We would like to draw your attention to the following TDK topics, which are related to real industrial challenges and offer direct corporate cooperation.
On the initiative of the Kautz Faculty, cooperation has been established with multiple corporate partners, whom offer several TDK topics. The companes provide an external consultant for the topics, who supports the student in the preparation of the thesis and also cooperates with the university consultant.
If any of the topics are of interest to you, please contact us at kgk.tdk@sze.hu!
Gránit Bank
1. Artificial intelligence in banking – efficiency gains and new risks
Real impact on operations and profitability – cost reduction and profit growth, increasing ‘black-box’ exposure and emerging previously unexamined risks
2. The Future of Credit Risk Decision-Making – Data, Digitalization, and AI
How are digitalization, alternative data, and artificial intelligence transforming bank credit risk decisions from loan applications to monitoring and collections?
3. Gen Z's expectations for the future banking sector.
K&H Bank
Bosch
1. Examination of the industrial applicability of academic results in the automotive industry and its related fields
Abstract: In Hungary, the history of the partially parallel evolution of industry and academia, the rising number of industrial players, and the accelerating automotive development cycles emerging in the mid-2020s necessitate closer cooperation between Hungarian universities and automotive development companies. In recent years, increasing emphasis has been placed on making university research more practical and on communicating results in an application-oriented manner. While such efforts within the engineering field are welcome, it is also necessary to support these processes from the perspectives of business development, as well as innovation, process, and resource management. Generally speaking, the tools typically used in either industry or academia cannot be straightforwardly applied within this hybrid academic-industrial environment. Furthermore, communication styles in these two worlds differ vastly; therefore, special attention must be paid to understanding the respective operational practices of the parties involved.
The development of this topic is expected to yield the following results:
- Situation assessment: Data collection at both the management level (university competence centers, commercialization entities, research leads, Bosch executives, and innovation managers) and the engineering level (R&D managers, research and development engineers) is required to identify communication gaps, external constraints, business interests (analyzing the situations of Bosch Hungary and Bosch Global separately), existing examples of successful and unsuccessful collaboration, and the results of commercialization efforts to date (note: the research may potentially be extended to other universities).
- Structuring management processes based on selected criteria (derived from the findings of the previous step), with a preference for: information management (e.g., determining at which stage, to whom, and at what level of maturity university research results should be presented to advance commercialization), communication strategies, and—as alternatives—organizational development, roles, and the legal framework.
- Business models: Listing and evaluating various business models to determine which ones are most suitable or advantageous for the commercialization of academic research results.
- Expectation management: Identifying both realistic and unrealistic expectations.
Variations:
- commercialization models, metrics, and related processes (assessment of potential, performance evaluation of research results),
- the expected transformation of centrally funded schemes (e.g., EU grants) and their role in the industrial application of research results,
- market trends—primarily in Europe and the Americas—alongside Chinese innovation models and in response to them, with a particular focus on academic-industry collaborations.
2. Opportunities for the talent pipeline of highly qualified engineers through talent development programs, spanning from secondary school to employment.
Abstract: With the spread of artificial intelligence, expectations regarding the highly skilled workforce in research and development have shifted. Accelerated development cycles and product concepts emerging from the collaboration of multiple engineering disciplines require development team members to possess competencies that cannot be easily categorized within the confines of a specific engineering major or training program. Artificial intelligence replaces many automatable processes previously performed by humans; consequently, adaptability, originality, and creativity are becoming increasingly important in the expectations placed on the workforce. Identifying personnel who offer high intellectual added value necessitates talent development starting as early as the final years of secondary school. Through well-structured programs, we design and implement career pathways that supplement or even transform traditional training methods, ensuring that recent university graduates meet these evolving requirements.
By developing this topic, we expect to achieve the following results / answer the following questions:
- a comprehensive picture of changing workforce demands and their impact on university talent development,
- knowledge of current trends in the development of education, particularly at Hungarian universities,
-a comprehensive overview of talent support programs, spanning from secondary schools to the labor market, - survey among talented students, gaining insight into their decisions and challenges,
- formulating recommendations—taking the aforementioned factors into account—on how to keep talent management on the right track, as well as identifying the new areas and methodologies required for educating highly qualified students (e.g., soft skills, teamwork, business knowledge, etc.)
- how to combine human creativity, digitalization, and classical engineering knowledge in technical fields,
- how industrial problems can (and should) be placed at the center of nurturing technical talent.
Waberer's
1. The situation and future of logistics in the Balkans
–What negative impact does the growing number of transport companies—primarily from Eastern countries (Romania, Bulgaria, Ukraine, Turkey, Latvia, Lithuania)—have on international freight transport?
BI-KA Logisztika
1. The economics of electric trucks on short, repetitive industrial shuttles: TCO parity and difference sharing between client and carrier
Research question: Under what conditions does a BEV achieve TCO parity with a diesel vehicle in the domestic context? Factors examined: daily mileage, number of shifts, electricity costs, road tolls, subsidies, and residual value. Additionally: what is the client’s willingness to pay, and who bears the cost difference?
Method: TCO model with sensitivity analysis, supplemented by interviews with the client. Győr is an ideal setting for this, given the abundance of automotive suppliers in the area.
2. Driver retention in road freight transport: determinants of turnover and the integration of third-country national workers
Research question: What drives drivers’ intention to quit? Potential factors include wages, commuting, scheduling, vehicle condition, and the relationship with dispatchers. How do these factors differ between domestic drivers and those from third countries?
Method: Questionnaire, ideally incorporating conjoint analysis of the benefits package. It is advisable to extend the sample to include drivers from partner carriers, in addition to those from BI-KA.
Challenge: Reaching the drivers and language barriers; therefore, strong corporate support is required.