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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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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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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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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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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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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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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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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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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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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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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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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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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Dario Staehelin, Mateusz Dolata, Livia Stöckli, Gerhard Schwabe, How Patient-Generated Data Enhance Patient-Provider Communication in Chronic Care: Field Study in Design Science Research, JMIR Medical Informatics, Vol. 12, 2024. (Journal Article)
Background
Modern approaches such as patient-centered care ask health care providers (eg, nurses, physicians, and dietitians) to activate and include patients to participate in their health care. Mobile health (mHealth) is integral in this endeavor to be more patient centric. However, structural and regulatory barriers have hindered its adoption. Existing mHealth apps often fail to activate and engage patients sufficiently. Moreover, such systems seldom integrate well with health care providers’ workflow.
Objective
This study investigated how patient-provider communication behaviors change when introducing patient-generated data into patient-provider communication.
Methods
We adopted the design science approach to design PatientHub, an integrated digital health system that engages patients and providers in patient-centered care for weight management. PatientHub was developed in 4 iterations and was evaluated in a 3-week field study with 27 patients and 6 physicians. We analyzed 54 video recordings of PatientHub-supported consultations and interviews with patients and physicians.
Results
PatientHub introduces patient-generated data into patient-provider communication. We observed 3 emerging behaviors when introducing patient-generated data into consultations. We named these behaviors emotion labeling, expectation decelerating, and decision ping-pong. Our findings show how these behaviors enhance patient-provider communication and facilitate patient-centered care. Introducing patient-generated data leads to behaviors that make consultations more personal, actionable, trustworthy, and equal.
Conclusions
The results of this study indicate that patient-generated data facilitate patient-centered care by activating and engaging patients and providers. We propose 3 design principles for patient-centered communication. Patient-centered communication informs the design of future mHealth systems and offers insights into the inner workings of mHealth-supported patient-provider communication in chronic care. |
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Fynn Bachmann, Cristina Sarasua, Abraham Bernstein, Fast and Adaptive Questionnaires for Voting Advice Applications, In: Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, Springer, Cham, 2024-09-09. (Conference or Workshop Paper published in Proceedings)
The effectiveness of Voting Advice Applications (VAA) is often compromised by the length of their questionnaires. To address user fatigue and incomplete responses, some applications (such as the Swiss Smartvote) offer a condensed version of their questionnaire. However, these condensed versions can not ensure the accuracy of recommended parties or candidates, which we show to remain below 40%. To tackle these limitations, this work introduces an adaptive questionnaire approach that selects subsequent questions based on users’ previous answers, aiming to enhance recommendation accuracy while reducing the number of questions posed to the voters. Our method uses an encoder and decoder module to predict missing values at any completion stage, leveraging a two-dimensional latent space reflective of political science’s traditional methods for visualizing political orientations. Additionally, a selector module is proposed to determine the most informative subsequent question based on the voter’s current position in the latent space and the remaining unanswered questions. We validated our approach using the Smartvote dataset from the Swiss Federal elections in 2019, testing various spatial models and selection methods to optimize the system’s predictive accuracy. Our findings indicate that employing the IDEAL model both as encoder and decoder, combined with a PosteriorRMSE method for question selection, significantly improves the accuracy of recommendations, achieving 74% accuracy after asking the same number of questions as in the condensed version. |
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Jan Von der Assen, Jasmin Hochuli, Thomas Grübl, Burkhard Stiller, The Danger Within: Insider Threat Modeling Using Business Process Models, In: 2024 IEEE International Conference on Cyber Security and Resilience (CSR), Institut of Electrical and Electronics Engineers, 2024-09-02. (Conference or Workshop Paper published in Proceedings)
Threat modeling has been successfully applied to model technical threats within information systems. However, a lack of methods focusing on non-technical assets and their representation can be observed in theory and practice. Following the voices of industry practitioners, this paper explored how to model insider threats based on business process models. Hence, this study developed a novel insider threat knowledge base and a threat modeling application that leverages Business Process Modeling and Notation (BPMN). Finally, to understand how well the theoretic knowledge and its prototype translate into practice, the study conducted a real-world case study of an IT provider's business process and an experimental deployment for a real voting process. The results indicate that even without annotation, BPMN diagrams can be leveraged to automatically identify insider threats in an organization. |
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Nicholas Mayone, Pascal Kunz, Beytullah Yigit, Wissem Soussi, Burkhard Stiller, Gürkan Gür, IPv6 Connection Shuffling for Moving Target Defense (MTD) in SDN, In: 2024 IEEE International Conference on Cyber Security and Resilience (CSR), Institut of Electrical and Electronics Engineers, 2024-09-02. (Conference or Workshop Paper published in Proceedings)
Moving Target Defense (MTD) is the defensive strat-egy of obscuring an entity by controlled changes in its attack surface. This approach alone does not secure a system but challenges potential attacks with additional complexity. This work presents an MTD solution called “Randomized Host and Service Shuffling in IPv6 (RHSS6)” against network reconnaissance attacks and evaluates its effects on performance and security. To achieve this goal, a Software Defined Networking (SDN) based prototype was developed in which RHSS6 performs two MTD strategies, IP Shuffling and Port Shuffling. Measurements on TCP and UDP traffic are made to evaluate the performance impact of RHSS6. An MTD network with both IP Shuffling and Port Shuffling had similar performance results compared to a baseline network; however, the video stream bit rate was significantly lower when Port Shuffling was enforced. Regarding the security gain, RHSS6 was effective in increasing the average number of scan attempts needed to identify a targeted host in a network with a fixed address range. We conclude that a defender using RHSS6 can adjust the probability of an attacker locating targeted hosts in a network by selecting a suitable address space and port range. Such parameters and shuffling trigger time can be optimized to maximize the benefits for different scenarios while minimizing the operational overhead. |
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Ronak Jain, Vatsal Khandelwal, Silent networks: The role of inaccurate beliefs in reducing useful social interactions, In: Working paper series / Department of Economics, No. 455, 2024. (Working Paper)
Inaccurate beliefs about social norms can reduce useful social interactions and adversely affect an individual’s ability to deal with negative shocks. We implement a randomized controlled trial with low-income workers in urban India who lack access to formal financial and healthcare support. We find that the majority of individuals underestimate their community’s willingness to engage in dialogue around financial and mental health concerns. Belief correction leads to a large increase in the demand for network-based assistance. We show that the effects are driven by a reduction in the perceived costs of violating social norms arising due to concerns around reputation and insensitivity. We structurally estimate a network diffusion model and predict that our belief correction intervention will not lead to a shift in equilibrium engagement. Consistent with this, 2 years later, we find that the average beliefs of those exposed to the intervention are significantly more optimistic but still lower than the information delivered in the experiment. We compute the strength of counterfactual interventions needed to generate a sustained effect and find that belief correction can be used to generate both the demand and funding for such policies. |
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Minahil Asim, Ronak Jain, Vatsal Khandelwal, Great expectations? Experimental evidence from schools in Pakistan, In: Working paper series / Department of Economics, No. 454, 2024. (Working Paper)
We study the effect of communicating student-specific teacher expectations on academic performance. We randomize whether students (a) receive high-performance expectations, (b) are additionally paired with a classmate for encouragement, (c) receive information about past performance, or (d) receive no message. Expectations increase math scores by 0.19σ, with especially large effects among students who randomly received ambitious expectations and were predicted to performpoorly. Information provision has comparably large effects (0.16σ), particularly in schools with low parental literacy. However, pairing students only improves scores when peers have similar characteristics. Our findings highlight low-cost, sustainable ways of leveraging teachers to improve performance. |
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