Business Intelligence patří k velmi diskutovaným tématům v oblasti podnikové informatiky, a to více než deset let. Ačkoliv se funkcionalita těchto systémů stále zdokonaluje, není zcela prozkoumán/prověřen mechanizmus jejich vlivu na výkonnost podniků. Proto je cílem práce identifikovat a analyzovat faktory související s využitím systémů Business Intelligence, a to faktory, které mají vliv na rozhodovací procesy v českých podnicích. Výstupem práce by měl být model vazeb a příčinných souvislostí Business Intelligence na účinnost a účelnost rozhodovacích procesů v českých podnicích. Téma předpokládá znalosti z oblasti podnikového hospodářství a managementu a současně informatiky (ideálně aplikované/podnikové informatiky).

Školitelem pro toto téma je docent Radoslav Škapa. Detailní informace o školiteli, jeho publikacích a výzkumných projektech naleznete zde.

Cílem práce je zodpovědět otázku, zda jednotlivci v podniku (a kteří, v jakých pozicích) mohou významně ovlivnit a ovlivňují environmentální profil (výkonnost) podniků, či zda zásadní roli hrají skupiny-stakeholdeři. Téma vyžaduje znalosti z oblasti podnikové ekonomiky a zejména managementu; znalost psychologie či sociální psychologie je výhodou.

Školitelem pro toto téma je docent Radoslav Škapa. Detailní informace o školiteli, jeho publikacích a výzkumných projektech naleznete zde.

Modern businesses use policies and approaches that help create working conditions and environments in which employees are satisfied, feel intrinsically motivated and have sufficient resources to cope with the job demands. Such policies and approaches can lead to the attraction and retention of high-quality employees, promote high work performance of individuals and teams and support the well-being of employees as important stakeholders. Positive human resources management integrates topics such as leadership,work-life balance, job design, perceived organizational support, job attitudes or employee well-being. The dissertation will focus on a specific subtopic of positive human resources management and enhance the current understanding of how a company can create quality conditions for its employees and how thisaffects employees and the company's performance.

The supervisor for this topic is associate professor Jakub Procházka. Detailed information about the supervisor, his publications and research projects are available here.

The thesis aims to identify the factors that can affect consumer adoption of emerging technologies (such as Generative AI-Chat GPT) in the context of electronic service quality in electronic commerce. After a systematic literature review, the candidate will prepare an initial interview schedule. Based on qualitative results, the factors will be identified, and a structural model will be proposed and tested. For the quantitative part, second generation analysis such as structural equational modelling will be used. The study will have both theoretical and managerial implications.

The supervisor for this topic is Doctor Prateek Kalia. Detailed information about the supervisor, his publications and research projects are available here.

Under this thesis, the candidate will try to understand small or medium-sized sellers’ perceptions of using immersive technologies (such as augmented, virtual reality) in e-commerce. Based on mixed method approach the candidate will interview the stakeholders to identify the underlying factors. The structural model thus stemming out will be tested through structural equational modelling. The study will try to bring interesting insights for the marketers, for instance even if virtual shopping is exciting who should bear the cost to create/provide the supporting infrastructure? Is it feasible for small businesses to invest in immersive technologies and be profitable or do they expect big e-commerce players (such as Amazon) to create infrastructure and small e-retailers will list the products using such platforms, etc.?

The supervisor for this topic is Doctor Prateek Kalia. Detailed information about the supervisor, his publications and research projects are available here.

The aim of this research stream is to explore the effectiveness of eWOM through a comprehensive dissertation. Commence with a systematic literature review to identify and summarize influencing factors of eWOM. Based on this, develop and test a conceptual model using quantitative research methods, including surveys (survey-experiments) and experiments. Employ Structural Equation Modeling (SEM) and other advanced statistical techniques for in-depth analysis. Clear presentation and detailed elaboration of the findings are essential, showcasing the theoretical and practical implications of eWOM's effectiveness. The research should be characterized by methodological rigor and clarity, and should result in several scientific articles.

The supervisor for this topic is Doctor Dušan Mladenović. Detailed information about the supervisor, his publications and research projects are available here.

This research endeavor seeks to unravel the intricate impacts of Generative AI on electronic Word of Mouth (eWOM). Initiating with a thorough systematic literature review, candidates will identify and distill the factors influencing eWOM and subsequently articulate and validate a conceptual model. The utilization of quantitative research methodologies, such as surveys, survey-experiments, and experiments, is imperative. In-depth analysis employing Structural Equation Modeling (SEM) and advanced statistical methods will shed light on the nuanced relationships. A clear and detailed exposition of the findings is crucial, underscoring the theoretical and applied ramifications of Generative AI’s influence on eWOM. The study mandates methodological rigor and clarity, aiming to culminate in the publication of several scientific articles.

The supervisor for this topic is Doctor Dušan Mladenović. Detailed information about the supervisor, his publications and research projects are available here.

Emerging information technologies enable businesses in different industry sectors to transform their business models digitally and utterly create and deliver new business value to their customers. This topic covers the enabled business value of emerging information technologies, including Blockchain, Internet of Things, Artificial Intelligence, and social platforms, among others. Potential applications could be supply chain, sharing economy, circular economy, tourism etc. Both quantitative and qualitative approaches are welcomed; however, quantitative methods based on publicly available panel (historical) data are more favored.

The supervisor for this topic is associate professor Ahad Zareravasan. Detailed information about the supervisor, his publications and research projects are available here.