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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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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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Artificial intelligence for crew scheduling in aviation sector

This research aims to relive the factors on applying AI in crew scheduling and rostering on low-cost airlines, IndiGO Airlines was chosen as base, to minimize the time and effort of human resources and increase effectiveness. This research looks into the possibility of utilizing artificial intelligence proposed model to schedule through a decision support system to reduce mistake from human intervention. Techniques employed includes of extensive literature searches, six qualitative interviews with two respondents per industry and 109 quantitative online surveys for crew scheduling department respondents. The data collected from the survey was analyzed and presented in the form of graphs to ease interpretation of the this research by concentrating on the challenges and costs involved in Artificial Intelligence. Thus, the techniques such as Data reduction and abduction logic have been used to find the sound information out of the whole set of information.From the survey results and interview questions, there are major benefits of incorporating AI in crew scheduling and rostering. The study also presents the best approach that low-cost airlines can adopt to lower errors and uphold performance, effectively showing that the adoption of AI in the industry is significantly beneficial

Author: Slavia Robert Kanjirethingal

Supervisor: Nadežda Spiridovska

Degree: Professional Master

Year: 2024

Work Language: English

Study programme: Aviation Management

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Apply a Machine Learning Model to Mitigate Bias in the Future AI-based Recruitment

In the contemporary landscape of Human Resources, the integration of artificial intelligence presents both opportunities and challenges, especially in the field of recruitment encompassing all stages of the process, from candidate sourcing to final selection. However, this integration is not without its challenges. Biased data, originating from historical data or societal prejudices, can present a significant obstacle, potentially perpetuating discriminatory practices. The study "Apply a Machine Learning Model to Mitigate Bias in the Future AI-based Recruitment" aims to comprehensively analyze existing biases from both human and artificial intelligence perspectives within the recruitment process. In its framework, answers to the research questions are sought: what are the existing biases in the recruitment process, both explicit and implicit, and how can biases in the recruitment process be effectively mitigated or eliminated through modeling techniques in future AI-based recruitments systems. Through a data-driven approach and the development of machine learning models, will be discover what kind of biases exist in the selection process and how to mitigate them.

Author: Ērika Todjēre

Supervisor: Jeļena Kijonoka

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

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