Tobias Schultheiss, Uschi Backes-Gellner, Does updating education curricula accelerate technology adoption in the workplace? Evidence from dual vocational education and training curricula in Switzerland, Journal of Technology Transfer, 2022. (Journal Article)
 
In an environment of accelerating technological change and increasing digitalization, firms need to adopt new technologies faster than ever before to stay competitive. This paper examines whether updates of education curricula help to bring new technologies faster into firms’ workplaces. We study technology changes and curriculum updates from an early wave of digitalization (i.e., computer-numerically controlled machinery, computer-aided design, and desktop publishing software). We take a text-as-data approach and tap into two novel data sources to measure change in educational content and the use of technology at the workplace: first, vocational education curricula and, second, firms’ job advertisements. To examine the causal effects of adding new technology skills to curricula on the diffusion of these technologies in firms’ workplaces (measured by job advertisements), we use an event study design. Our results show that curriculum updates substantially shorten the time it takes for new technologies to arrive in firms’ workplaces, especially for mainstream firms. |
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Lucien Heitz, Juliane A Lischka, Alena Birrer, Bibek Paudel, Suzanne Tolmeijer, Laura Laugwitz, Abraham Bernstein, Benefits of Diverse News Recommendations for Democracy: A User Study, Digital Journalism, Vol. 10 (10), 2022. (Journal Article)
 
News recommender systems provide a technological architecture that helps shaping public discourse. Following a normative approach to news recommender system design, we test utility and external effects of a diversity-aware news recommender algorithm. In an experimental study using a custom-built news app, we show that diversity-optimized recommendations (1) perform similar to methods optimizing for user preferences regarding user utility, (2) that diverse news recommendations are related to a higher tolerance for opposing views, especially for politically conservative users, and (3) that diverse news recommender systems may nudge users towards preferring news with differing or even opposing views. We conclude that diverse news recommendations can have a depolarizing capacity for democratic societies. |
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Nori Geary, Lori Asarian, Gwendolyn Graf, Susanna Gobbi, Philippe Tobler, Jens F Rehfeld, Brigitte Leeners, Increased meal size but reduced meal-stimulated plasma cholecystokinin concentrations in women with obesity, Endocrinology, Vol. 164 (1), 2022. (Journal Article)
 
To better understand the physiological basis of obesity in women, we investigated whether obesity or menstrual cycle phase affects laboratory test-meal size or meal-stimulated plasma cholecystokinin (CCK) concentration. Women with healthy weight (body mass index [BMI] of 18.5-24.9 kg/m2, N = 16) or obesity (BMI 30-39.9 kg/m2, N = 20) were tested once in the late-follicular or peri-ovulatory phase (LF/PO) and once in the mid-luteal phase (ML). Meals of ham sandwiches were offered and blood was sampled. Menstrual cycle phases were verified with participants’ reports of menses and measurements of progesterone and luteinizing hormone (LH) concentrations. Women with obesity ate significantly larger meals than women with healthy weight, (mean, 711 [95% CI, 402-1013] kJ, P = 0.001, during the LF/PO and 426 [105-734] kJ, P = 0.027, larger during the ML). Women with healthy weight ate smaller meals during LF/PO than ML (decrease, 510 [192-821 kJ], P = 0.008), but women with obesity did not (decrease, 226 [−87-542] kJ, P = 0.15). CCK concentrations 18 to 30 minutes after meal onset were lower in women with obesity than in women with healthy weight during LF/PO (3.6 [3.1-4.1] vs 6.1 [4.5-7.7] pmol/L; P = 0.004), but not during ML, with a significant interaction effect (1.8 [1.2-2.4] pmol/L, P = 0.048). Women with obesity consumed larger meals than women with healthy weight but displayed reduced meal-stimulated plasma CCK concentrations. These data are consistent with the hypothesis that a defect in CCK secretion compromises satiation in obese women and contributes to the development or maintenance of obesity. |
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Urban Ulrych, Nikola Vasiljevic, Global Currency Hedging with Ambiguity, In: Brown Bad Lunch Seminar. 2022. (Conference Presentation)

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Giulia Crestini, Andrea Giuffredi-Kähr, Radu Petru Tanase, Martin Natter, Does Pricing Transparency Benefit or Harm the Retailer-Customer Relationship?, In: Annual Conference of the Decision Sciences Institute. 2022. (Conference Presentation)

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Silke Adam, Aleksandra Urman, Dorothee Arlt, Teresa Gil-Lopez, Mykola Makhortykh, Michaela Maier, Media Trust and the COVID-19 Pandemic: An Analysis of Short-Term Trust Changes, Their Ideological Drivers and Consequences in Switzerland, Communication Research, 2022. (Journal Article)

We analyze short-term media trust changes during the COVID-19 pandemic, their ideological drivers and consequences based on panel data in German-speaking Switzerland. We thereby differentiate trust in political information from different types of traditional and non-traditional media. COVID-19 serves as a natural experiment, in which citizens’ media trust at the outbreak of the crisis is compared with the same variables after the severe lockdown measures were lifted. Our data reveal that (1) media trust is consequential as it is associated with people’s willingness to follow Covid-19 regulations; (2) media trust changes during the pandemic, with trust levels for most media decreasing, with the exception of public service broadcasting; (3) trust losses are hardly connected to ideological divides in Switzerland. Our findings highlight that public service broadcasting plays an exceptional role in the fight against a pandemic and that contrary to the US, no partisan trust divide occurs. |
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Pavlína Wurzelová, Gül Çalikli, Alberto Bacchelli, Interpersonal Conflicts During Code Review, In: 25th ACM Conference On Computer-Supported Cooperative Work And Social Computing, ACM, New York, USA, 2022. (Conference or Workshop Paper published in Proceedings)
 
Code review consists of manual inspection, discussion, and judgment of source code by developers other than the code's author. Due to discussions around competing ideas and group decision-making processes, interpersonal conflicts during code reviews are expected. This study systematically investigates how developers perceive code review conflicts and addresses interpersonal conflicts during code reviews as a theoretical construct. Through the thematic analysis of interviews conducted with 22 developers, we confirm that conflicts during code reviews are commonplace, anticipated and seen as normal by developers. Even though conflicts do happen and carry a negative impact for the review, conflicts-if resolved constructively-can also create value and bring improvement. Moreover, the analysis provided insights on how strongly conflicts during code review and its context (i.e., code, developer, team, organization) are intertwined. Finally, there are aspects specific to code review conflicts that call for the research and application of customized conflict resolution and management techniques, some of which are discussed in this paper. Data and material: https://doi.org/10.5281/zenodo.5848794 |
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Anna Giarratana, Mariia Kaliuzhna, Stefan Kaiser, Philippe Tobler, Adaptive coding occurs in object categorization and may not be associated with schizotypal personality traits, Scientific Reports, Vol. 12 (1), 2022. (Journal Article)
 
Processing more likely inputs with higher sensitivity (adaptive coding) enables the brain to represent the large range of inputs coming in from the world. Healthy individuals high in schizotypy show reduced adaptive coding in the reward domain but it is an open question whether these deficits extend to non-motivational domains, such as object categorization. Here, we develop a novel variant of a classic task to test range adaptation for face/house categorization in healthy participants on the psychosis spectrum. In each trial of this task, participants decide whether a presented image is a face or a house. Images vary on a face-house continuum and appear in both wide and narrow range blocks. The wide range block includes most of the face-house continuum (2.50–97.5% face), while the narrow range blocks limit inputs to a smaller section of the continuum (27.5–72.5% face). Adaptive coding corresponds to better performance for the overlapping smaller section of the continuum in the narrow range than in the wide range block. We find that participants show efficient use of the range in this task, with more accurate responses in the overlapping section for the narrow range blocks relative to the wide range blocks. However, we find little evidence that range adaptation in our object categorization task is reduced in healthy individuals scoring high on schizotypy. Thus, reduced range adaptation may not be a domain-general feature of schizotypy. |
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Erich Walter Farkas, Francesco Ferrari, Urban Ulrych, Pricing Autocallables under Local-Stochastic Volatility, In: Peter Carr Gedenkschrift Conference. 2022. (Conference Presentation)

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Lutharsanen Kunam, Luca Rossetto, Abraham Bernstein, A Multi-Stream Approach for Video Understanding, In: MM '22: The 30th ACM International Conference on Multimedia, ACM, New York, NY, USA, 2022. (Conference or Workshop Paper published in Proceedings)
 
The automatic annotation of higher-level semantic information in long-form video content is still a challenging task. The Deep Video Understanding (DVU) Challenge aims at catalyzing progress in this area by offering common data and tasks. In this paper, we present our contribution to the 3rd DVU challenge. Our approach consists of multiple information streams extracted from both the visual and the audio modality. The streams can build on information generated by previous streams to increase their semantic descriptiveness. Finally, the output of all streams can be aggregated in order to produce a graph representation of the input movie to represent the semantic relationships between the relevant characters. |
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Jakub Loko, Klaus Schoeffmann, Werner Bailer, Luca Rossetto, Björn þóR Jónsson, Open Challenges of Interactive Video Search and Evaluation, In: MM '22: The 30th ACM International Conference on Multimedia, ACM, New York, NY, USA, 2022-11-10. (Conference or Workshop Paper)
 
During the last 10 years of Video Browser Showdown (VBS), there were many different approaches tested for known-item search and ad-hoc search tasks. Undoubtedly, teams incorporating state-of-the-art models from the machine learning domain had an advantage over teams focusing just on interactive interfaces. On the other hand, VBS results indicate that effective means of interaction with a search system is still necessary to accomplish challenging search tasks. In this tutorial, we summarize successful deep models tested at the Video Browser Showdown as well as interfaces designed on top of corresponding distance/similarity spaces. Our broad experience with competition organization and evaluation will be presented as well, focusing on promising findings and also challenging problems from the most recent iterations of the Video Browser Showdown. |
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Luca Rossetto, Werner Bailer, Jakub Lokoč, Klaus Schoeffmann, IMuR 2022 Introduction to the 2nd Workshop on Interactive Multimedia Retrieval, In: MM '22: The 30th ACM International Conference on Multimedia, ACM, New York, NY, USA, 2022. (Conference or Workshop Paper)
 
The retrieval of multimedia content remains a difficult problem where a high accuracy or specificity can often only be achieved interactively, with a user working closely and iteratively with a retrieval system. While there exist several venues for the exchange of insights in the area of information retrieval in general and multimedia retrieval specifically, there is little discussion on such interactive retrieval approaches. The Workshop on Interactive Multimedia Retrieval offers such a venue. Held for the 2nd time in 2022, it attracted a diverse set of contributions, six of which were accepted for presentation. The following provides a brief overview of the workshop itself as well as the contributions of 2022. |
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Loris Sauter, Ralph Gasser, Abraham Bernstein, Heiko Schuldt, Luca Rossetto, An Asynchronous Scheme for the Distributed Evaluation of Interactive Multimedia Retrieval, In: MM '22: The 30th ACM International Conference on Multimedia, ACM, New York, NY, USA, 2022-11-10. (Conference or Workshop Paper published in Proceedings)
 
Evaluation campaigns for interactive multimedia retrieval, such as the Video Browser Shodown (VBS) or the Lifelog Search Challenge (LSC), so far imposed constraints on both simultaneity and locality of all participants, requiring them to solve the same tasks in the same place, at the same time and under the same conditions. These constraints are in contrast to other evaluation campaigns that do not focus on interactivity, where participants can process the tasks in any place at any time. The recent travel restrictions necessitated the relaxation of the locality constraint of interactive campaigns, enabling participants to take place from an arbitrary location. Born out of necessity, this relaxation turned out to be a boon since it greatly simplified the evaluation process and enabled organisation of ad-hoc evaluations outside of the large campaigns. However, it also introduced an additional complication in cases where participants were spread over several time zones. In this paper, we introduce an evaluation scheme for interactive retrieval evaluation that relaxes both the simultaneity and locality constraints, enabling participation from any place at any time within a predefined time frame. This scheme, as implemented in the Distributed Retrieval Evaluation Server (DRES), enables novel ways of conducting interactive retrieval evaluation and bridged the gap between interactive campaigns and non-interactive ones. |
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Alexander Wagner, Krisen und nachhaltige Investitionen, In: The Market, p. online, 9 November 2022. (Newspaper Article)
 
Die Erwartung ist klar: Nachhaltige Investitionen sollten in Krisenzeiten besser abschneiden als der Markt. Doch genau das zeigte sich beim Angriff Russlands auf die Ukraine nicht. Das muss Ansporn sein, mit klareren Faktoren die widerstandsfähigen Unternehmen zu identifizieren. |
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Tobias Schlegel, Curdin Pfister, Uschi Backes-Gellner, Tertiary education expansion and regional firm development, Regional Studies, Vol. 56 (11), 2022. (Journal Article)
 
This study investigates the impact of a tertiary education expansion on regional firm development, as measured by average profits per firm. We exploit the quasi-random establishment of universities of applied sciences (UASs) – bachelor’s degree-granting three-year colleges teaching and conducting applied research – to construct treatment and control groups and to apply both a difference-in-differences model and an event study design. We find that after the establishment of new UASs in Switzerland, average profits per firm in the treated municipalities increase by 19.6% more than in the control group. This increase corresponds roughly to an additional annual growth in average profits per firm in the treatment group of 0.7%. The effects start shortly after the establishment of UASs but also persist over a period of up to 10 years. |
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Lauren Howe, Jochen Menges, Remote work mindsets predict emotions and productivity in home office: A longitudinal study of knowledge workers during the Covid-19 pandemic, Human - Computer Interaction, Vol. 37 (6), 2022. (Journal Article)
 
Millions of employees across the globe, including a large proportion of knowledge workers, transitioned to remote work during the COVID-19 pandemic. As remote work continues to characterize work post-crisis, it is imperative to understand how employees adjust to remote work. The current research explores the extent to which knowledge workers hold a fixed mindset about remote work (e.g., that a person either is or is not suited to remote work and this cannot be changed) and tested how this mindset shaped well-being during coronavirus-related lockdown. In a longitudinal five-week study of 113 knowledge workers transitioning to remote work, we find that knowledge workers who endorsed a more fixed mindset about remote work experienced more negative and less positive emotion during remote work. The increased negative emotion prompted by fixed mindsets was associated with lesser perceived productivity among these knowledge workers in subsequent weeks. We conclude that understanding how fundamental beliefs (e.g., beliefs about the learnability of remote work) affect employee experiences can help create a brighter future as technology further enables remote work. Encouraging employees to view remote work as a skill that can be learned and developed could help people thrive in the new world of work. |
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Xianxiao Xu, Multiclass Outlier Detection and Visualization Based on Isolation Forest, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
 
Isolation forest is a popular anomaly detector due to its model-free structure and validity in detecting outliers across different types of datasets. This thesis presents solutions for two main issues in terms of isolation-based outlier detection algorithms. First, there is an adjustment to the isolation-based outlier detection model to improve the detection accuracy of Isolation Forest (iForest) and Extended Isolation Forest (EIF). The EIF is an extension of iForest, which addresses the block artifacts issue of iForest. Motivated by the failures of outlier detection on some real-world benchmark datasets by EIF, an adjusted EIF regarding the problem arising from the randomness of split hyperplane is presented. The outlier detection accuracy and precision of the adjusted EIF show that it is capable of enhancing the performance of both iForest and EIF. However, the drawback of the adjustment is that it is not time efficient. Second, this thesis proposes methods to generate a credible image presentation with outliers scattered in the relative areas based on isolation-based detection for multi-variate datasets. Inspired by the fact that neither iForest nor EIF can detect local outliers for each class in multi-class datasets, and few related works have been done in this direction, several class-wise detectors based on EIF and adjusted EIF are proposed in this thesis. By comparing the graphs, one of the methods achieves the best performance in providing insights for identifying potential outliers in clustering datasets. |
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Maximilian Tornow, Item-Based Ranking Creation: A Human-Centered Approach Combining Visual Analytics with Active Learning, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
 
With the ever-increasing amount of and widely spread access to data, decision-making is becoming a complex task. Decision-making tasks can often be supported by utilizing rankings to help decision-makers to understand their different options. Existing solutions for the creation of
rankings are often time-consuming, targeted towards experts only, unintuitive to use, or attributebased and therefore need mathematical understanding for their interpretation.
We propose Ranking Companion, a human-centered approach combining visual analytics with active learning to create item-based ranking. Ranking Companion makes rankings intuitively and interactively available to end users, while reducing the necessary amount of input provided by
users to create meaningful rankings. Our novel approach allows users to create rankings iteratively and remain in full control of the input provided to the machine learning model. Moreover, Ranking Companion provides explainability for the underlying machine learning model.
In this work, we apply Ranking Companion in a decision task in the musical domain: finding new artists to listen to. Our approach is evaluated using feedback on design iterations by visual analytics experts, a usage scenario, as well as a case study. The evaluations show that the approach indeed decreases time necessary for providing model input, while increasing user acceptance of the provided rankings for certain user groups. |
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Tanzil Kombarabettu, Human-in-the loop simulation-based testing for self-driving cars, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)

Simulation-based testing helps in the improvement of cyber-physical systems (CPS) such as self-driving cars (SDC) because it increases the efficiency, diversity, and relevance of tests from a human perspective. The importance of human feedback in validating test cases cannot be overstated. Despite this, testing SDCs in simulated environments does not take human factors into account. Previous research demonstrates how to optimize the test case through selection, improve classification and accuracy when test cases result in a fault, and improve testing cost-effectiveness. However, test validity, relevance, and safety perception from a hu- man point of view were not addressed. In this thesis, we investigate the variety of possible scenarios (static and dynamic obstacles) and examine how humans perceive safety and the level of realism of the SDC test case with various factors such as interaction with the car and different views (i.e., the VR view, the outside view, and the driver’s view). We propose an approach called SDC-Alabaster (SDC humAn-in-the Loop simulAtion-BASed Testing sElf- driving caRs) that uses a virtual reality (VR) headset to illustrate SDC test scenarios, create the sensation of being in SDCs and to enable users to experiment with the experience. Our results show the perception of realism and safety without obstacles is higher than with ob- stacles, and CARLA was more realistic and safer than the BeamNG simulator with a p-value > 0.01e-16, The distribution is 85%( ˆA12). Our results also show interactions with vehicles make humans safer compared to those without interactions with a p-value > 0.001, and the distribution is 36%( ˆA12), and users’ perceptions of safety and realism vary with and without VR headsets, and the failure cases that are most important to test are also regarded as less re- alistic by participants’. In addition, we discovered factors such as using an advanced AI agent for traffic cars, using voice feedback in VR, and integrating participants’ driving will help test scenarios be more realistic, and the perception of participants’ safety can be improved in simulation-based testing of SDCs. |
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Lukas Zehnder, Costs of Code Review Goals and Code Review Strategies, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Master's Thesis)
 
The reviewer’s mental attitude might be the reason for detecting or missing defects while reviewing code. Previous research showed that asking developers to focus on security vulnerabilities while reviewing code increased the likelihood of vulnerability detection by eight times.
In this study, we investigated the effects of a code review goal on the review effectiveness and examined the differences between strategy descriptions of high-performing and low-performing reviewers. We conducted an online code review experiment with 56 participants, which were assigned to three treatments: Ad-hoc Review, Functional Instructions and Security Instructions. Our results indicate that a code review goal in form of a functional instruction decreases the likelihood of finding security defects by five times. However, we did not find a significant relationship between a security goal and functional issues. Furthermore, we could not confirm the results of a previous study that a security instruction increases the likelihood of finding security defects. In regards to strategies, high-performing participants reported more often to perform security checks than low-performing participants. These results are an initial indication of the effect of goals on code review effectiveness and the differences between the strategy descriptions
of low- and high-performing reviewers.
Data and Material: https://doi.org/10.5281/zenodo.7323595 |
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