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"volume": "28","number": "4","pages": "9","abstract": "To mitigate the spread of contagious diseases, there is an ongoing discussion surrounding interventions that strategically target individuals who, due to their social network position, are responsible for more infections than others.\r\nHowever, the practical identification of these individuals using conventional network metrics is considerably challenging due to the lack of required data.\r\nA potential remedy to this quandary is the development of easily observable proxy metrics for measuring influential spreading. \r\nThis study aims to assess the viability of such an approach using the example of contact tracing.\r\nUtilizing an empirically calibrated agent-based model, the study investigates the extent to which the efficacy of contact tracing can be enhanced by prioritizing influential spreaders, identified using age and household size as proxy measures.\r\nThe results reveal that the effectiveness of contact tracing is significantly influenced by whose contacts are traced.\r\nWhen the contacts of those causing the most infections are traced, it can substantially enhance the efficacy of contact tracing, even when they are identified solely based on proxy metrics such as age and household size.\r\nFor the examined case of the German state of Baden-Württemberg, it appears that middle-aged individuals residing in larger households are responsible for most infections.\r\nTherefore, prioritizing contact tracing for this specific demographic group seems to be a robust strategy to improve contact tracing.\r\nOverall, the results support the potential of the proposed approach to reduce the overall societal costs of non-pharmaceutical interventions while increasing their impact.\r\nFurther empirical testing of the approach appears worthwhile.",
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"label" : "AI-Human collaboration in the cockpit: Towards safe single-pilot operations by explainable information exchange",
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"booktitle": "53rd Congress of the German Society for Psychology / 15th Congress of the Austrian Psychological Society",
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"author": [
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{"first" : "David Alexander", "last" : "Tsoi"},
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{"first" : "Zamira", "last" : "Daw"}
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"label" : "Can personalized feedback encourage sustainable washing behavior? A field study",
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"url": "",
"author": [
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"authors": [
{"first" : "Laura", "last" : "Höpfl"},
{"first" : "Maria", "last" : "Wirzberger"}
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"label" : "Critical Transformers: Psychological perspectives on the human-technology partnership and its impacts on society",
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"year": "2024",
"url": "",
"author": [
"Cornelia Sindermann","Maria Wirzberger"
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"authors": [
{"first" : "Cornelia", "last" : "Sindermann"},
{"first" : "Maria", "last" : "Wirzberger"}
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"venue" : "53rd Congress of the German Society for Psychology / 15th Congress of the Austrian Psychological Society",
"bibtexKey": "sindermann2024critical"
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"intraHash" : "776785bd941f4b566ad6f7720e8f5593",
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"label" : "Simulation and ChatGPT: Large language models as tools for model analysis",
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"booktitle": "Conference Proceedings for the 2024 System Dynamics Conference",
"year": "2024",
"url": "",
"author": [
"Ivan Dula","Tabea Berberena","Ksenia Keplinger","Maria Wirzberger"
],
"authors": [
{"first" : "Ivan", "last" : "Dula"},
{"first" : "Tabea", "last" : "Berberena"},
{"first" : "Ksenia", "last" : "Keplinger"},
{"first" : "Maria", "last" : "Wirzberger"}
],
"bibtexKey": "dula2024simulation"
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{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/2a632ab175f3ac190d854c92110d20b8e/simtech",
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"intraHash" : "a632ab175f3ac190d854c92110d20b8e",
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"label" : "Efficacy of personalized feedback in encouraging sustainable washing behavior: evidence from a pilot study in Germany",
"user" : "simtech",
"description" : "",
"date" : "2025-09-12 20:26:23",
"changeDate" : "2026-02-16 15:06:37",
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"pub-type": "article",
"journal": "Frontiers in Psychology","publisher":"Frontiers Media SA",
"year": "2025",
"url": "",
"author": [
"Laura Höpfl","Ivan Đula","Francisco Kiss","Rebecca Walter","Maria Wirzberger"
],
"authors": [
{"first" : "Laura", "last" : "Höpfl"},
{"first" : "Ivan", "last" : "Đula"},
{"first" : "Francisco", "last" : "Kiss"},
{"first" : "Rebecca", "last" : "Walter"},
{"first" : "Maria", "last" : "Wirzberger"}
],
"volume": "15","pages": "1473953","abstract": "ntroduction: Reducing household energy consumption through behavioral changes is a key strategy in addressing the emissions driving the climate crisis. Behavioral changes in affluent households toward more sustainable practices can have a significant positive impact. Prior research highlighted the role of individual values and motivational factors in shaping sustainable clusters. A more personalized approach toward encouraging the resulting clusters of people to adopt more sustainable strategies seems promising. Such an approach could incorporate aligned feedback, which has been proven to be a powerful mechanism throughout learning processes.\r\n\r\nMethod: Over 9 weeks, a pilot study with 50 participants investigated the impact of different types of feedback on washing behavior. The within-subjects design included (1) a baseline condition, (2) feedback on energy consumption (kWh), and (3) feedback on monetary costs per cycle (EUR). Data collection encompassed pre- and post-condition surveys, a final comprehensive survey, and a diary-formatted table. The primary objective was to evaluate the potential for individualization. Asynchronous structured interviews were conducted at the end to explore participants' perceptions and washing behaviors.\r\n\r\nResults: While we found effects for the feedback manipulation, we found no differences between user clusters in individual washing behaviors. Furthermore, participants qualitatively reported habitual changes, feeling more knowledgeable about the monetary impacts of specific washing programs and temperatures, and wished for a more accessible preset time function. Most participants expressed willingness to switch to a dynamic energy price if it translated to significant cost savings.\r\n\r\nDiscussion: Our findings may support the notion that individualized behavior change strategies are promising. In general, these strategies should be easily applicable, cost-effective, and promote habits to be exerted regularly. Arising methodological limitations suggest further research in this domain. From an applied perspective, our research provides valuable insights for designing products, services, and regulations by governments and companies, empowering them to develop more effective strategies for reducing energy consumption.",
"bibtexKey": "hopfl2025efficacy"
}
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"id" : "https://puma.ub.uni-stuttgart.de/bibtex/23eb9b24ed2183a2102ad741efde6a5c8/simtech",
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"intraHash" : "3eb9b24ed2183a2102ad741efde6a5c8",
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"label" : "Promoting sustainable behavior: addressing user clusters through targeted incentives",
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"date" : "2025-09-12 20:18:51",
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"journal": "Humanities and Social Sciences Communications","publisher":"Palgrave",
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"url": "",
"author": [
"Laura Höpfl","Maximilian Grimlitza","Isabella Lang","Maria Wirzberger"
],
"authors": [
{"first" : "Laura", "last" : "Höpfl"},
{"first" : "Maximilian", "last" : "Grimlitza"},
{"first" : "Isabella", "last" : "Lang"},
{"first" : "Maria", "last" : "Wirzberger"}
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"volume": "11","number": "1","pages": "1--12","abstract": "Given the urgency of climate change action and the significant climate impact of household emissions, understanding the drivers of individuals\u2019 sustainable behavior patterns is more important than ever. Consequently, we investigate whether different clusters of individual users can be distinguished regarding sustainability-related values, attitudes, and intentions. If these diverse clusters exist, we can explore tailored approaches to promote sustainable behavior patterns among them based on their unique needs and targets. For this purpose, we employ a mixed-method approach combining qualitative interviews with a quantitative survey. The obtained insights help us identify core factors that drive sustainable behavior, develop representations of different user groups, and suggest individualized interventions for supporting sustainable behavior patterns. The qualitative part comprised interviews with ten participants, resulting in the development of qualitative personas. Emerging differences could subsequently be used to select validated psychological scales for the quantitative part to confirm the differences. Applying data-driven clustering, we identify five intention-based clusters that vary regarding factors such as belief in climate change, collaboration, or skepticism concerning sustainability. Building on both qualitative and quantitative insights, five validated personas are created for research and practical use. These personas include Socially Sustainable, Responsible Savers, Unconcerned Spenders, Comfort-Oriented, and Skeptical Consumers. Individuals corresponding to the selected persona may, for example, respond positively to sustainability benefits, while others may be more receptive to hedonistic benefits. Addressing related varying motivational factors raises the demand for individualized interventions. These could be achieved by incorporating the personas\u2019 needs with more individualized products and services to promote sustainable behavior.",
"bibtexKey": "hopfl2024promoting"
}
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"intraHash" : "e096debee0876e49719b555500a5dca9",
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"label" : "Conceptualizing Responsible Adoption of Artificial Agents in the Workplace: A Systems Thinking Perspective",
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"date" : "2025-09-12 20:08:38",
"changeDate" : "2026-02-16 15:06:37",
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"pub-type": "incollection",
"year": "2024",
"url": "https://doi.org/10.1007/978-3-031-76970-2_15",
"author": [
"Ivan Ðula","Tabea Berberena","Ksenia Keplinger","Maria Wirzberger"
],
"authors": [
{"first" : "Ivan", "last" : "Ðula"},
{"first" : "Tabea", "last" : "Berberena"},
{"first" : "Ksenia", "last" : "Keplinger"},
{"first" : "Maria", "last" : "Wirzberger"}
],
"abstract": "Following recent technological developments, organizations and businesses seek to improve their effectiveness by increasing the use of artificial agents in the workplace. Previous research suggests that humans react to the adoption of artificial agents in three ways: 1) some humans appreciate algorithmic advice (algorithm appreciation); 2) some humans oppose algorithmic advice (algorithm aversion); and 3) some humans fully relinquish control to artificial agents (automation bias). Using tools and methods form the field of systems thinking, we analyze the existing literature on human-machine interactions in organizational settings and develop a conceptual model that provides an underlying structural explanation for the emergence of algorithm appreciation, algorithm aversion, and automation bias in various contexts. In doing so, we create a powerful visual tool that can be used to ground discussions about the responsible adoption of artificial agents in the workplace and the long-term impact they cause for organizations and humans within them. We use the model to hypothesize possible behavioral outcomes produced by the proposed structure.",
"doi" : "10.1007/978-3-031-76970-2_15",
"bibtexKey": "dula2024conceptualizing"
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"intraHash" : "aa8a38e7e47d8d03270ae0adf1d512e6",
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"label" : "From challenges to opportunities: navigating the human response to automated agents in the workplace",
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"url": "https://doi.org/10.1057/s41599-024-03962-x",
"author": [
"Ivan Ðula","Tabea Berberena","Ksenia Keplinger","Maria Wirzberger"
],
"authors": [
{"first" : "Ivan", "last" : "Ðula"},
{"first" : "Tabea", "last" : "Berberena"},
{"first" : "Ksenia", "last" : "Keplinger"},
{"first" : "Maria", "last" : "Wirzberger"}
],
"abstract": "Workers are increasingly embracing Artificial Intelligence (AI) to optimise various aspects of their operations in the workplace. While AI offers new opportunities, it also presents unintended challenges that they must carefully navigate. This paper aims to develop a deeper understanding of workers\u2019 experiences with interactions with automated agents (AA) in the workplace and provide actionable recommendations for organisational leaders to achieve positive outcomes. We propose and test a simulation model that quantifies and predicts workers\u2019 experiences with AA, shedding light on the interplay of diverse variables, such as workload, effort and trust. Our findings suggest that lower-efficiency AA might outperform higher-efficiency ones due to the constraining influence of trust on adoption rates. Additionally, we find that lower initial trust in AA could lead to increased usage in certain scenarios and that stronger emotional and social responses to the use of AA may foster greater trust but result in decreased AA utilisation. This interdisciplinary research blends a systems dynamics approach with management theories and psychological concepts, aiming to bridge existing gaps and foster the sustainable and effective implementation of AA in the workplace. Ultimately, our research endeavour contributes to advancing the field of human-AI interaction in the workplace.",
"doi" : "10.1057/s41599-024-03962-x",
"bibtexKey": "dula2024challenges"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/2ed4fbf2848c0cd2d51365595988652b4/simtech",
"tags" : [
"EXC2075","METEOR_3","PNX","curated"
],
"intraHash" : "ed4fbf2848c0cd2d51365595988652b4",
"interHash" : "798989ef76b57ea4c9b5eabd80482eaa",
"label" : "Effiziente Modellierung flexibler Robotersysteme zur Echtzeitsimulation am Beispiel eines Leichtbauroboters",
"user" : "simtech",
"description" : "",
"date" : "2025-05-16 09:57:57",
"changeDate" : "2025-10-16 15:35:53",
"count" : 4,
"pub-type": "preprint",
"publisher":"Universität Stuttgart",
"year": "2025",
"url": "https://elib.uni-stuttgart.de/handle/11682/16349",
"author": [
"Sebastian Hoschek","Philipp Rodegast","Jakob Gesell","Jonas Scheid","Jörg Fehr"
],
"authors": [
{"first" : "Sebastian", "last" : "Hoschek"},
{"first" : "Philipp", "last" : "Rodegast"},
{"first" : "Jakob", "last" : "Gesell"},
{"first" : "Jonas", "last" : "Scheid"},
{"first" : "Jörg", "last" : "Fehr"}
],
"copyright" : "info:eu-repo/semantics/openAccess",
"language" : "de",
"doi" : "10.18419/OPUS-16330",
"bibtexKey": "https://doi.org/10.18419/opus-16330"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/222bd48b9c5df6375654727c982125149/simtech",
"tags" : [
"EXC2075","PN7-6(II)","PNX","curated"
],
"intraHash" : "22bd48b9c5df6375654727c982125149",
"interHash" : "f87d2c872f2e6f474113b724ada23083",
"label" : "A benchmark of muscle models to length changes great and small",
"user" : "simtech",
"description" : "",
"date" : "2025-02-12 22:42:49",
"changeDate" : "2025-02-28 16:08:06",
"count" : 16,
"pub-type": "article",
"journal": "Journal of the Mechanical Behavior of Biomedical Materials","publisher":"Elsevier BV",
"year": "2024",
"url": "http://dx.doi.org/10.1016/j.jmbbm.2024.106740",
"author": [
"Matthew Millard","Norman Stutzig","Jörg Fehr","Tobias Siebert"
],
"authors": [
{"first" : "Matthew", "last" : "Millard"},
{"first" : "Norman", "last" : "Stutzig"},
{"first" : "Jörg", "last" : "Fehr"},
{"first" : "Tobias", "last" : "Siebert"}
],
"volume": "160","pages": "106740",
"issn" : "1751-6161",
"doi" : "10.1016/j.jmbbm.2024.106740",
"bibtexKey": "Millard_2024"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/2d967334e0e1673115b49cc5f64a3b7a6/simtech",
"tags" : [
"EXC2075","PNX","curated"
],
"intraHash" : "d967334e0e1673115b49cc5f64a3b7a6",
"interHash" : "567912cd4c1492f96e17d17d42aa3dce",
"label" : "Documenting Research in Simulation Science to Enhance Understanding for Reusability",
"user" : "simtech",
"description" : "",
"date" : "2024-12-05 08:39:05",
"changeDate" : "2025-02-25 11:13:52",
"count" : 9,
"pub-type": "article",
"journal": "Royal Society Open Science",
"year": "2024",
"url": "",
"author": [
"Sibylle Hermann","Jörg Fehr"
],
"authors": [
{"first" : "Sibylle", "last" : "Hermann"},
{"first" : "Jörg", "last" : "Fehr"}
],
"volume": "11","number": "10",
"issn" : "2054-5703",
"doi" : "https://doi.org/10.1098/rsos.240776",
"bibtexKey": "hermann2024accepteddocumenting"
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,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/2c2d0b618b4e46ed049c92ab1a4f09ae2/simtech",
"tags" : [
"PNX","PN7","EXC2075"
],
"intraHash" : "c2d0b618b4e46ed049c92ab1a4f09ae2",
"interHash" : "24686d34e22b161ee931faf9c77f1a63",
"label" : "Promoting sustainable behavior: addressing user clusters through targeted incentives",
"user" : "simtech",
"description" : "",
"date" : "2024-09-25 09:40:54",
"changeDate" : "2024-10-04 08:49:24",
"count" : 4,
"pub-type": "article",
"journal": "Humanities and Social Sciences Communications",
"year": "2024",
"url": "http://dx.doi.org/10.1057/s41599-024-03581-6",
"author": [
"Laura Höpfl","Maximilian Grimlitza","Isabella Lang","Maria Wirzberger"
],
"authors": [
{"first" : "Laura", "last" : "Höpfl"},
{"first" : "Maximilian", "last" : "Grimlitza"},
{"first" : "Isabella", "last" : "Lang"},
{"first" : "Maria", "last" : "Wirzberger"}
],
"abstract": "AbstractGiven the urgency of climate change action and the significant climate impact of household emissions, understanding the drivers of individuals\u2019 sustainable behavior patterns is more important than ever. Consequently, we investigate whether different clusters of individual users can be distinguished regarding sustainability-related values, attitudes, and intentions. If these diverse clusters exist, we can explore tailored approaches to promote sustainable behavior patterns among them based on their unique needs and targets. For this purpose, we employ a mixed-method approach combining qualitative interviews with a quantitative survey. The obtained insights help us identify core factors that drive sustainable behavior, develop representations of different user groups, and suggest individualized interventions for supporting sustainable behavior patterns. The qualitative part comprised interviews with ten participants, resulting in the development of qualitative personas. Emerging differences could subsequently be used to select validated psychological scales for the quantitative part to confirm the differences. Applying data-driven clustering, we identify five intention-based clusters that vary regarding factors such as belief in climate change, collaboration, or skepticism concerning sustainability. Building on both qualitative and quantitative insights, five validated personas are created for research and practical use. These personas include Socially Sustainable, Responsible Savers, Unconcerned Spenders, Comfort-Oriented, and Skeptical Consumers. Individuals corresponding to the selected persona may, for example, respond positively to sustainability benefits, while others may be more receptive to hedonistic benefits. Addressing related varying motivational factors raises the demand for individualized interventions. These could be achieved by incorporating the personas\u2019 needs with more individualized products and services to promote sustainable behavior.",
"issn" : "2662-9992",
"doi" : "10.1057/s41599-024-03581-6",
"bibtexKey": "hopfl2024promoting"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/235a2e1c8c96e1ff7fffaf8af1b87f059/simtech",
"tags" : [
"EXC2075","PNX","curated"
],
"intraHash" : "35a2e1c8c96e1ff7fffaf8af1b87f059",
"interHash" : "a4b58408db5b62e5283e2786b64298db",
"label" : "Hooked on artificial agents: a systems thinking perspective",
"user" : "simtech",
"description" : "",
"date" : "2024-08-12 12:42:36",
"changeDate" : "2024-09-12 12:04:14",
"count" : 7,
"pub-type": "article",
"journal": "Frontiers in Behavioral Economics",
"year": "2023",
"url": "",
"author": [
"Ivan Ðula","Tabea Berberena","Ksenia Keplinger","Maria Wirzberger"
],
"authors": [
{"first" : "Ivan", "last" : "Ðula"},
{"first" : "Tabea", "last" : "Berberena"},
{"first" : "Ksenia", "last" : "Keplinger"},
{"first" : "Maria", "last" : "Wirzberger"}
],
"volume": "2","pages": "1223281","abstract": "Following recent technological developments in the artificial intelligence space, artificial agents are increasingly taking over organizational tasks typically reserved for humans. Studies have shown that humans respond differently to this, with some being appreciative of their advice (algorithm appreciation), others being averse toward them (algorithm aversion), and others still fully relinquishing control to artificial agents without adequate oversight (automation bias). Using systems thinking, we analyze the existing literature on these phenomena and develop a conceptual model that provides an underlying structural explanation for their emergence. In doing so, we create a powerful visual tool that can be used to ground discussions about the impact artificial agents have on organizations and humans within them.",
"doi" : "10.3389/frbhe.2023.1223281",
"bibtexKey": "dula2023hooked"
}
]
}