decision-making

This article delves into the pivotal role that business analytics plays in the era of Big Data, focusing on how it transforms decision-making processes in contemporary organizations. Big Data analytics has become an essential tool for businesses striving to gain a competitive edge in an increasingly data-driven world. The research outlines the main trends in the application of Big Data technologies, such as the integration of artificial intelligence (AI) and machine learning (ML), predictive analytics, and real-time data processing.

This article explores the advantages and challenges of implementing business analytics in corporate management. The study examines the current state and future prospects of the business analytics market, analyzing various types of analytics: descriptive, diagnostic, predictive, and prescriptive. The research highlights the key benefits of using analytical tools in business, such as improved forecasting accuracy, effective risk management, and business process optimization.

Purpose of the research. Exploration of the research gaps in order to understand how DAOs can encourage initiatives/practices to protect the interests of various stakeholders as well as identifying and comparing the main problems and prospects for creating and scaling DAOs in the existing economic realities. The following hypotheses that DAO is a form of science-oriented entrepreneurship and creates opportunities for involving unused entities in diverse   economic processes were analyzed.

Описано методології планування потреб у ресурсах. Проаналізовано програмні комплекси систем розподілу ресурсів і обґрунтовано потребу в розробленні своєї системи підтримки прийняття рішень. Проведено тестування прототипу СППР розподілу обмежених ресурсів, яка реалізує розроблені моделі та алгоритми.

Проаналізовано головні типи невизначеностей, які з’являються під час розв’язання задач сценарного планування. Запропоновано для подолання невизначе- ностей в задачах сценарного планування визначати інформаційні ситуації та відповідно до інформаційних ситуацій та типів невизначеності системно використовувати методи аналізу та прийняття рішень.

Nowadays, manufacturers must deal with huge international competition and continually improve their performances.  In this context, several essential approaches namely CBM (Condition-based maintenance), PHM (Prognostics and Health Management), and PLM (Product Lifecycle Management) are used for manufacturing systems to maintain and increase their availability, reliability and performance.  This implies that operational usage data of the manufacturing equipment must then be made available to all stakeholders concerned through efficient informational chains.  However confronted with a large a

Modern requirements to competitiveness, especially in the leading industries, set the priority of the development of enterprises in the energy sector.  Projecting the organizational development of power supplying companies are considered as a complex problem, which has the various technical and organizational components, the implementation of which involves non-trivial approaches and increased costs.  Therefore, to manage these projects is advisable to use a proactive approach and develop the specially adapted models and methods within the proactive management.  In order to ensure decision-

Game model of decision-making in hierarchical systems functioning in the conditions of aprioristic uncertainty it is constructed. The adaptive recurrent method and algorithm of stochastic game solving are developed. Computer modelling of stochastic game of decision-making in hierarchical system with structure of a binary tree is executed. Influence of parameters on convergence of a game method is investigated.

The system aspects of optimality problem within the framework of the structure of decision-making process, connecting it with DM models and tasks, theoretical and practical aspects of optimal solution peculiarity were analyzed. The analysis entropic specification and their impact on the optimal level of practical decisions was made. The DM methods specifications in context of optimal decisions-making were compared, the consumption of partitioning and threshold method, as one of the most flexible for decision-making in different conditions were justified.