"Scientific research" Almanac

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  RESEARCHING THE POTENTIAL OF BIG DATA AND IOT FOR DEVELOPING AN INTELLIGENT BUSINESS ENVIRONMENT

  With the growing penetration of digital technologies and their increasing importance for businesses, Big Data and the Internet of Things (IoT) have become key concepts driving business transformation. These technologies enable the real-time collection, processing, and analysis of massive volumes of data, creating conditions for building ... With the growing penetration of digital technologies and their increasing importance for businesses, Big Data and the Internet of Things (IoT) have become key concepts driving business transformation. These technologies enable the real-time collection, processing, and analysis of massive volumes of data, creating conditions for building intelligent business environments. The purpose of this study is to examine and analyse the potential of Big Data and IoT for building an intelligent business environment in Bulgaria. To achieve this goal, the following tasks have been established: assessing the knowledge and understanding of these technologies between two major groups of specialists – IT professionals and business managers; and investigating the significance of Big Data and IoT in business process transformation. The main research thesis is that the integration of Big Data and IoT leads to significant improvements in efficiency, innovation, and management decision-making. The study employed a mixed strategy, which included structured interviews with experts and quantitative analysis of the obtained data. The results indicate that, despite the respondents' extensive experience in IT and management, the ideas of IoT and Big Data Analytics (BDA) are new to some of them, requiring extra training and clear standards for implementation. IoT and BDA have been regarded as critical to operational efficiency and corporate transformation, but issues such as integration, data security, and network management remain. A clear definition of project goals and roles, as well as an emphasis on automation and cross-departmental collaboration, are essential for the successful implementation of these technologies.

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  SAFETY AND SUSTAINABILITY OF EVENT TOURISM IN BULGARIA

  The aim of this study is to conduct a systematic analysis of sustainability measures and security and safety aspects related to the implementation of event tourism in Bulgaria as a tourist destination. This goal is achieved through several research tasks: a theoretical review of the existing contemporary literature in the field of the research ... The aim of this study is to conduct a systematic analysis of sustainability measures and security and safety aspects related to the implementation of event tourism in Bulgaria as a tourist destination. This goal is achieved through several research tasks: a theoretical review of the existing contemporary literature in the field of the research problem; the development of the structure and design of the study, along with the selection of appropriate methodology; the research and collection of data on the safety and sustainability of the destination, as well as information on the current state of event management issues; and the analysis of the results of the study, summaries and formulation of conclusions. The study is based on two levels of research. The first level concerns the security, safety and sustainability of the destination in which event tourism is implemented, and the subject of the second level is the organisation of events and the behaviour of consumers. This approach allows covering those aspects of the implementation of event tourism in which the connections with sustainability and security and safety have a certain significance. The object of the study is event tourism in destination Bulgaria, and its subject is the degree of safety and sustainability in organising and conducting. The theoretical foundation is built on scientific publications by established authors in reputable journals, with scientific review, as well as strategic and planning documents of leading world organisations directly involved in the researched issues. The methodology employs a mixedmethods approach, utilising both qualitative and quantitative techniques. The results of the study confirmed the thesis that the implementation of event tourism, in which a level of security and safety is ensured and is carried out in accordance with the principles of sustainability, is a consequence of ensuring these characteristics at the destination level, as well as at the event management level. It is established that sensitivity to security and safety is stronger than reactions to the dimensions of sustainability.

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  AUTOMATIC ALGORITHMS FOR ARIMA MODEL IDENTIFICATION IN TIME SERIES FORECASTING: A LITERATURE REVIEW

  Forecasting plays a crucial role in effective planning and management within both the economic and public sectors, especially in a rapidly evolving environment. Despite its importance, producing accurate forecasts requires considerable expertise and is a labourintensive process prone to subjective errors, especially when processing large ... Forecasting plays a crucial role in effective planning and management within both the economic and public sectors, especially in a rapidly evolving environment. Despite its importance, producing accurate forecasts requires considerable expertise and is a labourintensive process prone to subjective errors, especially when processing large volumes of data. These challenges make the role of automation of forecasting processes increasingly necessary in modern practice. The objective of this study is to derive the advantages and shortcomings of various automatic algorithms for ARIMA model identification and to determine the extent to which these algorithms reduce subjectivism in the modelling process. The research includes three main tasks: (1) to justify the necessity of automation of the forecasting process and reveal the challenges to its implementation, as well as to trace its evolution; (2) to motivate the automation of ARIMA model identification on the basis of revealing their nature and the key stages in the modelling process; (3) to present and compare automatic approaches that solve ARIMA model identification challenges in order to further evaluate their effectiveness and applicability. The results of the study show that automated ARIMA algorithms provide high accuracy and reliability of forecasts, significantly reducing the time and resources required for the analysis. In addition, automation facilitates adaptation to changing data and conditions, which is key to making timely decisions in a dynamic environment. The findings of this study can assist organisations in selecting appropriate automated methods for time series forecasting.