Competitive Advantages and Clustering of SMEs:
An Analysis of Clustering Effect on Competition
in Small-Scale Enterprises in Istanbul
Yıldız Yılmaz GuzeyIzmir University, Turkey
Ozlem Tasseven Dogus University, Turkey
According to Michael Porter’s Diamond Model, a business cluster is defined as geographic concentration of inter-connected companies and institutions working in a common industry. In addition, clusters encompass an array of collaborating and competing services and providers that create a specialized infrastructure, which supports the cluster’s industry. The economic cluster model, represents a synergy, a dynamic relationship and a network between not only the companies that comprise a cluster but also the successful partnering of the stakeholders. Today in all over the world, successful clusters have established a greater competitive advantage and wealth creation for their regions when compared to companies not in a cluster. Given this success more policy makers and regions are considering fostering cluster development as building blocks of regional economies. Research is planned and performed for understanding the clustering in SMEs (small and medium enterprises) industrial estate in Istanbul if it gives a competitive advantage to the cluster members or not. It is performed to determine and satisfy the lack of knowledge about the small and medium enterprises’ issues, technologic systems, production quality standards, capacity usage ratios, interactions with other firms, habits of following the technologic improvements and clustering effects on the members.
Keywords: clusters, small and medium enterprises (SMEs), clustering
Introduction
Clusters are geographic concentrations of interconnected companies and institutions in a particular field. They extend downstream to channels and customers and laterally no manufactures of complementary products and to companies in industries related by skills, technologies, or common inputs (Rosenfeld, 1991). Perceiving cluster as a term was significantly increased by Michael Porter’s studies. Rosenfeld (1995) and Audretsch (1998) mentioned that Porter’s clusters determine the following:
(1) Related firms with each other (e.g., SMEs at Egyptian Bazaar, they are selling familiar products: jewelry, spice and giftware, etc.).
(2) Distribution channels, customers, suppliers and the firms which are expecting benefits from same sectors, such as technology producers.
(3) Related institutions about a sector (e.g., colleges, organizations, education and standardized firms). Clusters are the key organizational unit for understanding and improving the performance of regional
Yıldız Yılmaz Guzey, Ph.D., associate professor, Department of International Trade and Finance, Izmir University. Ozlem Tasseven, Ph.D., assistant professor, Department of Economics and Finance, Dogus University.
collection of unrelated firms (Tracy & Clark, 2003). Firms cluster together within a region because each firm benefits from being located near other similar or related firms. The firms in a cluster have common competitive strengths and needs. Given the popularity of the cluster approach, it is valuable to understand what clusters are, why they exist, how to identify them, how they matter for regional economic development, and how to use cluster analysis in policy and practice. Clusters represent a fundamental organizing framework for understanding regional economies and for developing economic strategies (Hirst & Thompson, 1996).
Clusters occur in many types of industries, in both larger and smaller fields, and even in some local businesses, such as restaurants, car dealers, and antique shops. They are present in large and small economies, in rural and urban areas, and at several geographic levels. Clusters vary in size, breadth, and state of development. Cragg (2002) and Porter (1998) argued that some clusters consist primarily of small-and medium-sized firms.
Cluster Theory
According to Newlands, the theoretical approaches about Business Clusters are striking in their variety (Newlands, 2003). A wide set of arguments drawn upon to establish what advantages rely on spatial concentration and to determine the balance between competition and cooperation that generates the advantages (Perry, 1995).
There are five main approaches about clustering:
(1) Agglomeration Theory: (Marshall, 1890, 1923, 1927): Agglomeration Theory explains that firms cluster to share a “commons” of business services, labour pool and to enable individual specialization. Theory viewed business clusters as collections of atomistic businesses, connected through market relations rather than deliberate collaboration (Perry, 1995).The sources of agglomeration economy allow firms within the same industry to gain from their mutual presence close to each other. Cluster membership benefits helped small firms located in clusters substitute for the internal scale advantages obtained by large firms. Reduced information costs are the key feature of Marshall’s economies (McCann, 1997). When firms are located together, it suggests that there is relatively easy access to representatives of other firms of interests (Perry, 1995).
(2) Transaction Coasts and the “Californian School”: According to Transaction Coasts and the Californian school, business cluster formation is related with market conditions that increase the uncertainty faced by individual businesses and risk. In response to market condition, production chains have tended to “disintegrate” among independent businesses connected through transactions.
(3) Flexible Specialization: This theory assumes, cluster members gain from the transfer of industry intelligence outside formal transaction. Firms in a cluster are expected to become interdependent through the flexibility of individual firms boundaries.
(4) Innovative milieu and the GREMI research group: Innovative milieu and the GREMI research group argues that clustering supports a collective learning process operating through skilled labour mobility, customer-supplier interaction and informal “cafeteria effects”.
(5) Institutional and evolutionary economics: Theory assumes that the wisdom of clustering comes from where business and institutional dependencies lock a particular business community into a common response.
From the other approaches, there are three underlying processes are identified and present: trust, localized learning and externalization.
Dimensions of Clustering
including geography, social distance, technology, and production flows. Not all clusters operate in all dimensions. Clustering is about proximity; the underlying rationale is that businesses that are closer to one another have advantages that are unavailable to businesses that are farther away. Some firms that are close to one another perform differently from otherwise similar peers located elsewhere (Crang & Martin, 1991; Benner, 2002).
There are three dimensions of clusters:
(1) Life cycle (existing, emerging, and potential): There is general agreement that clusters exhibit a life cycle, which draws from “product lifecycle” and “industry life cycle” theories. The cluster life cycle also includes the possibility that clusters may reinvent or redefine themselves as markets and technology change (Sadowski, Maitland, & Van Dongen, 2002).
(2) Linkages (buyer-supplier or labour pool): Most firms buy inputs (raw materials, services, components) from other firms.
(3) Geography (regional or statewide): Characterizing the dimensions of clustering, as with defining clusters in the first place, is not an exact science (Santarelli & D’Altri, 2003).
Clusters and Competitive Advantage Relations
In order to continue their existence enterprises must have competitive advantage against their competitors. Although a number of states and regions are using the cluster model to analyze their economies and organize key industries, only a few begin to show fundamental changes in the provision of economic services based on clusters (Rosenfeld, 2003). There are three advantages that can be used in clustering strategies (Sternberg, 1991; Stoneman & Toivanen, 1997; Rosenfeld, 1995).
(1) Cost Advantage: In clustering structures, it’s easier to get customers. It’s more effective and cheaper to use common utilities such as transportation, communication, energy, cleaning, security etc..
(2) Variety Advantage: Relationships and correlative competition pressure turn enterprises to find new products and services in order to strengthen their abilities.
(3) Resource Advantage: Easier labour force, easier financing, easier goods and services, easier capital and finally easier information and technology.
Porter (1998) stated that factors attracting clusters are:
(1) Labour pool: One of the reasons for SMEs to make clustering structure is to attain labour pool easily. (2) Supplier specialization: If SMEs find any potential customers about a specific subject, they can spend their money develop specialization.
(3) Information knowledge: Labour forces that are focusing on same economical intentions and problems, provide shared information knowledge.
(4) Entrepreneurship: Entrepreneurship is the key element of economical improvement.
(5) Path dependency: Economical opportunities appear on a specific region, are the results of existing economical activities.
(6) Culture: When we analyze cluster firms, the most important component is social intercourse between SMEs. It is not only about relationship between employee and employers. It is also related with customers.
(7) Local demand: Consumers demand is also effective for clusters.
Clusters can make competitive advantages by combining those factors together. Competitive advantage grows out of the value a firm is able to create for its buyer and this can be diagnosed through the value chain. Sternberg (1991) and Rosenfeld (1991, 1995) stated that innovation is seen to be central in creating a
competitive advantage by perceiving or discovering new and better ways to compete in an industry and bringing them to market.
Types of Business Clusters Generally Based on Different Kinds of Knowledge
(1) Techno clusters—These types of clusters are generally new technology-oriented, well adapted to the knowledge-based economy, and generally have collaborative networks with University or research centers etc..
(2) Historic knowhow-based clusters—Historic knowhow-based clusters are based on more traditional activities than other types of clusters that maintain their advantage in know-how as an core competency over the years or over the centuries (e.g., Grand bazaar).
(3) Factor endowment clusters are based on comparative advantage and have geographical position. Their comparative advantage generally related with their location. For example, some fish companies located near the seaside or wine production clusters located some sunny region. Like Italy, Sicily, France and San Francisco Napa Valley.
Lighting Sector
Definition and Content of the Lighting
Lighting is an element that steps forward with its both decorative and functional feature. Light was used in street lamps in 18th century then it started to be used in spaces. With the fast development of the technology and creativities of designers made lighting an important decoration element, beyond the lighting need. The aim of lighting is not obtaining a certain lighting level, it became providing the ideal and correct visual conditions. Today, lighting firms, with the developing designs are not only producing and selling lamps or ampoules but also they are creating decorative solutions by designing projects that are suitable for every space.
Lighting Sector in Turkey
In 1990, Turkey’s export was 13.8 million dollars, import 12.52 million dollars and foreign trade volume was at 26.3 million dollars level. With the crisis of 1994 import reduced to 11.6 million dollars level, export raised to 20.9 million dollars level. However, between the years of 1996-2000, import was one step forward than export. After the economic crisis in 2001, Turkey lighting sector turned towards export rapidly and came into prominence with its exporter identity. In 2002 and 2003, the increase trend in export went on. Turkish lighting sector which is developed in recent years, multiplied the lighting alternatives of the architects projects in international market and on the other hand, it started to export its products to foreign markets. The number of firms, manufacturing in accordance with the international quality standards is rising every day in Turkey. Table 1
Production Values According to Year
Years Production values (TL)
2000 4,969,199 2001 6,552,975 2002 12,918,373 2003 19,035,189 2004 18,939,798
As shown in Table 1, in 2000, our yearly manufacturing amount of 4.9 million TL showed four times increase in a short period of four years. This sector became ready to be a very important and fast developing
sector with high income and added value (see Table 2). Table 2
Production of Lighting Equipments According to Terms (TL)
Years Term I Term II Term III Term IV
2000 1,192,698 1,266,885 1,203,377 1,306,139
2001 1,072,973 1,385,914 1,558,905 2,535,183
2002 3,495,734 3,234,709 2,845,402 3,342,528
2003 4,971,325 4,496,370 4,889,033 4,678,044
2004 4,075,465 4,971,977 5,038,851 4,852,505
Sector and Employment
The number of the people that lighting equipments sector employ in our country is nearly 10,000. Considering that actual manufacturing firms start production in full capacity, it is expected that they will employ nearly 20,000 people.
Research
This research is planned and performed to investigate whether the clustering in Şişhane & Küçükköy Lighting Industrial Estate gives a competitive advantage to the enterprises in Şişhane and Küçükköy or not. Scope of research is planned as the small and medium enterprises in Şişhane & Küçükköy Lighting Industrial Estate, Istanbul. Research hypothesis are given in Table 3.
Table 3
Research Hypothesis
Procurement method of the companies of their raw materials—input & benefiting from cluster members.
Procurement method of the companies of their raw materials—input & having advantage of procuring raw materials—input of the cluster.
Sales method of the products & input & having advantage of procuring raw materials—input of the cluster. Sales method of the products & insufficiency of warehousing areas.
Company strategies & relationship among cluster members.
Cooperation opportunities with other companies and partnership with cluster members.
Cooperation opportunities with other companies and opportunities of cluster members to have cooperation and advantage. Having advantage in procurement of the goods-raw material & sufficiency of carriage/transport/infrastructure.
To feel lucky because of location & opportunities of cluster members to have cooperation and advantage.
Ninety-nine Small and medium enterprises that are in Şişhane & Küçükköy Lighting Industrial Estate are sampled. The samples are chosen randomly from all sectors. Basic terms used in the analysis are as follows:
z Enterprises that employed (1-20) people are: small; z Enterprises that employed (21-101) people are: medium; z Enterprises that employed (101-more) people are: large.
Face to face interview method is used in the analyses. In research, there are 47 questions that are open-ended and multiple-choices. We have made face to face interview for the application of questionnaires with 99 firms and have evaluated the results using SPSS Program (Statistical Product and Service Solutions). Research is performed to determine and satisfy the lack of knowledge about the small and medium enterprises in
cluster, clustering, cost advantages, and interactions with other firms and clustering effects on business functions.
Data Analysis
Survey sheets were coded and numbered, filed and tagged with the firms’ details. All questionnaires have been evaluated. For testing research hypothesis given in Table 3, Chi Square-Fisher & Yates-techniques are used. Table 4
Research Site Description
Location Frequency Percent Valid percent
Şişhane Küçükköy Other
Both Şişhane and Küçükköy Valid total 35 48 11 5 99 35.4 48.5 11.1 5.1 100.0 35.4 48.5 11.1 5.1 100.0
Age of owner Frequency Percent Valid percent Cumulative percent
< 1961 1961-1970 1971-1980 > 1980 Missing system Total 32 47 17 2 1 99 32.3 47.5 17.2 2.0 1.0 100.0 32.7 48.0 17.3 2.0 100.0 32.7 80.6 98.0 100.0
Lighting industry Frequency Percent Valid percent
Lamp shade manufacturers
Lighting—Lighting tools manufacturers Lighting—Painting industry Lighting—Lighting glass Lighting—Decoration Lighting—Electricity industry Lighting—Steel industry Lighting—Furniture Lighting—Advertising industry
Lighting—Chandeliers crystal parts manufacturers Lighting
Lighting glass manufacturing Decoration
Electricity industry Sandblasting Steel industry
Chandeliers crystal parts manufacturers Valid total 2 2 2 3 2 4 6 1 1 2 63 1 1 1 1 3 4 99 2.0 2.0 2.0 3.0 2.0 4.0 6.1 1.0 1.0 2.0 63.6 1.0 1.0 1.0 1.0 3.0 4.0 100 2.0 2.0 2.0 3.0 2.0 4.0 6.1 1.0 1.0 2.0 63.6 1.0 1.0 1.0 1.0 3.0 4.0 100
Enterprises’ time of incorporation distribution Frequency Percent Valid percent Cumulative percent 1961-1990 1991-2000 2001-2009 Valid total 16 44 39 99 16.2 44.4 39.4 100.0 16.2 44.4 39.4 100.0 16.2 60.6 100.0 100.0
Enterprises’ incorporators Frequency Percent Valid percent Cumulative percent By me With my partners By my father Took over Valid total 50 30 15 4 99 50.5 30.3 15.2 4.0 100.0 50.5 30.3 15.2 4.0 100.0 50.5 80.8 96.0 100.0 The business main activity subject when
it was first established Frequency Percent Valid percent Cumulative percent Same Other Valid total 78 21 99 78.8 21.2 100.0 78.8 21.2 100.0 78.8 100.0
(Table 4 continued)
Legal structures Frequency Percent Valid percent Cumulative percent Joint stock company
Limited partnership Personal property Valid total 2 61 36 99 2.0 61.6 36.4 100.0 2.0 61.6 36.4 100.0 2.0 63.6 100.0
Closed areas (m2) Frequency Percent Valid percent Cumulative percent < 100 m2 100-199 m2 200-299 m2 300-399 m2 > 399 m2 Valid total 6 32 20 18 23 99 6.1 32.3 20.2 18.2 23.2 100.0 6.1 32.3 20.2 18.2 23.2 100.0 6.1 38.4 58.6 76.8 100.0
Closed areas’ sufficiency (m2) Frequency Percent Valid percent Cumulative percent Yes No Total Missing system Valid total 70 28 98 1 99 70.7 28.3 99.0 1.0 100.0 71.4 28.6 100.0 71.4 100.0
Business expansion Frequency Percent Valid percent Cumulative percent No
At the same place At different place Total Missing system Valid total 71 11 16 98 1 99 71.7 11.1 16.2 99.0 1.0 100.0 72.4 11.2 16.3 100.0 72.4 83.7 100.0
Employees’ numbers working in production Frequency Percent Valid percent Cumulative percent No workers 1-9 person(s) 10-19 20-29 > 29 Valid total 12 32 42 11 2 99 12.1 32.3 42.4 11.1 2.0 100.0 12.1 32.3 42.4 11.1 2.0 100.0 12.1 44.4 86.9 98.0 100.0 Employees’ numbers working in
other departments Frequency Percent Valid percent Cumulative percent No workers 1-3 person(s) 4-6 > 6 Valid total 5 48 36 10 99 5.1 48.5 36.4 10.1 100.0 5.1 48.5 36.4 10.1 100.0 5.1 53.5 89.9 100.0 Enterprises’ average capacities in last
three months Frequency Percent Valid percent Cumulative percent
< 40% 40%-59% 60%-79% > 79% Valid total 4 39 50 6 99 4.0 39.4 50.5 6.1 100.0 4.0 39.4 50.5 6.1 100.0 4.0 43.4 93.9 100.0
Enterprises’ suppliers Frequency Percent Valid percent Cumulative percent From wholesaler From producer Directly import Valid total 16 73 10 99 16.2 73.7 10.1 100.0 16.2 73.7 10.1 100.0 16.2 89.9 100.0
Description of products Frequency Percent Valid percent Cumulative percent Semi-finished product Finished product Valid total 18 81 99 18.2 81.8 100.0 18.2 81.8 100.0 18.2 100.0
(Table 4 continued)
Customer Frequency Percent Valid percent Cumulative percent
To retailers Wholesalers Factories Retailers/wholesalers Wholesalers/dealer Retailers/W.salers/dealers Retailers/W.salers/factories Retailers/W.salers/export comp. Retailers/W.salers/directly export W.salers/Exp. Comp./directly ex. Retailers/W.salers/dealers/D. Ex. Retailers/W.salers/exp. com./D. Exp.
Retailers/W.salers/dealers/Exp.comp/D. Exp. Total 1 10 1 51 2 5 3 6 10 1 3 5 1 99 1.0 10.1 1.0 51.5 2.0 5.1 3.0 6.1 10.1 1.0 3.0 5.1 1.0 100.0 1.0 10.1 1.0 51.5 2.0 5.1 3.0 6.1 10.1 1.0 3.0 5.1 1.0 100.0 1.0 11.1 12.1 63.6 65.7 70.7 73.7 79.8 89.9 90.9 93.9 99.0 100.0
Technology usage Frequency Percent Valid percent Cumulative percent Modern Traditional Valid total 45 54 99 45.5 54.5 100.0 45.5 54.5 100.0 45.5 100.0
Technology renovations of enterprises Frequency Percent Valid percent Cumulative percent Yes Partially No Total Missing system Valid total 32 47 19 98 1 99 32.3 47.5 19.2 99.0 1.0 100.0 32.7 48.0 19.4 100.0 32.7 80.6 100.0
When the small and medium enterprises in Şişhane & Küçükköy Lighting Industrial Estate are classified, as can be seen in Table 4, from 99 respondent SMEs, it is found that:
(1) 63.6% of the enterprises are operating in lighting business;
(2) 6.1% of the enterprises are operating in both lighting business and steel industry (supply industry of lighting equipments);
(3) 4% of the enterprises are operating in “chandeliers crystal parts manufacturing” business; (4) 4% of the enterprises are operating in both lighting and electricity industry (bulb-cable etc.). Table 5
The Results of Hypothesis Tests
Research hypothesis Relationship Test P-value
Procurement method of the companies of their raw materials—input & benefiting from
cluster members. Significant Fisher 0.000
Procurement method of the companies of their raw materials—input & having advantage
of procuring raw materials—input of the cluster. Not significant Fisher 0.276 Sales method of the products & input & having advantage of procuring raw
materials—input of the cluster. Not significant Fisher 0.456
Sales method of the products & insufficiency of warehousing areas. Not significant Fisher 0.68 Company strategies & relationship among cluster members. Significant Fisher 0.000 Cooperation opportunities with other companies and partnership with cluster members. Significant Yates 0.000 Cooperation opportunities with other companies & opportunities of cluster members to
have cooperation and advantage. Not significant Fisher 1.000
Having advantage in procurement of the goods-raw material & sufficiency of
carriage/transport/infrastructure. Not significant Fisher 0.059 To feel lucky because of location & opportunities of cluster members to have cooperation
According to Chi-square test results as given in Table 5, we find that there is a statistically significant relationship between technique of production,raw materials and inputs & benefiting from cluster members. We obtained that there is a statistically significant relationship between cooperation opportunities with other companies & partnership with cluster members. Also, it is found that there is a relationship between Company strategies & relationship among cluster members.
Conclusions
In summary, survey targets the clustering, structural characteristics and what kind of competitive advantages lighting firms are getting from Şişhane & Küçükköy Lighting Industrial Estate. The results shows that the enterprises are mostly located in Küçükköy (48.5%), most of the owners were bornbetween the years 1961-1970 (47.5%),the enterprises are mostly operating in only lighting sector (63.6%), the firms generally opened between 1991-2000 (44.4%), mostly have established own business (50.5%), legal structure of firm is limited partnership with 61.6%, And business activity area is mostly between 100-199 m2 (32.3%), most of the owners do not think expanding their business (71.7%), most firms have 10-19 employers in production with 42.4% and 1-3 employers in other departments with 48.5%, the average capacity of enterprises in last three months is between 60%-79% (50.5%), most of enterprises are supplying from producers (73.7%), most of enterprises sell their products to “retailers/wholesalers” (51.5%), most of enterprises believe that being together with another lighting enterprises is an advantage (97%), all of the enterprises reach their target customer easily.
By this research, we found a relationship between competitive advantage and cluster membership. As a results of the hypothesis tested, it is found, that there is a relationship between technique of production,raw materials and inputs & benefiting from cluster members, Cooperation opportunities with other companies & partnership with cluster members, company strategies &relationship among cluster members. Existence of raw material suppliers at Şişhane and Küçükköy and being closer of these suppliers to the enterprises give advantage to them in terms of saving time and money (transportation and stock cost can be minimized so profitability can be maximized). Enterprises follow style and trend innovations from each other and they determine their manufacturing new product and growing decisions according to the leaders of the sector. The firms make use of other firms around their company by not only raw material and product technique but also directing their customers to the other firms around.
As Porter (1998) stated, cluster is a system of interconnected firms whose value as a whole is greater than the sum of its parts. Small and medium enterprises in Şişhane & Küçükköy Lighting Industrial Estate are also working together as one company for developing and helping each others.
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