Are Development Plans Stimulating the Establishment of SMEs · Web view“The New Institutionalism” proposed by Di Maggio and Powell (1991) tries explain how organizations become

Institute for Small Business & Entrepreneurship 7-9 November 2007 - Glasgow, Scotland

Are Development Plans Stimulating the Establishment of SMEs?: A Study of Turkish SMEs

Recep Kök, Full ProfessorDokuz Eylul University Faculty of Economics and Administrative Sciences

Department of Economics 24. Sok. No:2 35160 Dokuzcesmeler-Buca/IZMIR TURKEYTel: +90 232 4204180 Email: [email protected]

Website: http//:kisi.deu.edu.tr/recep.kok

Ethem Duygulu, Assistant ProfessorDokuz Eylul University Faculty of Economics and Administrative Sciences

Department of Business Administration

Nevzat Şimşek, Assistant ProfessorDokuz Eylul University Faculty of Economics and Administrative Sciences

Department of Economics

Abstract

The main aim of this paper is to examine the relation between development plans and reasons of establishment, types of activities and clustering of SMEs in Turkey taking regard of two basic forms of capitalism for seen in the economic theory. In this perspective whether there is a real relationship between the establishment of organizations and environmental factor and governmental regulations is questioned. The first hypothesis of this paper is that “investment incentives cause industrial/sectoral clusters between regions in Turkey”. Second hypothesis is that “investment incentives lead to regional resources to be used in the region –though partially- and help to decrease the inequality of income distribution between regions and contribute to the improvement of investment climate in low-income regions as a result”. Coordinated market economy hypothesis is confirmed according to the models and estimators demonstrated from Turkish case. In Turkey it is possible to conclude that economy policies including regulations towards priority regions in development improve resource usage process and decrease income inequality by changing the way of industrial clustering between regions.

Keywords (JEL Classification): D61, L16, L51, M13, R10

Are Development Plans Stimulating the Establishment of SMEs?: A Study of Turkish SMEs Page 1 of 14


1. IntroductionAlthough economists has proceeded a long way in studying the factors affecting the

formation of organizations, the debate still continues because of the increase in the interest in cultural and institutional differences, increase in the variety of theoretical approaches (turning towards to upper levels of analysis), increases in epistemological and methodological approaches. In this paper, the authors aim to participate in this debate in the literature in view of macroeconomic basis and try to test the effect of Development Plans on the establishment of SMEs (Small and Medium Size Enterprise) in a Liberal Market Economy-Coordinated Market Economy by econometric and statistical techniques for Turkey.

Nowadays one of the different forms of capitalist system applications is Liberal Market Economy in which the government intervention to resource allocation is the least. In this form, political choices and organizational structure of market economy occur automatically parallel to institutional structure. “Free contract”, “private ownership” “free entry-exit to markets” and “competitive market mechanism” are basic elements of institutional structure of market economy (Hall and Soskice, 2001: 55). The other form is coordinated market economy which is not consistent with free price system. In this form, market imperfections are emphasized and it is stated that government intervention to market economy is necessary to form efficiency in production, consumption and distribution (second best). The institutional structure of coordinated market economy depends on “limited and prevalent ownership” and “social government order and principals of democratic planning” (Hall and Soskice, 2001: 90). One of the most important welfare differences between countries depending on institutional differences can be analyzed economic systems approach in the literature.

The aim of the this paper is to analyze the reasons of establishment of SME’s, activities and clustering dimension of SME’s and the relation between SME’s and Development Plans in Turkey by taking regard of the two basic forms of capitalism in theory. In the paper, whether a valid relationship between the establishment of organizations and environmental factors and government regulations occurs leads to important results. In this respect, our starting point is the basic hypothesis of institutional and ecological approaches trying to explain aspects such as reasons of establishment of organizations, which factors affect establishment of organizations, types of organizations and the reason of clustering of these types in specific regions. In other words the aim of this paper is to analyze the development of SME’s in view of medium-term economic policies foreseen in Development Plans in Turkey, to analyze application results of planned approach encouraging establishment of SME’s and to test whether the results are consistent with the basic hypothesis.

“Organizational ecology”, “institutional theories” and “organizational economies” have been the most important models examined in the literature recently. For example Williamson (1975) “Transaction Cost Economics”, Meyer and Rowan (1977) “Institutional Theory”, Hannan and Freeman (1977) “Population Ecology” and Pfeffer and Salancik (1978) “The External Control of Organizations- The Resource Dependence Perspective” are the most popular organizational models.

In this paper, we develop and test hypotheses that are consistent with the literature. The first hypothesis is that “investment incentives cause industrial/sectoral clusters between regions in Turkey”. Second hypothesis is that “investment incentives lead to regional resources to be used in the region –though partially- and help to decrease the inequality of income distribution between regions and contribute to the improvement of investment climate in low-income regions as a result”.

Analyzing these hypotheses in institutional economic perspective, American intuitionalists emphasizing the importance of institutional structures on national development and international competition process should be stated. This approach continues in form of new institutional approach known as second-generation intuitionalists. Institutional structure is examined in three different approaches in the literature (Hall and Soskice, 2001: 2-4). First approach is interventionist approach, second is neo-corporatism that leads various social groups to participate in the democratic process collectively and third is social production systems approach that concerns the institutional structure in sectoral basis (Schmitter, and Lehmbruch, 1979: 33).

According to Zysman (1983: 57) the government intervention to economy is explained by timing of industrialization thesis in theorical perspective. Leading of supporting funds (such as investment tax credit) towards developing regions to real economy depends on efficient inter-regional capital fluidity. As there are differences in opportunity costs between regions, supporting funds given to private firms by government creates an important effect on the expected return of the entrepreneur. In this regard the entrepreneur who finances real economy wants to benefit from the region’s sources with his limited floating capital and from the



governmental incentives (incentives to priority regions in development) and uses market arguments effectively (second best theory). Thus, market-imperfection will be partial and welfare state will be emphasized (Castles and Mitchell, 1992: 8-10). In view of the aim of this paper, regarding the first phases of industrialization of countries, it has been stated that incentives, such as foreign exchange allotment (credit usage) has given to real sector and these incentives have encouraged economic policies accelerating industrialization in view of competition strategy (Vitols, 2001: 1-2).

Development of institutional infrastructure is explained by the technological infrastructure effect with respect to competition power of countries. One of the factors supporting this process is the demand structure that explains the market structure. In this structure, investments or total investment elements (fixed investment, floating capital, exchange rate allotment, etc.) are explained by supply-side cost structure and per capita income according to settlement units (cities) constitutes demand-side purchasing power (Dosi, Pavitt and Soete, 1990: 35-39).

Institutional theory is an approach that contains different concepts rather than a single theory. Approaches which analyze processes that drive organizations to act similarly are gaining importance among institutionalization approaches which are valued by Meyer & Rowan’s (1977) studies. “The New Institutionalism” proposed by Di Maggio and Powell (1991) tries explain how organizations become similar in their organizational structures, their way of doing work even in their strategies because of normative pressure originating from legislation, professional institutions and other institutions that made up the organization’s environment. According to Di Maggio & Powell (1992) there are two main factors that cause the similarity between organizations. These are competitive and institutional pressure. These pervasive influences force organizations among time to become similar by regulative, isomorphic, normative and imitative mechanisms. Any external pressure, mostly originating from the government that drives the organization act in a similar manner may be called the regulative factor. Obligation to have a waste treatment facility, obligation to fulfill clauses of the incentive certificates and obligation to obey economic regulations may be given as examples for regulative factors. According to Hinings and Slack (1994) the concept of isomorphism may be realized by bigger and powerful organizations, dictating their organizational structures as the best alternative to little and powerful organizations. The similarity is mostly because of the uncertainty that the organizations are facing. In environments with significant uncertainty due to political or economical instability, organizations choose successful organizational models and try to imitate them. Lack of choice among existing structuring options causes normative resemblance. Obtaining a system certificate (HACCP, ISO, TQM) in order to sustain operations or becoming a member of non-governmental organizations (Businessmen’s Association), becoming a member of the official chambers, general acceptance by the public causes normative resemblance.

An evaluation of theoretical framework of the interregional industrial clusters reveals that industrial clusters that concentrate in different economical regions requires a reassessment (government intervention) of the resources (Nelson, 1995: 175-180). In this context, industry specific or priority regions in development specific reassessment of the resources by the institutional structure in a country (State Planning Organization for Turkey) may be explained by the intervention approach.

In this paper, we will relate our results to the following policy statements that can be seen in the Five Year Development Plans of Turkey after 1980 (5 th and 6th Five Year Plan etc.) and Bill of Government Incentives in SME Investments (Bill Number 2000/1822), that are shaped mostly by coordinated market economy form: “Low-interest loans given to SMEs will be increased in line with the budgetary means, a system which will enable project based loan applications to be evaluated without the need of a mortgage will be developed…” and “Research and development actions will be supported in favor of SMEs…”

Ecological approach which is born in the mid-70s differs radically from most organizational approaches. Hannan & Freeman (1977) defined organizational ecology as “an approach related to organizations’ macro-sociology which is founded upon environmental and evolutional models of change in order to understand the forces that shape the organizational structure among time”. Organizational Ecology uses a biological analogy and statistical analysis to try and understand the conditions under which organizations emerge, grow, and die. In line with the definition organizational ecology draws attention to three processes; emergence of the organizations as well as species (processes) natural selection of the organizations and continuance of the organization. From an analytical point of view organizational ecology can be analyzed in four parts; individual, organizational, population and community. Hannan and Freeman (1977) used the word population to define organizations as a whole not the individual



members and organizational populations resemble in some points. For this specific reason, organizational ecology approach differs from other ecological models in the way that it chooses population as analysis unit. Organizational ecology draws attention to the fact that organizational environment shapes the organization’s survival efforts instead of conscious strategy decision and adaptation to organizational structure. Therefore, surviving organizations are in fact alike and are the ones that respond to environments’ requests which results in having similar organizational characteristics.

When two approaches are taken into consideration, institutional and environmental factors are two important motives that drive entrepreneur behavior in micro levels. Similarly Gartner (1985) points out that in creating a new business there are four important factors; individual, organization, process and environment. Factors like entrepreneur experience, availability of risk capital, technical capability of labor, legal and administrative regulations, proximity of universities (collaboration), living conditions, high vocational and industrial differences, availability of financial resources, strong agricultural and industrial base, attitudes and behaviors of regional community, easiness of reach in transportation, availability of infrastructure and land are effective in environment sub construct. Most of the factors in fact draw the line between development and underdevelopment.

The study is planned as follows. In the second part primary and secondary data used in the study are presented as well as the econometric and statistical models that will use these data. In the third part model results and findings are analyzed. The last part contains the results of the study.

2. Model and Data Sources In this paper various econometric and statistical techniques are used so as to test the

hypotheses. In statistical measures 46775 SME’s data that corresponds to population is formed by survey method and from KOSGEB (Administration of Development and Support of Small and Medium Sized Enterprises) User Status Definition Form. Expressive results for manufacture industry depending on the results of econometric models necessitates the detailed analyzes of the paper in micro basis. In the same sector 9333 firms representing SME’s in Organized Industrial Regions (OIR) are chosen as samples from this database. The reasons for choosing OIRs are specific institutional reasons such as having been established according to governmental-legal regulations according to private laws, etc. which is important in regard of the aim of the paper. In Turkey according to the results from 9333 firms, 2024 surveys were made in OIRs and attitude scale of firm owners regarding regulatory basis of institutionalism are gained and determined.

Variables of primary database are variables that have been developed by the authors taking into account the types of activities depending on NACE, incentives and Kostova’s (1997) three dimensional country institutional profile regarding measuring attitudes. In country institutional profile variable, five statements that have been used to measure regulatory dimension by Kostova (1997) are transformed to eleven statements in the paper and reliability tests are performed. Descriptive statistical techniques are used to represent the 9333 firms. In this sample, a crosstab test is made to capture regarding subjects of activities and incentives in regions specifically and in the country generally.

1980-2006 secondary variables, which are used in econometric analysis, are provided from the Treasury. In the econometric part two basic models are formed by Kök, the one of which is resource allocation model and the other is usage of incentives according to priority regions in development.

In estimating resource allocation model, panel data method including 27 years (1980-2006 period) and 5 cross-sections (energy, services, manufacture, mining and agriculture) is used. The Model 1 is as follows:

Yit = αit + DOVit + D1it + D2it + D3it + D4it + D5it + eiti=1…5 industries and t=1980…2006Opportunity cost variable (dependent proxy variable Y): fixed investments / number of

incentives is formed by Kök by the following method. This variable is formed according to the hypothesis that the return of fixed cost per incentive will be equalized depending on the market economy. In this respect this variable represents intersectoral average opportunity cost. If opportunity cost is below average than Y=0, if it is above average than Y=1. The probability of allocation resource to an industry or settlements by each entrepreneur occurs according to coordinated economies approach. The probability that the capital accumulation in developed regions is used in the same region or the entrepreneur in developing region uses the sources in his region can be explained by opportunity return between regions. DOV variable constitutes the supporting fund from government by the entrepreneur per incentive. D1=energy, 1, others 0,



D2=services 1, others 0, D3=manufacture 1, others 0, D4=mining 1, others 0 and D5= agriculture 1 others 0 are dummy variables defining sectors.

One of the most important features of the development plan that encourage the establishment of SME’s and strengthen them (that affect the behavior of entrepreneur against production of goods and services) is the opportunity cost of goods. Industrial opportunity cost play an important role on the distribution of demands of entrepreneur on incentives regarding alternative industries in country scale and regional scale. Between 1980-2006 period regarding fixed investments per incentive in industrial scale, opportunity cost variable (proxy) is determined. Here entrepreneur should estimate the way of resource allocation to the sector in which he will invest. For example in a specific domestic and foreign market structure (sectors in GNP, per capita income in settlements) as long as entrepreneurs estimated opportunity returns of industrial production processes or industrial opportunity costs. They will transfer resources to the real sector. All cross examine and solution parameters regarding analysis of investment (fixed investment) and production capacity (employment) and market structure of these industries are important in view of industrial analysis and group dynamics. Here resource allocation model both determines the way of industrial clustering and provides guidelines for entrepreneurs.

The cross section stock data of 2006 had been used in the usage of incentives according to priority regions in development model. The Model 2 is as below:

ILi = βi + KBGi + TOPYATi + ISTi + eii=1…81 Provinces of TurkeyThe dependent variable IL in this notation is the dummy variable that is ranked as 0 if the

province is a priority region in development and as 1 if it is a developed region. KBG is the per capita national income. TOPYAT represents the average investment per incentive and IST represents the employment capacity (number of employees) that accrues with incentive. This model explains the resource usage tendency in each sector. In fact the resource usage process that arises by the combination of entrepreneurship facilities and the incentive policies aims at overcoming the disequilibrium among different regions (residential areas).

Log-linear, logit, and probit models extend the principles of generalized linear models (ex., regression) to better treat the case of dichotomous and categorical variables. Logit model is a statistical method that enables the classification according to the probability rules by calculating the forecasted values of dependent variable as probability values and analyses tabulated or raw data. In other words the discrete variables in those models turn into continuous form by the probability distribution. The binary forecasters in the two model of this study to analyze the dummy data are produced by the logit method (Grene, 1987: Ch.9).

3. ResultsAs the a priori acceptance placed in the theoretical framework and MODEL 1 taken as

reference, as seen in table 1, and the sectoral resource allocation are evaluated the first hypothesis of the study is found out to be compatible with the theoretical construct. According to the model while a increase of 1 percent in the DOV raises the probability of alternative cost increase by 6.21E-07 (1.0000014), the resource allocation oriented at all sectors raises the probability of the decrease in alternative cost as a whole. However this decrease in those sectors excluding the manufacturing and service sectors hadn’t been found out to be statistically significant. Accordingly the resource allocation is manufacturing and service directed as for industrial clustering. By these results the statistical insignificance of especially the energy and mining industries’ coefficients can be explained as the investments are generally made in those sectors by government. However the insignificance of agricultural sector can be assessed to the low-yield property of the sector.

TABLE 1: Resource Allocation Model (MODEL1)Basic Variables

(Industry Clusters)Dependent Variable: Alternative cost variable Y Coefficient z-Statistics and Prob.

C -0.747066 -1.824 (0.0681)DOV 6.21E-07 2.6213 (.0088)D1 (Energy) --- ---



D2 (Service) -1.196690 -1.810 (0.0703)D3 (Manufacturing) -1.991903 -2.147 (0.0318)D4 (Mining) -0.572101 -0.929 (0.3524)D5 (Agriculture) -0.162822 -0.278 (0.7810)Dep Y=0 96Log likelihoodHannan-Quinn

-75.663241.262298

As the variables explaining each sector one by one are evaluated according to the results of MODEL 2 in table 2 the forecasters incompatible with the above industrial clustering had been obtained.

Table 2: Usage of Incentives According to Priority Regions in Development Model (MODEL2)BasicVariables

Dependent Variable: IL = 0 Developing, IL = 1 DevelopedEnergy Service Manufacturing Mining Agriculture

C-5.05

-3.23 (0.00)

-5.36-4.37 (0.00)

-5.39-4.54 (0.00)

-3.98-4.38 (0.00)

-6.19-4.45 (0.00)

KBG3.88E06

3.23 (0.00)

2.08E063.56

(0.00)1.85E06

3.09 (0.00)

2.43E063.95

(0.00)3.51E07

3.97 (0.00)

TOPYAT -9.07E08-2.31 (0.02)

2.42E070.71

(0.47)4.02E07

1.65 (0.09)

-6.86E08-0.30 (0.76)

4.86E071.62

(0.10)IST

2.92E031.39

(0.16)2.07E04

2.92 (0.00)

5.14E052.62

(0.00)5.44E05

0.56 (0.57)

2.99E041.07

(0.28)Dep IL=0Dep IL=1

3728

5031

5031

4731

4731

LoglikelihoodHannan QuinMcFaddenR-sq.

-16.633770.6876810.625614

-26.703600.8055550.504531

-25.534900.7766980.526216

-32.425730.9823740.381339

-25.293350.7994930.517420

According to this, for instance a increase of 1 percent in per capita income related with the coordinated market economy argument at manufacturing industry raises the developing region’s probability of becoming a developed region by 1.85E-06 (1.000004) and a increase of 1 percent in total investment per incentive raises the developing region’s probability of becoming a developed region by 4.02E-07 (1.0000009). On the other hand a increase of 1 percent in employment raises the developing region’s probability of becoming a developed region by 5.14E-05 (1.0001184). The statistical insignificance of TOPYAT (total investment/number of incentives) variable related to the service sector is found to be compatible with the framework (expectations) of the study because the incentives given to the service sector are generally characterized with tourism incentives. Those incentives have been predominantly given to the developed regions in Turkey because of the weather conditions.

The meaningful results obtained for the production industry depending on the results of econometric models have been evaluated according to the NACE classification in this sector for 9333 firms throughout the country and in specific regions with micro-scaled descriptive statistics and for 3034 firms having an ability to represent it, depending on the attitude scale results.

Considering the general features of the exemplification, as seen in Tab.3, in the distribution of incentives depending on the number of firms the Eastern Anatolia (20.9%) and the Black Sea Region (19.2%) have the biggest share. It must be studied whether the local people and settlement have an effect on this distribution, as well as in the nation policies the tendency of the politic understanding towards these regions. And sure enough, the distribution of the firms in OIR, seem to support these findings in sub-categories in Tab.3.

Table 4: Characteristic of the Sample (Depending on the Number of Incentive Certificate) KOSGEB-All KOSGEB-OIR OIR



N=46775 N=9333 N=3034Incentive Certificate Incentive Certificate Incentive CertificateExist Non-exist Exist Non-exist Exist Non-exist

Mediterranean 289 4313 62 242 21 936,3% 93,7% 20,4% 79,6% 18,4% 81,6%

Aegean 435 5633 109 759 34 1387,2% 92,8% 12,6% 87,4% 19,8% 80,2%

Marmara 1157 18349 291 2696 242 13755,9% 94,1% 9,7% 90,3% 15,0% 85,0%

Central Anatolia 782 7686 392 3213 122 7259,2% 90,8% 10,9% 89,1% 14,4% 85,6%

East Anatolia 235 891 78 188 14 3620,9% 79,1% 29,3% 70,7% 28,0% 72,0%

South-East Anatolia 224 2486 86 398 50 988,3% 91,7% 17,8% 82,2% 33,8% 66,2%

Black Sea 498 2092 119 223 14 7219,2% 80,8% 34,8% 65,2% 16,3% 83,7%

Not responded 1705 477 0Total Firms 3620 41450 1137 7719 497 2537

But in the results of Survey study it has been observed that the share of Black Region included in the same table in OIR has decreased and that of South Eastern Anatolia has increased. On the other hand, it is important to note that in terms of the number of firms and the number of incentive certificates (in which region) are relatively smaller than the other regions, while the Marmara and Inner Anatolian regions are higher. It can be said that this situation has occurred because of two possible reasons; incentive politics for the regions are restrictive and lack of sources with cognitive processes of local people. Yet, it must be kept in mind that these two regions are in a developed local one in respect of agglomerate factors.

The regional distribution of economic activities relating to manufacture according to NACE classification is demonstrated in Table 4.

Table 4: Regional Distribution of Economic Activities* N=8670Mediterranea

nAegea

n MarmaraCentral Anatolia East Anatolia South-East Anatolia Black Sea

15 6,63 15,94 18,05 22,99 11,42 16,08 8,8916 0,00 21,43 35,71 0,00 21,43 14,29 7,1417 4,70 14,35 44,96 10,00 2,87 20,17 2,9618 4,65 11,63 68,99 6,20 0,00 5,43 3,1019 0,00 5,26 88,60 3,51 0,88 1,75 0,0020 15,00 8,33 21,67 36,67 3,33 3,33 11,67



21 1,68 8,38 26,26 52,51 3,91 4,47 2,7922 0,00 6,15 41,54 50,77 0,00 1,54 0,0023 4,76 9,52 28,57 23,81 19,05 9,52 4,7624 5,83 11,41 33,50 37,86 2,67 7,04 1,7025 2,13 10,67 39,54 37,13 2,70 3,41 4,4126 6,25 22,60 14,90 35,34 9,62 3,85 7,4527 2,14 4,17 25,48 63,81 0,95 1,07 2,3828 5,79 7,73 29,42 50,52 2,08 1,34 3,1229 1,28 7,52 25,51 63,28 0,68 0,38 1,3530 0,00 20,00 33,33 33,33 0,00 6,67 6,6731 0,50 9,50 35,50 49,50 1,00 1,75 2,2532 0,00 14,29 50,00 28,57 0,00 7,14 0,0033 0,00 3,70 14,81 76,54 0,00 0,00 4,9434 2,40 10,80 36,40 46,00 1,20 2,00 1,2035 2,63 10,53 44,74 42,11 0,00 0,00 0,0036 2,23 4,04 40,64 44,04 2,34 0,43 6,2837 0,00 13,04 43,48 43,48 0,00 0,00 0,0072 0,00 14,29 38,10 47,62 0,00 0,00 0,00* Definition of Economic Activity According to NACE Classification is presented in Appendix A.

In Mediterranean region fields of activity mostly concentrates on wood and cork production (excluding furniture), products that are made up of straw, wattles or materials alike that can be weaved. In Aegean Region other mineral products that are non-metallic, in Marmara region leather processing, handbags, luggage, and shoe and harness production is heavily observed. One thing should be remembered though; Marmara region being the most developed region in the country usually leads to relative leadership in all activity fields. As a matter of fact 18th activity field in horizontal section which is prêt-a-porter production, leather processing and painting especially concentrated in this region. In Central Anatolia region concentration is seen among two activity fields which are; medical devices, sensitive and optical devices as well as watch production along with heavy metal industry, machinery and equipment production which is also at the same level. 33rd activity field in the horizontal section being observed in this region is an important result. Textile production which is number 17 is significant in terms of South-eastern Anatolia region being second after Marmara region can be explained by the region’s availability for wool plantation as well as recent political attempts and tax exemptions and incentives intended to support regional development. In order to justify the results, activity fields originating from incentive certificates are examined in Table 5.



Table 5: Distribution of Economic Activities* According to Incentive Certificates N=8670Mediterranea

nAegea

n MarmaraCentral Anatolia East Anatolia South-East Anatolia Black Sea

15 16,95 12,04 4,50 6,15 34,21 22,35 17,3116 0,00 0,00 0,35 0,00 1,32 0,00 0,0017 13,56 10,19 24,91 5,13 9,21 38,82 11,5418 1,69 0,93 2,77 0,00 0,00 0,00 2,8819 0,00 0,00 2,42 0,51 0,00 0,00 0,0020 8,47 0,00 1,04 1,28 1,32 2,35 7,6921 1,69 2,78 1,04 2,82 2,63 0,00 1,9222 0,00 0,00 0,69 0,51 0,00 0,00 0,0023 1,69 0,93 0,00 0,26 3,95 0,00 0,0024 3,39 6,48 3,11 3,85 1,32 11,76 2,8825 0,00 12,96 9,34 6,41 7,89 5,88 7,6926 13,56 9,26 2,77 4,36 14,47 7,06 11,5427 3,39 5,56 6,23 13,33 1,32 2,35 4,8128 16,95 6,48 11,07 10,51 6,58 1,18 2,8829 1,69 14,81 10,38 18,97 5,26 1,18 0,9630 0,00 0,00 0,35 0,00 0,00 0,00 0,0031 1,69 5,56 7,27 7,69 1,32 3,53 4,8132 0,00 0,00 0,69 0,00 0,00 1,18 0,0033 0,00 0,93 0,35 1,03 0,00 0,00 2,8834 1,69 2,78 4,84 3,59 1,32 2,35 0,0035 0,00 0,93 0,35 0,77 0,00 0,00 0,0036 13,56 5,56 5,19 12,05 7,89 0,00 20,1937 0,00 0,93 0,35 0,26 0,00 0,00 0,0072 0,00 0,93 0,00 0,51 0,00 0,00 0,00Total 100 100 100 100 100 100 100

* Definition of Economic Activity According to NACE Classification is presented in Appendix A.

In fact, in the distribution of incentive certificates taken related to the field of activity with No. 17 Southeast Anatolia region takes the greatest share. In spite of this it is seen that they had taken partially or no incentive certificates by the regions according to the NACE classification in the field of activity with no 16,19,23,30,32,33,35,37,72 respectively. Related to this the results of the independence test performed in order to determine whether there is a tendency to the field of activity with whether or not the incentive certificate is taken is presented in Table 6. According to the dependency test the nonexistence of the relationship between two variables is tested. In other words H0 is based on the “there is no difference among groups” principle. If the p value of the test result turns out to be less than the significance level proposed at the beginning H0 is rejected and the hypothesis that there exists a difference among groups will be accepted. In another perspective, the equality of the counted and expected values points out that the cases eventuated are independent. On the contrary any result unequal to the cell value points out that the cases eventuate depending on each other. As seen in Table 6, for all regions in the perspective of those taken incentive certificates there exists differences among expected and counted values. For instance, while for the field of activity with no 20 the number of enterprises increases depending on the number of certificates, number of enterprises is below the expected value in the field of activity with no 21. Again in the field of activity with no 21, 30, 32, 37 and 72 there is also independence but it shouldn’t be left out of account that the expected values are less than 5. Furthermore when the results obtained from table 6 is evaluated for those having no incentive certificates, it is seen that other factors are required to explain the entrepreneurship behavior. Therefore, in the study it is aimed at attitude estimation in order to test the perception differences related with the government regulations in the establishment of the corporations.



Table 6: Independence Test (crosstabs) ResultsECONOMIC ACTIVITY (All Regions) Total

20 27 22 31 29 72 30 19 35 15 18 21 24 23 28 26 36 34 25 32 17 33 16 37

Ince

ntiv

e Ce

rtific

ate

Count 6 32 5 13 39 0 2 8 4 19 1 4 25 1 31 21 32 10 33 1 36 9 2 0 477Expected Count 6 45 4 21 71 1 1 6 2 37 7 9 22 1 41 22 50 13 38 2 61 5 1 1 477% within certificate 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1% of Total 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Std. Residual 0 -2 1 -2 -4 -1 1 1 1 -3 -2 -2 1 0 -2 0 -3 -1 -1 0 -3 2 1 -1 Adjusted Residual 0 -2 1 -2 -4 -1 1 1 1 -3 -2 -2 1 0 -2 0 -3 -1 -1 0 -3 2 1 -1

1

Count 24 86 4 67 139 3 2 11 6 123 14 22 47 6 99 72 103 35 85 4 163 10 3 3 1137Expected Count 15 106 9 50 168 3 2 15 5 89 16 22 53 3 98 53 118 32 90 4 144 11 2 3 1137% within certificate 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

% of Total 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Std. Residual 2 -2 -2 2 -2 0 0 -1 0 4 0 0 -1 2 0 3 -1 1 0 0 2 0 1 0 Adjusted Residual 2 -2 -2 3 -3 0 0 -1 0 4 -1 0 -1 2 0 3 -2 1 -1 0 2 0 1 0

2

Count 96 754 61 333 1202

18 14 106 33 586 116 157 365 15 674 344 837 215 618 25 987 72 12 21 7719Expected Count 104 721 58 342 114

117 15 103 36 602 108 151 361 18 665 361 804 215 609 25 981 75 14 20 771

9% within certificate 0,0 0,1 0,0 0,0 0,2 0,0 0,0 0,0 0,0 0,1 0,0 0,0 0,0 0,0 0,1 0,0 0,1 0,0 0,1 0,0 0,1 0,0 0,0 0,0 1,0% of Total 0,0 0,1 0,0 0,0 0,1 0,0 0,0 0,0 0,0 0,1 0,0 0,0 0,0 0,0 0,1 0,0 0,1 0,0 0,1 0,0 0,1 0,0 0,0 0,0 0,8Std. Residual -1 1 0 0 2 0 0 0 0 -1 1 0 0 -1 0 -1 1 0 0 0 0 0 -1 0 Adjusted Residual -2 3 1 -1 5 0 -1 1 -1 -2 2 1 0 -2 1 -2 3 0 1 0 1 -1 -1 1

Total

Count 126 872 70 413 1380

21 18 125 43 728 131 183 437 22 804 437 972 260 736 30 1186

91 17 24 9333Expected Count 126 872 70 413 138

021 18 125 43 728 131 183 437 22 804 437 972 260 736 30 118

691 17 24 933

3% within certificate 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1% of Total 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

1 represents those take certificate and 2 represents those take no certificate.Chi-Square Tests Value Df Asymp. Sig. (2-sided)Pearson Chi-Square 1881,32 48 0Likelihood Ratio 745,628 48 7,05E-126 N of Valid Cases 9333 A15 cells (20,0%) have expected count less than 5. The minimum expected count is ,87.



The corporate view scale is had been developed on our part on the base of Kostova’s (1997) three dimensional country institutional profile and had been used for the purpose of measuring corporate view perception. The five statements used by Kostova (1997) in order to measure the used regulatory dimension are transformed into 11 statements and the reliability analysis had been performed. In this context the alpha value of 11 statements is 0.9597 (n=2991). Fivefold likert scale had been used in the questionnaire to measure statements related to the regulatory dimension of corporate view. Scale is arranged as from the negative to positive assessments with 1 and 5 respectively (1-strongly disagree and 5-strongly agree). In the above table 7 a brief description is given about the content of the statements aiming to configure questionnaire.

Table 7: Corporate View Perception (Regulatory dimension)Item No Statement Explanations1 ….helps to establish their corporations2 .... legal necessity, ,….. grants facility by minimizing regulation3 ……appropriate……..provides special incentives4 ……helps business development5 ……extend any aid to restart business even there is a failure6 ……grants any facility to start business 7 ……grants any facility to gain information about the legislation related with the established business 8 ……retrieves the loss when they establish a new corporation and lose money9 ……helps all to benefit from opportunities provided to others when they want to establish a new

corporation 10 ….endeavors to decrease the instability and uncertainty for those establishing new corporations 11 ….grants any facility in the technological transfers necessary to establish a new corporation

Two analyses are performed incrementally for the attitude perception related with the government’s regulatory dimension. In the first analysis all attitude statements are defined as a general variable by combining them as one variable. Then the perception of this dimension is tested on region basis by t-test.

As mentioned in the Table below, the effects of governmental regulations on incentive policies are not statistically significant.

Table 8: t- test General Regulation Macro Attitude Perception According to Regions

Regions Incentive Certificate N Mean Std. Deviation Std. Error Mean

Mediterranean Government 1 21 2,5758 1,05169 ,22950 2 92 2,6472 ,94387 ,09841Eastern Anatolia Government 1 14 2,3182 ,81604 ,21810 2 35 2,3558 ,88453 ,14951Aegean Government 1 34 2,7674 ,96058 ,16474 2 135 2,5657 1,02880 ,08854Southeast Anatolia Government 1 50 2,3655 ,98744 ,13964 2 97 2,4189 ,95838 ,09731Central Anatolia Government 1 117 2,3963 ,91397 ,08450 2 717 2,4194 ,97630 ,03646Black Sea Government 1 14 2,0195 ,85962 ,22974 2 71 2,4507 ,97179 ,11533Marmara Government 1 240 2,4580 ,99281 ,06409 2 1354 2,4570 1,00779 ,027391 represents those take certificate and 2 represents those take no certificate. Sig. 0.05



Table 9: The government’s role perception of those taking certificates an those taking no certificates according to the regions

AEGEANItems N Mean F F sig T sig9 34

1382,972,51

.991 .321 1,9592,054

.05

.04

10 34138

3.032.56

3,177 .076 1.9362.062

.05

.04BLACK SEA

Items N Mean F F sig T sig4 14

721,862,56

.732 ,395 -1,956-2,240

.05

.035 14

721,642,35

2,778 ,099 -1,989-2,436

.05

.026 14

721.862,46

1.090 ,300 -1,890-2,257

.06

.037 14

721,932,64

1,79 ,184 -2,039-2,491

.04

.02Significance level .05

Especially the negative perception judgment on the basis of sub-scale basis of Black Sea region which stands in the forefront about having share from the incentives with a 19,2 percentage can be an important result. On the other hand, the perception judgment in the whole scale should be evaluated as a criticism that it is aimed at the direct investment demand of firms and the government does not make necessary regulations adequately rather than evaluating this as the tools government uses as regulatory instruments don’t achieve their aims. The existed difference related to the justice perception is important for policymakers and implementers. Moreover the negative results, in the whole country scale, can be evaluated as the opportunity perception about the utilization of resources in the macro economic frame is not equal. Especially when the negative results are evaluated with our own observations in the area as the researchers it is determined that the entrepreneurs in the developing countries keep up their expectation from the government too much. It is possible to explain the attitude and perception results there by the expectation of great incentive and investment allowance.

4. ConclusionBy evaluating the above two models depending on the primary and secondary data

together, Coordinated Market Economies hypothesis are verified in the context of estimators obtained from the Turkey economy sample.

As mentioned before, there exists no difference among those who take incentive certificate and those who do not according to the government’s regulatory dimension. An interesting result, when the mean values are evaluated and the scale’s five-fold feature is considered, it is seen that the respondents are in a negative favor that the government is not regulatory (mean 2,43) on the regional basis. Especially when the negative results are evaluated with our own observations in the area as the researchers, it is determined that the entrepreneurs in the developing countries expect too much from the government. It is possible to explain the attitude and perception results by the expectation of great incentive and investment allowance.

Consequently, it is possible to say that the economic policy applications (providing resource transfers) involving regulations regarding the priority regions in development in Turkey will improve the resource usage process and will decrease the disequilibrium of income by altering direction of interregional industrial clustering. In fact by the estimators obtained from the SME subject experiences in Turkey, we find empirical evidences that verify the fundamental hypothesis of the study and our results are compatible with the Coordinated Market Economies thesis stated in the theoretical framework.

Relative differences between the above results of survey research and econometric results can be explained as follows: Survey findings concern a specific time in 2006. Econometric results consist of time series including 27 years. Estimators in Model 2 are provided from stock variables including 27 years. Findings of the survey reflect the behaviour and attitude of entrepreneurs in the year in which they activate. Therefore in this study for Turkey, economy policy predictions are suggested to depend on econometric models.

References



Castles, F.G. and Mitchell, D. (1992); “Identifying Welfare State Regimes: The Links between Politics, Instruments, Outcomes”, Governance, 5(1).

Di Maggio ve Powell (1991), The New Institutionalism in Organizational Analysis, Chicago, IL: University of Chicago Pres.

Dosi, G., Pavitt K. and Soete L. (1990); The Economics of Technical Change and International Trade, Hervester-Wheatsheaf, London.

Gartner, A. (1985); “A Conceptual Framework for Describing the Phenomenon of New Venture Creation”, Academy of Management Review, 10(4).

Greene, W.H., (1987); Econometric Analysis, Prentice Hall, Chapter 19.Hall, P.A. and Soskice, D. (2001); “Varieties of Capitalism: The Instutional Foundations of

Comparative Advantage”, Oxford University Pres.Hannan M.T. and Freeman J. (1977); “The Population Ecology of Organizations”, American

Journal of Sociology, 82.Hinings B. and Slack T. (1994); “Institutional Pressures and Isomorphic Change: An Empirical

Test”, Organization Studies, 15(6).Kostova, T. (1997); “Country Institutional Profiles: Concept and Measurement”, Academy of

Management Proceedings. Meyer, J.W. and Rowan, B. (1977); “Institutionalized Organizations: Formal Structure as Myth

and Ceremony”, American Journal of Sociology, 83.Nelson, R. R. (1995), “Co-evaluation of Industry Structure, Technology and Supporting Instutions

and The Making of Comparative Advantage”, International Journal of the Economics of Business.

Pfeffer, J. and Salancik, G. R. (1978); The External Control of Organizations: A Resource Dependence Perspective, New York: Harper & Row.

Schmitter, P.C. and Lehmbruch, G. (1979); Trends Towards Corporatist Intermediation, London. Vitols S. (2001); “The Origins of Bank- Based and Market- Based Financial Systems: Germany,

Japan and The United States, Discussion Paper FS 101-302, Berlin: Wissenscaftszentrum Berlin für Sozialfosrschung.

Williamson, O.W. (1975), Markets and Hierarchies, Analysis and Antitrust Implications: A Study in the Economics of Internal Organisations, New York: Free Press.

Zysman, J. (1983); Governments, Markets and Growth: Financial Systems and the Politics of Industrial Change, Ithaca: Cornell University Press.



Appendix A:15 Manufacture of food products and beverages16 Manufacture of tobacco products17 Manufacture of textiles18 Manufacture of wearing apparel; dressing and dyeing of fur19 Tanning and dressing of leather; manufacture of luggage, handbags, saddlery, harness and footwear20 Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials21 Manufacture of pulp, paper and paper products22 Publishing, printing and reproduction of recorded media23 Manufacture of coke, refined petroleum products and nuclear fuel24 Manufacture of chemicals and chemical products25 Manufacture of rubber and plastic products26 Manufacture of other non-metallic mineral products27 Manufacture of basic metals28 Manufacture of fabricated metal products, except machinery and equipment29 Manufacture of machinery and equipment n.e.c.30 Manufacture of office machinery and computers31 Manufacture of electrical machinery and apparatus n.e.c.32 Manufacture of radio, television and communication equipment and apparatus33 Manufacture of medical, precision and optical instruments, watches and clocks34 Manufacture of motor vehicles, trailers and semi-trailers35 Manufacture of other transport equipment36 Manufacture of furniture; manufacturing n.e.c.37 Recycling72 Computer and related activities


Documents

Are Development Plans Stimulating the Establishment of SMEs · Web view“The New Institutionalism” proposed by Di Maggio and Powell (1991) tries explain how organizations become