Program for Regional Conflict Prevention when Using Natural Resources
DOI:
https://doi.org/10.17059/2020-2-23Keywords:
conflicts in mining regions, interests of the population, priority projects, shared funding, program, compensation projects, optimization model, an optimality criterion, rating scale, sequencing of the projects, project fundingAbstract
The extraction of natural resources in the mining regions causes environmental pollution, changes the landscape, and reduces biodiversity, and leads to conflicts between the local population and the mining enterprises. The paper aims to design a methodological tool for eliminating social tensions in the mining regions during field development and exploitation. The goal can be achieved by creating compensation projects that take into account the priorities assessed by the stakeholders: the population, the regional authorities and the mining enterprise. As the compensation projects strive to solve social and environmental problems in the mining regions, they include the direct financial compensation to the population, development of traditional enterprisers, reduction of environmental pollution, infrastructure development, etc. We focused on two logically connected tasks: 1) assessing the significance of compensation projects and funding by the regional budget and the mining enterprise; 2) determining the sequencing of the considered projects. For solving the first task, we proposed a method of the multi-criteria significance assessment of program projects from the perspective of the population, the regional authorities and the mining enterprise, based on a specific unified rating scale. This method uses a technique that cuts off options with low interest in the projects. Thus, it allows assessing the significance of the program projects, as well as calculating the shares of funding by the mining enterprise and the regional budget. For solving the second task, we applied the economic and mathematical model and the heuristic method, determining which projects should be implemented first. The experimental calculations showed that the developed compensation programs comply with the preferences of the stakeholders. The application of the developed approach can contribute to the balanced socio-economic development of the mining regions in conditions of intensive field development and exploitation.References
Kuleshov, V. V. (Ed.). (2017). Resursnye regiony Rossii v «novoy realnosti» [Resource regions of Russia in “new reality”]. Novosibirsk: Institute of Economics and Industrial Engineering, SB RAS, 308. (In Russ.)
Tolstolesova, L. A. (2010). Finansovo-investitsionnye resursy razvitiya territoriy syrevoy spetsializatsii [Financial and investment resources in development of territories with raw material specialization]. Problemy sovremennoy ekonomiki [Problems of modern economics], 4(36), 189–193. (In Russ.)
Eder, L. V., Sablin, K. S. & Provornaya, I. V. (2017). Nauchnye podkhody k obosnovaniyu prioritetnykh innovatsionno-tekhnologicheskikh napravleniy prostranstvennoy spetsializatsii resursnykh regionov Rossii [Scientific approaches to the rationale of priority innovation-technological directions of spatial specialization of resource regions of Russia]. Fundamentalnye issledovaniya [Fundamnetal research], 5, 220–224. Retrieved from: http://fundamental-research. ru/ru/article/view?id=41538 (Date of access: 15.03.2019). (In Russ.)
Kirchmeer, L. V. (2019). Monitoring ekologo-sotsialno-ekonomicheskogo razvitiya dobyvayushchego regiona [Monitoring of ecological and socio-economic development of the extracting region]. Azimut nauchnykh issledovaniy: ekonomika i upravlenie [Azimuth of Scientific Researches: Economics and Management], 8(1(26)), 173–175. DOI: 10.26140/ anie-2019–0801–0036.
Tulupov, A. S. (2017). Vozmeshchenie ekologicheskogo vreda v ekonomike gornogo proizvodstva [Compensation for environmental damage in the economy of mining]. Gornyy zhurnal [Mining Journal], 8, 61–65. DOI: 10.17580/ gzh.2017.08.11. (In Russ.)
Valeeva, E. I. & Moskvochenko, D. V. (2016). Regionalnyy analiz antropogennoy transformatsii landshaftov Khanty-Mansiyskogo avtonomnogo okruga [Regional analysis of anthropogenic transformation of landscapes of the Khanty-Mansiysk Autonomous Okrug]. Retrieved from: http://bva.wmsite.ru/problemy-vzaimodejstvija/vypusk2/valeeva (Date of access: 17.03.2019). (In Russ.)
Acharya, S., Morichi, S. & Yoshida, T. (1999). Role of infrastructure investment in regional growth and dynamic simulation approach. Journal of the Eastern Asia Society for Transportation Studies, 3(2), 39–54. Retrieved from: http://www. easts.info/on-line/journal/vol3no4/34004.pdf (Date of access: 02.03.2019)].
Novoselov, A. L., Novoselova, I. Yu. & Zheltenkov, A. V. (2016). Kompensatsionnyy mekhanizm povysheniya effe- ktivnosti regionalnogo razvitiya [Compensation mechanism for increasing regional development efficiency]. Vestnik Moskovskogo gosudarstvennogo oblastnogo universiteta. Seriya: Ekonomika [Bulletin of the Moscow Region State University. Series: Economics], 3, 84–93. (In Russ.)
Barbier, E. B. (2005). Natural Resources and Economic Development. Cambridge University Press, 410.
Barbier, E. B. (2003). The Role of Natural Resources in Economic Development. Australian Economic Papers, 42, 253–272. DOI: 10.1111/1467–8454.00198
Kuklin, A. A. & Korobkov, I. V. (2018). Vybor effektivnoy traektorii sotsialno-ekonomicheskogo razvitiya regiona [Selection of an Effective Trajectory of Regional Socio-Economic Development]. Ekonomika regiona [Economy of region], 14(4), 1145–1155. DOI: https://doi.org/10.17059/2018–4–7 (In Russ.)
Kuklin, A. A., Pecherkina, M. S., Tyrsin, A. N. & Surina, A. A. (2017). Metodicheskiy instrumentariy diagnostiki riskov dlya blagosostoyaniya lichnosti i territorii prozhivaniya [Methodological Tools for Detection of Risks to the Welfare of the Individuals and the Territory of Residence]. Ekonomika regiona [Economy of Region], 13(4), 1030–1043. DOI: 10.17059/2017–4–5 (In Russ.)
Chepurnykh, N. V., Novoselov, A. L. & Glubokiy, A. I. (1997). Okhrana okruzhayushchey prirodnoy sredy v Samarskoy oblasti. Programmnyy aspekt [Environmental protection in the Samara region: a programmatic aspect]. Moscow: Nauka, 203. (In Russ.)
Bordley, R., Tibiletti, L. & Uberti, M. (2015). A Target-Oriented Approach: A “One-Size” Model to Suit Humans and Econs Behaviors. Applied Mathematical Sciences, 9(100), 4971–4978. DOI: http://dx.doi.org/10.12988/ams.2015.55401
Kirichuk, S. & Eremenko, L. (2012). Programmno-tselevoy metod kak instrument formirovaniya mestnykh byudzhetov [Target-Oriented Approach as a Tool for the Formation of Local Budgets under Current Conditions]. Ekonomicheskaya politika [Economic Policy], 6, 165–170. (In Russ.)
Yandyganov, Ya. Ya., Vlasova, E. Ya. & Vedernikova, E. N. (2010). Tselevye ekologicheskie programmy. Metody. Praktika [Target environmental programs. Methods. Practice]. Ekaterinburg: AMB, 466. (In Russ.)
Braginskiy, O. B., Tatevosyan, G. M., Sedova, S. V., Pisareva, O. M. & Kunitsyna, N. N. (2013) Metodologiya obosnovaniya investitsionnykh programm i ikh optimizatsii pri ogranichennykh finansovykh resursakh. Na primere khimicheskogo kompleksa [Methodology of Investment Programs’ Studying and Its Optimization in Bounded Financial Resources (the Example of Chemical Industry)]. Moscow: CEMI RAS, 81. (In Russ.)
Utyakova, G. Sh. & Biryukova, V. V. (2016). Formirovanie investitsionnoy programmy razvitiya vertikalno-integrirovannoy neftyanoy kompanii [The forming of investment program progress of the vertically integrated oil company]. Internet-zhurnal «Naukovedenie» [“Naukovedenie”], 8(6). Retrieved from: http://naukovedenie.ru/PDF/148EVN616. pdf (Date of access: 26.03.2016). (In Russ.)
Kochkarov, R. A. (2007). Tselevye programmy. Instrumentalnaya podderzhka [Target programs: instrumental support]. Moscow: Economics, 223. (In Russ.)
Novoselov, A. L., Medvedeva, O. E. & Novoselova, I. Yu (2016). Ekonomika, organizatsiya i upravlenie v oblasti nedropolzovaniya [Economics, organization and management in the field of subsoil use. Textbook and case study]. Moscow: Urait, 645. (In Russ.)
Gavade, R. K. (2014). Multi-Criteria Decision Making: An overview of different selection problems and methods. International Journal of Computer Science and Information Technologies, 5(4), 5643–5646
Pomerol, Ch. & Barba-Romero S. (2000). Multicriterion Decision in Management: Principles and Practice. Boston: Kluwer Academic Publishers, 295.
Van Delft, A. & Nijkamp, P. (1977). Multi-criteria analysis and regional decision-making. Vol. 8. Springer Science & Business Media, 140.
Ekel, P. Y., Martini, J. S. C. & Palhares, R. M. (2008). Multicriteria analysis in decision making under information uncertainty. Applied Mathematics and Computation, 200(2), 501–516. DOI: 10.1016/j.amc.2007.11.024.
Peng, K.-H. & Tzeng, G.-H. (2013). A hybrid dynamic MADM model for problem-improvement in economics and business. Technological and Economic Development of Economy, 19(4), 638–660. DOI: 10.3846/20294913.2013.837114.
Leung, Y. (1985) Basic issues of fuzzy set theoretic spatial analysis. Papers of the Regional Science Association, 58(1),
35–46.
Liou, J. J. H., & Tzeng, G.-H. (2012). Comments on “Multiple criteria decision making (MCDM) methods in economics: an overview”. Technological and Economic Development of Economy, 18(4), 672–695. DOI: 10.3846/20294913.2012.753489.
Novoselov, A., Potravny, I., Novoselova, I. & Gassiy, V. (2017). Selection of priority investment projects for the development of the Russian Arctic. Polar Science, 14, 68–77. DOI: 10.1016/j.polar.2017.10.003.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2020 I. Yu. Novoselova, A.A. Avramenko, R.A. Aliev
This work is licensed under a Creative Commons Attribution 4.0 International License.
