Tomás Lagos, Junyeong Choi, Brittany Segundo, Jianbang Gan, Lewis Ntaimo, Oleg A Prokopyev, Bilevel optimization approach for fuel treatment planning, European Journal of Operational Research, Vol. 320 (1), 2025. (Journal Article)
Various fuel treatment practices involve removing all or some of the vegetation (fuel) from a landscape to reduce the potential for fires and their severity. Fuel treatments form the first line of defense against large-scale wildfires. In this study, we formulate and solve a bilevel integer programming model, where the fuel treatment planner (modeled as the leader) determines appropriate locations and types of treatments to minimize expected losses from wildfires. The follower (i.e., the lower-level decision-maker) corresponds to nature, which is adversarial to the leader and designs a wildfire attack (i.e., locations and time periods, where and when, respectively, wildfires occur) to disrupt the leader’s objective function, e.g., the total expected area burnt. Both levels in the model involve integrality restrictions for decision variables; hence, we explore the model’s difficulty from the computational complexity perspective. Then, we design specialized solution methods for general and some special cases. We perform experiments with semi-synthetic and real-life instances to illustrate the performance of our approaches. We also explore numerically the fundamental differences in the structural properties of solutions arising from bilevel model and its single-level counterpart. These disparities encompass factors like the types of treatments applied and the choice of treated areas. Additionally, we conduct various types of sensitivity analysis on the performance of the obtained policies and illustrate the value of the bilevel solutions. |
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Xinran Wang, Zisu Wang, Mateusz Dolata, Jay F Nunamaker, How credibility assessment technologies affect decision fairness in evidence-based investigations: A Bayesian perspective, Decision Support Systems, Vol. 187, 2024. (Journal Article)
Recently, a growing number of credibility assessment technologies (CATs) have been developed to assist human decision-making processes in evidence-based investigations, such as criminal investigations, financial fraud detection, and insurance claim verification. Despite the widespread adoption of CATs, it remains unclear how CAT and human biases interact during the evidence-collection procedure and affect the fairness of investigation outcomes. To address this gap, we develop a Bayesian framework to model CAT adoption and the iterative collection and interpretation of evidence in investigations. Based on the Bayesian framework, we further conduct simulations to examine how CATs affect investigation fairness with various configurations of evidence effectiveness, CAT effectiveness, human biases, technological biases, and decision stakes. We find that when investigators are unconscious of their own biases, CAT adoption generally increases the fairness of investigation outcomes if the CAT is more effective than evidence and less biased than the investigators. However, the CATs' positive influence on fairness diminishes as humans become aware of their own biases. Our results show that CATs' impact on decision fairness highly depends on various technological, human, and contextual factors. We further discuss the implications for CAT development, evaluation, and adoption based on our findings. |
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Lucia Malär, Andrea Giuffredi-Kähr, The Dark Triad of brand personality: Scale development and validation, Psychology & Marketing, Vol. 41 (11), 2024. (Journal Article)
Despite the considerable magnitude of negative brand personalities in the marketplace, prior research has disproportionately focused on positive personality traits. To address this research gap, the authors present a conceptual and empirical approach that draws from the Dark Triad of psychology and applies it to the branding domain. They conceptualize and validate the Dark Triad of brand personality which comprises brand narcissism, Machiavellianism, and psychopathy dimensions. Through a multiphase scale development process, a reliable and valid 12‐item brief version of the Dark Triad of brand personality is created, enabling its assessment in both research and management contexts. Examining the Dark Triad in branding is crucial as it provides a unique lens to understand the rise of negative, dark brand personalities. It accounts for brand personality aspects not yet captured by existing scales, including manipulation, exploitation, grandiosity, and lack of empathy. This introduction of the Dark Triad brand personality opens new avenues for research into brand transgressions and ethics in brand management. In terms of managerial implications, insights from this research can inform strategic brand management, enabling companies to better manage their brand's image. |
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Mamiza Haq, Steven Ongena, Juying Pu, Eric K M Tan, Do banks engage in earnings management? The role of dividends and institutional factors, Journal of Banking and Finance, Vol. 168, 2024. (Journal Article)
We investigate the impact of dividend policy on earnings quality and opportunistic earnings management for individual banks across 45 developed and developing countries between 1996 and 2019. Our estimates show that high dividend payments reduce earnings management, hence mitigate agency problems. This mitigation is especially prevalent among well-capitalised and non-listed banks. Greater investor protection and government regulation appear to strengthen the negative association between dividend policy and earnings management. Our results hold robustly across many different specifications. |
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Kathrin Wardatzky, Evaluating the Pros and Cons of Recommender Systems Explanations, In: RecSys '24: 18th ACM Conference on Recommender Systems, 2024-10-14. (Conference or Workshop Paper published in Proceedings)
Despite the growing interest in explainable AI in the RecSys community, the evaluation of explanations is still an open research topic.
Typically, explanations are evaluated using offline metrics, with a case study, or through a user study. In my research, I will have a closer look at the evaluation of the effects of explanations on users. I investigate two possible factors that can impact the effects reported in recent publications, namely the explanation design and content as well as the users themselves. I further address the problem of determining promising explanations for an application scenario from a seemingly endless pool of options. Lastly, I propose a user study to close some of the research gaps established in the surveys and investigate how recommender systems explanations impact the understanding of users with different backgrounds. |
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Lucien Heitz, Nicolas Mattis, Oana Inel, Wouter van Atteveldt, IDEA – Informfully Dataset with Enhanced Attributes, In: NORMalize 2024: The Second Workshop on the Normative Design and Evaluation of Recommender Systems, 2024-10-14. (Conference or Workshop Paper published in Proceedings)
In this paper, we present the Informfully Dataset with Enhanced Attributes (IDEA) for news article recommendations. The dataset consists of an open-source collection of user profiles, news articles with a high topic and outlet diversity, item recommendations, and rich user-item interactions from a field study on behavioral changes in news consumption. The records include both quantitative data from real-time session tracking as well as self-reported data from user surveys on satisfaction with news, knowledge acquisition, and personal background information. This paper outlines the data collection procedure and potential use cases of the dataset for designing normative recommender systems. It provides the documentation of all data collections together with insights into the data quality. |
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Lucien Heitz, Sanne Vrijenhoek, Oana Inel, Recommendations for the Recommenders: Reflections on Prioritizing Diversity in the RecSys Challenge, In: RecSys Challenge '24: ACM RecSys Challenge 2024, 2024-10-14. (Conference or Workshop Paper published in Proceedings)
The RecSys Challenge 2024, co-organized by the Danish news outlet Ekstra Bladet, called for participants to develop a news recommender system that accurately predicts which news article a reader is most likely to select from a given list. In the context of this challenge, the organizers explicitly stated their interest in beyond-accuracy objectives. However, the setup of the challenge did not facilitate pursuing these more normative goals: a missed opportunity, given the quality of the dataset. In this paper, we highlight the issues encountered in a submission that prioritized normative diversity. We reflect on the responsibility of conferences, RecSys in particular, when it comes to promoting beyond-accuracy objectives and provide recommendations for future challenge iterations. |
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Lucien Heitz, Julian A Croci, Madhav Sachdeva, Abraham Bernstein, Informfully – Research Platform for Reproducible User Studies, In: RecSys '24: Eighteenth ACM Conference on Recommender Systems, ACM Digital library, 2024-10-14. (Conference or Workshop Paper published in Proceedings)
This paper presents Informfully, a research platform for content distribution and user studies. Informfully allows to push algorithmically curated text, image, audio, and video content to users and automatically generates a detailed log of their consumption history. As such, it serves as an open-source platform for conducting user experiments to investigate the impact of item recommendations on users' consumption behavior. The platform was designed to accommodate different experiment types through versatility, ease of use, and scalability. It features three core components: 1) a front end for displaying and interacting with recommended items, 2) a back end for researchers to create and maintain user experiments, and 3) a simple JSON-based exchange format for ranked item recommendations to interface with third-party frameworks. We provide a system overview and outline the three core components of the platform. A sample workflow is shown for conducting field studies incorporating multiple user groups, personalizing recommendations, and measuring the effect of algorithms on user engagement. We present evidence for the versatility, ease of use, and scalability of Informfully by showcasing previous studies that used our platform. |
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Stevo Pavicevic, Thomas Keil, The role of military directors in holding the CEO accountable for poor firm performance, Strategic Management Journal, 2024. (Journal Article)
Research Summary
Why do some boards of directors dismiss the CEO when a firm performs poorly, while others do not? We argue that military directors—outside directors with military backgrounds—on the board increase the likelihood of CEO dismissal under low‐performance conditions. Military service instills a lifelong system of values and beliefs related to accountability—the obligation to accept responsibility for one's own actions and outcomes—which leads military directors to attribute low performance to the CEO and hold the CEO strictly accountable for such performance. This argument is supported by extensive quantitative data on CEO dismissal in publicly listed firms and qualitative data obtained from interviews with military directors who have served on boards of those firms.
Managerial Summary
Military directors—outside directors with military backgrounds—frequently occupy seats on the boards of publicly listed firms in the United States. Military service instills an enduring system of values and beliefs rooted in accountability, which, we argue, makes military directors more inclined to attribute performance shortfalls to the CEO and advocate for more rigorous CEO accountability, resulting in CEO dismissal. Our argument is supported by quantitative data on CEO dismissals within publicly listed firms and qualitative data derived from interviews with military directors who have served on boards of those firms. Our findings underscore that principles ingrained via military service may influence corporate governance, particularly one of its core components: executive accountability. |
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Armin R Veres, Daria Schumm, Thomas Grübl, Katharina O E Müller, Bruno Rodrigues, Burkhard Stiller, Demo: Secure Inventorying and Lifecycle Management of IoT Devices with DLT, In: 2024 IEEE 49th Conference on Local Computer Networks (LCN), Institute of Electrical and Electronics Engineers, 2024-10-08. (Conference or Workshop Paper published in Proceedings)
Security management of Internet-of-Things (IoT) infrastructures encompassing the entire lifecycle of products and their continuous certification are fundamental functions to guarantee a high level of security. This paper demonstrates a DLT-based platform enabling secure inventorying and management of IoT devices and sensors distributed across multiple stakeholders. This work makes use of the Hyperledger framework, Decentralized Identifiers (DID), and Manufacturer Usage Description (MUD) files for IoT device inventorying and the identification of critical software updates. |
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Jan Von der Assen, Alberto Huertas Celdran, Rinor Sefa, Burkhard Stiller, Gérôme Bovet, MTFS: a Moving Target Defense-Enabled File System for Malware Mitigation, In: 2024 IEEE 49th Conference on Local Computer Networks (LCN), Institute of Electrical and Electronics Engineers, 2024-10-08. (Conference or Workshop Paper published in Proceedings)
Ransomware has remained one of the most notorious threats in the cybersecurity field, for which Moving Target Defense (MTD) has been proposed as a novel defense paradigm. Although various approaches leverage MTD, few of them rely on the operating system and, specifically, the file system, thereby making them dependent on other computing devices, rendering defense against certain threats unrealistic. File-based approaches are less studied here while showing limitations in resource usage and defense effectiveness. Furthermore, existing ransomware defenses merely restore data or detect attacks without preventing them. Thus, this paper introduces the MTFS file system and the design and implementation of three novel MTD techniques – one delaying attackers, one trapping recursive directory traversal, and another one hiding file types. The effectiveness of the techniques is shown in three experiments. First, it is demonstrated that the techniques can delay and mitigate ransomware on real IoT devices. Secondly, in a broader scope, the solution was confronted with 13 ransomware samples, highlighting that it can save 97% of the files. Regarding overhead, the defense system consumes only a small amount of resources, highlighting the feasibility of proactive defense. |
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Agha Durrani, Steven Ongena, Aurea Ponte Marques, Decoding market reactions: The certification role of EU-wide stress tests, Economic Modelling, Vol. 139, 2024. (Journal Article)
We study the market’s reaction to the disclosure of EU-wide stress test results across four periods (2014, 2016, 2018, and 2021). Our novel approach contributes to the literature by studying how stress test disclosures influence both the mean and variance (first and second moments) of bank stock performance, extending beyond previous studies focused mainly on the first moment of equity returns. Using one-factor market and structural Engle–Siriwardane type GARCH models, we find that the publication of stress tests provides new information to the markets: Banks with weaker performance in the tests experience, on average, a reduction in stock returns and an increase in volatility, while the reverse holds for banks performing well. Our findings confirm the important role of stress tests in enhancing transparency and market discipline, thereby supporting investors in assessing the resilience of the banking sector more effectively, particularly during periods of higher uncertainty. |
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Alper Kara, Steven Ongena, Yilmaz Yildiz, Does being a responsible bank pay off? Evidence from the COVID-19 pandemic, Journal of Financial Stability, Vol. 74, 2024. (Journal Article)
We investigate whether banks’ initial responses during the first wave of the COVID-19 pandemic in supporting their customers, communities, and governments were perceived as value-enhancing by investors. Using a unique responsible banking measure for a sample of the largest US and European commercial banks, we find a negative relationship between responsible bank behavior and stock market performance, particularly in the first wave of the pandemic. We also find that riskier banks were affected more negatively if they behaved responsibly. Overall, our findings show that banks’ responsible behavior during a crisis reduces, or at best is not relevant to, shareholder value. |
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Reto Eberle, Swiss Audit Monitor 2024: Analyse des Revisionsmarkts der kotierten Unternehmen in der Schweiz, Expert Focus, Vol. 98 (8), 2024. (Journal Article)
In einem jährlich auf www.swissauditmonitor.ch veröffentlichten Report werden die Revisionshonorare, die zusätzlichen Honorare, die Mandatsdauer der Revisionsgesellschaften und die verwendeten Rechnungslegungsstandards von Unternehmen des Swiss Market Index (SMI) und des Swiss Performance Index (SPI) erhoben und ausgewertet. Der 8. Ausgabe des Swiss Audit Monitor liegt das Geschäftsjahr 2023 zugrunde. Dieser Beitrag fasst die wichtigsten Erkenntnisse zusammen. |
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Nils Hossli, Martin Natter, René Algesheimer, On the importance of congruence between personal and work values – How value incongruence affects job satisfaction: A multiple mediation model, International Journal of Wellbeing, Vol. 14 (3), 2024. (Journal Article)
This study proposes a novel conceptualization of work values designed to quantify the degree of incongruity between personal values and workplace demands. We define work values as the priorities individuals wish to be recognized for in their workplace, while personal values are those the individual personally identifies with. By contrasting personal and work values, we provide evidence for value incongruence among employees and showed that this measurement of value incongruence effectively predicts key job-related metrics. Value incongruence directly reduces job satisfaction, but its primary impact is indirect. Our multiple mediation analysis reveals that it mainly affects job satisfaction through perceived job meaningfulness, relationships with supervisors, and opportunities for career advancement. We discuss the implications of our findings for various stakeholders and suggest potential improvements for individual and societal well-being linked to the future of work. |
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Johannes Brumm, Feng Xiangyu, Laurence Kotlikoff, Felix Kübler, When Interest Rates Go Low, Should Public Debt Go High?, American Economic Journal: Macroeconomics, Vol. 16 (4), 2024. (Journal Article)
Is deficit finance free when real borrowing rates are routinely lower than growth rates? Specifically, can the government make all generations better off by perpetually taking from the young and giving to the old? We study this in stochastic closed- and open-economy OLG models. Unfortunately, Pareto gains are predicted only for implausible calibrations. Even then, the gains reflect improved inter-generational risk sharing, improved international risk sharing, and beggaring thy neighbor-not intergenerational redistribution, per se. As we show, theoretically and quantitatively, low government borrowing rates suggest state-contingent bilateral transfers between generations-not unconditional, unilateral redistribution from future to current generations. |
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Damiano Pregaldini, Uschi Backes-Gellner, How middle-skilled workers adjust to immigration: the role of occupational skill specificity, International Journal of Manpower, Vol. 45 (8), 2024. (Journal Article)
Purpose
Our study explores the effects of immigration on the employment of native middle-skilled workers, focusing on how this effect varies with the specificity of their occupational skill bundles.
Design/methodology/approach
Exploiting the 2002 opening of the Swiss labor market to EU workers and using register data on the location and occupation of these workers, our findings provide novel results on the labor market effects of immigration.
Findings
We show that the inflow of EU workers led to an increase in the employment of native middle-skilled workers with highly specific occupational skills. This finding could be attributed to immigrant workers reducing existing skill gaps, enhancing the quality of job-worker matches, and alleviating firms' capacity restrictions. This allowed firms to create new jobs, thereby providing increased employment options for middle-skilled workers with highly specialized skills.
Originality/value
Previous literature has predominantly highlighted the disadvantages of specific occupational skills compared to general skills in the context of labor market shocks. However, our findings reveal that workers with specific occupational skills can benefit from an immigration-driven labour market shock. These results suggest that policy conclusions regarding the role of specific occupational skills should be more nuanced. |
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Giacomo Vaccario, Shuqi Xu, Manuel Mariani, Matúš Medo, The quest for an unbiased scientific impact indicator remains open, Proceedings of the National Academy of Sciences of the United States of America, Vol. 121 (41), 2024. (Journal Article)
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Lorenzo Costantini, Francesco Laio, Manuel Mariani, Luca Ridolfi, Carla Sciarra, Forecasting national CO2 emissions worldwide, Scientific Reports, Vol. 14, 2024. (Journal Article)
Urgent climate action, especially carbon emissions reduction, is required to achieve sustainable goals. Therefore, understanding the drivers of and predicting CO2 emissions is a compelling matter. We present two global modeling frameworks—a multivariate regression and a Random Forest Regressor (RFR)—to hindcast (until 2021) and forecast (up to 2035) CO2 emissions across 117 countries as driven by 12 socioeconomic indicators regarding carbon emissions, economic well-being, green and complexity economics, energy use and consumption. Our results identify key driving features to explain emissions pathways, where beyond-GDP indicators rooted in the Economic Complexity field emerge. Considering current countries’ development status, divergent emission dynamics appear. According to the RFR, a −6.2% reduction is predicted for developed economies by 2035 and a +19% increase for developing ones (referring to 2020), thus stressing the need to promote green growth and sustainable development in low-capacity contexts. |
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Lisya Kaspi, Danfei Hu, Allon Vishkin, Yulia Chentsova-Dutton, Yuri Miyamoto, Jan Cieciuch, Akiva Cohen, Yukiko Uchida, Min Young Kim, Xiaoqin Wang, Jiang Qiu, Michaela Riediger, Antje Rauers, Yaniv Hanoch, Maya Tamir, Motivated to feel better and doing something about it: Cross-cultural differences in motivated emotion regulation during COVID-19, Emotion, 2024. (Journal Article)
Emotion regulation is linked to adaptive psychological outcomes. To engage in such regulation, people must be motivated to do it. Given that people in different countries vary in how they think about unpleasant emotions, we expected motivation to decrease unpleasant emotions to differ across countries. Furthermore, given that emotion regulation strategies operate in the service of motivation, we expected people who are less motivated to decrease unpleasant emotions to use emotion regulation strategies less across countries. To test these predictions, we conducted two studies during the COVID-19 pandemic: Study 1 in 2020 (N = 1,329) and Study 2 in 2021 (N = 1,279). We assessed the motivation to decrease unpleasant emotions and the use of emotion regulation strategies among members of East Asian countries (i.e., Japan, South Korea, and China) and Western countries (i.e., United States, United Kingdom, and Germany). Because we found substantial variation within these two broader cultural categories, we examined motivation and overall strategy use in emotion regulation at the country level. In both studies, motivation to decrease unpleasant emotions was the lowest in Japan and relatively high in the United States. As expected, across countries, weaker motivation to decrease unpleasant emotions was associated with using emotion regulation strategies less. We discuss implications of our findings for understanding cultural differences in motivated emotion regulation. |
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