Evaluation of the Financial Management Strategy Pursued by the Recreation Companies Irina G. Pavlenko1[0000-0001-6783-6273] and Igor A. Bukreev2[0000-0002-6903-946X] 1 V. I. Vernadsky Crimean Federal University, Taurida Academy, 4 Vernadsky Ave., Simferopol, 295000, Russia 2 V. I. Vernadsky Crimean Federal University, Humanities and Education Science Academy in Yalta (branch), 14 Halturin str., Yalta, 298635, Russia 11irin@rambler.ru Abstract. The study is focused on the methodology of DuPont multiplicative model application in the financial management, specifically, its modification fitting into the recreational environment; the latter is demonstrated on the ex- ample of one of the enterprises in Big Yalta. The article discusses the impact factors and their effects on the efficiency of the recreation companies in terms of the financial management strategy and attempts to present the system of in- terrelated ratios and their interpretations reflecting different financial manage- ment strategies. The theoretical analysis of the recreation industry according to the general-to-specific pattern allowed for the modification of the DuPont mod- el which takes into account business operations alone and other activities, the recreation industry being “the specific”. Further on, the study specifies the im- pact factors on the pre-tax profit clarifying that the discrepancies in business accounting and tax accounting require additional studying which lies beyond the scope of the current research. As a result, we obtain a model of a mixed type which allows taking into account the factors that affect operating and other ac- tivities in terms of the bottom line and profitability. However, it is emphasized that the applied factorial method of chain substitution is not flawless and is only relevant for the enterprise used as the demonstrative modified model; hence, the idea is to use the integrated total of the ratios based on the factors of the model to evaluate their impact on the recreation industry performance in Big Yalta and the subregions of Crimea (method of correlation analysis). Keywords: Financial Strategy; Evaluation of the Financial Management; Mul- tiplicative Model; Recreation Industry; Model Modification. Proceedings of the 10th International Scientific and Practical Conference named after A. I. Kitov "Information Technologies and Mathematical Methods in Economics and Management (IT&MM-2020)", October 15-16, 2020, Moscow, Russia © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org) 1 Introduction Recreation business has a range of positive effects including health gain, reduced medical expenses during the year, environmental improvement and preservation and increased labor efficiency, which allows to refer it to a social category of business. Recently, the commercial activity has deflected from its original trajectory of combin- ing beach recreation with therapeutic function, which to a great extent estranges this type of business from the social category and strategically creates problems for recre- ation businesses whose resources remain unengaged in the off-season period. Thus, putting the recreation infrastructure into the operation mode before the high season and putting it on halt after the period of activity results in lower competitive ability of the product and greater expenses, which leads to higher prices. When it concerns recreation business development, personal benefits and social benefits large- ly go hand in hand when it comes to strategic planning which, in its turn, has to meet the external challenges rather than follow the will of a separate enterprise. In this case, the efficiency of the strategy of the recreation business management greatly depends not only on the economic environment, but also on the financial in- sight and financial management that has to be evaluated based on the profitability ratios related to business activity, assets, equity and other operating and overhead expenses as well as the effects of the other activities, including investment and fi- nance. First of all, the financial management is evaluated through the financial leverage effects as the positive changes are often neutralized by the high loan rates, which makes businesses rely on the factors stimulating growth of the asset turnover ratio and return on sales. 2 Theoretical background The financial strategy at the enterprise has been the focus of many researchers includ- ing I. A. Blank [1; 2], Yu. Brigham and O.L. Gapenski [3]. M. S. Oborin [4; 5] stud- ied the financial strategy as a part of the management mechanism at the recreation complex, and Yu. N. Vorobyov [6] and G. G. Yermolenko [7]. analyzed the recrea- tion companies’ financial performance. When evaluating the efficiency of the business management, the first things to be taken into account are the income and the efficiency indices calculated based on the expenses on the operating, investment and other business activities [4]. Thus, this study of the financial management strategy uses the widely known DuPont multiplica- tive model which traditionally includes three factors and its modification designed in accordance with the specific features of the recreation industry [1]. The study materials used to observe the functioning of the DuPont model and ana- lyze its constituent factors include recreation companies in Big Yalta which made 10% of the selected data [8]. The other selected data for the comparative analysis were on the other subregions. In the current situation, the use of such analysis tools as financial leverage effect and DuPont strategic model for developing the financial strategy of the company as a part of the general business strategy is impeded due to the low return on assets and, hence, insufficient equity of many enterprises in Big Yalta and Big Alushta, the situa- tion being worse in other subregions of Crimea [1; 3; 6; 7]. The financial strategy is understood as an integrated system of financial manage- ment which is also a part of the general business strategy that makes a program or a complex of strategic solutions to effective resource management [1]. In the western economic theories, the financial strategy has to coordinate the external financial sources with the general strategy of business development. [9]. Formula 1 in its initial modification has the following expanded form: (1) where TI is the total income from all kinds of activities (operating and others); NI is net income; AC is aggregate capital (the total assets); EQ is equity. 3 Methodological approaches Thus, on studying the works by Russian researches [1; 2; 3; 10; 11; 12; 13; 14] and analyzing the activity of the recreation companies, we may conclude that factorial analysis of the return of equity according to DuPont model plays a key role in devel- oping the financial strategy and is characterized by the following factors: 1) Financial leverage factor or its opposite, solvency ratio (SLR). The im- pact of the leverage factor on the return of equity (ROE) for the majority of the com- panies in the subregions of Crimea is negative which is confirmed by the positive, but yet low correlation ratio (0.15) between ROE and SLR. Thus, operating efficiency based on debt financing would be a solution for the majority of enterprises in Big Yalta with the correlation ratio -0.68; 2) The return on assets (ROA) factor in the recreation industry shows great potential in the conditions of growing economic activity in the off-season period and can add to the effect produced by the product profitability factor (PPR) as the pricing of the service does not only include the expenses in the high season, but also the ex- penses related to the infrastructure maintenance in the off-season period. The latter are comprised of the wages paid for servicing, heating and other expenses in the off- season when the accommodation services are hardly provided. In many recreation companies, the annual amortization of a big share of the fixed-capital assets has to be recovered within 3 – 4 month of active work; 3) The product profitability factor (PPR). Cost reduction has a positive ef- fect on the product profitability (PPR), which ceteris paribus in the Crimean recrea- tion industry, could make a significant change only in case of the revitalization of the business activity in the off-season period (criterion of business activity in the off- season period in the marginal approach > variable costs) that we outlined earlier as an outcome of the rising return on assets. It is noteworthy that business activity revitali- zation in the off-season period acquires particular importance for big enterprises which could make use of the scale effect. This means that even relatively big compa- nies can spend more on the sales promotions by introducing special services or reduc- ing prices. 4) Operating activity factor. The increase in the operating activity in the off-season period is a solution in terms of another factor to be included into the DuPont modification model – the operating income. The theoretical analysis of the recreation industry peculiarities and their actualiza- tion in the DuPont model allow for its modification as a result of the general-to- specific approach, the specific being the recreation industry. The model as shown in formula 2 is of the mixed kind which takes into account operating and other activities in the bottom line and productivity (Table 1). (2) where (AC/EQ) can be replaced by (EQ/AC); OI is operating income; SR is sales revenues; TI is total income from all kinds of activities (operating and others); NP is net profit; Pother is profit from other activities; AC is aggregate capital of the company (all its assets); EQ is equity. It should be noted in terms of the operating activity and other activities that if the latter are not proportional to the former, but take the same direction, presumably, the growth of the business activity in the recreation industry is happening at the expense of the operating activity. Though, eventually, should the company come close to its maximum potential realization, this correlation has to be inverse. In this correlation the ratios do not have to be compared in their absolute values. The profit from other activities can have a positive effect on the bottom line of the company, should the operating costs be considerable, and thus, also on the net profit. The relevance of the other activities in the recreation industry should also be con- nected with the off-season factor which causes enterprises to engage their assets into rental activities, use their funds to earn some interest and sell the assets which become not fully used or loss-making due to the changed environment. It is evident that in the conditions of the increased business activity other incomes and costs will be taking a smaller part in the overall business performance whereas the share of the operating activity in the company’s income will be bound to grow. 4 Results The DuPont model has been tested and the obtained results are presented in Table 1 on the example of AO Sanatorium “Ai-Petri”. The impact of the factors was not evaluated solely based on the regular return on equity ratio, but also on another modification as we took into account the peculiarities of both business and tax accounting. Herewith, it is important to stress that in this respect tax management is another factor that can be studied in detail following the general-to-specific approach; unfortunately, the current research leaves no room for it. Table 1. Modified factor DuPont model on the example AO Sanatorium “Ai-Petri”. Year 2018 2017 Changes Key business performance indices Operating income 434225 378591 55634 Other incomes 8535 5687 2848 Other expenses 28185 23202 4983 Total income from all kinds of activities 442760 384278 58482 Operating profit 88434 51519 36915 Pre-tax profit 68784 34004 34780 Assets over the period 315954 268145 47809 Equity of the enterprise 300306 256517 43789 Return on sales 0.204 0.136 0.068 Factors of ROE SR/TI ratio . 0.981 0.985 -0.004 Return on assets TI/AC 1.401 1.433 -0.032 Correlation ratio, AC/EQ 1.052 1.045 0.007 Operating activity ratio 0.294 0.201 0.094 Other activities ratio -0.065 -0.068 0.003 ROE = Pre-tax profit/ EQ 0.229 0.133 0.096 Impact of the profitability factors on ROE The return on sales factor 0.099738 88.8% The sales revenue factor -0.00137 0.9% The total income factor -0.00663 6% The aggregated capital 0.001897 factor 1.7% Operating activity factor 0.09364 97.4% Other activities factor 0.003 2.6% The joint effect of both 0.09649 100% kinds of activities The data for the calculation are taken from [8; 11; 12;13; 14]. Using the index of pre-tax profit rather than net profit provides for a different repre- sentation of return on equity ratio (Formula 3): (3) where PTprofit is the pre-tax profit; NP is net profit; EQ is equity. The carried-out analysis shows that operating activity of AO Sanatorium “Ai-Petri” played a key role in return on equity. Among several factors that had an impact on the return on equity there was the return on sales factor which amounted to 88.8% in the operating activity whose ration reached 97.4% compared to only 2.6% ratio of other activities, which though having a negative effect on the overall performance still al- lows compensating at least some expenses in the off-season period. The studied material includes a selection of enterprises of different scale in terms of the number of employees and assets. We also tried to eliminate all the enterprises whose sales revenues were subject to considerable oscillations and instead focused on the enterprises showing operating stability (based on the sales revenues dynamics over the period of 4 years). We excluded the enterprises with limited access to their data due to the status of Federal State Budgetary Institutions (Table 2). Table 2. Enterprises showing stable dynamics in their development. Sales revenues over the 4 year period in Big Yalta subregion 2015 2016 2017 2018 Average Enterprise growth rate AO Sanatorium - - 378 591 434 225 1.047 “Ai-Petri” OOO “Kirov 120 398 153 881 191 988 301 051 1.162 Sanatorium” OOO Sanatorium 8 552 12 492 10 437 16 615 1.168 “Kurort Mishor” State unitary 412 689 465 482 466 300 463 853 0.998 enterprise SGK“Russya” OOO"SKOK “Ai- 286 234 308 049 387 129 1.079 Danil” ООО Sanatorium 9 238 8 557 9 266 11 893 1.087 “KIEV” ООО “SKK 2 982 6 532 9 471 41 374 1.635 “Goluboy Zaliv” OOO “Oasis“ 11 000 15 182 11 621 17 514 1.147 “Bukhta Mechty” ООО “SGK 19 019 28 755 21 601 22 891 1.020 "Zaporozhye” PAO “G/K 1193 624 1244 279 790 832 675 615 0.949 “YALTA- INTOURIST” State unitary enter- - 1 916 1 910 1 660 0.954 prise of the Republic of Crimea “Sanato- rium FOROS” Total in Big Yalta 1891 231 2375 683 2344 042 2507 759 1.023 Compiled and calculated based on [8] The selection includes a number of out-of-line enterprises that should not be taken into account when carrying out the analysis as they show nontypical patterns, which can impact the outcome. The enterprises that stand out in terms of their indices are OOO Sanatorium “Kiev” and OOO “SKK “Goluboy Zaliv”, both showing very low solvency ratio and negative return on equity. The enterprises with high return on equity and loan capital are located in different subregions of Crimea, but most of them are in Yalta: AO “Kirov Sanatorium”, AO Sanatorium “Kurort-Mishor”, PAO “G/K “YALTA-INTOURIST” and State unitary enterprise of the Republic of Crimea “Sanatorium FOROS”. Efficiency of the financial management is directly connected with the credit and loan availability. For instance, the majority of the enterprises accumulate a big share of their internal funds and solvency ratio is close to 1 whereas only enterprises show- ing high profitability can afford a considerable share of loans (Table 3). Table 3. Key indices of the business activity of the recreation enterprises in Big Yalta in 2018. Activity Re- Return Solven- Re- Sales Other Return on ratio turn on cy ratio turn revenue income the aggre- on equity (SLR)= on s (SR) s gate capital assets = EQ/AC sales = (ROA (NP/EQ (ROS) (PTprofit/E ) = (TI ) = OI Q) /AC) /SR 1.40 0.18 0.22 0.95 0.20 434225 0 1.7 0.29 0.09 0.25 0.12 301051 11031 1.59 0.47 0.21 0.37 0.15 16615 0 Values of 0.33 0.00 0.00 0.98 0.01 463853 2248 the stud- 1.04 0.22 0.22 0.97 0.17 387129 24412 ied ratios 1.19 0.12 0.08 0.62 0.11 133939 1360 in Big 4.96 0.23 0.27 0.97 0.06 17514 19 Yalta 1.77 0.12 0.15 0.93 0.09 22891 0 0.42 0.31 0.16 0.39 0.67 675615 5265 0.34 0.32 0.21 0.64 0.63 1660 0 Total, for 0.62 0.25 0.14 0.69 0.27 2454492 52870 all the enterpris- es The calculation is based on [4; 5; 8; 9; 10; 11; 12; 13; 15]. When analyzing the factors of the selected strategic model, we discovered the correla- tion between the return of equity (ROE) and the solvency ratio (SLR) which proves that not all the recreation enterprises on the list used loans. On the example of the studied enterprise, we many conclude that return on equity (ROE) has good potential for growth at the expense of the increasing operating activi- ty and return on assets which amounts to 15.2% whereas PPR amounts to 82%. The PPR factor is well-grounded when applying the method of chain substitution; howev- er, it has to be made clear that return on assets and growth of the operating activity ratio are highly underrated. When applying other methods of factorial analysis [16], the obtained results may differ as the joint effect is taken into account; in the mean- time, it is evident that studying the factor impacts on the activity of only one enter- prise in the recreation industry is not enough and cannot be representative, thus, a study carried out in the field of recreation industry requires elaboration of a different approach (Table 4). Table 4. Key correlation ratios of the factors of the DuPont model modification effecting en- terprises in Big Yalta, 2018. Key correlation ratios Big Yalta Crimea’s subregions Return on assets (ROA) = (TI/AC) and return on equity 0.08 0.32 (ROE) = (NP/EQ) Solvency Ratio (SLR)= EQ/AC and return on equity (ROE) - 0.68 0.15 = (NP/EQ) Return on equity (ROE) = (NP/EQ) and return on sales 0.46 0.28 (ROS) = OI/SR Sales revenues (SR) and other incomes 0.39 0.48 The calculation is based on [17; 18] The studied correlation ratios should show inverse relationship in case the financial leverage effect has a positive value. As the enterprises start to grow at the expense of the loan capital use, the solvency ratio decreases and the return on equity increases, which explains the negative relationship between the changes in ROE and SLR. In the subregions of Crimea, this relationship is positive, though the ratio is rather low (0.15) whereas in Big Yalta the relationship is negative (-0.68). The correlation between ROE and PPR can be either positive or negative depend- ing on the changes in ROA, i.e. all the three ratios have to be studied together. For example, in case of business growth, there can be a drop in PPR due to the focus on the demand stimulation activities accompanied either by reduced pricing or increase in extra costs, which will eventually lead to rising ROE showing a negative relation- ship with PPR, but a positive one with SLR, should the business growth be stimulated by loan capital. It is important to remember that economic growth results in extra losses and expenses on sales promotions which can respectively be covered by cost reduction achieved due to scale effect; in this case the correlation between ROE and PPR will be positive [19; 20; 21]. Hence, it is necessary to collect additional information on the changes in the busi- ness activity in the off-season period as in the high season demand exceeds supply. The correlation ratio which reflects this condition is the relationship between sales revenues (SR) and other incomes whose insignificant values may be explained as a result of decreasing share of other activities in the total income due to the activation of the activity in the off-season period. The PPR and ROA correlation ratio in the subregions of Crimea is rather low (0.28), which allows suggesting that other activities make up a big share in the busi- ness activity of the companies, but it is less efficient in comparison with the compa- nies in Big Yalta where this ratio amounts to 0.8. The other activities depend on the vigorousness of the operating activity in the off-season (the relationship is negative) [22; 23]. The results presented in Table 3 and Table 4 allow making conclusions in terms of the financial management of the enterprises in Big Yalta as compared to the other subregions of Crimea. ROE of the selected enterprises in Big Yalta amounts to 25% and their performance is characterized by the distinct ROE and SLR correlation ratio which equals -0.68 whereas its value is positive (0.15) in the other subregions of Cri- mea. Under the circumstances, return on aggregate capital (14%), which is always lower than ROE, is another evidence of the loan use and efficient operation. In this way, the correlation ratios help evaluate the economic condition of an enterprise and, thus, define the trajectories of its further development. 5 Discussion When interpreting the obtained correlation ratios, it is necessary to take into account the development tendencies in the recreation industry. Specifically, starting 2015 the industry has been enjoying a considerable growth in customers, which has had a posi- tive effect on the occupancy rate; however, the received data show that the situation is not so straightforward for the recreation companies as the peculiarities of the subre- gions and different level of business activity play a big part [24; 26]. The enterprises in Big Yalta and other subregions of Crimea selected within the scope of this research show significant discrepancies as per their efficiency ratios; for this reason, they have been studied separately. Moreover, the enterprises in the subre- gions can also be classified into different groups depending on the mode of business activity. According to the elaborated methodology of correlation ratios which has been par- tially presented above, the enterprises of the subregions of Crimea have been grouped as per their ROA ratios presented in Table 5. We should conclude that, like many other enterprises, AO Sanatorium “Ai-Petri” largely relies on self-funding, which adds to the solvency ratio; however, the data obtained on the other recreation enter- prises of Big Yalta differs, which also concerns the ROE/SLR ratio at -0.68 suggest- ing efficient debt financing. The enterprises in the subregions of Crimea in the group with ROA (above aver- age) show semblance with the enterprises of Big Yalta in terms of their performance. Enterprises in both groups show economic growth and sales growth (which corre- sponds to the tendencies in the industry) and use debt funding contributing to their effective development and ROE growth [25; 27; 28]. The difference, however, lies in the fact that the enterprises in the subregions of Crimea are more subject to the effects of the ROA/ROE correlation in comparison with Big Yalta, the latter showing positive relationship between PPR and ROE, which, most probably, signifies the growing demand for the recreation service and, hence, growth in prices. Table 5. Interpretation of the obtained correlation ratios reflecting the financial strategy of the recreation companies. Ratios (ROA) (SLR) (PPR) Commentary on the obtained per and and and correlation ratios group (ROE) (ROE) (ROE) The overall business activity of the enter- prise is growing at the expense of the ac- tivity invigoration in the off-season period (+ROA) achieved due to discounts and (ROA) -0.612 -0.017 other expenses on sales promotions, which above 0.738 slightly affects product profitability (-PPR), average though partial compensation is possible due to the scale effect in case the ratio is low. Nevertheless, there is an overall tendency for ROE growth (+ROE) as the growth is funded from the loan capital (-SLR), i.e. priority is given to debt financing. The enterprises increase their activity (ROA) (+ROA) which results in the product prof- average itability growth (+PPR) due to the scale effect but they mostly rely on their internal funds (+SLR) accompanied by increase in the return on equity (+ROE), i.e. the priori- 0.688 0.208 0.718 ty is given to self-financing. Slim down in operation. A drop in return on assets (-ROA) and increase in return on (ROA) equity (+ROE) happen due to cutting on below the nonprofitable production and services, average -0.289 0.589 0.207 which leads to increase in product profita- bility (+PPR). The share of debt financing (+SLR) which could not be repaid shrinks as the interest on credit exceeds return on aggregate capital, i.e. the priority is given to self-financing. The calculation was based on the Average value of ROA 0.916 weighted arithmetic mean. The calculation was based on the Variance 0.607 squared deviation from the mean. The ratio was calculated as root Standard deviation 0.779 mean square of the variance. The coefficient was calculated as a ratio of the standard deviation to Coefficient of variation 0.849 the mean. The calculation is based on [8] The negative PPR/ROE correlation in the subregions of Crimea indicates that the enterprises are actively engaged in the demand stimulation activities resulting in growing expenses and reduced prices for the service. Recently, the share of the cus- tomers consuming recreation services has been increasing on the western and eastern coasts of Crimea. The enterprises of Big Yalta show greater efficiency in comparison with the enter- prises in the other subregions of Crimea, which is evident from the higher profitability ratios and active debt funding in the financial management. At the subregional level, this also contributes to the competitive advantage that Big Yalta has over the other subregions [29; 30]. 6 Conclusions The obtained data allow making conclusions as for the financial management strate- gies applied at the enterprises of Big Yalta in comparison with the other subregions of Crimea. Thus, the average ROE of the studied enterprises of Big Yalta amounts to 25% and is accompanied by a distinct negative ROE/SLR ratio of -0.68 as compared to the positive ratio of 0.15 shown by the enterprises in the subregions; however, thorough analysis reveals that the ROE/SLR ratio of the enterprises with ROA (above average) approximates the ratio in Big Yalta. Another peculiarity lies in the fact that ROA/ROE ratio has a much greater value in the subregions than in Big Yalta. The negative PPR/ROE correlation in the subregions of Crimea within the studied group proves that these enterprises actively carry out demand stimulation activity unlike the enterprises in Big Yalta where profitability is geared by the demand growth. 7 Acknowledgements The study was carried out as a part of the applied research АААА-А19- 119012390078-9 “Development of the coastal destinations in the Republic of Crimea till 2030”. References 1. Blank, I.A.: Financial Strategy of the Enterprise [in Russian]. Nika-Centr: Elga, Kiev (2004). 2. Blank, I.A.: Financial Management [in Russian]. Nika-Centr: Elga, Kiev (2004). 3. Brigham, Yu., Gapenski, O.L.: Financial Management [in Russian]. Ekonomicheskaya shkola, Saint-Petersburg (1997). 4. Oborin, M.S.: Peculiarities of development and evaluation of the mechanism of the recrea- tional complex of the Republic of Crimea at the stage of its integration into the economy of Russia [in Russian]. Rossijskoe Predprinimatelstvo 19(2), 565–576 (2018). 5. Oborin, M.S.: Process approach to the improvement of the management mechanism in the hospitality industry of Russian and the Republic of Crimea [in Russian]. Servis Plus 12(2), 42–53 (2018). 6. Vorobyov, Yu.N.: Funding of the development of the recreational institutions [in Russian]. Nauchnyi Vestnik: Finansy, Banki, Investicii, 3, 46–49 (2012). 7. Yermolenko, G.G., Panasko, D.S.: Analysis of the financial and economic activity of the recreational complex of the Republic of Crimea: finding innovation priorities [in Russian]. Nauchnyi Vestnik: Finansy, Banki, Investicii, 3, 23–28 (2014). 8. SINAPS – search and tender analytics, https://synapsenet.ru/searchorganization/proverka- kontragentov, last accessed 2020/01/10. 9. Bender, R., Ward, K.: Corporate Financial Strategy. Butterworth Heinemann (2010). 10. Kovalev, V.V.:Financial Analysis: Methods and Procedures [in Russian]. Financy i statistika, Moscow (2002). 11. Lubkov, V.A.: Objects and stages of the strategic analysis organization [in Russian]. Rossijskoe Predprinimatel`stvo (2013), http://www.creativeconomy.ru/articles/28721/, last accessed 2020/01/11 12. Parushina, N.V.: Development of the Methodology of the Financial Sustainability Analysis of the Enterprises Based on the Professional Competencies Management [in Russian]. Oryol (2018). 13. Tsvetkova, A.O., Zamyshlyaeva, E.L, Parushina, N.V.: Problems of credit granting to businesses and their solutions [in Russian]. Ekonomicheskaya Sreda, 3(29), 44–50 (2019). 14. Nadvornaya, G.G., Klimchuk, S.V., Oborin, M.S., Gvarliani, T.E.: Theory and methodolo- gy of the economic potential evaluation of the enterprise [in Russian]. Ekonomicheskie i Social`nye Peremeny: Fakty`, Tendencii, Prognoz, 6(48), 70–90 (2016). 15. Chekulina, T.A., Parushina, N.V., Lyutneva, N.A.: Economic analysis of the business acrtivity efficiency [in Russian]. Vestnik OrelGIE, 3(45), 157–160 (2018). 16. Dolya, V.T.: Economic Analysis: Theory and Applied Methods [in Russian]. Kondor, Ki- ev (2003). 17. Karlberg, K.: Regression Analysis in Microsoft Excel [in Russian]. Dialektika, Moscow (2019). 18. Sokolov, G.A., Sagitov, R.V.: Introduction into Regression Analysis and Planning of Re- gression Experiments in Economics [in Russian]. Infra-M, Moscow (2016). 19. Bukreev, I.A.: Development strategy of the business activity in the recreation industry based on the subregional peculiarities of Crimea [in Russian]. Servis v Rossii i za Rubezhom, 2, 110–118 (2019). 20. Pavlenko, I.G., Bukreev, I.A.: Resource allocation in the business development in Big Yal- ta recreation industry [in Russian]. Voprosy Regional`noy Ekonomiki, 4(37), 84–89 (2018). 21. Tarasenko V.S., Yena V.G., Berezhnaya I.V. Ustoichivy Krym. Kurortopolis Bolshaya Yalta [Stable Crimea. Big Yalta Resortopolis]. Simferopol, IT ARIAL, (2010). 22. Tsohla S.Yu. Transformatsiya Recreatsiynoi Diyal’nosti ta Turystychnykh Regionalnykh Rynkiv Kurortno-Rekreatsiynykh Poslug [Transformation of Recreational Activity and Tourist Regional Markets of Hospitality Services]. Simferopol, Tavria, (2008). 23. Tsohla S.Yu. Kontsepsiya ekonomichnogo rozvytku kurortno-rekreatsiynoi sfery Ukrainy [Concept of the Economic Development of the Hospitality Sector of Ukraine]. Simferopol, DIAYPI, (2012). 24. Ostovskaya A.A., Pavlenko I.G. “Formation of the competitive strategy of development for regional tourist destinations,” Financial and Economic Tools Used in the World Hospi- tality Industry: Proc. of the 5th Int. Conf. on Management and Technology in Knowledge, Service, Tourism & Hospitality (SERVE 2017), Bali, Indonesia & Moscow, Russia, pp. 161-165. (2018) 25. Tatarkin A.I., Doroshenko V.S. Region kak samorazvivayushayasya sotsial’no- ekonomicheskaya sistema [Region as an inherent sponteneously developing socio- economic system]. Economy of the Region, vol. 1, pp. 15-23. (2011) 26. Pavlenko I.G., Ostovskaya A.A., Kirenkina E.S. Transition model: to the ecologically bal- anced development of the ecosystem of wellness resort territories // IOP CONFERENCE SERIES: EARTH AND ENVIRONMENTAL SCIENCE. The conference proceedings. Far Eastern Federal University. С. 022072. (2019). 27. Strategiya social'no-ehkonomicheskogo razvitiya Respubliki Krym do 2030 goda [Strategy for socio-economic development of the Republic of Crimea until 2030]. Available at: http://minek.rk.gov.ru/file/File/minek/2017/strategy/strategy-shortvers.pdf. Reference date: 17.10.2020. 28. The authority on world travel & tourism. Economic impact 2016 Russian Federation. Lon- don: World travel & tourism council, 18 р. (2016) 29. Avdeeva Z.K., Kovriga S.V., Makarenko D.I. Kognitivnoe modelirovanie dlya resheniya zadach upravleniya slabostrukturrovannymi sistemami (situatsiyami) [Cognitive Modeling for the Purpose of Solving Managemnet Problems in the Semistructured Systems (situa- tions)]. Big Systems Management, Moscow: IPU RAN, p.193. (2007) 30. Kulba V.V., Kononov D.A., Kosyachenko S.A., Shubin A.N. Metody Formirovaniya Stsenariev Razvitiya Sotsio-Ekonomicheskih Sistem[Methods of Building Scenarios of Socio-Economic Systems Development]. Moscow: SINTEG, (2004).