that seek to provide a decent lie or workers and citizens be they rom Brasilia,Vladivostok or Hyderabad. Levels o afuence have been correlated with quanta o oreign direct invest-ments (FDI) received, whether the trigger was selfess service or ‘sacricing one’s own selshness viamaking all prosperous’.

Indeed, like any vanilla investment, FDI too is an investment by an investor in a specic industrial sec-tor, which is highly linked to geographical moorings, as in a parallel sense observed about internationaltrade by Ghemawat’s CAGE model. FDI would nd its appearance in industrial activity over a largetract o land, or setting up marketing channels or placement o oerings on buying shelves or consumersor industrial buyers; but it essentially resides in a city. The administrative unction o any commercialenterprise, willy-nilly, is based in a city, maybe with production acilities situated in the near or distant

precincts. Consequently, although FDI infuences the economy o a vast region per se, it emphatically in-fuences cities therein. So any city wishing to shoot up its competitiveness has to go gunning or FDI—orregions around it and or its own direct uplitment. The same goes or quasi-cities that spring up in andaround SEZs.

Data over the past years would indicate that a ranking can be developed or FDI attracted by variouscities, apportioned pro rata over their GDP onto the state’s FDI. This shows that the top winners are Delhi,Mumbai, Bengaluru and Hyderabad. However, as FDI winnings is a global canvas battle, Indian cities arear rom entering such ace-os with other cities in the world. For Indian cities, competitiveness via FDIstill carries a surrealist eel. Tangible realism needs to be brought orth.

It needs no vocierous proclaiming that there is a compelling urgency or all cities to project them-selves as branded destinations or FDI. Intense soul-searching and mapping o competitive positioning

alone shall enable every city to carve out its unique appeal as an investment destination, rather than aaceless, generic, monolithic we-are-open-to-all-kind o investments pitch. Aping the leading cities by thelaggards shall be surely a utile and counter-productive exercise.

As Proessor Porter illuminates, actor advantages are to be created not inherited. On the value chain,the regions that are actor-led scores lower than the ones that are eciency-led, which again score lowerthan the innovation-led regions. Indian cities have to discover where it is they have and can pitch orcompetitive advantages and advantages that can be sustainable. An integrated analytic look at the ourpillars o Porter’s Diamond Model, done careully, siting realistic assessments rom biases and political-ly-motivated slanting o acts, shall duly brighten the path ahead. For instance, why should Ahmedabad




ask or FDI in voice-based outsourcings, when it does not have suitable labor pool (as large as Bengaluru,Pune or Delhi). Instead, it should walk into showing itsel as the best destination or concept arbitrage, aknowledge kind o outsourcing, drawing on entrepreneurial and managerial traditions its people are verystrong on. Bengaluru can’t beat Hyderabad on cost o living index; why doesn’t it move its IT sector ontohigh-end priced services. Why can’t Jaipur be an all-season tourist hub, conceiving adventure sports or

its harsh summers? Ater all, cities in Arizona are as hot as Jaipur and still enjoy signicant tourism.Again, we have seen that attracting FDI is shadily managed by Indian cities and governments. In thisworld o online connectivity, no city has a decent tell-all website. Ironically, Holland maintains a betterFDI India site than does the Indian Union Government! There is no serious activity to associate an FDIinvestor with a local alliance partner; and how can that be done, there is no detailed proling o localentrepreneurs who can thus be brought together! Which city has a dedicated think tank tracking whatcycle industries are undergoing in various parts o the world? The investor is nothing other than an orga-nized or loosely-ormed think tank, acting or a large organization, seeking optimal or maximal returnson investment (RoI).

Is this FDI investor being reached? Some itsy-bitsy oreign tours with ministers and their entouragemeeting small pools o the Indian community abroad never do the trick. Is adequate aith being won over

by showing accountability and objectivity in governance, inspiring condence that investments wouldn’trun into hot weather down the line? I these questions make policy-makers squirm, the rst tentativeseedlings towards shaping competitiveness have been sowed.




pApErs And idEAsprEsEntEd At thE13 tCi GlobAl

CompEtitivEnEssConfErEnCE 2010, indiA




Examining Open Innovation PracticesAmong International Networks OfClusters Andersen, Lise, University of Southern Denmark Smith, Madeline, EKOS Ltd

Wise, Emily, Lund University, Sweden

Those who work with clusters spend time tryingto encourage collaborative behaviors between com-panies through trust-building, knowledge-sharingand learning. The social capital generated can makethe dierence between being just a group o compa-nies in the same sector, and being a truly innovative,growing and successul cluster.

The importance o social capital wasn’t always

at the heart o cluster approaches. Initial studiesocused on agglomeration, beneting the companiesthrough economies o scale, pools o specialized skillsand shared inrastructure. However, this spatial anal-ysis ailed to adequately explain the success o someindustrial groupings and the ailure o others.

It is thereore with interest that cluster practi-tioners and policymakers have viewed the rise oopen innovation, which acknowledges the require-ment or companies to collaborate beyond their or-ganizational boundaries. Open innovation builds on

the assumption that valuable ideas and knowledgecan emerge rom internal as well as external sourc-es and can enter the market rom inside or out-side the company. Thereore, companies that lookoutside their in-house resources have better accessto ideas, expertise and technology than those thatrely solely on in-house sources. In a global econ-omy, global links and connections are essential.Such connections help in the dissemination o newtechniques, acilitate the adoption o new practices

and the development o new products and customervalue. This undamental shit in behavior rom apreviously internally-controlled innovation processand mindset to a more open innovation process hasled a recent paper rom the Economist IntelligenceUnit to claim “the uture belongs to those who col-laborate...with many players, rom customers andpartners, to competitors, distributors and univer-sity researchers.”

Clusters play a key role in helping to build thosenetworks and connections. Clusters can be a valu-able means to bring the dierent knowledge triangleactors in an innovation system together, connectingcompanies to universities and research institutions.

Research-driven clusters build on the knowledgestrength o a region and through establishing link-ages, joint strategies and collaborations across theTriple Helix, help produce a route to exploitationrom those ideas. For policymakers, clusters are agreat opportunity to support this type o collabora-tive behavior, to help companies explore open in-novation, and help overcome barriers that preventcompanies engaging in this type o innovation.

Social capital plays an essential role in the pur-suit o open innovation collaborations, and many

companies are already stressing the importance oclusters when engaging in open innovations activi-ties with external actors.

It’s not surprising, then, that policymakers arebeginning to ask “What does social capital withinand between clusters have to do with open innova-tion practices? What role, i any, can policy play?”

The presentation introduces action research ona network o ICT clusters in the Baltic Sea Regionthat is scheduled commenced in early October. The

research will explore the role that cluster organiza-tions and other actors have in acilitating open inno-vation activities between companies in a cluster. Theresearch will also examine whether open innovationactivities within and between clusters support greatercollaboration within and among clusters thereby os-tering a stronger international innovation dynamic.

The action research will lever the cluster dynam-ics survey (introduced and discussed at previous TCIconerences) to examine social capital between clus-ters in an international context, as well as a newly

developed interview questionnaire to gain insightson open and user-driven innovation tools used bycompanies working in international contexts.

The aim o the presentation is to discuss and gainpeer perspectives on the research approach plannedor exploration o the ollowing research questions:a) Is it important to have strong internal cluster dy-

namics (i.e. social capital) beore pursuing openinnovation activities internationally?




b) Do open innovation activities between clusterscreate a stronger international innovation dy-namic?

c) Do existing policies support open innovation ac-tivities within a cluster and between clusters in-

ternationally?n What activities are undertaken by regional au-thorities in this regard?n What role is played by cluster organizations/in-termediaries?n What are companies’ perspectives on these poli-cies?

A urther challenge to be explored is whetherencouraging open innovation between clusters atan international scale threatens to undermine theinternal dynamics and growth o social capital with-

in a regional cluster. How can the best balance beachieved between building social capital and strongdynamics on a local level with sourcing knowledgeand working with open innovation practices inter-nationally?

The aim o the research is to gain a better un-derstanding o the interdependence between socialcapital, open innovation, cluster building and inter-nationalization. The role o social capital in open in-novation activities and cluster building will be looked

at, and social capital and open innovation processesunction in an international context will be exploredto gain a better understanding o how open innova-tion activities between clusters can contribute to astronger international innovation dynamic. Finally,how policies can support open innovation activitieswithin and between clusters in an international con-text will be explored.

Comparative Analysis of Marketing

Externalities and Process KnowledgeSpillovers Among Various IndustrialClusters Arbi, Khalil A.University of Management and Technology, Lahore

Fast-paced globalization has put corporate andSME rms under great pressure to maintain theircomparative advantage. Prevailing literature on

cluster development suggests that small and me-dium rms consider location as key point or theirsustainable comparative advantage. From variousstudies across the globe, businessmen take locationo their business as a undamental source o suc-

cess. It is claimed that networking and co-locationare big sources o business knowledge that are nec-essary to compete in the international market.

The studies done by Brown, P. et al (2010) andFelzensztein et al (2008) cover analysis o market-ing externalities across various geographical loca-tions. Studies done by Brown, P. cover electronicclusters o New Zealand in which the authors havegiven analysis o active and passive marketingexternalities. On the other hand, research romFelzensztein et al covers a comparative study o

salmon-arming industry cluster across two dier-ent geographic locations i.e. Scotland and Chile.Both studies have given a detailed analysis o mar-keting externalities, but the dierence among themis that one is conned to only a single geographiclocation, while the other takes into account onecluster in two dierent geographic locations. Theresults o both studies are somehow same with lit-tle dierences due to dierent nature o industrialclusters.

This research has been executed to make a com-parison o marketing externalities and productionprocess knowledge spillover across various indus-trial clusters o Pakistan. It is dierent rom theabove mentioned studies in many aspects. Here wehave taken our dierent industrial clusters in thePunjab province o Pakistan. Two o these clusters,surgical instrument and sports goods are ound inthe same geographical location o Sialkot, whereasthe other two cutlery and textile clusters are oundin Wazirabad and Faisalabad, respectively. The re-

sults rom these clusters will be multidimensionaland provide more in-depth knowledge about thebehavior o various rms working at the same aswell as in dierent locations. Interesting ndingswill come rom two dierent clusters working inthe same location.

The objective o the research is to provide ananalysis about how various rms working in thesame cluster dier with rms working in other




industrial clusters. Obviously there are dierenc-es and similarities o their behaviors. We want tocatch the nature o benets rom marketing andproduction process externalities that these rmscurrently enjoy. The results o this research will ex-

pose the underlying characteristics o various clus-ters situated at the same and at dierent locations.The research results will show the extent o benetsgained by rms across various locations and vari-ous disciplines o business. It has been statisticallyseen that the selected our industrial clusters havevaried perormance in the international market.Some o them are highly export-oriented whereassome are perorming airly in the internationalarena. The results o this research can also be usedto evaluate cluster perormance at an international

level. Along with export perormance, we have alsotried to catch innovation in the clusters as well.An increased networking and knowledge spilloverhas a logical consequence o increased innovation.In this research, our intention is also to gauge thelevel o innovation in each sector as well.

Clusters as Incubators for Innovation Bode, Alexander Hessenmetall Cluster-Initiative, Germany

During recent years clusters have gained muchattention rom both practitioners as well as re-searchers. The organization o clusters is regard-ed as one vital instrument or increasing competi-tiveness o member companies or even o a wholeregion. The underlying assumption is that col-laboration o companies that compete in dierentelds, the so-called “competition”, stimulates in-novation. Knowledge spillover among companies

rom a region shall result in a unique combinationo resources and a pool o knowledge. As a resulto this process, specic cluster companies achievea competitive advantage. However, one problemmany clusters ace is that they have trouble inacquiring money or the work they are providing.Many clusters are ounded by public unding e.g.in Europe by unds or regional development romthe European Union. This sponsorship ensures asucient cash fow or a certain period, mostly

three to ve years. However, ater the unding pe-riod most clusters got into trouble or they couldnot implement a sustainable business model. Themember companies are not willing to pay the totalcost o the cluster-coordination because the ben-

ets o the cooperation or the members are nottransparent or maybe too low to justiy the costs.Most clusters in the EU will disappear ater theunding period, i to they cannot deliver measur-able results or their members.

It is this paper’s aim to introduce a sustainablecluster model that delivers measurable and valu-able benets to its members. Hence, we like to in-troduce a model o a cluster with network charac-teristics that is used as a platorm or collaborativeinnovation activities.

The central constituent element o clusters,which is agreed upon, is the geographical concen-tration o its players. As is evident in literature,the (competition) relations between the players aresubject o ongoing discussions. Thereore, the re-lationship between the individual players o clus-ters can be anything rom competitive (respectivelynon-competitive) to cooperative.

Networks are characterized by the relations be-tween the parties, which are mainly o a coopera-

tive nature. The geographical expansion, however,is not a constitutive characteristic o networks.Production networks or example can span globallywhile innovation networks between suppliers andcustomers cover a smaller region. Networks mayprove to be an essential element o clusters. Thepresence o a cluster does not necessarily lead tothe establishment o a network.

These observations lead to two possible param-eters or classiying both clusters and networks:(1) geographical expansion—a network can be at

any point on the continuum between global and re-gional, while a cluster is concentrated in a region,and (2) intercompany relations—while a network isinitiated or close cooperation, companies within acluster can cover the total bandwidth between co-operation and competition.

The “cluster with network characteristics” isan approach that uses the most promising aspectso both concepts. As a prerequisite or generating




competitive advantage the cluster with networkcharacteristics is established among companiesrom one industry that have overlapping but com-plementary assets. The regional component acili-tates the control, as people rom one region see

each other again, and they may easily lose theirreputation they will not so easily be attracted by“ree-riding”.

The collaboration in a cluster with networkcharacteristics is based upon mutual trust. Estab-lishing trust is a work-intensive process that re-quires commitment rom all members. The level ovalue-generating activities within a cluster is close-ly linked to an increasing level o trust. As highvalue generation requires collaboration in eldswith core competencies, companies only open up

the heart o their company i they have condencein the other cluster members. Cluster activities inthe start-up phase are comprised o activities notcrucial to competition in order to slowly establishsome level o trust. Starting rom exchange o ex-periences on the market in general or the collabo-ration or sourcing o indirect materials lasting tosharing knowledge on general topics, or examplethe eect o the economic crisis.

Once a sucient level o trust is established, the

members can tackle more core activities leading tothe enlargement o the common knowledge base.This is also the starting point or joint technologyand R&D projects together with research institu-tions. As clusters are a pool o relevant playersrom one industry with complement resources andcompetences, this is the ideal pool or starting upintercompany innovation projects.

A certain level o trust is mandatory or col-laborative innovation projects. In order to establishtrust some prerequisites are necessary:n Participating companies need a phase or learn-ing and getting to know potential co-innovationpartnersn The number o cluster members should not betoo high so that it is possible to get to know every-body within a reasonable time ramen Open mindset o participating personsn Continuity in participating employees rom onecompany

n Eternal cluster-management, as an uncommit-ted coordinator

These prerequisites show that huge regionalclusters with 50 or more companies, organizingjust “get-togethers” are not the ideal platorm to

establish sucient trust. Thereore, such kind oclusters can’t be used to initiate intercompany in-novation projects. For establishing a platorm ortechnology-driven collaborative R&D projects,companies need a cluster with network charac-teristics that provides a smooth initiation phaseor trust building among a manageable numbero companies. The companies can see and mea-sure the benets o such an approach and aremore willing to pay or the benecial activitieso the cluster. All in all one can state that the

cluster with network characteristics is a sustain-able business model or an innovative cluster thatcreates benets or the member companies andor the region.

Analytical Framework towardsCompetitive Clusters Local EconomicDevelopment [CCLED]: Application toDelhiChoe, KyeongAe, Asian Development Bank Roberts, Brian, SPMS Australia

Cities play a signicant role in the economicdevelopment o Asian countries. The urban GDPper capita in most developing countries in Asia istwo-times greater than that in rural areas on anaverage. Within a decade, more than 50% o thepopulation o Asia will live in cities. By 2030, al-most all new jobs and wealth in Asian countrieswill be created in cities. This means that most o

the secondary and tertiary industry sectors are ag-glomerated in cities and city-regions, as the keyorces o the engine o economic growth.

In tandem, economic challenges in developingAsian countries have become more complex—urban populations are growing at great cost tothe environment; income gaps between countriesand urban and rural areas widening; and climatechange has increased risks o natural disasters.




These trends aect the sustainable industry growthand reduce the eectiveness o the local economicdevelopment.

Industries tend to locate where businesses canhave a competitive advantage, relying on cities’

competitiveness too. Cities oer shared accessto common inrastructure linking supply chainsand networks, and to required human resourcesand skills, which help to reduce production andtransaction costs. Yet, government resources arelimited to provide supporting inrastructure orrapidly growing urban areas and pose enormouschallenges. Governments and entrepreneurs inAsian cities need to nd ways to improve theircompetitiveness, i they are to maintain sustain-able development in a world where cities compete

or global trade and investment.Despite these backdrops, structured system-

atic inormation is hardly available to assistsurging industries and micro, small and mediumenterprises to achieve competitive clusters in andaround city-regions in Asia. How can Asian cit-ies and industries become more sustainable andmore competitive? What are the attributes thatmake their urban industries competitive? Howcan governments or development agencies iden-

tiy and strategically invest, to boost competi-tiveness and sustainability? I so, which industryclusters in which locality should get support un-der limited resources available? Most o theseissues have not been well assessed systematical-ly—until now.

An innovative new analytical ramework ex-amining clusters and competitiveness o cities hasbeen initiated and ormulated by the Asian Devel-opment Bank (ADB). The Competitive Cluster Lo-cal Economic Development (CCLED) approaches

to assess not only the strengths but also the de-ciency gaps in acilitating competitive industrialclusters, in a selected city-region. At the end, ac-tion plans are prepared or enhancing competi-tiveness o industry clusters and the cities.

This presentation will demonstrate the inno-vative analytical process o CCLED, applying the6-step method in the Delhi National Capital Terri-tory in India as a case study.

Step one: Ranking competitiveness

Major competitiveness actors with relevant attri-butes are prepared. In this case, ve key actorsare used (Ernst and Young, 2007)—city prosper-ity, urban governance, inrastructure, business

environment and quality o lie. Using weightedand aggregated scores rom the ve key competi-tiveness actors, a group o cities can be rankedor their competitiveness, and national average iscalculated as the benchmarking score.

Step two: Evaluating the key drivers o cit-

ies’ competitiveness

From the result o step one, a city (or a city-region) could be selected or its local economicdevelopment. The technique in step one details

out strengths and deciency gaps toward enhanc-ing competitiveness o the selected city within acountry. This result will be matched with the in-rastructure needs o the industry clusters, whichwill be identied at step ve.

Step three: Assessing structures and chang-

ing patterns o multisector industry in a se-

lected city-region

Using the government’s standard industry classi-cation, this step explores the prole o the in-

dustry; how the percentage distribution o localindustrial sectors in the city-region have changed(using location-quotient and shit-share tech-niques), by comparing census data o at least veyears interval. It demonstrates which industrysector is the largest contributor to the local econ-omy, and how industry sectors have been grow-ing or declining over time in the city-region. Thetop three employment-generating industries in theDelhi-region in 2005 were manuacturing (31%

o total employment), retail trade (25%) and ser-vices (16%).

Step our: Mapping the selected industry

clusters using GIS

Once key stakeholders determine which industryis to be invested in to increase competitiveness,those rms and enterprises in the selected indus-try-sector are geographically mapped out. Thisresult is useul or geographically locating clus-




ters in a city-region and or urther inrastructuresupports by the government. In the Delhi-region,automobile component manuacturing, generalmachinery/equipment manuacturing and textilesindustry-clusters were identied under the manu-

acturing industry.Step fve: Analyzing competitiveness o se-

lected industry clusters using Porter’s Dia-

mond Model

Each selected industry cluster is analyzed orits competitiveness using 39 attributes underthe ve actors o Porter’s Diamond Model. Forexample, in case o the textile industry-clusterin the Delhi-region, out o the 39 competitive-ness attributes, 72% have an average score o

less than 2.5 out o the maximum score at 5. Tocompete at the international textile market, allve competitiveness actors in the textile indus-try cluster in Delhi need to be improved abovethe score o 3.66.

Step six: Preparing business and action plans

or the selected industry cluster

The results rom step two and ve provide use-ul inormation in what the deciencies are tostrengthen the competitiveness o industry clus-

ters as well as supporting inrastructure in thecity-region. Key stakeholders pursuing urtherinterventions, based on the analysis results romthe previous steps, prepare a business plan. Actionplans are also prepared laying out priorities andurgencies to oster the competitiveness o industryclusters, as well as inrastructure needed or theselected industry cluster area. Pre-easibility in-vestment proposals can also be included or seek-ing investments by PPP, government or interna-

tional development agencies.The CCLED analysis ramework provides astrategic oundation that is useul to enhancecompetitiveness o the selected industry clusters,as well as helpul or inormed decision-makingby the government to decide where and what in-rastructure to provide rst, or ostering localeconomic development, important or Asian cit-ies in the context o a rapidly-changing globaleconomy.

Stimulating Transsectoral Innovation in‘Mature’ Clusters Eetgerink, Frank East Netherlands Development Agency (Oost NV)

The region East Netherlands (two provinces)accommodates three universities, acting as crys-tallization points o knowledge-intensive entre-preneurial activities and clusters. The clustersare well established with cluster organizationssupported by the triple helix partners. Food Val-ley is built on knowledge rom Wageningen Uni-versity and Research (WUR). Health Valley islocated at the campus o the Radboud University(RU) Nijmegen, close to the academic hospital

UMC St. Radboud. Innovation Platorm Twenteis based close to the Technical University Twente(TU). The three main cluster organizations areconnected through an innovation policy programTriangle o the provinces Gelderland and Overijs-sel. Triangle aims at stimulating the synergy be-tween the clusters through the unding o innova-tion projects.

Connecting the clusters there are three themes:bio-based economy (combining agroood and tech-nology), ood and health, and RedMedTech High-

way (medical technology, imaging, biomedical).These themes recently emerged out o the clusteractivities.

The regional innovation policy was quite suc-cessul in the last ew years. The cluster organiza-tions are in place and enjoy support and legitimacywith the regional partners. At the national level,the ood cluster is best recognized. The fipside othe coin is a tendency o clusters to institutional-ize into ‘sectors’, which is in a way counterproduc-

tive to open innovation and ‘neue Combinationen’.Clusters could develop into a state o lock-in, wheretransactions become suboptimal.

The region needs sectoral and economic diver-sity to balance too much dependency on spearheadsectors or big dominant companies. Transsectoralinnovations stimulate economic diversity, which isby denition related to variety.

A question to answer could be: how can a regionstimulate related variety through transsectoral in-




novations, how to keep networks and clusters openenough to prevent stagnation or lock-in?

A part o the answer can be ound in analyses odynamics in alliances and the groups/teams involvedin open innovation projects. All sorts o multi-party

collaborations, combinations o partners, exist inthe triple helix. I we understand the dynamics insuch groups, the agenda building, leadership, pat-terns o processes better, we could intervene andstimulate better.

The Triangle innovation policy grew out o‘Knowledge Mapping NEW Triangle’ (NEW =Nijmegen, Enschede, Wageningen). The startingpoint was the assumption that i you can identiy‘hot’ spots o cutting-edge knowledge or technolo-gies and the persons who are the leading and ac-

knowledged experts in these elds, and, i they donot know each other, you can connect and acili-tate them in research programs. This will with highprobability lead to new combinations o knowledgeand can eventually lead to innovations through con-nected businesses.

This approach could be combined with the po-tential market drive o societal challenges relevantor the main clusters, like ‘Feed the World’, ‘Re-newable energy and sustainable production’, ‘A-

ordable health care in an ageing society’ etc. Ora starting point can be a by denition be a trans-sectoral integrating theme, like Smart Living (ICT,domotica, smart energy, care, building, technicalinstallation, etc.).

Another challenge would be the international-ization o clusters trough international cross sectorcombinations o clusters. We are currently devel-oping a European project under the Interreg 4Bscheme addressing this subject.

Clusters 2.0: How to Think Positive andThink Big in a Crisis Period? Estévez, Joan Martí ACC1Ó, Catalonia Government

In Catalonia, cluster policy was started around1993 with a ocus on promoting strategic changein the 23 micro-clusters (narrow approach in smallgeographical areas) identied at that time. Since

then, there has been an interesting evolution ininter-cluster reinorcement—an open-cross innova-tion approach.

One o the most remarkable experiences we areinvolved in is a corporate entrepreneurship project

with 20 cluster leaders o the clusters we are devel-oping at the moment. Through this process we aregenerating a new community o inter-cluster lead-ers (ashion, ICT, motorcycles, pharmaceutical,ood, etc.) working together, sharing interests innew projects, which become new companies, havingthese leaders as investors. The result is, basically,the generation o new companies with an expectedhigh growth and a global reach, because they havethe powerul management skills and nance capac-ity o these leaders. These cluster leaders share the

view o thinking positive and big to get out o thecrisis through transormational projects.

Learning Clusters in Creative Environ-ments Haasis, Klaus MFG Baden-Württemberg mbh

In our days the business environment that wework in changes nearly every day. Globalization

causes developments that are hard to understandand even harder to oresee, the nancial crisis a-ects sectors you wouldn’t expect and two yearslater business again develops aster than ever. Tocope and keep track with such developments doingbusiness as usual isn’t enough—not or companiesand at least not or cluster initiatives.

The classic cluster management approach needsto be thought through and adapted. The Maniestoo the European Year o Creativity and Innova-

tion 2009 states that workplaces need to be trans-ormed into learning sites. More than ever, this ap-plies to cluster organizations. They have to supporttheir members in dicult times and open their eyesor strategic uture developments. New cluster ap-proaches shouldn’t only be business-oriented, butalso need an empathic component ocusing on in-dividual persons. The presentation addresses thesechallenges and will demonstrate how learning andchange processes can be organized.




We will look at two components that are essen-tial or learning organizations, knowledge manage-ment and relationship management—knowledgemanagement to learn rom and with each other,and relationship management meaning to trust

each other.Knowledge management

Peter Senge explains in “The Fith Discipline: TheArt and Practice o the Learning Organization”that a learning organization has to be skilled inspecic undamental disciplines. He describes vecomponents a “learning organization” requires:1. Personal mastery o one’s capacities2. Team learning through group discussion o indi-

vidual objectives and problems

3. Employees and managers are also encouragedto examine together their oten negative per-ceptions or “mental models” o company peopleand procedures

4. Shared vision5. Systems thinking

These principles support the “learning rom andwith each other” in organizations. This concept notonly applies to organizations, but also to regionsand clusters. The presentation gives an overviewon how to adapt this very appealing concept to acluster environment and why cluster managers andregional representatives will be well advised to im-plement it in their uture strategies.

Relationship management

One aspect that remains a key element o all suc-cessul clustering approaches is relationship man-agement and along with it the aspect o trust. Clus-ter actors need trust to learn rom each other andto benet rom collaboration and exchange.

Currently we nd people cautious about shar-ing their knowledge and inormation with eachother—a development also mirrored in Europe inpublic discussions on privacy issues o services like“Google Street View” or Facebook. Boundariesbetween open and closed, real and virtual becomemore blurred. How do we deal with that challenge?Creating a trustul environment or cluster organi-zations is a crucial rst step that can be supportedby dierent approaches:

n Appreciative inquiry, a concept brought to lie byDavid Cooperrider, serves to analyze the strengthso an organization and how to oster them. Thismethod promotes positive relationships and buildson the basic goodness in persons, situations or or-

ganizations. That way it enhances a system’s ca-pacity or collaboration and change.n The person-centered approach rom Carl Rog-ers, who was an infuential American psychologist,can contribute to create, ensure and increase trustbetween the dierent actors. Carl Rogers has devel-oped his own approach to understand personalityand human relationships, the so-called person-cen-tered approach. This approach ound wide appli-cation in various domains such as psychotherapyand counseling, education, organizations and other

group settings. It can be used as an eective toolor cluster management.n Positive psychology by Martin Seligman andMihaly Csikszentmihalyi is a branch o psychologythat seeks “to nd and nurture genius and talent”,and “to make normal lie more ullling” not sim-ply to treat mental illness.

Using the example o MFG as a well-experiencedcluster organization (recognized as “ExcellentKnowledge Organization” by the Federal Ministry

o Economics and Technology) and the CreativeIndustries in Baden-Württemberg, the presenta-tion will demonstrate dierent practical exampleson how to make use o the concepts introduced interms o regional and cluster management.

Internationalization of regional innova-tion networks Hyder, Akmal , University of Gävle, Sweden Roxenhall, Tommy, Mid Sweden University

It is becoming increasingly common or net-works o actors (universities, research institutes,enterprises and government organizations, etc.) tobe ormed in order to jointly develop innovations.Such networks are oten encouraged and nancedby regional and national authorities. However,more and more innovations are created betweenactors in the international arena. The regional in-novation networks must thereore be able to at-




tract international operators and investors, and torecruit individuals with key skills that are active inthe international market.

Studies show that regional innovation networkhas established relationships with international ac-

tors, but ew have knowledge o how to interna-tionalize it (Vinnova 2008). Furthermore, ongoingglobalization creates new challenges or process in-novation networks. Research institutions and com-panies are woven together in very complex networksthat cut across national boundaries. An increasednumber o companies that are continuously look-ing or research expertise around the world createconsiderable pressure on regional innovation net-works to enable them to compete with the leadinginnovation networks in the world. Paradoxically,

the regional innovation networks in their specicareas o expertise collaborate with world-leadinginnovation networks so that competitive knowledgeand skills are guaranteed.

In many cases, regional innovation networks areworking with many small businesses and they needto attract more oreign companies as partners. Thisis to help smaller companies to come out on oreignmarkets with technology solutions and productsthat smaller companies have developed in the re-

gional innovation system. This is o course not aneasy task or regional innovation networks as thereare many competitive players active in the globalmarket seeking international outlets. This com-plexity also explains why many regional companieswith high technological potential ail to grasp asatisactory position in the international market.It is our conviction that mere contact or certainaccess to other oreign networks is not adequate,regional networks need to establish some vital tieswith oreign partners or long-term collaboration

and development.In general, there is a lack o knowledge about

how regional innovation networks are internation-alized through collaboration with innovation net-works in other countries. The purpose o this projectis thereore to study such processes. The hub o aregional innovation network contacts their oreigncolleagues in order to create a partnership betweenthem by orming a strategic alliance. Once such a

vital alliance is established, it becomes easier ormember companies to identiy relevant partnersto establish dierent kind o contacts or gettinga oothold in the oreign market. By exploring theknowledge on internationalization o regional in-

novation networks, this work can make a practicalcontribution in organizing innovative companiesaround hub o their local networks and get ben-et o internationalization through long-term ties(strategic alliances) established with vital oreignpartners.

Arizona Nanotechnology: Our ClusterStrategy Kim, Matt QuantTera, Arizona

In general terms, nanotechnology, the scienceo the small, involves research and development oextremely small components and structures, andtranscends many disciplines. Semiconductor rms,or example, have process geometries approaching65 nanometers and require intense research anddevelopment to produce high quality integratedcircuits at those extremely small dimensions. Inmore specic terms, nanotechnology involves using

quantum properties that occur at very small sizes,and by utilizing these eects that arise rom smalldimensions it is possible to create structures thathave unique properties that are normally unrealiz-able in nature.

The presentation describes how the two maincategories o nanotechnology—nano-engineeringo the solid state and molecular nano-engineer-ing—allow the ormation o new types o manmadestructures and how it is possible to nano-engineer

the materials to enhance certain physical proper-ties, with applications o these materials to energy,biology and the environment.

With nanotechnology allowing or control andtailor making o materials properties, its impor-tance in Arizona, nationally and internationallywill be discussed. The Arizona NanotechnologyCluster promotes technology statewide or Arizo-na. How linkages to the general public, governmentand other organizations make or an important and




necessary base or economic technology develop-ment will be described.

New Approaches towards Cluster Man-agement Excellence

Köcker, Gerd Meier zu Agency Competence Networks, Germany

Clusters provide ertile ecosystems or compa-nies to thrive, which drives innovation, regional de-velopment and competitiveness. Ater many yearso eorts to develop clusters, the challenge today isnot to create more clusters, but rather to enhancethe competitiveness and sustainability o existingand new clusters, and to create more dynamic clus-ters with global reach.

One o the key questions today is how to better pro-mote clusters and how to make better use o excellentclusters in response to societal challenges. This wouldrequire shiting ocus rom supporting clusters to us-ing them more eectively. Clusters are said to pro-vide a more productive and innovative environmentor enterprises, and this could also be used to achievea higher impact o research and innovation support.The issue is not to consider clusters as privileged oreven exclusive partners or nding better solutions,

but to build upon and exploit the cluster concept,which is based on collaboration between companiesand research institutes and other institutions oeringknowledge to businesses. Thus, clusters and clusterorganizations must seek excellence in order to bet-ter serve the needs o enterprises and support theircompetitiveness; this should be the baseline objectiveo all cluster initiatives worldwide.

However, today enterprises and clusters ace newways o dealing with innovation and management

o knowledge in order to be ecient and success-ul in a more open‐knowledge environment. Clusterorganizations play an important role in catalyzingand acilitating action in cluster initiatives.

Promoting cluster excellence is o high rel-evance, especially or cluster managers. So ar,there are three approaches prevailing how to pro-mote cluster management excellence.n Benchmarking o cluster managements2 n European Cluster Excellence Initiative3

n Quality Frame4 Benchmarking organizational cluster manage-

ment perormance and the quality o cluster orga-nizations is already an accepted approach withinEurope. There is clear evidence that benchmarking

can lead to much better results than conventionalevaluation approaches. As benchmarking has to beunderstood as a voluntary comparison among clus-ter in order to stimulate mutual learning among theinvolved cluster management, it is not a new type oranking or rating. Furthermore, it is not policy-orscientic-driven.

The most common cluster management bench-marking approach was designed in 2007 by theAgency o Competence Networks Germany, in or-der to enable measurement, assessment and com-

parison between clusters’ perormance. Dedicatedocus is given to cluster organizations, but otheraspects related to the cluster ramework conditionsand cluster actors are also regarded.

The benchmarking approach is based on sevendimensions and 60 specic indicators:

n Cluster structuren Financing o cluster organizationn Typology and governancen

Diversity o services oered by the cluster or-ganizationn Output o servicesn International orientation and visibilityn Achievements and reputation

Besides the practical approach, the quality andcompleteness o the comparative portolio, againstthe individual cluster managements are compared,is the key success actor or benchmarking. Soar, the comparative portolio contains 85 clustersbenchmarked so ar. All o them ulll high quality

in order to be listed in this portolio. Clusters romvarious European countries are listed, like rom

2 Meier zu Köcker, Rosted (eds.), Promoting Cluster Excellence-

Measuring and Benchmarking the Quality o Cluster Organiza-

tions and Perormance o Clusters, Conerence Proceeding o

EC-Expert Workshop, 2010, http://www.clusterobservatory.

eu/index.php?id=102&nid=

3 http://www.cluster-excellence.eu4 http://www.iit-berlin.de/veroeentlichungen/quality-rame.pd




Austria, Denmark, Germany, Hungary, Norwayand Switzerland.

An additional key success actor or the recogni-tion o the benchmarking approach is the ollowingaspects that are regarded in the current approachn

Cluster managements can be benchmarkedagainst pre-selected groups with specic charac-teristics (technological domain-wise, size-wise,age-wise)n A fexible approach allows to encompass thebroad variety o clusters and cluster initiativesn A simple procedure consisting o a ace-to-acedialogue (max. hal-day) between the cluster man-agement and the Benchmarking Teamn The benchmarking is mainly addressed to thecluster management. It doesn’t provide inorma-

tion whether a publicly-unded cluster initiative hasmet the political objectives nor can substitute animpact assessment

The main objective o the European Cluster Ex-cellence Initiative (ECEI) is to gather key Euro-pean organizations in order to identiy and set upquality indicators and peer-assessments o clustermanagement. The ECEI aims at developing train-ing materials and setting up a relevant approachto label the quality o cluster organizations. Such

labeling is intended to support cluster managers inachieving high levels o excellence and succeedingin their peer-assessments. Besides, the ECEI will

then create and act as a club o proessionals andinstitutions promoting cluster management excel-lence. Figure 1 reveals the our key areas.

Quality rame stands as quite a new approach,which is based on a peer-assessment according to

the internationally recognized EFQM-Model (Eu-ropean Foundation or Quality Management). Thepresentation reveals the specic approach, how toset up the peer review groups and results

European Clusters Go International:Current Status and Key Success Fac-tors Köcker, Gerd Meier zu, Agency Competence Networks, Ger- many Müller, Lysann, Agency Competence Networks, Germany Zombori, Zita, POLUS Programme, Hungary

Creating stronger linkages between clustersin dierent locations that oer complementary

strengths is one o the most promising ways toget access to the most advanced technologies,best know-how or relevant markets. Changes inthe global economic environment are also makingcluster linkages on the international level more im-portant. As rms within clusters internationalizetheir activities in creative ways, it is important thatcluster initiatives and organizations (which supportthem) internationalize too. Policy makers on alllevels as well as cluster organizations give a lot oattention and make considerable eorts in order to

better internationalize clusters and their rms. Al-though, as evidence shows, most actors involved inclusters are interested in learning rom and devel-oping concrete activities with partners in other geo-graphical locations internationally, there is still alack o knowledge about main barriers and driversas well as about the progress made so ar. Futurepolicy supporting measures can only be eective ithe real demand o the cluster organizations andcluster rms are known.

The ndings presented here are the outcomeso the second European cluster poll in which morethan 100 clusters rom 11 countries participated.Dedicated attention was given to involve mainlymatured and internationally-competitive clusters.As the rst poll was made in 2007 and the Euro-pean cluster landscape and ramework conditionshave changed dramatically, the current ndingsshow what has been gained within the last threeyears and how the current challenges looks like.

Figure 1: The key areas o the European ClusterExcellence Initiative




The main ndings can be summarized like ol-lowing:n Cluster organizations in Europe are taking overmore and more responsibility to actively supporttheir cluster rms in internationalization matters.n

The barriers and enablers or internationaliza-tion did not change much over the last ew years.Financial and personnel shortages are still the mainhuddles, but quality o products and technologies isstill an important aspect.n Whereas the existence o an internationalizationstrategy was still an exception in 2007 (only 10%o the participating clusters had have such strategyset into orce), nowadays more clusters have an ap-propriate strategy in orce.n Most European clusters made considerable prog-

ress in going international with oten positive impacton the business development o the cluster rms.n There is clear evidence that cluster organizationsbeing in charge with internationalization matterson behal o the cluster rms perorm much betterin this respect than clusters where the cluster rmseel responsible to internationalize.n Whereas good progress in initiating internationalco-operations has been gained, little progress is re-ported o increasing international visibility and rep-

utation. This is considered a considerable challenge.n EC-unded projects with ocus on internation-alization matters have been very successul, i thebeneting cluster organizations really have a man-date to support cluster rms to go international.I not, those projects mostly ail and do not revealany positive impact on the cluster organizations orrespective rms.Based on the statistical evaluation and deepeningexpert interviews, there is clear evidence that clus-ter rms and cluster organizations tend to be more

successul in going international than others, i theollowing key success actors are ullled:n High competitiveness o the products and ser-vices provided by the cluster rmsn The cluster organization is ocially in chargeand has a mandate to support cluster rms goinginternationaln The cluster (organization) has developed andimplemented an internationalization strategy,

which is implemented and accepted by the clusterrms

The presentation will discuss the ndings men-tioned and also reveal that there are considerablecountry specic dierences although mainly the

most competitive clusters have been invited to thecluster poll. The ndings are expected to contributeto better understand how clusters and cluster or-ganizations should internationalize, what the mainkey success actors are and how policy makers canbetter support clusters and cluster organizationsgoing international.

The authors are convinced that the main ndingsare o relevance not only or the current situationin Europe rather than or all clusters world wideinterested in internationalizing their business.

The Road to Prosperity is Paved withInnovation: Embracing the Prosperity“Value Chain” McCord, Mark T. Deloitte Consulting, LLPUSAID Jordan Economic Development Program

The presentation discusses the eects o innova-tion on the creation o prosperity, as well as a ve-

pronged methodology or promoting innovation.This methodology ocuses on business development,research and development, access to nancing, de-velopment o a world-class workorce, and creationo an enabling environment that promotes innova-tion. This methodology is the common thread thatinnovation-oriented countries have used to build aculture o prosperity. The methodology is outlinedin order to promulgate the development o a pros-perity “value chain”, the premise o which is that

innovation drives productivity, thereby buildingcompetitiveness, which creates prosperity.The major themes o the presentation are:

n Linking innovation and prosperityA. I it isn’t broken, x it anyway: The practical

denition o innovation Innovation is the prac-tice o turning ideas into reality, thereby improv-ing process, outputs and ultimately prosperity.

B. Begin with the end in mind: The groundwork or




innovation is laid through the development o acohesive strategy that includes the involvemento the public and private sectors as well as aca-demia, and the implementation o the strategyin an organized manner to promote prosperity.

C. Acceleration is the Key: Innovation acceleratesa country’s ability to achieve impact targets bycreating a culture o prosperity.

D. Innovation’s Dirty Little Secret: Countries thatare known or innovation must continue to in-novate or they will not sustain the prosperity de-veloped through implementation o their initialstrategies.

n The prosperity value chainA. Innovation drives productivityB. Productivity builds competitiveness

C. Competitiveness creates prosperityD. Prosperity is sustained through innovation

The premise o the prosperity value chain is thatprosperity supports economic, social, and politicalstability, countries must continue to innovate tosustain prosperity, and that innovation must per-meate society, which comes through a change in theway citizens think about their quality o lie, theirgovernment, their economy, and ultimately theirvalue system.n

The innovation methodologyA. Develop a strategy: The development o an in-novation strategy must include infuential mem-bers o the public, private, and academic sectors,as well as civil society. Until a cohesive strategyis developed, other elements o the methodol-ogy cannot be implemented. The strategy shouldinclude a ocus on target sectors where innova-tion can make the country competitive and ulti-mately prosperous.

B. Develop a world-class workorce: Countries must

ocus on core sectors and develop a workorcewithin these sectors that will promote competi-tiveness. Development o the workorce has tocome beore other elements o the methodologyin order to lay the oundation or success.

C. Develop a supportive enabling environment: Thecatalyst or innovation can come either romthe private sector (as in the case o Nokia inFinland) or the public sector (as in the cases o

Ireland and New Zealand). However, a publicsector must collaborate with the private sectorto develop an enabling environment that sup-ports innovation and ultimately the creation oprosperity.

D. Business development: Innovation begins at“home”, meaning that i local companies beginto innovate, thereby moving up the prosperityvalue chain, signicant impact will be created inthe areas o job creation, revenue enhancementsand public support. This will create a “mass” oinnovative and competitive companies that willin turn create opportunities or oreign directinvestment.

E. Support or research and development: For in-novation to take root, a country must develop

signicant support or research and developmentby building alliances between the academic com-munity, the private sector and the government.

F. Access to nancing: Access to capital is cru-cial i companies and ultimately countries areto move up the prosperity value chain. This in-cludes, but is not limited to, start up capital, an-gel networks, research and development undingand other mechanisms designed to promote in-novation.

n

Conclusions:A. Prosperity trickles down not up: Countriesmust ocus on high value jobs that are creat-ed through innovative approaches in targetedsectors. High value jobs will create economicopportunities throughout the strata o society,thereby increasing prosperity. The premise isthat poverty alleviation programs, which havelong been a staple o development in emergingmarkets, will not build prosperity because theydo not promote innovation and/or productivity.

They do not build competitiveness, but simplymake countries “less poor”.

B. Innovation is like cellular division: Innovationhas to continue in order or countries to main-tain prosperity, which means that mental modelshave to be changed and that there must be broad-based support or innovation throughout society.

C. Every day without innovation is another day oalling behind: The gap between countries around




the world is widening. Thereore, it is time to stopthinking about the development o an innovativeculture and move on with making it happen.

Cluster Research in Norwegian

Regions: The Case of the NorwegianWater Cluster Normann, Anne Katrine Research Council of Norway

The presentation has two interlinked parts; oneis on the Program or Regional R&D and Innovation(Norwegian acronym: VRI), which is the ResearchCouncil o Norway’s main support mechanism orresearch and innovation in Norway’s regions; theother part is a presentation o a case study—the

creation o a water cluster, which has been undedby this program. Here the method or developinglearning networks is central.

VRI is one o the main programs unding inno-vation and organization research. VRI encouragesinnovation, knowledge development, and addedvalue through regional cooperation and a strength-ened research and development eort within andor the regions. The program’s time-rame is tenyears (2007-2017), and it oers proessional andnancial support to long-term, research-based de-

velopment processes in the regions. It is designedto promote greater regional collaboration betweentrade and industry, R&D institutions and the gov-ernment authorities, and to establish close ties toother national and international network and inno-vation measures. Fundamental components o theVRI program include research activity, exchangeo experience, learning, and cooperation acrossscientic, proessional and administrative bound-aries. Results o the unded research projects are

an indicator o the success o this kind o researchprogram and unding mechanisms.Innovative networks and clusters have been the

subject o extensive research, while there is less re-search on how they develop. It is debatable to whatextent it is possible to impact on and manage thedevelopment process o clusters. The assumptionhere is that while it is not possible to manage, itis possible to spark mechanisms that support and

stimulate the cluster development process. Thismust be done according to the participants’ needs,and building legitimacy is a vital part o the pro-cess. Legitimacy and trust are intertwined. An as-sumption is that development o trust is essential

or the establishment o regional networks. Net-work IGP (individual, in group and in plenary) andnetwork refections are methods that can developtrust through organizing persons rom dierententerprises to partake in individual and collectiverefection processes. These methods have proven tohave a positive eect on the development o inno-vative networks. IGP unction as meeting places,and implies that the participants are rom dierententerprises; group work with persons rom dierententerprises; people rotate or each group work so

that people that are new to each other have to col-laborate. Optimal organizational learning process-es are assumed to be achieved through a combina-tion o individual and collective processes, which isconducive to high levels o innovation.

The case is the water cluster in the VRI region oVestold in Southern Norway, where 20 core rmsorm the cluster. The research poses the questionwhether social researchers can contribute directlyto the development o inter-rm networks, condu-

cive to an industrial cluster. Furthermore, whichmethods are adequate or acilitating networksamong knowledge-intensive small and medium-sized enterprises? The method chosen is decisiveor the process o developing networks. The methodneeds to center on ways to impact on and developinterpersonal relations. The nature o interpersonalrelations has an impact on innovation. It is not su-cient to be innovative in terms o products. Theproduction o services is rapidly expanding and itis necessary to work smarter, and hence, process

innovation becomes increasingly more important.Process innovation depends on abstract, tacit andcontextual knowledge. Such knowledge can only beshared through interaction, and hence, the devel-opment o personal relations and social networkscan be an ecient innovation strategy. The natureo interaction depends on, among other actors,geographical distance. Geographical proximitybetween enterprises makes interaction easier than






a daily basis. Networking/partnering/clustering iswithout a doubt one o the strategies that can beused in various cases or various purposes. However,a company usually does not possess such knowledgeon the appropriate networking/partnering/cluster-

ing orm or later the implementation. Governmentalsupport usually reers either to clusters or techno-logical platorms, while the other orms are prac-tically not promoted. This is appropriate in certaincases, but rom the viewpoint o consultants andcompanies, this is at the same time also a “trap”, asespecially small and medium-sized companies do notdecide at the same time or only also or other typeso networking/partnering/clustering, which might beeven more appropriate or their own cases. The ap-propriate orm or perhaps more orms o network-

ing/partnering/clustering at the same time, as wellas management adapted to this has a important in-fuence on the development or even competitivenesso an individual company or a group o connectedcompanies.

The next question that arises in the process onetworking/partnering/clustering is connected tovarious aspects o networking/partnering/clustering,which can be classied under general managerialaspects (e.g. legal-ormal, nancial, HR, etc.), and

numerous other aspects, among which are regional,sector-based aspects and the aspects connected withthe basic purpose o networking/partnering/cluster-ing, i.e. the interest or economic aspect, innovationaspect, knowledge-sharing aspect, perhaps the as-pect o internationalization, etc. This is actually thecentral element o connecting that originates romthe purpose o networking/partnering/clustering,and also substantially aects the selected network-ing/partnering/clustering orm, networking/partner-ing/clustering management, the selection o methods

and tools, and others.I we analyze the needs or the appropriate

management style or the necessary methods andtools with regard to the current phase o the lie-cycle o networking/partnering/clustering devel-opment, or i we analyze the trends in the envi-ronment or all previous elements o the modelor trends in relation to the selected combination,we perhaps get the recommended business, orga-

nizational and managerial model and the recom-mended methods and tools.

Researching combinations that originate romthe research model bring numerous new questionsto light, as well as new development challenges o

the networking/partnering/clustering management,or example:n Can we similarly to technology transers, wherewe can successully transer technology even romone sector into a completely new, seemingly non-complementary sector, develop also a business, or-ganizational or managerial model o networking/ partnering/clustering and related methods and tools,which is transerred rom one networking/partner-ing/clustering orm into a completely dierent net-working/partnering/clustering orm even or a di-

erent purpose? Can we learn something rom goodor bad practices, good or bad training programs, orapplied methods and tools introduced in strategic al-liances, and transer part or all o these experiences,good practices, methods and tools to clusters or per-haps technology platorms, cooperatives, etc. I yes,in which cases and in what way?n In what way and which trends should be moni-tored, or which are the trends that most aect themanagement and methods and tools in a network?n

Which methods and tools will be necessary orsuccessul networking/partnering/clustering o com-panies or networking/partnering/clustering manage-ment in the uture, and do potential governmentalinitiatives or the development o these methods andtools meet the trends?n In what way should companies, consultants andalso those oering governmental or other supportto companies be taught that the issue o network-ing/partnering/clustering is complex, and that itthereore should also be treated this way, and that

proessional management correspondingly qualiedor networking/partnering/clustering management isnecessary especially or some individual networking/ partnering/clustering orms or perhaps according toan individual combination o elements evident in thegraph?

There are many other questions and developmentchallenges arising, yet all probably demand moremanagerial dynamics than what we are used to.




Links between Business Competenceand Learning Networks: TheoreticalModel Rissanen, RiittaSavonia University of Applied Sciences, Finland

Business competence and capability to use andcreate knowledge in learning networks are in a keyrole among business leadership skills. Especially,past research in management (Nonaka, von Krogh& Voelpel, 2006; Doz & Kosonen, 2007, Prahalad& Krishanan, 2008) emphasizes the meaning ostrategic competences, learning, networking andinnovation as a success actor in various businesscontexts. Earlier studies have ound the connection

between dynamic capabilities and organizationallearning as a source o innovation-based strategy,where management can eectively coordinate in-ternal and external competences and create newcompetences (Teece, Pisano, Suen, 1997; Zollo &Winter, 2002). Furthermore, empirical researchresults show (Ritter, 1999), that such actors asavailability o internal resources, network orienta-tion o human resources management, integrationo communication culture and openness o corpo-rate culture, infuence a company’s network com-

petence.Learning organizations (Senge, 1990) and net-

works (Tidd, Bessant, Pavitt, 2005) have a key rolein sharing knowledge and learning to design alli-ances. In successul alliances, the people-relatedactors or competences, or example creation otrust and inormal networking, are signicant.

The theoretical orientation o this paper encour-ages diverse approaches o business competences,learning networks and innovation perormance,

into to the same eld o discussion, in order to laythe oundation or later empirical testing. This pa-per aims at giving a conceptual basis o “businesscompetence” and “learning network” or utureempirical research, as well as attempts to identiythe components o a theoretical model.

This study attempts to answer the ollowingquestions—how the concept o business competenceand the concept o learning network is dened andveried empirically in previous research, and what

are the links and interaction between these twoconcepts.

Funding Innovation in Atacama, Chile:Where the Money Comes From

Salvador, Marynella Atacama Regional Development Agency, Chile

Implementing competitiveness programs andinnovative initiatives with a regional and localperspective, sometimes represent problems thatgo ar beyond putting in place perect methodolo-gies and to have in place social capital, becausewhat it is needed in practice is unding in orderto put in place actions and projects that would beable to keep the energy o the process and the con-dence o both the private and the public sector.

Atacama Regional Government, under the Inno-vation Fund or Competitiveness (FIC), released therst public competition to und innovative projectsto promote and develop economic and institutionalenvironments that encourage innovation in the re-gion.

In a process never held beore, the Atacama Re-gional Council, through its Commission o Scienceand Technology, the Regional Government and the

Regional Development Agency (ARDP) developedthe basis o a contest that responds to a vision othe requirements o the territory and innovationneeds o the region.

In this contest may participate universities(state or recognized by the state), or institutes,technology centers, public or private, having suit-able human and material resources as well as ex-perience in research, technological development,transer and technology diusion, and whose main

activity is research, technological development andtranser and technology diusion.The projects should be ramed in the axes de-

ned as strategic by the Regional Government,which are contained in the Regional InnovationAgenda 2010, prepared by the ARDP, ater exami-nation and evaluation o regional experts. The ini-tiatives presented in this contest, shall be designedto promote science, applied research, innovativeentrepreneurship, development, dissemination and




technology transer, including or the strengthen-ing o regional innovation networks, training andattracting skilled human resources, inrastructureand equipment support and promotion o culturetowards innovation and entrepreneurship.

In the case o the Atacama region, the overallamount available or this item is $ 671,633,100,approx. 1.4 million dollars.

The FIC is a nancing tool or the implementa-tion o national and regional innovation, aimed atstrengthening the national innovation system andin regions, providing transparency, fexibility andstrategic direction or public action by the State.Thus, this und is the main instrument to providenew and additional resources to the various eortsthat the State is doing around innovation.

With this orientation, the instrument is joiningthe regional institutions in the process o strategicdecision on the issue o innovation and resource al-location, under the leadership o the Regional Gov-ernments (Gores), rom the provisions o the Bud-get Law Public Sector, which states that they denethe destination o the resources available, takinginto account the National Innovation Strategy orCompetitiveness, the respective Regional Develop-ment Strategy (ERD), the Strategic Innovation and

Improvement Plans Competitiveness (PMC).From the point o view o local innovation andcompetitiveness, this case marks a milestone ordecentralization in the management o public undswith resources rom the FIC. On the one hand,accredited institutions can submit projects thatstrengthen regional capacities and networks or in-novation, training and attracting skilled human re-sources, inrastructure and equipment support andpromotion o culture towards innovation and entre-preneurship. On the other hand, is in innovation,

where indicators o competitiveness place Atacamain eighth place (2008 SUBDERE CompetitivenessIndicator), the percentage o public unding allo-cated to I+D+ is relatively low, o the 15 regionsoccupied last, there are 21 doctors, which placesit at number 13; not le patents which places it inlast place, along with three other regions.

Thereore, we are working o the quartile model:government, private sector, technological institution

and nancial issues, in a technical model that ac-knowledges the gaps and constraints that currentlyexist in the region to innovate the requirements ora qualitative leap and streamline—a model thatrecognizes the particular character o innovation

according to a regional but global vision, and hasalso been built on the basis o an agenda that waselaborated with a bottom up technique.

Thus, through this competition, the innovativeculture will be strengthened, implementing andtranserring methods to activate the regional sys-tem, generating elements to balance economic de-velopment depending on the conditions o the terri-tory in respect o water, energy and environment.

It is being considered that people are importantor innovation and competitiveness so it is impor-

tant to attract, develop, strengthen and maintainskills, promoting, inter alia, training initiatives andadvanced technical work or innovation throughprograms—construction and updating maps o ap-plied skills in the regional productive sector, seto researchers in industry, specialized internshipsand technological development, dissemination andtranser o best business practices in innovation.

These are some o the lines to which institu-tions can access a proposal that is expected to be

welcomed and represents a clear eort to shit to-wards decentralization o productive innovation,towards increasing business initiatives to improveproductivity and boost the regional economy on asustained basis as a contribution rom Atacama toa more developed Chile in 2020.

Emerging Business Clusters in RussianToys and Baby-Goods IndustrySheresheva, Marina, State University - Higher School of

Economics, RussiaGorokhov, Dmitry, State University - Higher School of Eco- nomics, Russia

The purpose o the paper is to analyze the caseo building relationships within the Russian toys andbaby-goods industry. Ater all the macroeconomicand political changes o the past decades in Russia,the industry was heavily damaged. At the beginning




o the decade Russian toys and baby-goods produc-ers seemed to have no competitive advantages atall. Their market share has allen to less than 10%o the ast growing Russian toys and baby-goodsmarket (14 to 20% per year).

The situation in the market began to change re-cently. The most active rms o the industry start-ed to build intensive relationships aiming to raisecompetitiveness in Russia and abroad. Russian toysand baby-goods producers and retailers started tocreate win-win situations considering each other ascollaborators, not as adversaries. There are someobvious results o such activity. Relational assetsbuilt by actors that now appraise the role o inten-sive relationships helped them to strengthen theirconsolidated position and to gain governmental

support o their initiatives as well as to create newvalue by combining complementary assets and keycompetencies.

The paper presents the results o preliminaryresearch carried out by means o in-depth inter-views conducted with top managers, as well asinterviews with industry experts. The study isbased on the IMP network approach that oersa solid ground to observe network relationshipsin which economic actors are involved. Looking

at the changes in the industry and analyzing therecent evolution o inter-rm networking, we aimto nd out which orms o long-term relationshipsare the most promising or the industry in modernconditions. What orms o inter-organizationalcooperation can better help Russian toys and ba-by-goods enterprises to gain sustainable competi-tive advantage and to ght the problems broughtby the world economic crisis?

The paper is organized around the ollowingtopics. Firstly, it ocuses on the literature on the

subject, ollowed by a brie overview o the de-velopments in the Russian toys and baby-goodsindustry pointing out some industry-specic andcountry-specic eatures and showing the trend toreappraisal o long-term inter-organizational rela-tionships, regarded now as one o the main actorso success. It also aims to discuss some results othe research paying main attention to recent initia-tives in clustering and their possible eects on the

competitiveness and prot-generating capacity ocooperating actors.

What is the Role of Government in Cre-ating Prosperity in the New Economy?

Singh, IndiraOntario Mineral Industry Cluster Council

Governments around the world aspire to createprosperity or their citizens but, over time, very ewhave been successul in achieving and sustainingthis goal. The presentation will ocus on what con-stitutes prosperity, what are its key components,and how governments can activate and harnessthem. In this context, a number o government pol-icies, programs and interventions will be exploredand presented to illuminate the pivotal role o gov-ernments at the ederal, provincial, and regional/ municipal levels as they participate in the creationo enduring prosperity.

Internationalization Initiatives withinClusters: Both the Means and the EndSolé, Albert Cluster Development, Barcelona

Boosting exports is usually seen as one o thetop goals within a cluster. Not surprisingly, a groupo local companies within a region and a valuechain is better equipped to compete in the glob-al arena when cluster dynamics are in place andSMEs tackle strategic common needs collabora-tively. Nevertheless, internationalization is morethan that. Field experience increasingly tells ushow clusters turn to internationalization in orderto strengthen cluster strategies that will improve

and sustain overall competitiveness. Just like the‘cluster’ concept, internationalization thereore be-comes the ‘means’ to an end (competitiveness), notan end in itsel.

The ocus o the presentation is to demonstratethe above by means o cases and examples that al-low the audience to amiliarize them with clusterpractice cases, and get inspired by the ongoing ap-plications o cluster initiatives worldwide.




Two key concepts discussed are international-ization as the ‘means’ to strengthen cluster strate-gies, and internationalization and access to globalmarkets as the natural goal o any cluster. Inter-nationalization sustains and enriches the execution

o the strategies or the uture by improving thevalue chain o its member companies with interna-tional initiatives and alliances. On the other hand,in an increasingly globalized economy, the interna-tional component must be inherent to any cluster’sstrategic plan. In a cluster development project,companies are more condent and committed tocollaborate in non-local markets. Both these thingsare done with the ultimate goal o increasing com-petitiveness in a global context.

The presentation introduces examples in the ol-

lowing two areas, classic export-oriented set andmore strategy support ones.

Initiatives to increase sales by expanding into in-

ternational markets

n International public procurementn institutional support to oster Cluster initiativesin strategic countriesn Inter-cluster collaboration in third marketsn Representation in strategic markets

Initiatives to reinorce strategy

n By strengthening competitiveness along the val-ue chain

-Delocalization o phases o the value chain-Joint productive internationalization

n By innovating in product design and manuac-turing

-Penetration o markets with sophisticated de-mand (test your product or service)

-Partnerships, alliances and consortiums with

companies o superior know-how or technology oninternational projects / programs

-Gain access to the consumption habits o theend consumer in order to innovate in product/ser-vicen By excelling at the raw materials sourcing

-Grant access to key raw materialsSpecial attention is given to cross-national, in-

ter-cluster collaboration, a eld where cluster de-

velopment is increasingly getting involved through-out Europe. The case o solar power clusters inSpain and France that collaborate to penetratethird countries around the Mediterranean basin,taking advantage o geographical and cultural

links, with complementary specializations alongthe value chain, and the establishment o Europeandecision-making institutions being headquarteredin both Barcelona and Marseille.

In addition, a third section explores how region-al development agencies can support the interna-tionalization process o companies and how clus-ters acilitate this public-private eort. Based onour years o experience being in charge o sectoralpolicies at the Catalan Competitiveness Agency,examples o how a cluster approach had helped

the agency to tackle initiatives that were in actin position to better assist the real strategic needso the companies, and optimized public resourcesto support the companies’ long-term strategies areintroduced.

Long-term Sustainability of Cluster ini-tiatives: The Cluster Innovation SystemSolé, Albert Cluster Development, Barcelona

Cluster Development’s high degree o special-ization and the act that, throughout its history, therm sustained long-term relationships with a widearray o public-sector clients has gradually trig-gered the materialization o cluster developmentprojects that, because o its approach and nature,are at the ront line o the cluster arena at presenttimes. That is to say, experienced clients with clus-ter experts on their teams (rom regional govern-

ments to local development agencies) increasinglyrequire to take the cluster concept one step or-ward, dening solutions to guarantee the cluster’sability to collaboratively identiy and implementthose initiatives that better serve winning competi-tive strategies.

Generally speaking, clusters are developed ol-lowing this basic methodological process:0. Strategy development: Shared vision and discus-

sion on the strategic ocus o the cluster




1. Cluster activation: Formalization and articula-tion o the cluster, with transer o leadershiprom the sponsor o the initiative to cluster com-panies and institutions

2. Cluster innovation system: Systematization o

promotion and management o projects withinthe cluster and consolidation o the visibilityand international positioning o the clusterStep number 2 will be the goal o the presenta-

tion. Those cases in which the cluster manages andparticipating companies and institutions manage tosustain the innovation-driven collaborative dynam-ics, to later draw the theoretical conclusions basedon eld experience (not the other way around) willbe outlined. Oten times we see how a cluster initia-tive successully manages to kick-start the process

and captures the ‘momentum’ to deliver short-termaction initiatives. The real challenge, though, ishow to bring into the ormula the proper struc-tures, leadership and support to do that on a regu-lar basis, and without missing the strategic ocusthe cluster needs.

Given that Cluster Development SL works withboth emerging and mature clusters, it is with thissecond group particularly that we have learn thedos and don’ts o long-term cluster dynamization,

and the purpose o this presentation is to conveyour learning experience in this eld.

How to establish a cluster innovation system

The training o the cluster manager is not enough toguarantee that the cluster aithully ollows a road-map towards the shared vision and, more so, that itis able to reinvent itsel and rene the strategy asinescapable changes take place in global business.It is not a matter o the cluster manager’s abilityalone, as that ‘roadmap’ is seldom a detailed plan

that goes beyond the rst year o implementation.Rather, the enduring cluster operations and process-es require that a specic set o ingredients are inplace in order to oster the continuous mushroom-ing and implementation o strategic projects withinthe cluster. Thereore, it is imperative to establisha working methodology that goes beyond the mereacilitation o group discussions. This methodologywill have to encompass three basic areas and three

dierent phases towards the generation o strategicprojects:

Area 1: Strategic content

The strategic content deals with the ongoing abil-

ity to continuously identiy, structure and developthose key areas o special interest or cluster com-panies that better support the strategic rameworkagreed upon during the activation o the cluster.Unlike other tools used to identiy the current stra-tegic position o a cluster (oten criticized or beingtoo ‘static’), the proposed working scheme has todo with building on successes and ailures o pre-vious years. The strategic content must noticeablyinfuence the annual calendar o cluster activitiesand projects.

Area 2: Process

The process development has a dual objective—among cluster companies, rst, and internation-ally speaking as well. Oten times the local valuechain is not comprehensive enough, orcing us tolook overseas and to establish strategic alliancesamong clusters in order to develop state-o-the-artor excellent projects.

Area 3: CommunicationThe communication process is key to the cluster’snational and international visibility and to acili-tate the integration o new members and to estab-lish linkages with other clusters and internationalnetworks o experts.

The methodology is divided into three phases,each one consisting o dierent tools to generatecontent, to establish a cluster’s network o innova-tion (process), and or the visibility and positioningo the cluster (communication). The phases are the

ollowing:n To establish a technology monitoring and com-petitive intelligence system

It has to do with the denition and updating ostrategies or the uture o the cluster. It is nurturedby the continuous exposure to business trends andinternational best practices that may infuence thekey success actors within a business segment. Thisactivity does not need to be done constantly, but the




platorm or debate and discussion must be takeninto account.n To reach consensus on and denition o the di-erent areas to developn To identiy and select those projects that must be

pursued immediately because either they representshort-term opportunities or because o strategicrelevancen To establish a process or the execution o proj-ects

The project management process o those proj-ects identied in the previous phase has to be spe-cic, measurable and duly timed. It has to allowor a diversity o company typologies (with dierentcapacities and resources) to participate according tothe initiative, main objective and included tasks.

Improving Competitiveness and Innova-tion Through Better Cluster Manage-mentStürzebecher, Daniel Project Manager, Cluster Excellence, MFG Baden-Württem- berg mbH

How can cluster initiatives be managed proes-sionally? And what skills do cluster managers needwhen striving or cluster excellence? These ques-tions are being explored by the consortium aroundCluster-Excellence.eu—the European Cluster Ex-cellence Initiative, a PRO INNO Europe Projectlead by IESE Business School, University o Na-varra. Thirteen project partners rom nine coun-tries—all well experienced in the eld o clustermanagement and support—create a uniorm set ocluster quality indicators and develop a label orpromoting excellence in cluster management. The

European Cluster Managers’ Club and the Cluster-Collaboration Platorm set up within the rame-work o Cluster-Excellence.eu are modules to os-ter excellence in cluster management.

Today, everybody can claim him or hersel to be acluster manager. While management at the compa-ny level has been developed as a science by businessschools across the world, the skills needed or clustermanagement are still in a nascent stage. They are

only transmitted rom master to apprentice basedon experience on good judgement in codied knowl-edge. Cluster excellence means a more ecientcluster management that ollows a methodologicalapproach. Needless to say that better cluster man-

agement not only serves the companies involved butresults in a more ecient use o public unds pro-vided through cluster organizations. All modules oCluster-Excellence.eu, thereore, target those clus-ter organizations who want to become excellent.

In order to make clusters competitive, the excel-lence o cluster management organizations has to beimproved based on the given ramework conditions.The promotion o high quality standards o cluster-related activities and services could be one o themain approaches to make cluster management more

ecient. But to translate this overall goal into real-ity, a precondition is to make excellent cluster man-agement measureable beore it can be improved.

Cluster-Excellence.eu thus is structured arounda set o indicators that will dene “quality clustermanagement”. The cluster quality label developedwithin the project will be based on these indicators.The overall approach is to create an independent,voluntary proo o cluster management excellencethat is accepted and recognised all over Europe. The

quality label will motivate cluster managers to com-pare with each other and to learn rom the best. Itis applicable or all dierent types o clusters exist-ing all over Europe and will enable cluster managersto demonstrate their excellence towards interestedthird parties like members, stakeholders and policymakers. The ollowing aspects are important to pointout, in order to clariy the intention o the label:n The quality Label ocuses on cluster manage-ment, not on the ramework conditions or a clusteras such.n It is based on a modular set o quality indicatorsand a transparent process o how to benchmarkthem.n The quality label is voluntary and enables clustermanagers to receive proo o their cluster manage-ment excellence by an independent third body ac-cording to clear indicators.

The European Cluster Managers’ Club and theEuropean Cluster Collaboration Platorm, both




modules in the ramework o Cluster-Excellence.eu,will support and promote the adoption o the label.

The Club will be the rst proessional associa-tion or cluster managers striving or excellence.It will provide dierent services to improve cluster

managers’ skills. These range rom the promotiono the label and the training materials to tailoredactivities like workshops and case studies on issueso special concern or cluster managers.

Clustering in the Republic of MacedoniaTrajanoska, Nikolina Ministry of Economy, Republic of Macedonia

Clustering represents a new, airly unknownmethod or economic development and busi-ness partnership in the Republic o Macedonia.According to the research, three actors can beidentied that are critical or the development osuccessul clusters in the region:1. The presence o unctioning networks and

partnerships2. A strong innovation base, with supporting

R&D activities where appropriate3. The existence o a strong skills base

Assessment o current situationThe process o clustering in the Republic o Mace-donia started in 2002 with the support o USAIDproject Macedonia Competitiveness Activities(2002-2006).

2002: Mapping, identifcation o potential clusters

Conclusion rom the mapping exercise: Cultureo cooperation is low but there are groups withpotential or cluster development

Strategic decision: “Bottom-up approach”,

learning by doing

2004: Pilot projects

Start with the pilot projects, invitation or the in-terested groups to become pilots

Selection o ve projects with the highest in-terest and potential2007/2009: Cluster policy design (Ministry o

Economy)

Cluster development program

Direct measures:

n Incentives or networking: Specialization invalued/production chains, development o tech-nology networksn

Promotion o networking: Network o experts,management support in development o “localclusters”, experiences exchangen Incentives or cluster development: Supportor initial phase (one year), support in develop-ment (two years)

Indirect measures:

n Incentives or investment in R&D: Industrialresearch, technology investment or groups ocompanies and R&D institutionsn Incentives or productivity increase measures:Introduction o new management tools, qualitystandards and continuous improvement systemsin value/production chain

Several cluster initiatives are already oper-ating in Macedonia—textiles, inormation tech-nology, wine, tourism, lamb meat, sheep cheese,agricultural mechanization, automotive compo-nents, wood processing, ood-processing, ashiondesign, etc. These clusters are at various stages o

development and as such need specic support tourther accelerate their development.The key weakness that all existing Macedo-

nian clusters share is a lack o potential or inno-vation, development o new products and servicesto compete better in the global markets. Existingclusters have mainly been created with the pur-pose o “grouping o small enterprises” to bettersell on the markets and have done much less in thearea o sharing and creating economies o scalein purchasing, applicable research and develop-ment and innovation. Big companies are gener-ally not active members o Macedonian clusters.Analysis o successul clusters around the worldshows that successul clusters gather, apply andexpand knowledge and create innovative solutionsto business challenges. These qualities o cluster-ing still need to evolve in Macedonia.

According to the survey, Macedonian rmswould highly appreciate policy measures oriented




in the enhancement o collaboration in networksand clusters regionally and internationally (5.26on the scale between 1 and 6).

According to the interviewees, the mostpromising areas or networks/clusters in Mace-

donia are the ood industry (35.3%), agriculture(39.4%), tourism (23.5%), winery (20.6%), tex-tiles (18.6%), IT (18.6%), etc.

Macedonian companies exhibit the highestintensity o cooperation (networking) with theirsuppliers (score o 3.71 on the scale between 1 =weak and 6 = strong). The intensity o coopera-tion with the customers is not ar behind (3.67).As expected the intensity o cooperation withcompetitors is much lower (2.23). In all threekinds o cooperation the exchange o inormation

is the expertise, training and joint developmento products/services. In the case o cooperationwith competitors, there are possibilities o jointpurchasing and joint marketing, but this provedto be less customers is stronger in the case omajority oreign-owned than majority domestic-owned rms, and in the case o export-orientedthan in domestic-market-oriented rms. Thus, itseems that export market orientation stimulatescooperation/networking with other rms and that

oreign-owned rms are more aware o the ben-ets o networking.

Measures

The ollowing measures or collaboration in clus-ters and networks are introduced by the govern-ment:1. Further awareness raising and training or

clustering/networking: Awareness raisingactivities will be implemented by seminars,regional and international conerences and

match-making events. Knowledge aboutclustering and cluster management will bestrengthened by training sessions and interna-tional knowledge and experience exchanges.

2. Support cluster analysis and strategy develop-ment accompanied with action plan and spe-cic projects: Cluster analysis and strategydevelopment will be supported by the govern-

ment together with action-oriented initiativesmobilizing a set o strong leaders rom busi-ness, government and universities in a processthat will enable competitiveness o Macedo-nian clusters. Specic development and inter-

national cooperation projects o clusters wouldbe co-nanced by the government.3. Supply chain partnerships acceleration: To im-

prove the competitive position o the Macedo-nian industry, stronger supply chain partnershipled by key exporters needs to be created. Groupso companies that co-operate as buyers and sup-pliers will be invited to apply or co-nancingo analysis o existing supply chain and jointprojects. Such projects can deal with variety otheir business challenges, or example “on time

delivery” implementation, better positioning onthe wholesale or retail markets, implementationo common inormation system to track orders,inventory, etc.

4. Stimulation o, technological centers and parkson the regional level, support o networks oR&D institutions to provide a variety o ap-plicable technological services and integratedand ecient innovations: Members o such anetwork are to become a complete network o

highly-qualied individuals and advanced tech-nological inrastructures driven towards pro-moting a solid and competitive industrial web.

Expected results

Implementation o policy measures in clusteringand networking will lead to the improvement ounderstanding o the positive eects o clusteringand networking or the Macedonian industry.

Governmental support to clustering and net-working will emerge throughout the public-pri-

vate dialogue, which will be benecial or both,the public and private sector, to better overcomechallenges o collaboration.

Implementation o policy measures (supportedby the government as well as other donors, EUprograms and unds) will contribute to the cre-ation o demonstration clusters as best practicesor uture innovation-based clustering.




The Role of International Cluster Coop-eration in Increasing the Prosperity ofRegionsTõnnisson, Rene Baltic Innovation Agency, Estonia

When in 1776 Adam Smith published his seminalwork Wealth o Nations, his intention was to exam-ine what makes nations prosper, but incidentally healso laid down the oundations o classical economictheory.

Based on some empirical experiences the presenta-tion examines what role clusters play in making theirregions prosper and more specically what is the roleo international cluster cooperation in this respect,

dened in the current presentation as intentional andstructured attempt or internationalization.The presentation ocuses on the ways how clus-

ters and cluster initiatives that are strongly engagedin international cooperation can contribute to theincrease o prosperity in their own and other coop-eration regions. It particularly ocuses on innovativecluster-based international cooperation approachesas new ways to stimulate prosperity.

The presentation includes the rsthand experi-ences gained rom such innovative cooperation proj-

ects like European Business and Technology Cen-ter (EBTC) in India, iRegions (Internet-based andmobile technologies or regions in the net economy),CLOE (Cluster Linked over Europe) and also refectson the policy discussions and recommendations bythe European Cluster Policy Group in this area.

Special mentions

Al-Zo’ubi, Kawthar A., Ministry o Planning andInternational Cooperation, Jordan; Asra, Sunil,

MDI, India; Ba, Ibrahima, PCE-USAID; Breault,Bob, Breault Research Organization, USA; Ca-vanagh, Stephen, Auckland Tourism, Events, Eco-nomic Development Ltd, New Zealand; Chaplin,Gareth, New Zealand Trade and Enterprise; Chap-

lin, Gareth, New Zealand Trade and Enterprise;Eklund, Lars, The Scandinavian CompetitivenessGroup, Sweden; Enright, Michael, Enright Scottand Associates, HK; Fowcs-Williams, Ior, Clus-ter Navigators Ltd, New Zealand; Frater, Paul,Green Chip Ltd; Fuller, Cli, New Zealand Tradeand Enterprise; Gulati, Mukesh, Foundation orMSME Clusters, India; Gupta, V. K., MDI, India;Hagenauer, Simone, EcoPlus, Austria; Johansson,Cecilia, Vinnova, Sweden; Korpi, Anna, EduClus-ter Finland; Koziarski, Alan, New Zealand Trade

and Enterprise; Kunt, Vedat, Vego Consulting,Turkey; Lalis, Georgette, European Commission,DG Enterprise and industry; Lehmacher, Wol-gang, GeoPost Intercontinental; Maini, N.K.,SIDBI, India; Markkanen, Mikko, BusinessArena, Finland; Marsé, Marta, Government oCatalonia, Spain; Mittal, Manoj, SIDBI, India;Montoya, Manuel, CLAUT Automotive Clustero Nuevo Leon, Mexico; Nawangwe, Barnabas,Makerere University, Uganda; Pamminger, Wer-

ner, European Cluster Collaboration Platorm andClusterland Upper Austria; Ribas, Eduard, ClusterDevelopment, Spain; Sarkar, Tamal, Foundationor MSME Clusters, India; Shah, Jagat, ClusterPulse, India; Sorvari, Rauli, Regional Councilo Central Finland; Subirà, Antoni, IESE Busi-ness School, Spain; Taylor, Joy, Desert KnowledgeAustralia; Wade, Ibrahima, SCA, Senegal; Wael-broeck-Rocha, Elisabeth, BIPE, France; Walker,Richard, Economic Development Australia



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