Behavioral Information Design for Forecasting Dashboards: Equilibria, Mechanisms, and Calibration
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| Publicado en: | ProQuest Dissertations and Theses (2025) |
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| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 100 | 1 | |a Kayongo, Paula Ogol | |
| 245 | 1 | |a Behavioral Information Design for Forecasting Dashboards: Equilibria, Mechanisms, and Calibration | |
| 260 | |b ProQuest Dissertations & Theses |c 2025 | ||
| 513 | |a Dissertation/Thesis | ||
| 520 | 3 | |a Online platforms increasingly rely on information dashboards to influence decision-making in uncertain environments. Rideshare platforms use pricing dashboards to influence where and when drivers operate. Advertising platforms display auction dashboards to guide bidding behavior. Public agencies publish forecast dashboards to shape public responses to extreme weather or health risks. These dashboards function not as neutral displays but design artifacts that systematically structure information, influencing how users perceive and respond to it. By choosing what information to display and how to present it, designers can guide attention, influence trust, and steer behavior to align user actions with intended system outcomes. This dissertation investigates how strategic dashboard design influences decision-making and system outcomes in uncertain environments, particularly when decision makers operate under cognitive limitations and computational constraints. Through a series of behavioral experiments in strategic, auction, and forecast-based decision-making environments, I examine how dashboards influence user behavior and system outcomes. By systematically varying dashboard design features, i.e, information disclosure, uncertainty visualization, and feedback, I show that dashboards impact belief formation, shift strategic reasoning, and improve decision-making and inference. Collectively, these studies establish dashboard design as a key tool for shaping behavior and outcomes in information-mediated decision environments. | |
| 653 | |a Computer science | ||
| 653 | |a Computer engineering | ||
| 653 | |a Web studies | ||
| 773 | 0 | |t ProQuest Dissertations and Theses |g (2025) | |
| 786 | 0 | |d ProQuest |t ProQuest Dissertations & Theses Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3245496017/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3245496017/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |