http://dl.gi.de/handle/20.500.12116/10598 2026-07-23T06:23:54Z http://dl.gi.de/handle/20.500.12116/10732 Digitalization: Opportunity and Challenge for the Business and Information Systems Engineering Community Legner, Christine; Eymann, Torsten; Hess, Thomas; Matt, Christian; Böhmann, Tilo; Drews, Paul; Mädche, Alexander; Urbach, Nils; Ahlemann, Frederik 2017-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/10731 Successful Business Model Types of Cloud Providers Labes, Stine; Hanner, Nicolai; Zarnekow, Ruediger The acceleration of technical change in the fast moving electronics market increases the uncertainty and risk for IT providers. Influenced by new IT provisioning concepts such as cloud computing, providers are looking to identify stable guidelines and success factors within existing and new business models. The authors have conducted an intensive analysis of the business model characteristics of 45 providers in the cloud market that are critical to success. A cloud business model framework with 105 characteristics was used to systemize the business models, and the data was analyzed statistically in regard to indicators for success. The results revealed 42 success-related business model characteristics, and a cluster analysis led to three common combinations of characteristics that describe meta types of cloud business models. The most promising meta type is a specialized cloud provider with customer-oriented branch solutions, while small-scale newcomers with aggregation services experience difficulties to be competitive. To evaluate and verify the results and the success of each business model type, 12 expert interviews were conducted. The interview statements were aggregated and summarized to offer recommendations for action and a prediction for the success of cloud business models. 2017-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/10729 Meta Modeling for Business Process Improvement Johannsen, Florian; Fill, Hans-Georg Conducting business process improvement (BPI) initiatives is a topic of high priority for today’s companies. However, performing BPI projects has become challenging. This is due to rapidly changing customer requirements and an increase of inter-organizational business processes, which need to be considered from an end-to-end perspective. In addition, traditional BPI approaches are more and more perceived as overly complex and too resource-consuming in practice. Against this background, the paper proposes a BPI roadmap, which is an approach for systematically performing BPI projects and serves practitioners’ needs for manageable BPI methods. Based on this BPI roadmap, a domain-specific conceptual modeling method (DSMM) has been developed. The DSMM supports the efficient documentation and communication of the results that emerge during the application of the roadmap. Thus, conceptual modeling acts as a means for purposefully codifying the outcomes of a BPI project. Furthermore, a corresponding software prototype has been implemented using a meta modeling platform to assess the technical feasibility of the approach. Finally, the usability of the prototype has been empirically evaluated. 2017-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/10730 Recommendation-Based Conceptual Modeling and Ontology Evolution Framework (CMOE+) Gailly, Frederik; Alkhaldi, Nadejda; Casteleyn, Sven; Verbeke, Wouter Within an enterprise, various stakeholders create different conceptual models, such as process, data, and requirements models. These models are fundamentally based on similar underlying enterprise (domain) concepts, but they differ in focus, use different modeling languages, take different viewpoints, utilize different terminology, and are used to develop different enterprise artifacts; as such, they typically lack consistency and interoperability. This issue can be solved by enterprise-specific ontologies, which serve as a reference during the conceptual model creation. Using such a shared semantic repository makes conceptual models interoperable and facilitates model integration. The challenge to accomplish this is twofold: on the one hand, an up-to-date enterprise-specific ontology needs to be created and maintained, and on the other hand, different modelers also need to be supported in their use of the enterprise-specific ontology. The authors propose to tackle these challenges by means of a recommendation-based conceptual modeling and an ontology evolution framework, and we focus in particular on ontology-based modeling support. To this end, the authors present a framework for Business Process Modeling Notation (BPMN) as a conceptual modeling language, and focus on how modelers can be assisted during the modeling process and how this impacts the semantic quality of the resulting models. Subsequently, a first, large-scale explorative experiment is presented involving 140 business students to evaluate the BPMN instantiation of our framework. The experiments show promising results with regard to incurred overheads, intention of use and model interoperability. 2017-01-01T00:00:00Z