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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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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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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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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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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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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Pejman Abedifar, Seyed Javad Kashizadeh, Steven Ongena, Flood, farms and credit: The role of branch banking in the era of climate change, Journal of Corporate Finance, Vol. 85, 2024. (Journal Article)
Using Iran’s unexpected flood in April 2019 as a natural experiment, we show that local branches bridge the time gap between the disaster and governmental aids by immediately increasing their lending for two months following the flood. Analyzing proprietary information on more than 53,000 farmers, we find that farmers with a stronger relationship with their branch - particularly younger and females - are more likely to receive a recovery loan. Our findings underscore that despite recent technological advancements, relationship-based branch banking is still important for agrarian societies during catastrophic events. |
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Lucia Alessi, Stefano Battiston, Virmantas Kvedaras, Over with carbon? Investors’ reaction to the Paris Agreement and the US withdrawal, Journal of Financial Stability, Vol. 71, 2024. (Journal Article)
How financial investors may react to policy events related to sustainability and climate change mitigation in particular, is a key question with implications for sustainable finance and financial stability. We address this question by carrying out a multi-period difference-in-difference approach on a confidential database of securities holdings of the European Central Bank, and we provide evidence of several effects related to the Paris Agreement. In aggregate, investors reduced their participation in the equities of high-carbon firms in response to the agreement, and the trend reverted after the US’s announcement of withdrawal from the agreement. However, the reaction varies across categories and geographies of the securities holders, their ownership size, and the emissions of owned firms. In particular, transition risk has been taken up by less regulated financial institutions and the BRIC countries. Our results highlight that the redirection of global financial flows towards climate action requires clear and unanimous signals from the global community of policy makers. |
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Henrik Cronqvist, Tomislav Ladika, Elisa Pazaj, Zacharias Sautner, Limited attention to detail in financial markets: Evidence from reduced-form and structural estimation, Journal of Financial Economics, Vol. 154, 2024. (Journal Article)
We show that firm valuations fell after a key expense became more visible in financial statements. FAS 123-R required firms to deduct option compensation costs from earnings, instead of disclosing them in footnotes. Firms that granted high option pay experienced earnings reductions, while fundamentals remained unchanged. These firms were more likely to miss earnings forecasts, and they experienced recommendation downgrades and valuation declines. Our findings suggest that market participants exhibited limited attention to option costs before FAS 123-R. As we reuse the FAS 123-R natural experiment, we show how one can address confounding channels by integrating reduced-form and structural estimation. |
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Grzegorz Hałaj, Serafin Martinez-Jaramillo, Stefano Battiston, Financial stability through the lens of complex systems, Journal of Financial Stability, Vol. 71, 2024. (Journal Article)
In this cover paper, we introduce a Special Issue (SI) published after the fourth edition of a series of financial stability conferences organized by Bank of Mexico, CEMLA, Bank of Canada, Zurich University and the Journal of Financial Stability in November 2021. Before providing our perspective on why the research papers included into the SI are of great relevance, we give a brief and personal overview of recent directions in financial stability research in general, esp., related to topics accentuated by the COVID-19 pandemic or post-pandemic economic and financial conditions and their complexity. Papers published in the SI cover four topics of research in the financial stability field, featuring some outstanding and innovative projects presented during the conference. The first topic is on interconnectedness and shock transmission in the financial system, diving deep into asset fire sales, interconnectedness of various segments of the financial system, in addition to banks, on the optimality of systemic risk capital buffers, and on how risks are priced in the interbank market network. The second one touches upon climate change risks looking at investors’ reactions to international climate policy developments, in particular on the Paris Agreement front and how to jointly model physical and transition risk in the banking system, including the important concept of double materiality. The third topic is represented by projects focused on policy analysis for systemic risk mitigation, specifically dealing with macroprudential policy instruments and crisis mitigation policies. Finally, research papers in the last topic on big data and market data focus on the innovative ways to explore the growing body of data sources, such as data collected by regulators, including credit register data, supervisory data and market data on financial transactions, to better understand sources and implications of systemic risk. |
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Manuel Mariani, Dario Mazzilli, Aurelio Patelli, Dries Sels, Flaviano Morone, Ranking species in complex ecosystems through nestedness maximization, Communications Physics, Vol. 7 (102), 2024. (Journal Article)
Identifying the rank of species in a complex ecosystem is a difficult task, since the rank of each species invariably depends on the interactions stipulated with other species through the adjacency matrix of the network. A common ranking method in economic and ecological networks is to sort the nodes such that the layout of the reordered adjacency matrix looks maximally nested with all nonzero entries packed in the upper left corner, called Nestedness Maximization Problem (NMP). Here we solve this problem by defining a suitable cost-energy function for the NMP which reveals the equivalence between the NMP and the Quadratic Assignment Problem, one of the most important combinatorial optimization problems, and use statistical physics techniques to derive a set of self-consistent equationswhose fixed point represents the optimal nodes’ rankings in an arbitrary bipartite mutualistic network. Concurrently, we present an efficient algorithm to solve the NMP that outperforms state-ofthe- art network-based metrics and genetic algorithms. Eventually, our theoretical framework may be easily generalized to study the relationship between ranking and network structure beyond pairwise interactions, e.g. in higher-order networks. |
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Lorenzo Casaburi, Jack Willis, Value chain microfinance, Oxford Review of Economic Policy, Vol. 40 (1), 2024. (Journal Article)
We study the provision of financial services to small firms, consumers, and workers in developing countries as part of value chain relationships: value chain microfinance (VCMF). We first explore how VCMF can both overcome barriers to financial access—including asymmetric information, enforcement, and behavioural biases—and strengthen value chains, but also how it can introduce new challenges. We then review a recent empirical literature at the intersection of value chains and microfinance, studying the demand for and effects of VCMF in credit, insurance, and savings markets. We conclude by highlighting promising directions for future work. |
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Andreas G F Hoepner, Ioannis Oikonomou, Zacharias Sautner, Laura T Starks, Xiao Y Zhou, ESG Shareholder Engagement and Downside Risk, Review of Finance, Vol. 28 (2), 2024. (Journal Article)
We show that engagement on environmental, social, and governance issues can benefit shareholders by reducing firms’ downside risks. We find that the risk reductions (measured using value at risk and lower partial moments) vary across engagement types and success rates. Engagement is most effective in lowering downside risk when addressing environmental topics (primarily climate change). Further, targets with large downside risk reductions exhibit a decrease in environmental incidents after the engagement. We estimate that the value at risk of engagement targets decreases by 9% of the standard deviation after successful engagements, relative to control firms. |
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Lauren Howe, Laura M Giurge, Alexander Wagner, Jochen Menges, CEOs Showing Humanity: Seemingly Generic Human Care Statements in Conference Calls and Stock Market Performance during Crisis, Academy of Management Discoveries, 2024. (Journal Article)
Conference calls provide opportunities for CEOs to inform market participants (i.e., financial analysts and investors) about their companies’ prospects. Much research has focused on how CEOs speak about business-related topics in these calls, yet surprisingly the literature has not considered how statements that go beyond financial information affect market participants. When we explored archival data of how CEOs of publicly traded U.S.-based companies from the Russell 3000 Index spoke about COVID-19 in conference calls as the pandemic began in 2020, we noticed that about half of CEOs made human care statements that expressed a concern for people, with seemingly little direct financial relevance. However, although these statements were largely generic, vague expressions rather than clear plans, we discovered that the more such statements CEOs made, the better their companies fared on the stock market when stock prices tumbled globally. Follow-up explorations unveiled a negative association between CEO human care statements and stock volatility, meaning that market participants discounted these companies’ future earnings less. Our explorations suggest that it pays off for CEOs to go beyond mere financial information and show some humanity, with implications for downstream theorizing about CEO impression management. |
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Francesco Barile, Tim Draws, Oana Inel, Alisa Rieger, Shabnam Najafian, Amir Ebrahimi Fard, Rishav Hada, Nava Tintarev, Evaluating explainable social choice-based aggregation strategies for group recommendation, User modeling and user-adapted interaction, Vol. 34 (1), 2024. (Journal Article)
Social choice aggregation strategies have been proposed as an explainable way to generate recommendations to groups of users. However, it is not trivial to determine the best strategy to apply for a specific group. Previous work highlighted that the performance of a group recommender system is affected by the internal diversity of the group members’ preferences. However, few of them have empirically evaluated how the specific distribution of preferences in a group determines which strategy is the most effective. Furthermore, only a few studies evaluated the impact of providing explanations for the recommendations generated with social choice aggregation strategies, by evaluating explanations and aggregation strategies in a coupled way. To fill these gaps, we present two user studies (N=399 and N=288) examining the effectiveness of social choice aggregation strategies in terms of users’ fairness perception, consensus perception, and satisfaction. We study the impact of the level of (dis-)agreement within the group on the performance of these strategies. Furthermore, we investigate the added value of textual explanations of the underlying social choice aggregation strategy used to generate the recommendation. The results of both user studies show no benefits in using social choice-based explanations for group recommendations. However, we find significant differences in the effectiveness of the social choice-based aggregation strategies in both studies. Furthermore, the specific group configuration (i.e., various scenarios of internal diversity) seems to determine the most effective aggregation strategy. These results provide useful insights on how to select the appropriate aggregation strategy for a specific group based on the level of (dis-)agreement within the group members’ preferences. |
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Sergei Ketkov, A study of distributionally robust mixed-integer programming with Wasserstein metric: on the value of incomplete data, European Journal of Operational Research, Vol. 313 (2), 2024. (Journal Article)
This study addresses a class of linear mixed-integer programming (MILP) problems that involve uncertainty in the objective function parameters. The parameters are assumed to form a random vector, whose probability distribution can only be observed through a finite training data set. Unlike most of the related studies in the literature, we also consider uncertainty in the underlying data set. The data uncertainty is described by a set of linear constraints for each random sample, and the uncertainty in the distribution (for a fixed realization of data) is defined using a type-1 Wasserstein ball centered at the empirical distribution of the data. The overall problem is formulated as a three-level distributionally robust optimization (DRO) problem. First, we prove that the three-level problem admits a single-level MILP reformulation, if the class of loss functions is restricted to biaffine functions. Secondly, it turns out that for several particular forms of data uncertainty, the outlined problem can be solved reasonably fast by leveraging the nominal MILP problem. Finally, we conduct a computational study, where the out-of-sample performance of our model and computational complexity of the proposed MILP reformulation are explored numerically for several application domains. |
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Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdran, Timo Schenk, Adrian Lars Benjamin Iten, Gérôme Bovet, Gregorio Martínez Pérez, Burkhard Stiller, Studying the Robustness of Anti-Adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors, IEEE Transactions on Dependable and Secure Computing, Vol. 21 (2), 2024. (Journal Article)
Device fingerprinting combined with Machine and Deep Learning (ML/DL) report promising performance when detecting spectrum sensing data falsification (SSDF) attacks. However, the amount of data needed to train models and the scenario privacy concerns limit the applicability of centralized ML/DL. Federated learning (FL) addresses these drawbacks but is vulnerable to adversarial participants and attacks. The literature has proposed countermeasures, but more effort is required to evaluate the performance of FL detecting SSDF attacks and their robustness against adversaries. Thus, the first contribution of this work is to create an FL-oriented dataset modeling the behavior of resource-constrained spectrum sensors affected by SSDF attacks. The second contribution is a pool of experiments analyzing the robustness of FL models according to i) three families of sensors, ii) eight SSDF attacks, iii) four FL scenarios dealing with anomaly detection and binary classification, iv) up to 33% of participants implementing data and model poisoning attacks, and v) four aggregation functions acting as anti-adversarial mechanisms. In conclusion, FL achieves promising performance when detecting SSDF attacks. Without anti-adversarial mechanisms, FL models are particularly vulnerable with > 16% of adversaries. Coordinate-wise-median is the best mitigation for anomaly detection, but binary classifiers are still affected with > 33% of adversaries. |
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Reint Gropp, Thomas Mosk, Steven Ongena, Ines Simac, Carlo Wix, Supranational Rules, National Discretion: Increasing versus Inflating Regulatory Bank Capital?, Journal of Financial and Quantitative Analysis, Vol. 59 (2), 2024. (Journal Article)
We study how banks use "regulatory adjustments" to inflate their regulatory capital ratios and whether this depends on forbearance on the part of national authorities. Using the 2011 EBA capital exercise as a quasi-natural experiment, we find that banks substantially inflated their levels of regulatory capital via a reduction in regulatory adjustments — without a commensurate increase in book equity and without a reduction in bank risk. We document substantial heterogeneity in regulatory capital inflation across countries, suggesting that national authorities forbear their domestic banks to meet supranational requirements, with a focus on short-term economic considerations. |
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