Formation of the competitive potential of the agricultural territories

The purpose of the study is to develop a mechanism for the formation of the competitive potential of the agricultural territories of Kazakhstan as the basis for ensuring the dynamic development of agricultural business in Kazakhstan. The research methodology is based on strategic alternative modelin...

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Autores:
Anokhina, Marina
Abdrakhmanov, Rakhat
Evgenevna Gridneva, Yelena
Arrieta - López, Milton
Romanovna Dzhalilova, Nuray
Meza - Godoy, Abel
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/6147
Acceso en línea:
https://hdl.handle.net/11323/6147
http://doi.org/10.9770/jesi.2020.7.3(32)
https://repositorio.cuc.edu.co/
Palabra clave:
Agro-industrial complex
Kazakhstan
Agricultural territories
Competitive potential
Cognitive modeling
Fuzzy cognitive maps
Static and dynamic analysis
Strategic alternatives
Competitiveness management strategy
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openAccess
License
CC0 1.0 Universal
id RCUC2_656db8a16b6aacc3c7a5d140174adfa8
oai_identifier_str oai:repositorio.cuc.edu.co:11323/6147
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Formation of the competitive potential of the agricultural territories
title Formation of the competitive potential of the agricultural territories
spellingShingle Formation of the competitive potential of the agricultural territories
Agro-industrial complex
Kazakhstan
Agricultural territories
Competitive potential
Cognitive modeling
Fuzzy cognitive maps
Static and dynamic analysis
Strategic alternatives
Competitiveness management strategy
title_short Formation of the competitive potential of the agricultural territories
title_full Formation of the competitive potential of the agricultural territories
title_fullStr Formation of the competitive potential of the agricultural territories
title_full_unstemmed Formation of the competitive potential of the agricultural territories
title_sort Formation of the competitive potential of the agricultural territories
dc.creator.fl_str_mv Anokhina, Marina
Abdrakhmanov, Rakhat
Evgenevna Gridneva, Yelena
Arrieta - López, Milton
Romanovna Dzhalilova, Nuray
Meza - Godoy, Abel
dc.contributor.author.spa.fl_str_mv Anokhina, Marina
Abdrakhmanov, Rakhat
Evgenevna Gridneva, Yelena
Arrieta - López, Milton
Romanovna Dzhalilova, Nuray
Meza - Godoy, Abel
dc.subject.spa.fl_str_mv Agro-industrial complex
Kazakhstan
Agricultural territories
Competitive potential
Cognitive modeling
Fuzzy cognitive maps
Static and dynamic analysis
Strategic alternatives
Competitiveness management strategy
topic Agro-industrial complex
Kazakhstan
Agricultural territories
Competitive potential
Cognitive modeling
Fuzzy cognitive maps
Static and dynamic analysis
Strategic alternatives
Competitiveness management strategy
description The purpose of the study is to develop a mechanism for the formation of the competitive potential of the agricultural territories of Kazakhstan as the basis for ensuring the dynamic development of agricultural business in Kazakhstan. The research methodology is based on strategic alternative modeling for agricultural territories competitiveness management with the help of fuzzy cognitive logic. The study used a cognitive approach to decision making in the management of poorly structured systems proposed by V. Silov and actively developed in the works of modern scientists. Fifteen competent experts were invited to select the concepts and build a fuzzy cognitive map of the formation of the competitive potential of the agricultural territories of Kazakhstan. To carry out calculations and justify the content of the strategy, the authors used the software product “Intelligent generation of the best alternatives” (“IGLA”). The result of the study is the developed strategy for the management of agricultural territories competitiveness in Kazakhstan with a set of strategic goals and the best option for managerial impact, ensuring the formation of agricultural export potential of the region. The proposed version of the content of the strategy for managing the competitiveness of the agricultural territories of Kazakhstan can be used either as a system or as its separate elements in managing the development of agricultural business in the country and in developing strategic planning programs for the agro-industrial complex of the region. The novelty of the study in theoretical terms is justified by the approach to the formation of the country's agricultural export potential through ensuring the competitiveness of its agricultural territories. In methodological terms, the novelty of the study is expressed by the use of cognitive modeling technologies to develop a strategy for managing the competitiveness of Kazakhstan's agricultural territories, the implementation of which will allow achieving sustainable dynamics of agricultural production and increase the efficiency of the agricultural economy. The purpose of the study is to develop a mechanism for the formation of the competitive potential of the agricultural territories of Kazakhstan as the basis for ensuring the dynamic development of agricultural business in Kazakhstan. The research methodology is based on strategic alternative modeling for agricultural territories competitiveness management with the help of fuzzy cognitive logic. The study used a cognitive approach to decision making in the management of poorly structured systems proposed by V. Silov and actively developed in the works of modern scientists. Fifteen competent experts were invited to select the concepts and build a fuzzy cognitive map of the formation of the competitive potential of the agricultural territories of Kazakhstan. To carry out calculations and justify the content of the strategy, the authors used the software product “Intelligent generation of the best alternatives” (“IGLA”). The result of the study is the developed strategy for the management of agricultural territories competitiveness in Kazakhstan with a set of strategic goals and the best option for managerial impact, ensuring the formation of agricultural export potential of the region. The proposed version of the content of the strategy for managing the competitiveness of the agricultural territories of Kazakhstan can be used either as a system or as its separate elements in managing the development of agricultural business in the country and in developing strategic planning programs for the agro-industrial complex of the region. The novelty of the study in theoretical terms is justified by the approach to the formation of the country's agricultural export potential through ensuring the competitiveness of its agricultural territories. In methodological terms, the novelty of the study is expressed by the use of cognitive modeling technologies to develop a strategy for managing the competitiveness of Kazakhstan's agricultural territories, the implementation of which will allow achieving sustainable dynamics of agricultural production and increase the efficiency of the agricultural economy
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-04-01T19:38:50Z
dc.date.available.none.fl_str_mv 2020-04-01T19:38:50Z
dc.date.issued.none.fl_str_mv 2020
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.doi.spa.fl_str_mv http://doi.org/10.9770/jesi.2020.7.3(32)
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 2345-0282
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/6147
http://doi.org/10.9770/jesi.2020.7.3(32)
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv Andersen, E. 2017. The farming system component of European agricultural landscapes. European Journal of Agronomy, 82: 282-291.
Atkin, R.H., Casti, J. 1977. Polyhedral dynamics and the geometry of systems, IIASA Research Report. IIASA, Laxenburg, Austria: RR77-006.
Avdeeva, Z.K., Kovriga, S.V., and Makarenko, D.I. 2007. Cognitive modeling for solving problems in the management of weakly structured systems (situations). Management of Large Systems, 16: 26–39.
Axelrod, R. 1976. The Structure of Decision: Cognitive Maps of Political Elites. Princeton, NJ: Prinston University Press.
Bautin, V. M., Kozlov, V. V., Merzlov, A. V. 2004. Ustoichivoe razvitie selskikh territorii: voprosy strategii i taktiki [Sustainable rural development: issues of strategy and tactics]. Moscow: FGNU ”Rosinformagrotekh”.
Bondarenko, L. 2015. Regionalnaya politika gosudarstvennoi podderzhki selskikh territorii [Regional policy of state support for rural areas]. APK: ekonomika, upravlenie: teoreticheskii i nauchno-prakticheskii zhurnal, 3: 71-82.
Borisov, V. V., Kruglov, V. V., Fedulov, A. S. 2007. Fuzzy models and networks. Moscow. Hot line — Telecom.
Casti, J. 1982. Connectivity, complexity, and catastrophe in large-scale systems. Moscow. Mir publishing house.
D’Amico, M., Coppola, A., Chinnici, G., di Vita, G., Pappalardo G. 2013. Agricultural systems in the European Union: an analysis of regional differences. New Medit, 12(4): 28-34.
Duff, A., Padilla A. 2015. Latin America: agricultural perspectives. Retrieved from: https://economics.rabobank.com/publications/2015/september/latin%2Damerica%2Dagricultural%2Dperspectives/
Erokhin, D. V., Lagerev, D. G., Laricheva, E. A., Podvesovskii, A. G. 2010. Strategic management of innovative activity of the enterprise. Bryansk. BSTU.
Gorelov, V. I., Karelova, O. L., Ledashcheva, T. N. 2012. System modeling in socio-economic sphere. Moscow. Logos.
Guiomar, N., Godinho, S., Pinto-Correia, T., Almeida, M., Bartolini, F., Bezák, P., Biró, M., Bjørkhaug, H., Bojnec, Š., Brunori, G. et al. 2018. Typology and distribution of small farms in Europe: Towards a better picture. Land Use Policy, 75: 784-798.
Guth, M., & Smędzik-Ambroży, K. 2019. Economic resources versus the efficiency of different types of agricultural production in regions of the European Union. Economic Research-Ekonomska Istraživanja. https://doi.org/10.1080/1331677X.2019.1585270
Ikonnikova, O. V. 2014. Osnovnye podkhody k klassifikatsii selskikh territorii: rossiiskii i zarubezhnyi opyt [The main approaches to the classification of rural areas: Russian and foreign experience]. Selskoe, lesnoe i vodnoe khozyaistvo, 11. Retrieved from: http://agro.snauka.ru/2014/11/1658
Isaev, R. A., Podvesovskii, A. G. 2017. Generalized Model of Pulse Process for Dynamic Analysis of Sylov’s Fuzzy Cognitive Maps. CEUR Workshop Proceedings of the Mathematical Modeling Session at the International Conference Information Technology and Nanotechnology (MM-ITNT 2017), 1904: 57-63.
Khasanov, S., Yuldoshev, S. 2001. Metodika otsenki investitsionnogo klimata [Investment Climate Assessment Methodology]. Investitsii v Rossii, 5, 40-46.
Khitskov, I. et al. 2016. Selskaya territoriya — tsentr prityazheniya APK [Rural territory as the gravity center of the agricultural sector]. APK: ekonomika, upravlenie: teoreticheskii i nauchno-prakticheskii zhurnal, 11: 77-84.
Kolodenkova, A. E. 2017. Methods of decision support in the analysis of the feasibility of projects for information and management systems of industrial facilities. Ph.D. Thesis. Ufa State Aviation Technical University.
Kopeliovich, D. I., Podvesovskii, A. G., Safonov, A. L., Vilyukha, A. V., Isaev, R. A. 2018. Application of Fuzzy Cognitive Models in Computer — Aided Production Tooling Design. Herald of Computer and Information Technologies, 3: 20-35.
Kosko, B. 1986. Fuzzy cognitive maps. International Journal of Man-Mashine Studies. 24(1): 65-75.
Krioni, N. K., Kolodenkova, A. E., Korobkin, V. V., Gubanov, N. G. 2016. Intelligent decision-making support system using cognitive modeling for project feasibility assessment on creating complex technical. International Journal of Applied Business and Economic Research, 14(10): 7289–7300.
Kruglov, V. V., Dli, M. I. 2002. Intellectual information systems: computer support of fuzzy logic and fuzzy inference. Moscow. Fizmatlit.
Kulinich, A. A. 2010. Computer systems for modeling cognitive maps: approaches and methods. Problems of Management, 3: 2-16.
Logantsova, N. V. 2013. Metodika tipologizatsii selskikh territorii po urovnyu sotsialno-ekonomicheskoi bezopasnosti [Methodology of typologization of rural territories by the level of socio-economic security]. Ekonomika selskogo khozyaistva Rossii: Nauchno-Proizvodstv. Zhurnal, 9, 63-69.
Maksimov, V. I. 2001. Cognitive technologies – from ignorance to understanding. Cognitive analysis and management of the development of situations (СASC). Proceedings of the 1st International Conference. Moscow. Institute of Control Sciences of the Russian Academy of Sciences, 1: 4–18.
Nechaev, V. 2016. Upravlenie zemelnymi resursami na osnove prognoza razvitiya rynka i ispolzovaniya zemel selskokhozyaistvennogo naznacheniya v Rossiiskoi Federatsii [Land management based on the forecast of market development and use of agricultural land in the Russian Federation]. APK: ekonomika, upravlenie: teoreticheskii i nauchno-prakticheskii zhurnal, 6: 43-53.
Podvesovskii, A. G., Lagerev, D. G., Korostelyov, D. A. 2009. Application of Fuzzy Cognitive Models for Construction of Alternatives Set in Decision Problems. Bulletin of Bryansk State Technical University, 24: 77-84.
Povesovskii, A. G., Lagerev D. G., Korostelev D. A. 2007. SPPR ”IGLA”. Sistema podderzhki prinyatiya reshenii “Intellektualnyi Generator Luchshikh Alternativ”. Bryanskii gosudarstvennyi tekhnicheskii universitet. Zaregistrirovana v OFAP. Svidetelstvo № 50200701348 [The “Intelligent Generator of the Best Alternatives” Decision Support System. Bryansk State Technical University. Registered at the Branch Fund of Algorithms and Programs (OFAP). Certificate No. 50200701348]. Retrieved from: http://iipo.tubryansk.ru/quill/download.html
Roberts, F. 1978. Graph Theory and its applications to problems of society, society for industrial and applied mathematics. Philadelphia: Society for Industrial and Applied Mathematics.
Silov, V. B. 1995. Making strategic decisions in fuzzy environment. Moscow. INPRO-ROS.
Skalnaya, M. 2018. Dokhody selskogo naseleniya kak faktor sotsialnoi ustoichivosti selskikh territorii [The income of the rural population as a factor in the social stability of rural areas]. APK: ekonomika, upravlenie: teoreticheskii i nauchno-prakticheskii zhurnal, 1, 62-71.
Tarasov, A. N., Antonova, N. I. et al. 2016. Tipologizatsiya selskikh territorii na osnove diversifikatsii ekonomiki: monografiya [Typology of rural areas based on economic diversification: a monograph]. Rostov-on-Don: Azov Pechat.
The World Bank (2019b). Retrieved from: http://www.worldbank.org/en/country
The World Bank (2019а). Retrieved from: https://data.worldbank.org/indicator/NV.AGR.TOTL.ZS?view=chart
USDA. (2017). World Agriculture Production. Retrieved from: URL:https://apps.fas.usda.gov/psdonline/circulars/production.pdf
Voronin, A. G. Strategicheskoe planirovanie i upravlenie razvitiem territorii [Strategic planning and territory development management]. Moscow, 2007.
Zinchuk, G. M., Makekadyrova, A. S., Anokhina, M. E. et al. Formirovanie konkurentnogo potentsiala agrarnykh territorii Rossii [Formation of the competitive potential of agrarian territories of Russia. Ministerstvo nauki i vysshego obrazovaniya Rossiiskoi Federatsii. Moscow: 2018.
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spelling Anokhina, Marina2a6f5a6d0e363330f6baf0075aece493Abdrakhmanov, Rakhat20caf83df33b265ff5a51aabe9652157Evgenevna Gridneva, Yelenae67be87afb2d00ca29e5e640456e7ddcArrieta - López, Milton854541a40f8ab7296df9e55a8e2e52edRomanovna Dzhalilova, Nurayed011619bf5ea2165c570dac82ddb4c6Meza - Godoy, Abel597c5429df364c98f543696c32b6a30d2020-04-01T19:38:50Z2020-04-01T19:38:50Z20202345-0282https://hdl.handle.net/11323/6147http://doi.org/10.9770/jesi.2020.7.3(32)Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The purpose of the study is to develop a mechanism for the formation of the competitive potential of the agricultural territories of Kazakhstan as the basis for ensuring the dynamic development of agricultural business in Kazakhstan. The research methodology is based on strategic alternative modeling for agricultural territories competitiveness management with the help of fuzzy cognitive logic. The study used a cognitive approach to decision making in the management of poorly structured systems proposed by V. Silov and actively developed in the works of modern scientists. Fifteen competent experts were invited to select the concepts and build a fuzzy cognitive map of the formation of the competitive potential of the agricultural territories of Kazakhstan. To carry out calculations and justify the content of the strategy, the authors used the software product “Intelligent generation of the best alternatives” (“IGLA”). The result of the study is the developed strategy for the management of agricultural territories competitiveness in Kazakhstan with a set of strategic goals and the best option for managerial impact, ensuring the formation of agricultural export potential of the region. The proposed version of the content of the strategy for managing the competitiveness of the agricultural territories of Kazakhstan can be used either as a system or as its separate elements in managing the development of agricultural business in the country and in developing strategic planning programs for the agro-industrial complex of the region. The novelty of the study in theoretical terms is justified by the approach to the formation of the country's agricultural export potential through ensuring the competitiveness of its agricultural territories. In methodological terms, the novelty of the study is expressed by the use of cognitive modeling technologies to develop a strategy for managing the competitiveness of Kazakhstan's agricultural territories, the implementation of which will allow achieving sustainable dynamics of agricultural production and increase the efficiency of the agricultural economy. The purpose of the study is to develop a mechanism for the formation of the competitive potential of the agricultural territories of Kazakhstan as the basis for ensuring the dynamic development of agricultural business in Kazakhstan. The research methodology is based on strategic alternative modeling for agricultural territories competitiveness management with the help of fuzzy cognitive logic. The study used a cognitive approach to decision making in the management of poorly structured systems proposed by V. Silov and actively developed in the works of modern scientists. Fifteen competent experts were invited to select the concepts and build a fuzzy cognitive map of the formation of the competitive potential of the agricultural territories of Kazakhstan. To carry out calculations and justify the content of the strategy, the authors used the software product “Intelligent generation of the best alternatives” (“IGLA”). The result of the study is the developed strategy for the management of agricultural territories competitiveness in Kazakhstan with a set of strategic goals and the best option for managerial impact, ensuring the formation of agricultural export potential of the region. The proposed version of the content of the strategy for managing the competitiveness of the agricultural territories of Kazakhstan can be used either as a system or as its separate elements in managing the development of agricultural business in the country and in developing strategic planning programs for the agro-industrial complex of the region. The novelty of the study in theoretical terms is justified by the approach to the formation of the country's agricultural export potential through ensuring the competitiveness of its agricultural territories. In methodological terms, the novelty of the study is expressed by the use of cognitive modeling technologies to develop a strategy for managing the competitiveness of Kazakhstan's agricultural territories, the implementation of which will allow achieving sustainable dynamics of agricultural production and increase the efficiency of the agricultural economyengEntrepreneurship and Sustainability IssuesCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Agro-industrial complexKazakhstanAgricultural territoriesCompetitive potentialCognitive modelingFuzzy cognitive mapsStatic and dynamic analysisStrategic alternativesCompetitiveness management strategyFormation of the competitive potential of the agricultural territoriesArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionAndersen, E. 2017. The farming system component of European agricultural landscapes. European Journal of Agronomy, 82: 282-291.Atkin, R.H., Casti, J. 1977. Polyhedral dynamics and the geometry of systems, IIASA Research Report. IIASA, Laxenburg, Austria: RR77-006.Avdeeva, Z.K., Kovriga, S.V., and Makarenko, D.I. 2007. Cognitive modeling for solving problems in the management of weakly structured systems (situations). Management of Large Systems, 16: 26–39.Axelrod, R. 1976. The Structure of Decision: Cognitive Maps of Political Elites. Princeton, NJ: Prinston University Press.Bautin, V. M., Kozlov, V. V., Merzlov, A. V. 2004. Ustoichivoe razvitie selskikh territorii: voprosy strategii i taktiki [Sustainable rural development: issues of strategy and tactics]. Moscow: FGNU ”Rosinformagrotekh”.Bondarenko, L. 2015. Regionalnaya politika gosudarstvennoi podderzhki selskikh territorii [Regional policy of state support for rural areas]. APK: ekonomika, upravlenie: teoreticheskii i nauchno-prakticheskii zhurnal, 3: 71-82.Borisov, V. V., Kruglov, V. V., Fedulov, A. S. 2007. Fuzzy models and networks. Moscow. Hot line — Telecom.Casti, J. 1982. Connectivity, complexity, and catastrophe in large-scale systems. Moscow. Mir publishing house.D’Amico, M., Coppola, A., Chinnici, G., di Vita, G., Pappalardo G. 2013. Agricultural systems in the European Union: an analysis of regional differences. New Medit, 12(4): 28-34.Duff, A., Padilla A. 2015. Latin America: agricultural perspectives. Retrieved from: https://economics.rabobank.com/publications/2015/september/latin%2Damerica%2Dagricultural%2Dperspectives/Erokhin, D. V., Lagerev, D. G., Laricheva, E. A., Podvesovskii, A. G. 2010. Strategic management of innovative activity of the enterprise. Bryansk. BSTU.Gorelov, V. I., Karelova, O. L., Ledashcheva, T. N. 2012. System modeling in socio-economic sphere. Moscow. Logos.Guiomar, N., Godinho, S., Pinto-Correia, T., Almeida, M., Bartolini, F., Bezák, P., Biró, M., Bjørkhaug, H., Bojnec, Š., Brunori, G. et al. 2018. Typology and distribution of small farms in Europe: Towards a better picture. Land Use Policy, 75: 784-798.Guth, M., & Smędzik-Ambroży, K. 2019. Economic resources versus the efficiency of different types of agricultural production in regions of the European Union. Economic Research-Ekonomska Istraživanja. https://doi.org/10.1080/1331677X.2019.1585270Ikonnikova, O. V. 2014. Osnovnye podkhody k klassifikatsii selskikh territorii: rossiiskii i zarubezhnyi opyt [The main approaches to the classification of rural areas: Russian and foreign experience]. Selskoe, lesnoe i vodnoe khozyaistvo, 11. Retrieved from: http://agro.snauka.ru/2014/11/1658Isaev, R. A., Podvesovskii, A. G. 2017. Generalized Model of Pulse Process for Dynamic Analysis of Sylov’s Fuzzy Cognitive Maps. CEUR Workshop Proceedings of the Mathematical Modeling Session at the International Conference Information Technology and Nanotechnology (MM-ITNT 2017), 1904: 57-63.Khasanov, S., Yuldoshev, S. 2001. Metodika otsenki investitsionnogo klimata [Investment Climate Assessment Methodology]. Investitsii v Rossii, 5, 40-46.Khitskov, I. et al. 2016. Selskaya territoriya — tsentr prityazheniya APK [Rural territory as the gravity center of the agricultural sector]. APK: ekonomika, upravlenie: teoreticheskii i nauchno-prakticheskii zhurnal, 11: 77-84.Kolodenkova, A. E. 2017. Methods of decision support in the analysis of the feasibility of projects for information and management systems of industrial facilities. Ph.D. Thesis. Ufa State Aviation Technical University.Kopeliovich, D. I., Podvesovskii, A. G., Safonov, A. L., Vilyukha, A. V., Isaev, R. A. 2018. Application of Fuzzy Cognitive Models in Computer — Aided Production Tooling Design. Herald of Computer and Information Technologies, 3: 20-35.Kosko, B. 1986. Fuzzy cognitive maps. International Journal of Man-Mashine Studies. 24(1): 65-75.Krioni, N. K., Kolodenkova, A. E., Korobkin, V. V., Gubanov, N. G. 2016. Intelligent decision-making support system using cognitive modeling for project feasibility assessment on creating complex technical. International Journal of Applied Business and Economic Research, 14(10): 7289–7300.Kruglov, V. V., Dli, M. I. 2002. Intellectual information systems: computer support of fuzzy logic and fuzzy inference. Moscow. Fizmatlit.Kulinich, A. A. 2010. Computer systems for modeling cognitive maps: approaches and methods. Problems of Management, 3: 2-16.Logantsova, N. V. 2013. Metodika tipologizatsii selskikh territorii po urovnyu sotsialno-ekonomicheskoi bezopasnosti [Methodology of typologization of rural territories by the level of socio-economic security]. Ekonomika selskogo khozyaistva Rossii: Nauchno-Proizvodstv. 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