Henner Gimpel
Biographic Data
| ID | 4029418 |
|---|---|
| NAME | Henner Gimpel |
| GIVEN NAMES | Henner |
| FAMILY NAME | Gimpel |
| SIGNATURE | GIMPEL H |
| AFFILIATIONS | University of Hohenheim |
| ORCID | 0000-0003-1730-2614 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2007 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
The Crowd Without People
Large Language Models (LLMs) are transforming the innovation process by scaling ideation and creativity. This yields the challenge of evaluating the growing flood of ideas. In simpler contexts, tasks with clear criteria and well-defined outcome possibilities, where human evaluators are also a bottleneck, LLM systems are already being used as a scalable and cheap alternative. In this study, we assess whether LLMs and LLM agents can be used as eval…
Idea Evaluation for Solutions to Specialized Problems
Complex problems such as climate change pose severe challenges to societies worldwide. To overcome these challenges, digital innovation contests have emerged as a promising tool for idea generation. However, assessing idea quality in innovation contests is becoming increasingly problematic in domains where specialized knowledge is needed. Traditionally, expert juries are responsible for idea evaluation in such contests. However, experts are a sub…
Digital Facilitation of Group Work to Gain Predictable Performance
Group work is a commonly used method of working, and the performance of a group can vary depending on the type and structure of the task at hand. Research suggests that groups can exhibit "collective intelligence"—the ability to perform well across tasks—under certain conditions, making group performance somewhat predictable. However, predictability of task performance becomes difficult when a task relies heavily on coordination among group membe…
Advancing Content Synthesis in Macro-Task Crowdsourcing Facilitation Leveraging Natural Language Processing
Macro-task crowdsourcing presents a promising approach to address wicked problems like climate change by leveraging the collective efforts of a diverse crowd. Such macro-task crowdsourcing requires facilitation. However, in the facilitation process, traditionally aggregating and synthesizing text contributions from the crowd is labor-intensive, demanding expertise and time from facilitators. Recent advancements in large language models (LLMs) hav…
Citizens' preferences on smart energy technologies and services for smart districts
The design of sustainable urban environments is one of the most pressing endeavors. Particularly the emergence of digital technologies has triggered a range of technocentric movements for urban development, such as smart cities or districts. City stakeholders, including city or district planners, public administrators, or governance stakeholders, expect technological innovations to enhance life in the city. However, citizens are under-represented…
Towards Artificial Intelligence Augmenting Facilitation
Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, contribute to work addressing climate change. Macro-task crowdsourcing aims to use the wisdom of a crowd to tackle non-trivial tasks such as wicked problems. However, macro-task crowdsourcing is labor-intensive and complex to facilitate, which limits its efficiency, effectiveness, and use. Technological advancements in artificial intelligence (AI) might overcome these…
Preferences in Negotiations
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Preferences in Negotiations
Towards Artificial Intelligence Augmenting Facilitation
Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, contribute to work addressing climate change. Macro-task crowdsourcing aims to use the wisdom of a crowd to tackle non-trivial tasks such as wicked problems. However, macro-task crowdsourcing is labor-intensive and complex to facilitate, which limits its efficiency, effectiveness, and use. Technological advancements in artificial intelligence (AI) might overcome these…
Digital Facilitation of Group Work to Gain Predictable Performance
Group work is a commonly used method of working, and the performance of a group can vary depending on the type and structure of the task at hand. Research suggests that groups can exhibit "collective intelligence"—the ability to perform well across tasks—under certain conditions, making group performance somewhat predictable. However, predictability of task performance becomes difficult when a task relies heavily on coordination among group membe…
Advancing Content Synthesis in Macro-Task Crowdsourcing Facilitation Leveraging Natural Language Processing
Macro-task crowdsourcing presents a promising approach to address wicked problems like climate change by leveraging the collective efforts of a diverse crowd. Such macro-task crowdsourcing requires facilitation. However, in the facilitation process, traditionally aggregating and synthesizing text contributions from the crowd is labor-intensive, demanding expertise and time from facilitators. Recent advancements in large language models (LLMs) hav…
Citizens' preferences on smart energy technologies and services for smart districts
The design of sustainable urban environments is one of the most pressing endeavors. Particularly the emergence of digital technologies has triggered a range of technocentric movements for urban development, such as smart cities or districts. City stakeholders, including city or district planners, public administrators, or governance stakeholders, expect technological innovations to enhance life in the city. However, citizens are under-represented…
Idea Evaluation for Solutions to Specialized Problems
Complex problems such as climate change pose severe challenges to societies worldwide. To overcome these challenges, digital innovation contests have emerged as a promising tool for idea generation. However, assessing idea quality in innovation contests is becoming increasingly problematic in domains where specialized knowledge is needed. Traditionally, expert juries are responsible for idea evaluation in such contests. However, experts are a sub…
The Crowd Without People
Large Language Models (LLMs) are transforming the innovation process by scaling ideation and creativity. This yields the challenge of evaluating the growing flood of ideas. In simpler contexts, tasks with clear criteria and well-defined outcome possibilities, where human evaluators are also a bottleneck, LLM systems are already being used as a scalable and cheap alternative. In this study, we assess whether LLMs and LLM agents can be used as eval…
Computer Science (5 works) · Human–computer interaction (4 works) · Psychology (4 works) · Data science (3 works) · Engineering (3 works) · Facilitation (3 works) · Knowledge management (3 works) · Mobile Crowdsensing and Crowdsourcing (3 works) · Open Source Software Innovations (3 works) · Artificial Intelligence (2 works)