Centre for Entrepreneurship
Centre for Entrepreneurship

Masterarbeiten

Das Fachgebiet für Entrepreneurship und Innovationsmanagement bietet die Möglichkeit, Masterarbeiten zu aktuellen Forschungsthemen, mit Bezug zu den Forschungsgebieten des Lehrstuhls, zu verfassen. Bevor Sie Vorschläge einreichen, informieren Sie sich bitte in Ihrer Prüfungsordnung über studiengangsspezifische Anforderungen und Details. 

Nachfolgend finden Sie nähere Informationen zum Verfassen einer Masterarbeit an unserem Lehrstuhl.

Bitte beachten Sie auch den "Leitfaden" zum Verfassen einer Masterarbeit.

Voraussetzungen

Für das Schreiben einer Masterarbeit an dem Fachgebiet für Entrepreneurship und Innovationsmanagement müssen in der Regel kein spezieller Studiengang oder spezifische Kurse belegt wurden sein. Allerdings müssen Sie ausgeprägtes Interesse, Wissen und Motivation auf im Bereich "Entrepreneurships" nachgeweisen sowie über sehr gute Englischkenntnisse verfügen.

Es werden Themenvorschläge bevorzugt, die innerhalb der Forschungsfelder des Lehrstuhls liegen. Über andere Themenvorschläge wird individuell entschieden.

Das Fachgebiet akzeptiert nur Masterarbeiten in englischer Sprache.

Bitte prüfen Sie vorab die Themenvorschläge des Fachgebietes für Masterarbeiten (siehe unten), bevor Sie eine Anfrage senden.

Nur Masterstudenten können ihre Abschlussarbeit an unserem Lehrstuhl schreiben!

Das Fachgebiet kann nur eine begrenzte Anzahl von Abschlussarbeiten betreuen. Bitte haben Sie Geduld!

Anfragen

Bitte senden Sie alle allgemeinen Anfragen und individuelle Themenvorschläse an
a.bamberg(at)tu-berlin.de

Individuellen Themenvorschlägen sollten folgende Punkte enthalten:
- eine kurze Begründung Ihres Interesses / Ihrer Motivation und Ihres Wissens im Bereich "Entrepreneurship"
- ein Lebenslauf
- ein Exposé oder detaillierte Beschreibungen Ihrer Forschungsüberlegungen und der geplanten Struktur der Masterarbeit

Verfügbare Themen für Masterarbeiten

Entrepreneurial Well-being and Psychology

Supervisors: Karina Cagarman & Nicolas Noak

Currently we do not have any topics open and due to capacity limitations we can only supervise additional master theses in exceptional cases.

If you still believe you want to write a master thesis on topics among well-being and psychology, you can submit your own topic proposals and an absolutely solid abstract (topic, research question/gap, methodology & data, expected results, time schedule - 2 pages max) to BOTH nicolas.noak(at)tu-berlin.de and karina.cagarman(at)tu-berlin.de.

Note: Please be aware that handing in a proposal does not mean you are accepted for supervision. There is no guarantee your proposal will get accepted.

 

How to measure sustainability in the sporting goods industry

The textile industry belongs to the dirtiest industries in the world. Over 6000 different chemicals are being used in the production process, some of which are prohibited in the EU because they can cause cancer. The CO2 emissions exceed the once from all international flights and cruises combined. The waste and pollution of water is another important environmental dimension, just to state a few. In order to generate more sales many companies take advantage of the missing definition of the term “sustainability” and trick consumers with greenwashing campaigns. Transparency plays a crucial role in this.

Activities:

  • Define and distinguish the term sustainability
  • Create an objective evaluation framework of sports products (apparel, equipment, nutrition) on their sustainability & fairness (social responsibility) in order to make products comparable
  • Find and define the important dimensions within the sporting goods industry

 

Master Thesis in cooperation between TU Berlin (Prof. Dr. Jan Kratzer) and the start-up PLANETICS (https://www.planetics.de ).

Interested students prepare a two page research concept and send it to Prof. Dr. Jan Kratzer

The evolutionary nature of systematic engineering design methods

The topic is open for more than one master thesis. Therefore, it is rather broadly described with all steps and facets below. As the master thesis is an individual work all interested students are asked to narrow down the topic. The topic also allows for doing joint master thesis projects as long as the individual contributions can be clearly distinguished and graded as the examination regulations require:

Foremost in the last century systematic engineering design methods have been developing. Nowadays systematic design methods are generally used in new product development (NPD)/ Research & Development (R&D) endeavours and follow a simple and organized logic from breaking down the issue/technology into components and sub-components, systematically varying solutions to them up to the discursive/stage gate structure of the entire process. Systematic design methods can also be translated into dynamics of formal and informal social networks as prior studies show. The master theses should engage in these dynamics of social networks. The theoretical and empirical research should be executed within online forums as the source of data. The central research question is “do organized formal structures applying systematic engineering design methods resemble self-organized dynamics and structures of formal and informal social networks in online forums?”

The thesis would ask for a comprehensive literature review into social networks and the dynamics of social networks and systematic engineering design methods. This literature study should result in a number of specific research questions.

In addition, a comprehensive literature study to learn about the underlying theoretical perspectives is required. The study might encompass to read about evolutionary theory, behavioural group dynamics, social networks and collective good theories, management and design theories.

In a third step it would ask to search for suitable online forums, which allow to define, operationalize and measure of informal and formal network structures (open discussion forums in engineering/construction; specific professional engineering forums; crowdsourcing platforms or others).

The fourth step would be to use adequate network algorithm to measure the dynamic nature of formal and informal networks respectively formal and informal group structures. Taking this step might require to getting acquainted with the essential software for example R, condor, python, UCInet etc. as well as probably required text mining/analysing software such as Atlas ti or MAXQDA.

After collecting all data the dynamics of formal and informal social networks need to be analysed using classical statistical software as SPSS or R and special software on social networks as for example UCInet or SIENA.

The master thesis research is based on a research cooperation between Eindhoven University of Technology (Dr. Mohsen Jafari Songhori) and TU Berlin. When you are interested in this topic please shortly draft on 2-3 pages an outline/essay along the lines given here and send this per email to Prof. Dr. Jan Kratzer and in Cc m.jafari.songhori(at)tue.nl.

Engaging in this master thesis topic would be an endeavour into the analytics of big data and data science and current software around it.

Relevant literature

  • Le, Qize, and Jitesh H. Panchal. "Analysis of the interdependent co-evolution of product structures and community structures using dependency modelling techniques." Journal of Engineering Design 23.10-11 (2012): 807-828.
  • Hasan, Sharique, and Rembrand Koning. "Designing social networks: joint tasks and the formation and endurance of network ties." Journal of Organization Design 9.1 (2020): 1-19.
  • Kratzer, Jan, Hans G. Gemuenden, and Christopher Lettl. "Revealing dynamics and consequences of fit and misfit between formal and informal networks in multi-institutional product development collaborations." Research Policy 37.8 (2008): 1356-1370.
  • Sosa, Manuel E., Steven D. Eppinger, and Craig M. Rowles. "The misalignment of product architecture and organizational structure in complex product development." Management science 50.12 (2004): 1674-1689.

 

 

How Do Entrepreneurs Learn From Their Failures: The Crowdfunding Campaigns case

In recent years, crowdfunding has become an important tool for entrepreneurs and innovators. For instance, the global crowdfunding market has grown tremendously from $0.5 billion in 2009 to $34.4 billion in 2015, with now around 1250 platforms in more than 50 countries [3]. Using crowdfunding platforms, entrepreneurs can request required funds for realization of their creative work directly from supporters rather than traditional means of fund raising such as banks or foundations [1, 2].

In 2020, more than 60% of projects have failed to secure their target goal on “kickstarter” one of the most popular crowdfunding platforms [4]. Therefore a key challenge is to understand drivers of entrepreneurs’ success. Relevantly, a major research stream in crowdfunding has been devoted to examining the potential drivers of successful crowdfunding campaigns, and and have taken a factor-oriented approach [5]. However, entrepreneurial activities are prone to changes via the accumulation of experience, and therefore, dynamics of entrepreneurial processes over crowdfunding platforms appears to be under-studied (ibid).

In this master thesis, students use the extant management literature of “learning from failures” (see references in [6,7]), and develops a system dynamics (simulation) model [8] and analyses that model by looking at success/failure of projects on “kickstarter” [the data is downloaded/available], or other platforms. The final goal is to understand “how do innovators learn from their own or the others failures over time?”

The thesis would ask for a comprehensive literature review into crowdfunding, the underlying organizational learning theories, and relevant system dynamic models. This literature study should result in a number of specific research questions.

In addition, a comprehensive literature study to learn about the underlying theoretical perspectives is required. The study might encompass to read about evolutionary theory, behavioural group dynamics, social networks and collective good theories, management and design theories.

In a second step, the project require either use the current downloaded dataset, or web scrape one/two online crowdfunding platform, and download a large number of crowdfunding campaigns/photos/texts....

The third step would be to develop a system dynamic (SD) model of the dynamics of trajectories from failure to success over crowdfunding platforms. Taking this step might require to getting acquainted with the relevant simple software tools  such as Vensim. Next, the developed SD model will be validated using the downloaded dataset [9].

The master thesis research is based on a research cooperation between Eindhoven University of Technology (Dr. Mohsen Jafari Songhori) and TU Berlin. When you are interested in this topic please shortly draft on 2-3 pages an outline/essay along the lines given here and send this per email to Prof. Dr. Jan Kratzer and in Cc m.jafari.songhori(at)tue.nl.

Engaging in this master thesis topic would be an endeavour into the analytics of big data and data science and current software around it.

References

  1. E. M. Gerber, J. Hui, Crowdfunding: Motivations and deterrents for participation, ACM Transactions on Computer-Human Interaction (TOCHI) 20 (6) (2013) 34.
  2. P. Belleflamme, T. Lambert, A. Schwienbacher, Crowdfunding: Tapping the right crowd, Journal of Business Venturing 29 (5) (2014) 585 – 609.
  3. Massolution, 2015, 2015 CF Crowdfunding Industry Report.
  4. https://www.kickstarter.com/help/stats
  5. Yang, Lusi, and Jungpil Hahn. "Learning from prior experience: an empirical study of serial entrepreneurs in IT-enabled crowdfunding." Available at SSRN 3006930 (2016).
  6. Dillon, R. L., C. H. Tinsley, P. M. Madsen, and E. W. Rogers. 2016. Organizational correctives for improving recognition of near-miss events. Journal of Management 42 (3): 671697.
  7. Azadegan, A., R. Srinivasan, C. Blome, and K. Tajeddini. 2019. Learning from near-miss events: An organizational learning perspective on supply chain disruption response. International Journal of Production Economics 216:215226.
  8. Sterman, John. Business dynamics. Irwin/McGraw-Hill c2000.., 2010.
  9. Ballard, Timothy, et al. "An integrated approach to testing dynamic, multilevel theory: Using computational models to connect theory, model, and data." Organizational Research Methods (2019): 1094428119881209.

 

Indices as a data source to study antecedents of organizational resilience

We live in times where major crisis can occur almost instantly and with limited possibility for firms to predict them. Events resulting from climate change, overpopulation, ethical/religious/political/social conflicts, poverty, terrorism, technology and business failures only to mention a few may instantly propel systemic and global crises. Over the last 12 years for example the world has seen two major crises causing massive disruptions on a global scale: the world’s financial crisis and the Covid-19 crisis.

Firms need to develop a capability to cope with such crises: Organizational resilience is an organization’s ability to absorb strain and preserve or improve functioning, despite the presence of adversity. For this purpose, organizations need to comprehend complex situations, to cope with unexpected situations, and to control unwanted variability.

While understanding the factors that influence organizations’ resilience is of major relevance, however the corresponding empirical investigation is challenging due to a lack of data. What is needed are objective and high-quality data over time spans of many years. In order to serve investors and shareholders many institutions evaluate certain aspects of enterprises in terms of indices reaching from A as “Ardour Global Alternative Energy Index“ to W as “WilderHill New Energy Global Innovation Index“ and many more. Therefore, the question arises whether these indices would be suitable to study the question at hand. The objective of this master thesis would be to study indices from different institutions on a global scale and to extract single or segments of indices that can help to understand, explain and predict organizational resilience.

The master thesis research is based on a research cooperation between WU Vienna (Prof. Dr. Christopher Lettl) and TU Berlin (Prof. Dr. Jan Kratzer). When you are interested in this topic please shortly draft on 2-3 pages an outline/essay along the lines given here and send this per email to Christopher.Lettl(at)wu.ac.at and Prof. Dr. Jan Kratzer

Annual reports as a data source to study antecedents of organizational resilience

We live in times where major crisis can occur almost instantly and with limited possibility for firms to predict them. Events resulting from climate change, overpopulation, ethical/religious/political/social conflicts, poverty, terrorism, technology and business failures only to mention a few may instantly propel systemic and global crises. Over the last 12 years for example the world has seen two major crises causing massive disruptions on a global scale: the world’s financial crisis and the Covid-19 crisis.

Firms need to develop a capability to cope with such crises: Organizational resilience is an organization’s ability to absorb strain and preserve or improve functioning, despite the presence of adversity. For this purpose, organizations need to comprehend complex situations, to cope with unexpected situations, and to control unwanted variability.

While understanding the factors that influence organizations’ resilience is of major relevance, however the corresponding empirical investigation is challenging due to a lack of data. What is needed are objective and high-quality data over time spans of many years. Corporations and larger enterprises are by legal terms obliged to reveal data for its shareholders on an annual basis, so-called annual reports. Therefore, the question arises whether data in annual reports would be suitable to study the question at hand. The objective of this master thesis would be to study annual reports on a global scale and to extract patterns that can help to understand, explain and predict organizational resilience.

The master thesis research is based on a research cooperation between WU Vienna (Prof. Dr. Christopher Lettl) and TU Berlin (Prof. Dr. Jan Kratzer). When you are interested in this topic please shortly draft on 2-3 pages an outline/essay along the lines given here and send this per email to Christopher.Lettl(at)wu.ac.at and Prof. Dr. Jan Kratzer.