Tim Meyer-Hollatz’s research while affiliated with University of Bayreuth and other places

As artificial intelligence (AI) and machine learning (ML) advance, concerns about their sustainability impact grow. The emerging field "Sustainability of AI" addresses this issue, with papers exploring distinct aspects of ML’s sustainability. However, it lacks a comprehensive approach that considers all ML development phases, treats sustainability holistically, and incorporates practitioner feedback. In response, we developed the sustainable ML design pattern matrix (SML-DPM) consisting of 35 design patterns grounded in justificatory knowledge from research, refined with naturalistic insights from expert interviews and validated in three real-world case studies using a web-based instantiation. The design patterns are structured along a four-phased ML development process, the sustainability dimensions of environmental, social, and governance (ESG), and allocated to five ML stakeholder groups. It represents the first artifact to enhance each ML development phase along each ESG dimension. The SML-DPM fuels advancement by aggregating distinct research, laying the groundwork for future investigations, and providing a roadmap for sustainable ML development.

The importance of digitalization and sustainability has grown significantly in recent years, and organizations must consider both aspects when developing new products and services. Howev-er, identifying ideas that align with digital and sustainability goals remains challenging. This study addresses this gap by developing a digital sustainability-oriented innovation evaluation framework following the design science research paradigm. By conducting a systematic litera-ture review and 13 expert interviews, we identified 13 criteria that depict the unique characteris-tics of digital sustainability-oriented innovations, particularly relevant at the front-end of inno-vation. The criteria are structured within a framework that helps practitioners to evaluate and select innovations that align with digital and sustainability objectives. Thus, it simultaneously promotes digital and sustainable development. By bridging the gap between digital and sustain-ability innovation evaluation, our research contributes to the organizations' twin transfor-mation, combines two distinct research streams, and offers practical guidance for organizations embracing digital sustainability-oriented innovations.

Cities worldwide are seeking to enhance their sustainable mobility by reducing individual motorized transportation. While intermodal mobility-combining multiple transportation modes in one journey-is a key solution, individuals encounter challenges initiating intermodal journeys owing to the proliferation of mobility services. Providing accurate information at the right time is crucial amidst this complexity. While research has examined information needs for each mobility mode independently, the relationships between modes, phases, and information needs have barely been empirically investigated. Through a sequential mixed-method approach involving a literature review and a survey of >500 participants, this study identifies and validates the concept of phase-and mode chain-sensitive information needs. The findings provide initial insights, emphasizing phase relationships, mode chain relationships, and the interplays between phases and mode chains-a holistic understanding. This research can guide the design of more effective traveler information systems, aiding the shift toward sustainable urban mobility.

https://www.fit.fraunhofer.de/content/dam/fit/de/documents/ey-fraunhofer-fit-study_building-a-digital-and-sustainable-future_2023.pdf