Dieses essential gibt einen Überblick über verschiedene Go-to-Market-Strategien für zweiseitige digitale Plattform-Geschäftsmodelle. Zunächst liegt der Fokus auf den Strategien zur sequenziellen, simultanen und viralen Kundenakquise. Im zweiten Teil zeigt der Beitrag, mit welchen Faktoren man positive Interaktionen fördert, um eine kritische Masse an Nutzern zu gewinnen.

This study demonstrates the need for novel gas engine control systems for com-
bined heat and power plants, also known as cogeneration power plants, connected to natural
gas grids. Hydrogen addition to natural gas grids in a range of up to 5% by volume is already
permitted throughout Europe. This offers the possibility to reduce carbon dioxide emissions
of end consumers connected to public natural gas grids and contributes to climate protec-
tion. However, conventional engine controls are not designed for natural gas/hydrogen mixture
operation. We tested fuels with up to 30% hydrogen by volume using a commercial six-cylinder
spark ignition engine, designed for natural gas or biogas operation in power plants. With engine
settings according to usual cogeneration operation, nitrogen oxide emissions increased expo-
nentially with increasing hydrogen amounts. We demonstrate that the usual approach of using
the lower heating value of the fuel mixture to regulate the engine is unable to accommodate the
hydrogen induced changes. For this reason, we developed a mathematical model to determine
the nitrogen oxide emissions based on boost pressure and power output. The idea behind this
novel approach is to regulate the engine based on emissions, regardless of the fuel gas. In this
work the approach for this virtual sensor is described and its performance demonstrated.

The wave of digitization has begun. Organizations deal with huge amounts of data, such as logs, websites, and documents. A common way to make the information contained in these sources machine-accessible for automated processing is to first extract the information and then store it in a knowledge graph. A key task in this approach is to recognize entities. While common named entity recognition (NER) models work well for common entity types, they typically fail to recognize custom entities. Custom entity recognition requires data to be manually annotated and custom NER models to be trained. To efficiently extract the information, this paper proposes an innovative solution: Our Gazetteer approach uses a knowledge graph to create a coarse and fast NER component, reducing the need for manual annotation and saving human effort. Focusing on a university use case, our Gazetteer is integrated into a chatbot for entity recognition. In addition, data can be annotated using the Gazetteer and an NER model can be trained. Subsequently, the NER model can be used to recognize unseen custom entities, which are then added to the knowledge graph. This will improve the knowledge graph and make it self-extending.

Extracting triples of subjects, objects, and predicates from text to populate knowledge bases traditionally involves several intermediate steps such as co-reference resolution, named entity recognition, and relationship extraction. Treating triple extraction as translation task from source sentences to sets of triples, we present an end-to-end solution for information extraction that uses task prefixes to prompts a fine-tuned large language model to extract triples from text. Thus, the need for data labeling and training multiple models is reduced.

The following paper presents the evaluation of an artificially intelligent assistant system (DIAS) with a service-oriented chatbot as a central communication element. The conversational AI (Artificial Intelligence) is supposed to increase information transparency in higher education environments and thus support students, teachers, and administrative staff. The exploratory study had two objectives: first, we intended to find out about the usability and utility of the DIAS chatbot using the CUQ (Chatbot Usability Questionnaire) score and benchmark the results against other conversational agents. Secondly, we were interested in possible effects among the different variables of interest, which could contribute to further theory development of chatbots in education. The results show that the DIAS chatbot scored above average, and can support students in finding relevant information, particularly if they use the assistant frequently. Positive aspects included the intuitive use, a welcoming persona (expressed in design & language) and easy navigation. The negative feedback showed potential for improvement particularly in content quality and handling dialogue mistakes, which is a general shortcoming of conversational AI at this development stage. The results can be used as a guidance for future research and theory building. However, they must be considered carefully due to several study limitations.

In a current research project at the Ansbach University of Applied Science, an AI-based quiz function was created to serve as a voluntary student-oriented support offer to determine their learning progress in their respective courses by means of conducting self-assessment quizzes. The application takes lecture scripts as input and applies a question generation model to create questions that students can answer. In order to evaluate the given answers, another language model is involved to perform Natural Language Inference (NLI). Users can engage with the system via a graphical user interface currently provided via a web app. To assess preliminary feasibility and perception of the model prototype, a qualitative focus group discussion following a semi-structured interview guideline prepared by the research team according to similar studies in the education field (Sek et al. 2012) was conducted with five participants. A transcript of the discussion was prepared and analyzed using the qualitative content analysis method according to Kuckartz. Overall, the quiz function was well received by the participants of the focus group. However, the prototype still has potential when it comes to generating meaningful questions and transparently assigning categories to the given answers. Furthermore, the quiz parameters should be individually adjustable by users. In the following paper, the development of the service is illustrated by outlining the considerations for the application design and the training procedure of the language models. Afterwards, the design of the qualitative focus group is described including the presentation of the results.

This study investigates the potential benefits and drawbacks of adding hydrogen to natural
gas grids on stationary cogeneration plants. Fuel blended with up to 30% hydrogen by
volume was tested using a commercial six-cylinder spark ignition engine designed for pure
natural gas operation without modifications to the engine. In line with normal practice for
cogeneration plant engines, the power output, the lower heating value of the air/fuel
mixture, the ignition timing and the engine speed were held constant. Results show that
increasing hydrogen concentration led to an earlier peak cylinder pressure, indicating
significantly accelerated combustion. As a result, peak pressures were up to 39% higher
than with natural gas and up to 10% of fuel burned before top dead center. Despite this,
thermal efficiency improved up to 6%. Cycle-by-cycle variation decreased by half, indi-
cating reduced misfires on account of hydrogen. However, nitrogen oxide emissions
increased exponentially with increasing hydrogen amounts. Our findings suggest that
hydrogen-enriched natural gas is a promising fuel for stationary cogeneration plants, but
modifications to engine control settings are necessary to ensure optimal performance and
compliance with nitrogen oxide emission regulations. These modifications might include
adjustments to the mixture control system and ignition timing.

Ambidextrie im Innovationsmanagement bezieht sich auf die Fähigkeit eines Unternehmens, sowohl das Kerngeschäft zu stärken (Exploit) als auch mit neuen Angeboten in bestehenden oder neuen Märkten zu agieren (Explore). Dabei besteht die Herausforderung darin, beide Innovationsmodi in einer komplementären Art und Weise einzusetzen, anstatt sich auf einen der beiden Modi zu beschränken. Eine ambidextre Ausrichtung und die Fähigkeit, beide Innovationsmodi, Exploit und Explore, gleichzeitig und in dem Maß einzusetzen, das die Umstände erfordern, ermöglicht es Unternehmen, schnell auf Veränderungen in der Branche zu reagieren und sich langfristig im Markt zu behaupten. Für eine erfolgreiche Umsetzung von Ambidextrie im Innovationsmanagement spielen die Unternehmenskultur, der Führungsstil resp. das Führungsverständnis ebenso eine Rolle, wie Grundsatzentscheidungen in Bezug auf die Digitalisierung. Es ist entscheidend, dass Unternehmen die Potenziale von Ambidextrie erkennen und lernen, den Exploit- und Explore-Modus gezielt und optimal einzusetzen, um langfristig Wettbewerbsvorteile zu erzielen. Dieser Grundlagenartikel fokussiert insbesondere auf die im weiteren Heft weniger angesprochenen Themenbereiche. Er ordnet die Ambidextrie im Innovationsmanagement anhand der Themenfelder Kultur, Führung und Digitalisierung ein und liefert Argumente, weshalb die Akzeptanz und Nutzung von Ambidextrie zu Wettbewerbsvorteilen führen.