Generative AI in Idea Development: The Role of Numeric and Visual Feedback

Human creativity is a crucial factor in developing innovative ideas. Many ideas are being generated, but only a few receive feedback, as creating feedback is a costly and time-consuming effort in innovation. While feedback promises higher idea quality, previous work requires human experts with domain expertise. Generative AI could provide automated feedback and is expected to transform creative work. This short paper presents an experimental series in which we let humans collaborate with generative AI to develop ideas. Based on dual-coding and media synchronicity theory, we conceptualize numerical and visual feedback to overcome cognitive barriers. We manipulate feedback modalities and timing to personalize the interaction. Our contributions provide evidence on when and why specific co-creative arrangements between humans and generative AI are favorable

Towards Predicting Supplier Resilience: A Tree-Based Model Approach

ith looming uncertainties and disruptions in today's global supply chains, such as lockdown measures to contain COVID-19, supply chain resilience has gained considerable attention recently. While decision-makers in procurement have emphasized the importance of traditional risk assessment, its shortcomings can be complemented by resilience. However, while most resilience studies are too qualitative in nature and abstract to inform supplier decisions, many quantitative resilience studies frequently rely on complex and impractical operations research models fed with simulated supplier data. Thus there is the need for an integrative, intermediate way for the practical and automated prediction of resilience with real-world data. We therefore propose a random forest-based supervised learning method to predict supplier resilience, outperforming the current human benchmark evaluation by 139 percent. The model is trained on both internal ERP data and publicly available secondary data to help assess suppliers in a pre-screening step, before deciding which supplier to select for a specific product. The results of this study are to be integrated into a software tool developed for measuring and tracking the total cost of supply chain resilience from the perspective of purchasing decisions