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Evaluation of Personnel Training System in an Organization

Personnel training is crucial for enhancing organizational performance and achieving strategic objectives. Evaluating training programs involves analyzing the knowledge gained, skills acquired, and overall employee development. This evaluation helps determine whether financial investments in training are justified and predicts the rationality of further investments.This research aims to evaluate training programs in airlines, focusing on their unique training systems and developing recommendations for improvement. The study has three main objectives:• Explore theoretical aspects of personnel training systems in modern enterprises, emphasizing the concept of a learning organization.• Analyze and evaluate existing personnel training programs through case studies of two organizations.• Develop recommendations to enhance the effectiveness of personnel training systems.The analysis of theoretical aspects and existing training systems highlights current strengths and weaknesses. Based on these insights, specific recommendations have been developed to improve personnel training programs. These guide HR managers in optimizing training practices and fostering continuous improvement, enhancing individual performance, and contributing to the organization's strategic objectives.

Author: Aaliyah Lyubov Mikhaylova

Supervisor: Ishgalei Ishmuhametov

Degree: Master

Year: 2024

Work Language: English

Study programme: Business and Management

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Risks Factors Affecting Transparency of Trading Activities in Financial Market

Research goal is to determine the risk factors affecting the transparency of trading activities of financial institutions in financial markets.Research object is transparency of trading activities in the financial market.Research subject is risk factors’ effect on trading activities of financial institutions.Chapter 1 provides an overview of the financial industry in Latvia.Chapter 2 covers theoretical review of risk management and market transparency of trading activities in the financial sector.Chapter 3 chapter is analytical and provides information about the risks affecting market transparency in trading operations.

Author: Aleksandra Fesjuka

Supervisor: Jeļena Popova

Degree: Master

Year: 2024

Work Language: English

Study programme: Business and Management

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Improvement of machine leaning algorithms performance by data set dimensionality reduction using cellular automata

A significant challenge in Machine Learning is dealing with high-dimensional data. Complexity knowns as the "curse of dimensionality" results in deterioration оf Machine Learning algorithms performance as the dimensionality and dataset size increases. Cellular automata are a dynamical discrete computational system with mathematical functions knows as rules that result in complex global behaviour. We used one-dimensional elementary cellular automata as a tool for dataset size. Model variables were selected for initial status vector generation and its further transformation to format that is suitable for cellular automata rules application known in cellular automata theory as configuration. Then model iterated through all possible cellular automata rules and various epochs variations were applied. Model performance for reduced dataset was compared with benchmark results of original dataset after standard dimensionality reduction technics used. It was concluded that applied cellular automata rules can be used as alternative methods for dataset size reduction without deteriorating model performance.

Author: Alexey Kuchvalskiy

Supervisor: Dmitry Pavlyuk

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

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Change management in catering companies in the context of the digital economy

The first chapter describes that based on digital platforms as the main factor of production, labor relations and labor functions are being transformed. In the modern economy, various industries and activities are being transformed, new industries are being formed, based only on the use of new technologies.The second chapter describes that the catering sector is very competitive in the Latvian market. In the context of transformation of the labor market, there are changes in the requirements for employees, which are associated with their personal development and desire for personal growth. Digitalization is transforming existing jobs, requiring workers to have new skills to perform new tasks, requiring continuous training.The third chapter describes that in a market economy, digital business transformation can drive growth, productivity and competitiveness. Digitalization allows us to minimize the risk of human error and free up specialists’ time to solve more important issues.The fourth chapter analyzes the main activities and problem areas of the enterprise, analyzes and proposes promising concepts for personnel management of an existing enterprise in the Latvian public catering market, since in modern changing conditions personnel are the key asset of the enterprise.

Author: Alīna Uļjanovska

Supervisor: Oksana Skorobogatova

Degree: Master

Year: 2024

Work Language: English

Study programme: Business and Management

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Use of Artificial Intelligence in Human Resource Management

The integration of Artificial Intelligence into Human Resource Management processes presents an evolving domain of exploration and practical application. The widespread adoption of AI technologies presents the potential for significant transformations in products, innovation processes and business models. The research aim is to develop a framework for effective use of AI in Human Resource Management. The subject of the research is AI-based solutions in Human Resource Management. The object of the research is Human Resource Management processes in an enterprise.A multifaceted research approach was used to scrutinize the effective utilization of AI in HRM: Literature review, Case Studies, Employee Surveys, Interviews with HR experts.During this research, the author highlighted aspects of contemporary HRM that can be improved using AI technologies; made a list of the recommended practices for integrating AI-based solutions into HRM; developed a framework for AI tools implementation and found out that HR experts’ and employees’ overall perspective on AI within HRM appears optimistic.This research holds both theoretical and practical significance, driving advancements in theoretical knowledge, informing organizational practices, and shaping the future of work in the digital age.

Author: Ana Enache

Supervisor: Yulia Stukalina

Degree: Master

Year: 2024

Work Language: English

Study programme: Business and Management

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