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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.20402 |
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| _version_ | 1866918167209574400 |
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| author | Maiden, Neil Zachos, Konstantinos Lockerbie, James Petrianakis, Kostas Brown, Amanda |
| author_facet | Maiden, Neil Zachos, Konstantinos Lockerbie, James Petrianakis, Kostas Brown, Amanda |
| contents | This paper presents a new computational model of creative outcomes, informed by creativity theories and techniques, which was implemented to generate more novel opportunities for innovation projects. The model implemented five functions that were developed to contribute to the generation of innovation opportunities with higher novelty without loss of usefulness. The model was evaluated using opportunities generated for an innovation project in the hospitality sector. The evaluation revealed that the computational model generated outcomes that were more novel and/or useful than outcomes from Notebook LM and ChatGPT4o. However, not all model functions contributed to the generation of more novel opportunities, leading to new directions for further model development |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_20402 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A computational model and tool for generating more novel opportunities in professional innovation processes Maiden, Neil Zachos, Konstantinos Lockerbie, James Petrianakis, Kostas Brown, Amanda Artificial Intelligence This paper presents a new computational model of creative outcomes, informed by creativity theories and techniques, which was implemented to generate more novel opportunities for innovation projects. The model implemented five functions that were developed to contribute to the generation of innovation opportunities with higher novelty without loss of usefulness. The model was evaluated using opportunities generated for an innovation project in the hospitality sector. The evaluation revealed that the computational model generated outcomes that were more novel and/or useful than outcomes from Notebook LM and ChatGPT4o. However, not all model functions contributed to the generation of more novel opportunities, leading to new directions for further model development |
| title | A computational model and tool for generating more novel opportunities in professional innovation processes |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2510.20402 |