4. Molnar E. et al.indd 137Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155.DOI: 10.15201/hungeobull.69.2.4 Hungarian Geographical Bulletin 69 2020 (2) 137–155. Introduction It is expected that the “fourth industrial revo- lution” based on the combined application of various key-innovations, the so called cyber- physical systems (CPS) will drastically trans- form current production networks and thus the geography of industry (Boston Consult- ing Group, 2015). Such changes may affect deeply the automotive industry that became an important sector of the East-Central Euro- pean economies over the last three decades. Countries relying on foreign direct invest- ments, following an export-oriented growth model and treating the automotive industry as a strategic sector have increasingly sig- nificant roles in the international production networks of the sector (Schamp, E.W. 2005; Pavlínek, P. et al. 2017). In certain countries vehicle production has a great impact even on the spatial structure of manufacturing industry and in this way, for example in Hungary, it has an important role in shaping spatial economic inequalities (Kiss, É. 2010; Lengyel, I. and Varga, A. 2018). As a result, the future of the automotive industry is also the question of general modernization and regional development. Although the innovations of the fourth Although the innovations of the fourth industrial revolution are already present in industrial revolution are already present in Hungary, the volume of changes is hard to Hungary, the volume of changes is hard to estimate due to the lack of comprehensive estimate due to the lack of comprehensive analyses. Furthermore, the boundaries of analyses. Furthermore, the boundaries of Industry 4.0 are flexible: technological innova-Industry 4.0 are flexible: technological innova- tions occur not as the result of an overwhelm-tions occur not as the result of an overwhelm- ing revolutionary transformation, but rather ing revolutionary transformation, but rather 1 University of Debrecen, H-4032 Debrecen, Egyetem tér 1. Hungary. E-mails: molnar.erno@science.unideb.hu, kozma.gabor@science.unideb.hu, mesmark94@gmail.com 2 Geographical Institute, Research Centre for Astronomy and Earth Sciences. H-1112 Budapest, Budaörsi út. 45. Hungary; University of Sopron, Faculty of Economics, H-9400 Sopron, Erzsébet u. 9. Hungary. E-mail: kiss.eva@csfk.mta.hu Upgrading and the geography of the Hungarian automotive industry in the context of the fourth industrial revolution Ernő M O L N ÁR 1, Gábor K O Z M A 1, Márk M ÉS Z ÁR O S 1 and Éva K I S S 2 Abstract The present study focuses on the geographical investigation of the automotive industry in Hungary that has been integrated into the global production networks as a relevant sector of the reindustrialization in East- Central Europe. The aim of the paper is to reveal the dominant spatial trends in this sector since the economic crisis of 2008, and how these are connected to the issue of upgrading influenced also by digitalization. The analysis is primarily based on the official industrial employment data however other secondary sources are also used. It has been stated that the growth of the Hungarian automotive industry showing to the direction of geographical concentration and expansion is accompanied by the regional stability of the sector. Quality indicators expressing upgrading indicate correlation with the spatiality of car factories and Tier 1 suppliers carrying out more complex activities, but a more significant functional upgrading is only realised in the capital city with increasingly research-development focused profile. Results suggest only moderate upgrading despite the gradual adaptation of Industry 4.0 technologies. Keywords: Industry 4.0, upgrading, automotive industry, geography, Hungary. Received November 2019, Accepted April 2020. Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155.138 as the part of a gradual evolutionary process; as the part of a gradual evolutionary process; their rationally selective adaptation depend-their rationally selective adaptation depend- ing on company demands and possibilities is ing on company demands and possibilities is typical (typical (Szalavetz, A. Szalavetz, A. 2016;2016; Nagy, Cs. Nagy, Cs. et alet al.. 2020). The effects of the transformation are 2020). The effects of the transformation are clear primarily in the increase of the produc-clear primarily in the increase of the produc- tion efficiency – related mostly to automation tion efficiency – related mostly to automation – in the Hungarian automotive industry that – in the Hungarian automotive industry that has predominantly a production function has predominantly a production function ((Losonci, D. Losonci, D. et alet al. . 2019; 2019; Szalavetz, A. Szalavetz, A. 2019). 2019). Nevertheless, certain innovations (modelling, Nevertheless, certain innovations (modelling, simulation, uniform company software) help simulation, uniform company software) help to establish functions beyond production, to to establish functions beyond production, to share certain tasks with the centre and to spe-share certain tasks with the centre and to spe- cialize to partial tasks in some fields relevant cialize to partial tasks in some fields relevant from digitalization point of view (from digitalization point of view (Szalavetz, Szalavetz, A. A. and and Somosi, S. Somosi, S. 2019).2019). At this point Industry 4.0 connects to the At this point Industry 4.0 connects to the research of upgrading. In the case of semi-research of upgrading. In the case of semi- periphery economies like Hungary, up-periphery economies like Hungary, up- grading – which means higher local value grading – which means higher local value added – would be especially important in the added – would be especially important in the change of position in the international pro-change of position in the international pro- duction networks. This could be achieved by duction networks. This could be achieved by increasing the production efficiency, chang-increasing the production efficiency, chang- ing product structures and the functions in ing product structures and the functions in the production networks or by shifting to-the production networks or by shifting to- wards more promising industries and value wards more promising industries and value chains (chains (Humphrey, J. Humphrey, J. and and Schmitz, H.Schmitz, H. 2002; 2002; Kaplinsky, R. Kaplinsky, R. 2013). According to the global 2013). According to the global production network theory upgrading is es-production network theory upgrading is es- sential to avoid exclusion from the produc-sential to avoid exclusion from the produc- tion networks due to the increase of expenses tion networks due to the increase of expenses (by keeping low cost-capability ratios) trig-(by keeping low cost-capability ratios) trig- gered by going beyond the role of cheap gered by going beyond the role of cheap producer (producer (Yeung, H.W. Yeung, H.W. and and Coe, N.M. Coe, N.M. 2015).2015). The role of the “fourth industrial revolu-The role of the “fourth industrial revolu- tion” shall not be regarded absolute, either tion” shall not be regarded absolute, either from the future of the automotive industry from the future of the automotive industry or from the point of view of the upgrad-or from the point of view of the upgrad- ing perspectives of East-Central European ing perspectives of East-Central European economies. The geography of this sector is economies. The geography of this sector is also greatly influenced by new products (e.g. also greatly influenced by new products (e.g. electric, autonomous and connected cars, car electric, autonomous and connected cars, car sharing) and business models. These will in-sharing) and business models. These will in- fluence not only the structure of value chains fluence not only the structure of value chains but also – depending on the involvement of but also – depending on the involvement of info-communication companies playing an info-communication companies playing an increasingly important role in the innova-increasingly important role in the innova- tions of the automotive sector – who leads tions of the automotive sector – who leads these networks (these networks (Peters, SPeters, S. . et alet al. . 2016;2016; Yin, Y Yin, Y. . et alet al.. 2018). Apart from the technology and 2018). Apart from the technology and the products, changes in trade regulations the products, changes in trade regulations determining production organization and determining production organization and stricter environmental protection specifica-stricter environmental protection specifica- tions influencing product development are tions influencing product development are also important factors (also important factors (Dicken, P. Dicken, P. 2011).2011). The present study focuses on the geograph-The present study focuses on the geograph- ical investigation of the automotive industry ical investigation of the automotive industry in Hungary. The dominant regional trends in Hungary. The dominant regional trends since the economic crisis of 2008 are studied since the economic crisis of 2008 are studied and their relationship with the process of up-and their relationship with the process of up- grading influenced by digitalization as well. grading influenced by digitalization as well. The study can be divided into four major The study can be divided into four major structural units. In the first unit – based on structural units. In the first unit – based on the relevant literature background – the spa-the relevant literature background – the spa- tial structure of the automotive industry, its tial structure of the automotive industry, its characteristics in East-Central Europe and in characteristics in East-Central Europe and in Hungary, and the relevant correlations with Hungary, and the relevant correlations with the fourth industrial revolution and upgrad-the fourth industrial revolution and upgrad- ing are discussed. The second unit presents ing are discussed. The second unit presents the database and methods of the empirical the database and methods of the empirical investigation in detail. Regional data are investigation in detail. Regional data are analysed in the third structural unit and the analysed in the third structural unit and the obtained results are interpreted in the fourth obtained results are interpreted in the fourth unit. The main contribution of this paper to unit. The main contribution of this paper to the economic geography literature is that it the economic geography literature is that it reveals the connection between the way of reveals the connection between the way of participation in the international production participation in the international production networks and the geography of the automo-networks and the geography of the automo- tive industry on case of Hungary. tive industry on case of Hungary. The geography of automotive industry reflecting Industry 4.0 and upgrading The automotive industry has a specific “nest- ed structure” (Sturgeon, T. et al. 2008). Car companies and the major suppliers work mainly at a global scale while their produc- tion systems are organised either regionally or at the level of national economies. This phenomenon is the result of the different product preference of regional markets, lo- gistical reasons and political pressure due to the “sensitivity” of the sector expecting cars assembled locally to use preferably lo- cally manufactured parts. Those elements 139Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155. of the production networks that prefer cost efficiency move to the so called integrated peripheries (Pavlínek, P. 2018) where they target regions close to the centre (e.g. the core regions of the EU) in both geographical and cultural sense offering appropriate in- frastructural background and relatively well- trained labour. In this way, they can enjoy the closeness of markets and the possibility of favourable cost-value production (Barta, Gy. 2012; Domański, B. et al. 2013). Beside this tendency, the formation of local Beside this tendency, the formation of local clusters within the above regional production clusters within the above regional production systems can be observed. As platform con-systems can be observed. As platform con- cepts aiming for the partial standardization cepts aiming for the partial standardization of products for different markets and econo-of products for different markets and econo- mies of scale become widespread car produc-mies of scale become widespread car produc- ers require their suppliers to follow them to ers require their suppliers to follow them to new markets (new markets (Humphrey, J. Humphrey, J. andand Memedovic, Memedovic, O. O. 2003). Geographical closeness is especially 2003). Geographical closeness is especially advantageous for the manufacturers of large, advantageous for the manufacturers of large, heavy and model specific parts, not only heavy and model specific parts, not only saving logistic costs but facilitating just-in-saving logistic costs but facilitating just-in- time supply and more flexible responses to time supply and more flexible responses to customer demand. Spatial concentration is customer demand. Spatial concentration is made even stronger by the modularization made even stronger by the modularization of production (of production (Túry, G. Túry, G. 2017). In the course 2017). In the course of modularization, the car is assembled using of modularization, the car is assembled using pre-assembled modules making the estab-pre-assembled modules making the estab- lishment of pre-assembly plants and supplier lishment of pre-assembly plants and supplier parks next to the automobile factories. As parks next to the automobile factories. As suppliers are also interested in the develop-suppliers are also interested in the develop- ment of component parts and modules, they ment of component parts and modules, they move next to automobile factories because move next to automobile factories because direct communication between them is pos-direct communication between them is pos- sible in this way in the course of joint devel-sible in this way in the course of joint devel- opments (opments (Sturgeon, T. Sturgeon, T. et alet al. . 2008).2008). The above regional and local site selection The above regional and local site selection strategies resulted in the development of an strategies resulted in the development of an automotive agglomeration (automotive agglomeration (Grosz, A. Grosz, A. 20062006; ; Pavlínek, P. Pavlínek, P. et al.et al. 2009) identified in East-2009) identified in East- Central Europe extending over the neigh-Central Europe extending over the neigh- bouring areas of Czechia, Slovakia, Poland bouring areas of Czechia, Slovakia, Poland and Hungary crossing the borders of national and Hungary crossing the borders of national economies. This concentration of the auto-economies. This concentration of the auto- motive industry can be explained by – apart motive industry can be explained by – apart from the already discussed factors – histori-from the already discussed factors – histori- cal traditions (cal traditions (Hardi, T. Hardi, T. 2012), multistage 2012), multistage investments of car companies enterinvestments of car companies entering the ing the region after the regime change and gradually region after the regime change and gradually increasing degree of intra-regional division increasing degree of intra-regional division of labour (of labour (Molnár, E. Molnár, E. et al. et al. 2015). Although 2015). Although the recent economic crisis had its effects on the recent economic crisis had its effects on the automotive industry of the region (the automotive industry of the region (Kiss, Kiss, É. É. 2012), its position – despite the partial re-2012), its position – despite the partial re- location of the more labour-intensive activi-location of the more labour-intensive activi- ties – strengthened (ties – strengthened (Pavlínek, PPavlínek, P. . et alet al.. 2017). 2017). Upgrading in the East-Central European Upgrading in the East-Central European automotive industry also had its role in automotive industry also had its role in achieving this better position. However, the achieving this better position. However, the realisation of this upgrading seems to be – realisation of this upgrading seems to be – regarding especially the functional elements regarding especially the functional elements – limited (– limited (Jürgens, U. Jürgens, U. and and Krzywdzinski, M. Krzywdzinski, M. 20112011; Éltető, A. ; Éltető, A. et al.et al. 20152015; Pavlínek, P. ; Pavlínek, P. 2018).2018). According to certain scenarios, the “fourth According to certain scenarios, the “fourth industrial revolution” may question the role industrial revolution” may question the role of the East-Central European region in the of the East-Central European region in the international production networks. While ex-international production networks. While ex- perience so far does not justify negative ex-perience so far does not justify negative ex- pectations, analysts see the state of “the calm pectations, analysts see the state of “the calm before the storm” in the situation (before the storm” in the situation (Szalavetz, Szalavetz, A. A. and and Somosi, S. Somosi, S. 2019). Despite the effects of 2019). Despite the effects of Industry 4.0 innovations on upgrading the Industry 4.0 innovations on upgrading the gap between value production by foreign par-gap between value production by foreign par- ent companies and that by local subsidiaries ent companies and that by local subsidiaries does not seem to be reduced (does not seem to be reduced (Szalavetz, A. Szalavetz, A. 2019). This supports the suspicion that tech-2019). This supports the suspicion that tech- nological innovations cement core-periphery nological innovations cement core-periphery relations (relations (Lengyel, I. Lengyel, I. et alet al.. 2016).2016). Analyses focus very little on the local ef-Analyses focus very little on the local ef- fects of Industry 4.0. However, there is a fects of Industry 4.0. However, there is a suggestion that the adaptation of innova-suggestion that the adaptation of innova- tions is influenced by the dual character of tions is influenced by the dual character of the Hungarian industry. Certain industries the Hungarian industry. Certain industries (including automotive manufacturing), (including automotive manufacturing), large companies and businesses with foreign large companies and businesses with foreign ownership (i.e. actors with better resource ownership (i.e. actors with better resource supply) are ahead in the process. Their un-supply) are ahead in the process. Their un- equal spatial distribution also influences equal spatial distribution also influences the geography of the adaptation of innova-the geography of the adaptation of innova- tions in Hungary (tions in Hungary (Nick, G. Nick, G. et alet al.. 2019). The 2019). The applications of new technologies take place applications of new technologies take place gradually and this means primarily the de-gradually and this means primarily the de- velopment of existing capacities instead of velopment of existing capacities instead of building new factories (building new factories (Szalavetz, A.Szalavetz, A. 2016). 2016). Finally, according to some opinions, Industry Finally, according to some opinions, Industry 4.0 appreciates locally available competent 4.0 appreciates locally available competent suppliers: in changing circumstances not for-suppliers: in changing circumstances not for- Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155.140 eign investments bring a technological catch-eign investments bring a technological catch- up, but the technological catch-up of local up, but the technological catch-up of local businesses generates foreign investments businesses generates foreign investments ((Szalavetz, A. Szalavetz, A. and and Somosi, S. Somosi, S. 2019). These 2019). These ideas indicate the important role of quality ideas indicate the important role of quality location choice factors that are difficult to location choice factors that are difficult to reproduce and of local or regional clusters reproduce and of local or regional clusters with a significant history even in the age of with a significant history even in the age of Industry 4.0.Industry 4.0. The role of local clusters in upgrading is The role of local clusters in upgrading is explained by the idea of “dynamic strategic explained by the idea of “dynamic strategic coupling” in the global production network coupling” in the global production network concept. According to this, the development concept. According to this, the development of a region is the result of successful global – of a region is the result of successful global – local interactions influenced at a local scale local interactions influenced at a local scale by the concentration of knowledge, abilities by the concentration of knowledge, abilities and experience in the industry (economies and experience in the industry (economies of scale), and by co-operation and learning of scale), and by co-operation and learning possibilities (economies of scope) (possibilities (economies of scope) (Coe, N.M. Coe, N.M. andand Hess, M. Hess, M. 2011). The regional institutional 2011). The regional institutional background is important in the coupling pro-background is important in the coupling pro- cess and it can be regarded as the derivate cess and it can be regarded as the derivate of national and supranational actors that is of national and supranational actors that is specific to the location. Institutes can steer up-specific to the location. Institutes can steer up- grading forward with strengthening local fac-grading forward with strengthening local fac- tors while local factors showing greater com-tors while local factors showing greater com- plementarity with the demands of companies plementarity with the demands of companies controlling production networks strengthen controlling production networks strengthen the position of regional institutes against glob-the position of regional institutes against glob- al actors (al actors (Coe, N.M. Coe, N.M. et alet al. . 2004). Accordingly, 2004). Accordingly, the East-Central European automotive cluster the East-Central European automotive cluster presented earlier – based on local synergies presented earlier – based on local synergies – has relatively advantageous chances for up-– has relatively advantageous chances for up- grading (grading (Pavlínek, P. Pavlínek, P. et al.et al. 2009).2009). The analysis of the relationship between The analysis of the relationship between spatial concentrations and upgrading occurs spatial concentrations and upgrading occurs in several papers on automotive industry. In in several papers on automotive industry. In the case of the supplier network of the Czech the case of the supplier network of the Czech Skoda, for example, simultaneous spatial ex-Skoda, for example, simultaneous spatial ex- pansion and concentration were observed. pansion and concentration were observed. While low cost and excessive labour are of-While low cost and excessive labour are of- fered in the periphery, quality location fac-fered in the periphery, quality location fac- tors dominate in the traditional core areas. tors dominate in the traditional core areas. The development of spatial concentrations The development of spatial concentrations is driven by increasing interdependence of is driven by increasing interdependence of automobile factories and suppliers due to automobile factories and suppliers due to modularization, just-in-time organisation of modularization, just-in-time organisation of supply, reducing logistic costs and service supply, reducing logistic costs and service requirements for the products that can be sat-requirements for the products that can be sat- isfied easier from closer areas (isfied easier from closer areas (Pavlínek, P. Pavlínek, P. andand Janák, L. Janák, L. 2007). According to experience 2007). According to experience from Poland, the embedding of automobile from Poland, the embedding of automobile manufacturers and their shift towards prod-manufacturers and their shift towards prod- ucts with higher value added, i.e. upgrading ucts with higher value added, i.e. upgrading results in the rise of spatial agglomerations. results in the rise of spatial agglomerations. In the development of the largest concentra-In the development of the largest concentra- tion in Upper Silesia, for example, histori-tion in Upper Silesia, for example, histori- cal traditions, establishment of automobile cal traditions, establishment of automobile factories as focus points in the neighbouring factories as focus points in the neighbouring Czech and Slovakian regions, the concentra-Czech and Slovakian regions, the concentra- tion of part factories, the local possibilities of tion of part factories, the local possibilities of research and development and higher edu-research and development and higher edu- cation together with the concentration of in-cation together with the concentration of in- dustry and population all had a major role; dustry and population all had a major role; and they provided greater resistance for the and they provided greater resistance for the region at the time of the crisis (region at the time of the crisis (Gwosdz, K. Gwosdz, K. andand Micek, G. Micek, G. 2010; 2010; Domański, B. Domański, B. et alet al. . 2013).2013). The spatial structure of the Hungarian au-The spatial structure of the Hungarian au- tomotive industry with no automobile man-tomotive industry with no automobile man- ufacturing traditions and supplier network ufacturing traditions and supplier network prior to the regime change (in contrast to the prior to the regime change (in contrast to the Czech or Polish examples) can be explained Czech or Polish examples) can be explained by the importance of geographical location by the importance of geographical location close to the western regions, industrial tra-close to the western regions, industrial tra- ditions associated with commercial vehicle ditions associated with commercial vehicle production (skilled labour) and well-estab-production (skilled labour) and well-estab- lished infrastructure (motorways, industrial lished infrastructure (motorways, industrial parks) (parks) (Barta, Gy. Barta, Gy. 20022002; Kiss, É. ; Kiss, É. andand Tiner, Tiner, T. T. 2012). The retaining strength of industrial 2012). The retaining strength of industrial concentrations is suggested by the regional concentrations is suggested by the regional stability of the automotive industry and also stability of the automotive industry and also by its decreasing and increasing spatial con-by its decreasing and increasing spatial con- centration at the time of growth and recession centration at the time of growth and recession respectively (respectively (Molnár, E. Molnár, E. 2013). The process 2013). The process of embedding – interpreted initially via the of embedding – interpreted initially via the development of the local supplier network development of the local supplier network and then in a much more complex way – re-and then in a much more complex way – re- ceived significant attention due to the domi-ceived significant attention due to the domi- nance of the greenfield investments of large nance of the greenfield investments of large foreign companies (foreign companies (Sass, M. Sass, M. and and Szanyi, M. Szanyi, M. 20042004; Fekete, D. ; Fekete, D. andand Rechnitzer, J. Rechnitzer, J. 2019). 2019). The relationship between embedding and The relationship between embedding and upgrading occur in the strategy of the major upgrading occur in the strategy of the major companies in the automotive industry estab-companies in the automotive industry estab- lished in Hungary following the turn of the lished in Hungary following the turn of the millennium that accelerate their embedding millennium that accelerate their embedding in order to create the local atmosphere re-in order to create the local atmosphere re- quired for upgrading sooner (quired for upgrading sooner (Józsa, V. Józsa, V. 2019).2019). 141Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155. The automotive industry – due to its size The automotive industry – due to its size and extensive industrial connections – leaves and extensive industrial connections – leaves its mark on the geography of the entire its mark on the geography of the entire Hungarian industry. Micro- and macro-scale Hungarian industry. Micro- and macro-scale radical changes, the strong differentiation of radical changes, the strong differentiation of the spatial dynamics of the industry were in the spatial dynamics of the industry were in the background of the drastic transforma-the background of the drastic transforma- tion at the time of the regime change (tion at the time of the regime change (Kiss, Kiss, É. É. 2002;2002; Nemes Nagy, J. Nemes Nagy, J. and and Lőcsei, H. Lőcsei, H. 2015). 2015). The dominance of the north-western part of The dominance of the north-western part of the country and that of the agglomeration the country and that of the agglomeration around the capital became general; how-around the capital became general; how- ever, this seems to ease somewhat as a con-ever, this seems to ease somewhat as a con- sequence of the reindustrialization – partly sequence of the reindustrialization – partly due to automotive investments – of certain due to automotive investments – of certain counties in North Hungary and the Great counties in North Hungary and the Great Plain after 2008 (Plain after 2008 (Barta, Gy. Barta, Gy. 2002;2002; Kiss, É. Kiss, É. 2010; 2010; Lux, G. Lux, G. 2017).2017). The inclination of the automotive industry The inclination of the automotive industry to form clusters at the local level, the quality to form clusters at the local level, the quality factors of selecting site location associated factors of selecting site location associated with the spatial concentrations of the sector with the spatial concentrations of the sector and relevant upgrading (and Industry 4.0), and relevant upgrading (and Industry 4.0), and the experience that the geographical and the experience that the geographical transformations of the industry reflect the transformations of the industry reflect the structural changes of those involved form structural changes of those involved form the theoretical basis of the present spatial the theoretical basis of the present spatial research at the subnational level.research at the subnational level. Database and methods Industrial employment data necessary for the county level (NUTS 3) analysis were provided by Hungarian Central Statistical Office. The 20 units (the capital city and 19 counties) al- low only a general regional analysis, but no more detailed time series data are available. It has to be noted that, although the interpre- tation of counties as industrial geographical units always raises questions, the use of county data has a well-established practice. Official- ly, counties are classified into seven regions (NUTS 2 level) in Hungary. But, in this study the regional division of counties follows the historical traditions of Hungarian industry and the location choice of the automotive firms. Employment data were chosen primarily Employment data were chosen primarily because they are suitable for structural analy-because they are suitable for structural analy- ses. Linking the geography of the automotive ses. Linking the geography of the automotive industry to the issue of upgrading influenced industry to the issue of upgrading influenced by Industry 4.0 makes it necessary to focus by Industry 4.0 makes it necessary to focus on indices reflecting structural changes. For on indices reflecting structural changes. For this the number of non-manual workers and this the number of non-manual workers and average gross earnings of those working in average gross earnings of those working in the sector were used. A higher proportion of the sector were used. A higher proportion of non-manual workers suggest the lower signifi-non-manual workers suggest the lower signifi- cance of labour-intensive physical activities, cance of labour-intensive physical activities, increasing automation of production and also increasing automation of production and also the significant role of research and develop-the significant role of research and develop- ment, logistics and other strategic functions ment, logistics and other strategic functions beyond direct production (beyond direct production (Szalavetz, A. Szalavetz, A. andand Somosi, S. Somosi, S. 2019). As different activity structures 2019). As different activity structures may be behind the data on the employment may be behind the data on the employment of manual and non-manual workers, ratios of of manual and non-manual workers, ratios of average gross earnings relative to the national average gross earnings relative to the national industry and local economic average were also industry and local economic average were also analysed. It was presumed that the differenc-analysed. It was presumed that the differenc- es of the indicator reflect not only the labour es of the indicator reflect not only the labour market differences of the counties but also the market differences of the counties but also the structure of automotive industrial activities. To structure of automotive industrial activities. To ground spatial research at the subnational level ground spatial research at the subnational level by investigating the effects of technological in-by investigating the effects of technological in- novations on employment data is not without novations on employment data is not without history in Hungary (history in Hungary (Tóth, I.JTóth, I.J. . et alet al.. 2016).2016). At the same time, a number of factors make At the same time, a number of factors make it difficult to accurately outline the spatial it difficult to accurately outline the spatial footprint of the automotive industry. One footprint of the automotive industry. One of the factors is that the activities classified of the factors is that the activities classified in the statistical category of motor vehicle in the statistical category of motor vehicle industry do not cover the entire automo-industry do not cover the entire automo- tive industry because of the wide range of tive industry because of the wide range of suppliers integrated into its value chains. suppliers integrated into its value chains. Approximately there are 480 operating com-Approximately there are 480 operating com- panies and more than 100,000 employees in panies and more than 100,000 employees in the motor vehicle industry, but according to the motor vehicle industry, but according to another source there is 900 companies and another source there is 900 companies and 175,000 employees (175,000 employees (MAGE MAGE 2020). The latter 2020). The latter numbers also include the automotive sup-numbers also include the automotive sup- pliers registered in other industries. At the pliers registered in other industries. At the same time, the aggregation of employment same time, the aggregation of employment data at the sector level makes it impossible data at the sector level makes it impossible to systematically filter out suppliers outside to systematically filter out suppliers outside the motor vehicle industry, therefore the the motor vehicle industry, therefore the present analysis was made using the smaller present analysis was made using the smaller data that could be clearly assigned to the au-data that could be clearly assigned to the au- tomotive industry. As a result, the present tomotive industry. As a result, the present analysis can be applied primarily to the ‘up-analysis can be applied primarily to the ‘up- Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155.142 per regions’ of the supplier pyramids domi-per regions’ of the supplier pyramids domi- nated by transnational companies. However, nated by transnational companies. However, focusing on the structural changes, this lim-focusing on the structural changes, this lim- itation – due to the uneven distribution of itation – due to the uneven distribution of value-added in the supplier pyramid and value-added in the supplier pyramid and the producer-driven character of the value the producer-driven character of the value chain – can only slightly influence the valid-chain – can only slightly influence the valid- ity of our findings. A characteristic feature ity of our findings. A characteristic feature of functional upgrading the development of of functional upgrading the development of local suppliers registered in other industries local suppliers registered in other industries remains partly hidden.remains partly hidden. Another problem is the fact that the in-Another problem is the fact that the in- dustrial classification of companies con-dustrial classification of companies con- sidered along value chains varies in time. sidered along value chains varies in time. Consequently, there may be statistical rea-Consequently, there may be statistical rea- sons – in addition to real developments – sons – in addition to real developments – for the increase and decrease in data. Data for the increase and decrease in data. Data register based on the headquarters of com-register based on the headquarters of com- panies has a similar effect, which assigns panies has a similar effect, which assigns the performance of companies present in the performance of companies present in some counties to the county designated as some counties to the county designated as headquarters, showing its role as more sig-headquarters, showing its role as more sig- nificant than it is. When analysing employ-nificant than it is. When analysing employ- ment data, the fact that the employment of ment data, the fact that the employment of temporary workers offered by specialized temporary workers offered by specialized agencies became widespread in the studied agencies became widespread in the studied period has to be addressed. The automotive period has to be addressed. The automotive industry employed the greatest number of industry employed the greatest number of temporary workers – 16,900 people – in 2018 temporary workers – 16,900 people – in 2018 (Pénzügyminisztérium 2019). In the light of (Pénzügyminisztérium 2019). In the light of the sector’s statistics this not only means that the sector’s statistics this not only means that they do not contain a large portion of tem-they do not contain a large portion of tem- porary workers and the real significance of porary workers and the real significance of motor vehicle industry is underestimated, motor vehicle industry is underestimated, but also that in some counties temporary but also that in some counties temporary workers can also be the cause of reduced workers can also be the cause of reduced employment (not shrinking in fact) in auto-employment (not shrinking in fact) in auto- motive industry. Since the ratio of temporary motive industry. Since the ratio of temporary workers is higher among manual workers, workers is higher among manual workers, therefore this phenomenon also affects the therefore this phenomenon also affects the indicators of employment structure.indicators of employment structure. In order to identify dominant spatial In order to identify dominant spatial trends (concentration vs. expansion, dif-trends (concentration vs. expansion, dif- ferences in quantity and quality indices), ferences in quantity and quality indices), simple spatial inequality indices (concentra-simple spatial inequality indices (concentra- tion index, Hoover index) were also calcu-tion index, Hoover index) were also calcu- lated based on employment data. Changes lated based on employment data. Changes in centres of gravity were also examined. In in centres of gravity were also examined. In the analysis, employment data were com-the analysis, employment data were com- plemented with other secondary sources. plemented with other secondary sources. In addition to foreign trade statistics, the In addition to foreign trade statistics, the spatial data of economic organisations, data spatial data of economic organisations, data of investments supported by so called indi-of investments supported by so called indi- vidual government decision, annual reports vidual government decision, annual reports from certain companies and press releases from certain companies and press releases on businesses in the industry were utilized. on businesses in the industry were utilized. The timeframe for the research (2008–2018) The timeframe for the research (2008–2018) is optimal for comparison not only because is optimal for comparison not only because of the unchanged statistical framework of of the unchanged statistical framework of the industry, but it also enables the uniform the industry, but it also enables the uniform analysis of the economic crisis, the recovery analysis of the economic crisis, the recovery and then the new growth period together.and then the new growth period together. Description of the spatial processes The long-term growth of employment in the motor vehicle industry in Hungary has only been temporarily disrupted by the economic crisis. The number of people employed fell by 18 per cent from 2008 to 2009, only to increase again every year afterwards. Pre-crisis condi- tions were restored roughly in 2013, but taken as a whole there was a 35 per cent increase between 2008 and 2018. Although the county concentration of employment in the period of crisis and recovery was rather strengthened and then slightly weakened, the distribution of the automotive industry between regions is stable. The loss of significance of Central Hun- gary was offset by an increase in the share of three other regions. However, while in the first half of the period Northern Transdanubia was the winner of a moderate realignment, in recent years the share of Northern Hungary and the Great Plain could grow even at the expense of the former (Table 1). The development trajectory of each county The development trajectory of each county is more colourful. Between 2008 and 2013 is more colourful. Between 2008 and 2013 half of the counties showed an increase in the half of the counties showed an increase in the employment of automotive industry while employment of automotive industry while between 2013 and 2018 17 of the 20 spatial between 2013 and 2018 17 of the 20 spatial units. However, in almost a third of the units. However, in almost a third of the counties – including Komárom-Esztergom counties – including Komárom-Esztergom and Pest – employment in the sector in 2018 and Pest – employment in the sector in 2018 did not come even close to the level of 2008. did not come even close to the level of 2008. Apart from the rise of Győr-Moson-Sopron, Apart from the rise of Győr-Moson-Sopron, the increasing number of counties with sig-the increasing number of counties with sig- 143Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155. nificant employment in automotive industry nificant employment in automotive industry can be observed. Two of the newly emerging can be observed. Two of the newly emerging counties are east of the Danube: Bács-Kiskun counties are east of the Danube: Bács-Kiskun and Borsod-Abaúj-Zemplén, however, have and Borsod-Abaúj-Zemplén, however, have an increasing ratio of employment in the au-an increasing ratio of employment in the au- tomotive industry in their region tomotive industry in their region (Figure 1 (Figure 1 andand 2). 2). The change in the number of non-manual The change in the number of non-manual workers mostly followed the indicators of workers mostly followed the indicators of the total number of employees. The ratio of the total number of employees. The ratio of non-manual workers increased almost con-non-manual workers increased almost con- tinuously and approached the average of the tinuously and approached the average of the manufacturing industry. The spatial concen-manufacturing industry. The spatial concen- tration of non-manual workers remained al-tration of non-manual workers remained al- ways below the index calculated for the total ways below the index calculated for the total number of employees, while differences in the number of employees, while differences in the distribution of non-manual and manual work-distribution of non-manual and manual work- ers decreased. Most non-manual workers are ers decreased. Most non-manual workers are related to the automotive industry of Győr-related to the automotive industry of Győr- Moson-Sopron, Fejér and the rapidly growing Moson-Sopron, Fejér and the rapidly growing Veszprém county. Apart from the latter, only Veszprém county. Apart from the latter, only Budapest and some eastern counties showed Budapest and some eastern counties showed ratios of non-manual workers characteristi-ratios of non-manual workers characteristi- cally above the national average (cally above the national average (Table 2).Table 2). In counties with the largest expansion of In counties with the largest expansion of employment in the automotive industry, the employment in the automotive industry, the ratio of non-manual workers increased only ratio of non-manual workers increased only slightly. This suggests that the growth of this slightly. This suggests that the growth of this sector remains mainly linked to the deploy-sector remains mainly linked to the deploy- ment of production capacities requiring pri-ment of production capacities requiring pri- marily manual workers. Labour hire regis-marily manual workers. Labour hire regis- tered not in the automotive industry may also tered not in the automotive industry may also contribute to the above trends. It also causes, contribute to the above trends. It also causes, on the one hand a more modest increase of on the one hand a more modest increase of employment in the automotive industry, and employment in the automotive industry, and on the other hand a higher ratio of non-man-on the other hand a higher ratio of non-man- ual workers. Significant differences among the ual workers. Significant differences among the counties indicate internal structural differenc-counties indicate internal structural differenc- es in the sector. Budapest pulled from the rest es in the sector. Budapest pulled from the rest of the counties from 2017 to 2018, however, of the counties from 2017 to 2018, however, Table 1. Number and share of employees in the Hungarian motor vehicle industry, 2008–2018 Regions, counties 2008 2009 2013 2018 Number % Number % Number % Number % Central Hungary Budapest Pest Northern Transdanubia Fejér Győr-Moson-Sopron Komárom-Esztergom Vas Veszprém Southern Transdanubia Baranya Somogy Tolna Zala Northern Hungary Borsod-Abaúj-Zemplén Heves Nógrád Great Plain Bács-Kiskun Békés Csongrád Hajdú-Bihar Jász-Nagykun-Szolnok Szabolcs-Szatmár-Bereg 11,562 2,468 9,094 45,411 11,069 14,701 9,764 5,364 4,513 2,711 891 202 539 1,079 9,433 3,457 5,120 856 7,615 2,477 1,929 392 218 754 1,845 15.1 3.2 11.9 59.2 14.4 19.2 12.7 7.0 5.9 3.5 1.2 0.3 0.7 1.4 12.3 4.5 6.7 1.1 9.9 3.2 2.5 0.5 0.3 1.0 2.4 9,153 2,178 6,975 37,891 9,319 12,607 7,756 4,724 3,485 2,132 626 242 399 865 7,765 3,099 3,930 736 5,992 1,967 1,525 298 191 708 1,303 14.5 3.5 11.1 60.2 14.8 20.0 12.3 7.5 5.5 3.4 1.0 0.4 0.6 1.4 12.3 4.9 6.2 1.2 9.5 3.1 2.4 0.5 0.3 1.1 2.1 8,332 1,652 6,680 46,593 8,307 20,028 5,990 6,536 5,732 3,350 980 304 741 1,325 8,328 5,768 2,338 222 7,457 5,358 128 143 210 905 713 11.3 2.2 9.0 62.9 11.2 27.0 8.1 8.8 7.7 4.5 1.3 0.4 1.0 1.8 11.2 7.8 3.2 0.3 10.1 7.2 0.2 0.2 0.3 1.2 1.0 9,557 2,709 6,848 64,695 10,811 25,279 8,245 8,974 11,386 3,748 1,189 239 1,002 1,318 14,139 9,237 4,055 847 11,384 9,142 210 205 286 958 583 9.2 2.6 6.6 62.5 10.4 24.4 8.0 8.7 11.0 3.6 1.1 0.2 1.0 1.3 13.7 8.9 3.9 0.8 11.0 8.8 0.2 0.2 0.3 0.9 0.6 Hungary total 76,732 100.0 62,933 100.0 74,060 100.0 103,523 100.0 Source: Central Statistical Office, Budapest, 2019. Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155.144 Fig. 1. Dynamics of the Hungarian automotive industry by the number of employees between 2008 and 2013 and its state in 2013. Source: Data of Central Statistical Office. Fig. 2. Dynamics of the Hungarian automotive industry by the number of employees between 2013 and 2018 and its state in 2018. Source: Data of Central Statistical Office. 145Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155. the increase in the rate of non-manual work-the increase in the rate of non-manual work- ers was accompanied by a sharp decline in ers was accompanied by a sharp decline in the number of people employed in the sector.the number of people employed in the sector. Average gross earnings recorded in the Average gross earnings recorded in the motor vehicle industry showed a significant motor vehicle industry showed a significant increase with values above the national aver-increase with values above the national aver- age throughout the studied period. The spa-age throughout the studied period. The spa- tial concentration of gross earnings exceeded tial concentration of gross earnings exceeded that of the employees, while the differences that of the employees, while the differences in the spatial distribution of employed peo-in the spatial distribution of employed peo- ple and gross earnings decreased. Counties ple and gross earnings decreased. Counties are polarized: solely the front-runner Győr-are polarized: solely the front-runner Győr- Moson-Sopron performed always above the Moson-Sopron performed always above the industrial average. Regarding the counties industrial average. Regarding the counties with high employment growth, Veszprém with high employment growth, Veszprém was also able to achieve relative average was also able to achieve relative average gross earnings growth. Although average gross earnings growth. Although average gross earnings also depend on the local la-gross earnings also depend on the local la- bour market environment, it is notable that bour market environment, it is notable that the figures of counties outstanding from the the figures of counties outstanding from the national average of the motor vehicle indus-national average of the motor vehicle indus- try – with the exception of Budapest – also try – with the exception of Budapest – also showed the highest difference compared to showed the highest difference compared to local average earnings local average earnings (Table 3).(Table 3). As a summary, it can be concluded that, As a summary, it can be concluded that, between 2008 and 2018, on the one hand, between 2008 and 2018, on the one hand, the number of counties standing out in rela-the number of counties standing out in rela- tion to at least one of the analysed indicators tion to at least one of the analysed indicators (share of non-manual workers, average gross (share of non-manual workers, average gross earnings) was reduced, and, on the other earnings) was reduced, and, on the other hand, showed greater overlap with the major hand, showed greater overlap with the major locations of the sector locations of the sector (Figure 3 (Figure 3 andand 4). 4). Not only the industry as a whole, but also Not only the industry as a whole, but also its qualitative indicators show increasing spa-its qualitative indicators show increasing spa- tial concentrations only during the period of tial concentrations only during the period of crisis and recovery, while differences in the crisis and recovery, while differences in the distribution of qualitative and quantitative distribution of qualitative and quantitative indicators decrease. As a consequence there indicators decrease. As a consequence there is a geographical convergence regarding the is a geographical convergence regarding the (quantity and) quality factors (quantity and) quality factors (Figure 5 (Figure 5 andand 6). 6). Table 2. Number and share of non-manual employees in the Hungarian motor vehicle industry, 2008–2018 Regions, counties 2008 2009 2013 2018 Number % Number % Number % Number % Central Hungary Budapest Pest Northern Transdanubia Fejér Győr-Moson-Sopron Komárom-Esztergom Vas Veszprém Southern Transdanubia Baranya Somogy Tolna Zala Northern Hungary Borsod-Abaúj-Zemplén Heves Nógrád Great Plain Bács-Kiskun Békés Csongrád Hajdú-Bihar Jász-Nagykun-Szolnok Szabolcs-Szatmár-Bereg 1,822 509 1,313 8,176 2,016 2,937 1,323 930 970 359 155 35 72 97 2,332 840 1,254 238 1,516 657 433 49 47 169 161 15.8 20.6 14.4 18.0 18.2 20.0 13.5 17.3 21.5 13.2 17.4 17.3 13.4 9.0 24.7 24.3 24.5 27.8 19.9 26.5 22.4 12.5 21.6 22.4 8.7 1,647 498 1,149 7,713 1,843 2,723 1,378 896 873 316 131 34 59 92 2,109 835 1,054 220 1,352 554 390 38 47 171 152 18.0 22.9 16.5 20.4 19.8 216 17.8 19.0 25.1 14.8 20.9 14.0 14.8 10.6 27.2 26.9 26.8 29.9 22.6 28.2 25.6 12.8 24.6 24.2 11.7 1,779 464 1,315 10,804 2,150 4,236 1,500 1,323 1,595 502 177 49 138 138 2,061 1,276 731 54 1,860 1,413 42 37 47 196 125 21.4 28.1 19.7 23.2 25.9 21.2 25.0 20.2 27.8 15.0 18.1 16.1 18.6 10.4 24.7 22.1 31.3 24.3 24.9 26.4 32.8 25.9 22.4 21.7 17.5 2,987 1,294 1,693 16,433 3,085 5,867 2,379 1,970 3,132 600 204 24 192 180 3,805 2,337 1,314 154 2,831 2,317 66 53 68 223 104 31.3 47.8 24.7 25.4 28.5 23.2 28.9 22.0 27.5 16.0 17.2 10.0 19.2 13.7 26.9 25.3 32.4 18.2 24.9 25.3 31.4 25.9 23.8 23.3 17.8 Hungary total 14,205 18.5 13,137 20.9 17,006 23.0 26,656 25.7 Source: Central Statistical Office, Budapest, 2019. Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155.146 Fig. 4. Types of counties by share of non-manual workers and average gross earnings in the Hungarian motor vehicle industry, 2018. Source: Data of Central Statistical Office. Table 3. Average gross earnings of employees in the Hungarian motor vehicle industry in percentage of the sector’s average and the average of the given area’s economy, 2008–2018 Regions, counties 2008 2009 2013 2018 NAS% GAE% NAS % GAE% NAS% GAE% NAS% GAE% Central Hungary Budapest Pest Northern Transdanubia Fejér Győr-Moson-Sopron Komárom-Esztergom Vas Veszprém Southern Transdanubia Baranya Somogy Tolna Zala Northern Hungary Borsod-Abaúj-Zemplén Heves Nógrád Great Plain Bács-Kiskun Békés Csongrád Hajdú-Bihar Jász-Nagykun-Szolnok Szabolcs-Szatmár-Bereg 92 103 89 106 84 126 109 112 85 58 74 60 59 44 106 84 124 84 83 112 77 56 62 96 51 82 85 108 128 98 145 126 146 112 75 91 82 74 61 136 109 149 116 112 154 108 73 81 134 71 91 105 88 107 83 132 105 104 94 56 71 60 58 43 101 83 118 79 84 113 78 55 63 95 55 83 89 108 132 102 156 123 140 128 76 93 86 74 61 135 113 146 115 119 161 114 73 84 140 81 85 75 87 108 85 126 98 102 101 58 65 60 63 51 91 85 109 60 93 99 85 72 65 82 76 89 75 119 144 112 156 125 146 150 90 100 95 88 82 142 138 149 103 151 156 148 110 101 133 132 95 108 90 107 88 123 97 100 102 62 66 64 62 58 88 84 100 62 93 97 70 74 66 86 61 100 107 123 137 112 148 123 135 141 93 101 96 84 92 132 132 135 100 144 142 118 107 100 131 108 Hungary total 100 107 100 110 100 126 100 124 Notes: NAS% = in percentage of the sector’s (motor vehicle industry) average. GAE% = in percentage of the average of the given area’s (county, region) economy. Source: Central Statistical Office, Budapest, 2019. Fig. 3. Types of counties by share of non-manual workers and average gross earnings in the Hungarian motor vehicle industry, 2008. Source: Data of Central Statistical Office. 0 50 km High share of both indicators (share of non-manual worker above the national average, gross earnings above 90% of the national average) Low share of both indicators High share of average gross earnings (above 90% of the national average) High share of employed non-manual workers (above the national average) 0 50 km High share of both indicators (share of non-manual worker above the national average, gross earnings above 90% of the national average) Low share of both indicators High share of average gross earnings (above 90% of the national average) High share of employed non-manual workers (above the national average) 147Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155. According to our calculations the location According to our calculations the location of the centres of gravity of the studied indica-of the centres of gravity of the studied indica- tors is in the central part of Transdanubia. The tors is in the central part of Transdanubia. The indicators also show a typically westward indicators also show a typically westward shift between 2008 and 2018. The centres of shift between 2008 and 2018. The centres of gravity of non-manual employment can be gravity of non-manual employment can be found further east, while those of the gross found further east, while those of the gross earnings are further north-west compared to earnings are further north-west compared to the number of people employed the number of people employed (Figure 7).(Figure 7). The results declined that – despite the The results declined that – despite the strengthening of some eastern “bridgeheads” strengthening of some eastern “bridgeheads” – a significant eastern shift in the Hungarian – a significant eastern shift in the Hungarian automotive industry would have taken place. automotive industry would have taken place. The impact of Budapest and some better-The impact of Budapest and some better- performing eastern counties on non-manual performing eastern counties on non-manual employment as well as the effect of Northern employment as well as the effect of Northern Transdanubia showing higher average values Transdanubia showing higher average values in the spatiality of earnings are also accentu-in the spatiality of earnings are also accentu- ated. The position of the centres of gravity also ated. The position of the centres of gravity also reflects the recurrence of the traditional North–reflects the recurrence of the traditional North– South differences of Hungarian industry.South differences of Hungarian industry. Explanation of the spatial processes The geography of the Hungarian motor vehi- cle industry reflects the location decision of foreign companies and – to a much lesser ex- tent – the spatiality of the emerging domestic automotive industrial suppliers. 97 per cent of the turnover in the sector can be related to foreign-controlled companies, and this is well above the national average of 53 per cent and one of the highest in the manufacturing industry (KSH, 2016). The expansion of the employment in the automotive industry in- dicates that Hungary remains an investment destination, and the negative expectations associated with the spread of Industry 4.0 innovations do not appear to be confirmed during the studied period. Automation has not caused a decrease: even if some of the workforce was liberated due to technological reasons, it is mostly redeployed within the firms in “headcount neutral transformation”, because capacity expansion is still common. The progress of automation is delayed partly, because foreign workers are employed in or- der to ease labour shortage (Székely, S. 2019). The vast majority of the sector’s employ-The vast majority of the sector’s employ- ment growth is attributable to some promi-ment growth is attributable to some promi- nent companies in five counties. These are nent companies in five counties. These are mostly foreign-owned subsidiaries estab-mostly foreign-owned subsidiaries estab- lished before 2008, whose multi-stage invest-lished before 2008, whose multi-stage invest- ments play a decisive role in the stability of ments play a decisive role in the stability of the space structure of the Hungarian auto-the space structure of the Hungarian auto- motive industry motive industry (Table 4).(Table 4). However, the success of these subsidiaries However, the success of these subsidiaries in the competition for new investments can in the competition for new investments can only be partly explained by technologically-only be partly explained by technologically- based improvements in cost-capability ratios based improvements in cost-capability ratios even in ideal cases. Government support may even in ideal cases. Government support may have also contributed to their success. The have also contributed to their success. The most spectacular example of new develop-most spectacular example of new develop- ments on old sites is the functional upgrad-ments on old sites is the functional upgrad- ing of Audi’s factory, where the car assembly ing of Audi’s factory, where the car assembly plant was transformed into a full car produc-plant was transformed into a full car produc- tion plant (including stamping plant, car body tion plant (including stamping plant, car body factory and paint shop) – with the relocation factory and paint shop) – with the relocation of activities from Germany – employing thou-of activities from Germany – employing thou- sands of people. The growth of a company sands of people. The growth of a company however was not always linked only to loca-however was not always linked only to loca- Fig. 5. Concentration indices of the analysed indicators. Source: Data of Central Statistical Office. Fig. 6. Hoover indices of the qualitative indicators and the total number of employees. Source: Data of Central Statistical Office. 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 2008 Non-manual employees Gross earnings of (full-time) employees Employees 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 5.0 5.5 6.0 6.5 7.0 7.5 8.0 9.0 8.5 9.5 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Non-manual employees/total employees Gross earnings of (full-time) employees/total employees Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155.148 Fig. 7. Changes in the centres of gravity regarding the studied indicators of the Hungarian motor vehicle industry. Source: Data of Central Statistical Office. tions within the priority counties. For exam-tions within the priority counties. For exam- ple, hundreds of employees were employed at ple, hundreds of employees were employed at the newly established and purchased sites (in the newly established and purchased sites (in the Great Plain) of SMR Automotive Mirror the Great Plain) of SMR Automotive Mirror Technology headquartered in Győr-Moson-Technology headquartered in Győr-Moson- Sopron county and nearly 1,500 employees Sopron county and nearly 1,500 employees were employed at the Budapest unit of the were employed at the Budapest unit of the Continental subsidiary located in Veszprém Continental subsidiary located in Veszprém county in 2018. In fact, data suggesting spatial county in 2018. In fact, data suggesting spatial concentrations mask geographical expansion concentrations mask geographical expansion in the case of Northern Transdanubian com-in the case of Northern Transdanubian com- panies operating in other regions too.panies operating in other regions too. IIn the strengthening of the eastern bridge-n the strengthening of the eastern bridge- heads of the automotive industry the process heads of the automotive industry the process of expansion concentrated in space, with of expansion concentrated in space, with both quantitative and qualitative elements both quantitative and qualitative elements is realised. The location selection of the com-is realised. The location selection of the com- panies in the east is justified by the fact that panies in the east is justified by the fact that new investments with employment growth new investments with employment growth are increasingly constrained in Northern are increasingly constrained in Northern Transdanubia due to the scarcity of human Transdanubia due to the scarcity of human resources and, on the other hand, the develop-resources and, on the other hand, the develop- ment of transport and other infrastructure the ment of transport and other infrastructure the number of potential locations for investments number of potential locations for investments increase (increase (Molnár, E. Molnár, E. 2013). In Borsod-Abaúj-2013). In Borsod-Abaúj- Zemplén and Bács-Kiskun counties, howev-Zemplén and Bács-Kiskun counties, howev- er, the concentrated presence of automotive er, the concentrated presence of automotive companies in the county seats (Miskolc and companies in the county seats (Miskolc and Kecskemét) is not unprecedented. Their ac-Kecskemét) is not unprecedented. Their ac- celerating embedding process, one of the most celerating embedding process, one of the most important fields of which (due to upgrading important fields of which (due to upgrading as well) is education supplying the human as well) is education supplying the human resources (resources (Józsa, V. Józsa, V. 2019), could hardly be 2019), could hardly be met without the infrastructure and industrial met without the infrastructure and industrial traditions of their cities. For this reason, it is traditions of their cities. For this reason, it is particularly true that for Bács-Kiskun county particularly true that for Bács-Kiskun county that its automotive industry is highly concen-that its automotive industry is highly concen- trated in its county seat. The fact that Daimler trated in its county seat. The fact that Daimler chose Kecskemét is not ground-breaking, con-chose Kecskemét is not ground-breaking, con- sidering that the city already had significant sidering that the city already had significant foreign capital (including the German auto-foreign capital (including the German auto- motive industry) at the turn of the millenni-motive industry) at the turn of the millenni- BicskeBicske BicskeBicske BicskeBicske TabajdTabajd TabajdTabajd TabajdTabajd VerebVereb VerebVereb VerebVereb VértessomlóVértessomló VértessomlóVértessomló VértessomlóVértessomló SzárligetSzárliget SzárligetSzárliget SzárligetSzárliget MórMór MórMór MórMór CsákvárCsákvár CsákvárCsákvár CsákvárCsákvár GántGánt GántGánt GántGánt OroszlányOroszlány OroszlányOroszlány OroszlányOroszlány ZámolyZámoly ZámolyZámoly ZámolyZámoly SzárSzár SzárSzár SzárSzár BokodBokod BokodBokod BokodBokod BodajkBodajk BodajkBodajk BodajkBodajk AlcsútdobozAlcsútdoboz AlcsútdobozAlcsútdoboz AlcsútdobozAlcsútdoboz ÓbarokÓbarok ÓbarokÓbarok ÓbarokÓbarok CsákberényCsákberény CsákberényCsákberény CsákberényCsákberény VértesacsaVértesacsa VértesacsaVértesacsa VértesacsaVértesacsa PusztavámPusztavám PusztavámPusztavám PusztavámPusztavám FelcsútFelcsút FelcsútFelcsút FelcsútFelcsút LovasberényLovasberény LovasberényLovasberény LovasberényLovasberény VértesboglárVértesboglár VértesboglárVértesboglár VértesboglárVértesboglár CsókakőCsókakő CsókakőCsókakő CsókakőCsókakő VárgesztesVárgesztes VárgesztesVárgesztes VárgesztesVárgesztes BodmérBodmér BodmérBodmér BodmérBodmér SörédSöréd SörédSöréd SörédSöréd ÚjbarokÚjbarok ÚjbarokÚjbarok ÚjbarokÚjbarok 20082009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Number of employeesNumber of employees Gross earnings of full-time employeesGross earnings of full-time employees Number of non-manual employeesNumber of non-manual employees 2008 2009 2010 2011 20122012 2013 2014 2015 20162016 2017 2018 2008 2009 2010 2011 2012 2013 2014 20152015 2016 2017 2018 0 3 km 0 3 km 0 3 km 149Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155. um (um (Marsa, A. Marsa, A. 2002). This was induced by a 2002). This was induced by a number of factors, such as its central location number of factors, such as its central location close to the agglomeration of Budapest, its close to the agglomeration of Budapest, its transport capabilities and, consequently, the transport capabilities and, consequently, the proximity of European and local suppliers, as proximity of European and local suppliers, as well as its educational culture and technical well as its educational culture and technical higher education (higher education (Vápár, J.Vápár, J. 2013 2013; Szemereyné ; Szemereyné Pataki, K. Pataki, K. 2014).2014). The benefits of geographical proximity The benefits of geographical proximity and the exploitation of industrial agglomera-and the exploitation of industrial agglomera- tion indicate concentrated growth in space. tion indicate concentrated growth in space. Suppliers located near car factories played a Suppliers located near car factories played a significant role in the development of several significant role in the development of several industrial parks in Northern Transdanubia in industrial parks in Northern Transdanubia in the 2000s (the 2000s (Molnár, E. Molnár, E. 2013). A similar phe-2013). A similar phe- nomenon can be observed with Mercedes in nomenon can be observed with Mercedes in Bács-Kiskun county, where the German car Bács-Kiskun county, where the German car maker was followed by several companies maker was followed by several companies (e.g. Brose, Magna/Antolin). The main driv-(e.g. Brose, Magna/Antolin). The main driv- ing force of the process is to reduce logistical ing force of the process is to reduce logistical costs and make deliveries flexible and safer. costs and make deliveries flexible and safer. Geographical proximity is especially impor-Geographical proximity is especially impor- tant for large, components difficult to trans-tant for large, components difficult to trans- port and also for just-in-time components. A port and also for just-in-time components. A good example is the factory “Kirchhoff” estab-good example is the factory “Kirchhoff” estab- lished close to the Suzuki’s automobile factory lished close to the Suzuki’s automobile factory in Esztergom, for which it manufactures car in Esztergom, for which it manufactures car body parts. Like this is experienced at com-body parts. Like this is experienced at com- panies (e.g. Lear in Győr, Magyar Toyo Seat panies (e.g. Lear in Győr, Magyar Toyo Seat in Nyergesújfalu and Adient in Kecskemét) in Nyergesújfalu and Adient in Kecskemét) producing seat modules near car factories.producing seat modules near car factories. Geographical proximity can also cover rela-Geographical proximity can also cover rela- tionships that go far beyond local dimensions. tionships that go far beyond local dimensions. The experiences of a survey carried out by The experiences of a survey carried out by PriceWaterhouse Coopers (2018) on the final PriceWaterhouse Coopers (2018) on the final users of suppliers’ products also proved this. users of suppliers’ products also proved this. According to their study the final users of the According to their study the final users of the surveyed Hungarian suppliers’ products are surveyed Hungarian suppliers’ products are Volkswagen in 61 per cent, Audi in 56 per cent, Volkswagen in 61 per cent, Audi in 56 per cent, Daimler in 51 per cent, BMW in 49 per cent, Daimler in 51 per cent, BMW in 49 per cent, Renault in 42 per cent, Ford in 40 per cent, PSA Renault in 42 per cent, Ford in 40 per cent, PSA in 37 per cent and Suzuki in 37 per cent. Merely in 37 per cent and Suzuki in 37 per cent. Merely Table 4. Major companies in the Hungarian automotive industry by the number of employees and county, 2008–2018 Name of companies by counties Year of foundation Number of employees (ca.) Change in employees in % of the county Year of largest employment 2008 2018* Győr-Moson-Sopron county Audi Hungaria Motor Ltd. / Audi Hungaria Co. SMR Automotive Mirror Technology Hungary Lp. AUTOLIV Ltd. BOS Automotive Products Magyarország Lp. Rába Futómű Ltd. Rába Járműalkatrész Ltd. – 1993 1993 1990 1992 1999 2001 14,701 5,939 788 942 681 1,415 987 25,279 12,726 2,549 2,198 1,128 666 598 100 64 17 12 4 –7 –4 – 2018 2018 2016 2018 2008 2008 Vas county Schaeffler Savaria Ltd. BPW Hungária Ltd. GM Powertrain Ltd. / Opel Szentgotthárd Ltd. – 1996 1991 1990 5, 64 1 220 1 259 659 8,974 3 485 1 518 1 007 100 63 7 10 – 2018 2018 2017 Veszprém county Continental Automotive Hungary Ltd. Johnson Controls / Yanfeng Hungary Ltd. Valeo Auto-Electric Magyarország Ltd. Johnson Controls / Adient Mezőlak Ltd. Poppe + Potthoff Hungária Ltd. – 1990 2014 1998 2002 1996 4,513 1,127 –** 737 265 237 11,386 3,770 2,345 1,936 874 551 100 38 34 17 9 5 – 2018 2018 2018 2018 2018 Borsod-Abaúj-Zemplén county Robert Bosch Energy and Body Systems Ltd. S.E.G.A. Hungary Ltd. Joyson Safety Systems Hungary Ltd. – 2003 2016 2013 3,457 960 0 0 9,237 2,306 1,601 1,799 100 23 28 31 – 2015 2017 2018 Bács-Kiskun county Mercedes Benz Manufacturing Hungary Ltd. Knorr-Bremse Fékrendszerek Ltd. Bosal / ACPS Automotive Ltd. Magna / Antolin Hungary Ltd. – 2008 1989 2003 2010 2,477 0 890 154 0 9,142 4,281 1,011 935 604 100 64 2 12 9 – 2018 2018 2018 2018 *Motor vehicle companies with at least 500 employees in 2018. **The factory of Johnson Controls at Pápa existed in 2008 as a unit of the company’s subsidiary, thus its data is not involved in the data of Veszprém county. Source: County TOP 100 publications, ceginfo.hu, Ministry of Justice database of electronic reports. Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155.150 19 per cent of companies sell only in Hungary, 19 per cent of companies sell only in Hungary, and only 7 per cent of those surveyed deliv-and only 7 per cent of those surveyed deliv- ered within 50 kilometres and just over 15 per ered within 50 kilometres and just over 15 per cent within 200 km (PriceWaterhouse Coopers, cent within 200 km (PriceWaterhouse Coopers, 2018). The positive impact of the automotive 2018). The positive impact of the automotive agglomeration in East-Central Europe on the agglomeration in East-Central Europe on the growth of the Hungarian automotive indus-growth of the Hungarian automotive indus- try is demonstrated, in addition to the above try is demonstrated, in addition to the above results, by that of Slovakia, directly adjacent results, by that of Slovakia, directly adjacent to the counties of Northern Transdanubia, be-to the counties of Northern Transdanubia, be- came the second largest market for engines and came the second largest market for engines and vehicle parts manufactured in Hungary, but vehicle parts manufactured in Hungary, but Czechia, Poland and Austria are also ranked Czechia, Poland and Austria are also ranked high high (Table 5).(Table 5). Counties with good quality indicators are Counties with good quality indicators are the plants of car manufacturers near the peak the plants of car manufacturers near the peak of the supplier pyramids and also those of of the supplier pyramids and also those of Tier 1 suppliers engaged in more complex Tier 1 suppliers engaged in more complex activities. In counties that performed well activities. In counties that performed well almost continuously (Bács-Kiskun, Heves almost continuously (Bács-Kiskun, Heves and Veszprém) the influence of one or two and Veszprém) the influence of one or two prominent Tier 1 suppliers with significant prominent Tier 1 suppliers with significant local value added can be recognised. These local value added can be recognised. These international companies were among the first international companies were among the first to arrive to Hungary and largely built on lo-to arrive to Hungary and largely built on lo- cal industrial traditions (Knorr-Bremse set-cal industrial traditions (Knorr-Bremse set- tled in Kecskemét utilised the heritage of the tled in Kecskemét utilised the heritage of the Tool Works, ZF from Eger based its activities Tool Works, ZF from Eger based its activities on the transmission plant of the Csepel au-on the transmission plant of the Csepel au- tomobile factory, but former Bakony Works tomobile factory, but former Bakony Works also had a history motor vehicle parts pro-also had a history motor vehicle parts pro- duction in Veszprém). Significant functions duction in Veszprém). Significant functions apart from production can also be observed apart from production can also be observed in these companies: e.g. R&D (at Continental in these companies: e.g. R&D (at Continental and Valeo in Veszprém, at Knorr-Bremse in and Valeo in Veszprém, at Knorr-Bremse in Kecskemét, at ZF in Eger) or IT services (at Kecskemét, at ZF in Eger) or IT services (at ZF in Eger), often involving departments in ZF in Eger), often involving departments in Budapest too. In addition to their increas-Budapest too. In addition to their increas- ing non-manual worker employment rate, ing non-manual worker employment rate, which is significantly above the average of which is significantly above the average of the automotive industry, their relevant local the automotive industry, their relevant local supplier background should also be high-supplier background should also be high- lighted (lighted (Marsa, A.Marsa, A. 2002; 2002; Sass, MSass, M. and. and Szanyi, Szanyi, M. M. 2004; 2004; Józsa, V. Józsa, V. 2019). Not primarily the 2019). Not primarily the car assembly plants, but these companies car assembly plants, but these companies producing greater local value added seem producing greater local value added seem to be the real success stories of the FDI-based to be the real success stories of the FDI-based Hungarian automotive industry.Hungarian automotive industry. The ratio of non-manual workers in the au-The ratio of non-manual workers in the au- tomotive industry does not fully reflect the tomotive industry does not fully reflect the importance of non-production functions, as importance of non-production functions, as these activities may not be recorded for the these activities may not be recorded for the motor vehicle industry. The best example for motor vehicle industry. The best example for this is the R&D in the automotive industry this is the R&D in the automotive industry because many of companies (e.g. develop-because many of companies (e.g. develop- ment bases of TNCs, Hungarian engineering ment bases of TNCs, Hungarian engineering offices, higher education – research institu-offices, higher education – research institu- tions) taking part in it belong to the “official” tions) taking part in it belong to the “official” motor vehicle industry only in a small ratio. motor vehicle industry only in a small ratio. The R&D experts of the sector exist in great-The R&D experts of the sector exist in great- er numbers in the regions of Budapest and er numbers in the regions of Budapest and Győr. (The latter is the largest location of the Győr. (The latter is the largest location of the Hungarian motor vehicle industry.) Several Hungarian motor vehicle industry.) Several prominent automotive companies registered prominent automotive companies registered in the field of engineering activities, techni-in the field of engineering activities, techni- cal consulting, technical testing and analysis, cal consulting, technical testing and analysis, Table 5. TOP 10 market of the export of Hungarian motor vehicle industry, 2008–2018 Country Export,* million EUR Change 2008–2018, million EUR Share of all export of motor vehicle industry in 2018, %2008 2018 Germany Slovakia Czechia Spain United Kingdom Poland Sweden Austria Mexico France 3,853 431 528 432 240 275 49 217 94 134 5,257 1,348 674 581 479 363 359 351 340 254 1,404 917 145 149 240 89 311 133 246 120 44.7 11.5 5.7 4.9 4.1 3.1 3.1 3.0 2.9 2.2 *Internal combustion engines and their parts, and motor vehicle parts (current prices). Source: International Trade Centre. 151Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155. and research and development (e.g. Robert and research and development (e.g. Robert Bosch and Thyssenkrupp Components Bosch and Thyssenkrupp Components Technology or Trigo Quality Support and Technology or Trigo Quality Support and EDAG) operate there. Robert Bosch, the EDAG) operate there. Robert Bosch, the largest unit of automotive R&D in Hungary, largest unit of automotive R&D in Hungary, originally established as a sales and logistic originally established as a sales and logistic centre, increased the number of its employ-centre, increased the number of its employ- ees from nearly 600 to 3,000 between 2008 ees from nearly 600 to 3,000 between 2008 and 2018, and is now typically engaged in and 2018, and is now typically engaged in product and software development. Based on product and software development. Based on this, not only the role of Budapest in research this, not only the role of Budapest in research and development will be enhanced, but the and development will be enhanced, but the functions of Győr-Moson-Sopron beyond functions of Győr-Moson-Sopron beyond production will also be more visible.production will also be more visible. Finally, supports granted on the basis of in-Finally, supports granted on the basis of in- dividual government decisions as part of the dividual government decisions as part of the investment promotion policy also influence investment promotion policy also influence the spatiality of the industry. On the basis of the spatiality of the industry. On the basis of data from ninety automotive investments reg-data from ninety automotive investments reg- istered not only in the motor vehicle industry istered not only in the motor vehicle industry in the narrow sense after 2008, it can be seen in the narrow sense after 2008, it can be seen that, during the years of crisis and recovery, that, during the years of crisis and recovery, reduced investment has been concentrated in reduced investment has been concentrated in the old key areas of this sector the old key areas of this sector (Table 6).(Table 6). On the other hand, in contrast to the stabil-On the other hand, in contrast to the stabil- ity of the regional distribution of the sector ity of the regional distribution of the sector between 2008 and 2018 – with the realisation between 2008 and 2018 – with the realisation of ongoing investments – an eastward shift is of ongoing investments – an eastward shift is likely in the future. The largest growth in the likely in the future. The largest growth in the Great Plain can be expected in Hajdú-Bihar Great Plain can be expected in Hajdú-Bihar county, which has been virtually absent from county, which has been virtually absent from the map of the automotive industry, where, the map of the automotive industry, where, in addition to the BMW car assembly plant in addition to the BMW car assembly plant which is under construction and the attempt which is under construction and the attempt to establish local bus production, the con-to establish local bus production, the con- centrated occurrence and capacity expansion centrated occurrence and capacity expansion of several suppliers (Continental, Schaeffler, of several suppliers (Continental, Schaeffler, ThyssenKrupp) also play an important role ThyssenKrupp) also play an important role in turning Debrecen into a centre of the in turning Debrecen into a centre of the Hungarian motor vehicle industry (Hungarian motor vehicle industry (Molnár, Molnár, E. E. and and Kozma, G.Kozma, G. 2018). 2018). Conclusions The present study analysed the change in the geography of the significantly growing Hungarian automotive industry in the dec- ade since the latest economic crisis in 2008. The overall increase in employment indicates that Hungary is still the target of capacity ex- pansion. The spatially concentrated growth Table 6. Financial supports and expected new workplaces in the Hungarian automotive industry by individual government decisions since 2008 Regions, counties Share of all supports, % Share of all expected new workplaces, % 2009–2013 2014–2018 2009–2013 2014–2018 Central Hungary Budapest Pest Northern Transdanubia Győr-Moson-Sopron Vas Komárom-Esztergom Fejér Veszprém Northern Hungary Borsod-Abaúj-Zemplén Heves Great Plain Bács-Kiskun Hajdú-Bihar Jász-Nagykun-Szolnok 13 7 6 87 45 16 6 20 0 0 0 0 1 1 0 0 2 1 1 35 12 0 12 3 8 28 8 18 35 12 10 8 27 13 14 68 31 12 7 17 0 0 0 0 5 5 0 0 3 0 3 37 11 0 12 3 10 27 11 14 33 8 7 9 Hungary total, % Hungary total in numbers 100 141,664* 100 621,766* 100 6,997 100 20,327 * In thousand EUR at price in 2018. Source: Ministry of Foreign Affairs. Molnár, E. et al. Hungarian Geographical Bulletin 69 (2020) (2) 137–155.152 expected from the upgrading in the interna- tional production networks and the increase in the quality of industrial concentrations have been only partially achieved. The re- sult of processes towards both concentration and expansion is characterised, on the one hand, by the massive growth of certain coun- ties in Northern Transdanubia and, on the other hand, by the expansion of the indus- try concentrated in one or two new counties. This results in stability in the distribution of the automotive industry between regions. In terms of quality indicators, there is typically a difference between significant and less im- portant locations and (above all) in terms of Budapest – outside Budapest. The present analysis indicates a moderate upgrading mostly without strategic functions, defined by foreign subsidiaries, and an industry that is gradually and selectively adapting the innovations of the “Fourth Industrial Revolution”. Like other studies (Gerőcs, T. and Pinkasz, A. 2019; Szalavetz, A. and So- mosi, S. 2019; McKinsey & Company 2020), the present analysis obtained no proof of a spectacular shift in the productive role of Hungary and in the grounds of its growth in automotive industrial networks. However, the example of the capital city points out that – in the case of appropriate local conditions – there is still some room for the implemen- tation of functional upgrading, despite the dependent situation. However, based on the last year data a However, based on the last year data a trend change is emerging. After the maxi-trend change is emerging. After the maxi- mum reached in the first quarter of 2019 – mum reached in the first quarter of 2019 – for the first time in three consecutive quar-for the first time in three consecutive quar- ters since the crisis – the number of people ters since the crisis – the number of people employed in the sector began to decrease, employed in the sector began to decrease, in almost all counties. In the background of in almost all counties. In the background of the events general global economic develop-the events general global economic develop- ments and specific problems related to the ments and specific problems related to the competitiveness of the German automotive competitiveness of the German automotive industry can be found (industry can be found (Haider, M.Haider, M. 2020). The 2020). The large investment deferred in the second half large investment deferred in the second half of the year (Mercedes 2of the year (Mercedes 2ndnd phase in Kecskemét) phase in Kecskemét) also suggests this. Although the relocation also suggests this. Although the relocation of certain labour-intensive activities was of certain labour-intensive activities was observed during the 2008 crisis, structural observed during the 2008 crisis, structural constraints are now more pronounced in ad-constraints are now more pronounced in ad- dition to economic fluctuations. Efficiency dition to economic fluctuations. Efficiency increase of production based on innovations increase of production based on innovations of Industry 4.0 and the disruptive effects of of Industry 4.0 and the disruptive effects of electromobility (reduced number of employ-electromobility (reduced number of employ- ees in the Hungarian economy specialized ees in the Hungarian economy specialized partly on the production of internal combus-partly on the production of internal combus- tion engines due to the spread of electric mo-tion engines due to the spread of electric mo- tors with less complexity) are mostly cited tors with less complexity) are mostly cited as explanations (as explanations (Fabók, B. Fabók, B. and and Stubnya, B. Stubnya, B. 2019). To these conjunctural and structural 2019). To these conjunctural and structural problems the negative effects of the corona-problems the negative effects of the corona- virus pandemic can also be added in 2020. virus pandemic can also be added in 2020. The decreasing demand for cars, the disinte-The decreasing demand for cars, the disinte- gration of supply chains and the protection gration of supply chains and the protection of employees can lead globally to the radical of employees can lead globally to the radical decrease of production (decrease of production (Rózsa, T. Rózsa, T. 2020). Its 2020). Its mid- and long-term consequences still can-mid- and long-term consequences still can- not be foreseen. But significant changes are not be foreseen. But significant changes are expected in the new decade which presum-expected in the new decade which presum- ably also brings a new era in the history and ably also brings a new era in the history and geography of the Hungarian motor vehicle geography of the Hungarian motor vehicle industry.industry. 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