R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 111 https://journals.urfu.ru/index.php/r-economy Online ISSN 2412-0731 Original Paper © Solosina, M.I., Shchepina, I.N., 2020 doi 10.15826/recon.2020.6.2.010 Analytical tools for economic research of small municipalities and gaming techniques for community involvement (the case of Voronezh region in Russia) M.I. Solosina1 , I.N. Shchepina1, 2 1 Voronezh State University, Voronezh, Russia; e-mail: maria.solosina@gmail.com 2 CEMIRAS, Moscow, Russia ABSTRACT Relevance. The article deals with the issues of strategic territorial development in Russian regions and municipalities and the analytical tools for studying them. While there is a diversity of tools for studying large municipalities, the choice of tools for smaller urban and rural settlements is quite limited. This is the research gap this study seeks to address. Research objective. This study focuses on the case of municipal districts and settlements in Voronezh region. The aim is to show how the proposed methodology can be applied for such cases. Data and methods. The study relies on the methods of systemic analysis and synthesis, comparison and generalization, multidimensional statistics as well as on the use of gaming techniques. The data for the analysis were obtained from federal, re- gional and municipal statistics; municipal information systems of settlements of Voronezh region; municipal information system MISS ‘Volost’; and from the executive authorities of Voronezh region. Results. The analysis of the set of in- dicators, including the municipal product to GRP, for the period between 2006 and 2015 has shown that the town of Liski is one of the leading municipalities in Voronezh district (the municipal product of Liskinsky accounts for over 5% of the region’s GRP). We also applied our gaming technique to establish communi- cation between the authorities and local communities in developing the project for creation of a historical and archeological park in the settlement of Kostenki in Voronezh region. Conclusions. The proposed methodology can be quite pro- ductive in building socio-economic profiles of small municipalities, comparing them with others and revealing the interrelations between them. The gaming techniques are effective for enhancing the involvement of local communities in municipal strategic planning. KEYWORDS analytical tools, gaming techniques, strategic territorial development, municipality, systemic approach Аналитические инструменты экономических исследований малых муниципалитетов и игровые техники для вовлечения общественности (пример Воронежской области в России) М.И. Солосина1 , И.Н. Щепина1, 2 1 Воронежский государственный университет, Воронеж, Россия; e-mail: maria.solosina@gmail.com 2 Центральный экономико-математический институт Российской академии наук, Москва, Россия АННОТАЦИЯ Актуальность. В статье рассматриваются вопросы стратегического тер- риториального развития российских регионов и муниципалитетов и ана- литические инструменты для их изучения. Хотя существует множество инструментов для изучения крупных муниципалитетов, выбор инстру- ментов для небольших городских и сельских поселений весьма ограничен. Это пробел в исследованиях, на устранение которого нацелено это иссле- дование. Цель исследования. Данное исследование рассматривает муни- ципальные районы и поселки в Воронежской области. Цель состоит в том, чтобы на их примерах показать применение предложенной методологии. Данные и методы. Исследование опирается на методы системного анали- за и синтеза, сравнения и обобщения, многомерного статистического ана- лиза, а также на использование игровых технологий. Данные для анализа были получены из федеральной, региональной и муниципальной стати- стики; муниципальные информационные системы населенных пунктов КЛЮЧЕВЫЕ СЛОВА аналитический инструментарий, организационные механизмы, стратегическое территориальное развитие, муниципалитет, системный подход FOR CITATION Solosina, M.I., Shchepina, I.N. (2020) Analytical tools for economic research of small municipalities and gaming techniques for community involvement (the case of Voronezh region in Russia). R-economy, 6(2), 111–124. doi: 10.15826/recon.2020.6.2.010 http://doi.org/10.15826/recon.2020.6.2.010 http://doi.org/10.15826/recon.2020.6.2.010 112 https://journals.urfu.ru/index.php/r-economy R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 Online ISSN 2412-0731 Воронежской области; муниципальная информационная система МИСС «Волость»; и от органов исполнительной власти Воронежской области. Результаты. Анализ набора показателей, включая муниципальный про- дукт к ВРП, за период с 2006 по 2015 г. показал, что город Лиски является одним из ведущих муниципальных образований в Воронежской области (муниципальный продукт Лискинского района составляет более 5% ВРП региона). Мы также применили организационный игровой механизм для установления связи между властями и местными сообществами при раз- работке проекта создания историко-археологического парка в поселке Костенки Воронежской области. Выводы. Предложенная методология мо- жет быть весьма продуктивной для построения социально-экономических профилей малых муниципальных образований, сравнения их с другими и выявления взаимосвязей между ними. Игровые технологии эффектив- ны для повышения вовлеченности местных сообществ в муниципальное стратегическое планирование. ДЛЯ ЦИТИРОВАНИЯ Solosina, M.I., Shchepina, I.N. (2020) Analytical tools for economic research of small municipalities and gaming techniques for community involvement (the case of Voronezh region in Russia). R-economy, 6(2), 111–124. doi: 10.15826/recon.2020.6.2.010 Introduction Strategic planning has now become essential for settlements, towns, cities and other territorial entities as they get involved into the global com- petition for development resources (investment, human capital, technologies, etc.). Strategic plans and similar documents should incorporate the vision and aspirations of local communi- ties. These documents should also be based on comprehensive analysis of the current situation and development prospects of the territorial unit, including its strengths and weaknesses and development priorities. In Russia, the system of strategic territorial planning has been developing intensively over the past 15 years. One of the significant stages was Federal Law No. 172 ‘On Strategic Planning in the Russian Federation’ adopted in 2014. The law requires methodological uniformity of such documents on the regional and municipal levels, as well as their consistency with the state strat- egy for economic and social development. To devise such strategies, it is necessary to conduct preliminary quantitative analysis of the statistics characterizing the socio-economic situation and development trends of the territory. National, re- gional and municipal-level documents are usu- ally drawn based on federal and regional statis- tics, while for smaller municipalities (urban and rural settlements), this can be a problem due to the lack of statistical data. This problem can be addressed through the expansion of the database and development of tools of regional and muni- cipal statistics. The lack of data in the official statistics da- tabase (Russian Federal State Statistic Service – Rosstat) causes a shortage of available tools for analyzing the socio-economic situation in small municipalities. For our research, we used alterna- tive resources, such as the municipal information system MISS ‘Volost’ and the data provided by the executive authorities of Voronezh region (Depart- ment of Economic Development, Department of communications, Department for the Develop- ment of Municipalities of Voronezh region). As a result, we were able to create our own research database. Since there are more than 22,000 municipa- lities in Russia, and only in 15 of them the popu- lation exceeds one million, the available tools for studying urban and rural settlements often prove ineffective in the Russian context. For example, more than a half of inhabitants of Voronezh re- gion live in the municipalities (446 urban and rural settlements of Voronezh region) selected for our empirical analysis. To measure the so- cio-economic parameters in these municipalities, we need appropriate tools that would also help us make adequate comparisons. An important factor and the main resource for the development of settlements is human capital. The strategic nature of the social system (settlement, city, country) determines its read- iness for dynamic changes and development (Arshinov, 2007). Some territories may turn out to be more attractive to people than others due to the opportunities they offer, which inevitably af- fects migration trends (Tiebout, 1956). The article describes a set of analytical tools that could be used for building socio-economic profile of small municipalities (urban and rural settlements) and gaming techniques for creating projects of strategic territorial development in- volving local communities. Questions of territorial strategic develop- ment are discussed by Glazyrin (2016), Glazychev (2005), Zubarevich (2010), Makarov (2010), and Pilyasov (2016). Ayvazyan, Afanasyev, Kudrov http://doi.org/10.15826/recon.2020.6.2.010 R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 113 https://journals.urfu.ru/index.php/r-economy Online ISSN 2412-0731 (2016, 2018) give particular attention to these questions on the regional level. Most studies, however, focus on territorial strategic develop- ment on the national and regional levels, some also consider the level of municipal districts, but little is said about smaller settlements. The 2009 World Bank Report ‘A New Look at Economic Geography’ (2009) discusses the growth points of a territory in regional and global economies and ways of determining them. Socio-economic development of territo- ries was analyzed by Lee (2000), Florida (2010), Shachar (1971), Efrat (1994), Portnov (2004), Malizia (1986), Bontje (2004), Grimm (1995), Shapero (1981). The issues related to territorial development projects involving local communi- ties are investigated by V. E. Lepsky (2009), Vagin (2016), Kutuzov, Koveshnikova (2007), Myas- nikova (2015), and Tyurin (2007). The second part of our study discusses the use of gaming techniques for involvement of commu- nities in municipal strategic planning and is thus based on the concept of the game. Conceptually, this part relies on the works by Huizinga (2014) and Shchedrovitsky (1981). A significant contribution to the discussion of the theoretical and practical studies of municipal strategic management in Russia is made by such organizations as the Institute for Urban Econo- mics Foundation, Leontief Center, Center for Strategic Research, and the network of Centers for Applied Urban Studies. It should be noted, however, that most of the above-described economic studies dealing with the methodological problems of studying muni- cipalities in Russia are of theoretical or descriptive character. There is a perceived need for applied research in this sphere, which is the gap that our paper seeks to address. Methodology and Data This study focuses on the case of Voronezh region, which comprises 446 urban and rural set- tlements and 32 municipal districts, excluding the city of Voronezh. The study relies on the analysis of the legal acts, including those regulating the development of municipalities; federal, regional and municipal statistics; data from municipal in- formation systems of settlements of Voronezh re- gion or RIAS (regional information and analytical system); data from municipal information system MISS ‘Volost’; data from the executive authorities of Voronezh region (Department of Economic Development, Department of Communications, Department for the Development of Municipal- ities of Voronezh region) (Bystryantseva et al., 2016). The first part of the study uses multidimen- sional statistics and relies on the methods of sys- temic analysis and synthesis, comparison and generalization. The second part of the article de- scribes a specific case when gaming techniques were applied to stimulate community engage- ment. The methodological approach includes the following stages. At the first stage, the data are col- lected from various sources: Rosstat, regional and municipal statistics, municipal information sys- tems, reports on the performance of local author- ities, passports of municipalities, and so on. At the second stage, we select and cross-validate indica- tors and identify the typological data blocks. Fi- nally, the socio-economic status of municipalities is assessed through the following procedure: 1. Evaluation and comparison of the indica- tors of the gross municipal product (GMP) (Pet- rykina et al., 2016). To assess the GMP, we used the values of the average number of employees and the average monthly wage: G ,ii i r r ASGRP MP AE AE AS = ⋅ ⋅ where GMPi is the gross municipal product esti- mate for the i-th municipal district; GRP, gross regional product; AEr, the average number of em- ployees in the region; AEi, the average number of employees of the i-th municipal district; ASr, the average monthly wage in organizations of the re- gion; ASi, the average monthly wage in organiza- tions in the i-th municipal district. G ,jij j i i ASGMP MP AE AE AS = ⋅ ⋅ where GMPj is the gross municipal product esti- mate for the j-th settlement; GMPi is the assess- ment of the GMP of the i-th district; AEi, the av- erage number of employees of the i-th municipal district; AEj, the average number of employees of the j-th settlement; ASi, the the average monthly wage in organizations of the i-th municipal dis- trict; ASj, the average monthly wage in organiza- tions of the j-th settlement. To compare the GMP at the level of urban settlements, we introduced an adjusted coefficient for calculating the GMP of urban settlements http://doi.org/10.15826/recon.2020.6.2.010 114 https://journals.urfu.ru/index.php/r-economy R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 Online ISSN 2412-0731 (Petrykina et al., 2017), due to the differences in databases: the GMP of settlements was calculated according to the data of the settlement passports while the GMP of municipal districts was calcu- lated according to the Rosstat data. 2. Allocation of clusters of municipalities by using the methods of multivariate statistical anal- ysis according to the following criteria: by eco- nomic specialization (in accordance with OKVED (All-Russian Classifier of Economic Activities), by the level of socio-economic development, and by the number of workers employed in various types of economic activity (Petrykina et al., 2017). A comparative analysis of the results obtained through cluster analysis (Solosina, 2019). 3. Construction and comparison of economic profiles of settlements (Solosina, 2019). The methodology for constructing an eco- nomic profile proposed in this study includes several stages. First, a database is formed and indicators are selected for urban settlements of Voronezh region. Second, the maximum, minimum and average value for each indicator are calculated: max , 1 ;,maxj ij i x x j n= = min , 1 ;,minj ij i x x j n= = 1 , m ij j i x x m= = ∑ where j is the number of the indicator, i is the number of the city settlement, xij is the value of the indicator. Third, the average value is taken as the com- parison base, equal to 100% or 1, in relation to which the levels for each indicator are calculated for each urban settlement. , 1, , 1, ; ijij j x z i m j n x = = = , ; 1, max jmax j j x z j n x = = , ; 1, min jmin j j x z j n x = = 1, .1, jz j n= = The minimum and maximum values are cal- culated for the levels relative to the average for each indicator. Finally, for each urban settlement, a diagram of the scatter of values for each indicator is built. At the same time, two graphs are plotted on the chart: average values and indicator values for the given settlement. The resulting diagram rep- resents the economic profile of the given settle- ment (Fig. 1). Another key aspect of our research method- ology is the focus on the organizational mecha- nism – system-social design methodology (SSD) (Solosina, 2019), which has been proven effective for engaging members of local communities in strategic territorial development. This is a com- municational method aimed at involving people in the process of strategic planning and imple- mentation of strategic documents. 1 2 x1 n j Value of zi1–zin for i-th municipality zij max min zj = 1 z1 Figure 1. Economic profile of a settlement http://doi.org/10.15826/recon.2020.6.2.010 R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 115 https://journals.urfu.ru/index.php/r-economy Online ISSN 2412-0731 There are two approaches to the process of strategic development at the municipal level: ‘ad- ministrative-expert’ and ‘partner’ (Solosina & Schepina, 2016). A distinctive feature of the lat- ter approach is the involvement of residents in the process of strategic decision-making and develop- ment of appropriate tools for doing so. Members of local communities are involved into the stra- tegic planning process with the help of gaming techniques. The basis of the SSD methodology is the ‘game square’ method proposed by M.A. Kutu- zova, which includes a series of game seminars (problem seminar / project seminar / strategic game / operational game) and developed on the basis of military operational-tactical games and organizational-activity games (the for- mat was initially developed by G.P. Shchedro- vitsky (1981)). The main stages of the game and its preparation within the SSD framework are shown in Figure 2 below. First, the technical task for the game is agreed upon with the customer. The customer may be, for example, the municipal administration, a re- gional executive authority, a self-governing terri- torial body, an action group, or a business. After agreeing on the technical specifications, the game master and the game support team develop the scenario by conducting preliminary research and analysis. Second, the list of participants is drawn: it is necessary to involve all the participants interested in solving the problem posed by the customer. To participate in the game, one must know the rules of the game and the terminology, which is why the preparatory materials should be sent to par- ticipants in advance. When the game starts, the first stage is to discuss and revise the rules and terminology, which is necessary to stimulate creative thinking of the participants. Then, in accordance with the methodology, game participants go through all SSD stages such as research, situation analysis, forecasting, development of scenarios, creation of a project line, and start-up projects. Following that, the participants are transferred from the game into the real project space. At this stage, the participants discuss the future prospects of the project developed during the game. Based on the results of the game, the game report is pre- pared, which contains all the material that was collected and analyzed. There are three types of game project out- comes: the game product; development of the participants’ soft skills; and the network. The game product is a system-social model of the project which includes: concepts, values, project characteristics, activities, system of management and leadership, roadmap, and potential risks. Soft skills are the skills and competencies of the participants that are developed through their ex- perience of team work. A network is here under- stood as an action group that creates and signs the project declaration, thereby indicating their interest in further participation. The uniqueness of SSD lies in the gaming component, since it is the game tools that help create a common strategy for a system-social project, motivate people to join such projects and become part of project teams. The SSD methodology is focused on the creation of a sys- tem-social project and the formation of the insti- tutional environment for creating other projects within the framework of the SSD project. Expert support at all stages allows project participants to maintain the strategic focus of the project. Results We applied the above-described methodolog- ical approach to assess the socio-economic status of municipalities in Russia by focusing on the case of the town of Liski in Voronezh region. Technical task for the game List of participants Distribution of materials to prepare for the game Game Game report research, problematization, analysis, forecast, scenario creation game scenario 1 2 3 4 5 Figure 2. Stages of the game and its preparation http://doi.org/10.15826/recon.2020.6.2.010 116 https://journals.urfu.ru/index.php/r-economy R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 Online ISSN 2412-0731 In accordance with the regional plan for the development of Voronezh region, Liski is the ad- ministrative center of Liskinsky district, which in total includes 23 urban and rural settlements. Since 2013, Liskinsky district has been one of the leading municipal districts in Voronezh re- gion, according to the results of the comprehen- sive assessment of the regin’s socio-economic development. We used the Rosstat data and settlement pass- ports to obtain GMP estimates for Liskinsky mu- nicipal district for 2006, 2010 and 2015, and then for the town of Liski itself. Let us compare the GMP values of Liskin- sky municipal district for 2006, 2010 and 2015 (see Table 1), given that the average monthly wage in Voronezh region in 2015 amounted to 27,772.7 rubles, GRP was 823,133.6 million rubles, the average number of employees was 500,356. The GMP was just over 5% of the region’s GRP. Since 2006, Liskinsky municipal district, along with Rossoshansky municipal district and Bor- isoglebsky city district, has been among the three leading municipalities in terms of GMP (Table 1). Table 1 The GMP of Liskinsky municipal district in 2006, 2010 and 2015 Year Average num- ber of employ- ees, people Average monthly wage, rub GMP, mln rub GMP in % to GRP 2006 29,870 7,773.7 8,908.05 5.36 2010 27,651 15,181.3 17,933.96 5.17 2015 26,247 26,571.0 41,310.52 5.02 Source: compiled by the authors. After evaluating the general indicator of so- cio-economic development – the GMP at the district and settlement levels, we identifed the ty- pological group of this municipality. To do this, we used cluster analysis (Tables 2, 3). In 2015, according to the results of clustering in terms of socio-economic development, Liskinsky munic- ipal district belonged to cluster A together with Rossoshansky, Pavlovsky, Novousmansky munic- ipal areas and Borisoglebsky municipal districts. In terms of economic specialization, the areas like Pavlovsky, Novousmansky, Bobrovsky, Ka- lacheevsky, Ostrogozhsky, and Talovsky munic- ipal districts belong to cluster 2 (Table 2) – the leading cluster in terms of crop and livestock pro- duction. At the same time, the town of Liski ranks second in terms of the volume of production (works and services) in such types of economic activities as “Production and distribution of elec- tricity, gas and water” and “Manufacturing”. Thus, the municipalities in this cluster can be character- ized as “agricultural leaders”, although they also have a fairly well developed sphere of industrial production (Table 3). In each column of Table 2, the leading mu- nicipalities are highlighted in orange. Those mu- nicipalities that rank second after the leaders are highlighted in yellow. These two groups include municipalities with the following characteristics: – clustering: a combination of clusters A – 1 and A – 2 (for both groups); – gross municipal product (GMP): more than 2% of GRP (orange group) and 1–2% of GRP (yel- low group); – population: over 70,000 (orange group) and 40,000–70,000 (yellow group); – wages: more than 25,000 rubles (for both groups). Other colors highlight the groups of munic- ipalities that have the same types in two clusters. Next, we turn to the adjusted estimate of the GMP obtained for some urban settlements of Vo- ronezh region in 2015, including Liski (Table 3). Liski is the leader in terms of the GMP (22,241.72 million rubles), followed by Rossosh (18,425.98 million rubles). As for the number of employees and type of activity (Table 3), Liski, along with Rossosh, be- longs to cluster 1 with a high number of employ- ees in “Manufacturing industries” and with fairly high rates of employees in “Agriculture, hunting and forestry”, “Production and distribution of electricity, gas and water.” Thus, according to the selected indicators of economic specialization, the employment structure of Liski does not fully correspond to the specialization of Liskinsky mu- nicipal district. It is more industrial than in the district as a whole. The city has large enterprises manufacturing metal structures and building ma- terials and processing agricultural products. At the following stage, we are going to turn to the economic profile of the town of Liski and con- sider the town’s progress during the given period (Figures 2–4). In 2006–2015, Liski maintained the leading position in the following indicators: total number of employees; the number of employees in ‘Man- ufacturing’; ‘Transport and communications’ (the town has a large railway junction and a river port); ‘Agriculture, hunting and forestry’; ‘Wholesale and retail trade, repair of motor vehicles, motorcycles, http://doi.org/10.15826/recon.2020.6.2.010 R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 117 https://journals.urfu.ru/index.php/r-economy Online ISSN 2412-0731 Table 2 Municipal districts in Voronezh region in 2015 Municipal districts Clusters by the level of socio-eco-nomic development (A-F) Clusters by economic specialization (1–4) GMP in % GRP Population, people Wages, rub. Rossoshansky A 1 3.74 93,368 25,571.3 Borisoglebsky A 1 2.01 63,678 21,046.8 Liskinsky A 2 5.02 101,764 26,571.0 Pavlovsky A 2 1.70 55,990 21,476.4 Novoysmansky A 2 1.52 79,183 25,594.6 Semiluksky A 3 1.27 67,558 22,340.7 Anninsky B 2 1.05 41,195 19,513.8 Ramonsky B 3 1.72 32,440 25,361.3 Bobrovsky C 2 1.23 49,148 21,004.6 Kalacheevsky C 2 1.08 53,670 19,732.4 Buturlinovsky C 3 0.88 47,918 18,846.2 Ertilsky C 3 0.51 23,839 18,430.2 Novohopersky C 4 0.71 38,787 20,119.0 Bogucharsky C 4 0.62 35,732 19,069.6 Khokholsky C 4 0.61 29,702 22,213.6 Verhnemamonsky C 4 0.38 19,890 19,526.9 Petropavlovsky C 4 0.23 18,103 20,542.5 Repyevsky C 4 0.23 15,742 21,055.7 Talovsky D 2 0.86 39,785 20,320.7 Verkhnekhavsky D 3 0.65 24,665 23,856.3 Kashirsky D 3 0.49 24,343 23,979.1 Ternovsky D 3 0.36 19,824 18,791.5 Vorobyevsky D 3 0.33 17,071 19,239.2 Podgorensky D 4 0.54 25,338 20,726.4 Nizhnedevitsky E 4 0.40 18,989 24,963.0 Ostrogozhsky F 2 1.51 58,950 23,236.9 Gribanovsky F 2 0.74 31,100 21,096.1 Kantemirovsky F 3 0.85 34,923 21,898.2 Paninsky F 3 0.54 26,531 19,435.3 Povorinsky F 4 0.60 32,755 21,014.2 Olkhovatsky F 4 0.54 23,356 20,585.7 Kamensky F 4 0.48 18,921 22,470.7 Source: compiled by the authors. Table 3 Urban settlements in Voronezh region in 2015 Clusters in terms of so- cio-economics development Economy: Cluster spe- cialization (1–4) Clusters of mu- nicipalities GMP adjusted for settle- ments’ GMP, million rub. Popula- tion Wage, rub Rossosh A 1 industrial 1 industrial 18,425.98 62,688 22,776 Liski A 2 agricultural leaders + electroenergy 1 industrial 22,241.72 54,788 26,572 Pavlovsk A 2 agricultural leaders + electroenergy 4 with low rates 6,426.22 25,081 22,063 Davydovskoe A 2 agricultural leaders + electroenergy 4 with low rates 1,343.52 5,258 16,725 Latnensky A 3 agricultural 4 with low rates 1,050.44 7,359 20,626 Anninsky B 2 agricultural leaders + electroenergy 4 with low rates 3,441.91 16,729 19,221.8 Ramon B 3 agricultural 4 with low rates 2,856.75 8,381 19,800 Kalach C 2 agricultural leaders + electroenergy 2 agricultural 1,956.36 19,248 12,065 http://doi.org/10.15826/recon.2020.6.2.010 118 https://journals.urfu.ru/index.php/r-economy R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 Online ISSN 2412-0731 Clusters in terms of so- cio-economics development Economy: Cluster spe- cialization (1–4) Clusters of mu- nicipalities GMP adjusted for settle- ments’ GMP, million rub. Popula- tion Wage, rub Bobrov C 2 agricultural leaders + electroenergy 4 with low rates 3,290.01 19,956 16,780 Buturlinovka C 3 agricultural 2 agricultural 3,772.99 25,230 18,600 Ertil C 3 agricultural 2 agricultural 1,904.31 10,740 18,530 Kantemirovskoe C 3 agricultural 4 with low rates 1,888.86 11,113 22,600 Novokhopersk C 4 with low rates 2 agricultural 2,022.34 13,845 19,500 Boguchar C 4 with low rates 4 with low rates 1,446.83 11,162 17,322 Khokholskoe C 4 with low rates 4 with low rates 855.34 7,549 14,916 Yelan-Kolenovskoe C 4 with low rates 4 with low rates 560.92 3,635 20,600 Nizhnekislyayskoye C 4 with low rates 4 with low rates 465.77 3,576 16,200 Talovskoe D 2 agricultural leaders + electroenergy 4 with low rates 1,643.26 11,736 15,937 Podgorensky D 4 with low rates 4 with low rates 1,026.02 5,750 21,004 Gribanovskoe F 2 agricultural leaders + electroenergy 2 agricultural 3,193.01 15,255 22,400 Ostrogozhsk F 2 agricultural leaders + electroenergy 3 electrical energy 5,027.35 32,944 16,772 Pereleshinskoe F 3 agricultural 4 with low rates 437.31 2,797 18,100 Source: the authors’ calculations based on the original dataset 0 2 4 6 8 10 12 Po pu la tio n de ns ity Pe rc en ta ge o f a gr ic ul tu ra l l an d Pe rc en ta ge in du st ri al la nd T ot al e m pl oy ed in th e ec on om y T ot al n um be r of e m pl oy ee s N um be r of e m pl oy ee s ‘A gr ic ul tu re , hu nt in g an d fo re st ry ’, pe op le N um be r of e m pl oy ee s ‘M in er al e xt ra ct io n’ , p eo pl e N um be r of e m pl oy ee s ‘M an uf ac tu ri ng ’, pe op le N um be r of e m pl oy ee s ‘P ro du ct io n an d di st ri bu tio n of e le ct ri ci ty , g as … N um be r of e m pl oy ee s ‘C on st ru ct io n’ , p eo pl e N um be r of e m pl oy ee s ‘W ho le sa le a nd re ta il tr ad e, r ep ai r, e tc .’, p er s. N um be r of e m pl oy ee s ‘T ra ns po rt an d co m m un ic at io ns ’, pe op le N um be r of e m pl oy ee s ‘F in an ci al a ct iv iti es ’, pe op le N um be r of e m pl oy ee s ‘E du ca tio n’ N um be r of e m pl oy ee s ‘H ea lth an d so ci al s er vi ce s’ , p eo pl e N um be r of e m pl oy ee s ‘� e pr ov is io n of o th er u til ity , s oc ia l a nd … N um be r of e m pl oy ee s in b ud ge t or ga ni za tio ns � na nc ed fr om th e… A ve ra ge m on th ly s al ar y A ve ra ge h ou si ng H ou si ng e qu ip m en t w at er s up pl y H ou si ng e qu ip m en t w ith g as su pp ly Pr op or tio n of p er so ns o ld er th an w or ki ng a ge C oe � ci en t o f n at ur es . p op ul at io n gr ow th M ig ra tio n gr ow th r at e Average Liski Figure 3. Economic profile of Liski for 2006 Source: the authors’ calculations based on the original dataset End Table 3 http://doi.org/10.15826/recon.2020.6.2.010 R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 119 https://journals.urfu.ru/index.php/r-economy Online ISSN 2412-0731 household products and personal items’; ‘Educa- tion’ (the town has several professional colleges and branches of universities); ‘Healthcare and so- cial services’. It should be noted that we don’t have the data for 2006 on such indicators as the share of industrial land and the share of agricultural land. Moreover, in 2010 and 2015, the share of industri- al land reached its maximum, and the share of ag- ricultural land, its minimum, which characterizes the city as an industrial center. In comparison with other settlements, Lis- ki was losing its position in terms of the number of employees in ‘Construction’ (even though the town is producing building materials) and ‘Fi- nancial activity’. The indicators of natural and mi- gration growth showed negative dynamics since 2010, the population of the city decreased by 2%. In the other indicators, the city retained its posi- tion (Fig. 3–5). We believe that the proposed methodological approach and its visualization can help be used for managerial decision-making and strategic plan- ning of municipalities. Engaging and Involving Local Communities in Municipal Strategic Planning: Gaming Techniques Involving people into the process of strategic planning is a key to successful implementation of municipal strategies. The proposed SSD meth- odology was tested in the settlement of Kostenki in 2017. Kostenki is a comparatively small settle- ment, located 47 km from the city of Voronezh. The population is 1485 people, according to the settlement’s passport, aged 0-6 (45 people); 7–17 (96 people); 18–45 (560 people); 46–59 (295 peo- ple); and 60 or older (479 people). On the terri- tory of the settlement, there are two agricultural 0 1 2 3 4 5 6 7 8 9 10 Po pu la tio n de ns ity Pe rc en ta ge o f a gr ic ul tu ra l l an d Pe rc en ta ge in du st ri al la nd T ot al e m pl oy ed in th e ec on om y T ot al n um be r of e m pl oy ee s N um be r of e m pl oy ee s ‘A gr ic ul tu re , hu nt in g an d fo re st ry ’, pe op le N um be r of e m pl oy ee s ‘M in er al e xt ra ct io n’ , p eo pl e N um be r of e m pl oy ee s ‘M an uf ac tu ri ng ’, pe op le N um be r of e m pl oy ee s ‘P ro du ct io n an d di st ri bu tio n of e le ct ri ci ty , g as a nd … N um be r of e m pl oy ee s ‘C on st ru ct io n’ , p eo pl e N um be r of e m pl oy ee s ‘W ho le sa le a nd re ta il tr ad e, r ep ai r, e tc .’, p er s. N um be r of e m pl oy ee s ‘T ra ns po rt an d co m m un ic at io ns ’, pe op le N um be r of e m pl oy ee s "F in an ci al a ct iv iti es ’, pe op le N um be r of e m pl oy ee s ‘E du ca tio n’ N um be r of e m pl oy ee s ‘H ea lth a nd s oc ia l s er vi ce s’ , p eo pl e N um be r of e m pl oy ee s ‘� e pr ov is io n of o th er ut ili ty , s oc ia l a nd p er so na l… N um be r of e m pl oy ee s in b ud ge t o rg an iz at io ns �n an ce d fr om th e m un ic ip al … A ve ra ge m on th ly s al ar y A ve ra ge h ou si ng H ou si ng e qu ip m en t w at er s up pl y H ou si ng e qu ip m en t w ith g as su pp ly Pr op or tio n of p er so ns o ld er th an w or ki ng a ge C oe � ci en t o f n at ur es . p op ul at io n gr ow th M ig ra tio n gr ow th r at e Average Liski Figure 4. Economic profile of Liski for 2010 Source: the authors’ calculations based on the original dataset http://doi.org/10.15826/recon.2020.6.2.010 120 https://journals.urfu.ru/index.php/r-economy R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 Online ISSN 2412-0731 enterprises and 639 private farms. According to the statistics, the average monthly wage in the district in 2015 was 22,213.6 rubles, and the aver- age wage of workers in peasant farms, 10,644 ru- bles. The average number of workers in peasant farms was 8 people. In total, the average number of workers (external part-timers excluded) in the district in 2015 was 3809. Kostenski rural settle- ment (Kostenki) is located in Khokholsky district, which has the MP of 5011.91 million rubles or 0.61% of GRP (Tables 2 and 3). The settlement of Kostenki has a unique tour- ist potential. Kostenki is world-famous for its rich historical and cultural heritage and natural beauty. The first people settled in these places 50,000 years ago, the first dwellings date back 25,000 years, there 0 2 4 6 8 10 12 14 Po pu la tio n de ns ity Pe rc en ta ge o f a gr ic ul tu ra l l an d Pe rc en ta ge in du st ri al la nd T ot al e m pl oy ed in th e ec on om y T ot al n um be r of e m pl oy ee s N um be r of e m pl oy ee s ‘A gr ic ul tu re , hu nt in g an d fo re st ry ’, pe op le N um be r of e m pl oy ee s "M in er al e xt ra ct io n’ , p eo pl e N um be r of e m pl oy ee s ‘M an uf ac tu ri ng ", pe op le N um be r of e m pl oy ee s ‘P ro du ct io n an d di st ri bu tio n of e le ct ri ci ty , g as a nd w at er ’,… N um be r of e m pl oy ee s ‘C on st r u ct io n’ , p eo pl e N um be r of e m pl oy ee s ‘W ho le sa le an d re ta il tr ad e, r ep ai r, e tc .’, p er s. N um be r of e m pl oy ee s ‘T ra ns po rt an d co m m un ic at io ns ’, pe op le N um be r of e m pl oy ee s ‘F in an ci al a ct iv iti es ’, pe op le N um be r of e m pl oy ee s ‘E du ca tio n’ N um be r of e m pl oy ee s ‘H ea lth an d so ci al s er vi ce s’ , p eo pl e N um be r of e m pl oy ee s ‘� e pr ov is io n of o th er ut ili ty , s oc ia l a nd p er so na l s er vi ce s’ ,… N um be r of e m pl oy ee s ‘H ot el s an d re st au ra nt s’ N um be r of e m pl oy ee s ‘O pe ra tio ns w ith r ea l e st at e ... ’ A ve ra ge m on th ly s al ar y A ve ra ge h ou si ng H ou si ng e qu ip m en t w at er s up pl y H ou si ng e qu ip m en t w ith g as s up pl y Pr op or tio n of p er so ns o ld er th an w or ki ng a ge C oe � ci en t o f n at ur es . p op ul at io n gr ow th M ig ra tio n gr ow th r at e Liski Average Figure 5. Economic profile of Liski for 2015 Source: the authors’ calculations based on the original dataset are the cultural layers in the area that store samples of primitive art (Paleolithic Venus). The modern village of Kostenki is the heir to the city of Kostyensk, an outpost of the 17th centu- ry on the southern outskirts of Russia. Kostyensk constituted a part of the Belgorod system of de- fensive fortifications protecting the local commu- nities from Tatar raids from the south. Then, with the decline of its functionality as a fortress, the city lost its status and became a rural settlement. The customer of the game was the entrepre- neur who planned to create an archeological park on the territory of Kostenki. The game was aimed at developing a SSD model for creation of such a park, devising possible scenarios for this project and a roadmap for its implementation. There were http://doi.org/10.15826/recon.2020.6.2.010 R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 121 https://journals.urfu.ru/index.php/r-economy Online ISSN 2412-0731 20 participants in the game: students, entrepre- neurs, historians, journalists and economists. The key participants were the Director of the Kosten- ki Open-Air Museum and the customer (initiator of the project). The participants of the game be- longed to various age and professional groups. Residents of the settlement participated in a number of regional programs: for example, in 2016 the municipality received 96,000 rubles for the improvement of a children’s playground and in 2017, the residents of the settlement decided to participate in the budgeting program and submit- ted their road repair project for the 2018 compe- tition. Below are the outcomes of the game, which fall within three categories: the game product, the participants’ soft skills, and the network. 1. Game product Participants of the game pointed out that there recently Russian people has started to take more interest in the history of their country, re- gion, community and family, which means that the project of Kostenki may benefit from this trend. The result of the game was the partici- pants’ common vision of the future development of archeological park ‘Kostenki’ and the sur- rounding area. 1.1. System-social model of the project. The historical and archaeological park is the result of a joint effort of the community, entrepre- neurs and local authorities. Participants of the game pointed out that free time is now becoming a key development re- source for people and that archaeological park in Kostenki could follow the concept of life history, which corresponds to this trend. The creation of an archaeological park in- cludes the study of the types of activities that could be offered to its visitors such as educational on- line and off-line events involving representatives of the academia and members of local communi- ties; amateur archeology course; expositions with augmented reality experiences; experience-based programs for tourists (e.g. experience life in the Paleolithic Age) and volunteering programs. All types of project activities fall within the concept of leisure as time for personal develop- ment and education. 1.2. The main characteristics of the project in- clude the following. 1.2.1. Collective decision-making mecha- nism and creation of an appropriate management structure. The proposed range of activities, on the one hand, makes the system more stable, on the other hand, it requires appropriate management at all stages of the project development; 1.2.2. Networking. The project, among other things, stimulates participants to build relations within the project team and interact with external stakeholders; 1.2.3. Brand development. The archeological park as a heritage project capitalizes on the site’s unique location and history; 1.2.4. Rules of cooperation. The game relies on a system of rules devised by the participants themselves; participants should meet a set of re- quirements such as willingness to invest resour- ces; motivation; sharing the project’s values; 1.2.5. Megaproject. In order to manage sev- eral projects at once, efficient leadership and an organizational structure are necessary. The management should include an expert council responsible for the development and im- plementation of the project strategy, the search for strategic partners, analysis of the project’s trajectory and so on. There should also be mana- gers responsible for specific areas and issues. In order to create such a management structure, it is necessary to distinguish between operational and strategic aspects of the project. For example, to realize a subproject aimed at organizing a series of lectures on Kostenki, it is necessary to devise a strategy, select topics, prepare materials, choose the time and place, coordinate the work of orga- nizers, and so on. All this requires the organiza- tional structure to be horizontal and flexible, able to quickly adapt to the changing situation. 1.3. Project risks. Certain risks, primarily of organizational nature, should be considered: for example, the loss of strategy or uniqueness of the project or disagreements between the parties in- volved in project realization. 2. Development of Participants’ Soft Skills and the Network For the project team, it is essential that all its participants should enhance their teamwork and other basic skills. At the first stage of the project, a project dec- laration is devised and signed. The declaration is necessary to indicate the participants’ commit- ment to the values and goals of the project. One of the significant outcomes of the game is to create an action group that would be responsible for im- plementation of the project in real life. According to the SSD methodology, the par- ticipants of the game go through the following http://doi.org/10.15826/recon.2020.6.2.010 122 https://journals.urfu.ru/index.php/r-economy R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 Online ISSN 2412-0731 stages: research – analysis – forecasting – de- vising development scenarios – developing subprojects – start-up stage. In the game, these stages take less time than in real life, so the game prepares participants for future realization of the project and helps them develop the necessary skills. The SSD methodology is aimed at developing a strategic territorial development project and can be used at the stages of strategy development and implementation. Conclusions The article proposes methodological tools for investigating socio-economic development of small municipalities and gaming techniques for involving local communities in municipal strate- gic planning. The methodological approach is based on the integrated use of our original databases (Bystry- antseva et al., 2016) and enables us to conduct analysis of individual municipal districts and com- pare them with other municipalities. We tested these tools by using the data on Voronezh region and showed the role specific municipalities (for example, the town of Liski) play in the region’s so- cio-economic system (Solosina, Shchepina, 2016). To make the proposed approach more effec- tive, it could be combined with other analytical tools, for example, SWOT analysis. We could also build socio-economic profiles of municipalities to reveal their strengths and weaknesses and de- velopment trends and describe their relationships with other municipalities. 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Retrieved from https://open- knowledge.worldbank.org/handle/10986/5991 Zubarevich, N.V. (2010). Regions of Russia: inequality, crisis, modernization. Moscow: Indepen- dent Institute for Social Policy, 160. (In Russ.) http://doi.org/10.15826/recon.2020.6.2.010 http://www.inesnet.ru/article/regionalnye-strategii-razvitiya-mezhdu-strategicheskim-proryvom-i-strategicheskim-tupikom/ http://www.inesnet.ru/article/regionalnye-strategii-razvitiya-mezhdu-strategicheskim-proryvom-i-strategicheskim-tupikom/ http://www.inesnet.ru/article/regionalnye-strategii-razvitiya-mezhdu-strategicheskim-proryvom-i-strategicheskim-tupikom/ https://openknowledge.worldbank.org/handle/10986/5991 https://openknowledge.worldbank.org/handle/10986/5991 124 https://journals.urfu.ru/index.php/r-economy R-ECONOMY, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 Online ISSN 2412-0731 Information about the authors Maria I. Solosina – Phd. in Economics, Leading Engineer of Interfaculty Research Laboratory of Economics and Management (Khusulnova st. 40, 394068, Voronezh, Russia); e-mail: maria.solo- sina@gmail.com Irina N. Shchepina – Doctor of Economic Sciences, Professor of Informational Technology and Mathematical Methods in Economy Department (Khusulnova st. 40, 394068, Voronezh, Rus- sia); chief researcher, Central Economics and mathematics Institute Russian Academy of Sciences (117418, Moscow, Nakhimovsky pr. 47); e-mail: shchepina@mail.ru ARTICLE INFO: received January 24, 2020; accepted May 6, 2020 Информация об авторах Солосина Мария Игоревна – кандидат экономических наук, ведущий инженер межфакультетской научно-исследовательской лаборатории экономики и управления Воронежского государственного университета (394068, Россия, Воронеж, ул. Хользунова, 40); e-mail: maria.solosina@gmail.com Щепина Ирина Наумовна – доктор экономических наук, профессор кафедры информационных технологий и математических методов в экономике Воронежского государственного университета (394068, Россия, Воронеж, Воронежская обл., ул. Хользунова, 40); главный научный сотрудник ЦЭМИ РАН (117418, Россия, Москва, Нахимовский пр., 47); e-mail: shchepina@mail.ru ИНФОРМАЦИЯ О СТАТЬЕ: дата поступления 24 января 2020 г.; дата принятия к печати 6 мая 2020 г. http://doi.org/10.15826/recon.2020.6.2.010 mailto:shchepina@mail.ru mailto:shchepina@mail.ru