Thesis Topics

Are you passionate about biodiversity, sustainability accounting, and cutting-edge research methods? We’re seeking a dedicated Master’s student to join our project, which aims to rigorously evaluate leading biodiversity-footprinting frameworks through an expert-based voting study.

What you’ll do

• Design and administer a Delphi or multi-criteria decision analysis (MCDA) survey to biodiversity scientists, sustainability officers, standard-setters, and corporate accountants
• Develop clear evaluation criteria (e.g., scientific validity, measurability, usability, comparability, stakeholder relevance) based on our literature review
• Recruit and engage 15–20 specialists to iteratively rate and refine their judgments across rounds
• Analyze results to identify consensus scores, rank frameworks, and highlight areas of divergence

Why it matters

• Fills a crucial methodological gap by complementing desk-based scoring with expert validation
• Provides you with hands-on experience in Delphi/MCDA techniques, survey design, and stakeholder engagement

You bring

• Strong interest in biodiversity or sustainability accounting
• Familiarity with survey tools (Qualtrics, SurveyMonkey) and basic stats (Excel, R, or Python)
• Excellent communication skills to liaise with international experts

Please contact maximilian.blaschke(at)tum.de for questions.

Description:

The automation of accounting processes has accelerated significantly over the past decades, driven by advances in software, artificial intelligence, and data processing capabilities. Tasks that were traditionally manual—such as bookkeeping, invoice processing, and financial reporting—are increasingly being handled by intelligent systems, Robotic Process Automation (RPA), and machine learning tools.

This thesis aims to systematically review the academic and practitioner literature on automation in accounting, with a particular focus on how automation trends have evolved over time and what impact they have had on the profession, required skills, organizational structures, and strategic decision-making. In addition to the structured literature review, the student may conduct a small number of expert interviews to supplement the academic findings with practical insights from industry or consulting.

Possible Research Questions:

• How has the degree of automation in accounting evolved from the 1980s to today?
• Which technologies have driven major shifts in accounting workflows?
• What impacts has automation had on the role of accountants and required skill sets?
• How do firms balance efficiency gains from automation with risks such as loss of oversight or auditability?

Requirements:

• Interest in accounting, digital transformation, and technology trends
• Ideally: background in accounting, finance, information systems, or business analytics
• Good research and writing skills; experience with literature reviews is a plus
• Optional: interest in conducting qualitative interviews

Methodological Approach:

Structured Literature Review + Expert Insights

• Systematic search and categorization of peer-reviewed and high-quality practitioner literature
• Thematic clustering by technology type, timeline, and organizational impact
• Optional: 2–3 expert interviews with accounting professionals, auditors, or software providers to enrich and validate findings
  Goal: Synthesize academic and practical perspectives to understand key trends and impacts of automation in accounting

Language: German or English

Start: ASAP

Application: Please stick to the regular application process via our chair’s online form

Contact: Alina Buss (alina.buss(at)tum.de)

First literature to start with:

• Bose, S., Dey, S. K., & Bhattacharjee, S. (2023). Big Data, Data Analytics and Artificial Intelligence in Accounting: An Overview. In Business 2023 (Chapter 3, pp. 32–51). Edward Elgar Publishing. https://doi.org/10.4337/9781800888555.00007
• Berikol, B. Z., & Killi, M. (2021). The Effects of Digital Transformation Process on Accounting Profession and Accounting Education. In K. T. Çalıyurt (Ed.), Ethics and Sustainability in Accounting and Finance, Volume II (pp. 219–231). Springer, Singapore. https://doi.org/10.1007/978-981-15-1928-4_13
• Gonçalves, M. J. A., Ferreira da Silva, A. C., & Ferreira, C. G. (2022). The Future of Accounting: How Will Digital Transformation Impact the Sector? Informatics, 9(1), 7. https://doi.org/10.3390/informatics9010007

Description:

Machine Learning (ML) and Deep Learning (DL) techniques have become integral to the digital transformation of accounting. From fraud detection and predictive analytics to automated classification and forecasting, these technologies enhance efficiency, accuracy, and insight generation across various accounting tasks.

This thesis aims to systematically explore non-generative AI applications—specifically ML and DL models—in accounting. The focus lies on practical use cases, technological requirements, limitations, and organizational implications. Importantly, generative AI (e.g., ChatGPT, LLMs) is explicitly excluded from the scope to ensure a clear focus on predictive and classification-oriented AI systems.

Possible Research Questions:

• What are the most common ML/DL applications in accounting processes such as auditing, forecasting, or fraud detection?
• How do ML/DL models differ in their accounting use cases compared to traditional rule-based systems?
• What data, skills, and infrastructure are required to successfully implement ML/DL in accounting departments?
• What are the key limitations and risks (e.g., data quality, model bias, explainability) of using ML/DL in accounting?
• How are accounting roles and decision-making processes affected by the adoption of ML/DL technologies?

Requirements:

• Interest in accounting, data analytics, and AI technologies
• Ideally: background in accounting, finance, business analytics, or information systems
• Strong research and writing skills; technical familiarity with ML/DL concepts is a plus
• Optional: interest in practical validation (e.g., expert interviews or reviewing case studies)

Methodological Approach:

Systematic Literature Review + Optional Survey or Expert Interviews

• Systematic review of academic and practitioner literature on ML/DL in accounting
• Categorization by use case, algorithm type (e.g., decision trees, neural networks), and impact on workflows
• Optional: conduct a survey or 2–3 expert interviews with professionals in finance, auditing, or AI implementation

Goal:

Map the current landscape of non-generative AI in accounting, identify opportunities and limitations of ML/DL applications, and explore their organizational implications.

Language: English or German

Start: ASAP

Application: Please apply via the regular application process on our chair’s online portal

Contact: Alina Buss (alina.buss(at)tum.de)

First literature to start with:

• Ranta, M., Ylinen, M., & Järvenpää, M. (2023). Machine learning in management accounting research: Literature review and pathways for the future. European Accounting Review, 32(3), 607-636.
• Sun, T. (2019). Applying deep learning to audit procedures: An illustrative framework. Accounting Horizons, 33(3), 89-109.

Description:

Generative Artificial Intelligence (GenAI), such as large language models like GPT, is increasingly transforming accounting. From automating report and document generation to intelligent support for financial data analysis and anomaly detection, GenAI offers numerous opportunities. At the same time, challenges around data quality, compliance, explainability, and ethics remain critical.

This thesis aims to systematically explore current applications of GenAI in accounting, examine the associated potentials and risks, and analyze the impact on workflows, job roles, and governance. In addition to a structured literature review, practical insights can be gathered through a survey or expert interviews with professionals from industry, consulting, or software providers.

Possible Research Questions:

• What are the current use cases of generative AI in accounting?
• How do GenAI-driven technologies change accounting workflows such as bookkeeping, controlling, and reporting?
• What risks (e.g., error proneness, compliance, data privacy) arise with the use of GenAI in accounting?
• How do organizations respond to re-defining accounting roles in the light of GenAI adoption?

Requirements:

• Interest in AI, accounting, and digital transformation
• Background in business administration, information systems, accounting, or related fields preferred
• Strong research and writing skills; experience with literature reviews is a plus

Methodological Approach:

Systematic Literature Review + Optional Survey or Expert Interviews

• Structured analysis of academic publications and practitioner articles on GenAI and accounting
• Thematic categorization by application areas, opportunities, and risks
• Optional: conduct a survey or 2–3 interviews with practitioners from companies, consulting firms, or software vendors

Goal:

Develop a comprehensive understanding of the current state, challenges, and implications of generative AI in accounting for processes, roles, and governance.

Language: English or German

Start: ASAP

Application: Please apply via the regular application process on our chair’s online portal

Contact: Alina Buss (alina.buss(at)tum.de)

First literature to start with:

• Dong, Mengming Michael, Stratopoulos, Theophanis C., & Wang, Victor Xiaoqi (2024): A Scoping Review of ChatGPT Research in Accounting and Finance, in: International Journal of Accounting Information Systems, Vol. 55, No. 100715, pp. 1-29.
• Zhao, Joanna, & Wang, Xinruo (2023): Unleashing Efficiency and Insights: Exploring the Potential Applications and Challenges of ChatGPT in Accounting, in: Journal of Corporate Accounting & Finance, Vol. 35, No. 1, pp. 269-276.

Description:

The use of Generative AI (GenAI) in accounting is rapidly gaining traction – from automatically generating reports and memos to drafting compliance documentation or assisting with financial commentary. However, not every accounting process is equally suitable for GenAI-based optimization.

This thesis aims to develop a structured evaluation framework to assess which accounting processes offer high potential for GenAI-based improvement. The focus is on identifying process characteristics (e.g., repetitiveness, complexity, data availability) that influence the applicability and success of GenAI tools in practice.

Possible Research Questions:

• What are the key criteria for evaluating the suitability of accounting processes for GenAI applications?
• Which accounting areas (e.g., reporting, controlling, compliance) offer the greatest GenAI potential?
• What organizational or technical barriers limit the adoption of GenAI in accounting workflows?

Requirements:

• Strong interest in accounting, digital transformation, and AI
• Ideally: background in accounting, finance, business analytics, or information systems
• Good analytical and writing skills; structured thinking
• Optional: interest in validating the framework through interviews or case studies

Methodological Approach:

Literature Review + Framework Development + Optional Case Validation

• Review of existing AI and process automation literature in the accounting context
• Synthesis of criteria for process suitability (e.g., input standardization, compliance sensitivity)
• Optional: expert interviews to validate the framework or apply it to real-world accounting processes

Goal:

Develop a practical evaluation framework to help organizations identify where GenAI adds the most value in accounting workflows.

Language: English or German

Start: ASAP

Application: Please apply via the regular application process on our chair’s online portal

Contact: Alina Buss (alina.buss(at)tum.de)

First literature to start with:

• Dong, Mengming Michael, Stratopoulos, Theophanis C., & Wang, Victor Xiaoqi (2024): A Scoping Review of ChatGPT Research in Accounting and Finance, in: International Journal of Accounting Information Systems, Vol. 55, No. 100715, pp. 1-29.
• Denni-Fiberesima, D. (2024, April). Navigating the generative AI-enabled enterprise architecture landscape: Critical success factors for AI adoption and strategic integration. In International Conference on Business and Technology (pp. 210-222). Cham: Springer Nature Switzerland.

(BA/MA): From Idea to Implementation – How Generative AI Supports Innovation and Process Reengineering in Organizations

Description:

Generative AI tools are not only changing existing processes, but also enabling organizations to fundamentally rethink and redesign how work is done. Whether in finance, HR, customer service, or R&D – GenAI can support process innovation by accelerating ideation, documentation, prototyping, and testing.

This thesis explores how GenAI contributes to process innovation and reengineering, focusing on its role in early-stage idea generation, design support (e.g., process documentation via natural language), and transformation initiatives.

Possible Research Questions:

• How do companies use GenAI in innovation and process redesign efforts?
• Which stages of the process innovation lifecycle (e.g., ideation, modeling, testing) benefit most from GenAI support?
• What are the risks and organizational challenges in embedding GenAI into innovation processes?

Requirements:

• Interest in innovation management, digital transformation, and AI tools
• Ideally: background in business administration, information systems, or digital strategy
• Good research and writing skills; openness to exploring real-world cases
• Optional: interest in conducting interviews with innovation managers or process designers

Methodological Approach:

Structured Literature Review + Optional Case Analysis / Expert Interviews

• Identification of GenAI-enabled innovation patterns in process transformation
• Mapping of GenAI use across different innovation stages
• Optional: Interviews with professionals working in digital innovation or transformation

Goal:

Analyze and structure how GenAI supports business process innovation and reengineering, and derive practical recommendations for organizations.

Language: English or German

Start: ASAP

Application: Please apply via the regular application process on our chair’s online portal

Contact: Alina Buss (alina.buss(at)tum.de)

First literature to start with:

• van Dun, C., Moder, L., Kratsch, W., & Röglinger, M. (2023). ProcessGAN: Supporting the creation of business process improvement ideas through generative machine learning. Decision Support Systems, 165, 113880.
• Kanbach, D. K., Heiduk, L., Blueher, G., Schreiter, M., & Lahmann, A. (2024). The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective. Review of Managerial Science, 18(4), 1189-1220.
• Sedkaoui, S., & Benaichouba, R. (2024). Generative AI as a transformative force for innovation: a review of opportunities, applications and challenges. European Journal of Innovation Management.

Description:

Corporate emission accounting has grown significantly in both relevance and complexity in recent years. A particularly prominent debate centers on how to accurately account for scope 2 emissions, which refer to indirect emissions from purchased electricity. Two main approaches have emerged: the market-based and the location-based methods. These approaches differ primarily in their methodology, specifically regarding which emission factors are applied. This distinction carries broader implications, including questions about the appropriate degree of incentivizing decarbonization at the firm level and the reliability of market-based claims.

This thesis will provide a structured review of the existing literature on scope 2 emission accounting, focusing on the controversy surrounding the two approaches. Additionally, it will critically discuss various solution concepts and aim to offer a perspective on how to resolve the ongoing issues. The analysis will also reference the current and ongoing revisions to the Greenhouse Gas Protocol and the Science Based Targets initiative (SBTi) emission standard accounting guidelines.

Prerequisites: Interest in sustainability and energy markets

Methodology: Web- & literature review

Start: ASAP

First literature to start with:

Brandner et al. (2019). Creative accounting: A critical perspective on the market-based method for reporting purchased electricity (scope 2) emissions: Energy Policy

Kemper, Marina; Styles, Alexandra; Mundt, Juliane; Werner, Robert; Kreis, Philippa (2024) : Markt- vs. ortsbasierter Ansatz: Vorschlag zur Harmonisierung der Klimabilanzierung von Strom, Hamburg Institut Discussion Papers, HIC Hamburg Institut Consulting GmbH, Hamburg

Contact: Johannes Bösch (Please follow the official application process as described here)

Description:

The link between renewable energy deployment and energy import dependency has gained increasing attention in the context of EU energy resilience, especially amid current geopolitical uncertainties and climate policy ambitions. While policymakers often posit that renewables reduce dependency on energy imports, the empirical and theoretical underpinnings of this assumption remain fragmented across disciplines.

This thesis conducts a systematic literature review to synthesize the existing academic knowledge on the relationship between renewable energy shares and energy import dependency in EU member states. The review will identify dominant theoretical perspectives, key empirical findings, methodological approaches, and potential research gaps. Particular attention will be paid to how studies define and measure energy dependency, the types of renewables considered, and how structural and contextual variables (e.g., GDP, industrial structure, energy mix composition) are accounted for.

The objective is to provide a comprehensive and critical overview of the evidence base to inform future empirical work and policy evaluation.

Prerequisites:

Interest in energy policy and sustainability research; basic understanding of literature review methods

Methodology:

Systematic literature review

Start:

ASAP

First literature to start with:

• Awerbuch, S. & Sauter, R. (2006). Exploiting the oil–GDP effect to support renewables deployment, Energy Policy
• Banna, H. et al. (2023). Energy security and economic stability: The role of inflation and war, Energy Economics
• Zachmann, G. et al. (2018). Energy Security in Europe: The Role of Renewable Energy Sources, Bruegel
• Sovacool, B. K. & Mukherjee, I. (2011). Conceptualizing and measuring energy security: A synthesized approach, Energy
• Snyder, H. (2019). Literature reviews as a research strategy: An overview and guidelines, Journal of Business Research

Contact: Lars Nickel (lars.nickel@tum.de)

Description:

The resilience of national energy systems has become a strategic priority in the European Union, especially in light of geopolitical crises and climate policy goals. A central aspect of this resilience is energy import dependency, which measures the extent to which a country relies on foreign sources to meet its energy demand. Simultaneously, the expansion of renewable energy is seen as a key mechanism for strengthening energy security and reducing dependency.

This thesis investigates the relationship between the share of renewable energies in a country's energy mix and its level of energy import dependency. Drawing on statistical data, the thesis will test the explanatory power of renewables expansion for import dependency reduction.

The work will contribute to the understanding of how renewable energy deployment intersects with structural energy security and offer policy-relevant insights for strengthening EU energy independence.

Prerequisites:

Basic knowledge of econometrics and interest in energy policy or European energy markets

Methodology:

Descriptive statistics, correlation analysis, and multivariate regression using EU-level panel or cross-sectional data

Start:

ASAP

First literature to start with:

• Zachmann, G. et al. (2018). Energy Security in Europe: The Role of Renewable Energy Sources, Bruegel
• Banna, H. et al. (2023). Energy security and economic stability: The role of inflation and war, Energy Economics, 126, 106949.
• Awerbuch, S., & Sauter, R. (2006). Exploiting the oil–GDP effect to support renewables deployment, Energy Policy
• European Commission (2023). EU Energy Statistical Pocketbook
• IEA (2022). Energy Security and Renewables: Building Resilience in a Clean Energy Future

Contact: Lars Nickel (lars.nickel@tum.de)

Description: Electric vehicles (EVs) are rapidly gaining in market share in major economic regions, including Europe, the US, and China, driven by the automotive sector transformation towards sustainable mobility. The increase in EVs and subsequently in batteries results in a large demand for critical resources, such as Lithium or Cobalt, but accessibility is restricted due to geographical disparities in resource extraction, leading to potential supply-side vulnerabilities. Resource resilience and sovereignty over critical materials have become critical imperatives for governments and multinational organizations. 

Why it matters: Enterprises along the EV value chain face huge uncertainties and complexities in defining the right strategy to counteract vulnerabilities in resource access while increasing their own supply chain resilience. This thesis aims to provide valuable insights by providing an overview of different strategies companies apply to increase resource resilience in the EV battery sector. The findings will shed light on how companies mitigate vulnerabilities and identify promising practices in this area.

Methodology: Literature review and Case study methodology

Language: English

Start: ASAP

Application: Please stick to the regular application process via our chair’s online form

Contact: eric.wimmer@tum.de

Description: Impact investing is an innovative investment approach that combines the pursuit of financial returns with measurable positive social and environmental impact. This dual focus allows investors to align their portfolios with their values and contribute to meaningful global change. Although the impact investing industry currently faces challenges—with some venture capital firms moving away from the impact label—many others remain strongly committed, especially in areas like climate and social innovation, highlighting the sector’s resilience and evolving nature.

This thesis will conduct a systematic literature review to explore how impact investing originated and has developed over time. The research will examine its main performance indicators, key impact objectives, and the evolution of industry practices, providing a comprehensive understanding of the field’s trajectory and future outlook.

Prerequisites: Interest in ESG and Impact Investing, Independent working style  

Methodology: Literature Review

Start: ASAP 

Application: Please stick to the regular application process via our chair’s online form

Contact: Lubna Al-Duri (lubna.al-duri@tum.de)    

First literature to start with:

• Agrawal, A., & Hockerts, K. (2021). Impact Investing: Review and Research Agenda. Journal of Small Business and Entrepreneurship, 33(2), 153-181.
• Barber, B. M., Morse, A., & Yasuda, A. (2021). Impact investing. Journal of Financial Economics, 139(1), 162–185.
• Kovner, Anna and Josh Lerner, “Doing well by doing good? Community development venture capital,” Journal of Economics & Management Strategy, 2015, 24 (3), 643–663.

Description: 

The thesis will be embedded in a larger study examining how companies with significant Scope 3 emissions profiles respond to strategic and institutional uncertainty. The project investigates how firms navigate limited control over their value chain, increasing regulatory pressure, and growing demands for climate legitimacy—and what strategies, mechanisms, and trade-offs emerge in the process.

Research Questions:

• How do companies identify barriers and leverage points in Scope 3 governance?
• What role do stakeholders play in value chain decarbonization?
• Which strategic response mechanisms do companies adopt—accept, improve, avoid, explore, or reflect?
• To what extent do firms perceive Scope 3 frameworks (e.g., GHG Protocol, CSRD, SBTi) as fit for purpose?
• How do Scope 3 strategies vary by industry, supply chain position, or governance maturity? 

Prerequisites: Good German and English language skills, Interest in ESG, corporate sustainability strategies, and climate policy, Independent working style  

Methodology: 

You will conduct a qualitative case study based on expert interviews and company documents (e.g., climate reports, SBTi targets, ESG ratings). Your thesis will contribute to the theoretical understanding of corporate responses to Scope 3 complexity and complement an ongoing multi-case study

Start: ASAP 

Application: Please stick to the regular application process via our chair’s online form

Contact: Victoria Fohrer (victoria.fohrer@tum.de)     

First literature to start with:

• Hettler, M. & Graf-Vlachy, L. (2023). Corporate scope 3 carbon emission reporting as an enabler of supply chain decarbonization: A systematic review and comprehensive research agenda. Business Strategy and the Environment, 33(2), 263–282.
• Buchenau, N., Oetzel, J., & Hechelmann, R.-H. (2025). Category-specific benchmarking of Scope 3 emissions for corporate clusters. Renewable and Sustainable Energy Reviews, 208, 115019.
• Vieira, L.C., Longo, M., & Mura, M. (2024). Impact pathways: The hidden challenges of Scope 3 emissions measurement and management. International Journal of Operations & Production Management, 44(13), 326–334.

Description: 

Experts consider the integration of ESG metrics into executive compensation as "one of the most significant changes in executive compensation over the past decade" (Ellerman et al., 2021). Despite its strategic significance on corporate agendas, the integration of ESG into business practices is often only discussed superficially, with ESG frequently treated as a buzzword. 

This thesis aims to to analyze the prevailing incentivization approaches and systems. Depending on the degree level, this will be conducted through either a literature review or a multiple case study approach/quantitative analysis.  

Prerequisites: Good German language skills, Interest in ESG, managerial incentive systems & agency theory, Independent working style  

Methodology: Topic dependent (Literature review (BA only), Development of Framework, Multiple Case Study, Data collection or quantitative analysis)  

Start: ASAP 

Application: Please stick to the regular application process via our chair’s online form

Contact: Victoria Fohrer (victoria.fohrer@tum.de)     

First literature to start with:

• COHEN, KADACH et al. 2023 – Executive Compensation Tied to ESG
• Flammer, Hong et al. 2019 – Corporate governance and the rise of integrating corporate social responsibility criteria in executive compensation: Effectiveness and implications for firm outcomes
• Gebhardt, Thun et al. 2023 – Managing sustainability—Does the integration of environmental, social and governance key performance indicators in the internal management systems contribute to companies' 

Beschreibung:

Das produzierende Gewerbe in Deutschland und besonders kleine und mittlere Unternehmen (KMUs) sehen sich in den letzten Jahren einem dynamischen und unsicheren Wirtschaftsumfeld geprägt von einer Vielzahl von verschiedenartigen Schocks und neuartigen Bedrohungslagen gegenübergestellt. Diese Krisen üben erheblichen Druck auf die industrielle Produktion und die dafür benötigten Lieferketten der betroffenen Unternehmen aus. 

Aufgrund dieses unsicheren Wirtschaftsumfelds stehen Unternehmen vor der Herausforderung, wie ihr Produktionssystem künftig resilienter aufgestellt werden kann und welche Maßnahmen zu diesem Zweck ergriffen werden müssen. KI-Anwendungen haben ein enormes Potential die Resilienz in der Lieferkette und Produktion zu steigern, könnten kleinere und mittlere Unternehmen jedoch vor erhebliche Herausforderungen hinsichtlich Komplexität und Nutzenerwartung stellen. 

Ziel der Thesis ist den konzeptionellen Aufbau einer Nutzwertanalyse zu entwickeln, um den Nutzen der Implementierung von KI-Technologien qualitativ und quantitativ für entsprechende Anwendungsfälle bewerten zu können. 

Dabei stellen sich folgende Fragen:

·       Welche Einflussgrößen/ KPIs existieren für den Faktor Resilienz in produzierenden Unternehmen?

·       Welche qualitativen und quantitativen Bewertungskriterien messen den Nutzen von KI Use Cases?

Voraussetzung: Sprachkompetenz Deutsch, Interesse an KMU und KI

Methodik: Literaturrecherche, Explorative Case Study Research, Nutzwertanalyse

Start: ASAP

Bewerbung: Bewerbe dich über das reguläre Online-Formular unseres Lehrstuhls

Kontakt: Eric Wimmer (eric.wimmer@tum.de)

Description:

Das produzierende Gewerbe in Deutschland und besonders kleine und mittlere Unternehmen (KMUs) sehen sich in den letzten Jahren einem dynamischen und unsicheren Wirtschaftsumfeld geprägt von einer Vielzahl von verschiedenartigen Schocks und neuartigen Bedrohungslagen gegenübergestellt. Diese Krisen üben erheblichen Druck auf die industrielle Produktion und die dafür benötigten Lieferketten der betroffenen Unternehmen aus. 

Aufgrund dieses unsicheren Wirtschaftsumfelds stehen Unternehmen vor der Herausforderung, wie ihr Produktionssystem künftig resilienter aufgestellt werden kann und welche Maßnahmen zu diesem Zweck ergriffen werden müssen. KI-Anwendungen haben ein enormes Potential die Resilienz in der Lieferkette und Produktion zu steigern, könnten kleinere und mittlere Unternehmen jedoch vor erhebliche Herausforderungen hinsichtlich Komplexität und Nutzenerwartung stellen. 

Ziel der Thesis ist eine Übersicht zu Methoden für die Ergebnisverfolgung und das Nachhalten von KI-basierten Initiativen zu erstellen und deren prozessuale Anforderung zu bestimmen. 

Dabei stellen sich folgende Fragen:

·       Wie lassen sich Initiativen nachhaltig und effektiv in produzierenden Unternehmen nachhalten?

·       Wie lässt sich der Erfolg der Umsetzung qualitativ und quantitativ bemessen?

Voraussetzung: Sprachkompetenz Deutsch, Interesse an KMU und KI

Methodik: Literaturrecherche, Explorative Case Study Research

Start: ASAP

Bewerbung: Bewerbe dich über das reguläre Online-Formular unseres Lehrstuhls

Kontakt: Eric Wimmer (eric.wimmer@tum.de)

Description:

The transition toward more sustainable and circular products has put pressure on manufacturers to improve the repairability of their devices. Regulatory frameworks such as the EU Ecodesign Directive increasingly demand that products be easier to repair and maintain. While these requirements serve environmental and consumer goals, they also raise important economic questions: How costly is it for firms to make products more repairable? Which design features are particularly expensive to implement? And how do these costs influence firms’ strategic decisions?

This thesis aims to explore the production cost implications of improved product repairability. Using real-world examples, secondary data, or simulation-based methods, the student will investigate how repair-friendly design affects cost structures and which trade-offs manufacturers face when complying with repair-oriented regulation. The results will contribute to a better understanding of the economic feasibility of repairability improvements and may inform future policy and modeling work on sustainable product strategies.

Possible Research Questions:

• Which specific design features associated with higher repairability (e.g., modular design, standardized fasteners, non-glued components) affect production costs, and to what extent?
• Are there systematic differences in cost structures between products with high and low repairability scores?
• What role do economies of scale, material costs, or assembly time play in cost differentials?
• How do producers balance repairability and cost-efficiency in real-world product design?

Requirements:

• Interest in product development, sustainability, and manufacturing
• Ideally: background in industrial engineering, operations management, or cost accounting
• For quantitative approaches: experience with Excel, Python, or simulation-based tools is a plus (depends on the chosen method)

Possible Methodological Approaches:

Option 1: Qualitative Comparative Analysis and Expert Interviews

• Case selection of 2–3 products (e.g., notebook, vacuum cleaner, smartphone) with varying levels of repairability
• Analysis of relevant design and production features
• Expert interviews with product developers, cost engineers, or repair specialists (e.g., iFixit, Right to Repair networks)
• Goal: Identify key cost drivers related to repair-friendly product design

Option 2: Secondary Data / Document Analysis

• Use of repairability ratings (e.g., iFixit, French Repairability Index) in combination with public cost estimates or teardown-based BOM data (e.g., TechInsights, iFixit)
• Goal: Correlate repairability characteristics with estimated production costs

Option 3: Parametric Cost Simulation (for technically skilled students)

• Design of hypothetical product variants with varying levels of repairability
• Simulation of material, assembly, and development costs (e.g., based on cost structure models or simplified CAD-based estimates)
• Goal: Derive a cost function C(R), where R represents the level of repairability

Language: German or English

Start: ASAP

Application: Please stick to the regular application process via our chair’s online form

Contact: Alina Gries (alina.gries(at)tum.de)

Description:

In response to growing environmental concerns, the European Union has introduced regulatory initiatives such as the Ecodesign Directive and the proposed Right to Repair Directive, aiming to extend product lifespans and promote the circular economy. These regulations challenge firms to adjust their pricing strategies, product design choices, and business models.

The goal of this thesis is to conduct a structured literature review on how companies respond strategically to such regulation. The review will identify relevant theoretical and empirical studies, categorize their approaches, and synthesize their findings. This work will lay the foundation for further academic research on firm behavior in the context of sustainability and regulatory economics.

Objectives of the Thesis:

• Identify and analyze key literature on strategic firm responses to repairability, circularity, and product sustainability regulation
• Categorize contributions by methodological approach (e.g., theoretical modeling, empirical analysis, behavioral studies)
• Summarize central findings, trends, and theoretical frameworks
• Identify gaps in the literature and propose directions for future research

Requirements:

• Interest in strategic management, sustainability, and economic regulation
• Very good English skills (many sources will be in English)
• Strong motivation to work independently with academic literature
• Interest in and basic understanding of theoretical economic modeling – e.g., willingness to engage with formal papers such as Jin et al. (2023) using stylized firm models

Methodology:

• Structured literature search using databases such as Scopus, Google Scholar, and EBSCO
• Inclusion/exclusion criteria to identify relevant peer-reviewed papers and working papers
• Qualitative analysis and synthesis of findings
• Presentation of results in tabular and narrative form (e.g., literature matrix)

Selected Starting Points

• Chen Jin, Luyi Yang, and Cungen Zhu. “Right to Repair: Pricing, Welfare, and Environmental Implications”. In: Management Science 69.2 (2023), pp. 1017–1036
• Mostafa Sabbaghi and Sara Behdad. “Optimizing Design for Repairability: A Game Theoretic Approach for Incorporating Market Analysis”. In: Journal of Mechanical Design 147.7 (2025).
• Ece Gulserliler, Atalay Atasu, and Luk N. van Wassenhove. “Business Model Choice under Right-to-Repair: Economic and Environmental Consequences”. In: Working Paper (2022).
• Sayan Chowdhury and Nishant K. Verma. “Walking a tightrope: Impact of adopting voluntary right-to-repair policy on firm profit and consumer welfare”. In: International Journal of Production Economics 272.1 (2024), p. 109253. ISSN: 0925-5273.

Language: German or English

Start: ASAP

Application: Please stick to the regular application process via our chair’s online form

Contact: Alina Gries (alina.gries(at)tum.de)