The Use of Sholl and Kolmogorov Complexity Analysis in Researching on the Sustainable Development of Creative Economies in the Development Region of Bucharest-Ilfov, Romania

sustainability

Article The Use of Sholl and Kolmogorov Complexity Analysis in Researching on the Sustainable Development of Creative Economies in the Development Region of Bucharest-Ilfov, Romania

Karina Andreea Gruia 1,2 , Razvan-Cătălin Dobrea 3, Cezar-Petre Simion 3,*, Cristina Dima 3, Alexandra Grecu 1,2, Oana Simona Hudea 4, Marian Marin 1,2 , Ion Andronache 1 and Daniel Peptenatu 1,2 1 Research Center for Integrated Analysis and Territorial Management, University of Bucharest, 030018 Bucharest, Romania; [email protected] (K.A.G.); [email protected] (A.G.); [email protected] (M.M.); [email protected] (I.A.); [email protected] (D.P.) 2 Faculty of Geography, University of Bucharest, 010041 Bucharest, Romania 3 Faculty of Management, Bucharest University of Economic Studies, 010374 Bucharest, Romania; [email protected] (R.-C.D.); [email protected] (C.D.) 4 Faculty of Administration and Business, University of Bucharest, 030018 Bucharest, Romania; [email protected] * Correspondence: [email protected]

Received: 1 October 2019; Accepted: 4 November 2019; Published: 6 November 2019

Abstract: Nowadays, creative economies stand as a relevant indicator of the sustainable development of local and regional ones. The study aims to highlight the spatial behaviour of creative economies in the Bucharest-Ilfov Development Region, the most dynamic and complex regional economy in Romania. In order to assess the spatial dynamics of creative economies in the region, an economic database was created, at the level of the territorial administrative unit, for the two economic indicators considered important for the study, number of employees and turnover, under the auspices of the Classiﬁcation of National Economy Activities (NACE). The establishment of creative economies was made following the Government Decision no. 859 of 2014, with 66 codes for this sector. Annual cartographic models were developed for each indicator in QGIS (a free and open–source cross–platform desktop geographic information system application that supports viewing, editing, and analysis of geospatial data), for the period 2000–2016. For a relevant analysis of spatial behaviour, we used Sholl and Kolmogorov complexity, which highlighted speciﬁc patterns of spatial dynamics that help us to understand the role of creative economies in the sustainable development of regional economies. The results highlighted the role of accessibility corridors in the development of the regional economy.

Keywords: Sholl analysis; Kolmogorov complexity; spatial patterns; creative economies

1. Introduction The creative economy generates jobs and wealth, and is also a remarkable tool for urban and regional revitalization. Its signiﬁcance, role and importance are being studied more and more lately [1]. The basis of the creative economy is the capital of creative ideas and not necessarily physical capital [2], so it oﬀers the potential for growth and the development of new, creative, intangible products, service experiences and markets. Howkins mentions that creativity becomes an economic activity only when an idea becomes a business [3].

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Lately, more and more studies have analysed the growth of economic policies based on the development of cities’ creativity [4–7]. This interest accompanies a transition to a new economy [8] based on creativity, which includes creativity, the culture industry, the creative class and the urban environment as fundamental conditions [9]. Nowadays, these conditions are part of programs that underlie urban planning and are generally associated with urban entrepreneurship [10]. Creativity promotes urban economic growth, the competitiveness of cities and their vitality [11]. In this context, there is a need for regional and local policies that promote the creativity and culture of cities, with advantages for the urban economy if the regeneration of urban sites can be achieved. It should be noted, however, that these policies should include different axes, namely culture, art, industry and urban design, in order to create a comfortable city/urban environment that stimulates creativity [12]. Different spatial models of the creative economy have been analysed by geographical economists and regional researchers and their concentration has been noticed especially in metropolitan areas [13], giving the cities economic and social benefits [14–16]. The growth of the creative economy in today’s cities is largely a process of self-strengthening beyond the initial stage of cluster formation. This is because the high number of creative product companies offers different benefits that help them continuously grow. Benefits include both specialized funds and diversity of employability, as well as networks and knowledge exchanges, common providers and support services, institutional infrastructures and brand identity [17–20]. It has been found that the urban environment factors associated with the creative economy cover the demographic, social, economic and quality of life dimensions. The population represents the advantages of urbanization economies for professionals in the creative sector, in particular due to the high demand for creative activities and network effects, especially in large cities [21]. It is also considered that the density of the specialized employability in different activities of the creative sector is a positive factor explaining regional variations in creative economies. Another factor associated with the creative activities is related to the urban facilities or the quality of life associated with the place [13,17]. The causal relationship between facilities and the creative economy is complex. On the one hand, creative activities, favoured by many residents of the city, directly contribute to the facilities in the cities [15]. On the other hand, employees in the creative sector, in general, will have a greater demand for facilities, as they tend to remain in urban centres that have more facilities and a greater openness to diversity and new opportunities. Big cities are considered to have a higher concentration of creative economies [22]. In order to attract and maintain the creative class, in the cities, “the conversion of historic neighborhoods with mixed destination” took place, to promote “vibrant art scenes and outdoor activities”, “highlighting their cultural diversity” [23]. The complexity of the processes in emerging territorial systems structured around big cities, developed above, encouraged the scientific world to develop new methodologies that would help with understanding the patterns of their evolution. We opted for Sholl analysis and Kolmogorov complexity because they complement the familiar classical approaches. Sholl analysis provides information on the degree of branching, allowing the quantification of the dynamics on the development colour of some spatialized economic phenomena. The aim of our study was to identify these aspects in their dynamics. The benefit of Kolmogorov complexity lies in obtaining information about the complexity of the spatial distribution of creative economies, classified into five grey levels, at the level of the territorial administrative unit. The proposed algorithms can contribute to a greater knowledge of the spatial behaviour of the regional economy, with the results obtained being consistent supports to aid decision-making.

2. Materials and Methods

2.1. The Scope of the Research The study aimed to analyse the distribution of the creative economy in the Bucharest-Ilfov Development Region, on the basis of two economic indicators—turnover and number of employees. Sustainability 2019, 11, x FOR PEER REVIEW 3 of 19 up of Bucharest and Ilfov county, nine cities, 32 communes and 91 villages in total, and is the most developed development region in Romania (Figure 1). The region was chosen for this study because it is in first place in terms of the development of creativeSustainability economies,2019, 11, 6195making it a particularly attractive economic environment; in addition,3 of 19 the services sector is well developed and there is a high degree of accessibility. In 2016, the region accountedThe Bucharest-Ilfov for 55% of the Development turnover in Region the creative is one of sector the eight in developmentRomania, and regions 127,406 of Romania, employees made out of the 268,429up of Bucharest employees and trained Ilfov county, in this nine sector. cities, 32 communes and 91 villages in total, and is the most developed development region in Romania (Figure1).

Figure 1. The geographical location of the Bucharest-Ilfov Development Region within Romania. Figure 1. The geographical location of the Bucharest‒Ilfov Development Region within Romania. The region was chosen for this study because it is in ﬁrst place in terms of the development of creative economies, making it a particularly attractive economic environment; in addition, the services 2.2. Datasector Analysis is well developed and there is a high degree of accessibility. In 2016, the region accounted for 55% of the turnover in the creative sector in Romania, and 127,406 employees out of the 268,429 employees trainedThe time in thisspan sector. for the study of the dynamics and distribution of creative economies at the Bucharest‒Ilfov Development Region was 2000 to 2016. An economic database has been created at 2.2. Data Analysis the level of the administrative‒territorial unit, highlighting two economic indicators relevant to the analysis ofThe creative time span economies for the study(number of the of dynamicsemployees and and distribution turnover), ofaccording creative economiesto the Classification at the of NationalBucharest-Ilfov Economy Development Activities (N RegionACE). was The 2000 NACE to 2016. codes An belonging economic to database the creative has been economies created (Table at 1) werethe levelchosen of theaccordingly administrative-territorial to the Government unit, highlighting Decision no. two 859 economic of 2014, indicators regarding relevant the approval to the of analysis of creative economies (number of employees and turnover), according to the Classiﬁcation of the “Government Strategy for the development of the sector of small and medium-sized enterprises National Economy Activities (NACE). The NACE codes belonging to the creative economies (Table1) and the improvement of the business environment in Romania Horizon 2020.” The values for were chosen accordingly to the Government Decision no. 859 of 2014, regarding the approval of the turnover,“Government for a better Strategy analysis, for the are development expressed in of the sectornational of smallcurrency and medium-sized(Ron); according enterprises to the National and Bankthe of improvementRomania, 1 euro of the equals business 4.75 environment Ron. in Romania Horizon 2020”. The values for turnover, for a better analysis, are expressed in the national currency (Ron); according to the National Bank of Romania, 1 euroTable equals 1. NACE 4.75 codes Ron. for the creative activities established by H.G. 859/2014. Field of Activity NACE Creative Activities According to Codes NACE 5811 Book publishing 5812 Publishing of directories and mailing lists Information and 5813 Publishing of newspapers Communication 5814 Publishing of journals and periodicals 5819 Other publishing activities

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Table 1. NACE codes for the creative activities established by H.G. 859/2014.

NACE Codes Creative Activities Field of Activity According to NACE 5811 Book publishing 5812 Publishing of directories and mailing lists 5813 Publishing of newspapers 5814 Publishing of journals and periodicals 5819 Other publishing activities 5821 Publishing of computer games 5829 Other software publishing Motion picture, video and television programme 5911 production activities Motion picture, video and television programme Information and Communication 5912 post-production activities Motion picture, video and television programme 5913 distribution activities 5914 Motion picture projection activities 5920 Sound recording and music publishing activities 6202 Computer consultancy activities 6203 Computer facilities management activities Other information technology and computer service 6209 activities 6311 Data processing, hosting and related activities 6312 Web portals 6391 News agency activities 6399 Other information service activities n.e.c. 7111 Architectural activities Engineering activities and related technical 7112 consultancy 7120 Technical testing and analysis Research and experimental development on 7211 biotechnology Professional Scientiﬁc and Technical Other research and experimental development on 7219 Activities natural sciences and engineering Research and experimental development on social 7220 sciences and humanities 7311 Advertising agencies 7312 Media representation 7320 Market research and public opinion polling 7410 Specialised design activities 7420 Photographic activities 7430 Translation and interpretation activities Other professional, scientiﬁc and technical activities 7490 n.e.c. 8510 Pre-primary education 8520 Primary education 8531 General secondary education 8532 Technical and vocational secondary education 8541 Post-secondary non-tertiary education 8542 Tertiary education Education 8551 Sports and recreation education 8552 Cultural education 8553 Driving school activities 8559 Other education n.e.c. 8560 Educational support activities 8610 Hospital activities 8621 General medical practice activities 8622 Specialist medical practice activities 8623 Dental practice activities Human Health and Social Work 8690 Other human health activities Activities 8710 Residential nursing care activities Residential care activities for mental retardation, 8720 mental health and substance abuse 8730 Residential care activities for the elderly and disabled 8790 Other residential care activities Sustainability 2019, 11, 6195 5 of 19

Table 1. Cont.

NACE Codes Creative Activities Field of Activity According to NACE 9001 Performing arts 9002 Support activities to performing arts 9003 Artistic creation 9004 Operation of arts facilities 9101 Library and archives activities 9102 Museums activities Operation of historical sites and buildings and Arts Entertainment and Recreation 9103 similar visitor attractions Botanical and zoological gardens and nature reserves 9104 activities 9311 Operation of sports facilities 9312 Activities of sports clubs 9313 Fitness facilities 9319 Other sports activities 9321 Activities of amusement parks and theme parks 9329 Other amusement and recreation activities

2.3. GIS Analysis and Graphical Models Using QGIS 3.4 (Grüt, Switzerland), open-source software, maps were created for each year, for the period 2000–2016, for both the number of employees and the turnover, in a sequential colour scheme, at the level of territorial administrative unit. The graphical models show the evolution of the two indicators, with the highlights being the years 2000 (the beginning of the analysis time span), 2008 (when the maximum was reached in Romania for the two indicators), 2009 (the first year in which the economic crisis was registered) and 2016 (the last reference year). Combo-type charts analyse the evolution of the share of the creative sector in the Bucharest-Ilfov Region in terms of the total economy of the Bucharest-Ilfov Development Region (A) and the evolution of the share of the creative sector in the Bucharest-Ilfov Region in the total creative economy of Romania (B), as well as the matrix trend with reference to 2016, for the two indicators—presenting the first 20 creative codes with the most significant value of the share of the creative economy in the region, in terms of the total creative economy at the country level.

2.4. Pre-Processing Images In order to perform the Sholl and fractal analysis (Kolmogorov complexity), the colour gradient maps were turned into grey tones in five classes: for turnover—I (the white class has the highest values, over 60,000,000 Ron), II (a very light grey class with values between 10,000,000 and 60,000,000 Ron), III (the light grey class with values between 1,000,000 and 10,000,000 Ron), IV (the dark grey class, with values of 100,000–1,000,000 Ron) and V (the darkest colour, almost black, with values below 100,000 Ron) and for the number of employees—I (the white class has the highest value, with over 500 employees), II (the very light grey class with 250–500 employees), III (the light grey class with 100–250 employees), IV (the dark grey class with 50–100 employees) and V (the darkest colour, close to black, with under 50 employees). The built analysis was based on binary images, with the specific results due to segmenting the five classes of the image into grey tones and analysing the 8-bit greyscale images. The analysed images had a resolution of 2162 2552 pixels. × 2.5. Sholl Analysis Sholl is a quantitative analysis method that is usually the basis of neuronal studies to describe the morphological characteristics of an imaged neuron [24]. Mainly, Sholl analysis is used to measure the number of intersections per concentric shell at different distances from the centre. Sholl analysis is a binary analysis; the analysis is performed in ImageJ (Bethesda, MD, USA) through the Sholl analysis plugin [25–27]. In addition to the number of intersections per concentric shell, Sholl also calculated the average diameter of the dendrites or axons within each concentric shell. Mainly, Sholl analysis is used Sustainability 2019, 11, 6195 6 of 19 to measure the number of intersections per concentric shell at different distances from the centre. In our article, we propose using Sholl analysis to highlight the spatiotemporal dynamics of turnover and the number of employees in creative economies. The Sholl analysis plug-in is an improved algorithm for retrieving data from bitmap images with regression analysis, curve fitting and statistical inference, so an automatic estimation of the values of the arborization (branches) based on the Sholl analysis is possible. The plugin can perform Sholl analysis directly on 2D images of the objects to be analysed separately, isolated from the others. We should mention that this plugin can also perform 3D analysis using greyscale images; instead of circles, it uses spheres, and instead of pixels it uses voxels. The study proposes using Sholl analysis to highlight the spatiotemporal dynamics of turnover (Figure2) and the number of employees (Figure3) for the creative economies of the Bucharest-Ilfov region. The analysed binary images comprise the two classes with the highest values (white and very light grey for turnover: class I with values over 60,000,000 Ron and class II with values of 10,000,000–60,000,000 Ron, and again for employees: I with over 500 employees and class II with 250–500 employees. The sum of intersections (sampled), mean of intersections (sampled) and ramification index (fit) were analysed. a. Sum of intersections represents the sum of all intersections. b. Mean of intersections is given by Equation (1):

Sum o f intersections Mean o f intersections = , (1) Intersecting radii where “intersecting radii” is the number of sampling radii that intersect the (arboreal) object at least once. c. Ramification index allows the quantification of the degree of branching and is given by Equation (2) [28]: Max intersections Rami f ication Index = . (2) Number o f primary branches The ramification index is calculated only when the primary branches are valid and not equal to zero. The points of intersection were obtained when the “directions of development” intersect the concentric circles created with the help of Sholl analysis. The number of intersection points increases when new propagation directions appear or when the analysed phenomenon is spatially extended. The number decreases when it is compacted, disappearing from the propagation directions or when Sustainability 2019, 11, x FOR PEER REVIEW 7 of 19 the analysed phenomenon goes into decline, shrinking. 、

Figure 2. Spatiotemporal dynamics of turnover, 2000–2016.

Figure 2. Spatiotemporal dynamics of Figure 3. Spatiotemporal dynamics of the turnover, 2000–2016. number of employees, 2000–2016.

2.6. Fractal Analysis‒Kolmogorov Complexity Fractal analysis has been used since the 1980s as a tool to understand the complexity of the system, and has been applied in spatial analysis to study the phenomenon of urban agglomeration [31], forest dynamics [32] or economic phenomena [33]. It can be compared to classical approaches to binary fractal analysis such as Ruler Dimension [34,35] BoxCounting [31,36–38], Dilation Dimension [31,39], Mass Dimension [40], Local Connected Fractal Dimension [41], Perimeter-Area Dimension [42,43], Information Dimension [44], Minkowski Dimension [45], Multifractal Dimension [46,47] or recently Fractal Fragmentation Index [48–50]. Kolmogorov complexity is the indicator by which the degree of complexity of the turnover and the number of employees for the Bucharest‒Ilfov Development Region was established. Starting from Shannon entropy [51], Kolmogorov proposes a new theory of complexity. According to this theory, the Kolmogorov complexity of an object represents the length of the shortest computer program that produces that object as output (being a measure of the computing resources needed to reproduce the analysed object). The KC full image analyses the degree of complexity for all five classes of values. Kolmogorov complexity analysis was performed using open-source IQM 3.5 software (Graz, Austria) [52], and the complexity of the message is given by the size of the program needed to allow the receipt of such a message (Equation (3)). If x (t) is the trajectory of a dynamic system in a sampled space of n-dimensional phase at discrete time intervals Δt (for t > 0), the generalized Kolmogorov entropy, Kq, can be defined in this space and divided into the n-dimensional hypercubes of the side r (at time intervals Δt) through the following equation [53]:

𝐾𝑋=limlim lim ln ∑ 𝑝 , (3) → ∆→ → ∆ ,,…, ,,…,

where {X = xi} is the discrete random variable and xi = x (t = iΔt); 𝑝,,…, is the common probability

that the trajectory x (t = Δt) to be found in the box 𝑖, x (t = 2Δt) to be found in the box 𝑖 și x (t = NΔt)

to be found in the box 𝑖 . Complexity 0 means Kolmogorov complexity ≅ 0. As the image complexity increases, the Kolmogorov complexity grows.

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、

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Figure 3. Spatiotemporal dynamics of the number of employees, 2000–2016.

In this study we start from pixel 0 (the centre of Bucharest) to pixel 1790 (the maximum outside); the intersecting radii numbered 179, and the radius step was 10 pixels. The mean intersections were Figure 2. Spatiotemporalobtained dynamics by dividing of the numberFigure of 3. intersections Spatiotemporal by 179dynamics circles. of the turnover, 2000–2016. number of employees, 2000–2016. 2.6. Fractal Analysis-Kolmogorov Complexity Fractal analysis has been used since the 1980s as a tool to understand the complexity of the system, 2.6. Fractal Analysis‒Kolmogorov Complexity and has been applied in spatial analysis to study the phenomenon of urban agglomeration [29], forest Fractal analysis has beendynamics used since [30] orthe economic 1980s as phenomenaa tool to understand [31]. It can the be complexity compared toof classicalthe approaches to binary system, and has been appliedfractal in spatial analysis analysis such as to Ruler study Dimension the phenomenon [32,33] BoxCounting of urban agglomeration [29,34–36], Dilation Dimension [29,37], [31], forest dynamics [32] orMass economic Dimension phenomena [38], Local [33]. It Connected can be compared Fractal to Dimension classical approaches [39], Perimeter-Area to Dimension [40,41], binary fractal analysis suchInformation as Ruler Dimension Dimension [34,35] [42], BoxCounting Minkowski Dimension [31,36–38], [Dilation43], Multifractal Dimension Dimension [44,45] or recently [31,39], Mass Dimension [40],Fractal Local Fragmentation Connected Fractal Index [Dimension46–48]. Kolmogorov [41], Perimeter-Area complexity isDimension the indicator by which the degree of [42,43], Information Dimensioncomplexity [44], Minkowski of the turnover Dimension and the [45], number Multifractal of employees Dimension for the [46,47] Bucharest-Ilfov or Development Region recently Fractal Fragmentationwas established.Index [48–50]. Starting Kolmogorov from Shannon complexity entropy is the [49 ],indicator Kolmogorov by which proposes the a new theory of complexity. degree of complexity of Accordingthe turnover to thisand theory, the number the Kolmogorov of employees complexity for the of an Bucharest object represents‒Ilfov the length of the shortest Development Region was established.computer program Starting thatfrom produces Shannon that entropy object [51], as output Kolmogorov (being aproposes measure a of the computing resources new theory of complexity.needed According to reproduce to this thetheory, analysed the object).Kolmogorov The KC complexity full image analysesof an object the degree of complexity for all represents the length of theﬁve shorte classesst computer of values. program that produces that object as output (being a measure of the computing resourcesKolmogorov needed complexityto reproduce analysis the analysed was performed object). The using KC open-sourcefull image IQM 3.5 software (Graz, analyses the degree of complexityAustria) for [50 all], andfive theclasses complexity of values. of the message is given by the size of the program needed to allow Kolmogorov complexitythe analysis receipt of was such performe a messaged using (Equation open-source (3)). IQM 3.5 software (Graz, Austria) [52], and the complexityIf ofx ( thet) is message the trajectory is given of a by dynamic the size system of the inprogram a sampled needed space to of allown-dimensional phase at discrete the receipt of such a messagetime (Equation intervals (3)).∆t (for t > 0), the generalized Kolmogorov entropy, Kq, can be deﬁned in this space and If x (t) is the trajectory ofdivided a dynamic into system the n-dimensional in a sampled hypercubes space of n-dimensional of the side r (atphase time at intervalsdiscrete ∆t) through the following time intervals Δt (for t > 0), theequation generalized [51]: Kolmogorov entropy, Kq, can be defined in this space and 1 1 Xm(r) divided into the n-dimensional hypercubes of the side r= (at time intervals Δt) through the followingq KqX lim lim lim ln pi ,i ,...,i , (3) equation [53]: −r 0∆t 0N N∆t q 1 i1,i2,...,iN 1 2 N → → →∞ − where {X = xi} is the discrete random variable and xi = x (t = i∆t); pi ,i ,...,i is the common probability 1 2 N 𝐾𝑋=limlim lim ln ∑ 𝑝 , (3) that the trajectory→ ∆→ →x (t∆= ∆t) to be, found,…, in, the,…, box i1, x (t = 2∆t) to be found in the box i2 si x (t = N∆t) to be found in the box iN. Complexity 0 means Kolmogorov complexity 0. As the image complexity increases, the where {X = xi} is the discrete random variable and xi = x (t = iΔt); 𝑝,,…, is the common probability Kolmogorov complexity grows. that the trajectory x (t = Δt) to be found in the box 𝑖, x (t = 2Δt) to be found in the box 𝑖 și x (t = NΔt) This method has been implemented in various algorithms by using the routine length required for to be found in the box 𝑖 . storing or reproducing images. Some algorithms were the basis of the JPEG or ZIP format for image Complexity 0 means compressionKolmogorov [52complexity]. In this study,≅ 0. As the the PNG image format complexity was used, increases, with 10 iterationsthe that required system Kolmogorov complexity grows.bias corrections.

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3. Results

3.1. The Spatial Dynamics of Creative Economies

3.1.1. The Economic Dynamics of Turnover Sustainability 2019, 11, x FOR PEER REVIEW 8 of 19 The analysis of the turnover of the creative sector at the level of the Bucharest-Ilfov Development This method has been implemented in various algorithms by using the routine length required Region presents a positive trend, with an upward evolution during the 17 years analysed. In 2000, for storing or reproducing images. Some algorithms were the basis of the JPEG or ZIP format for the first year of the analysis, we observe a concentration of the highest values of the turnover in the image compression [54]. In this study, the PNG format was used, with 10 iterations that required municipalitysystem of bias Bucharest corrections. (with a maximum value of 2,112,885,299 Ron), followed by neighbouring localities such as Măgurele (11,113,383 Ron), Buftea (4,763,041 lei), Volunteers (3,438,509 Ron) and Pantelimon3. Results (2,899,094 Ron) (Figure4). Until 2008, a progressive trajectory and values of 13,649,703,013 Ron for the main growth pole, the municipality of Bucharest, followed by Voluntari, Măgurele, Buftea, 3.1. The Spatial Dynamics of Creative Economies Mogos, oaia and Corbeanca, are highlighted. Significant increases are observed at the end of the analysis (2015 and 2016), with maximum values 3.1.1. The Economic Dynamics of Turnover for the analysed period reached by Bucharest in 2016, with a turnover value of 27,598,264,903 Ron, being followedThe by analysis the surrounding of the turnover areas: Volunteersof the creati (1,149,679,236ve sector at Ron),the level Măgurele of the (300,4411,850 Bucharest‒Ilfov Ron), Development Region presents a positive trend, with an upward evolution during the 17 years Mogosoaia (166,098,459 Ron) and Otopeni (141,161,282 Ron) (Figure5). The codes with the most , analysed. In 2000, the first year of the analysis, we observe a concentration of the highest values of significant values are those for advertising, architecture and the IT field, respectively: 7311 (advertising the turnover in the municipality of Bucharest (with a maximum value of 2,112,885,299 Ron), followed agencies,by withneighbouring a value loca of 449,419,320lities such as Ron Măgurele in 2000, (11,113,383 reaching Ron), 2016 Buft withea (4,763,041 5,041,850,886 lei), Volunteers Ron), 7112 (engineering(3,438,509 activities Ron) and and Pantelimon related technical (2,899,094 consultancy, Ron) (Figure with 4). Until values 2008, of Rona progressive 244,020,034 trajectory in 2000 and and Ron 4,458,934,256values of 13,649,703,013 in 2016), and Ron 6202 for (computer the main growth consultancy pole, activitiesthe municipality totalling of RonBucharest, 138,029,029 followed in 2000by and RonVoluntari, 3,244,752,653 Măgurele, in 2016). Buftea, Mogoșoaia and Corbeanca, are highlighted.

2000 2001 2002

2003 2004 2005

2006 2007 2008

Figure 4. Cont.

Sustainability 2019, 11, 6195 9 of 19 Sustainability 2019, 11, x FOR PEER REVIEW 9 of 19

2009 2010 2011

2012 2013 2014

2015 2016 Sustainability 2019, 11, x FOR PEER REVIEW 10 of 19 Figure 4. Distribution of turnover in the creative sector in the Bucharest-Ilfov Development Region. Figure 4. Distribution of turnover in the creative sector in the Bucharest‒Ilfov Development Region.

Significant increases are observed at the end of the analysis (2015 and 2016), with maximum values for the analysed period reached by Bucharest in 2016, with a turnover value of 27,598,264,903 Ron, being followed by the surrounding areas: Volunteers (1,149,679,236 Ron), Măgurele (300,4411,850 Ron), Mogoșoaia (166,098,459 Ron) and Otopeni (141,161,282 Ron) (Figure 5). The codes with the most significant values are those for advertising, architecture and the IT field, respectively: 7311 (advertising agencies, with a value of 449,419,320 Ron in 2000, reaching 2016 with 5,041,850,886 Ron), 7112 (engineering activities and related technical consultancy, with values of Ron 244,020,034 in 2000 and Ron 4,458,934,256 in 2016), and 6202 (computer consultancy activities totalling Ron Figure138,029,029 5. The evolution in 2000 and of the Ron turnover 3,244,752,653 in the creative in 2016). sector in the Bucharest-Ilfov Development Region. Figure 5. The evolution of the turnover in Figure 6. Evolution of the share turnover In Figure 6 are presented the evolution of the share of the turnover in the creative sector versus In Figurethe total6 areturnover presented in thethe theregion creative evolution (A) andsector ofthe the sharein sharethe of Bucharest the of theturnover turnover‒Ilfov in the in creative the creative sectorin sector thein the creative versussame sector in terms of total the totalregion turnover versus in the the total region Developmentturnover (A) and in Romania the Region. share (B); of the the first turnover indicator in shows the creative a constant sector economyevolution, in the with(A same) and total creative economy region versussmall fluctuations, the total turnover falling between in Romania values (B); of the 4.49%, first indicatorwhich represents shows athe constant smallestin evolution, shareRomania of the with(B ). small fluctuations,turnover in the falling creative between sector values registered of 4.49%, in 2002, which and 8.99%, represents the highest, the smallest in 2011. share of the turnover in the creative sector registeredThe intrend 2002, matrix and 8.99%, for the the NACE highest, codes in 2011. in the creative sector of the turnover shows an evolution The trend matrixof for 20 the creative NACE activities codes in the (Table creative 2), sectorwhere of the the top turnover three positions shows an evolutionare occupied by basic activities of the of 20 creative activitiescreative (Table2 ),economies, where the top advertising three positions and arearchitecture, occupied by an basicd activities activities related of the to a field with a spectacular creative economies, advertisingtrajectory, andIT (codes architecture, 7311—advertising and activities agencies, related to awith field a withvalue a spectacularof 449,419,320 Ron in 2000 and reaching trajectory, IT (codes 7311—advertising agencies, with a value of 449,419,320 Ron in 2000 and reaching in in 2016 a value of 5,041,850,886 Ron; code 7112—engineering activities and related technical 2016 a value of 5,041,850,886 Ron; code 7112—engineering activities and related technical consultancies, consultancies, with a value of 244,020,034 Ron in 2000 and increasing to 4,458,934,256 Ron in 2016; IT with a value of 244,020,034 Ron in 2000 and increasing to 4,458,934,256 Ron in 2016; IT is represented by the code 6202 (computeris represented consultancy by the activities) code 6202 and (computer had values ofconsulta RON 138,029,029ncy activities) in 2000 and and had values of RON 138,029,029

RON 3,244,752,653 inin 2016). 2000 and RON 3,244,752,653 in 2016). Two time spans are highlighted: the pre-crisis period (2000–2008), when we observe increases in the various creative activitiesTable (for2. Trend example, matrix code of the 6202 first moved 20 NACE from codes the sixth for turnover position in to the the creati ﬁrst ve sector for 2000–2016.

NACE 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Codes 7311 1 1 1 1 1 28 27 24 24 26 24 23 22 22 23 2 1 7112 3 2 2 2 2 1 1 15 14 11 10 9 9 8 9 1 2 6202 6 6 3 3 3 2 2 1 1 1 1 1 50 47 44 3 3 8622 20 18 18 17 17 11 12 12 9 5 6 2 1 1 1 4 4 5829 16 15 15 15 15 14 13 13 11 7 4 3 5 3 2 5 5 7219 7 7 7 7 7 5 4 3 4 4 5 4 2 2 4 6 6 6311 4 4 4 4 4 3 3 2 6 9 7 7 3 4 6 8 7 6209 2 3 6 6 6 6 5 6 3 2 3 6 4 7 3 7 8 7120 11 13 12 13 14 16 15 14 15 16 12 12 8 6 7 9 9 7320 12 14 14 14 13 13 11 11 10 10 9 8 6 5 5 10 10 7312 14 11 10 11 11 7 6 4 2 3 2 5 7 9 10 11 11 8690 19 20 19 19 21 21 18 18 17 17 16 15 13 11 11 12 12 5911 5 5 5 5 5 4 7 7 7 8 8 10 10 10 8 13 13 7111 13 12 13 12 12 12 8 5 5 6 11 11 11 12 12 14 14 7490 15 16 16 16 16 15 16 16 16 18 17 16 14 15 14 15 15 5811 8 8 8 9 10 8 14 9 13 14 14 14 15 14 13 16 16 8623 23 25 25 27 27 22 20 20 22 22 23 21 20 20 18 18 17 6399 44 46 48 49 47 49 37 33 40 30 34 28 28 32 25 22 18 5914 17 19 50 24 23 24 25 31 33 23 21 22 21 21 20 20 19 5814 10 9 11 10 9 10 9 8 8 13 13 13 12 13 15 19 20

Notes: The numbers in the last column, which represents the year 2016 show the position of the NACE codes of that year. Two time spans are highlighted: the pre-crisis period (2000–2008), when we observe increases in the various creative activities (for example, code 6202 moved from the sixth position to the first position) but also decreases (for example, code 7311 dropped from first place to 24th in 2008), due to

Sustainability 2019, 11, 6195 10 of 19

position) but also decreases (for example, code 7311 dropped from first place to 24th in 2008), due to the growth dynamics of the activities of this sector both in Romania and at the European level. In the post-crisis period (2009–2016), creative activities present different development trajectories, so we have codes such as 7311 and 7112 in the first two positions, showing a clear evolution, but other codes that show stagnation (e.g., 7320 and 5811) or decreases (e.g., 5814 and 7111). The year 2016 epitomizes the dynamics of the 20 codes in the creative sector, representing the pole of productivity growth and Sustainability 2019, 11, x FOR PEER REVIEW 10 of 19 economic innovation.

Figure 6. Evolution of the share turnover in the creative sector in terms of total economy (A) and total Figure 5. The evolution of the turnover in Figure 6. Evolution of the share turnover creative economy in Romania (B). the creative sector in the Bucharest‒Ilfov in the creative sector in terms of total Development Region. Table 2. Trend matrix of theeconomy ﬁrst 20 NACE(A) and codes total for creative turnover economy in the creative sector for 2000–2016.

NACE in Romania (B). 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Codes 7311 1 1 1 1 1 28 27 24 24 26 24 23 22 22 23 2 1 The trend matrix for the NACE7112 codes3 in the 2 creative 2 2 sector 2 of 1 the 1 turnover 15 14 shows 11 an 10 evolution 9 9 8 9 1 2 of 20 creative activities (Table 2), where6202 the6 top 6three 3 positions 3 3 are 2 occupied 2 1 by 1basic 1 activities 1 1 of the 50 47 44 3 3 8622 20 18 18 17 17 11 12 12 9 5 6 2 1 1 1 4 4 creative economies, advertising and5829 architecture,16 15 an 15d activities 15 15 related 14 13 to 13a field 11 with 7 a 4spectacular 3 5 3 2 5 5 trajectory, IT (codes 7311—advertising7219 agencies,7777754344542246 with a value of 449,419,320 Ron in 2000 and reaching 6 6311 4444433269773468 7 in 2016 a value of 5,041,850,8866209 Ron; code2366665632364737 7112—engineering activities and related technical 8 7120 11 13 12 13 14 16 15 14 15 16 12 12 8 6 7 9 9 consultancies, with a value of 244,020,0347320 12Ron in 14 200 140 and 14 increasing 13 13 to 11 4,458,934,256 11 10 10 Ron 9 in 2016; 8 6IT 5 5 10 10 is represented by the code 6202 (computer7312 14 consulta 11ncy 10 activities) 11 11 and 7 had 6 values 4 2 of RON 3 2138,029,029 5 7 9 10 11 11 8690 19 20 19 19 21 21 18 18 17 17 16 15 13 11 11 12 12 in 2000 and RON 3,244,752,653 in 2016).5911 5 5 5 5 5 4 7 7 7 8 8 10 10 10 8 13 13 7111 13 12 13 12 12 12 8 5 5 6 11 11 11 12 12 14 14 7490 15 16 16 16 16 15 16 16 16 18 17 16 14 15 14 15 15 Table 2. Trend matrix of the first 581120 NACE8 codes 8 for 8 turnover 910 in the 8 creati 14ve sector 9 13 for 2000–2016. 14 14 14 15 14 13 16 16 8623 23 25 25 27 27 22 20 20 22 22 23 21 20 20 18 18 17 6399 44 46 48 49 47 49 37 33 40 30 34 28 28 32 25 22 18 NACE 5914 17 19 50 24 23 24 25 31 33 23 21 22 21 21 20 20 19 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Codes 5814 10 9 11 10 9 10 9 8 8 13 13 13 12 13 15 19 20 Notes: The numbers in the last column, which represents the year 2016 show the position of the NACE codes of 7311 1 1 1 1 1 28 27 24 24 26 24 23 22 22 23 2 1 that year. 7112 3 2 2 2 2 1 1 15 14 11 10 9 9 8 9 1 2 6202 6 6 3 33.1.2. 3 The Economic2 2 Dynamics1 1 of1 the Number1 1 of Employees50 47 44 3 3 8622 20 18 18 17 17 11 12 12 9 5 6 2 1 1 1 4 4 The analysis of the spatial distribution of the number of employees from the creative economies 5829 16 15 15 15 15 14 13 13 11 7 4 3 5 3 2 5 5 of the Bucharest-Ilfov region (Figure7) shows the dominant position of the Bucharest municipality, 7219 7 7 7 7 7 5 4 3 4 4 5 4 2 2 4 6 6 which totalled, in 2000, 39,618 employees in the creative sector, followed by cities in which this 6311 4 4 4 4 4 3 3 2 6 9 7 7 3 4 6 8 7 sector is growing: Măgurele (1,751 employees), Volunteers (becoming a private sector hub) with 286 6209 2 3 6 6employees, 6 6Buftea 5 (known6 for3 its film2 industry)3 6 with4 219 employees,7 3 7 and Pantelimon8 (210 employees). 7120 11 13 12 13The values14 16 show 15 a positive14 15 evolution 16 until12 2008,12 when 8 the 6 municipality 7 9 of9 Bucharest had a total of 7320 12 14 14 14125,814 13 employees,13 11 followed11 10by the10 cities 9 Volunteers 8 6 (2,133 5 employees), 5 10 M10ă gurele (1,951 employees), 7312 14 11 10 11Buftea 11 (1,2397 employees)6 4 and2 Otopeni3 2 (591 employees).5 7 9 After10 the11 economic 11 crisis, the number of 8690 19 20 19 19employees 21 21 in the18 creative 18 sector17 did17 not16 undergo 15 a13 significant 11 11 change 12 because12 this sector is dynamic 5911 5 5 5 5and some5 fields,4 7 such as7 IT, did7 not8 have8 to resort10 to10 redundancies10 8 in13 the post-economic13 crisis period; 7111 13 12 13 12 12 12 8 5 5 6 11 11 11 12 12 14 14 7490 15 16 16 16 16 15 16 16 16 18 17 16 14 15 14 15 15 5811 8 8 8 9 10 8 14 9 13 14 14 14 15 14 13 16 16 8623 23 25 25 27 27 22 20 20 22 22 23 21 20 20 18 18 17 6399 44 46 48 49 47 49 37 33 40 30 34 28 28 32 25 22 18 5914 17 19 50 24 23 24 25 31 33 23 21 22 21 21 20 20 19 5814 10 9 11 10 9 10 9 8 8 13 13 13 12 13 15 19 20

Sustainability 2019, 11, x FOR PEER REVIEW 11 of 19

the growth dynamics of the activities of this sector both in Romania and at the European level. In the post-crisis period (2009–2016), creative activities present different development trajectories, so we have codes such as 7311 and 7112 in the first two positions, showing a clear evolution, but other codes that show stagnation (e.g., 7320 and 5811) or decreases (e.g., 5814 and 7111). The year 2016 epitomizes the dynamics of the 20 codes in the creative sector, representing the pole of productivity growth and economic innovation.

3.1.2. The Economic Dynamics of the Number of Employees The analysis of the spatial distribution of the number of employees from the creative economies of the Bucharest‒Ilfov region (Figure 7) shows the dominant position of the Bucharest municipality, which totalled, in 2000, 39,618 employees in the creative sector, followed by cities in which this sector is growing: Măgurele (1,751 employees), Volunteers (becoming a private sector hub) with 286 employees, Buftea (known for its film industry) with 219 employees, and Pantelimon (210 employees). The values show a positive evolution until 2008, when the municipality of Bucharest had a total of 125,814 employees, followed by the cities Volunteers (2,133 employees), Măgurele (1,951 Sustainabilityemployees),2019, 11, 6195 Buftea (1,239 employees) and Otopeni (591 employees). After the economic crisis, the11 of 19 number of employees in the creative sector did not undergo a significant change because this sector is dynamic and some fields, such as IT, did not have to resort to redundancies in the post-economic however,crisis there period; were however, decreases there in were the numberdecreases of in employeesthe number of (especially employeesin (especially Bucharest, in Bucharest, as it is the as main area whereit is the most main of thearea employeeswhere most inof th thise employees sector work). in this sector work).

2000 2001 2002

2003 2004 2005

Sustainability 2019, 11, x FOR PEER REVIEW 12 of 19 2006 2007 2008

2009 2010 2011

2012 2013 2014

2015 2016

Figure 7. Distribution of the number of employees in the creative sector in the Bucharest-Ilfov Development Region.Figure 7. Distribution of the number of employees in the creative sector in the Bucharest‒Ilfov Development Region.

The period 2015–2016 is characterized by a positive trend, with the number of employees in creative sector activities increasing—Bucharest reached 112,326 employees in 2015 and 115,945 in 2016, followed by Volunteers (4,464 employees in 2015 and 4,156 in 2016), Măgurele (1,986 employees in 2015 and 2,058 in 2016) and Otopeni (561 employees in 2015 and 943 in 2016); Buftea suffered a decrease in the number of employees, from 546 in 2015 to 321 in 2016. The number of employees in the region showed an upward trend over the period analysed, starting from 42,366 employees in 2000 and reaching 127,406 in the final year of analysis (Figure 8). The NACE codes in which most of the employees were registered during this period were: 7112 (engineering activities and related technical consultancies), with 24,606 employees in 2008 and 20,546 employees in 2009; 7311 (advertising agencies), with 11,576 employees in 2008 and 11,518 in 2009; and 7219 (other research and experimental development in the natural sciences and engineering) with 9,494 employees in 2008 and 8,688 in 2009. The share of employees in the creative sector in the region rose throughout the analysed period, so the global economic crisis did not significantly affect this economic indicator (except in 2010, when a decrease occurred, down to a value of 8.83%) (Figure 9). The maximum value of 9.89% was registered in 2016. As for the share of employees in the creative sector of this region versus the total number of creative employees in Romania (B), things were different: the evolution presented fluctuations, with significant decreases in 2007–2008 due to the increase in value of other economic activities, which also produced decreases in the number of employees in the creative sector.

Sustainability 2019, 11, 6195 12 of 19

Figure 8. The evolution of employees in the creative sector in the Bucharest-Ilfov Development Region. Figure 8. The evolution of employees in Figure 9. Evolution of the share of the creative sector in the Bucharest‒Ilfov employees in the creative sector in terms of The share of employees in the creative sector in the region rose throughout the analysed period, Development Region. the total economy (A) and the total creative so the global economic crisis did not significantly affect this economic indicator (except in 2010, when a economy in Romania (B). decrease occurred, down to a value of 8.83%) (Figure9). The maximum value of 9.89% was registered in 2016. As for the share of employees in the creative sector of this region versus the total number of The analysis of the trend matrix for the number of employees of the creative sector at the region creative employees in Romania (B), things were different: the evolution presented fluctuations, with level offers an image on the growth potential and development of activities specific to this economic significant decreases in 2007–2008 due to the increase in value of other economic activities, which also sector. The first three codes present activities in the subdomain of architecture (7112—engineering Sustainability 2019, 11, x FOR PEERproduced REVIEW decreases in the number of employees in the creative sector. 13 of 19 activities and related technical consultancies), with 16,869 employees in 2016; advertising (7311— advertising agencies), with 12,600 employees in 2016; and health (8622—specialist medical practice activities), with 12,577 employees in 2016; followed by IT (present in this classification under four codes: 6202—computer consultancy activities, 6311—data processing, hosting and related activities, 6209—Other information technology and computer service activities, and 6399—other information service activities n.e.c.) and a total number, for the four codes, of 19,341 employees, representing 15% of the total employees in the creative sector in the region (Table 3).

Table 3. Trend matrix of the first 20 NACE codes for the number of employees in the creative sector for 2000–2016. Figure 9. Evolution of the share of employees in the creative sector in terms of the total economy (A) Figure 8. The evolution of employees in NACEFigure 9. Evolution of the share of and the total creative economy in2000 Romania 2001( B). 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 the creative sector in the Bucharest‒Ilfov Codesemployees in the creative sector in terms of Development Region. The analysis of the trend7112 matrixthe total for 2 economy the number 1 (A) and 1 ofemployees the1 total1 creative of1 the creative1 1 sector1 at the2 region1 level1 1 1 1 1 1 7311economy 3 in Romania 3 ( 3B ). 3 3 3 3 2 3 3 2 2 2 2 2 2 2 offers an image on the growth potential and development of activities specific to this economic sector. 8622 23 17 16 12 10 4 6 4 5 5 4 3 3 3 3 3 3 The first three codes present activities in the subdomain of architecture (7112—engineering activities The analysis of the trend matrix for the number of6202 employees 10 of the 9 creative 9 7sector 6 at the5 region5 6 7 7 5 5 5 5 5 4 4 and related technical consultancies), with 16,869 employees in 2016; advertising (7311—advertising level offers an image on the growth potential and development7219 1 of activities 2 specific 2 2 to 2this economic2 2 3 4 4 3 4 4 4 4 5 5 agencies), with 12,600 employees in 2016; and health (8622—specialist medical practice activities), with sector. The first three codes present activities in the subdomain5829 17 of architecture 19 15 17(7112—engineering 17 16 15 11 11 12 10 9 8 7 7 6 6 12,577 employees in 2016; followed by IT (present in this classification under four codes: 6202—computer activities and related technical consultancies), with 16,8697120 employees 5 5 in 2016; 4 advertising4 4 8 (7311—8 10 10 10 8 7 6 6 6 7 7 consultancy activities, 6311—data processing, hosting and related activities, 6209—Other information advertising agencies), with 12,600 employees in 2016;8690 and health 21 (8622—specialist 23 17 20 medical19 21 practice 19 18 18 15 13 10 9 9 9 8 8 technology and computer service activities, and 6399—other information service activities n.e.c.) and a activities), with 12,577 employees in 2016; followed by7320 IT (present 14 in 16 this 14classification 14 13 under15 four18 17 15 16 15 12 11 11 10 10 9 codes: 6202—computer consultancy activities, 6311—data6311 processing, 13 14 hosting 13 and16 related15 activities,13 11 9 2 8 6 6 7 8 8 9 10 6209—Other information technology and computer service7490 activities, 4 4 and 6399—other 20 9 9 information 10 14 14 13 14 14 14 13 13 11 12 11 service activities n.e.c.) and a total number, for the four8623 codes, of 16 19,341 15 employees, 12 13 representing14 14 15%16 13 13 13 12 11 12 10 12 11 12 of the total employees in the creative sector in the region7111 (Table 8 3). 6 6 6 5 6 4 5 6 6 7 8 10 12 13 13 13 6209 12 11 10 10 12 9 9 8 9 11 11 15 14 15 14 14 14 Table 3. Trend matrix of the first 20 NACE codes for th8621e number 27 of employees 21 19 in the21 creative20 sector20 20 20 19 20 17 16 16 16 16 17 15 for 2000–2016. 6399 47 48 54 49 51 52 52 43 52 39 37 33 28 31 22 19 16 5911 9 13 8 5 7 7 7 7 8 9 9 13 15 14 15 15 17 NACE 8559 20 18 18 19 21 19 21 21 21 22 21 18 17 17 17 16 18 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Codes 5811 6 7 5 8 8 11 12 12 16 17 16 17 18 18 18 18 19 7112 2 1 1 1 1 1 1 1 93291 2 31 1 30 1 281 261 271 251 251 25 24 25 23 22 23 22 24 21 20 7311 3 3 3 3 3 3 3 2 3 3 2 2 2 2 2 2 2 8622 23 17 16 12 10 4 6 4 5 Notes:5 The4 numbers3 3in the3 last column,3 3 which3 represents the year 2016 show the position of the 6202 10 9 9 7 6 5 5 6 7 7 5 5 5 5 5 NACE4 codes4 of that year. 7219 1 2 2 2 2 2 2 3 4 4 3 4 4 4 4 5 5 5829 17 19 15 17 17 16 15 11 11 12 10 9 8 7 7 6 6 7120 5 5 4 4 4 8 8 10 10 10 8 7 6 6 6 7 7 8690 21 23 17 20 19 21 19 18 18 15 13 10 9 9 9 8 8 7320 14 16 14 14 13 15 18 17 15 16 15 12 11 11 10 10 9 6311 13 14 13 16 15 13 11 9 2 8 6 6 7 8 8 9 10 7490 4 4 20 9 9 10 14 14 13 14 14 14 13 13 11 12 11 8623 16 15 12 13 14 14 16 13 13 13 12 11 12 10 12 11 12 7111 8 6 6 6 5 6 4 5 6 6 7 8 10 12 13 13 13 6209 12 11 10 10 12 9 9 8 9 11 11 15 14 15 14 14 14 8621 27 21 19 21 20 20 20 20 19 20 17 16 16 16 16 17 15 6399 47 48 54 49 51 52 52 43 52 39 37 33 28 31 22 19 16 5911 9 13 8 5 7 7 7 7 8 9 9 13 15 14 15 15 17 8559 20 18 18 19 21 19 21 21 21 22 21 18 17 17 17 16 18 5811 6 7 5 8 8 11 12 12 16 17 16 17 18 18 18 18 19 9329 31 30 28 26 27 25 25 25 24 25 23 22 23 22 24 21 20

Notes: The numbers in the last column, which represents the year 2016 show the position of the NACE codes of that year.

Sustainability 2019, 11, 6195 13 of 19 total number, for the four codes, of 19,341 employees, representing 15% of the total employees in the creative sector in the region (Table3).

Table 3. Trend matrix of the ﬁrst 20 NACE codes for the number of employees in the creative sector for 2000–2016.

NACE 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Codes 7112 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 7311 3 3 3 3 3 3 3 2 3 3 2 2 2 2 2 2 2 8622 23 17 16 12 10 4 6 4 5 5 4 3 3 3 3 3 3 6202 10 9 9 7 6 5 5 6 7 7 5 5 5 5 5 4 4 7219 1 2 2 2 2 2 2 3 4 4 3 4 4 4 4 5 5 5829 17 19 15 17 17 16 15 11 11 12 10 9 8 7 7 6 6 7120 5 5 4 4 4 8 8 10 10 10 8 7 6 6 6 7 7 8690 21 23 17 20 19 21 19 18 18 15 13 10 9 9 9 8 8 7320 14 16 14 14 13 15 18 17 15 16 15 12 11 11 10 10 9 6311 13 14 13 16 15 13 11 9 2 8 6 6 7 8 8 9 10 7490 4 4 20 9 9 10 14 14 13 14 14 14 13 13 11 12 11 8623 16 15 12Sustainability 13 14 2019 14, 11, 16x FOR 13PEER 13REVIEW 13 12 11 12 10 12 11 12 14 of 19 7111 8 6 6 6 5 6 4 5 6 6 7 8 10 12 13 13 13 6209 12 11 10 10 12 9 9 8 9 11 11 15 14 15 14 14 14 8621 27 21 19 21With 20 the 20 help 20 of the 20 matrix, 19 20 two 17periods 16 were 16 highlighted: 16 16 17 one15 between 2000 and 2008 (pre- 6399 47 48 54crisis), 49 where 51 52 you 52 can 43see increases 52 39 (for 37 example 33 28 8622, 31 8621 22 and 19 9329),16 decreases (for 7490) and 5911 9 13 8 5 7 7 7 7 8 9 9 13 15 14 15 15 17 8559 20 18 18stagnation 19 21 in 19the positions 21 21 that 21 the 22 creative 21 activiti 18 17es occupies, 17 17 it 16being18 a period in which the creative 5811 6 7 5sector 8 is 8characterized 11 12 by 12 an 16 economic 17 16dynamism 17 18, affirming 18 18 the 18 development19 based on the increase 9329 31 30 28 26 27 25 25 25 24 25 23 22 23 22 24 21 20 of productivity and the degree of economic innovation; and 2008 to 2016 (post-crisis), which presents Notes: The numbers in the last column, which represents the year 2016 show the position of the NACE codes of that year. a unique situation based on the competence of the specialists in the creative field, the contribution to increasing the absorption of European sources, the subdomains that are based on the With the help of the matrix,internationalization two periods were of their highlighted: work and one developing between 2000 products and 2008 and (pre-crisis), services for clients abroad (IT), as where you can see increaseswell (for as numerous example 8622, successful 8621 and start-ups. 9329), decreases (for 7490) and stagnation in the positions that the creative activities occupies, it being a period in which the creative sector is characterized by an economic3.2. The Sholl dynamism, and Kolmogorov affirming Complexity the development Analysis of based Creative on Economies the increase of productivity and the degree ofSholl economic analysis innovation; for turnover and 2008in the to 2016creative (post-crisis), sector (Figure which 10) presents reveals a a positive trend in the unique situation based onevolution the competence of creative of theeconomies. specialists One in sees the creativea growth field, stage the in contributionwhich the propagation to directions extend increasing the absorption ofspatially, European between sources, 2000 the subdomains and 2008, due that areto the based increa on thesingly internationalization significant development of the creative of their work and developingeconomies products and the and public services policies for clients that come abroad to their (IT), aid. as well The aseconomic numerous crisis that took hold in 2009 successful start-ups. is associated with the compacting of the phenomenon, causing a circular development towards the centre. After 2012, a downward trend represented by the circular economic development around the 3.2. The Sholl and Kolmogorovcity Complexityis observed. Analysis of Creative Economies Sholl analysis for turnoverFigure in the creative11 captures sector the (Figure period 10)s reveals of maximum a positive extension trend in the in evolutionthe development of the creative of creative economies. Oneeconomies. sees a growth It highlights stage in the which period the propagationof 2000–2008 directions as having extend a positive spatially, evolution and a maximum in between 2000 and 2008, due2008, to thefollowed increasingly by a decrease significant due development to the economic of the crisis, creative felt economies especially and keenly in 2009. The second the public policies that comegrowth to their period aid. is The located economic in 2010, crisis with that a tookmaximum hold in of 2009 10.07, is associatedan increase with that can be explained by the the compacting of the phenomenon,developing causingcreative aeconomies circular development around accessibility towards lanes, the centre. as well After as by 2012, the development possibilities a downward trend representedoffered by by the the circular northern economic area of developmentBucharest. around the city is observed.

Figure 10. Sholl analysis of theFigure turnover 10. of Sholl the creative analysis sector of the in turnover the Bucharest-Ilfov of DevelopmentFigure 11. Region. Branching index for turnover in the creative sector in the Bucharest‒Ilfov the creative sector in the Bucharest‒Ilfov Development Region. Development Region.

Figure 12 offers a complex picture of the distribution of job offers and the number of employees involved in creative activities in the region. The total number of intersections and their average follow the same positive trend determined by the appearance of the propagation directions—from 2005, a development towards the north; and from 2008, an increase towards the southeast, towards Popești- Leordeni. The number of employees showed a negative evolution in 2012, in which the development phenomenon was declining and creative activities were restricted in the area near the city (Figure 13).

Sustainability 2019, 11, x FOR PEER REVIEW 14 of 19

With the help of the matrix, two periods were highlighted: one between 2000 and 2008 (pre- crisis), where you can see increases (for example 8622, 8621 and 9329), decreases (for 7490) and stagnation in the positions that the creative activities occupies, it being a period in which the creative sector is characterized by an economic dynamism, affirming the development based on the increase of productivity and the degree of economic innovation; and 2008 to 2016 (post-crisis), which presents a unique situation based on the competence of the specialists in the creative field, the contribution to increasing the absorption of European sources, the subdomains that are based on the internationalization of their work and developing products and services for clients abroad (IT), as well as numerous successful start-ups.

3.2. The Sholl and Kolmogorov Complexity Analysis of Creative Economies Sholl analysis for turnover in the creative sector (Figure 10) reveals a positive trend in the evolution of creative economies. One sees a growth stage in which the propagation directions extend spatially, between 2000 and 2008, due to the increasingly significant development of the creative economies and the public policies that come to their aid. The economic crisis that took hold in 2009 is associated with the compacting of the phenomenon, causing a circular development towards the centre. After 2012, a downwardSustainability trend2019 represented, 11, 6195 by the circular economic development around the 14 of 19 city is observed. Figure 11 captures the periods of maximum extension in the development of the creative Figure 11 captures the periods of maximum extension in the development of the creative economies. economies. It highlights the period of 2000–2008 as having a positive evolution and a maximum in It highlights the period of 2000–2008 as having a positive evolution and a maximum in 2008, followed 2008, followed by a decrease due to the economic crisis, felt especially keenly in 2009. The second by a decrease due to the economic crisis, felt especially keenly in 2009. The second growth period growth period is located in 2010, with a maximum of 10.07, an increase that can be explained by the is located in 2010, with a maximum of 10.07, an increase that can be explained by the developing developing creative economies around accessibility lanes, as well as by the development possibilities creative economies around accessibility lanes, as well as by the development possibilities oﬀered by offered by the northern area of Bucharest. the northern area of Bucharest.

Figure 11. Branching index for turnover in the creative sector in the Bucharest-Ilfov Figure 10. Sholl analysis of the turnover of Figure 11. Branching index for turnover in Development Region. the creative sector in the Bucharest‒Ilfov the creative sector in the Bucharest‒Ilfov Development Region. Figure 12o ﬀers a complexDevelopment picture of the Region. distribution of job oﬀers and the number of employees involved in creative activities in the region. The total number of intersections and their average Figure 12 offers a complex picture of the distribution of job offers and the number of employees follow the same positive trend determined by the appearance of the propagation directions—from involved in creative activities in the region. The total number of intersections and their average follow 2005, a development towards the north; and from 2008, an increase towards the southeast, towards the same positive trend determined by the appearance of the propagation directions—from 2005, a Popesti-Leordeni. Sustainability 2019, 11, x FOR PEER REVIEW 15 of 19 development towards the north;, and from 2008, an increase towards the southeast, towards Popești- Leordeni. The number of employees showed a negative evolution in 2012, in which the development phenomenon was declining and creative activities were restricted in the area near the city (Figure 13).

Figure 12. Sholl analysis forFigure the number 12. Sholl of employeesanalysis for inthe the number creative of sector in theFigure Bucharest-Ilfov 13. The branch indicator for the Development Region. employees in the creative sector in the number of employees in the creative sector Bucharest‒Ilfov Development Region. in the Bucharest‒Ilfov Development The number of employees showed a negative evolution in 2012, in which the development Region. Sustainability 2019, 11, x FOR PEERphenomenon REVIEW was declining and creative activities were restricted in 15 the ofarea 19 near the city (Figure 13). In the chart showing the evolution of Kolmogorov complexity for turnover (Figure 14), the development of the creative economies is emphasized, showing the complexity of the process. Thus, for 2000 to 2008, there is a positive trend in terms of the growth of creative economies, which leads to an area with uneven distributions around the main communication axes and to the high value of Kolmogorov complexity. In 2010 there was a maximum of complexity due to the increasingly evident growth in the northern part of Bucharest, which offers more and more development opportunities, especially along the DN1 and the Bucharest‒Ploiești Highway, and due to the existence and growth of a large number of projects in that area. The period 2012–2016 presents a compaction of the turnover and a downward evolution of the Kolmogorov comple xity, with a minimum in 2014, as a result of Figure 12. Sholl analysis forFigure the number 13. The of branch indicatorthe uniformFigure for the 13.polarization number The branch of employees around indicator Buch in the forarest creative the of sectorthe creative in the Bucharest-Ilfov activities. employees in the creativeDevelopment sector in the Region. Asnumber to the of evolution employees of in Kolmogorov the creative sector complexity in the number of employees in the creative sector Bucharest‒Ilfov Development Region. (Figurein 15),the there Bucharest is an upward‒Ilfov Developmenttrend, with an increase in complexity each year analysed based on an In the chart showing the evolution of Kolmogorov complexity for turnover (Figure 14), the unevenRegion development. in the areas where employees are concentrated in the creative sector. This development of the creative economies is emphasized, showing the complexity of the process. Thus, complexity is accentuated due to the spreading along accessibility corridors, especially in the north In the chart showing the evolution of Kolmogor(Voluntari),ov complexity southeast for withturnover the Pope(Figurești‒ 14),Leordeni the area and towards the east, which has the A2 development of the creative economies is emphasizmotorway.ed, showing the complexity of the process. Thus, for 2000 to 2008, there is a positive trend in terms of the growth of creative economies, which leads to an area with uneven distributions around the main communication axes and to the high value of Kolmogorov complexity. In 2010 there was a maximum of complexity due to the increasingly evident growth in the northern part of Bucharest, which offers more and more development opportunities, especially along the DN1 and the Bucharest‒Ploiești Highway, and due to the existence and growth of a large number of projects in that area. The period 2012–2016 presents a compaction of the turnover and a downward evolution of the Kolmogorov complexity, with a minimum in 2014, as a result of the uniform polarization around Bucharest of the creative activities. As to the evolution of Kolmogorov complexity in the number of employees in the creative sector (Figure 15), there is an upward trend, with an increase in complexity each year analysed based on an uneven development in the areas where employees areFigure concentrated 14. Kolmogorov in the complexitycreative sector. of the This Figure 15. Kolmogorov complexity of the complexity is accentuated due to the spreading along accessibilityturnover of corridors, the creative especially sector inin thethe north number of employees in the creative sector (Voluntari), southeast with the Popești‒Leordeni area Bucharestand towards‒Ilfov Developmentthe east, which Region. has the A2 in the Bucharest‒Ilfov Development motorway. Region.

4. Discussion and Conclusions In this paper, we introduced Sholl analysis and Kolmogorov complexity to calculate the dynamics of the spatial distribution of turnover and the number of employees in creative economies in the Bucharest‒Ilfov Development Region. Sholl analysis is a key measure of dendritic complexity and has applications from assessing pathology-induced structure changes to estimating the expected number of synaptic anatomical

Figure 14. Kolmogorov complexity of the Figure 15. Kolmogorov complexity of the turnover of the creative sector in the number of employees in the creative sector Bucharest‒Ilfov Development Region. in the Bucharest‒Ilfov Development Region.

Sustainability 2019, 11, x FOR PEER REVIEW 15 of 19

Figure 12. Sholl analysis for the number of Figure 13. The branch indicator for the employees in the creative sector in the number of employees in the creative sector Bucharest‒Ilfov Development Region. in the Bucharest‒Ilfov Development Region.

In the chart showing the evolution of Kolmogorov complexity for turnover (Figure 14), the development of the creative economies is emphasized, showing the complexity of the process. Thus, Sustainability 2019, 11, x FOR PEER REVIEW for 2000 to 2008, there is a positive trend in 15 terms of 19 of the growth of creative economies, which leads to an area with uneven distributions around the main communication axes and to the high value of Kolmogorov complexity. In 2010 there was a maximum of complexity due to the increasingly evident growth in the northern part of Bucharest, which offers more and more development opportunities, Sustainability 2019, 11, 6195 15 of 19 especially along the DN1 and the Bucharest‒Ploiești Highway, and due to the existence and growth of a large number of projects in that area. The period 2012–2016 presents a compaction of the turnover for 2000 to 2008, there isand a positive a downward trend inevolution terms of of the the growth Kolmogorov of creative comple economies,xity, with which a minimum leads in 2014, as a result of to an area with uneven distributionsthe uniform polarization around the mainaround communication Bucharest of the axes creative and to activities. the high value of Kolmogorov complexity. In 2010As to there the evolution was a maximum of Kolmogorov of complexity complexity due to in the the increasingly number of employees evident in the creative sector growth in the northern part(Figure of Bucharest,15), there is which an upward oﬀers trend, more andwith more an increase development in complexity opportunities, each year analysed based on an Figure 12. Sholl analysisespecially for the number along of the DN1uneven and theFigure development Bucharest-Ploie 13. The branch in s, theti Highway,indicator areas where andfor the dueemployees to the existence are concentrated and growth in of the creative sector. This employees in the creativea large sector number in the of projectscomplexity in thatnumber area. is ofaccentuated Theemployees period in due 2012–2016 the tocreative the spreading presents sector a along compaction accessibility of the turnovercorridors, especially in the north Bucharest‒Ilfov Developmentand a downward Region. evolution(Voluntari), ofin the Kolmogorovthe southeast Bucharest complexity,with‒Ilfov the Development Pope withști a‒ minimumLeordeni inarea 2014, and as towards a result ofthe the east, which has the A2 uniform polarization aroundmotorway. BucharestRegion . of the creative activities.

In the chart showing the evolution of Kolmogorov complexity for turnover (Figure 14), the development of the creative economies is emphasized, showing the complexity of the process. Thus, for 2000 to 2008, there is a positive trend in terms of the growth of creative economies, which leads to an area with uneven distributions around the main communication axes and to the high value of Kolmogorov complexity. In 2010 there was a maximum of complexity due to the increasingly evident growth in the northern part of Bucharest, which offers more and more development opportunities, especially along the DN1 and the Bucharest‒Ploiești Highway, and due to the existence and growth of a large number of projects in that area. The period 2012–2016 presents a compaction of the turnover and a downward evolution of Figurethe Kolmogorov 14. complexity, with a minimum in 2014, as a result of Kolmogorov complexityFigure 14. ofKolmogorov the turnover complexity of the creative of the sector in theFigure Bucharest-Ilfov 15. Kolmogorov complexity of the the uniform polarization aroundDevelopment Bucharest Region.of the creative activities. As to the evolution of Kolmogorov complexity in theturnover number of of theemployees creative insector the creative in the sector number of employees in the creative sector Bucharest‒Ilfov Development Region. in the Bucharest‒Ilfov Development (Figure 15), there is an upwardAs trend, to the with evolution an increase of Kolmogorov in complexity complexity each year in analysed the number based of employeeson an in the creative sector Region. uneven development in the(Figure areas 15 where), there employees is an upward are trend,concentrated with an in increase the creative in complexity sector. This each year analysed based on complexity is accentuatedan due uneven to the developmentspreading along in theaccessibility areas where corridors, employees especially are concentrated in the north in the creative sector. This (Voluntari), southeast withcomplexity the Pope isști accentuated‒Leordeni4. areaDiscussion due toand the towards spreadingand Conclusions the along east, accessibilitywhich has the corridors, A2 especially in the north motorway. (Voluntari), southeast with the Popes, ti-Leordeni area and towards the east, which has the A2 motorway. In this paper, we introduced Sholl analysis and Kolmogorov complexity to calculate the dynamics of the spatial distribution of turnover and the number of employees in creative economies in the Bucharest‒Ilfov Development Region. Sholl analysis is a key measure of dendritic complexity and has applications from assessing pathology-induced structure changes to estimating the expected number of synaptic anatomical

Figure 14. Kolmogorov complexityFigure 15. of theKolmogorov complexityFigure 15. Kolmogorov of the number complexity of employees of the in the creative sector in the turnover of the creative Bucharest-Ilfovsector in the Developmentnumber Region. of employees in the creative sector Bucharest‒Ilfov Development Region. in the Bucharest‒Ilfov Development 4. Discussion and Conclusions Region. In this paper, we introduced Sholl analysis and Kolmogorov complexity to calculate the dynamics of the spatial distribution of turnover and the number of employees in creative economies in the 4. Discussion and ConclusionsBucharest-Ilfov Development Region. In this paper, we introducedSholl analysisSholl analysis is a key and measure Kolmogorov of dendritic complexity complexity to calculate and has the applications from assessing dynamics of the spatial distributionpathology-induced of turnover structure and the changesnumber of to employees estimating in the creative expected economies number of synaptic anatomical in the Bucharest‒Ilfov Developmentcontacts. Based Region. on these considerations, we applied the Sholl analysis to the GIS-generated image set Sholl analysis is a keyand measure found that of dendritic Sholl intersection complexity proﬁles and canhas beapplications reproduced from using assessing similar logic. pathology-induced structure changesIn previous to estimating studies of brainthe expected cell morphology number [of53 ,synaptic54], Sholl anatomical was used as a tool of discrimination of morphological features; in this paper we have followed the dynamics of the same phenomenon in 17 successive years. As far as we know, this is the ﬁrst time that an analysis of the Kolmogorov

complexity has been made for the dynamics of spatialization of some economic phenomena; fractal Sustainability 2019, 11, 6195 16 of 19 implementation was recently done by Helmut Ahammer from the Medical University of Graz, Austria through the IQM operator Logical Depth. There are also a number of limitations to the analysis. The Sholl analysis, to be comparable, must be performed at the same resolution, and binarization must be done based on the same algorithm, and the centre from which the concentric circles will be drawn will be central to the mass of the object to be analysed. KC analysis also implies a limitation, as its result is dependent on the image size. Therefore, in order to be valid and comparable, the images analysed must have the same resolution. The results obtained highlight the increase in knowledge brought about by Sholl and fractal analysis in terms of understanding the complex of factors that determine the sustainable development of the regional economy, as well as the role of the creative economies in the balanced development of the local economies. Instead of classical GIS, spatial analysis or fractal analyses, we opted for Sholl analysis due to the ability of this indicator to quantify the dynamics of the spatial distribution of turnover and the number of employees, depending on the increases and decreases of these parameters at the level of the territorial administrative unit. To identify the complexity of this dynamic at the level of the territorial administrative unit, we applied Kolmogorov complexity, which for this type of analysis is more versatile than Higuchi 1D, Higuchi 2D, or Pyramid Dimension. Detailed research into the creative economies has shown the important role of these economic activities in the evolution of each local economy, with the creative economies supporting the economic crisis very well and fostering an adaptive capacity to cope with structural crises. The applied methodology can help to model the adaptive capacity of the territorial systems, the limitations being highlighted in numerous specialized works [55–57]. Sholl analysis allowed the morphological characteristics of the spatial model of the distribution of creative economies to be identified, identifying the development directions and, indirectly, the determined factors. With the aid of the results obtained, the study contributes to the development of the established methodologies for qualitative and quantitative analysis of the spatial distribution of geographical processes and phenomena [38,40,49,51]. This algorithm is relevant for analysing the ways in which certain types of infrastructures determine groups of creative economies. Using Kolmogorov complexity for the analysis of the distribution of creative economies at a regional level has demonstrated the usefulness of this method for exceeding the current methodological limits in knowing the dynamics of the territorial reality, limits recorded in numerous specialized studies [58–60]. The obtained results showed the relevance of Sholl and fractal analysis in the advanced modelling of the structural dynamics of the local economies, with the fractal algorithms, together with the statistical and GIS models, offering a significant increase in knowledge.

Author Contributions: Conceptualization, K.A.G., D.P. and C.-P.S.; methodology, K.A.G., A.G., R.-C.D. and C.D.; software, I.A. and O.S.H.; validation, K.A.G., A.G., and D.P.; formal analysis, I.C. and D.P.; investigation, M.M.; resources, M.M. and C.D.; data curation, C.-P.S.; writing—original draft preparation, K.A.G., D.P. and R.-C.D.; writing—review and editing, K.A.G., C.-P.S., C.D. and D.P.; visualization, K.A.G., M.M., O.S.H. and A.G.; supervision, D.P., C.-P.S. and R.-C.D.; project administration, A.G.; These authors contributed equally to this work. Funding: This research was funded by the Romanian Ministry of Innovation and Research, grant PFE24/16.10.2018, “Increasing research capacity in the economic field through the development of transdisciplinary research infrastructures (CERTRAN)”. Conflicts of Interest: The authors declare no conflict of interest.

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