Sustainable development of environment in the tourism destination areas: tourists’ perception of the issue

Zakharchenko, Pavel; Костенко, Ганна; Zhvanenko, S.; Mukhin, Viktor S.

doi:10.1088/1755-1315/628/1/012024

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…• Nataliia Zachosova, The Bohdan Khmelnytsky National University of Cherkasy, Ukraine [38] • Pavel Zakharchenko, Berdyansk State Pedagogical University, Ukraine [39]…”

Section: M3e2 2022 Program Committee Membersmentioning

confidence: 99%

Advances in machine learning for the innovation economy: in the shadow of war

Danylchuk,

Semerikov

2023

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This preface introduces the selected and revised papers presented at the 10th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2022), held online in Ukraine, on November 17-18, 2022. The conference aimed to bring together researchers, practitioners, and students from various fields to exchange ideas, share experiences, and discuss challenges and opportunities in applying computational intelligence and data science for the innovation economy. The innovation economy is a term that describes the emerging paradigm of economic development that is driven by knowledge, creativity, and innovation. It requires new approaches and methods for solving complex problems, discovering new opportunities, and creating value in various domains of science, business,and society. Computational intelligence and data science are two key disciplines that can provide such approaches and methods by exploiting the power of data, algorithms, models, and systems to enable intelligent decision making, learning, adaptation, optimization, and discovery. The papers in this proceedings cover a wide range of topics related to computational intelligence and data science for the innovation economy. They include theoretical foundations, novel techniques, and innovative applications. The papers were selected and revised based on the feedback from the program committe members and reviewers who ensured their high quality. We would like to thank all the authors who submitted their papers to M3E2 2022. We also appreciate the keynote speakers who shared their insights and visions on the current trends and future directions of computational intelligence and data science for the innovation economy. We acknowledge the support of our sponsors, partners, and organizers who made this conference possible despite the challenging circumstances caused by the ongoing war in Ukraine. Finally, we thank all the participants who attended the conference online and contributed to its success.

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“…• Nataliia Zachosova, The Bohdan Khmelnytsky National University of Cherkasy, Ukraine [38] • Pavel Zakharchenko, Berdyansk State Pedagogical University, Ukraine [39]…”

Section: M3e2 2022 Program Committee Membersmentioning

confidence: 99%

Advances in machine learning for the innovation economy: in the shadow of war

Danylchuk,

Semerikov

2023

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Integration of Medicinal Plants into Comprehensive Supply Chains: The Threats and Opportunities of Environmental Devastation

Al‐Obaidi

Desa

Alobaidi

et al. 2022

Environmental Challenges and Solutions

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Financial potential of Black Sea resort and recreation territories

HUMENIUK,

KOSTENKO,

ZAPUKHLIAK

2023

Fìnansi Ukr.

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Introduction. In the context of the difficult socio-economic situation in Ukraine caused by the ongoing war, the issue of assessing the financial potential of the Black Sea resort and recreational areas in the context of their revitalization is becoming especially important. Problem Statement. The study is aimed at assessing the existing problems of the financial potential of the resort and recreational territories of the Black Sea region, identifying the prerequisites for its strengthening, analyzing the factors that influence the formation and use of financial resources of territorial communities. Purpose. The purpose of the article is to assess the financial potential of the Black Sea resort and recreational areas and identify trends in their further development in modern conditions. Methods. Various methods of analysis are used, including comparative analysis, statistical and graphical methods, economic modeling, quantitative methods, as well as system analysis and synthesis. Results. The article examines the issues of assessing the current state of the financial potential of the resort and recreational areas of the Black Sea region and the prerequisites for their further development. The components of the financial potential of resort and recreational territories are determined, which takes into account the financial potential of enterprises, the financial potential of households, and the budgetary potential as a source of financial resources of local authorities. The article focuses on assessing the budgetary potential of the Black Sea resort areas. The assessment was based on the indicators of the budgets of Odesa and Chornomorsk city territorial communities for 2018-2022. The revenues and expenditures of the Black Sea resort areas and their deviations from the planned indicators for the study period are analyzed. The level of financial support for hospitals and sanatoriums in the structure of expenditures of the resort areas' budgets is determined. The influence of the deficit/surplus on the formation of the budgetary financial potential and further development of the studied resort areas is determined. The components of the budgetary potential of the Black Sea resort and recreational areas and trends in their changes are investigated. Conclusions. The formation of the financial potential of resort and recreation areas of the Black Sea region for 2018-2022 is characterized by heterogeneity and instability in the sources of its filling. The revitalization of resort and recreation areas involves the reorientation of certain types of business activities and their adaptation to modern realities. Strengthening of the financial potential in the war and post-war period should take place by increasing the efficiency of managing the financial resources of local self-government, taking into account forecasting and planning, analysis and monitoring of the budget process, and the search for reserves.

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Sustainable development of environment in the tourism destination areas: tourists’ perception of the issue

Cited by 3 publications

References 4 publications

Advances in machine learning for the innovation economy: in the shadow of war

Advances in machine learning for the innovation economy: in the shadow of war

Integration of Medicinal Plants into Comprehensive Supply Chains: The Threats and Opportunities of Environmental Devastation

Financial potential of Black Sea resort and recreation territories

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