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Publication#116 Strommarkt: Flexibilität und Kraftwerksstrategie( 2024-07-15)
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PublicationAugmenting Divergent and Convergent Thinking in the Ideation Process: An LLM-Based Agent System( 2024-05-03)Generative Artificial Intelligence (GenAI) in general and Large Language Models (LLMs) in particular have recently gained considerable attention in innovation management as a means to augment the generation of innovative ideas. While this trend seems to grow at an astonishing pace, knowledge of how to leverage the transformative potential of LLMs for the generation of new ideas remains scarce in the scientific literature. This poses a major challenge for organizations striving to channel the inherent capabilities of LLMs for idea generation in a meaningful and efficacious manner. Against this backdrop, we design and instantiate an artifact that augments divergent and convergent thinking in the ideation process with the help of LLMs (i.e., LLM-based agent systems) following the design science research paradigm. Based on the insights from ten evaluation interviews with subject matter experts, we conclude that the integration of our artifact into existing ideation processes is useful and applicable.
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PublicationManaging artificial intelligence applications in healthcare: Promoting information processing among stakeholders( 2024-04)AI applications hold great potential for improving healthcare. However, successfully operating AI is a complex endeavor requiring organizations to establish adequate management approaches. Managing AI applications requires functioning information exchange between a diverse set of stakeholders. Lacking information processing among stakeholders increases task uncertainty, hampering the operation of AI applications. Existing research lacks an understanding of holistic AI management approaches. To shed light on AI management in healthcare, we conducted a multi-perspective literature analysis followed by an interview study. Based on the organizational information processing theory, this paper investigates AI management in healthcare from an organizational perspective. As a result, we develop the AI application management model (AIAMA) that illustrates the managerial factors of AI management in healthcare and its interrelations. Furthermore, we provide managerial practices that improve information processing among stakeholders. We contribute to the academic discourse by providing a conceptual framework that increases the theoretical understanding of AI's management factors and understanding of management interrelations. Moreover, we contribute to practice by providing management practices that promote information processing and decrease task uncertainty when managing AI applications in healthcare.
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PublicationBlueprint of the Common European Energy Data Space( 2024-03)This document addresses the concept of a Common European Energy Data Space (CEEDS), providing detailed approaches and recommendations for its real-world realization. In particular, the main objective of this blueprint is to guide on enhancing the existing data infrastructures, in the energy domain, towards the full embracement of data space solutions. Bridging this gap will empower the introduction of novel energy services, which will increase the efficiency and reliability of the energy systems while providing substantial benefits for every stakeholder. The key scope of this document is to present (i) a framework for new economically feasible business use cases and (ii) the general data space architecture that can enable them. This architecture aims to interconnect the existing data infrastructures, of legacy systems, with federated data spaces; at this scope, technical specifications have been included.
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PublicationConsumer-centric electricity markets: Six design principles( 2024-03)Key to the necessary decarbonization of energy systems is the large-scale expansion of renewable energy sources and their integration into the electricity system. This integration is challenging because the feed-in from renewable energy sources is highly intermittent and largely dependent on uncontrollable factors such as weather patterns. To maintain grid stability, which refers to the required balance between demand and supply in the electricity system, flexibility is key. Large flexibility potentials can be found on the electricity demand side. However, current electricity market design in Europe, while providing major flexibility incentives, often neglects small-scale electricity consumers and distributed energy resources. We contribute to shape future electricity markets with consumers at the heart by developing six design principles for a consumer-centric electricity market design. We proceed by conducting a systematic literature review and evaluate the findings by expert interviews. Based on the developed design principles, we define a consumer-centric electricity market design as a set of market rules that align with the rules of other relevant energy markets and allow for the efficient matching of electricity demand and supply, with consumers having nondiscriminatory market access, being exposed to fine-grained price signals, being able to express their preferences, and having sufficient possibilities to protect themselves against unexpected price spikes. By actively incorporating consumers into electricity markets, we contribute to the overarching goal of integrating renewable energy sources while promoting energy justice, i.e., supporting a balanced mix of economic, political, environmental, and social interests.
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PublicationA study on interoperability between two Personal Health Train infrastructures in leukodystrophy data analysis( 2024)The development of platforms for distributed analytics has been driven by a growing need to comply with various governance-related or legal constraints. Among these platforms, the so-called Personal Health Train (PHT) is one representative that has emerged over the recent years. However, in projects that require data from sites featuring different PHT infrastructures, institutions are facing challenges emerging from the combination of multiple PHT ecosystems, including data governance, regulatory compliance, or the modification of existing workflows. In these scenarios, the interoperability of the platforms is preferable. In this work, we introduce a conceptual framework for the technical interoperability of the PHT covering five essential requirements: Data integration, unified station identifiers, mutual metadata, aligned security protocols, and business logic. We evaluated our concept in a feasibility study that involves two distinct PHT infrastructures: PHT-meDIC and PADME. We analyzed data on leukodystrophy from patients in the University Hospitals of Tübingen and Leipzig, and patients with differential diagnoses at the University Hospital Aachen. The results of our study demonstrate the technical interoperability between these two PHT infrastructures, allowing researchers to perform analyses across the participating institutions. Our method is more space-efficient compared to the multi-homing strategy, and it shows only a minimal time overhead.
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PublicationSmartphone-Enabled Predictive Maintenance - Development and Implementation of a Reference Architecture and Processes( 2024)Predictive maintenance (PdM) is a hot topic in the field of manufacturing. However, its industry-wide realization lacks accepted integration concepts. Small and medium-sized enterprises (SMEs), in particular, tend to postpone PdM initiatives, primarily due to the high costs and effort of creating interoperability with established as well as in-use machines. PdM requires machine data to be proactively maintained. Therefore, in-use machines without integrated sensors must be replaced or cost-intensively upgraded. Furthermore, it is not advisable to invest in upgrades of existing machines, as they are cost-intensive, and their remaining lifespan is unknown as well as difficult to predict. One promising approach to applying PdM to these kinds of machines is the use of retail smartphones. With up to 16 sensors onboard, they offer an opportunity to cost-effectively collect required data without being tied to a single machine. Following a design science research approach, we present a reference software architecture consisting of a mobile and server application and reference processes for smartphone-enabled PdM to provide a lightweight approach, especially for SMEs. Together with five manufacturers and a software developer, we demonstrated and evaluated our artifacts using the software prototypes in a real-world setting.
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PublicationCapturing artificial intelligence applications’ value proposition in healthcare - a qualitative research study( 2024)Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can capture the value of AI applications on a managerial level. To overcome adoption hurdles, HC organizations would benefit from understanding how they can capture AI applications’ potential. We conduct a comprehensive systematic literature review and 11 semi-structured expert interviews to identify, systematize, and describe 15 business objectives that translate into six value propositions of AI applications in HC. Our results demonstrate that AI applications can have several business objectives converging into risk-reduced patient care, advanced patient care, self-management, process acceleration, resource optimization, and knowledge discovery. We contribute to the literature by extending research on value creation mechanisms of AI to the HC context and guiding HC organizations in evaluating their AI applications or those of the competition on a managerial level, to assess AI investment decisions, and to align their AI application portfolio towards an overarching strategy.
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PublicationThe Twin Transformation Butterfly: Capabilities for an Integrated Digital and Sustainability Transformation( 2024)Complex digitalization and sustainability challenges shape today’s management agendas. To date, the dedication of Information Systems research to both challenges has not been equal in terms of effort and reward. Building capabilities to leverage the synergetic potential of digital and sustainability transformation may enhance organizational performance and imply new value creation for the common good. To uncover such synergetic potential, this work conceptualizes the “twin transformation” construct as a value-adding reinforcing interplay between digital transformation and sustainability transformation efforts that improve an organization by leveraging digital technologies to enable sustainability and to guide digital progress by leveraging sustainability. The twin transformation conceptualization is complemented with a capability framework for twin transformation drawing from dynamic capability theory. This work contributes to descriptive knowledge of the interplay between digital transformation and sustainability transformation, setting a foundation for further theorizing on twin transformation and enabling organizations to twin transform.
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PublicationUnleashing the economic and ecological potential of energy flexibility: Attractiveness of real-time electricity tariffs in energy crises( 2024)The European energy crisis in 2021 and 2022 emphasized the importance of energy flexibility to mitigate price peaks and manage increased market volatility. Dynamic electricity tariffs are key to unlocking the potential of energy flexibility, as they incentivize flexible consumers to reduce their costs by shifting their load to periods of low prices. We quantify the potential of dynamic tariffs and focus on their economic and ecological potential particularly in energy crises. Using German Day-Ahead spot market data covering 2019 to 2022 as basis for a dynamic tariff, we determine the cost and emission spread between non-flexible and flexible industrial processes. Our results show that energy flexibility together with the real-time electricity tariff lead to energy cost reductions, with relative cost reductions of flexible loads being up to 12 times higher in the energy crisis. Moreover, pre-crisis electricity costs and associated emissions were highly positively correlated, implying flexibilities in real-time electricity tariffs may minimize electricity costs while simultaneously reducing emissions. Based on our results, we conclude that real-time electricity pricing provides a suitable instrument to (1) incentivize necessary investments in energy flexibility, especially in energy crises, and (2) facilitate flexible consumers to reduce costs and emissions at the same time.
