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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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Company Ekl/Ls Ltd personnel selection and recruitment system's procedure improvement

Company Ekl/Ls Ltd personnel selection and recruitment system's procedure improvement.The aim of the paper is to collect information on the process of search, attraction and selection of personnel, to identify the shortcomings of the process of search and selection of personnel on the example of EKL/LS Ltd. and to provide recommendations for their improvement.In accordance with the aim of the work, the following tasks were set:To look at the theoretical foundations of recruitment and selectionTo identify the characteristics of EKL/LS Ltd.To analyse the management system of EKL/LS Ltd.To analyse the recruitment and selection system of EKL/LS Ltd.Identify the main problems in recruitment and selection at EKL/LS Ltd.Develop recommendations for improving the recruitment and selection system at EKL/LS Ltd.

Author: Anastasija Horoļska

Supervisor: Tamila Mišāne

Degree: Bachelor

Year: 2024

Work Language: Latvian

Study programme: Business and Management

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Remote control of a robot manipulator by tracking human hand motion and gestures

Šī darba mērķis ir izveidot televadības sistēmu manipulatora robotam, izmantojot roku žestus un pozas. Tajā būs iekļauta žestu bibliotēka, lai interpretētu roku žestus un nosūtītu komandas robotam. Šī pieeja atvieglotu un paātrinātu mijiedarbību ar robotizētām sistēmām, padarot nepieciešamas minimālas sarežģītas ievades ierīces un plašas apmācības prasības.

Author: Antons Tjurins

Supervisor: Emmanuel Alejandro Merchan Cruz

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Robotics

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Unsupervised machine learning approach for hierarchical graph-based representation of natural language text collections.

Managing big data efficiently is important in various fields, much so when data consists of human-written documents. Recent advances in Natural Language Processing (NLP), particularly LLMs, allowed to solve many task in this domain, despite the high demand for labelled data, compute resources and specialized skills.To tackle these limitations, current study proposed a NLP pipeline to identify topic hierarchies in collections of scientific publications. The work focused on evaluation of available unsupervised machine learning methods and quality metrics in NLP, and development of visualization techniques to build a prototype of the pipeline.Proposed solution is based on the hARTM approach optimized for interpretability. It demonstrated the capacity to infer human-interpretable topic hierarchies from collections of scientific texts and construct meaningful hierarchy of topic-based document representations. The visualization approaches rely on MDS to present inter-document similarity and Sankey plots to show document cluster relatedness within topic hierarchy.Utility was demonstrated on two datasets, focusing on interpretability and meaning of the topic hierarchy and associated topic definitions. Potential application areas include personal education and scientific writing.

Author: Jevgenijs Bodrenko

Supervisor: Irina Jackiva

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

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