Abstract: Innovation increasingly depends on contributions that no single organization can provide alone. For artificial intelligence, this raises a fundamental question: how can bringing together organizations with different expertise and resources translate into innovation? Innovation ecosystems offer a setting for such collaboration, yet access to partners and opportunities for exchange does not ensure that participants benefit equally. This study asks how value creation in an AI innovation ecosystem can be conceptualized and translated into a performance measurement framework for ecosystem management and member reporting. We argue that measurement should connect ecosystem offerings with the interactions they enable and the benefits members experience. Following Design Science Research, the study draws on exclusive research access to an AI innovation ecosystem in Germany that brings together established firms, start-ups and research organizations. Two interview waves cover internal respondents of the orchestrator and member organizations, which allows us to examine where management objectives correspond with members' experiences and where they differ. The anticipated contribution is a theoretically grounded account of how performance measurement can capture value creation across autonomous organizations with different objectives, while supporting the management of collaborative innovation.

Bio: Claire Louise Wall is a PhD candidate at the Chair of Management Accounting at the Technical University of Munich (TUM). She holds a Master's degree in Management and Digital Technology from TUM and has gained practical experience in strategy, consulting, and industry. Her research focuses on value creation in AI innovation ecosystems, particularly on how collaboration between organisations enables innovation and how the resulting value can be measured.

Room details: IWI, Room 52-7024 (7th floor)

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