The Tourist and Recreational Potential of Cross-Border Regions of Russia and Kazakhstan during the COVID-19 Pandemic: Estimation of the Current State and Possible Risks
Abstract
:1. Introduction
2. Literature Review
- -
- Forms a necessary part of the process of achieving sustainable development goals in the EU Cross-Border Cooperation (CBC) model;
- -
- Contributes to the implementation of sustainable development goals to a greater extent than national tourism programs, which should be considered in the development of a destination;
- -
- Requires integrated management because cross-border regions have a more complex structure;
- -
- Has the ability to implement joint marketing strategies to increase tourist flow;
- -
- Primarily performs the integrative function of cultural tourism;
- -
- Includes unique types of tourism, such as smuggling tourism;
- -
- Has different degrees of tourist flow penetration into internal territories;
- -
- Should be ready to reorient activities to the domestic market in situations of significant reduction in tourist flow from abroad;
- -
- Has faster recovery time in the post-pandemic era than other tourism sectors.
3. Materials and Methods
- -
- Cluster 1—Natural Factors (11): average temperature in January, °C; average temperature in July, °C; average annual precipitation, mm; period of seasonal snow cover, days; absolute elevation of terrain relief, m; number of lakes (large, more than 100 sq. km), units; number of rivers (large, over 500 km), units; number of protected areas, units; number of protected plant species, units; number of protected animal species, units; number of natural monuments (of republican significance), units.
- -
- Cluster 2—Cultural and Historical Factors (11): number of historical and cultural monuments (of republican significance), units; number of archaeological monuments (of republican significance), units; number of monuments of urban planning and architecture (of republican significance), units; number of museums, units; number of theaters, units; number of zoos (including petting zoos), units; number of concert organizations, units; number of circuses, units; number of libraries, units; number of movie theaters, units (including those with 2–7 screens); number of entertainment and recreational parks, units.
- -
- Cluster 3—Social and Economic Factors (4): consumer product retail chains, quantity; number of trade markets, units; density of railway tracks, km per 1000 sq. km; length of public hard-surfaced motor roads, km.
- -
- Cluster 4—Infrastructure Support of Tourism (10): number of exercise and sports facilities (including number of ski resorts, rowing clubs, sports arenas, etc.), units; number of primary wellness tourism facilities (sanatorium-and-spa resorts, specialized medical centers, etc.), units; number of five-star hotels, units; number of four-star hotels, units; number of three-star hotels, units; number of accommodations without category, as well as one- and two-star hotels, units; hotel room capacity, units; number of airports, units; number of tourism firms and tour operators, units; headcount of workers in the tourism sector, in thousands.
4. Results
- -
- The risks for the tourism industry during the pandemic were collective and depended on compliance with safety recommendations by residents and visitors of certain regions.
- -
- Risks of economic losses in tourism arose regardless of the severity of quarantine restrictions. With strong isolation of the area due to a drop in the tourist flow, there was a threat of tourist organization closures, job losses, a reduction or complete loss of income, and a decrease in tax receipts. With weak isolation of the region, there was risk of infection for the local population and a risk of income decline for the economy. It is necessary to find a balance between safety requirements during a pandemic and the risk of economic losses. Under these conditions, the support of federal, republican, and regional authorities to organizations of the industries affected by COVID-19 is crucial.
- -
- The authorities should consider the impact of the pandemic not only in light of the risk to the economy but also in light of the risk to the social and environmental spheres. The pandemic has shown that the authorities must be ready not only to respond quickly to the need to ensure the safety of tourists and local residents but also to mitigate the risks in the social and environmental spheres.
- -
- The behavior of tourists and the generation of tourist flow are influenced not only by actual risks but also by potential exposure to risks when visiting a certain region. The perception of risk can negatively affect an area’s image and make it difficult to realize the tourist potential of the region. In this situation, the importance of informing tourists about safety measures to minimize the risk of visiting the region increases.
- -
- The pandemic has increased the number of tourism-associated risks and has shown a need for each person (tourists and personnel of travel companies) to comply with safety requirements (social distancing, use of disinfectants, use of masks, etc.). Before the pandemic, safety in tourism had been provided mainly by organizations of the tourism industry and tourist infrastructure. During the pandemic, travel safety became a problem not only for the tourism industry but also for every tourist and the authorities of the region. However, some destinations and types of tourism (ecological, rural tourism, etc.), as well as remote tourist areas, have experienced increased demand due to the opportunity to leave large cities with an increased risk of COVID-19 infection.
- The existing restrictions regarding the use of Visa and MasterCard payment systems will make it difficult to pay for services related to accommodations, food, housing, and transport; it should also be noted that when planning tourist trips, residents of the Republic of Kazakhstan may face a shortage of rubles in second-tier banks and be unable to use Visa or MasterCard, which may lead to reduced consumption of tourist products, as well as to changes in the timing of travel due to the need to search for convenient payment methods. This situation should improve once credit cards become valid in RF territory (for example, the Mir system).
- The inability to book hotels via the Booking.com online platform creates limitations and difficulties in the planning process and the generation of optimal tourist products. It also increases the amount of time that potential tourists spend searching for suitable facilities and accommodations.
- Changes in natural and climatic conditions may have an adverse impact on average annual precipitation, the period of seasonal snow cover, and the time period that determines snowmelt, which in turn can lead to intensive flooding of natural tourist areas during spring floods, for example.
- The shallowing and overgrowth of small lakes (medium and large) that have not been taken into account in the TRP assessment can lead to a reduction in tourist flows in beach tourism development within certain areas. These trends have been observed in a mild form at Sabandykol Lake in Bayanaul State National Natural Park of the Pavlodar Region, North Kazakhstan; at the Sol-Iletsky Lakes in the Orenburg Region; and at Yarovoye Lake in Altai Territory.
- The weathering of rocks in the areas of tourist destinations, which can lead to destruction of places of interest.
- The destruction and deterioration of tourism infrastructure and noncompliance with international standards.
- A low flow capacity in tourist areas, which can potentially lead to over-tourism in the case of an “influx” of incoming tourists, especially during a peak season. Such a situation has been observed for the last five years in Bayanaul National Natural Park and Alakol Lake, located on the Balkhash-Alakol Lowland (on the border of the Almaty and East Kazakhstan regions), and in the territories of Biryuzovaya Katun SEZ in Altai Territory.
- Existing restrictions due to the COVID-19 pandemic, including mandatory PCR tests when crossing the border (by air transport), masking, registration in the COVID-19 Free Travel Program, and participation in state programs for scanning QR codes for admission to restaurants and entertainment facilities. It should be noted that due to improvements in the epidemiological situation, on 11 March 2022, the Kazakhstan Interdepartmental Commission on Preventing the Spread of Coronavirus Infection decided to cancel mandatory masking outdoors, as well as the use of the Ashyq mobile application (only for regions located in the ‘yellow’ and ‘green’ zones).
5. Discussion
- Conventionally, the major risks associated with tourism are economic. The consequences of the pandemic, however, have shown that health risks are also a problem, and have pointed out the need to ensure increased safety for tourists and the local population in order to preserve lives and health. However, there are still no data in the statistical indicators that allow assessment of the impact of the risk of COVID-19 on the development of tourism in cross-border territories. This is due to a lack of data on the movement of tourists after they cross the border, and the lack of a selective study of the purposes for visiting the country. The most accurate information on the movement of tourists is currently provided by mobile operators, but such information is expensive and not available to individual researchers. The solution to the problem of tracking the movement of tourists could be, for example, the use of a “tourist passport”. In this document, the tourist could receive marks at certain destinations, which would allow him to receive discounts and/or souvenirs. A tourist passport has been implemented in a number of destinations and routes in Russia.
- Restrictions on tourist flows have led not only to economic consequences (a decrease in revenue, investments, and tourism wages) but also to a reinterpretation of the role individual entities play in the generation of tourist flows. Long-term pandemic restrictions have required state support, primarily financial and tax support, to prevent the bankruptcy of tourism enterprises. As part of another study we conducted, we looked at the impact of digital solutions on tourism support by state authorities. This study showed that the efficiency of tourism recovery in the border regions of the Russian Federation and Kazakhstan depends on the completeness and relevance of state information support measures. It should be noted that state support measures (at the federal and regional levels) did not appear immediately. The tourism industry was left to fend for itself with a catastrophic decline in tourist traffic due to border closures during the first few months of the pandemic. In our opinion, it is necessary to foresee possible scenarios for supporting tourism in advance, taking into account the consequences of the COVID-19 pandemic.
- Significant growth in industry digitalization is another consequence of the pandemic. There are no indicators in the official statistics of either country that reflect the level of digital technology application in tourism. Nevertheless, this factor has a significant impact on the possibility of realizing the region’s tourist potential. This trend has led to a reduction in the revenue of tour operators and travel agents, but allowed tourist service providers to maintain their level of revenue and reduce the drop in tourist flow in the regions. The pandemic has shown that, despite restrictions, the demand for travel has continued. A rapidly changing situation with the introduction of restrictive measures and the COVID-19 infection rate has led to reduced booking depth when buying tourist products, and the growing popularity of last-minute tours. Under these conditions, official information on pandemic restrictions has come into sharp focus.A pent-up demand has been primarily satisfied in areas where coronavirus restrictions were first lifted (even partially). The example of the tourist flow volume in Turkey after a number of restrictions had been lifted shows the significance of coordination between state authorities, tourism industry organizations, and tourism infrastructure to reduce risks and ensure a safe holiday for tourists. However, these measures should be global or at least coordinated by the authorities of the countries and/or regions with the greatest mutual tourist flows, since the removal of exit restrictions may be offset by remaining entry restrictions. The use of digital technologies in the context of limited social contact has made it possible to rebuild the mechanisms of interaction between tourism organizations and customers. In the context of the removal of coronavirus restrictions, the vast majority of travel agencies used digital technologies as intensively as they had done during the pandemic. It can be said that COVID-19 elicited an active interest in digital services, even among organizations that were not planning to digitize.
- More than thirty years since the breakup of the USSR and the transformation of the regions in question into border regions, a number of them have taken advantage of their cross-border position in terms of tourism development. The results of the research clearly show that not all regions have been able to realize their potential to the same extent. Reduced transportation costs when visiting neighboring regions (including those in another country) ceased to be a competitive advantage during the pandemic. The popularity of a particular tourist destination during the pandemic has fueled the safety concerns of a number of tourists and increased the risk of a refusal to travel.
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
Indicator | Astrakhan Region | Volgograd Region | Saratov Region | Samara Region (Borders Only at One Point) | Orenburg Region | Chelyabinsk Region | Kurgan Region | Tyumen Region with ADs (Autonomous Districts) | Omsk Region | Novosibirsk Region | Altai Territory | Republic of Altai |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Average temperature in January, °C | −3.6 | −5.9 | −7.5 | −13.8 | −11.7 | −14.6 | −18 | −15 | −16.8 | −18.9 | −16.1 | −13.7 |
Average temperature in July, °C | 25.6 | 24.6 | 22.6 | 20.7 | 23.2 | 19.6 | 19 | 19 | 19.6 | 19.1 | 19.9 | 18.9 |
Average annual precipitation, mm | 222 | 450 | 550 | 372 | 380 | 529 | 400 | 480 | 400 | 464 | 448 | 731 |
Period of seasonal snow cover, days | First snow cover in the first half of December, which can melt several times during the winter. Its depth is shallow—only about 4–10 cm. | 100 | 100 | 138 | 145 | 160 | 155 | 145 | 185 | 160 | 180 | 200 |
Absolute elevation of the terrain relief, m | 161.9 | 358.6 | 370 | 381.2 | 667.6 | 1406 | 210 | 1895 | 150.4 | 502 | 2490 | 4506 |
Number of lakes (large, more than 100 sq. km), units | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 2 | 4 | 2 | 1 |
Number of rivers (large, more than 500 km), units | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 12 | 2 | 4 | 4 | 0 |
Number of SPNRs (Specially Protected Natural Reservations), units | 56 | 58 | 92 | 215 | 336 | 155 | 123 | 139 | 27 | 82 | 121 | 58 |
Number of protected plant species, units | 143 | 46 | 306 | 286 | 183 | 230 | 208 | 173 | 188 | 179 | 212 | 180 |
Number of protected animal species, units | 187 | 143 | 253 | 272 | 138 | 182 | 156 | 142 | 197 | 157 | 146 | 135 |
Number of natural monuments (of republican significance)/in RF, SPNRs, units | 3 | 5 | 2 | 4 | 3 | 4 | 0 | 9 | 1 | 2 | 5 | 4 |
Number of historical and cultural monuments (of republican (federal) significance), units. | 44 | 66 | 61 | 110 | 37 | 18 | 19 | 53 | 10 | 10 | 34 | 0 |
Number of archaeological monuments (of republican (federal) significance), units | 98 | 1227 | 98 | 25 | 1287 | 292 | 708 | 1094 | 1202 | 639 | 2263 | 117 |
Number of monuments of urban planning and architecture (of republican (federal) significance), units | Since 2013, the list has not been maintained in the Russian Federation; they are included in the category of Cultural Heritage Sites | |||||||||||
Number of museums, units | 19 | 40 | 27 | 38 | 32 | 46 | 23 | 18 | 40 | 39 | 69 | 7 |
Number of theaters, units | 4 | 11 | 11 | 16 | 7 | 16 | 3 | 4 | 10 | 10 | 7 | 1 |
Number of zoos (including petting zoos), units. | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 |
Number of concert organizations, units | 4 | 7 | 2 | 5 | 1 | 4 | 1 | 1 | 6 | 5 | 6 | 3 |
Number of circuses, units | 2 | 1 | 2 | 1 | 1 | 2 | 0 | 1 | 1 | 1 | 0 | 0 |
Number of libraries, units | 238 | 599 | 920 | 735 | 897 | 819 | 514 | 468 | 773 | 860 | 960 | 157 |
Number of movie theaters, units (including those with 2–7 screens)/in RF, number of movie installations (unit, the indicator value for the year) | 8 | 71 | 0 | 29 | 106 | 64 | 65 | 7 | 90 | 82 | 111 | 0 |
Number of entertainment and recreation parks, units/in RF, of culture and recreation | 0 | 6 | 1 | 2 | 0 | 10 | 0 | 0 | 3 | 11 | 5 | 0 |
Consumer product retail chains, quantity | 9828 | 26,847 | 27,300 | 37,581 | 23,050 | 35,545 | 13,037 | 39,800 | 17,956 | 28,475 | 31,075 | 3365 |
Number of trade markets, units | 8 | 37 | 28 | 16 | 15 | 16 | 3 | 16 | 13 | 10 | 20 | 2 |
Density of railway tracks, km per 1000 sq. km | 128 | 143 | 228 | 256 | 117 | 203 | 104 | 17 | 53 | 85 | 86 | 0 |
Length of public hard-surfaced motor roads, km | 4078 | 16,653.4 | 17,259.9 | 17,959.8 | 20,664.6 | 21,370.1 | 9601.7 | 23,280.6 | 14,109.3 | 20,579.9 | 35,343.7 | 4604.5 |
Number of physical exercise and sports facilities (including number of ski resorts, rowing clubs, sports arenas, etc.), units | 1312 | 3928 | 3177 | 4181 | 3908 | 5516 | 2165 | 5896 | 3997 | 3565 | 4690 | 325 |
Number of primary wellness tourism facilities—sanatorium-and-spa resorts, specialized medical centers, etc./in RF, number of sanatorium-resort organizations | 3 | 23 | 23 | 39 | 27 | 43 | 19 | 30 | 16 | 34 | 38 | 2 |
Number of five-star hotels, units | 3 | 3 | 0 | 3 | 2 | 2 | 0 | 0 | 0 | 0 | 1 | 2 |
Number of four-star hotels, units | 6 | 12 | 9 | 18 | 5 | 21 | 4 | 16 | 5 | 19 | 10 | 5 |
Number of three-star hotels, units | 11 | 35 | 38 | 67 | 26 | 31 | 4 | 66 | 16 | 19 | 21 | 10 |
Number of accommodations w/o category, as well as one- and two-star hotels, units | 10 | 18 | 16 | 35 | 13 | 19 | 7 | 46 | 12 | 20 | 25 | 7 |
Hotel room capacity, units/in RF, number of rooms in collective accommodation facilities | 6841 | 10,922 | 8955 | 18,400 | 6905 | 18,964 | 2987 | 18,051 | 7053 | 12,817 | 12,886 | 4278 |
Number of airports, units/in RF, international only | 1 | 1 | 1 | 1 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 0 |
Number of tourism companies and tour operators, units. | 115 | 165 | 169 | 327 | 118 | 348 | 60 | 474 | 182 | 307 | 171 | 28 |
Headcount of workers in tourism sector, in thousands | 0.937 | 0.418 | 0.349 | 0.845 | 0.234 | 0.856 | 0.128 | 0.803 | 0.489 | 0.939 | 0.371 | 0.094 |
Headcount of workers in collective accommodation facilities in RF regions, in thousands | 3.175 | 4.24 | 4.718 | 9.166 | 4.375 | 8.517 | 2.791 | 10.618 | 4.242 | 6.476 | 8.71 | 1.257 |
- Great Russian Encyclopedia [Electronic resource]. URL: https://bigenc.ru/ (accessed on 21 January 2022).
- Federal list of tourist sites [Electronic resource]. URL: https://xn----7sba3acabbldhv3chawrl5bzn.xn--p1ai/ (accessed on 22 December 2021).
- Federal State Statistics Service [Electronic resource]. URL: https://rosstat.gov.ru/compendium/document/13295 (accessed on 22 January 2022).
- Unified interdepartmental information and statistical system [Electronic resource]. URL: https://www.fedstat.ru/indicator/55126 (accessed on 22 January 2022).
- Federal Air Transport Agency of Russia [Electronic resource]. URL: https://favt.gov.ru/dejatelnost-ajeroporty-i-ajerodromy-mezhdunarodnye-ajeroporty/ (accessed on 18 January 2022).
- Regions of Russia. Socio-economic indicators. 2021: P32 statistical collection/Rosstat.-M., 2021, 1112p.
- Voronin, V.V. Geography of the Samara Region/V.V. Voronin, V. A. Gavrilenkova; Voronin V. V., Gavrilenkova V. A.; State educational institution of additional professional education (advanced training) of specialists Samara Regional Institute for Advanced Studies and Retraining of Educational Workers.—Samara: GOU SIPKRO, 2008, 265p. ISBN 978-5-7174-0408-2.
- Geography of the economy of the Saratov region/I.A. Ilchenko, L.V. Makartseva, Yu.V. Preobrazhensky, O.A. Tsoberg.—Saratov: IC “Science”, 2018, 99p. ISBN 978-5-9999-3083-5.
- Nature of the Novosibirsk region: electronic textbook/T.A. Gorelova, N.V. Gulyaeva, V.M. Kravtsov, Yu.V. Kravtsov; Federal Agency for Education, Novosibirsk State Pedagogical University, Institute of Natural and Social and Economic Sciences, Department of Physical Geography.—Novosibirsk: Novosibirsk State Pedagogical University, 2010, 160 p.
- Ivanishcheva, N.A. Geography of the Orenburg region: textbook/N.A. Ivanishcheva, I.Yu. Filimonova, Zh.T. Sivokhip.—Orenburg: LLC “Agency” Press”, 2020, 121p.
Appendix B
Factor and Sub-Parameters | Atyrau Region | West Kazakhstan Region | Aktobe Region | Kostanay Region | North Kazakhstan Region | Pavlodar Region | East Kazakhstan Region | AVI | |
---|---|---|---|---|---|---|---|---|---|
NF (Natural Factors) | Average temperature in January, °C | −8 (−11) | −14 | −20.8 | (−13.8)–(−16.1) | (−12.8)–(−17.4) | (−14.9)–(−17.0) | (−16)–(−20) | - |
Average temperature in July, °C | +24 (+25) | +25 | +23.7 | 20.0–23.6 | 20.3–21.9 | 19.1–20.6 | 16–23 | - | |
Average annual precipitation, mm | 100–200 | 325 | 213–250 | 388 | 349 | 454 | 477 | - | |
Period of seasonal snow cover, days | 70–90 | 86–142 | 89–161 | 105–160 | 129–154 | 150–165 | 142 | - | |
Absolute elevation of the terrain relief, m | (−27.16)–223 Av.: 125 | 100–657 Av.: 378 | 100–200–657 Av.: 379 | 250–320 | 100–200 | 115–200 | 500–600; 2800–3600 | - | |
Number of lakes (large, more than 100 sq. km), units | 1 | 1 | 1 | 3 | 2 | 5 | 3 | 1.4 | |
Number of rivers (large, more than 500 km), units | 4 | 1 | 6 | 2 | 3 | 1 | 1 | 1.2 | |
Number of SPNRs (Specially Protected Natural Reservations), units | 3 | 3 | 2 | 5 | 16 | 5 | 12 | 7 | |
Number of protected plant species, units | 16 | 36 | 61 | 1112 | 831 | 58 | 4322 | 1873 | |
Number of protected animal species, units | 30 | 20 | 32 | 783 | 312 | 90 | 1662 | 606 | |
Number of natural monuments (of republican significance), units | 3 | 3 | 2 | - | 1 | 12 | 1 | 2 | |
CHF (Cultural and Historical Factors) | Number of historical and cultural monuments (of republican (federal) significance), units | 4 | 5 | 9 | 5 | 3 | 7 | 16 | 14 |
Number of archaeological monuments (of republican (federal) significance), units | - | 1 | - | - | - | 1 | 2 | 3 | |
Number of monuments of urban planning and architecture (of republican (federal) significance), units | 2 | 4 | 6 | 5 | 3 | 6 | 14 | 10 | |
Number of museums, units | 17 | 9 | 19 | 10 | 13 | 11 | 17 | 15 | |
Number of theaters, units | 1 | 2 | 2 | 4 | 3 | 3 | 2 | 4 | |
Number of zoos (including petting zoos), units | - | - | 3 | - | - | 1 | 1 | 0.5 | |
Number of concert organizations, units | 2 | 3 | 1 | 1 | 1 | 1 | 2 | 2 | |
Number of circuses, units | - | - | - | - | - | - | - | 0.25 | |
Number of libraries, units | 144 | 366 | 237 | 344 | 321 | 230 | 306 | 231 | |
Number of movie theaters, units (including those with 2–7 screens) | 2 | 7 | 2 | 5 | 3 | 4 | 6 | 6 | |
Number of entertainment and recreation parks, units | 2 | 5 | 7 | 9 | 6 | 4 | 11 | 9 | |
SEF (Social and Economic Factors) | Consumer product retail chains, quantity | 2786 | 4688 | 5644 | 9988 | 6054 | 8889 | 12,696 | 7115 |
Number of trade markets, units | 22 | 20 | 59 | 43 | 30 | 24 | 71 | 45 | |
Density of railway tracks, km per 1000 sq. km | 6.26 | 2.11 | 6.08 | 6.49 | 6.31 | 6.32 | 4.27 | 5.89 | |
Length of public hard-surfaced motor roads, km | 2322.3 | 4676.2 | 5530.5 | 6763.9 | 6981 | 4919 | 10,352.9 | 5559.2 | |
IST (Infrastructure Support of Tourism) | Number of physical exercise and sports facilities (including number of ski resorts, rowing clubs, sports arenas, etc.), units | 1128 | 1699 | 1831 | 2562 | 2891 | 3083 | 3245 | 2432 |
Number of primary wellness tourism facilities—sanatorium-and-spa resorts, specialized medical centers, etc. | 5 | 3 | 4 | 5 | 3 | 5 | 10 | 9 | |
Number of five-star hotels, units | 3 | - | - | - | - | - | 1 | 1 | |
Number of four-star hotels, units | 5 | 1 | 1 | 4 | 1 | - | 1 | 4 | |
Number of three-star hotels, units | 6 | 1 | 3 | 3 | - | - | 5 | 3 | |
Number of accommodations w/o category, as well as one- and two-star hotels, units | 74 | 38 | 56 | 101 | 50 | 65 | 172 | 108 | |
Hotel room capacity, units | 3216 | 1751 | 2010 | 2287 | 1824 | 3090 | 10,919 | 4285 | |
Number of airports, units | 2 | 1 | 1 | 1 | 1 | 1 | 4 | 1 | |
Number of tourist companies and tour operators, units | 25 | 40 | 31 | 34 | 22 | 41 | 30 | 79 | |
Headcount of workers in the tourism sector, in thousands | 4.5 | 6.4 | 4.7 | 5 | 3.1 | 6 | 8.7 | 6.5 |
- stat.gov.kz
- Agroclimatic Resources of the West Kazakhstan Region: scient. and appl. ref./Institute of Geography LLP, Astana, 2017, 128p;
- Agroclimatic Resources of the Actable Region: scient. and appl. ref./Institute of Geography LLP, Astana, 2017, 136p;
- Agroclimatic Resources of the Kostanay Region: scient. and appl. ref./Institute of Geography LLP, Astana, 2017, 139p;
- Agroclimatic Resources of the Pavlodar Region: scient. and appl. ref./Institute of Geography LLP, Astana, 2017, 127p;
- Agroclimatic Resources of the North Kazakhstan Region: scient. and appl. ref./Institute of Geography LLP, Astana, 2017, 125p;
- Hydrology.—Astana: The official Internet resource of Kazhydromet RSE of the Ministry of Energy of the Republic of Kazakhstan. [Electronic Source]. URL: https://kazhydromet.kz/ru (accessed on 31 January 2022);
- The Law of the Republic of Kazakhstan “On Protection and Use of Historical and Cultural Heritage Sites” No. 1488-XII dated 2 July 1992 (as amended and supplemented as of 24.05.2018)//Paragraph Information system [Electronic source].—E-data—[Astana, 2018];
- Tourism of Kazakhstan. 2016–2020: Stat. ref./Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. Bureau of National Statistics, Nur-Sultan, 2021, 101p;
- Culture in the Republic of Kazakhstan. 2016–2020: Stat. ref./Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. Bureau of National Statistics, Nur-Sultan, 2021, 130p;
- Retail and Wholesale Trade in the Republic of Kazakhstan. 2016–2020: Stat. ref./Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. Bureau of National Statistics, Nur-Sultan, 2021, 279p;
- Transport in the Republic of Kazakhstan. 2016–2020: Stat. ref./Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. Bureau of National Statistics, Nur-Sultan, 2021, 119p.
References
- Aletdinova, Anna, and Maxim Bakaev. 2019. Intelligent Data Analysis and Predictive Models for Regional Labor Markets. In Digital Transformation and Global Society. Communications in Computer and Information Science. Edited by Daniel A. Alexandrov, Alexander V. Boukhanovsky, Andrei V. Chugunov, Yury Kabanov, Olessia Koltsova and Ilya Musabirov. Cham: Springer International Publishing, vol. 1038, pp. 351–63. [Google Scholar] [CrossRef]
- Arbulú, Italo, Maria Razumova, Javier Rey-Maquieira, and Francesc Sastre. 2021. Measuring Risks and Vulnerability of Tourism to the COVID-19 Crisis in the Context of Extreme Uncertainty: The Case of the Balearic Islands. Tourism Management Perspectives 39: 100857. [Google Scholar] [CrossRef] [PubMed]
- Boldyrev, Yury, Sergey Chernogorskiy, Konstantin Shvetsov, Anatoly Zherelo, and Konstantin Kostin. 2019. A Mathematical Model of Regional Socio-Economic Development of the Russian Arctic Zone. Resources 8: 45. [Google Scholar] [CrossRef]
- Borovkov, Aleksey I., Marina V. Bolsunovskaya, Aleksei M. Gintciak, and Tatiana Ju Kudryavtseva. 2020. Simulation Modelling Application for Balancing Epidemic and Economic Crisis in the Region. International Journal of Technology 11: 1579. [Google Scholar] [CrossRef]
- Chan, Chung-Shing. 2021. Developing a Conceptual Model for the Post-COVID-19 Pandemic Changing Tourism Risk Perception. International Journal of Environmental Research and Public Health 18: 9824. [Google Scholar] [CrossRef] [PubMed]
- Cheng, Yun, Sha Fang, and Jie Yin. 2022. The Effects of Community Safety Support on COVID-19 Event Strength Perception, Risk Perception, and Health Tourism Intention: The Moderating Role of Risk Communication. Managerial and Decision Economics 43: 496–509. [Google Scholar] [CrossRef] [PubMed]
- Chernogorskiy, Sergey, Konstantin Shvetsov, and Vladimir Parkhomenko. 2018. Two Prediction Models for Some Economic Indicators of the Russian Arctic Zone. In Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016. Lecture Notes in Networks and Systems. Edited by Yaxin Bi, Supriya Kapoor and Rahul Bhatia. Cham: Springer International Publishing, vol. 15, pp. 358–67. [Google Scholar] [CrossRef]
- Chica, Manuel, Juan M. Hernández, and Jacques Bulchand-Gidumal. 2021. A Collective Risk Dilemma for Tourism Restrictions under the COVID-19 Context. Scientific Reports 11: 5043. [Google Scholar] [CrossRef]
- Dimopoulos, Dimitri, Dorothy Queiros, and Cina Van Zyl. 2021. Perspectives on the Impact of External Risks on the Future of Dive Tourism at a High Latitude Reef Complex in the Indian Ocean Region. Journal of the Indian Ocean Region 17: 178–204. [Google Scholar] [CrossRef]
- Dirin, D., E. P. Krupochkin, and E. Golyadkina. 2014. Methods of integrated assessment of the tourist and recreational potential of the region. Geography and Nature Management of Siberia 18: 64–78. [Google Scholar]
- Godovykh, Maksim, Abraham Pizam, and Frida Bahja. 2021. Antecedents and Outcomes of Health Risk Perceptions in Tourism, Following the COVID-19 Pandemic. Tourism Review 76: 737–48. [Google Scholar] [CrossRef]
- Grech, Victor, Peter Grech, and Stephanie Fabri. 2020. A Risk Balancing Act—Tourism Competition Using Health Leverage in the COVID-19 Era. International Journal of Risk & Safety in Medicine 31: 121–30. [Google Scholar] [CrossRef]
- Im, Jongho, Jewoo Kim, and Joon Yeon Choeh. 2021. COVID-19, Social Distancing, and Risk-Averse Actions of Hospitality and Tourism Consumers: A Case of South Korea. Journal of Destination Marketing & Management 20: 100566. [Google Scholar] [CrossRef]
- Istiak, Khandokar. 2021. Risk, Uncertainty and the Tourism Sector of North Africa. African Development Review 33: 329–42. [Google Scholar] [CrossRef]
- Ivanova, Marina, Tatiana Yakovleva, and Tamara Selenteva. 2020. The Models of Information Asymmetry in the Context of Digitization of Government. In Proceedings of the International Scientific Conference—Digital Transformation on Manufacturing, Infrastructure and Service. Saint Petersburg: ACM, pp. 1–6. [Google Scholar] [CrossRef]
- Joo, Dongoh, Wenjie Xu, Juhee Lee, Choong-Ki Lee, and Kyle Maurice Woosnam. 2021. ‘Residents’ Perceived Risk, Emotional Solidarity, and Support for Tourism amidst the COVID-19 Pandemic. Journal of Destination Marketing & Management 19: 100553. [Google Scholar] [CrossRef]
- Łapko, Aleksandra, Ewa Hącia, Roma Strulak-Wójcikiewicz, Kevser Çınar, Enrico Panai, and Lovorko Lučić. 2021. Eco-Friendly Tourism Decision Making During COVID-19—Sailing Tourism Example. Sustainability 14: 134. [Google Scholar] [CrossRef]
- Lee, Chien-Chiang, Godwin Olasehinde-Williams, and Seyi Saint Akadiri. 2021a. Geopolitical Risk and Tourism: Evidence from Dynamic Heterogeneous Panel Models. International Journal of Tourism Research 23: 26–38. [Google Scholar] [CrossRef]
- Leukhina, Maya, Tatyana Kudryavtseva, and Anton Tikhomirov. 2020. Analysis of Factors of Cross-Border Cooperation in Order to Increase the Competitiveness of Small and Medium-Sized Enterprises in Saint-Petersburg. In Proceedings of the 2nd International Scientific Conference on Innovations in Digital Economy: SPBPU IDE-2020. Saint Petersburg: ACM, pp. 1–9. [Google Scholar] [CrossRef]
- Mamraeva, Dinara Gabitovna, and Larissa Tashenova. 2020. Methodological Tools for Assessing the Region’s Tourist and Recreation Potentia. Economy of Region 16: 127–40. [Google Scholar] [CrossRef]
- Matiza, Tafadzwa, and Elmarie Slabbert. 2022. Tourism Reset: Reimagining South African Domestic Tourism in the Era of Covid-19. Tourism Review International 26: 103–20. [Google Scholar] [CrossRef]
- Nikolova, Liudmila Vasilevna, Dmitriy Grigorievich Rodionov, and Natalya Vladimirovna Afanasyeva. 2017. Impact of Globalization on Innovation Project Risks Estimation. European Research Studies Journal 20: 396–410. [Google Scholar]
- Park, Jinah, Serene Tse, Sherry D. B. Mi, and Haiyan Song. 2022. A Model for Cross-Border Tourism Governance in the Greater Bay Area. Journal of China Tourism Research, 1–25. [Google Scholar] [CrossRef]
- Pérez-Rodríguez, Jorge V., and María Santana-Gallego. 2020. Modelling Tourism Receipts and Associated Risks, Using Long-Range Dependence Models. Tourism Economics 26: 70–96. [Google Scholar] [CrossRef]
- Rather, Raouf Ahmad. 2021. Monitoring the Impacts of Tourism-Based Social Media, Risk Perception and Fear on Tourist’s Attitude and Revisiting Behaviour in the Wake of COVID-19 Pandemic. Current Issues in Tourism 24: 3275–83. [Google Scholar] [CrossRef]
- Rodionov, Dmitry, Liudmila Nikolova, Natalia Abramchikova, Maria Velikova, and Kalubi Rawlings Jerry Mazuba. 2020. Development of the Analysis Model of Innovative Projects Efficiency Management in the Context of Digitalization. In Proceedings of the 2nd International Scientific Conference on Innovations in Digital Economy: SPBPU IDE-2020. Saint Petersburg: ACM, pp. 1–7. [Google Scholar] [CrossRef]
- Rodionov, Dmitriy G., Evgenii A. Konnikov, and Magomedgusen N. Nasrutdinov. 2021. A Transformation of the Approach to Evaluating a Region’s Investment Attractiveness as a Consequence of the COVID-19 Pandemic. Economies 9: 59. [Google Scholar] [CrossRef]
- Rudyanto, Rudyanto, Rudy Pramono, and Juliana Juliana. 2021. Perception of Knowledge of the Risk of the COVID-19 Pandemic Regarding Touring Intentions and Tourism Travel Recommendations. Journal of Environmental Management and Tourism 12: 929. [Google Scholar] [CrossRef]
- Ruiz-Sancho, Salvador, Maria José Viñals, Lola Teruel, and Marival Segarra. 2021. Security and Safety as a Key Factor for Smart Tourism Destinations: New Management Challenges in Relation to Health Risks. In Culture and Tourism in a Smart, Globalized, and Sustainable World. Springer Proceedings in Business and Economics. Edited by Vicky Katsoni and Ciná van Zyl. Cham: Springer International Publishing, pp. 511–22. [Google Scholar] [CrossRef]
- Sánchez-Cañizares, Sandra M., L. Javier Cabeza-Ramírez, Guzmán Muñoz-Fernández, and Fernando J. Fuentes-García. 2021. Impact of the Perceived Risk from Covid-19 on Intention to Travel. Current Issues in Tourism 24: 970–84. [Google Scholar] [CrossRef]
- Shahzad, Syed Jawad Hussain, Thi Hong Van Hoang, and Elie Bouri. 2022. From Pandemic to Systemic Risk: Contagion in the U.S. Tourism Sector. Current Issues in Tourism 25: 34–40. [Google Scholar] [CrossRef]
- Shneider, Alexandra, Tatiana Kudryavtseva, and Igor Dukeov. 2020. Cross-Border Cooperation as a Factor in Increasing the Efficiency of Small and Medium-Sized Enterprises of St. Petersburg. In Proceedings of the International Scientific Conference—Digital Transformation on Manufacturing, Infrastructure and Service. Saint Petersburg: ACM, pp. 1–7. [Google Scholar] [CrossRef]
- Sikarwar, Ekta. 2021. Time-Varying Foreign Currency Risk of World Tourism Industry: Effects of COVID-19. Current Issues in Tourism 24: 887–91. [Google Scholar] [CrossRef]
- Škare, Marinko, Domingo Riberio Soriano, and Małgorzata Porada-Rochoń. 2021. Impact of COVID-19 on the Travel and Tourism Industry. Technological Forecasting and Social Change 163: 120469. [Google Scholar] [CrossRef] [PubMed]
- Tanina, Anna, Evgeny Konyshev, and Kamilya Tsahaeva. 2020. Agritourism Development Model in Digital Economy. In Proceedings of the 2nd International Scientific Conference on Innovations in Digital Economy: SPBPU IDE-2020. Saint Petersburg: ACM, pp. 1–6. [Google Scholar] [CrossRef]
- Teeroovengadum, Viraiyan, Boopen Seetanah, Eric Bindah, Arshad Pooloo, and Isven Veerasawmy. 2021. Minimising Perceived Travel Risk in the Aftermath of the COVID-19 Pandemic to Boost Travel and Tourism. Tourism Review 76: 910–28. [Google Scholar] [CrossRef]
- Toroptsev, E. L., A. S. Marahovskiy, and A. V. Babkin. 2019. Complex Modeling of the Economic Systems Stability. IOP Conference Series: Earth and Environmental Science 272: 32175. [Google Scholar] [CrossRef]
- Tseng, Kuan-Chieh, Hsiao-Hsien Lin, Jan-Wei Lin, I-Shen Chen, and Chin-Hsien Hsu. 2021. Under the COVID-19 Environment, Will Tourism Decision Making, Environmental Risks, and Epidemic Prevention Attitudes Affect the People’s Firm Belief in Participating in Leisure Tourism Activities? International Journal of Environmental Research and Public Health 18: 7539. [Google Scholar] [CrossRef]
- Vidishcheva, Evgeniya, Yuriy Dreizis, Andrey Kopyrin, and Marina Gunare. 2020. Identifying the Risks Impacting on the Sustainable Development of a Tourism Area. Edited by W. Strielkowski, E. Animitsa and E. Dvoryadkina. E3S Web of Conferences 208: 5018. [Google Scholar] [CrossRef]
- Villacé-Molinero, Teresa, Juan José Fernández-Muñoz, Alicia Orea-Giner, and Laura Fuentes-Moraleda. 2021. Understanding the New Post-COVID-19 Risk Scenario: Outlooks and Challenges for a New Era of Tourism. Tourism Management 86: 104324. [Google Scholar] [CrossRef]
- Volodin, Aleksandr, Maxim Ivanov, Mikhail Djanelidze, and Aleksandr Sokolitsyn. 2019. An Analytical Model of Economic Inequality in the Russian Regions and Its Correlation with the Global Trend in the Digital Economy. In SPBPU IDE ’19: Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy. New York: Association for Computing Machinery, pp. 1–4. [Google Scholar] [CrossRef]
- Wang, Xin, Ivan Ka Wai Lai, Quan Zhou, and Yu He Pang. 2021. Regional Travel as an Alternative Form of Tourism During the COVID-19 Pandemic: Impacts of a Low-Risk Perception and Perceived Benefits. International Journal of Environmental Research and Public Health 18: 9422. [Google Scholar] [CrossRef]
- Woosnam, Kyle Maurice, Zachary Russell, Manuel Alector Ribeiro, Tara J. Denley, Camila Rojas, Erin Hadjidakis, Joseph Barr, and Jackson Mower. 2021. ‘Residents’ Pro-Tourism Behaviour in a Time of COVID-19. Journal of Sustainable Tourism 30: 1858–77. [Google Scholar] [CrossRef]
- Wu, Chien-Hung. 2021. A Study on the Current Impact on Island Tourism Development under COVID-19 Epidemic Environment and Infection Risk: A Case Study of Penghu. Sustainability 13: 10711. [Google Scholar] [CrossRef]
- Xu, Linlin, Li Cong, Geoffrey Wall, and Hu Yu. 2021. Risk Perceptions and Behavioral Intentions of Wildlife Tourists During the COVID-19 Pandemic in China. Journal of Ecotourism, 1–20. [Google Scholar] [CrossRef]
- Zhu, Hui, and Fumin Deng. 2020. How to Influence Rural Tourism Intention by Risk Knowledge During COVID-19 Containment in China: Mediating Role of Risk Perception and Attitude. International Journal of Environmental Research and Public Health 17: 3514. [Google Scholar] [CrossRef] [PubMed]
Indicator Name | Scores | Weight Coefficient ** | |||
---|---|---|---|---|---|
0 | 1 | 2 | |||
NF (Natural Factors) | Average temperature in January, °C | 0–(−8) and (−25) | (−19)–(−14) | (−9)–(−18) | 0.06 |
Average temperature in July, °C | 11–15 | 16–19 | 20–25 | 0.06 | |
Average annual precipitation, mm | 600–800 | 400–600 | 300–400 | 0.05 | |
Period of seasonal snow cover, days | 0–140 | 140–160 | More than 160 | 0.07 | |
Absolute elevation of the terrain relief, m | 0–500 | 500–1000 | More than 1000 | 0.12 | |
Number of lakes (large, more than 100 sq. km), units | No | 1.3≤ | More than 1.3 | 0.12 | |
Number of rivers (large, more than 500 km), units | No | 1.2≤ | More than 1.2 | 0.12 | |
Number of SPNRs (Specially Protected Natural Reservations), units | No | 1.4≤ | More than 1.4 | 0.13 | |
Number of protected plant species, units | No | 1.0≤ | More than 1.0 | 0.06 | |
Number of protected animal species, units | No | 1.4≤ | More than 1.4 | 0.08 | |
Number of natural monuments) (of republican significance), units | No | 1.4≤ | More than 1.4 | 0.14 | |
CHF (Cultural and Historical Factors) | Number of historical and cultural monuments (of republican (federal) significance), units | No | 2.0≤ | More than 2.0 | 0.13 |
Number of archaeological monuments (of republican (federal) significance), units | No | 2.0≤ | More than 2.0 | 0.13 | |
Number of monuments of urban planning and architecture (of republican (federal) significance), units | No | 1.5≤ | More than 1.5 | 0.12 | |
Number of museums, units | No | 1.8≤ | More than 1.8 | 0.12 | |
Number of theaters, units | No | 1.7≤ | More than 1.7 | 0.08 | |
Number of zoos (including petting zoos), units | No | 1.5≤ | More than 1.5 | 0.08 | |
Number of concert organizations, units | No | 1.4≤ | More than 1.4 | 0.06 | |
Number of circuses, units | No | 1.4≤ | More than 1.4 | 0.08 | |
Number of libraries, units | No | 1.0≤ | More than 1.0 | 0.03 | |
Number of movie theaters, units (including those with 2–7 screens) | No | 1.2≤ | More than 1.2 | 0.05 | |
Number of entertainment and recreation parks, units | No | 1.8≤ | More than 1.8 | 0.12 | |
SEF (Social and Economic Factors) | Consumer product retail chains, quantity | No | 1.2≤ | More than 1.2 | 0.17 |
Number of trade markets, units | No | 1.1≤ | More than 1.1 | 0.16 | |
Density of railway tracks, km per 1000 sq. km | No | 1.6≤ | More than 1.6 | 0.33 | |
Length of public hard-surfaced motor roads, km | No | 1.7≤ | More than 1.7 | 0.34 | |
IST (Infrastructure Support of Tourism) | Number of physical culture and sports facilities (including: number of ski resorts, rowing clubs, sports arenas, etc.), units | No | 2.0≤ | More than 2.0 | 0.13 |
Number of primary wellness tourism facilities—sanatorium-and-spa resorts, specialized medical centers, etc. | No | 1.9≤ | More than 1.9 | 0.13 | |
Number of 5-star hotels, units | No | 1.1≤ | More than 1.1 | 0.09 | |
Number of 4-star hotels, units | No | 1.1≤ | More than 1.1 | 0.08 | |
Number of 3-star hotels, units | No | 1.6≤ | More than 1.6 | 0.12 | |
Number of accommodations w/o category, as well as 1- and 2-star hotels, units | No | 1.4≤ | More than 1.4 | 0.09 | |
Hotel room capacity, units | No | 1.8≤ | More than 1.8 | 0.09 | |
Number of airports, units | No | 1.8≤ | More than 1.8 | 0.11 | |
Number of tourist companies and tour operators, units | No | 1.7≤ | More than 1.7 | 0.09 | |
Headcount of workers in the tourism sector, in thousands | No | 1.6≤ | More than 1.6 | 0.06 |
Region | Brief Description |
---|---|
Astrakhan Region | This is a region with an ancient history, the center of many events reflected in the chronicles of Russia. The land is distinguished by its rich natural diversity, unique ethnic makeup, and cultural potential accumulated over centuries. The region’s main city—Astrakhan—proudly bears the titles of Caspian Capital, Keeper of Living History, and Precious Pearl of the Lower Volga Region. |
Volgograd Region | This is a land of natural beauty and national traditions. It is the homeland of Ataman Ermak Timofeevich, the conqueror of Siberia, and the popular rebels Stepan Razin and Kondraty Bulavin. It is a cradle of victory in the Great Patriotic War that preserves the memory of the fallen heroes in a mass grave on Mamayev Hill (Mamayev Kurgan). This is an area of archaeological monuments, including an ancient human encampment, Sarmatian villages, Savromat burial grounds, and Golden Horde cities. |
Saratov Region | This region is the place of the first landing by cosmonaut Yuri Gagarin. Here, in a moderate continental steppe climate on the banks of the Volga River, Saratov has been standing for more than 400 years. Once a major merchant center in the country, today it is a city of a dozen museums. In the cultural capital of the Volga Region, one can see a unique collection of paintings, including canvases by Aivazovsky and Petrov-Vodkin, or a collection of samovars. Outside the regional capital is the House with a Lion—a unique open-air museum of ancient house paintings and thermal pools. |
Samara Region | This region is located in the middle reaches of the Volga River. The regional capital boasts the longest river embankment in Russia and the tallest railway station building in Europe. Samara is also famous for producing the most popular beer in the country. The surrounding landscapes and the local way of life have inspired many famous Russian artists. One of the most picturesque and mystical places of the Samara region is the river bend, Samarskaya Luka. Here, one can see beavers, wild boar, elk, and foxes. |
Orenburg Region | This region is located in the very south of Russia, near the border with Kazakhstan. Its outline on the map resembles a flying dragon. The Orenburg region is a land of endless steppes. Here, one can experience a true winter and legendary Russian frost, but travelers will not freeze in these lands: the Orenburg down shawl, a traditional souvenir of the region, will protect them from the cold. |
Chelyabinsk Region | The locals like saying that the Chelyabinsk region is caressed by both subterranean and celestial deities. The famous Ural gems are mined in this region: underground treasures surrounded by fairy tales with which the entire population of the country is brought up. Most recently, in the capital of the region, hundreds of city cameras recorded the fall of a meteorite, which can now be seen in a museum. In addition to gems, there are modern ski resorts and national parks in the mountains of the Southern Urals. |
Kurgan Region | This region is called the gateway of Siberia. The Baikal Federal Highway passes through its territory, as does the Trans-Siberian Railway. People come here for walking and educational, cycling, equestrian, automobile, snowmobile, and ski tourism. The Kurgan territory boasts more than a thousand sites included in the list of cultural and historical heritage of the RF. |
Tyumen Region | This region is located in the southwestern part of the West Siberian Plain. It is where explorers started discovering new territories in the 16th century and where many travelers start getting acquainted with Siberia today. The only stone Kremlin in Siberia is located in Tobolsk. The region’s wooden architectural monuments are diverse—here, one can see the Baroque embodied in wood. Additional artifacts in the region include dinosaur skeletons and ancient human encampments. |
Omsk Region | There are more than twenty hunting reserves in the territory of the Omsk region; this is a real paradise for fans of hunting and fishing. Devotees of history will be interested in ancient encampments and settlements, burial mounds, and iconic monuments. Historical sites include Chudskaya Gora, Batakovo Tract, and the mysterious energy village of Okunevo, with its system of five lakes, one of which is fictional. |
Novosibirsk Region | The third largest city in Russia, Novosibirsk, is not a tourist center; as a rule, people come here on business. Nevertheless, the city, just like the region, has something to show its guests: the largest zoo in Russia, the scientific center of Akademgorodok (science campus), and a large number of museums and theaters. Ski resorts, Zveroboy Rocks, Barsukov Cave, Karachi Lake, nature reserves, and pine forests are great places for sports, walks, nature observations, and picking mushrooms and berries. |
The Republic of Altai | This is a land of mountains, the highest ridges in Siberia, separated by deep river valleys. It is also a land of unique natural areas, many of which are UNESCO World Heritage sites. The magnificent landscapes of the Altai peaks, with many beautiful mountain lakes and glaciers, attract travelers, scientists, climbers, writers, poets, artists, and photographers. |
Altai Territory | Here all travelers will find something to their taste: ancient encampments and caves for archaeologists, Altai cheese and Altai honey for gourmands, the Yarovoye Lake and the Belokurikha resort for fans of retreat. For those looking for communion with nature, there are cozy campsites surrounded by snow-capped mountains, ancient pine trees, and clean taiga air. |
Region | Brief Description |
---|---|
West Kazakhstan Region | This region was established on 10 March 1932. It is located in the northwestern part of the country and shares borders with five regions of the Russian Federation (Orenburg, Astrakhan, Volgograd, Saratov, and Samara). Flat terrain prevails throughout the area. The highest point is Ichka Mountain. There are approximately 200 rivers in the West Kazakhstan region, the three largest being the Ural, the Derkul, and the Chagan. In addition, there are 144 lakes in the region. Chalkar and Rybny Sacryl are among the largest. Cultural, educational, and religious tourism, and tourism for children and young people, are well-developed in the region. |
Aktobe Region | This region is located in the western part of the republic and was also established on 10 March 1932. All the rivers flowing through its territory belong to the Caspian Sea basin; the largest of them are the Emba, Or, Ilek, Irgiz, and Turgay. There are more than 150 lakes in the area. One of the most famous tourist sites is the Abat-Baytak sculptural monument dating back to the beginning of the 13th century. Scientists believe that it was erected during the emergence of the Golden Horde. No less famous are the Koblandy Batyr Mausoleum and the Museum of Local Lore. Cultural, educational, medical, geological, ecological, and event tourism are actively developed in the region. |
Kostanay Region | This region, located in the north of the republic, was established in 1936 (the territory consists of 196,000 sq km with a population of 879,100). The region has relatively flat terrain. The northern part consists of the southeastern edge of the West Siberian Lowland, and to the south of it is the Turgai Plateau. In the west of the region is the undulating plain of the Trans-Ural Plateau, and in the southeast, the spurs of Sary-Arka. The Turgai Hollow crosses the territory of the Kostanay region from north to south. In the central part of the Turgai Plateau, Sypsynagash Hollow runs from west to east. In the west is Mount Zhitikara; on the Torgai Plateau are the Kargaly, Zhylandy, Kyzbel, and Teke Mountains; at the eastern foot are the Kyzbel and Kyzemshekshoky mountains; and in the southeast are the Hill of Zhylanshykturme and Mount Kayyndyshoky. The Altyn Dala State Nature Reserve, the Naurzum State Nature Reserve, and the Mikhailovsky and Tounsorsky State Nature Reserves are located in the region. The region has the potential for the development of cultural, educational, and nature tourism. |
North Kazakhstan Region | This region is located in the northern part of the republic. It was established in 1936. The territory of the region covers 98,000 sq km, and the population is 563,300. The northern half of the territory is represented by the Esil Plain and the southern half by the Kokshetau Upland with the Zhaksy Zhangyztau, Imantau, and Ayyrtau mountains. The most popular sites of the region are Mamlyutsky, Smirnovsky, and Orlinogorsky State Natural Reserves, the State Natural Monuments of Zhanazhol, Serebryanyy Bor, Sosnovy Bor, and Sopka Orlinaya Gora, as well as a spring. Cultural, educational, gastronomic, and active tourism are well-developed in the region (there is a sports arena, a tennis center, swimming pools, fitness clubs, the Kulager racetrack, lakes, sports and recreational complexes, a rope park, as well as a ski complex with a ropeway). Ecological and social tourism and tourism for children and youth hold promise for development. |
Pavlodar Region | It was established in 1938 and is located in the north-eastern part of Kazakhstan. The total area of the territory is 124,800 sq km, and the population is 757,000. The region features a plain landscape. The right bank of the Irtysh River is located on the Barabinsk Lowland and the Kulyndyn Plain; the left bank is on the Irtysh Plain; and the southwestern part of the region is home to the hilly area of Sary-Arka, where the Bayanaul, Kyzyltau, Zeltau and other mountains stand out. In the region, there is the Bayanaul SNNP (State National Natural Park), as well as the Yertys-Ormany State Forest Nature Reserve, the Kyzyltau State Nature Reserves, and the floodplain of the Irtysh River. Sports (mainly hiking), water sports, and educational tourism are developed in the region. The region has huge potential for the development of ecological, ornithological, mining, and mineralogical tourism. |
East Kazakhstan Region | This region, established in 1932, is located in the territory of East Kazakhstan (283,200 sq km and population of 1,389,600). Mountainous and hillocky relief, as well as highly rugged terrain characteristics, are typical for a significant part of the region’s territory. In the east are the ridges of the Rudny Altai: Ivanovsky, Korzhinsky, Koksusky, Tigretsky, Ulbinsky, and Obninsky. The ridges of the Southern Altai are Katunsky, Southern Altai, and Sarymsakty, and farther south one will find the Kalbinsky Ridge, the Zaisan Basin, and the Tarbagatai Ridges. The western part of the region is represented by the hillocky area of eastern Sary-Arka with the mountains of Hanshyngys, Shyngystau, and Akshatau. Also found in the region are the West Altai and Markakol State Nature Reserves; the Katon-Karagai SNNP; the Semey Ormany State Forest Nature Reserve; Kuludzhunsky, Tarbagataysky, and Nizhne-Turgusunsky State Nature Reserves; the Karatalskiye Peski State Nature Reserve; the Sinegorskaya Pikhtovaya Roshcha State Natural Monument; and the Altai Botanical Garden. Various types of tourism are well-developed in the territory of the East Kazakhstan Region, including rural, beach, water, winter, primary wellness (there are 19 medical centers practicing treatment with specialized facilities), cultural, educational, ecological, sports, and mountain. |
Atyrau Region | This region was established in 1938; in the protected areas of the land there is a limestone plateau, which was once the bottom of an ancient ocean. The territory of the region is a semidesert and desert lying in the Caspian lowland plain. The region has a well-developed oil and gas industry. Some of the famous architectural monuments are mausoleums, such as Zhuban-Tam, made of mountain shell rock and crowned with a helmet-shaped dome, as well as Asaly-Koketai, a domed structure with an ornately shaped spire built in 1877. In this region, cultural, educational, water, beach, business, and event tourism have become popular. |
Estimation Steps | Cluster 1 (Step—0.023) | Cluster 2 (Step—0.023) | Cluster 3 (Step—0.083) | Cluster 4 (Step—0.023) | TRP Final Value (Step—0.118) |
---|---|---|---|---|---|
Low Potential (LP) | 0.052–0.075 | 0.042–0.065 | 0.168–0.251 | 0.071–0.094 | 0.402–0.520 |
Medium Potential (MP) | 0.076–0.099 | 0.066–0.089 | 0.252–0.335 | 0.095–0.118 | 0.521–0.639 |
Above-Medium Potential (AMP) | 0.1–0.123 | 0.09–0.113 | 0.336–0.419 | 0.119–0.142 | 0.64–0.758 |
High Potential (HP) | More than 0.123 | More than 0.113 | More than 0.419 | More than 0.142 | More than 0.758 |
Region | Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 | TRP Final Value |
---|---|---|---|---|---|
Russian Federation | |||||
Astrakhan Region | LP | MP | MP | AMP | MP |
Volgograd Region | MP | AMP | AMP | AMP | AMP |
Saratov Region | LP | MP | AMP | MP | AMP |
Samara Region | MP | AMP | AMP | HP | HP |
Orenburg Region | AMP | MP | AMP | MP | AMP |
Chelyabinsk Region | MP | HP | AMP | HP | HP |
Kurgan Region | LP | MP | MP | MP | MP |
Tyumen Region with ADs (Autonomous Districts) | HP | MP | HP | HP | HP |
Omsk Region | MP | AMP | MP | MP | AMP |
Novosibirsk Region | AMP | HP | AMP | AMP | AMP |
Altai Territory | HP | AMP | HP | AMP | HP |
Republic of Altai | AMP | LP | LP | LP | LP |
Republic of Kazakhstan | |||||
West Kazakhstan Region | MP | MP | LP | LP | LP |
Aktobe Region | MP | MP | LP | LP | LP |
Kostanay Region | MP | MP | MP | LP | MP |
North Kazakhstan Region | AMP | MP | LP | LP | LP |
Pavlodar Region | MP | AMP | MP | LP | MP |
East Kazakhstan Region | HP | AMP | MP | AMP | AMP |
Atyrau Region | MP | LP | LP | AMP | MP |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Tanina, A.; Tashenova, L.; Konyshev, Y.; Mamrayeva, D.; Rodionov, D. The Tourist and Recreational Potential of Cross-Border Regions of Russia and Kazakhstan during the COVID-19 Pandemic: Estimation of the Current State and Possible Risks. Economies 2022, 10, 201. https://doi.org/10.3390/economies10080201
Tanina A, Tashenova L, Konyshev Y, Mamrayeva D, Rodionov D. The Tourist and Recreational Potential of Cross-Border Regions of Russia and Kazakhstan during the COVID-19 Pandemic: Estimation of the Current State and Possible Risks. Economies. 2022; 10(8):201. https://doi.org/10.3390/economies10080201
Chicago/Turabian StyleTanina, Anna, Larissa Tashenova, Yevgeni Konyshev, Dinara Mamrayeva, and Dmitriy Rodionov. 2022. "The Tourist and Recreational Potential of Cross-Border Regions of Russia and Kazakhstan during the COVID-19 Pandemic: Estimation of the Current State and Possible Risks" Economies 10, no. 8: 201. https://doi.org/10.3390/economies10080201
APA StyleTanina, A., Tashenova, L., Konyshev, Y., Mamrayeva, D., & Rodionov, D. (2022). The Tourist and Recreational Potential of Cross-Border Regions of Russia and Kazakhstan during the COVID-19 Pandemic: Estimation of the Current State and Possible Risks. Economies, 10(8), 201. https://doi.org/10.3390/economies10080201