In this paper, two systematic literature searches are used to pursue questions about digitization in management reporting on the one hand and role-specific questions on the other. We assume that greater digitization in terms of efficiency and effectiveness will change the role of management accountants in general and in reporting in particular, as this should lead to more automation and possibly more time for consulting activities from management accountants/controllers. After a strictly documented filtering process, a total of 51 papers remained for the analysis of the research questions posed. As a result, in addition to research gaps in management reporting, the most important information technology (IT) tools in management accounting and management reporting can be identified. Concerning corporate performance and management accounting performance, the research also reveals a connection with digitization/IT trends in controlling, controller roles, and role conflicts. The systematic literature evaluations serve as a basis for further research to verify the possible causal relationships found.

Although the current literature on large amounts of data and data analysis is growing rapidly, profound assumptions and practical tasks are still missing in some areas. This paper focuses on SMEs and their approach to data analysis issues and their implementation. With the methodology of design research we use characteristics of SME types and link them with the corresponding requirements of the compatible data analysis system to increase performance. We derive a framework that serves as a starting point for further research. The results indicate that there are several requirements that companies need to consider when realigning or restructuring their internal database. Depending on the type of SME, we choose a performance grid analysis based on the characteristics and requirements of data analysis systems.

The major goal of dynamic load balancing is not primarily to equalize the load on the nodes of a parallel computing system, but to optimize the average response time of single requests or the throughput of all applications in the system. Therefore it is often necessary not only to keep all processors busy and all processor ready queue lengths within the same range, but to avoid delays and inefficient computations caused by foreseeable but ignored data flow and precedence constraints between related tasks. We present concepts for dynamic consideration of inter task dependencies within small groups of tasks and evaluate them observing real applications in a load balancing environment on a network of workstations. The concepts are developed from scheduling of single task graphs towards heterogeneous multi user operation scenarios.>