Still today, women are significantly underrepresented in top executive positions. While progress towards a higher female rate has been made within the last years, the gender gap on top organizational level is still to be solved. Past studies have identified several factors which account for the gender gap, among them differences in network structures and access to knowledge and social resources, as they tend to disadvantage women in their career path. Even though precarious employment (e.g., part-time work, fixed-term contracts) has previously been acknowledged for its (negative) impact on female workers, its consequences have mostly been disregarded when examining the underrepresentation of women in top organizational positions. The aim of a Master Thesis in this field is to explore this topic further with a qualitative (interview study) or quantitative research study, for instance with regard to the factors causing the negative impact for women, future approaches which help to reduce the negative effects etc.

If you are interested in this topic, please send a short draft (max. 1 page) of your proposed topic along with the formulation of a specific research question and an outline for the thesis to:

Digital sustainable entrepreneurship, so the embeddedness of digital technologies in sustainable business models of newly founded companies, has been in the centre of researchers’ interest for some time. While so far the focus has mainly been on the blended value propositions, the extensive opportunities which digital technologies offer for new sustainable business models has not been investigated in detail.

We therefore seek master theses which look into how existing sustainable business models can implement digital technologies. The focus of the master thesis could either be on the asset which existing companies could gain from applying certain new technologies, or on the difficulties and threats associated with their application (for instance, regarding tensions between financial value of sustainable products and the costs of value creation). Are there specific (internal or external) preconditions for a company’s successful implementation of digital technologies? What hinders, what supports their application? Which roles do the customers play in the (successful) implementation of such “digital sustainable business model innovations”?

If you are interested in this topic and would like to discuss it further, please get in contact with

An ongoing discussion on gender-based factors in entrepreneurship has provided profound insights on several conditions which differ between women and men when starting a business, among them the distinct availability of resources and a discrepancy in the support provided by the founder’s ecosystem. However, once anticipating a successful foundation of the start-up, little is known on how/if the external perception of the venture with its associated success factors differs depending on who the founder is (see further the AMJ article by Kanze, Huang, Conley and Higgins, 2018: “We ask men to win and women not to lose: Closing the Gender Gap in startup funding”). We hence are interested in Master Theses which investigate the external perception of success, for instance through the analysis of newspaper data on startup success. How does the perception of female and male success differ? What is the different perception based on (e.g., personal characteristics, educational background, etc.)?

If you are interested in this topic, please send a short draft (max. 1 page) of your proposed topic along with the formulation of a specific research question and an outline for the thesis to:

Background

Creativity and innovation go hand in hand. Understanding the dynamics of highly creative industries such as the music sector, can help the understanding of innovation dynamics in less creative fields as well.

Even though the abundance of data resulting from the digitalization of the music industry, offers a great opportunity to study these creative dynamics and to answer innovation and creativity related research questions, identifying, fetching, and analyzing the right data is not a trivial task.

Projects in this field will be decidedly quantitative and oriented to the identification and combination of data sources that will be subsequently explored and analyzed to answer innovation and creativity related questions regarding:

• Spatial analysis of music-similarity

• Identification of causal effects from industry/policy shocks on artists and labels

• Nature and relevance of creativity on performance outcomes (e.g. analysis of antecedents and consequents of remixing music)

By working on this topic, you will:

1. ­Have the chance to engage in an “applied” M.Sc. dissertation project in which you can develop and showcase your data science skills.

2. Be providing a very valuable contribution to (hopefully) future published studies by IfSTO researchers.

 

Goal

Familiarizing with:

• Associating a research question on creativity and innovation to data analysis

• Data collection via data dumps, APIs, and web scraping

• Data cleaning

• Data analysis

Potential methods

Exclusively quantitative, most likely involving the collection of your own data via web-scraping, API or public data-dump queries.

Please note that, due to their data intensive nature, projects in this field require a certain familiarity with programming languages (i.e. Python or R) before initiating the project. While the topic lends itself well to expanding one’s programming and analysis competences (e.g. accessing new data sources, scraping an unfamiliar website, applying a new analysis technique – e.g. panel-data regression, spatial econometrics, ML-classification), it is not suitable for novices (i.e. no prior experience outside of online-courses or introductory workshops)

If you are interested, please contact:

Reasons for the failure of innovative ideas before they enter the market have been discussed for a long time, ranging from internal lack of support within the organization, a lack of funding, to missing commitment from the firms’ decision makers etc. Besides these issues, one of the crucial obstacles during the organizational idea generation process is the missing identification of the real value of ideas, meaning the clear identification of the problem statement and the solution that is offered with the innovative idea.

Companies often struggle to identify this real value of new ideas early on. We hence seek bachelor theses which address and analyse reasons for failure that are caused by the missing identification of value, and develop ideas for organizational mechanisms that can alleviate these effects. Preferably, this will either be accomplished with a case study approach or with an in-depth qualitative analysis.

If you are interested, please contact:

The Gender Data Gap refers to circumstances where the majority of data on which organisational decisions are based are biased in favor of men. That is, data are often incomplete and unreliable because of the absence of information about women’s preferences, fit, etc. (e.g., devices designed to optimally fit male handspans, personal protective equipment designed for male bodies, and organisational practices such as informal networking over drinks in the evening, when women and caregivers are not present). Understanding Gender Data Gap effects is important for designing effective interventions to achieve gender equality all the way up the organisational ladder. To address this research gap, we are interested in Bachelor Theses which enlarge our current understanding of the Gender Data Gap’s (negative) impact on women as well as on organizations altogether. Possible questions, which can be focused on, are (but are not limited to):

1.  How do firm- and industry-level factors contribute to Gender Data Gap effects on women’s careers?

2.  How does the Gender Data Gap affect women’s careers and upward mobility?

3.  To what extent do Gender Data Gaps cause or exacerbate toxic cultures and workplaces?

 

If you are interested, please contact:

Previous studies have started to investigate the most relevant knowledge ties of managers within their networks. Especially when considering the vital role of innovations for organizations, the understanding of where the most important knowledge for innovation endeavors originates from is of high importance. While some studies have found out that predominantly the cross-hierarchical network ties can have a special impact on the generation of organizational innovations, we still aim to find out more about – among others – the specific type of knowledge transmitted between network partners as well as potential differences between managerial levels (e.g., top level vs. low level)..

If you are interested, please contact:

Research on start-ups has indicated that the factor of gender – both on founder side as well as on investor side – can have a significant impact on whether the start-up receives funding, how it is perceived on the market, as well as how (possible) success and (possible) failure are rated. To investigate this topic further and to analyze the specific conditions when gender has an effect, we are interested in Bachelor Theses in this field. The topic can be examined from different angles, among others:

(1)     Do investors, who finance a start-up idea, evaluate the same business idea differently when the idea is proposed by an all-male/all-female team or a mixed team? Why?

(2)     Do externals (e.g., media) evaluate a (un-)successful start-up differently when the founder of the start-up is male vs. female? Why?

(3)     What is the success/failure ascribed to (e.g., un/fortunate market conditions, personal factors, etc.) in case of a male vs. female founder?

If you are interested, please contact:

Many important decisions are not made alone, but decision-makers seek advice from others. Previous research indicates that advice can increase the accuracy of decisions if utilized effectively. Many studies in the field of advice taking have employed controlled experimental setups using optimal decision environments. However in natural contexts, advice is often taken under suboptimal conditions such as time pressure. It is currently unclear how variables such as time pressure influences the utilization of advice and the accuracy of decisions.

I am looking for students, who are interested in conducting quantitative research (mostly in form of surveys/experiments, but other methodology is possible as well). The aim is to find out, how different decision environments influence advice taking. The results will be incorporated into my research.

Some examples for questions that we can work on are: What is the influence of cognitive load on advice utilization? How does advice taking under time pressure influence the accuracy of judgments? How does deliberation influence advice taking? Interest or knowledge in quantitative methodology and statistics is desirable.

If you are interested, please contact:

The generation and exchange of knowledge within or across a firm’s boundaries is a crucial driver of innovation. 
The events of the past years have radically shaken the way knowledge is generated and/or exchanged. On the one hand, Covid-19 has changed human interactions and imposed new practices to communicate using communication platforms such as Zoom, MS Teams, and others, that have altered knowledge flows within and between organizations, on the other the advent of new general purpose technologies such as Artificial Intelligence are revolutionizing how knowledge is generated.

The uses of these new GPTs and their implications on the effectiveness and efficiency of knowledge generation and flow are still unclear and so are the consequences of these practices for the firms’ innovating activity. Has the volume of knowledge generated and exchanged within and between organizations increased or decreased with these technologies? What about the quality of knowledge and of the innovations generated? Are there differences across firms or industries? 

Given the extremely fast adoption of these new GPTs, answering these questions and understanding how firms (un)successfully enhance their innovating activity using them is urgent and compelling. 

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When applying new knowledge to innovate there is a tradeoff between using general or specialized knowledge. Whereas general knowledge offers a broader overview within and across knowledge domains, it might be more difficult and time consuming to understand and apply. On the other hand, specialized knowledge is easily and quickly applicable “off the shelf” but narrow and limited in scope.

When considering artificial intelligence and its possible applications for innovation it is still unclear whether it represents a source of general or specialized knowledge (or both of them), for this reason, it is still unclear if and how it is subject to the discussed trade-off.

Opening the black box and better understanding what AI (and its individual user interfaces) represent in terms of knowledge generated is of utmost important to understand how to properly use this tool in the context of innovation.

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Corporate Venture Capitalists sharing knowledge with start-ups: good or bad? For whom?

A Corporate Venture Capitalist (CVC) can offer more than just financial support to a start-up. For example, a CVC’s complementary resources are often a valuable asset that the new firm can leverage to scale up and be successful.

Recent research has started to look at the role of a CVC’s knowledge in steering the innovations of the start-up firm that can use this knowledge, as well as at the benefits in terms of innovation that a CVC receives from sharing its knowledge with a start-up. Indeed, since the knowledge shared can be analyzed by several perspectives such as the attributes of the knowledge exchanged, the mode with which it is exchanged, or the amount of knowledge exchanged, the implications of sharing knowledge between these two entities are not straight-forward and deserve investigation.
Taking different perspectives, we will delve into understanding how several aspects related to the sharing of knowledge between a CVC and a start-up affect both parties' innovating activity.

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I am looking for students, who are interested in conducting quantitative research (mostly in form of surveys/experiments, but other methodology is possible as well). The aim is to find out, under which conditions crowds act wise or mad, what impact crowd characteristics, social influence and cognitive biases have. The results will be incorporated into my research.

The wisdom of crowds in form of forecasts, decisions and evaluations is used in a variety of contexts ranging from sports, over politics to business applications. The underlying logic of crowd decisions is that crowds can be on average more accurate than individuals and even experts. However, there remain many open questions: How can we reduce herding behavior in crowd decisions? What influence do the characteristics of a crowd have? Do individual cognitive biases aggregate on a collective level? These are examples for overarching questions, we can research together in context of a bachelor thesis.

If you are interested please contact: