The Effect of Large Companies on Spatial Structure in Central and Eastern Europe with a Particular Focus on Enterprises in the Technology, Media _ Telecommunications Industry

Many theoretical and practical works aim at describing the spatial structure of Central and Eastern Europe. This article gives an overview of papers describing the spatial structure of Central and Eastern Europe with different methods. Our goal is to contribute to understanding the Central and Eastern European economic spatial structure and within this we examine the role of the Technology, Media & Telecommunications (TM&T) industry. This industry was chosen because it includes the most knowledge-intensive enterprises. We found that this industry plays a small role in the activities of the most important companies in the region. The capital's major economic centres are the capitals. Thus, both the Central European Pentagon and the New Banana spatial models are suitable for describing the spatial structure. The spatial picture of the TM&T industry is basically concentrated on relatively few large cities, and the region’s most important centre is Warsaw.


INTRODUCTION
The importance of multinational and transnational companies has increased in the globalised world and world economy, as well as the effect of supranational and national institutions and of governmental decisions. Big cities, the stage of many of these activities, have become the leading centres of the world economy. In the last few decades, the increasing economic leading role of the cities, the metropolitan concentration of the "new economy" and the political, administrative, cultural and social importance of cities have become determining factors (Enyedi 2003). Companies, institutions, national economies, different territorial units and individuals are continuously taking part in competition. They have to perform well in different race conditions. According to Enyedi (2012), new spatial forms have appeared lately and the urban agglomeration in its traditional sense has been replaced by the metropolitan region. "Several cities exist without their own agglomerations that cooperate with other cities in a system of special relationships. Cities create networks that serve as a base for regions..." Enyedi (2012, p. 25). The new economy of big cities has a concentrating effect. For companies and institutions, the opportunity to establish relationships, the variety of business services, the formation of "networks promoting interactive learning, creativity and innovation" Enyedi (2012. p. 18) and constant changes require the "closeness" of companies to each other. Therefore clusters, traditional and not traditional economic activities and the related services have become denser in these developed metropolitan regions. It has become accepted that global competition is actually the competition of big cities and regions as well (Bernek 2000;Lengyel & Rechnitzer 2000;Dicken 2007). At the same time, however, besides the intensive competition, closer cooperation than is also appearing in the economic space. Besides big companies, small and medium sized enterprises also are getting involved in global, regional and urban spaces in large numbers (Lux 2012).
The economic leading role of cities is reflected in the space structure and it has an effect on the appearance of nodes and networks. In our paper, we aimed to model the space structure of Central and Eastern Europe and to particularly examine the role of the Technology, Media & Telecommunications (TM&T) industry -which we consider to be the most innovative -in regional processes.

THE SPATIAL STRUCTURE OF CENTRAL AND EASTERN EUROPE IN CONSIDERATION OF CITIES
The regions of Central and Eastern Europe are also included in the literature dealing with the spatial structural forms of Europe. The zones, axes, forms, as well as the polycentric models can be identified for this area as well. Out of the spatial structural forms belonging to the first group, the "Central European Boomerang" may play the most important role. According to Gorzelak (2012), the determinant areas of the form -stretching from Gdansk to Budapest, including Poznan, Wroclaw, Prague, Brno and the triangle of Vienna-Bratislava-Budapest -are the capitals, the real stages of development. The Cucumber model is also linked to this, which is a developmental zone involving Berlin, Prague, Bratislava, Vienna and Budapest (Kunzmann 1998).
The "Red Octopus" of van der Meer (1998) or the "Blue Star" of Dommergues (1992) also include eastern tongues and effects. The other great group of the visualizations of the European space structures emphasizes the explanatory role of the polycentric space structure. According to Kunzmann & Wegener (1991) and Kunzmann (1992Kunzmann ( , 1996, the polycentric structure of our continent is determined by metropolitan regions (that can be found not only inside the "Blue Banana") as a Bunch of Grapes. The polycentric idea has become more and more popular and is a key element of ESDP (1999). It has played an increasingly important role in the European regional cohesion policy (Faludi 2005) and it appears intensively in Eastern European examinations (ESPON 2012) as well.
One of the reasons for the strengthening of the polycentric characteristics is the fact that there has been a spatial concentration process in Europe since the 1990s, whereby differences in the shrinking traditional industry in the small and medium sized cities and the services and high-tech in big cities have increased. At the mezzo (national) level, it is the division of labour among cities, while at the micro (urban region) level, the urban functions and the cooperation within the region are emphasized. In the BBSR (2011) work, however, the political, economic, scientific, transport and cultural functions of the urban areas are those that strongly influence the spatial structure. As for big cities and other cities, many classifications and rankings can be found in the literature, of which the demographic, the functional and the hierarchy-based classifications may be the most popular. Several of them include data for the region we examine; the GaWC classifying, based on functions or the ESPON research, stands out among them. The world according to GaWC is a city-centred world of flows, in contrast to the more familiar state-centred world of boundaries. Cities are assessed in terms of their advanced production services using the interlocking network model. Indirect measures of flows are derived to compute a city's network connectivity -this measures a city's integration into the world city network. The GaWC (Globalization and World Cities Research Network) ranked Prague, Warsaw and Budapest as gamma world cities in the region due to their role in the markets of advertising, banking and legal services (Beaverstock et al. 1999, Csomós 2012, 2015. This classification is in line with the classification of ESPON (2005ESPON ( , 2012, where the capitals of the region are listed on the 4 th MEGA level (Prague, Budapest, Warsaw and Bratislava) followed by cities like Bucharest, Ljubljana, Katowice, Sofia, Lodz and Poznan on the 5 th Mega level. In the hierarchical classification of the big cities of the world, Erdősi (2003) classified Budapest and Prague as international big cities with regional importance. Besides these classifications, other opinions and examinations also strengthen the leading spatial organising role of the capitals in the Central and Eastern European region (Sassen 1991, Enyedi 2003, Pénzes & Fekete 2014 and their regional economic leading role (Csomós 2011), as is shown in the Central European Pentagon model (Liebenath et al. 2007). Most researchers, however, agree that these big cities fall behind the economic leading role of Vienna or the large German cities (Csomós 2011). It is important to mention the "New Banana" model, which is the potential second European economic core. In this model we supplement the development zone with Berlin, Prague, Bratislava, Vienna and Budapest to Ljubljana and Zagreb (SIC 2006).

RESEARCH ASPECTS
In the following sections we examine more thoroughly the background of these spatial structural relations. In our study, we focussed on the following questions: what characterizes the spatial structure of Central and Eastern Europe? What is the regional pattern of the TM&T sector in the region? What are the most important centres, and what spatial structure model can be used to describe the spatial nodes of the sector?
One important aspect in planning the study was to carry out our calculations based on available data that provide accurate information about the status of the economy. Based on these considerations, we selected the Deloitte Central Europe Top 500 Report list, which includes the 500 most important companies of the examined region based on their estimated revenues. This list does not includes banking or insurance companies. Russia and Belarus were not included in the Deloitte Central Europe Top 500 Report due to difficulties in acquiring data from these countries as well as certain doubts concerning the credibility of the available figures (Raźniak et al. 2018). Therefore, 16 countries were included in our study.
The cities that host the headquarters of the companies on the list are included in the examination and the centroids of the cities are shown on our maps. The problem of headquarters and sites arises here, as it often does in statistics. It refers to the fact that the activity of a given company may not be performed in the city where the headquarters are registered. Instead, it may be at another site in many cases. As we did not aim at modelling the spatial distribution of production and its changes but rather the interrelation of the leading role of the centres and the general spatial structural relation through it, we did not deal with this problem, as we assigned the revenues of each company to the city that hosts its headquarters.
We considered it important to model both the current spatial structure and its changes in the recent past. We examined the current situation using the Deloitte Central Europe 500 2015, while we used the 2008 version of this list for comparison.

RESULTS
Analysing the data further (Table 1), we find that Poland shares 38%, the Czech Republic 16%, and Hungary 13% of the 500 most important companies of the region in 2015. As far as the revenues are concerned, the situation is similar, with the only exception that the share of Poland is as high as 36%. The sectoral distribution of the companies (Fig. 1) shows that 37% of the revenues comes from firms categorized in the field of Energy and Resources, followed by Consumer Business and Transportation with 29% and Manufacturing with 25%. The share of the Technology, Media and Telecommunication industry, which is the focus of our research, is only 5%.
The list is revealing in the aspect that it does not include several countries of the region. The companies of Albania, Belarus, Moldova and Montenegro are not among the 500 best performing companies of the region because they did not reach the cut-off value. Another important point is that the data of the companies in Austria, despite having the greatest effect on the Central European spatial structure, are not included in the list, so we cannot calculate with their headquarter data, either.

. Revenues (million EUR) of TOP 500 companies in Central and Eastern Europe, 2015
In Figure 2 we labelled settlements with more than 5 billion euro in corporate revenues. The 500 companies with the highest revenues belonged to 170 settlements in 2008, and to 196 in 2015. The data highlight the outstanding role of capitals and capital regions. The dominance of the cities in the Visegrád countries (Poland, Czech Republic, Slovakia and Hungary) is clear based on the map. Nonetheless, although there are visible spatial clusters, the spatial location of the examined companies is relatively scattered. The differences between the most important spatial structure models will be discussed later.
In essence, we can see this in the table of the 10 most important cities. In addition, the sweep of Plock is also remarkable (largely due to the energy sector) in 2015. For the years under review, the list has changed only on the 9th place, so the order between the big cities can be considered stable (Table 3).
In this article we assume that the control function in the economy of Central and Eastern Europe is performed by cities that are home to at least three top corporate headquarters. The same minimum number for the Command and Control Index in the world economy was listed by Csomós and Derudder (2014). In this article, this yields an Eastern European Command and Control Index (EECCI). The EECCI employs a standardization method based on the mean and the standard deviation of financial values for each corporation studied used by Csomós (2013) to create the Command Control Index (cited by Raźniak et al. 2017).
= � =1 + 2 where: Rixy = proportion of revenues from sales in the total dataset; Sixy = proportion of net income in the total dataset; i = number of company headquarters per city in a given year (i ≥ 3); n = total number of companies headquartered in city x in year y.
Source: Own compilation based on Deloitte Central Europe Top 500 , which indicate the highest economic potential and the strongest command and control functions, were noted for the capital cities of the five largest countries in Central and Eastern Europe: Budapest, Prague, Warsaw, Bratislava and Bucharest. Of the 22 cities, 13 showed an increase in the EECCI index value over the study period, with the biggest increase for Wroclaw (327% relative to 2008). The number of corporate headquarters in Budapest increased over the time period to the greatest extent. Several cities in the region experienced a decline in EECCI: Plzeň (-2%), Warsaw (-18%), Poznan (-40%), Sofia (-72%) and Ljubljana (-98%). Thirteen cities (including Budapest, Prague, Bucharest, Bratislava and Zagreb) experienced an increase in EECCI values, and nine cities experienced a decrease in EECCI values.
We next studied the competitiveness of cities having three or more headquarters. In this approach, development (revenues per capita), efficiency (revenues per net income), profitability (net income per headquarters) and embeddedness (headquarters per capita). The formula can be seen below.
We consider those cities to be competitive where the revenue per capita is higher than the average, while cities that are below the average in this value are at a competitive disadvantage. A complex competitive advantage is established when the revenues per capita and all three components of development for the given city have above average values. We can also speak of a multi-factor advantage if revenues per capita and two factors are above average, or a single-factor competitive advantage if just one factor meets this condition. Table 4 The competitiveness of cities with 3 or more large corporate headquarters  With GIS methods we have attempted to group the settlements on the list in order to determine their spatial pattern and to analyse how these cities effect the spatial structure of the region. In our work we used the ArcGIS 10.1 Grouping Analysis module. In the grouping process, we took into account the income, profits and the population of the given settlements. Several attempts were made to clearly distinguish the delimitation of the four clusters and to characterize them by the formation of groups. In terms of neighbourhoods, the relationship between the nearest 4 neighbours was considered relevant in the calculations.
The four clusters are shown in Figure 4. The first cluster consists of settlements located in the northwest of Poland, while the second consists of Slovenian and Croatian cities. The fourth cluster comprises a significant proportion of southwestern Poland, Czech, Slovakian and Hungarian cities, while the third one includes all other cities outside of it. By examining the features of the four clusters, we can state that the third has more than half of the income and nearly eight tenths of the population. In the case of net revenues, however, Cluster 4 is the most dominant. Cluster 4 is the most decisive factor for both per capita income and per capita revenues which is the region's dominant spatial unit (Table 8).   We can distinguish three clusters for TM&M. The first cluster belongs to Warsaw, which can be considered as the regional centre of the sector. The second cluster is the capitals of the region (except Ljubljana) supplemented with Rzeszów. The remaining cities can be classified in the third cluster. The characteristics of the clusters are shown in Table 9.

CONCLUSION
In our work, we tried to outline the economic structure of Central and Eastern Europe. We have proven that the Central European Pentagon and the New Banana model are best able to describe the region's economic structure. We indicated that the highest economic potential and the strongest command and control functions were noted for the capital cities of the five largest countries in Central and Eastern Europe: Budapest, Prague, Warsaw, Bratislava and Bucharest.
It can be concluded that the role of the TM&T industry within the 500 most important companies in the Central and Eastern Europe region is relatively small. Currently the role of this sector in the 500 most important enterprises appears to be declining, in contrast to the general trends of the world economy. This, in turn, is a general, but in our opinion, short-term -trend in the region, and we consider it important to study as one of the keys to future spatial structure processes.
In terms of the TM&T industry, the importance of the cities in the region, including Warsaw, can be highlighted, which capital is not only this industry but also in general the most important economic centre of the region. From the point of view of spatial structure, the western part of the region can be characterized by positive processes, which correspond most closely to the area bounded by the New Banana spatial structure model.