Formation of Integrated Territorial Structures of Domestic Tourism
DOI:
https://doi.org/10.17059/ekon.reg.2023-4-14Keywords:
integrated territorial structure, types of integration, management options, integrated tourism product, territorial integration, functional and management integrationAbstract
In the context of intensified sanctions against the Russian Federation, it is important to improve domestic tourism, utilise diverse tourism potential, and develop tourist areas by forming integrated tourism structures (ITS) to overcome municipal (regional) administrative barriers. The study presents theoretical and methodological aspects of the formation of integrated tourism structures affecting Russian tourism under economic transformation. A systems approach based on structural and functional analysis, content analysis, as well as sociological research methods were applied. Conditions for the integration of tourist space include the possibility of integrating tourist and recreational resources, relative positioning of tourist destinations, complementarity of services, shared transport systems, and similar climatic conditions. Tourism integration can be divided into horizontal, vertical, and diagonal. The study demonstrated the advantages of diagonal integration, which implies the creation of a governing body coordinating the activities of tourism enterprises and the hospitality industry. An integrated tourism structure can be formed by combining tourist areas of the Sochi city district and Tuapsinsky district in Krasnodar Krai. The article proposed to establish ITS Council, composed of heads of settlements in these districts, representatives of tourism enterprises (associations) and the hospitality industry, and leaders of national diasporas. Further, the Council’s tasks were defined. Establishment of an integrated territorial structure can be economically effective, resulting in an increase in the provision of additional and complementary services to tourists. Diagonal integration contributes to the formation of an integrated tourism product by combining complementary tourism products, reducing dependence on seasonal factors, creating new jobs, and increasing regional gross tourism product. The obtained results can be used by public authorities in the field of tourism when creating regional spatial development concepts.
References
Afanasyeva, T. V., & Yarushkina, N. G. (2009). Nechetkoe modelirovanie vremennykh ryadov i analiz nechetkikh tendentsiy [Fuzzy time series modeling and fuzzy trend analysis]. Ulyanovsk: UlGTU, 229. (In Russ.)
Andreeva, A. Yu. (2019). Novye tekhnologii intensivnogo razvitiya turisticheskoy industrii [New technologies for the intensive development of the tourism industry]. M.: YURGU, 15. (In Russ.)
Ashugatoyan, S. G. (2016). Evolution of views on the tourism spatial organization. Vestnik Udmurtskogo universiteta. Ser. Biologiya. Nauki o Zemle [Bulletin of Udmurt University. Series Biology. Earth Sciences], 26 (3), 127-134. (In Russ.)
Benur, A., & Bramwell, B. (2015). Tourism product development and product diversification in destinations. Tourism Management, 50, 213–224. https://doi.org/10.1016/j.tourman.2015.02.005
Bilozubenko, V., Yatchuk, O., Wolanin, E., Serediuk, T., & Korneyev, M. (2020). Comparison of the digital economy development parameters in the EU countries in the context of bridging the digital divide. Problems and Perspectives in Management, 18 (2), 206-218. http://dx.doi.org/10.21511/ppm.18(2).2020.18
Bocci, L., D’Urso, P., & Vitale, V. (2021). Clustering of the Italian Regions Based on Their Equitable and Sustainable Well-Being Indicators: A Three-Way Approach. Social Indicators Research, 155, 995-1043. https://doi.org/10.1007/s11205-020-02582-7
Brauksa, I. (2013). Use of Cluster Analysis in Exploring Economic Indicator Differences among Regions: The Case of Latvia. Journal of Economics, Business and Management, 1 (1), 42-45. https://doi.org/10.7763/joebm.2013.v1.10
Bukhvald, E. M., & Kolchugina, A. V. (2019). The spatial development strategy and national security priorities of the Russian Federation. Ekonomika regiona [Economy of region], 15 (3), 631-643. https://doi.org/10.17059/2019-3-1 (In Russ.)
Cheng, Z. (2014). Regional Economic Indicators Analysis Based on Data Mining. 2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications, 1, 726-730. https://doi.org/10.1109/isdea.2014.165
Dzhandzhugazova, E. A. (2021). Turistsko-rekreatsionnoe proektirovanie: uchebnoe posobie dlya vuzov, 3-e izd., ispr. i dop. [Tourist and recreational design: a textbook for universities. 3rd ed., revised and expanded]. Moscow: Publishing House Yurit, 257. (In Russ.)
Fahad, A., Alshatri, N., Tari, Z., Alamri, A., Khalil, I., Zomaya, A. Y., … Bouras, A. (2014). A survey of clustering algorithms for big data: Taxonomy and empirical analysis. IEEE Transactions, Emerging Topics in Computing, 2 (3), 267-279. https://dx.doi.org/10.1109/TETC.2014.2330519
Golobic, M., & Marot, N. (2011). Territorial impact assessment: Integrating territorial aspects in sectoral policies. Evaluation and Program Planning, 34 (3), 163-173. https://doi.org/10.1016/j.evalprogplan.2011.02.009
Gorbatiuk, K., Mantalyuk, О., Proskurovych, О., & Valkov, О. (2019). Analysis of regional development disparities in Ukraine with fuzzy clustering technique. SHS Web of Conferences. The 8th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2019), 65, 194-210. https://doi.org/10.1051/shsconf/20196504008
Grishina, I. V. (2020). Forecasting of capital investments into the fixed capital in regions until 2024: methods and results of territorial forecast for Russia. Regionalnaya ekonomika. Yug Rossii [Regional economy. The south of Russia], 8 (1), 49-62. https://doi.org/10.15688/re.volsu.2020.1.5 (In Russ.)
Hibbard, K. A., & Janetos, A. (2013). The regional nature of global challenges: a need and strategy for integrated regional modeling. Climatic Change, 118 (3), 565-577. http://dx.doi.org/10.1007/s10584-012-0674-3
Kanungo, T., Mount, D. M., Netanyahu, N. S., Piatko, C., Silverman, R., & Wu, A. Y. (2002). An Efficient k-means clustering algorithm: analysis and implementation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24 (7), 881-892. http://dx.doi.org/10.1109/TPAMI.2002.1017616
Kużelewska, U. (2014). Clustering Algorithms in Hybrid Recommender System on MovieLens Data. Studies in logic, grammar and rhetoric, 37 (1), 125-139. http://dx.doi.org/10.2478/slgr-2014-0021
Lappo, G. M., Polyan, P. M, & Selivanova, T. V. (2007). Agglomerations of Russia in the XXI century. Vestnik Fonda regionalnogo razvitiya Irkutskoy oblasti [Bulletin of the Regional Development Fund of the Irkutsk Region], 1, 45-52. (In Russ.)
Levchenko, K. K. (2021). Razvitie vezdnogo turizma i ego vliyanie na ekonomiku territorii [Development of inbound tourism and its impact on the territory’s economy]. M.: RUSINES, 116. (In Russ.)
Mazhar, L. Yu. (2014). Tourism over a distance and time: the geographer’s view. Sovremennye problemy servisa i turizma [Service and Tourism: Current Challenges], 1, 16-23. (In Russ.)
Nizhegorodtsev, R. M., Piskun, E. I., & Kudrevich, V. V. (2017). The Forecasting of Regional Social and Economic Development. Ekonomika regiona [Economy of Region], 13 (1), 38-48. https://doi.org/10.17059/2017-1-4 (In Russ.)
Nyikos, G., & Kondor, Z. (2020). New Mechanisms for Integrated Territorial Development in Hungary. Pro Publico Bono–Public Administration, 8 (1), 124-145. http://dx.doi.org/10.32575/ppb.2020.1.7
Pertzik, E. N. (2009). Large urban agglomerations: development, design problems. In: Problemy razvitiya aglomeratsiy Rossii [Problems of the development of agglomerations of Russia] (pp. 34-46). M.: Krassand. (In Russ.)
Piskun, E. I., & Khokhlov, V. V. (2019). Economic development of the Russian Federation’s regions: factor-cluster analysis. Ekonomika regiona [Economy of region], 15 (2), 363-376. DOI: https://doi.org/10.17059/2019-2-5 (In Russ.)
Polyan, P. M. (2014). Territorialnye struktury — urbanizatsiya — rasselenie: teoreticheskie podkhody i metody izucheniya [Territorial structure — urbanization — resettlement: theoretical approaches and methods of study]. M.: New Chronograph, 788. (In Russ.)
Preobrazhensky, V. S. (1975). Teoreticheskie osnovy rekreatsionnoy geografii [Theoretical foundations of recreational geography]. M.: Nauka, 224. (In Russ.)
Purnomo, A., Susanti, T., Rosyidah, E., Firdausi, N., & Idhom, M. (2022). Digital economy research: Thirty-five years insights of retrospective review. Procedia Computer Science, 197, 68-75. https://doi.org/10.1016/j.procs.2021.12.119
Stimson, R., Baum, S., & O’Connor, K. (2003). The Social and Economic Performance of Australia’s Large Regional Cities and Towns: Implications for Rural and Regional policy. Australian Geographical Studies, 41 (2), 131-147.
Tkachenko, A. A. (2015). Territorialnaya obshchnost v regionalnom razvitii i upravlenii [Territorial community in regional development and management]. Tver: Publishing House of Tver State University, 155. (In Russ.)
Walz, A., Lardelli, C., Behrendt, H., Grêt-Regamey, A., Lundström, C., Kytzia, S., & Bebi, P. (2007). Participatory scenario analysis for integrated regional modelling. Landscape and urban Planning, 81 (1-2), 114-131. http://dx.doi.org/10.1016/j.landurbplan.2006.11.001
Zhang, T., Ramakrishnan, R., & Livny, M. (1996). BIRCH: An Efficient Data Clustering Method for Very Large Databases. ACM SIGMOD Record, 25 (2), 103-114. https://doi.org/10.1145/235968.233324
Тindergen, J., & Bos, H. C. (1967). Mathematical models of economic growth [Matematicheskie modeli ekonomicheskogo rosta]. Trans. M.: Progress, 121. (In Russ.)
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Чуваткин Петр Петрович , Левченко Константин Константинович
This work is licensed under a Creative Commons Attribution 4.0 International License.
