Contributions in Merlin

While designing an HCI experiment, planning the sample size with a priori power analysis is often skipped due to the lack of reference effect sizes. On the one hand, it can lead to a false-negative result, missing the effect that is present in the population. On the other hand, it poses a risk of spending more resources if the number of participants is too high. In this work, I present the reference for small, medium, and large effect sizes for typing experiments based on a meta-analysis of well-cited papers from CHI conference. This effect size ruler can be used to conduct a priori power analysis or assess the magnitude of the found effect. This work also includes comparisons to other fields and conclude with a discussion of the existing issues with reporting practices and data availability. This paper and all data and materials are freely available at https://osf.io/nqzpr.

Der Zürcher Finanzprofessor Alexander Wagner beobachtete schon vor drei Jahren, dass die Aktien von Unternehmen mit klimafreundlichen Geschäftsstrategien auch unter Donald Trump überraschend hohe Renditen erzielten. Nun ist der Grund dafür klar.

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This Thesis examines how risk factors are priced in Switzerland from 1991 to 2019. Firstly, the Carhart four-factor model is applied, nding positive premiums for value and momentum and a negative premium for size. Momentum performs steadily throughout the whole period, while, consistent with international ndings, value stocks did not outperform growth stocks in the last decade. All Carhart factors improve the explanation of returns and are relevant to the Swiss market. Secondly, the model is extended with an international fear factor, and consistent with theory I nd that global fear is priced on the Swiss stock market and that stocks with low sensitivity to global uncertainty exhibit lower returns.

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The purpose of this thesis is to design a digital tool to support patients having atherosclerosis. I first identified the patients' expectations and needs. Then, I designed the features of the tool. 3 prototypes were designed, 6 consultations were filmed and reviewed, 28 interviews with patients and physicians took place, and 4 focus groups were held throughout the project. Research shows that patients forget the information provided by their doctor. The adherence to the treatment – which is central to the control of atherosclerosis and in the prevention of its complications such as heart attack or stroke – depends on the perception of the threats from the disease and on the understanding of the physician's recommendations. The prototype aimed to provide a tool explaining the disease, the risk factors, and keeping a record of health values, in order to support patients in between consultations. The patient could learn from the app, but she would also be requested to be proactive by frequently entering data into the app, such as weight, hours of exercise per week, or blood pressure. Hence, doctors would interact during the consultations with patients who are more informed, prepared and involved. The last version of the tool was a clickable prototype. Patients and physicians were enthusiastic about it. Many participants acknowledged that this conceptual model of the app already helped them to better understand atherosclerosis and its risk factors. They would all agree and be motivated to use it. However, further research is needed to, first, implement a real application and, second, test its effects and usage in a field study in order to validate if it would positively influence adherence.

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The field of Human-Computer Interaction has recently taken a growing interest in research with disadvantaged, marginalized communities, and participants, such as motor-impaired users, homeless adults, or people who struggle with mental health. These collaborations turned out to be very fruitful, because they enable the creation of designs such as automatically generated ability-based interfaces, communication and social support for visually impaired as well as homeless people. Previous scholarship has shown that there is a greater need to address the issues of marginalized and disadvantaged groups and that the incorporation of Human-Computer Interaction promises innovative solutions that significantly improve the lives of these groups. In cooperation with the Swiss Centre of Competence against Forced Marriage, this thesis explores the issue of forced marriage in Switzerland and the restrictions and challenges it imposes on creating a technical solution. The thesis proposes an app, designed through the findings of several interviews with affected, to help people affected by forced marriages in Switzerland, and tests and discusses its feasibility of use.

Within the past few years, public and permissionless blockchain projects (such as cryptocurrencies) have managed to change our perception of prevailing economic and organizational infrastructures. Foremostly, stakeholders of such projects are embedded in an (allegedly) decentralized governance structure. The importance of interest and incentive alignment across stakeholders within such projects is shown by academia. However, the granularity of so far elaborated frameworks is not high enough to profoundly capture these aspects. Moreover, a specific allocation of such interests and incentives to concrete stakeholders (or clusters thereof) is still missing, and a problematic oversimplification of stakeholder groups in public blockchains is present in literature. In the context of blockchain governance and a stakeholder analysis, we empirically derived a new framework, specifically tailored towards stakeholders, their interests and underlying rationale in public blockchains. We operationalized this framework (survey development) and gathered data on suitable online platforms. The data analysis allowed us to identify three main stakeholder clusters: user-investor, user-validator, and validator-investor. Using different (proprietary) analytical approaches, we profiled these clusters with comparable attributes regarding their inherent interest prioritisations and rationales (including motives and incentives). Based on these insights, we eventually derived lessons for (future) blockchain projects.