Decision tree as a tool for implementing a scenario approach for multi-level predictive models

Abstract

The paper presents a decision-making method for a quantitative income estimation depending on the intensity of the future tourist flow, as a complex indicator reflecting the level of the tourist market in a region or in a separate object (a hotel complex, sanatorium, tourist base, etc.). The authors proposed to use a three-level economic and mathematical model as a practical implementation of the hotel complex room stock management process. Each its level corresponds to a specific task. At the first level it is a pre-forecast study, substantiation and selection of forecasting models. At the second it is a forecast model and the quantitative value of the predicted indicator. At the third level it is a model tohelp a decision maker (DM) with decision making, i.e., a decision tree is applied as a tool. Thus, the authors present a complete system of models and methods of decision support. The results of pre-forecast analysis, development of predictive models, building, adaptation and implementation of top-level economic and mathematical models will help decision makers to make effective management decisions. There by the maneuver material resources, choose sales technologies and search for economic solutions, including in tourism recreational production activities.

Innovative methods and tools for obtaining pre-forecast information in the socio-economic processes research

“…The approbation of the software package was carried out on the basis of real data on the volume of the tourist flow to the ski village Dombay [10]. The pre-forecast information quantitative values and qualitative characteristics for the values of the tourist and recreational activities modeling lower level are obtained, which in turn are input data for the predictive models of the tourist and recreational activities management upper level (employment planning and the number of rooms booking), which becomes a particularly important fact in conditions for the development of domestic tourism in the existing framework of the epidemiological situation [7]. The synergistic effect obtained from the complex socio-economic processes research in the context of the triad results is important: the initial time series, a number of its increments and aggregated data.…”

“…The article presents the development of the information system for the complex socio-economic processes pre-forecast analysis by the method of the time series studying local fluctuations [6,7,9,11,12]. To visualize the model and describe all the actions performed by the developed program, the authors use a number of tools that allow to simulate actions in processes, to determine their order and the necessary resources.…”