Master's capstones / Магістерські завершальні проєкти (capstones)

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A SUBSYSTEM OF THE INTEGRATION OF THE EDUCATIONAL PORTAL WITH THE LLM-BASE EDUCATIONAL CONTENT GENERATION SYSTEM
(2024) Ivchenko, Oleksandr
LLM models have created a new era of learning and teaching methodologies. This article examines the profound impact of LLM models on the educational environment. The study explores their integration in various educational settings and highlights their universal application and transformative potential. LLM models have the potential to bridge gaps in education, provide an alternative perspective, generate high-quality resources, and provide exclusive education for people with different learning needs. The study highlights the potential of combining technology and human experience to create an enriched learning ecosystem. The future of learning, shaped by artificial intelligence technologies, promises an improved educational experience.
ANALYSIS OF INVESTMENT STRATEGIES FOR DRONE MANUFACTURING ON EXAMPLE OF AILAND SYSTEMS
(Manuscript, 2025) Tyshchenko, Daria
The drone manufacturing industry is one of the most dynamic and rapidly evolving sectors worldwide. It plays a vital role in defense, agriculture, logistics, and construction, with growing demand fueled by advances in technologies and AI. The full-scale war in Ukraine, along with these technological shifts, accelerated the need for enhanced drone capabilities. Ukraine's drone sector has demonstrated rapid growth since the start of the full-scale war in 2022, driving innovation and local production. International and local investors, venture capital firms, business acceleration, and government programs have increasingly supported this growth. However, the industry faces challenges, including supply chain reliance on China, regulatory hurdles, war-time risks, and export limitations. This capstone explores strategic investment opportunities in drone manufacturing, focusing on Ukraine. Through a financial analysis of Ailand Systems as a case study and risk and opportunities analysis using the PESTEL model, it provides insights into investment potential and strategic directions. The report is structured to first review the global market, then analyze investment opportunities, analyze a case study of Ailand Systems, identify industry challenges, and offer actionable recommendations for drone manufacturers on the example of Ailand Systems.
ANALYZING THE IMPACT OF AI ON THE DECISION-MAKING PROCESS IN MODERN MILITARY OPERATIONS IN THE KILL CHAIN FRAMEWORK
(Manuscript, 2025) Osaulenko, Volodymyr
This capstone project explores the transformative impact of artificial intelligence (AI) on decision-making processes within modern military operations, focusing on its integration into the Kill Chain framework. The research investigates key questions regarding the optimization of decision cycles and the role of AI in enhancing operational effectiveness. Participants in this study include an array of real-world applications, including unmanned aerial vehicles (UAVs) and AI-augmented weaponry. Through qualitative analysis and case studies, this research examines how AI technologies, such as machine learning and neural networks, can automate critical stages of the Kill Chain—detection, tracking, targeting, engagement, and assessment. The findings demonstrate that AI significantly shortens decision-making timelines, enhances precision in engagements, and ensures adaptability under complex battlefield conditions. A practical scenario featuring autonomous drone swarms illustrates these advantages, emphasizing resilience against electronic warfare and the ability to operate independently of human oversight. The results underscore the dual nature of AI in military contexts: while it offers unparalleled efficiency and operational gains, it also raises critical challenges related to accountability, ethical compliance, and legal frameworks. This research concludes with recommendations for developing transparent oversight mechanisms and fostering international cooperation to govern AI integration responsibly.
APPLICATION OF OPENAI API FOR SEMANTIC CONTENT ANALYSIS IN INTELLIGENT E-LEARNING SYSTEMS
(2024) Rybak, Mykola
The thesis aims to describe the practical aspects of using OpenAI API in intelligent e-learning systems. The proposed work contains three main parts. The first part covers a background overview, theoretical aspects of a Large Language Model (LLM), transformer-based Natural Language Processing (NLP) architecture description, and use cases of different transformers. Introduces the term semantic unit and defines its main elements and connection with the capstone project. The second part concerns the rationale of the chosen model’s type for the capstone project and its description and implementation. This part covers requirements for the capstone project, C4 architecture diagrams, an overview of essential modules, libraries, and code examples of the implemented solution leveraging OpenAI API. The final part demonstrates further research on architecture improvements for better semantic content analysis and interaction with intelligent e-learning systems, including a combination of encoder-decoder and embedding models in the solution.
ASSESSING THE IMPACT OF AI INTEGRATION ON BUSINESS EFFICIENCY AND PROFITABILITY: A CASE STUDY ANALYSIS
(Manuscript, 2025) Tkachuk, Oksana
The objective of this research is to evaluate how artificial intelligence (AI) can enhance business productivity and efficiency, particularly in response to the labor shortage crisis. This shortage is driven by demographic shifts, economic and social factors, skills mismatches, economic uncertainties, and evolving work preferences. Industries such as technology, healthcare, manufacturing, construction, finance, and education are most affected. AI technology has the potential to address these challenges, as evidenced by reports indicating significant improvements in productivity and potential GDP growth. This research aims to assess the impact of AI on business efficiency and profitability using real-case examples and modeling through Profit and Loss Financial Statements. The object of research in this study is the impact of AI technologies on business operations, with a focus on management-related aspects such as operational efficiency, financial performance, and strategic integration. The research addresses the critical challenges posed by global labor shortages and evaluates how AI can transform managerial processes to enhance productivity, profitability, and competitiveness. The study will examine AI's effects on operational efficiency, and financial performance, and provide a framework and roadmap for successful AI integration.
CHALLENGES OF TRANSFERRING BUSINESS PRACTICES: THE CASE OF “ECOSERVICE 2022” AND “BAV”
(2024) Zhuravel, Taras
This study analyzed the challenges of transferring business practices by conducting a case study involving two companies, examining the practical application of cross-cultural knowledge transfer and evaluating its effectiveness using the Kirkpatrick model. The significance of this research lies in its practical implications for organizations aiming to transfer business practices across different cultural contexts. The paper contributes to the existing body of knowledge by offering specific insights into the transfer of business practices from BAV to Ecoservice. By employing the Kirkpatrick model, the research provides valuable recommendations for fostering successful transfer of business practices in a globalized world.
CHALLENGES OF WOMEN’S LEADERSHIP IN PUBLIC SERVICE IN UKRAINE: THE CASE OF THE DIGITAL TRANSFORMATION
(2024) Onyiliogwu, Kateryna
This research study investigates the discrepancies between male and female leadership in Ukraine's public sector, focusing on the challenges that female leaders face in digital transformation. The Critical Incident Technique is used to analyse the experiences of ten senior female professionals working in the Ministry of Digital Transformation through semi-structured interviews. The study's key findings highlight a range of challenges that female leaders face, such as societal, organisational, interpersonal, and individual. This study fills a critical gap in the literature regarding women in leadership within the public sector, particularly in the digital transformation sphere. It contributes valuable insights to the broader discussion on gender diversity in Ukraine's public sector leadership.
COMPARISON OF ARCHITECTURAL PATTERNS WITHIN iOS APPLICATIONS
(2024) Skrypchenko, Mykyta
This work delves into the strategic selection of software architecture for iOS applications, underscoring the alignment of architectural decisions with specific project constraints and goals. Initial discussions centered around the challenges in using software metrics to compare various iOS architectures, leading to the proposal of a simplified framework aimed at aligning architectural choices with defined business objectives. The paper details the process of evaluating different architectural patterns — MVC, MVVM, VIPER, and TCA — considering these constraints and goals. This work contributes to the field by providing a practical example of how architectural decisions can be tailored to specific project constraints and goals, offering insights that can be valuable for software architects and developers working on similar Swift application projects.
CONSULTING ENGAGEMENT FOR A SOFTWARE ENGINEERING SERVICES COMPANY: TRANSITIONING FROM INBOUND LEAD GENERATION TO ACCOUNT-BASED MARKETING FOR ENHANCED B2B LEAD CONVERSION
(Manuscript, 2025) Makarchuk, Roman
This capstone project explores a consulting engagement with a software engineering services company aiming to transition from traditional inbound lead generation to a more strategic account-based marketing (ABM) approach. The company faced challenges with low-quality inbound leads and inconsistent B2B lead conversion rates, prompting the shift to ABM—a targeted strategy focusing on high-value accounts to improve engagement, alignment, and revenue outcomes. The consulting project involved three primary phases: problem statement and assessment, ABM implementation, results and observations. In the problem statement and assessment phase, existing inbound marketing efforts were evaluated, revealing misaligned targeting, lack of personalization, and weak sales-marketing collaboration. During the ABM implementation phase, the company’s Ideal Customer Profile (ICP) was refined, target accounts were identified, and a multi-channel ABM outreach plan was developed, including personalized content creation, stakeholder mapping, account-specific campaigns, and the integration of sales and marketing technologies. The results and observations phase focused on measuring and comparing performance metrices and drawing conclusions from the ABM approach adoption. Initial results demonstrated significant improvements in key performance indicators (KPIs) such as engagement rates, lead conversion, and pipeline processing efficiency. The ABM approach also better alignment between sales, marketing and presales teams, enabling more efficient resource allocation and higher deal closure rates. This project concludes that transitioning from inbound lead generation to ABM can significantly enhance B2B lead conversion for software engineering services companies. It highlights the importance of focusing on target accounts, building up stakeholder engagement, and cross-functional collaboration in achieving ABM success. Insights from this engagement provide a roadmap for other organizations considering a similar strategic shift to optimize their sales and marketing efforts.
CULTURAL INFLUENCE ON BARRIERS AND FACILITATORS OF KNOWLEDGE TRANSFER PRACTICES WITHIN MULTINATIONAL ORGANIZATIONS
(2024) Vyshnyvetskyy, Ivan
Knowledge transfer is critical for multinational corporations to leverage expertise and achieve organizational success across geographically dispersed teams. However, cultural differences between countries can impede effective knowledge sharing. This quantitative study aimed to elucidate how national and corporate cultural dimensions influence knowledge transfer behaviors within multinational organizations. A survey was conducted with 59 employees from managerial and clinical research roles across six European countries in a multinational pharmaceutical firm. Participants completed validated instruments measuring cultural values based on the GLOBE model, and readiness for knowledge transfer initiatives based on the Theoretical Domains Framework. Results of correlation and regression analyses found that higher in-group collectivism, performance orientation, and lower power distance cultural values were associated with greater readiness for knowledge transfer. Interestingly, younger yet more experienced employees exhibited higher openness to knowledge initiatives. There were also notable correlations between specific cultural dimensions and behavioral domains influencing knowledge exchange. These findings suggest national and corporate culture fundamentally shape employees' readiness for knowledge transfer. The results have important implications for organizational leaders seeking to implement effective knowledge management strategies across global teams. Fostering collectivistic, egalitarian and achievement-oriented cultural values may pave the way for smoother knowledge transfer. Overall, a multifaceted approach considering both cultural and individual factors is key for optimizing knowledge flows within multinational corporations. The study makes a useful contribution by providing quantitative empirical evidence linking cultural values to knowledge exchange behaviors. However, limitations like the small sample size from one organization indicate findings may have restricted generalizability. Further research with larger, more diverse samples is critically needed to validate and extend the results across various cultural contexts.
CUSTOM CRM SYSTEM FOR A LEGAL DEBT COLLECTION COMPANY
(2024) Bairaktar, Dmytro
DATA ANALYSIS AND LANGUAGE MODELS FOR D2C APPLICATIONS IN FOREIGN LANGUAGE LEARNING
(2024) Andriychuk, Sergiy
The landscape of foreign language learning has undergone a significant transformation in the digital age, particularly with the emergence of Direct-to-Consumer (D2C) applications. Relevance of the Topic At the forefront of educational technology, the integration of data analysis and language models in D2C language learning applications like WORDY represents a significant leap. Objective The primary objective of this study is to enhance the WORDY application for foreign language learning through the integration of advanced data analysis techniques and sophisticated language models. Structure of the Report This report offers a comprehensive analysis of the application of data analysis and language models in the WORDY application. It starts with a detailed literature review, leading into an exploration of the WORDY application's design. This design incorporates a thoughtful selection of technologies and frameworks to ensure optimal performance and user experience.
DECISION-MAKING AND RISK MANAGEMENT IN THE UKRAINIAN VENTURE CAPITAL ECOSYSTEM DURING WARTIME
(Manuscript, 2025) Dumych, Taras
Venture capital has played a significant role not only in the success of individual companies and industries but also in the economic success of entire countries, as evidenced by the experience of the United States. This study explores the decision-making and risk management strategies employed by venture capital firms within Ukraine's venture capital ecosystem. Specifically, it examines the impact of war on the functioning of this ecosystem and its players. The analysis draws on a combination of literature focused on venture capital and risk management, as well as practical insights gathered from survey interviews conducted with ten top executives of venture capital firms. By integrating both theoretical and practical perspectives, this study offers a comprehensive understanding of the subject.
DEVELOPING A GO-TO-MARKET STRATEGY FOR A UKRAINIAN FURNITURE MANUFACTURER
(Manuscript, 2025) Chernii, Volodymyr
This Capstone project focuses on developing a go-to-market strategy for a Ukrainian furniture manufacturer seeking to enter the niche market of furniture adapted to the needs of people with functional disorders. Driven by increasing demand, particularly in the context of post-war rehabilitation for veterans, the project aims to explore market opportunities, understand customer needs, and recommend actionable steps for market entry. The research employs a combination of qualitative methods (expert interviews) and environmental analyses (PESTEL and Porter’s Five Forces) to assess the external and micro environmental factors influencing the Ukrainian furniture industry overall. Insights from experts in universal design, rehabilitation therapy, and inclusivity highlight critical needs, such as ergonomic, modular, and height-adjustable furniture that balances functionality and aesthetics. The market for adaptive furniture in Ukraine remains underdeveloped, creating opportunities for first-movers. Potential customers in B2C include individuals with functional disorders and members of their households, while the B2B segment encompasses rehabilitation centers, public spaces, and NGOs. Critical product features include customizable designs to meet specific needs, affordability to overcome market barriers, and aesthetics to encourage adoption. The project concludes with a set of strategic recommendations to position the Client as a leader in inclusive furniture design, which could be achieved through cost-efficient product development, customer-centric solutions tested in rehabilitation centers, and close collaboration with experts in the field. Further steps are associated with profiling consumers and their needs through online surveys, developing MVPs, and testing these in focus groups.
DEVELOPING A STRATEGY FOR AN ORGANIZATION IN UKRAINE’S GRAIN MARKET CONSIDERING THE IMPACT OF THE WAR ON TRADE (CASE STUDY)
(Manuscript, 2025) Krechkevych, Igor
The ongoing war in Ukraine has caused significant disruptions to the nation’s grain market, affecting production, supply chains, and export capabilities. This capstone examines the strategic challenges and opportunities faced by Kernel Holding S.A., a leading agribusiness company in Ukraine, amidst these unprecedented conditions. Utilizing a combination of qualitative and quantitative research methods, the study evaluates Kernel’s market position, the impact of the war on its operations, and potential strategies for resilience and growth. Key findings highlight Kernel’s ability to adapt through diversification of export routes, technological investments, and sustainability practices. Strategic recommendations include short-term operational adjustments, mid-term market expansion, and a long-term focus on innovation and sustainability. These insights not only provide actionable strategies for Kernel but also contribute to broader discussions on crisis management and food security in volatile global markets.
DEVELOPMENT OF SOCIAL AND EVENT MANAGEMENT DISTRIBUTED APPLICATION
(2024) Kulomin, Dmytro
Purpose of this work is a creation of the product helping people and business to find each other, plan and organise activities and events. During the work on the problem different use-case were analysed and matched against existing solutions on the market. Work consists of observation of current state of industry, available products comparison, fit map creation and main use-cases identification. The result of the work is presented by the engineering solution in the form of main architectural decisions, storage and communication approaches analysis and the proof of concept implementation.
EFFECTIVE NEGOTIATION STRATEGIES FOR SUCCESSFUL IMPLEMENTATION OF PROJECTS IN THE RENEWABLE ENERGY SECTOR: THE CASE OF DTEK RENEWABLES
(Manuscript, 2025) Boiko, Serhii
This study examines effective negotiation strategies for implementing renewable energy projects, using DTEK Renewables as a case study. The research explores how negotiation processes shape project outcomes, focusing on stakeholder collaboration, transparency, and conflict resolution. The primary research question investigates the negotiation strategies contributing to project success in a complex, multilateral setting. Participants included project managers, investors, government officials, and community representatives engaged in DTEK Renewables' initiatives. Semi-structured interviews were conducted, yielding qualitative data analyzed through thematic analysis. Key themes identified include transparency, trust-building, strategy adaptation, and conflict management. Results highlight that transparency in sharing project information fosters trust among stakeholders. Trust enables flexibility in adapting negotiation strategies to various stakeholder needs. Conflict management, through facilitation and mediation, minimizes opposition and promotes mutually beneficial agreements. These interconnected elements form a "negotiation value chain" leading to successful outcomes. Data analysis underscores the importance of tailoring negotiation approaches to context-specific factors, such as cultural nuances and regulatory environments. While the study focuses on Ukraine, findings have broader implications for global renewable energy projects. Conclusions advocate for integrating transparency, trust, and context-sensitive strategies in project negotiations. Practical recommendations include public consultations, creating feedback mechanisms, and engaging independent mediators. Future research could quantify the impact of these strategies and compare them across international contexts to assess their universality.
EFFECTIVE STRATEGY PRIORITIZATION FOR SMES IN CRISIS MANAGEMENT: APPROACHES TO RESILIENCE AND RECOVERY
(Manuscript, 2025) Ponomarenko, Mykhailo
This research explores crisis management strategies employed by small and medium-sized enterprises (SMEs) in Ukraine to ensure survival and growth during severe disruptions, such as the ongoing war and prior global crises like COVID-19. The primary research questions include: How can SMEs effectively manage crises to remain resilient? What risks do they face, and what strategies mitigate these risks? The main aim of the study is to examine the crisis management strategies employed by small and medium-sized enterprises (SMEs) in Ukraine during severe disruptions and to identify actionable frameworks to enhance their resilience and recovery. The object of the research is the crisis management strategies and management practices of small and medium-sized enterprises (SMEs) in Ukraine, accumulated from the experience of Ukrainian enterprises, particularly during periods of severe disruptions such as economic instability, armed conflict, and other critical challenges. The study is based on qualitative interviews with SME owners and managers across various industries, supplemented by insights from international reports and surveys. Participants shared their experiences with challenges such as operational disruptions, financial instability, market shifts, and workforce retention issues. Key strategies adopted during the crisis included operational flexibility (employed by 75% of participants), digital transformation (70%), and market diversification (60%). Post-crisis recovery focused on sustainable practices and organizational culture enhancement, which participants identified as drivers of long-term resilience.
ENHANCING THE LEVEL OF MOTIVATION AMONG MILITARY PERSONNEL IN ORDER TO IMPROVE TASKS FULFILLMENT EFFICIENCY
(Manuscript, 2025) Shevchenko, Oleksander
Motivation of military personnel is a key factor in ensuring the effectiveness and combat readiness of a modern army. It has a direct impact on morale, commitment and performance, determining their ability to perform effectively in challenging environments. Understanding the motivational factors that drive military personnel to join the army, continue their service, or achieve high performance is important for strategic planning and maintaining the effectiveness of defense structures. Existing research on motivation in the military sphere is mainly focused on armies involved in conflicts on the territory of other states, such as peacekeeping missions or interventions abroad. However, such results often do not take into account the specifics of armies operating in the defense of their own territory, where the stakes are much higher both at the individual and collective level. This paper examines the impact of material and non-material incentives on military personnel motivation, with a focus on comparing the effectiveness of different types of incentives, such as cash bonuses, social benefits, medals, and career opportunities, as well as non-material factors such as recognition, team support, and psychological resilience. The study complements the existing work on motivational factors by analyzing their effectiveness in modern conditions and comparing theoretical models with empirical data. The methods used include a literature review and surveys of military personnel, which allows us to offer recommendations for increasing mobilization efficiency, improving service conditions, and reducing the level of unauthorized abandonment of units. The results showed that material incentives meet the basic needs of military personnel and are critical, but their effectiveness is reduced without the support of non-material aspects. Non-material incentives, such as recognition, team support, and leadership from commanders, have a lasting positive impact on morale and performance. Unit cohesion and social support also significantly reduce stress levels and increase combat effectiveness.
ExoCoDe: MODELING TRANSITS EVENTS VIA STATISTICAL AND MACHINE LEARNING TOOLS
(2024) Karakuts, Denys
This capstone project uses statistical and machine learning algorithms to detect exocomet transits in TESS telescope data. Exocomets, distinguished by their unique, asymmetric light curves, present a detection challenge due to their subtle signatures compared to planetary transits and light intensity. We develop a framework that integrates data preprocessing, feature extraction, visualizations, statistical methods, and machine learning regressors to characterize these transits efficiently. The project is built upon the existing progress of astrophysical research. It aims to enhance our understanding of exocometary activity, uncovering the potential of machine learning and statistical analysis in astronomical data interpretation.

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