Clusters and Competitive Advantage_9 pdf

Continued Province ISIC Industry Location Quotient Kastamonu 1320 Mining of non-ferrous metal ores, except uranium and thorium 17.2279 1512 Processing and preserving of fish and fish pr

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(Continued)

Province ISIC Industry

Location Quotient

1320 Mining of non-ferrous metal ores, except

uranium and thorium

19.1248

2720 Manufacture of basic precious and non-ferrous

metals

9.0355

1429 Other mining and quarrying n.e.c 7.2891

6021 Other scheduled passenger land transport 6.9192

7310 Research on and experimental development

of NSE (Natural Science and Engineering)

8.0999

1020 Mining and agglomeration of lignite 6.5639

1543 Manufacture of cocoa, chocolate and sugar

confectionery

2.8477Eskisehir 2412 Manufacture of fertilizers and nitrogen

compounds

15.6866

1421 Mining of chemical and fertilizer minerals 14.5554

9000 Sewage and refuse disposal, sanitation etc 12.4919

3330 Manufacture of watches and clocks 12.2847

1410 Quarrying of stone, sand and clay 4.4178Gaziantep 1722 Manufacture of carpets and rugs 20.1662

2424 Manufacture of soap, detergents, perfumes etc 6.1161

1532 Manufacture of starch and starch products 5.4365

1723 Manufacture of cordage, rope, twine and

netting

4.6398Giresun 1549 Manufacture of other food products n.e.c 9.5858

uranium and thorium

4.3470

6303 Other supporting transport activities 3.7061

1554 Manufacture of soft drinks; production of

mineral waters

3.2748

6022 Other non-scheduled passenger land transport 3.0346Gümüshane 2694 Manufacture of cement, lime and plaster 11.3555

uranium and thorium

7.0442

1513 Processing and preserving of fruit and vegetables 4.4383

4010 Production, collection and distribution of

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2022 Manufacture of builders’ carpentry and joinery 2.1415

Hatay 9000 Sewage and refuse disposal, sanitation etc 8.9314

1514 Manufacture of vegetable and animal oils and fats 4.3501

2320 Manufacture of refined petroleum products 3.9239

5040 Sale, maintenance and repair of motorcycles 3.1783Içel 7111 Renting of land transport equipment 28.1535

5110 Wholesale on a fee or contractual basis 5.1401

2429 Manufacture of other chemical products n.e.c 6.8240

Isparta 1421 Mining of chemical and fertilizer minerals 31.1074

2926 Manufacture of machinery for textile and leather

production

7.7432

3599 Manufacture of other transport equipment n.e.c 5.0527Istanbul 2421 Manufacture of pesticides and other

agrochemical products

3.9830

7413 Market research and public opinion polling 3.5430

7122 Renting of construction machinery and

equipment

7.3957

7492 Investigation and security activities 5.4076

1429 Other mining and quarrying n.e.c 5.1526Karaman 6022 Other non-scheduled passenger land transport 5.6724

5121 Wholesale of agricultural raw materials and live

animals

4.8861

5040 Sale, maintenance and repair of motorcycles etc 4.1601

7130 Renting of personal and household goods n.e.c 5.2590

4010 Production, collection and distribution

of electricity

4.5875

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(Continued)

Location Quotient

Kastamonu 1320 Mining of non-ferrous metal ores, except

uranium and thorium

17.2279

1512 Processing and preserving of fish and fish products 16.3051

2692 Manufacture of refractory ceramic products 9.1138

2022 Manufacture of builders’ carpentry and joinery 3.9766

2021 Manufacture of veneer sheets, plywood,

laminated board etc

3.3318

9000 Sewage and refuse disposal, sanitation etc 6.1036

1110 Extraction of crude petroleum and natural gas 10.6959

3599 Manufacture of other transport equipment n.e.c 8.9950

3140 Manufacture of accumulators, primary cells and

batteries

5.7115Kirikkale 2310 Manufacture of coke oven products 29.2998

1511 Production, processing and preserving

2694 Manufacture of cement, lime and plaster 3.9358

1410 Quarrying of stone, sand and clay 4.5353

2921 Manufacture of agricultural and forestry machinery 3.9829

2720 Manufacture of basic precious and non-ferrous

metals

9.0733

1020 Mining and agglomeration of lignite 6.7194Kocaeli 2412 Manufacture of fertilizers and nitrogen compounds 24.3247

of SSH (Social Sciences and Humanities)

6.2371

6022 Other non-scheduled passenger land transport 5.0692

Konya 2927 Manufacture of weapons and ammunition 29.2171

1543 Manufacture of cocoa, chocolate and sugar

confectionery

5.9826

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2921 Manufacture of agricultural and forestry machinery 4.8716Kütahya 1020 Mining and agglomeration of lignite 28.3098

1421 Mining of chemical and fertilizer minerals 12.5454

2691 Manufacture of non-structural, non-refractory

ceramic ware

8.0114

uranium and thorium

7.3370

of NSE

7.4615

7123 Renting of office machinery and equipment

(incl computers)

4.6570Manisa 2692 Manufacture of refractory ceramic products 9.7505

4550 Renting of construction equipment with operator 9.3036

3312 Manufacture of instruments for measuring,

testing etc

6.6454Mardin 1421 Mining of chemical and fertilizer minerals 24.4693

1110 Extraction of crude petroleum and natural gas 8.3912

2694 Manufacture of cement, lime and plaster 4.0050

6021 Other scheduled passenger land transport 2.6008Mugla 3512 Building and repair of pleasure and sporting

boats

11.8470

5510 Hotels and other providers of short-stay

accommodation

7.2328

3320 Manufacture of optical instruments,

photographic equipment

5.2021

3691 Manufacture of jewellery and related articles 5.2435

5211 Retail sale in non-specialist stores (food,

beverages or tobacco)

3.2656

3130 Manufacture of insulated wire and cable 2.8525

2691 Manufacture of non-structural, non-refractory

ceramic ware

14.3179

3420 Manufacture of bodies for motor vehicles etc 9.8496

2699 Manufacture of other non-metallic mineral

products n.e.c

7.1356

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(Continued)

Location Quotient

2695 Manufacture of articles of concrete, cement and

1410 Quarrying of stone, sand and clay 3.3016

2413 Manufacture of plastics in primary form 2.3887Rize 1549 Manufacture of other food products n.e.c 9.4490

2925 Manufacture of machinery for food and tobacco

2029 Manufacture of other products of wood, etc 5.0208

2021 Manufacture of veneer sheets, plywood,

laminated board etc

4010 Production, collection and distribution of

electricity

2.7454Sinop 1512 Processing and preserving of fish and fish

products

78.9327

2693 Manufacture of non-refractory clay and ceramic

products

4.6182

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3512 Building and repair of pleasure and sporting boats 4.3992

6303 Other supporting transport activities 4.2412Sirnak 1030 Extraction and agglomeration of peat 777.4033

5211 Retail sale in non-specialist stores (food,

beverages or tobacco)

3.0584

6719 Activities auxiliary to financial intermediation

4010 Production, collection and distribution

of electricity

3.1514

3720 Recycling of non-metal waste and scrap 9.1812

2921 Manufacture of agricultural and forestry

machinery

6.6159

Tokat 2692 Manufacture of refractory ceramic products 16.3351

3599 Manufacture of other transport equipment n.e.c 9.2227

1723 Manufacture of cordage, rope, twine and netting 7.4418

1512 Processing and preserving of fish and fish

7250 Maintenance and repair of office and accounting

1729 Manufacture of other textiles n.e.c 3.3449

S Urfa 5110 Wholesale on a fee or contractual basis 7.0048

7123 Renting of office machinery and equipment

(incl computers)

4.2859

1554 Manufacture of soft drinks; production of

mineral waters

3.5961

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(Continued)

Location Quotient

1711 Preparation and spinning of textile fibres; weaving

of textiles

25.3057

5240 Retail sale of second-hand goods 30.4632

5121 Wholesale of agricultural raw materials and live

animals

10.6603

uranium and thorium

7.3305

2921 Manufacture of agricultural and forestry machinery 2.9186

1020 Mining and agglomeration of lignite 2.6102Zonguldak 1010 Mining and agglomeration of hard coal 43.6150

2923 Manufacture of machinery for metallurgy 3.2441

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Fuzzy-Set Analysis

When applying the technique that Ragin (2000) introduces in his book Fuzzy-Set

Social Science, the first task is to assess the degree of fuzzy membership for each of the

variables included in the analysis Theoretical knowledge guides the identification

of the maximum (fuzzy membership score 1) and minimum (fuzzy membershipscore 0) scores as well as the boundaries of the categories in between Amongst thelatter the ‘crossover point’ (that is, the raw score corresponding to 0.5 in terms of thefuzzy membership score) is of special importance, since scores of less than 0.5 but

greater than 0 represent objects that are more out of the set than in it, and vice versa.

As in the case of crisp sets of Boolean algebra, fuzzy sets can be negated Predictably,

in the former negation switches membership scores from 1 to 0 and from 0 to 1,

whereas in the latter the membership of a case in the negation of fuzzy set A is calculated by subtracting its membership in set A from 1 In similar vein, it is possible

to calculate ‘logical AND’ and ‘logical OR’ with fuzzy sets Specifically, logical AND iscalculated by taking the minimum whereas logical OR is calculated by taking themaximum of each case in the sets that are intersected

The general principle regarding the ‘necessary conditions’, which are of vitalimportance in the method developed, holds both for crisp and fuzzy sets: whenever

a causal condition is necessary for an outcome, instances of the outcome will form

a subset of instances of the causal condition Arithmetically this translates into the

following: set A is a subset of set B if the membership scores of cases in set A are less than or equal to their respective membership scores in set B In other words, to

demonstrate necessity the researcher must show that the outcome is a subset of thecause The application of the subset principle when assessing the ‘sufficient conditions’,

on the other hand, requires the researcher to show that the cause is a subset of theoutcome, again by applying the arithmetic relationship ‘less than or equal to’.Finally, Ragin (2000) suggests that probabilistic criteria can be used in a fuzzy setanalysis to assess necessity and sufficiency Thus it is possible to introduce new conceptsthat imply, for instance, quasi-sufficiency of causal conditions using linguistic qualifiers(benchmarks) such as ‘more often than not’, ‘usually’ and ‘almost always’ It is thenpossible to use the conventional statistical analysis for proportions to assess whetherthe observed rate is significantly greater than the benchmark, using probabilisticcriteria

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Notes and References

1 Introduction: A Background to Clusters

1 It is certainly not the aim here to provide full coverage of the extensive literature

on the many aspects of clustering The works cited in the following pages shouldtherefore be considered as just some examples of the major contributions that haveaided our understanding of the subject

2 Examples of ground-breaking books in the new genre are Harvey’s The Limits of

Capital (1982), Massey’s Spatial Division of Labor (1984) and Smith’s Uneven Development

(1984)

3 The collapse of the socialist bloc cast some doubt on the credibility of Marxisttheory and its application to economic geography Neo-Marxist works nonethelesscontinue to be an influential part of the economic geography literature (Bryson

et al., 1999)

4 Different studies focus on different dimensions of urbanization, including increasingreturns, services, infrastructure and access to inputs and markets Here we shallconcentrate on the most relevant studies for our purposes: those which distinguishurbanization from localization

5 See, among others, Henderson (1988, 2000), Sveikauskas et al (1988) and Nakamura

(1985)

6 Since it is impossible to express these factors mathematically, Krugman (1995)thinks that they are best left to sociologists In his view there is no alternative tomodels, and all thinking involves implicit modelling However it should be borne

in mind that models are merely metaphors that enable us to understand certainaspects of reality, rather than portraying the reality itself Economic geographers,

on the other hand, think that the factors that are omitted from formal models play

a key role in determining the spatial agglomeration of economic activity (Martin,1999)

7 The examples in this section have been chosen from more recent studies Of coursethere are many older studies of the geographic concentration of individual indus-tries that provide detailed information on and insights into the emergence anddevelopment of clusters Two classic examples are those of the US shoe and leatherindustries (Hoover, 1937) and the US aircraft industry (Cunningham, 1951)

8 The products in question are dyes (Basel in Switzerland), pharmaceuticals (Basel,New York and New Jersey), packing and filling machinery (Bologna in Italy),continuous synthetic fibres (Fukui, Ishikawa and Toyama in Japan), musicalinstruments (Hamamatsu in Japan), ceramic tiles (Sassuolo in Italy); Scotch whisky(Scotland), factory automation equipment (Turin, Milan and Piacenza in Italy),motion pictures (Hollywood), optics (Oberkochen and Wetzlar in Germany),cutlery (Solingen in Germany), woollen textiles (Prato in Italy) and watches(Geneva and Jura in Switzerland) Enright (1990) also includes shorter abstracts ofother case studies in the appendix: freight forwarding (Basel in Switzerland), stone andstonework (Carrara in Italy), aerospace (Los Angeles), ski boots (Montebelluna in Italy),pens and pencils (Nuremberg in Germany), media (Munich in Germany), carbonfibres (Osaka in Japan), footwear (Pusan in South Korea), electronics (Silicon Valley

in the United States) and textile machinery (Zurich and St Gallen in Switzerland)

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Notes and References 185

9 For example in her analysis of districts in Tuscany – including Empoli (clothing),Santa Croce (leather tanning), Prato (textiles), Poggibonsi (furniture), Monsummano(footwear), Carrara (marble and building stone) and Arezzo (jewellery) – DeiOttati (1996) focuses on changes in the competitive context and the strategiesadopted by local firms, and concludes that a transformation occurred with respect

to strategies for product diversification, innovation and quality upgrading.Crestanello (1996) is also optimistic about the continuing success of the clusters in

Veneto and Tuscany, as are Brusco et al (1996), who argue that the ongoing success

of the clusters in Emilia-Romagna has shown that competitiveness is not renderedinvalid by high labour costs Becattini (1990), on the other hand, points to somesigns that Italian clusters have found it difficult to adjust to fluctuations in externalconditions, particularly the growth of unemployment

10 The distinguishing feature of the clusters in South Korea, which is classified as

a newly industrialized country, is that small and medium-sized enterprises arehierarchically networked and spatially clustered around large enterprises and

industrial conglomerates (chaebols) (Nadvi, 1994)

11 In his 1990 study Porter writes of clusters as groups of related industries, regardless

of geographical location, and stresses that such clusters tend to be localized inspace Thus a distinction should be made between how Porter uses the term cluster

in his 1990 study (closer to networks) and in his 1998 study (geographic clusters).See Chapter 2 for a discussion of this issue

12 For more on defining clusters see the methodology section in Chapter 3, whichdiscusses the scope and boundaries of clusters

13 This in turn means that old Fordist regions have undergone a major restructuring,which can be interpreted as a Schumpeterian process of localized creative destruc-tion The consequences of this have been serious enough to cause a ‘second industrialdivide’, according to Piore and Sabel (1984), who claim that flexible specialization is

a reaction to the ‘crisis of Fordism’ and can be considered as a partial return to morecraft-based modes of production, where there is ‘cooperative competition’ amongsmaller firms, greater reliance on social relationships (particularly trust) as a means oforganizing transactions, and flexible manufacturing equipment and techniques

14 The two perspectives covered in this section have parallels with the overallapproach in the management literature

15 Krugman’s (1991a) colourful account of the emergence and development of thecarpet industry in Dalton is just one of many interesting examples that point tothe importance of historical accident in the initiation of a cluster

16 This also points to the necessity of making a distinction between business andsocial networks, whose relative importance might result in different kinds of cluster(McDonald and Vertova, 2002)

2 Clusters in the Management Literature

1 With regard to the latter, McCann and Fingleton (1996) found tighter linkagesfollowing the adoption of just-in-time production by a small sample of Scottishelectronic firms

2 Relatedly, Parkin (1999) presents a game theoretic model that demonstrates thatinterfirm cooperation is best fostered by repeated contact, which is in turn reinforced

by geographic proximity

3 The temporary loss of custom that Swiss watch producers suffered as a result ofthe new technology introduced by Japanese companies is an interesting example

in this respect

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186 Notes and References

4 A likely explanation of such concentration is that other areas lack the necessaryinfrastructure, institutions and suppliers Remedying this would be inefficient andcostly, so concentration in a number of metropolitan areas is preferred, according

to Porter (1998) Germany, Italy, Switzerland and the United States provide goodexamples in this respect

5 See Öz (1999), Davies and Ellis (2000) and Konsolas (2002) for comprehensivereviews of this debate

6 Specifically, cluster charts were prepared for the years 1980, 1985 and 1990; clusterswere classified as ‘strong’, ‘fairly strong’, ‘potential’ or ‘latent’; and since Porter’smethods laid too little emphasis on international aspects in the case of a smallopen economy, ‘international business activities’ was added as a third outsideforce (Rouvinen and Yla-Anttila, 1999)

7 Padmore and Gibson (1998) view the branches of firms operating outside the targetregion as important sources of technology and skills

8 The case of Ireland is relevant in this regard in that the substantial increase inFDI has been instrumental in the noteworthy growth achieved by the country inrecent years

9 For example some firms (both foreign and American) choose to establish a presence

in Silicon Valley in order to keep up with the latest developments in the industry

10 Porter (1996, p 89) poses the related research question of why smaller countries,such as Austria, Chile, Denmark, Hong Kong and Singapore, and large countrieswhere much policy is made at the state level, such as Germany and the UnitedStates, seem to have economic advantages over other large countries

11 An entire issue of the Review of Black Political Economy was dedicated to this

debate

3 Industrial Clusters in Turkey

1 The house building sector of this industry is linked to the competitive housing/household goods cluster

2 The mathematical expression for the LQ is LQ (X ik /X k )/(Y i /Y), where X ik is

employment in sector i in region k, X k is total employment in the region, Y i is

national employment in sector i and Y is total national employment If the value

of this ratio is greater than one, the region’s share of the activity in question isgreater than the national average, which indicates the existence of spatial concen-tration (Üser, 1983)

3 Indices that measure the geographic concentration of establishments – C4ESTand C8EST – are also used by Enright (1990)

4 According to their results, agglomeration forces appear to have a stronger effect atthe four-digit industry level (Maurel and Sedillot, 1999)

5 It should be remembered that in this study clusters are not necessarily restricted

to small firm agglomerations, as discussed in Chapter 1

6 The related and supporting industries of a four-digit industry, as well as otherclusters and institutions that are linked to it, are examined separately for eachcase study in the following chapters

7 A review of the literature reveals that not many studies have focused specifically

on the overall spatial patterns of Turkish industry Üser’s (1983) dissertationand Eraydin’s (1997, 2002a, 2002b) works are notable exceptions For a recentcontribution see Akgüngör (2003)

8 All the necessary data are available for the year 1992 and have been obtainedfrom the State Institute of Statistics

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Notes and References 187

9 The list obtained by using the C8EMP indices is very similar to that obtained fromthe C4EMP indices, and hence is not reported here

10 The Istanbul metropolitan area consists of Istanbul, Kocaeli, Sakarya, Tekirdagand Bursa, the Izmir metropolitan area of Izmir, Manisa, Aydin and Denizli, theAdana metropolitan area of Adana, Mersin and Hatay, and the Ankara metropolitanarea of Ankara and Kirikkale The Regional centres are Kayseri, Gaziantep, Konya,Samsun and Eskisehir (Eraydin, 2002a)

11 The conclusions are the same if these groups are treated as proportions and thestandard statistical techniques are applied

12 See Appendix 2 for a brief description of this method

13 With regard to ‘suspect cases’, the category ‘other textile products’, for instance,might refer to different types of item in the SITC and ISIC systems

14 Following Ragin (2000), a benchmark proportion of 0.80 is used to represent thelinguistic qualifiers ‘almost always necessary’ and ‘almost always sufficient’, and

a benchmark proportion of 0.65 is used to represent the linguistic qualifiers ‘usuallynecessary’ and ‘usually sufficient’

15 In recent years, considerable attention has been paid to the relationship betweengeographic concentration and trade, and an extensive body of literature hasemerged to address various aspects of the issue (see for example Ellison and

Glaeser, 1999; Krugman, 1991a; Maurel and Sedillot, 1999; Midelfart-Knarvik et al., 2000) Jaffe et al (1993, p 578) compare the geographic location of patent citations

with that of the cited patents, and conclude that ‘paper trails’ left by knowledgespillovers in the form of citations are indeed geographically concentrated

16 Schmitz (1999) has used a survey to investigate whether enterprises in the oriented Sinos Valley in Brazil have stepped up their cooperation in response tointensified global competition in leather footwear

export-17 In the second part of his study on geographic concentration, Enright (1990)conducted qualitative case studies to investigate the possible contribution of

clustering to international competitiveness Roelandt et al (1999) have combined

quantitative and qualitative methods by using monographic case studies andinput – output tables Similarly Ziona (2000) argues for the use of quantitativetechniques to identify clusters, and qualitative techniques to analyse them

18 In terms of methodology the present study resembles Enright’s (1990) approach

19 A cluster map is a graphic way of portraying the various components of a clusterand identifying how they relate to each other This study follows Porter’s (1998,2000) approach, which first identifies the main product categories and then thelinks between inputs and products in these categories The map also portrays therelations between producers and their supporting government agencies, universities,research centres and trade associations Other clusters that are linked to the cluster

in question are included as well Porter’s cluster diagram therefore maps not onlythe input – output structure but also the local infrastructure that supports thecluster and its relations with other clusters For a discussion of alternative clustermapping techniques see Ziona (2000)

4 The Furniture Cluster in Ankara

1 The limited degree of international trade by cluster firms is manifest in the generallack of cooperative relations with foreign companies, although there are exceptions,such as in Casa and Balikçioglu

2 It is interesting to note that construction is one of the activities with which Turkishentrepreneurs have often begun their commercial activities It was Ankara in the

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