A Systematic Characterization of Artificial Intelligence Business Models as a Fundament for Business Model Innovation and Strategic Decision-Making - Wilga, Matthäus; Jalowski, Max; Kirschbaum, Julius; Roth, Angela (21st European Academy of Management (EURAM) Conference 2021, 2021)

Chatbots im Unternehmen: Rechtliches Risikomanagement zur Haftungsvermeidung - Schultz, Marion; Kirschbaum, Julius (2024)

Designing innovation ecosystems with functional roles – The case of industrial, intelligent manufacturing - Kirschbaum, Julius; Posselt, Tim; Möslein, Kathrin (Handbook on Digital Platforms and Ecosystems in Manufacturing, 2024)
Organizations increasingly engage in what can be described as innovation ecosystems. Organizational members of such ecosystems aim to achieve mutual agreement between the participating organizations on the contribution and allocation of resources and capabilities. The question is how this mutual agreement can be achieved. This study aims to take a first step towards solving this problem by introducing a new logic for resource and capability allocation. A set of archetypical functional roles is conceptualized, which enables structured discussions and mutual understanding amongst members of innovation ecosystems. Case studies are conducted for three platform types commonly used by industrial organizations: an industrial internet of things platform, a data marketplace and an innovation lab. The resulting functional roles can be used to map and analyze existing innovation ecosystems, as well as to explore new ecosystem designs and business models that organizations could aim to implemen
Keywords: IIoT platforms; ecosystem design; functional roles; industrial data marketplaces; industrial innovation labs; innovation ecosystems

Exploring Ecosystem Concepts - A Topic Modeling Approach - Kirschbaum, Julius; Winkler, Christian (EURAM 2024, 2024)
In contrast to previous literature reviews, this paper takes a computational approach to discriminate the numerous ecosystem concepts within the broader business and management literature. It aims to enable researchers to specify the types of ecosystems in the focus of their studies. While most previous research was based on comparatively small sample sizes, the computational approach employed in this research enables the analysis of a large dataset on ecosystem literature. Three topic modeling techniques and inductive category formation are utilized to identify ecosystem themes and concepts within various strands of research based on abstracts of academic literature. Results indicate the use of three perspectives on ecosystems: ecosystem as a catchphrase, ecosystem as a phenomenon, and ecosystem as a concept. Moreover, nine ecosystem themes with different uses of the term ‘ecosystem’ are identified. Based on the reviewed literature associated with each theme, seven preliminary dimensions are derived that define the characteristics of an ecosystem: the underlying view of the nature of an ecosystem as a metaphor vs. as an analogy and as a phenomenon vs. as a concept, context or domain, central element/nucleus, locality, ecosystem goal/outcome, types of entities and links between them. These dimensions enable research to specify the phenomena and concepts that they and thereby support rigorous study design.<br
Keywords: ecosystem concepts; ecosystem characteristics; literature analysis

Roleplaying in inter-organisational relationships – The Case of AI-based Innovation Ecosystems - Kirschbaum, Julius; Schymanietz, Martin; Möslein, Kathrin (BAM Doctoral Conference 2021, 2021)

The How and Why of AI - Kirschbaum, Julius; Schymanietz, Martin; Möslein, Kathrin (Dcotroal Colloquium EURAM 2021, 2021)

Uncovering the potential of chatbots during the development of industrial smart product-service systems - Koustas, Spyridon Georg; Kirschbaum, Julius; Möslein, Kathrin (Procedia CIRP, 2024)
Digitalization of manufacturing processes led to the emergence of smart product-service systems (sPSS), the development of which requires expertise across multiple domains, while the Internet of Things (IoT) technology landscape poses challenges regarding hardware selection. This paper proposes an industry chatbot that employs GPT-4 and bge-base-en models to assist manufacturers during the IoT sensor search and selection process. The chatbot utilizes a vectorized knowledge base to provide technical insights and recommend compatible hardware. User tests conducted with both experts and novices revealed the chatbot’s accuracy and potential for improvement. Overall, this approach holds promise for expediting the development of sPS
Keywords: Industry chatbots; IoT sensors; Industrial Product-Service Systems (IPSS)

Use-Case-based Innovation for Artificial Intelligence - An ontological Approach - Kirschbaum, Julius; Posselt, Tim; Roth, Angela (Thirtieth European Conference on Information Systems (ECIS 2022), 2022)
Keywords: artificial intelligence; innovation; adoption; use-case; ontology