Anel A. Kireyeva, Nailya K. Nurlanova / FOURTH INTERNATIONAL CONFERENCE 77-8277
Research on the Problems of Spatial Modernization of the Economy : Kazakhstan’s Experience
Anel A. Kireyeva*, Nailya K. Nurlanova**
This research aims to analyze the main problems of spatial modernization of the economy, and to develop new approaches to accelerate of innovations process from the cities‐centers to the underdeveloped regions. The study employs the method of ranking regions, the rate of innovation activity and comparative evaluation of R&D indicator. In addition, the authors proposed the method of modeling of innovation diffusion in the regions. According to the results of this theoretical and empirical study proved that modernization of the economy is realized faster in the regions with the best conditions for the diffusion of innovations, the higher the concentration of the population, a more developed infrastructure and reduced of administrative barriers.
Keywords: Spatial Modernization, Spatial Barriers, Regional Development, Innovation Cycle
JEL Classification: O31・R11・R12
The research on the problems of spatial modernization of the economy and spatial constraints of innovation development is one of the main tasks for economic geography and regional economy. Geographically the regions are unevenly placed by the Research and Development (R&D) and social structure. To this end, the regional development should be focused on the future geopolitical conditions. That is, to create the strategic adaptation, this can be achieved by the economic space modernization in regions. Therefore, its analysis and evaluation are direct interest to economic entities included in the regional innovation process. There are two ideas behind the principal research questions and hypotheses that are the subject of this research. The first of these is that, geographically, growth poles are considered to be centers for the generation and spatial diffusion of innovation. The second principal idea is center‐periphery theory (or model) of spatial development, created by Friedman. Thus, this study will try to expand researches in the field of these two ideas, and also to solve the problem of modernization of the economy. The present research is aimed to analyze the main problems of spatial modernization of the economy, and to develop new approaches to way out from crisis, to accelerate of innovations process from the cities‐centers to the underdeveloped regions, to introduce of new innovative products and to improve number of R&D employees.
2. Theoretical aspects of spatial barriers modernization of the economy
A constitutive element of this research of spatial development is a complete overview of the previous works. Long ago the regional science conclusively showed that the spatial inequality emerges as an objective effect of the competitive advantages concentration in certain territories and lack of these advantages in others. The tendency to concentration of economic activity in territories with the conditions favorable for business was discovered by G. Myrdal in the middle of the 20th century (Myrdal, 1957). The theory of "central places" by Crhistaller (1966) is highly abstract, but allows us to formulate the general idea of proper settle- ment on one or another territory. Also known theory by Hagerstrand (1966) “generation of innovations” reflects the undulating nature of spatial development. It should be highlighted that diffusion of innovation is a crucial factor in determining the human capital for the center periphery relations. But as noted earlier, there are two dominant models: the growth poles and the coreperiphery model. The first perspective refers to the attraction of activities and the concentration of growth in poles, from where the diffusion of growth is expected to occur towards the surrounding region (Perroux, 1955). The second model refers to the in tegrated spatial development; on the basis of the coreperiphery theory by Friedmann (1966) has become an important contribution to understanding of spatial development patterns. This model shows that the underdeveloped regions will inevitably become a hindrance to development of innovation and modernization of the economy. The spatial aspect of the growth pole theory triggered several questions concerning the relationships between the growth pole and the underdeveloped region, various effects of the growth pole on the underdeveloped regions, and the method of diffusion of economic growth from the growth pole to the underdeveloped regions. Nevertheless, theory of growth poles has undergone several variations to accommodate those geographic characters (Rodrigue et al, 2006). The most operational for this study is the coreperiphery model of spatial development, as the theory of Perroux, based on economic studies. This model is one of the most important contributions to the understanding of the spatial aspects. Between the city‐centers and the periphery there is a mobile zone, which can take over the functions of the center. This model works on all levels – from the world's cities and large agglomerations to regional and local centers (Perroux, 1955). Thus, the core‐periphery model by Friedman shows that important roles in the development of the country are centers‐cities. Thus, the core‐periphery model by Friedman shows that an important role in the development of the country is allotted to the centers‐cities. These cities are not been only an “important support”, but they will be the main “engine”, to translate modernization at the periphery (in the first place in the underdeveloped regions). The two models (the growth poles and the core‐periphery model), do not operate in a competitive way, but they are complementary to one another. In essence, the two models are applied in parallel in various combinations that depend on the particular characteristics and the stage of development of a country, the current international situation, and the strategic socio‐economic choices of the governments.
In this research we used the scientific methods of research. The scientific method investigates phenomena, acquiring new knowledge, or correcting and integrating previous knowledge (Goldhaber and Nieto, 2010). These methods are intended to be as objective as possi-ble, to reduce biased interpretations of results. There are difficulties in the understanding of the claimed methods. However these scientific methods are often presented as a fixed sequence of steps, they are better considered as general principles (Gauch, 2003). In practice, the modernization is limited to individual approaches and directions. The application of scientific methods in this research will allow systematize the available data by means of a theoretical and empirical analysis. Kazakhstan has a huge territory and its regions essentially differ by nature and climatic conditions, the level of economic development, the life quality of population, the availability of natural resources (Baimukhamedova et al, 2012). There are different ways of outlining the basic method used for scientific inquiry. The scientific community and philosophers of science generally agree on the following classification of method components: • generalization – process of establishing the common properties and signs of development of the regions, may be assigned any signs (abstract‐general) (Gavrilov, 2002); • hypothesis – method, which lies not simply in its perceived “truth”, but perhaps more in its ability to stimulate the research that will illuminate suppositions and areas of vagueness (Glen, 1994).
• system analysis – on the basis of the analysis of the regions as a whole set of elements in the totality of relations and connections between them (Ruzavin, 1999). This is an analysis of the current level of the innovative processes in the regions, the analysis of the ranking regions, comparative evaluation of R&D indicator in regions (Kireyeva, 2013); • modeling method – development of a model of the innovation cycle (Kireyeva,2012).
3.1. The current level of innovation processes in regions
Innovation “is the object embedded in production as a result of the carried out research or discovery, qualitatively different from the previous analogue” (Utkin, Morozova, 1996, p.10). It is obvious, that it is very important to explore regional context of the innovation process. The economic geography has placed agglomeration, knowledge spillovers, regional economic growth and spatial context at the center of its research (Feldman, 2000). The basis of the idea by Feldman: “the concept of location is defined as a geographical unit that facili- tates interaction and communication, the search for knowledge, and coordination tasks” (Feldman, 2000, p. 373). Certain empirical evidence shows the existence of knowledge spillovers within regions, but the evidence of the interregional relations of knowledge spillovers is still not investigated (Frenken et al, 2010). For instance, Kazakhstan possesses a vast territory, so that many regions have different levels of innovation capacity, which influence on the process of the modernization of the economy. Innovations con- tribute to the renewal of the regions, adaptation to scientific and technical progress and knowledge spillovers (Dunenkova, 2003). Thus, the coefficient of use of innovative potential depends on the location of the individual plants in the region, the structure of economic activity, specialization, as well as institutional initiatives of individual enterprises and administrations of regions (Untura, 2012).
<Table 1> Innovation activity rate of Kazakhstan’s regions 2008‐2011 2008, % 2009 % 2010, % 2011, % The Republic of Kazakhstan 4,8 4,0 4,0 4,3 Akmolinsk region 2,1 1,2 1,2 0,7 Aktobe region 5,6 4,1 4,0 6,1 Almaty region 2,1 1,9 1,4 0,9 Atyrau region 3,7 2,7 2,9 3,7 West‐Kazakhstan region 4,9 4,9 4,5 4,6 Zhambyl region 8,8 6,0 4,4 7,8 Karagandy region 6,1 6,5 6,2 7,0 Kostanay region 2,5 2,0 1,5 2,6 Kyzylorda region 2,4 3,0 1,5 6,1 Mangystau region 2,3 1,9 1,4 1,1 South‐Kazakhstan region 2,8 2,4 2,2 3,4 Pavlodar region 8,1 3,6 3,8 5,1 Nord‐Kazakhstan region 2,2 2,5 2,6 2,4 East‐Kazakhstan region 5,6 4,3 5,9 6,4 Astana city 3,0 1,8 2,1 2,6 Almaty city 7,2 6,4 6,7 5,4 Source: Statistical Yearbook of the Republic of Kazakhstan by the Agency for statistics (2011)
Anel A. Kireyeva, Nailya K. Nurlanova / FOURTH INTERNATIONAL CONFERENCE 77-8279
Thus, Table 1 demonstrates the level of innovative activity in the regions of Kazakhstan. This data shows that two‐thirds (2/3) of the regions have been positive indicators of the innovative development during the analyzed period (2008‐2011) and one‐third (1/3) of the regions have negative indicators. It is clear that the efficiency indicators have been higher in regions with large, densely populated agglomerations such as Zhambyl, Karagandy, East‐Kazakhstan, Aktobe, Kyzylorda. And the lowest indicators of innovation activity have found in the regions Akmola, Almaty, Mangistau and North‐Kazakhstan. Generalization: it’s important to maintain the regions with high in- novation activity, as they are growth poles and they will play the role of translator’s innovations to the periphery.
3.2. The analysis of ranking regions in the field of innovative activity
The policy of industrial development of the "poles growth" or cities with almost total disregard stimulation for the equalization policy dominates until now (Perroux, 1955). As a result the inequality of development zones of the modernization and underdeveloped periphery has grown up (Kireyeva, 2012). So, analysis of ranking regions in terms of innovative activity will help determine the spatial priorities of modernization of the economy. Procedure for ranking regions may help in verification methods, i.e. select “cumulative conditions” (Myrdal, 1957), in the form of indicators reflecting the development of new sectors of the economy, arrival on the territory of the state corporations, activation of small business and other (Untura, 2012). Leontiev conducted the analysis of innovative factors of the region development by the method of input‐ output balances (Leontiev, 1997). Granberg proposed analysis of in- novative activity of regions by evaluating of the structure and dynamics of the gross regional product (Granberg et al, 1998). Thus, the total lacks of all existing methods of the analysis of innovative activity are study and measure, but need research the economic situation and its consequence. The proposed alternative direction is connected with the phase of the analysis of innovative factors of regional development.
Source: compiled by the authors
<Figure 1> Innovative activity and innovative susceptibility in region
So, hypothesis that are two sources of all the changes in the eco- nomic activities of the region: the ability and sensitivity of the region to innovation. The economic equivalent of innovation receptivity of the region are extensive factors of regional growth (associated with the increase in production volumes in the result of increase of involved resources), and the equivalent of innovation the ability of the region are intensive factors of regional growth (associated with effective use of resources). According to this hypothesis the innovation activity of the region can be presented in the following Figure 1. The forces of innovative activity in the region may possess the following values of the phase: x = 0, (‐) 1, Where: x = 1 – the phase of innovative capacity growth in the region; x = 0 – the phase of the innovative capacity conservation in the region; x = ‐1 – the phase of innovative capacity loss in the region. Similarly, the force of innovative susceptibility of the region may possess the following values: y = 0, 1, Where: y = 1 – the phase of innovative susceptibility growth in the region; y = 0 – the phase of innovative susceptibility conservation in the region; y = ‐1 – the phase o of innovative susceptibility loss in the region.
Thus, it is possible to carry out the ranking of economic forces in the region for innovation potential. Table 2 shows the results of the ranking in terms of innovation capacity in regions of Kazakhstan.
<Table 2> Calculation of the ranking by indicator of innovative capacity Region No. Category Scores East‐Kazakhstan 1 region with high dynamics of innovative development 0,513 Pavlodar 2 region with high dynamics of innovative development 0,411 Zhambyl 3 region with high dynamics of innovative development 0,281 Almaty city 4 region with high dynamics of innovative development 0,264 Karaganda 5 region with high dynamics of innovative development 0,249 Aktobe 6 region with average dynamics of innovative development 0,236 Astana city 7 region with average dynamics of innovative development 0,225 Kostanay 8 region with average dynamics of innovative development 0,223 Kyzylorda 9 region with average dynamics of innovative development 0,182 Nord‐Kazakhstan 10 region with low dynamics of innovative development 0,156 South‐Kazakhstan 11 region with low dynamics of innovative development 0,134 Akmolinsk 12 region with low dynamics of innovative development 0,129 West‐Kazakstan 13 region with low dynamics of innovative development 0,116 Atyrau 14 region with low dynamics of innovative development 0,101 Almaty 15 region with low dynamics of innovative development 0,059 Mangystau 16 region with low dynamics of innovative development 0,052 Source: Statistical Yearbook of the Republic of Kazakhstan by the Agency for statistics (2011)
80 Anel A. Kireyeva, Nailya K. Nurlanova / FOURTH INTERNATIONAL CONFERENCE 77-82
While analyzing the factors determining the extent of innovative activity of the studied regions, it was found out that the greatest spatial barrier in the development of innovations have economic factors, among which are decisive: the lack of own funds of enterprises (32%), high cost of innovation (16%), the lack of financial assistance from the state (13%) and less significant influence high economic risk and low demand for new products and services. Among the main internal barriers to innovation – low innovation potential of enterprises (11%), the lack of information about new technologies (12%), the lack of qualified staff (6%). Generalization, economic inequality of regions is very large and will grow, for this reason need to search and development of the competitive advantages of the average developed and underdeveloped regions of the country combined with support for the alignment of regional policy measures.
3.3. Comparative evaluation of R&D indicator in regions
The term R&D or Research and Development refers to a specific group of activities within a business. R&D indicator is the most im- portant element in innovation processes are the creative minds. Organized in groups, teams or just by oneself, professional R&D em- ployees are the innovative entity in industrial innovation processes. R&D employees search for and recombine existing knowledge in order to create and to develop innovative products. The new regional innovation economics it is argued that a stimulating and supportive regional environment facilitates their innovation activities causing their productivity to differ systematically inter‐regionally (Desrochers, 2001). Hence, the R&D employees can be considered the necessary resource for innovation processes, while the factors presented below represent supportive elements (Broekel and Brenner, 2011). The problem of staffing for innovative economy stays unsolved today. Innovative development of the country is impossible without the highly qualified personnel such as engineers, developers and innovation managers. The absence of the required number of these specialists in government and among the entrepreneurs is a barrier for the innovation development (Gohberg and Kuznecova 2009). Hence, it's to be analyzed the indicator R&D, to help understand where bet- ter to start innovative processes. This very simple insight is, however, seldom discussed in the literature. In contrast to the other regional in- dicators this is not substitutable. Thus, Kazakhstan is presented as one of the most highly educated countries in the world, but in terms of economic development is a little behind the most countries. From a quantitative point of view the scientific potential of qualified specialists does not meet the needs of innovative development. Data on the number of staff employed in R&D can be seen in Table 3. According to these data it is visible, that the human resources are not sufficiently used in science and technology. During the analyzed period the number of employees has been almost unchanged. This table indicates the observed increase in staff in developed regions. However, that there was a significant reduction in the regions such Aktobe, West‐Kazakhstan, Kyzylorda and South‐Kazakhstan there. So, the general condition of science in Kazakhstan demands to reform the current system of innovation to attract the staff in regions with low rate of R&D indicator.
<Table 3> Number of personnel engaged in R&D of Kazakhstan’s regions 2008‐2011 2008, person 2009, person 2010, person 2011, person
The Republic of Kazakhstan 17 774 16 304 15 793 17 021
Akmolinsk region 468 559 555 615 Aktobe region 532 335 157 195
Almaty region 790 547 440 759
Atyrau region 681 633 554 582
East‐Kazakhstan region 657 542 1 757 1 852
Zhambyl region 417 414 474 344
West‐Kazakhstan region 1 140 1 039 170 459
Karaganda region 436 333 735 875
Kostanay region 72 74 415 324
Kyzylorda region 801 841 79 98
Mangistau region 353 259 404 474
Pavlodar region 187 181 258 187
Nord‐Kazakhstan region 147 200 136 106
South‐Kazakhstan 1 636 1 692 295 442
Astana city 1 468 1 430 1 146 1 531
Almaty city 7 989 7 225 8 218 8 178
Source: Statistical Yearbook of the Republic of Kazakhstan by the Agency for statistics (2011)
The regional economic policy should focus on creating of enabling environment for an innovation stage in the underdeveloped regions, such as to create of educational and scientific centers. It should be noted that the localized areas create a significant proportion of the value added of country, and thus the regional conditions largely determine the competitiveness of manufactured goods (Nurlanova, 2009). Thus, the innovative activities support is reasonable for the creation and development of such structures as industrial parks, technology incubators, and data banks of innovation. The key to the R&D and innovation process are the aspects of human and social capital (Broekel and Brenner, 2011). In the current debate wherein the coordinated R&D strategies, especially in levels of innovation, the empirical results are mixed and relatively limited. This might be connected to the fact that, apart from the industrial organizational models on joint ventures, theoretical literature largely remains mute (Cefis et al, 2009). Generalization, indicator R&D shows that for the Kazakhstan it’s important to reform the current system of regional innovative development, as well as to attract staff from the cities‐centers in under- developed regions. But it is obvious, the reproduction of the human capital in the peripheral territories occurs when optimization of the system of education and health in the conditions of depopulation, but reduction in the network should be gradually to be able to adapt for population.
Anel A. Kireyeva, Nailya K. Nurlanova / FOURTH INTERNATIONAL CONFERENCE 77-8281
3.4. Model of innovative cycle
In general, proposed the effective model of the innovation of the innovation cycle in the regions, which includes the separation of the main types of process innovation – technological and managerial. This model is shown in Figure 2. The suggested model consists of five major stages, starting from research and ending with the innovation diffusion. This model reflects the transformation of the results of the innovation process from the reception of new knowledge to a failure of innovation, and demonstrates clearly at what stages require modernization. This model allows defining the nature of the interaction among the participants of the process of innovative development of the region; establishing the procedure for information exchange and the sequence of use of the tools necessary for the effective formation of the innovative sphere of the region.
Technological innovation and modernization
Basic scientific research and the search for new data in the
Start of operation
Adoption of new technology
Phases of innovation cycle
Organizational and managerial innovation
Produc of innovation
Creation new purposes for the regions
Аnalysis and marketing research
Testing sample of innovations in the region
Example of the invention
Manufacture product of innovation
Adoption of organizational and managerial process
Distribution product of innovation in the regions
Technical exploitationproduct of innovation and modernization
Obsolescence product innovation or refusal to use it
Source: compiled by the authors
<Figure 2> Model of innovation cycle
These structural and technological changes occurring in the economy (innovation) are labeled by P. Romer. He pointed out that the innovation cycle creates a new theory of growth (Romer, 1986). In this context, the use of the regional model of the innovation cycle is carried out in two main directions: 1. to develop a specialized and integrated model of functioning of the economy of the regions (introduction of innovations, modernization of production); 2. to create of integrated models, oriented to application in practical activities of the regional innovation.
This work marks a starting point for further research in the field of spatial modernization of the economy. It provides some suggestions for improvement of future studies dealing with this subject. It also delivers industry specific insights into the coherence between the city‐ centers and peripheral regions. On the basis of these research findings of this paper, the practical implications are listed below: First, the analysis suggests that need help for the underdeveloped regions, but we should clearly understand the limits of opportunities and to choose the right mechanisms, even if in the country there are financial resources for large‐scale redistribution. This means that the key to problem solving of modernization of the economy is search and develop the competitive advantages in the medium and under- developed regions, in conjunction with support measures of alignment of the social and economic disparities between the territories. Second, it’s important to create the centers of innovation development outside of urban agglomeration, as they are growth poles and they will play the role of translator’s innovations to the periphery. These centers can be created in a few large regions of the country with high innovation potential in different areas of science. Then, they will be able to get the state support and financing, including foreign. In such cities, should be develop the educational‐scientific complexes (qualitative university and modern research facilities) with an effective system of stimulation of scientific activities. Third, the ranking of the regions can help to allocate traditional conditions (which are difficult to change) and the cumulative conditions, in the form of indicators reflecting the development of new sectors of the economy, the advent of innovative companies, activation of small business, etc. Fourth, it will be necessary to improve the quality of human capital. Thus, the analysis of R&D indicator shows that for the Kazakhstan it’s important to reform the current system of regional innovative development, as well as to attract staff from the cities‐centers in underdeveloped regions. But it is obvious, the reproduction of the human capital in the peripheral territories occurs when optimization of the system of education and health in the conditions of depopulation, but reduction in the network should be gradually to be able to adapt for population. Fifth, proposed by the author's vision the effective model of the innovation process in the regions, which demonstrates clearly at what stages require modernization, starting from research and ending with the innovation diffusion. This work marks the modernization of the economy is realized faster in the regions with the best conditions for the diffusion of innovations, the higher the concentration of the population, a more de- veloped infrastructure and reduced of administrative barriers. It is obvious, that was identified all three barriers of spatial development, as well as clearly they should be minimized. Similar barriers exist in some other countries, for example, Russia, Belarus, Ukraine and others. The results obtained in the research can be applied in other countries with similar spatial barriers on the way to modernization of the economy.
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