Achim Guldner, Rabea Bender, Coral Calero, Giovanni S Fernando, Markus Funke, Jens Gröger, Lorenz Hilty, Julian Hörnschemeyer, Geerd-Dietger Hoffmann, Dennis Junger, Tom Kennes, Sandro Kreten, Patricia Lago, Franziska Mai, Ivano Malavolta, Julien Murach, Kira Obergöker, Benno Schmidt, Arne Tarara, Joseph P De Veaugh-Geiss, Sebstian Weber, Max Westling, Volker Wohlgemuth, Stefan Naumann, Development and evaluation of a reference measurement model for assessing the resource and energy efficiency of software products and components—Green Software Measurement Model (GSMM), Future Generation Computer Systems, Vol. 155, 2024. (Journal Article)
In the past decade, research on measuring and assessing the environmental impact of software has gained significant momentum in science and industry. However, due to the large number of research groups, measurement setups, procedure models, tools, and general novelty of the research area, a comprehensive research framework has yet to be created. The literature documents several approaches from researchers and practitioners who have developed individual methods and models, along with more general ideas like the integration of software sustainability in the context of the UN Sustainable Development Goals, or science communication approaches to make the resource cost of software transparent to society. However, a reference measurement model for the energy and resource consumption of software is still missing. In this article, we jointly develop the Green Software Measurement Model (GSMM), in which we bring together the core ideas of the measurement models, setups, and methods of over 10 research groups in four countries who have done pioneering work in assessing the environmental impact of software. We briefly describe the different methods and models used by these research groups, derive the components of the GSMM from them, and then we discuss and evaluate the resulting reference model. By categorizing the existing measurement models and procedures and by providing guidelines for assimilating and tailoring existing methods, we expect this work to aid new researchers and practitioners who want to conduct measurements for their individual use cases. |
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Roberto Ulloa, Ana Carolina Richter, Mykola Makhortykh, Aleksandra Urman, Celina Sylwia Kacperski, Representativeness and face-ism: Gender bias in image search, New Media & Society, Vol. 26 (6), 2024. (Journal Article)
Implicit and explicit gender biases in media representations of individuals have long existed. Women are less likely to be represented in gender-neutral media content (representation bias), and their face-to-body ratio in images is often lower (face-ism bias). In this article, we look at representativeness and face-ism in search engine image results. We systematically queried four search engines (Google, Bing, Baidu, Yandex) from three locations, using two browsers and in two waves, with gender-neutral (person, intelligent person) and gendered (woman, intelligent woman, man, intelligent man) terminology, accessing the top 100 image results. We employed automatic identification for the individual’s gender expression (female/male) and the calculation of the face-to-body ratio of individuals depicted. We find that, as in other forms of media, search engine images perpetuate biases to the detriment of women, confirming the existence of the representation and face-ism biases. In-depth algorithmic debiasing with a specific focus on gender bias is overdue. |
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Massimo Filippini, Markus Leippold, Tobias Wekhof, Sustainable finance literacy and the determinants of sustainable investing, Journal of Banking and Finance, Vol. 163, 2024. (Journal Article)
In this paper, we survey a large sample of Swiss households to measure sustainable finance literacy, which we define as the knowledge and skill of identifying and assessing financial products according to their reported sustainability-related characteristics. To this end, we use multiple-choice questions. Furthermore, we measure Swiss private investors' level of awareness about sustainable financial products using open-ended questions. We find that Swiss households, which are generally highly financially literate by international standards, exhibit low levels of sustainable financial literacy compared to the current working definitions of sustainable finance. Moreover, despite its low level, knowledge about sustainable finance is a significant factor in the reported ownership of sustainable products. The empirical results also show a relatively low level of awareness. Generally, these empirical findings suggest a need to create transparent regulatory standards and strengthen information campaigns about sustainable financial products. |
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Emmanuel Mamatzakis, Steven Ongena, Pankaj C Patel, Mike Tsionas, A Bayesian policy learning model of COVID-19 non-pharmaceutical interventions, Applied Economics, Vol. 56 (25), 2024. (Journal Article)
This article examines the impact of non-pharmaceutical interventions on the initial exponential growth of the infected population and the final exponential decay of the infected population. We employ a Bayesian dynamic model to test whether there is learning, a random walk pattern, or another type of learning with evolving epidemiological data over time across 168 countries and 41,706 country-date observations. Although we show that Bayesian learning is not taking place, most policy measures appear to assert some effect. In particular, we show that economic policy variables are of importance for the main epidemiological parameters derived from the policy learning model. In an empirical second-stage application, we further investigate the underlying dynamics between the epidemiological parameters and household debt repayments, a key economic variable, in the UK. Results show no Bayesian learning, although a higher transmission rate would increase household debt repayments, while the recovery rate would have a negative impact. Therefore, suboptimal learning is taking place. |
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Narges Ashena, Oana Inel, Badrie L Persaud, Abraham Bernstein, Casual Users and Rational Choices within Differential Privacy, In: 2024 IEEE Symposium on Security and Privacy (SP), Institute of Electrical and Electronics Engineers, Los Alamitos, CA, USA, 2024-05. (Conference or Workshop Paper published in Proceedings)
In light of recent growth in privacy awareness and data ownership rights, differential privacy (DP) has emerged as a promising technique employed by several well-known data controller entities. This raises the question of how casual users, as the immediate recipients of privacy threats and risks, comprehend and perceive DP and its key parameter ε, as DP's provided protection depends on it. Existing studies show that ordinary users have the potential to understand the fundamental mechanism of DP and its implications for the privacy-utility trade-off when they are communicated clearly through textual and visual aids and, accordingly, make informed decisions about sharing their data under DP protection. However, these attempts either only implicitly mention a few possible values for ε, such as low, medium, and high, or altogether leave it out of the communication. In this paper, we conduct a between-subject user study (N=426) to investigate the effectiveness of nine interactive visual tools to communicate ε explicitly and on a continuous scale in a data-sharing scenario related to publishing positive COVID-19 test results. These interactive visual tools allow casual users to visualize DP's effects on data accuracy and/or privacy loss for various ε values. We found that visualizations incorporating the privacy loss component have a significant impact on assisting users in selecting values that are closer to the recommended values by experts. However, depending on the ratio between DP noise and underlying data, the accuracy loss component disparately affects users' ε decision; the bigger the relative error, the bigger the selected epsilon and vice versa. Thus, accuracy portrayals should be carried out with care. We contextualize our findings in the existing literature and conclude with insights and recommendations on effectively employing our findings to communicate DP to casual users. |
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Lauren Howe, Steven Shepherd, Nathan B Warren, Kathryn R Mercurio, Troy H Campbell, Expressing dual concern in criticism for wrongdoing: The persuasive power of criticizing with care, Journal of Business Ethics, Vol. 191 (2), 2024. (Journal Article)
To call attention to and motivate action on ethical issues in business or society, messengers often criticize groups for wrongdoing and ask these groups to change their behavior. When criticizing target groups, messengers frequently identify and express concern about harm caused to a victim group, and in the process address a target group by criticizing them for causing this harm and imploring them to change. However, we find that when messengers criticize a target group for causing harm to a victim group in this way—expressing singular concern for the victim group—members of the target group infer, often incorrectly, that the messenger views the target group as less moral and unworthy of concern. This inferred lack of moral concern reduces criticism acceptance and prompts backlash from the target group. To address this problem, we introduce dual concern messaging—messages that simultaneously communicate that a target group causes harm to a victim group and express concern for the target group. A series of several experiments demonstrate that dual concern messages reduce inferences that a critical messenger lacks moral concern for the criticized target group, increase the persuasiveness of the criticism among members of the target group, and reduce backlash from consumers against a corporate messenger. When pursuing justice for victims of a target group, dual concern messages that communicate concern for the victim group
as well as the target group are more effective in fostering openness toward criticism, rather than defensiveness, in a target group, thus setting the stage for change. |
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Suzanne Tolmeijer, Vicky Arpatzoglou, Luca Rossetto, Abraham Bernstein, Trolleys, crashes, and perception - a survey on how current autonomous vehicles debates invoke problematic expectations, AI and Ethics, Vol. 4 (2), 2024. (Journal Article)
Ongoing debates about ethical guidelines for autonomous vehicles mostly focus on variations of the ‘Trolley Problem’. Using variations of this ethical dilemma in preference surveys, possible implications for autonomous vehicles policy are discussed. In this work, we argue that the lack of realism in such scenarios leads to limited practical insights. We run an ethical preference survey for autonomous vehicles by including more realistic features, such as time pressure and a non-binary decision option. Our results indicate that such changes lead to different outcomes, calling into question how the current outcomes can be generalized. Additionally, we investigate the framing effects of the capabilities of autonomous vehicles and indicate that ongoing debates need to set realistic expectations on autonomous vehicle challenges. Based on our results, we call upon the field to re-frame the current debate towards more realistic discussions beyond the Trolley Problem and focus on which autonomous vehicle behavior is considered not to be acceptable, since a consensus on what the right solution is, is not reachable. |
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Pablo Koch Medina, Cosimo Munari, Qualitative robustness of utility-based risk measures, Annals of Operations Research, Vol. 336 (1-2), 2024. (Journal Article)
We contribute to the literature on statistical robustness of risk measures by computing the index of qualitative robustness for risk measures based on utility functions. This problem is intimately related to finding the natural domain of finiteness and continuity of such risk measures. |
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Kari A Leibowitz, Lauren Howe, Marcy Winget, Cati Brown-Johnson, Nadia Safaeinili, Jonathan Shaw, Deepa Thakor, Lawrence Kwan, Megan Mahoney, Alia J Crum, Medicine Plus Mindset: A Mixed-Methods Evaluation of a Novel Mindset-Focused Training for Primary Care Teams, Patient Education and Counseling, Vol. 122, 2024. (Journal Article)
Objectives
Patient mindsets influence health outcomes; yet trainings focused on care teams’ understanding, recognizing, and shaping patient mindsets do not exist. This paper aims to describe and evaluate initial reception of the “Medicine Plus Mindset” training program.
Methods
Clinicians and staff at five primary care clinics (N = 186) in the San Francisco Bay Area received the Medicine Plus Mindset Training. The Medicine Plus Mindset training consists of a two-hour training program plus a one-hour follow-up session including: (a) evidence to help care teams understand patients’ mindsets’ influence on treatment; (b) a framework to support care teams in identifying specific patient mindsets; and (c) strategies to shape patient mindsets.
Results
We used a common model (Kirkpatrick) to evaluate the training based on participants’ reaction, learnings, and behavior. Reaction: Participants rated the training as highly useful and enjoyable. Learnings: The training increased the perceived importance of mindsets in healthcare and improved self-reported efficacy of using mindsets in practice. Behavior: The training increased reported frequency of shaping patient mindsets.
Conclusions
Development of this training and the study’s results introduce a promising and feasible approach for integrating mindset into clinical practice.
Practice Implications
Mindset training can add a valuable dimension to clinical care and should be integrated into training and clinical practice. |
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Aleksandra Urman, Mykola Makhortykh, “Foreign beauties want to meet you”: The sexualization of women in Google’s organic and sponsored text search results, New Media & Society, Vol. 26 (5), 2024. (Journal Article)
Search engines serve as information gatekeepers on a multitude of topics dealing with different aspects of society. However, the ways search engines filter and rank information are prone to biases related to gender, ethnicity, and race. In this article, we conduct a systematic algorithm audit to examine how one specific form of bias, namely, sexualization, is manifested in Google’s text search results about different national and gender groups. We find evidence of the sexualization of women, particularly those from the Global South and East, in search outputs in both organic and sponsored search results. Our findings contribute to research on the sexualization of people in different forms of media, bias in web search, and algorithm auditing as well as have important implications for the ongoing debates about the responsibility of transnational tech companies for preventing systems they design from amplifying discrimination. |
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Anna Scolobig, Maria João Santos, Rémi Willemin, Richard Kock, Stefano Battiston, Owen Petchey, Mario Rohrer, Markus Stoffel, Learning from COVID-19: A roadmap for integrated risk assessment and management across shocks of pandemics, biodiversity loss, and climate change, Environmental Science & Policy, Vol. 155, 2024. (Journal Article)
The COVID-19 pandemic demonstrated the fragility of international, national, regional, and local risk management systems. It revealed an urgent need to improve risk planning, preparedness, and communication strategies. In parallel, it created an opportunity to drastically re-think and transform societal processes and policies to prevent future shocks originating not only from health, but also combined with those related to climate change and biodiversity loss. In this perspective, we examine how to improve integrated risk assessment and management (IRAM) capacities to address interconnected shocks. We present the results from a series of workshops within the framework of the University of Zurich and University of Geneva. Initiative "Shaping Resilient Societies: A Multi-Stakeholder Approach to Create a Responsive Society". This initiative gathered experts from multiple disciplines to discuss their perspectives on resilience; here we present the key messages of the "Pandemics, Climate and Sustainability” thinking group. We identify a roadmap and selected research areas concerning the improvement of IRAM analysis capacities, practices, policies. We recommend the development of robust data systems and science-policy advice systems to address combined shocks emerging from health, biodiversity loss and climate change. We posit that further developing the IRAM framework to include these recommendations will improve societal preparedness and response capacity and will provide more empirical evidence supporting decision-making and the selection of strategies and measures for integrated risk reduction. |
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Rainer Winkelmann, Neglected heterogeneity, Simpson’s paradox, and the anatomy of least squares, Journal of Econometric Methods, Vol. 13 (1), 2024. (Journal Article)
When a sample combines data from two or more groups, multivariate regression yields a matrix-weighted average of the group-specific coefficient vectors. However, it is possible that the weighted average of a specific coefficient falls outside the range of the group-specific coefficients, and it may even have a different sign compared to both group-level coefficients, a manifestation of Simpson’s paradox. The result of the combined regression is then prone to misinterpretation. The purpose of this paper is to raise awareness of this problem and to state conditions under which such non-convex weighting or sign reversal can arise, for a model with two regressors and two groups. Two illustrative examples, an investment equation estimated with panel data, and a cross-sectional earnings equation for men and women, highlight the relevance of these findings for applied work. |
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Alexander Soutschek, Christopher J Burke, Pyungwon Kang, Nuri Wieland, Nick Netzer, Philippe Tobler, Neural reward representations enable utilitarian welfare maximization, Journal of Neuroscience, 2024. (Journal Article)
From deciding which meal to prepare for our guests to trading-off the pro-environmental effects of climate protection measures against their economic costs, we often must consider the consequences of our actions for the well-being of others (welfare). Vexingly, the tastes and views of others can vary widely. To maximize welfare according to the utilitarian philosophical tradition, decision makers facing conflicting preferences of others should choose the option that maximizes the sum of subjective value (utility) of the entire group. This notion requires comparing intensities of preferences across individuals. However, it remains unclear whether such comparisons are possible at all, and (if they are possible) how they might be implemented in the brain. Here, we show that female and male participants can both learn the preferences of others by observing their choices, and represent these preferences on a common scale to make utilitarian welfare decisions. On the neural level, multivariate support vector regressions revealed that a distributed activity pattern in the ventromedial prefrontal cortex (VMPFC), a brain region previously associated with reward processing, represented preference strength of others. Strikingly, also the utilitarian welfare of others was represented in the VMPFC and relied on the same neural code as the estimated preferences of others. Together, our findings reveal that humans can behave as if they maximized utilitarian welfare using a specific utility representation and that the brain enables such choices by repurposing neural machinery processing the reward others receive.Significance statementIn many situations politicians and civilians strive to maximize the welfare of social groups. If the preferences of group members are in conflict, identifying the utilitarian welfare-maximizing option requires that decision makers can compare the strengths of conflicting preferences on a common scale. Yet, there is a fundamental lack of understanding which brain mechanisms enable such comparisons of conflicting utilities. Here, we show that brain regions involved in reward processing compute welfare comparisons by representing the preferences of others with a common neural code. This provides a neurobiological mechanism to compute utilitarian welfare maximization as desired by moral philosophy in the Humean tradition. |
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Alexander Lill, André Meyer, Thomas Fritz, On the Helpfulness of Answering Developer Questions on Discord with Similar Conversations and Posts from the Past, In: 46th International Conference on Software Engineering (ICSE 2024), ACM Digital library, 2024-04-14. (Conference or Workshop Paper published in Proceedings)
A big part of software developers’ time is spent finding answers to their coding-task-related questions. To answer their questions, developers usually perform web searches, ask questions on Q&A websites, or, more recently, in chat communities. Yet, many of these questions have frequently already been answered in previous chat conversations or other online communities. Automatically identifying and then suggesting these previous answers to the askers could, thus, save time and effort. In an empirical analysis, we first explored the frequency of repeating questions on the Discord chat platform and assessed our approach to identify them automatically. The approach was then evaluated with real-world developers in a field experiment, through which we received 142 ratings on the helpfulness of the suggestions we provided to help answer 277 questions that developers posted in four Discord communities. We further collected qualitative feedback through 53 surveys and 10 follow-up interviews. We found that the suggestions were considered helpful in 40% of the cases, that suggesting Stack Overflow posts is more often considered helpful than past Discord conversations, and that developers have difficulties describing their problems as search queries and, thus, prefer describing them as natural language questions in online communities. |
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Development in times of hype: How freelancers explore Generative AI?, In: ICSE '24: IEEE/ACM 46th International Conference on Software Engineering, IEEE/ACM, 2024-04-14. (Conference or Workshop Paper published in Proceedings)
The rise of generative AI has led many companies to hire freelancers to harness its potential. However, this technology presents unique challenges to developers who have not previously engaged with it. Freelancers may find these challenges daunting due to the absence of organizational support and their reliance on positive client feedback. In a study involving 52 freelance developers, we identified multiple challenges associated with developing solutions based on generative AI. Freelancers often struggle with aspects they perceive as unique to generative AI such as unpredictability of its output, the occurrence of hallucinations, and the inconsistent effort required due to trial-and-error prompting cycles. Further, the limitations of specific frameworks, such as token limits and long response times, add to the complexity. Hype-related issues, such as inflated client expectations and a rapidly evolving technological ecosystem, further exacerbate the difficulties. To address these issues, we propose Software Engineering for Generative AI (SE4GenAI) and Hype-Induced Software Engineering (HypeSE) as areas where the software engineering community can provide effective guidance. This support is essential for freelancers working with generative AI and other emerging technologies. |
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Bennet Schwoon, Dennis Schoeneborn, Andreas Scherer, Enacting a grand challenge for business and society: Theorizing issue maturation in the media-based public discourse on COVID-19 in three national contexts, Business & Society, Vol. 63 (4), 2024. (Journal Article)
While today it is universally acknowledged that COVID-19 has generated immense challenges for businesses and societies worldwide, public perceptions varied significantly at the time of the pandemic’s initial appearance, even among democratic societies with comparable media systems. The growing scholarship on grand societal challenges in management and organization studies, however, tends to neglect the initial social construction of issues as complex, uncertain, evaluative, and widespread. We address this shortcoming by exploring the initial communicative enactment of COVID-19 in the media-based public discourse in Switzerland, Germany, and the United Kingdom. By applying a social problem work lens, we identify three mechanisms that explain the maturation of COVID-19 into a grand challenge, further showing how these are contextually dependent on differences in discourse quality. We add to research on grand challenges, issue maturation, and framing dynamics by theorizing how issues become constructed and acknowledged as grand challenges in the first place. |
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Chiara Colesanti Senni, Skand Goel, Adrian von Jagow, Economic and financial consequences of water risks: The case of hydropower, Ecological Economics, Vol. 218, 2024. (Journal Article)
Reduced water availability poses risks for many economic activities. This paper studies how water risks affect hydroelectricity generation in Europe and the US and whether these risks are priced in by financial markets. To this end, we build a novel dataset for the period 2015–2022, which combines plant-specific hydroelectricity generation with geo-specific water physical risks and equity returns. We find that water risks, measured using model-based aggregate water risk metrics as well as precipitation anomalies, are significantly associated with reduced electricity generation, although the effect disap- pears after two months. We then link the power plants in our sample to the equity returns of their owners to investigate whether financial markets adequately price water risks. Using a portfolio sorts approach, we find weak evidence of a negative risk pre- mium. Given the real negative effect of water risks on generation, we conclude that the lack of a positive risk premium amounts to mispricing of water risks by financial markets. |
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Antonio Moreno, Steven Ongena, Alexia Ventula Veghazy, Alexander Wagner, “Long GFC”? The global financial crisis, health care, and COVID‐19 deaths, Economic Inquiry, Vol. 62 (2), 2024. (Journal Article)
Do financial crises affect long‐term public health? To answer this question, we examined the relationship between the 2007–2009 Global Financial Crisis (GFC) and the 2020–2022 COVID‐19 pandemic. Specifically, we examined the relationship between the financial losses derived from the GFC, and the health outcomes associated with the first wave of the pandemic. European countries that were more affected by the financial crisis had more deaths relative to coronavirus cases. An analogous relationship emerged across Spanish provinces and US states. Part of the transmission from finances to health outcomes appears to have occurred through cross‐sectional differences in health care facilities. |
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Andrew McBride, Lauren Howe, Janaki Gooty, George C Banks, Seeing with counterfactual lenses: Alternative assumptions at the intersection of leadership and identity, Leadership Quarterly, Vol. 35 (2), 2024. (Journal Article)
Two increasingly popular domains of research have made great strides explaining leadership via an identity lens (Haslam et al., 2022). These domains focus either on a leader’s own identity or on a leader’s influence in representing and altering the identities of others. Our paper contributes to these areas by highlighting dominant assumptions underlying the literatures and generating counterfactual assumptions in need of systematic exploration. It is important to acknowledge and evaluate assumptions because of the role they play in what we study and how we interpret data. As such, our paper brings existing assumptions to light and generates counterfactuals that are in need of more sustained empirical work. Our work thus sets out to a) expose existing assumptions at the intersection of leadership and identity, b) generate theoretically plausible counterfactual assumptions and c) identify themes tying our counterfactual assumptions together. Together, this paper supports, challenges, and promotes the extension of research applying an identity lens to leadership. |
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Shuqi Xu, Manuel Mariani, Linyuan Lu, Lorenzo Napolitano, Emanuele Pugliese, Andrea Zaccaria, Citations or dollars? Early signals of a firm’s research success, Technological Forecasting and Social Change, Vol. 201, 2024. (Journal Article)
Scientific and technological progress is largely driven by firms in many domains, including artificial intelligence and vaccine development. The early identification of the future performance of innovation players is a relevant goal for policymakers and practitioners. In this work, we investigate how the future trajectory of a firm can be predicted by the economic or technological value of its early patents. By inspecting the patenting life cycles of 7440 publicly listed firms, we find that the economic value of a firm’s early patents is an accurate predictor of various dimensions of a firm’s future research success. At the same time, a smaller set of future top-performers do not generate early patents of high economic value, but they are detectable via the technological value of their early patents. Importantly, the observed heterogeneity of the firms’ temporal success patterns markedly differs from the patterns previously observed for individuals’ research careers. |
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