"Scientific research" Almanac

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  ANALYTICAL MODELS APPLICABLE IN ASSESSING THE FINANCIAL SUSTAINABILITY OF ENTERPRISE

  Forecasting the financial sustainability of enterprises is a priority problem in the context of modern economic and social conditions. Analytical models that are constructed through discriminant analysis provide an opportunity to predict financial sustainability. Their testing in our country would contribute both to the enrichment of the theory of ... Forecasting the financial sustainability of enterprises is a priority problem in the context of modern economic and social conditions. Analytical models that are constructed through discriminant analysis provide an opportunity to predict financial sustainability. Their testing in our country would contribute both to the enrichment of the theory of economic analysis and to the timely detection of the risk of deteriorating financial stability of existing enterprises. In a dynamic and unpredictable environment, attention should be paid to sustainable development procedures, which will help clarify the obligations of investors and increase transparency on the part of financial institutions and companies regarding how they consider sustainable development in the decision-making process. of solutions. In this regard, analytical procedures are established as a particularly important component of the audit, due to the interest of clients not only in their current state, but also in the growth prospects. Such predictions could be made if the assumption that the company will remain operational for the foreseeable future is substantiated beforehand. In the field of statutory audit, one of the main objectives of the EC is: improving the information value of audits for investors and assessment of enterprises. The results of the application of analytical models for assessing the financial sustainability of enterprises can be particularly useful in their timely use to make informed decisions in the field of internal and external control.

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  UNCOVERING SHOPPING PATTERNS IN BIG DATA ENVIRONMENTS

  In this study, we present the feasibility of applying selected algorithms to rapidly detect regular, common, and recurring patterns of shopping behavior for products or services purchased simultaneously and/or in some temporal sequence. Such analyses are often defined by the term „'market basket analysis“. The object of the present study is the ... In this study, we present the feasibility of applying selected algorithms to rapidly detect regular, common, and recurring patterns of shopping behavior for products or services purchased simultaneously and/or in some temporal sequence. Such analyses are often defined by the term „'market basket analysis“. The object of the present study is the analysis of large data sets of sales transactions observed across multiple individual acts of purchase, and the subject matter is the discovery of the capabilities of some numerical algorithms from the field of machine learning to detect hidden patterns in acts of purchase by processing data from individual customer „market baskets“. The goal is to convince the reader of the possibilities of extracting association rules from big data through demonstrations with publicly available open data. The exposition follows a „concept-to-application“ logic and consistently provides answers to the questions of „why“ it is necessary to do it, „what“ it is done with, and „how“ it is done. After a brief introduction to the logic and specifics of the most popular algorithms for discovering patterns by extracting association rules from large datasets, we provide detailed working procedures and instructions for analyzing and interpreting the analytical results. Finally, we provide a synopsis and provide guidelines and recommendations for using the analytical procedures in a marketing context.

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  BENEFIT SEGMENTATION OF BULGARIAN TOURIST

  The peculiarities of consumer behaviour is of key importance for the successful customer centric approach implementation in tourism marketing. The majority of existing studies focused on Bulgarian tourist market groups customers on the basis of the tourist nationality or the type of tourism practiced. Insufficient researched remains attitudes and ... The peculiarities of consumer behaviour is of key importance for the successful customer centric approach implementation in tourism marketing. The majority of existing studies focused on Bulgarian tourist market groups customers on the basis of the tourist nationality or the type of tourism practiced. Insufficient researched remains attitudes and expectations. The study aims to segment Bulgarian tourists by using benefit segmentation approach. Benefits are described via 16 binary variables. Data is collected via online survey with 858 valid respon¬ses. The segmentation was performed by cluster analysis. Segments identification is made both by hierarchical and non-hierarchical clustering algorithms. The existence of five segments has been proven. They are profiled on the base of socio-demographic and behavioural characteristics. Recommendations for using the information from the study in business practice and scientific researches are formulated.