One of the main conditions for increasing the level of ecosystem service delivery through the prism of decentralization is in-depth analysis and monitoring of the state of ecosystems, which will allow the development of priority services on a fee basis. The article shows the influence of the integrated territorial communities (ITC) on the activities of the territorial and recreational system, which allowed to optimize the costs of recreation facilities. The classification of forest ecosystem services according to the evaluation indicators has been systematized. From a practical point of view, the model of the optimal functioning organization of the recreational object was adapted, which was preceded by the analysis of forestry, which allowed to determine the capacity of a single recreational load. The model of recreational object optimum functioning organization on the example of forestry was built, which allows to increase the recreation on the objects of recreation. A descriptive model of the recreational area, the key object of which is the complex of ecosystem services of forest located in the territory of the ITC is proposed. Its structure offers the arrangement of recreation rooms in the territory of the forestry for temporary stay, which will allow to generate income. The issue of income in the part of recreation is quite painful, since recreational places are free for recreation.
Innovative policy and regional management leverages should create the foundations for the “impulse” to form the Ukrainian market of natural gas and its distribution. Efficient and desirable economic reforms in the activity of the gas distribution companies of the Western region of Ukraine will contribute to increasing their competitiveness level by implementing innovative activities. The paper aims to make an integral estimation of the competitive positions of the gas distribution companies that function on the Western Ukrainian market of natural gas distribution among consumers and develop practical recommendations directed at forming and implementing the innovative policy of improving their competitiveness. To achieve the aim, the authors have developed the methodology of calculating the competitiveness level for the gas distribution companies that function on a certain natural gas distribution market of any scale. Based on the results of the conducted research, the paper shows that the competitiveness condition of most gas distribution companies of the Western region of Ukraine is either of critical – І or satisfactory – ІІ levels. Meanwhile, it is worth mentioning that only AT “Chernivtsihaz” is characterized by the highest rate of competitiveness integral estimation among all the companies operating on the market of the natural gas distribution among consumers in the Western region of Ukraine. Therefore, it was identified as level ІІІ – “decent” level, which is the average competitive indicator.
The paper considers the problem of studying the impact of key determinants on the industrial enterprise business model economic efficiency and aims to build an optimal model for predicting the industrial enterprise business model effectiveness using neural boundaries. A system of key determinants key factors has been developed. Significant factors were later used to build neural networks that characterize the studied resultant trait development vector. The procedure for constructing neural networks was performed in the STATISTICA Neural Networks environment. As input parameters, according to the previous analysis, 6 key factor indicators were selected. The initial parameter is determined by economic efficiency. According to the results of the neural network analysis, 100 neural networks were tested and the top 5 were saved. The following types of neural network architectures, multilayer perceptron, generalized regression network and linear network were used. Based on the results of the neural network modeling, 5 multilayer perceptrons of neural network architectures were proposed. According to descriptive statistics, the best model was a multilayer perceptron, with the MLP 6-10-1 architecture, which identifies a model with 6 input variables, one output variable and one hidden layer containing 10 hidden neurons. According to the analysis of the sensitivity of the network to input variables, it was determined that the network is the most sensitive to the variable the share of electricity costs in total costs. According to the results of selected neural networks standard prediction, the hypothesis of the best neural network was confirmed as Absolute res., Squared res, Std. Res for the neural network MLP 6-10-1 reached the optimal value and indicate that the selected model really has small residues, which indicates a fairly high accuracy of the forecast when using it.
This paper investigates the issues of the management improvement of business-processes on conditions of digital transformation. Based on studies of domestic and foreign scientists, it was established that the intensive process of digitization of the economy generates the emergence of new digital technologies and solutions, the specificity of their impact on business models of enterprises needs additional scientific study. Generalized conceptual diagram of the system modeling process is proposed. It has been found that digital transformation has led to changes in the business process management of enterprises, which have been driven by improved efficiency and manageability of operations, and have become a challenge oriented to the experience of successful global companies. A business process model was built "as is", then a model "to be" be based on them modelling the digitized business process network of JSC Ukrtransnafta, which was carried out using BPMN Visio 2010 Premium. It is determined that the efficiency of functioning of the modern state is largely determined by the speed and quality of decision making. This is not possible without digitization in the new paradigm of digital transformation. It allows not only to digitize the data, but also to improve internal discipline and speed up the decision-making process.
Purpose. The purpose of the article is to diagnose the financial and economic conditions of the agricultural insurance market in the context of transformational changes, which allows identifying the dependences of variables among the indicators of insurance in Ukraine. Methodology / approach. The final goal of diagnosis is to build models that describe the variables and allow assessing the impact of some insurance indicators on the number of insurance contracts, which allows conducting regression of projected and observed values among insurance indicators during 2005–2019. The direct selection was also applied, which allowed starting without variables in this model by checking the addition of each variable with the use of the selected criterion of conformity of the model; as well as the repeatedness of this process until the best state of the model. Results. The modelling results allowed us to determine that among the insurance indicators in the agricultural insurance market, the dependent variable is the indicator of the number of insurance contracts. As a result of the regression, it was stated that for the dependent variable the USD / UAH exchange rate and the subsidy, mln UAH, have a significant impact on the number of insurance contracts. Less importance had the area, thousand hectares, and the remaining variables did not determine such an impact. The obtained regression value of the predicted and observed value stated an adequate model, as the slope of the regression line is 45°. Originality / scientific novelty. The novelty is improvement of the diagnostic algorithm for assessing trends in the agricultural insurance market in terms of transformational changes, taking into account the regression which made it possible to establish the dependences of variables among insurance indicators; validity of the use of direct selection with repeatedness of which the best possible state of the model is achieved. Practical value / implications. The comparison of the studied insurance indicators in the agricultural insurance market allowed determining the relationship between variables with the separation of their weight, which affect insurance contracts, which confirms the adequacy of the application of diagnostics which will be used during the evaluation of insurance contracts at enterprises of the agricultural insurance market.
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