TIMEA

Studies at the inwa Institute for Sustainable Water Systems at Hof University of Applied Sciences on the success factors of digitalisation in water management and on dealing with climate change in the Upper Franconia region and in the development of sponge cities have consistently shown that responsible stakeholders (e.g. cities and municipalities, planning engineers and architects, authorities) increasingly feel overwhelmed by the complexity of the tasks. As a result, the individual stakeholder groups limit themselves to their individual tasks, neglect the necessary analysis of the interlinked challenges and restrict the selection of solutions to proven standard solutions. There is no transfer of innovation. In order to counteract this behaviour, the Hof researchers developed the method of multi-level analysis (MEA) to record, define and evaluate different (impact) areas, especially at the beginning of complex (infrastructure) processes. MEA is based on a spatial view of complex tasks (micro, meso, macro and meta levels). Several identical task-related main criteria and associated individual criteria from research and the individual project are assigned to each level, correlated with each other and evaluated in a multi-stage process. This process is carried out for the general task requirements and for the planned solutions.

Depending on the project, several hundred individual criteria and their interactions must be taken into account. Due to this wealth of data, the current MEA version (Excel) can only be used effectively with the support of the Hof researchers, which considerably limits its dissemination. Without research support, there is a risk of distorted subjective perception and thus interpretation of the data by MEA users. As a result, important details, dependencies and trends are overlooked due to the limited capacity (mental and time-related) and perception of MEA users and the advantages of suitable innovation solutions remain unutilised. In order to prevent evaluation errors due to the individual interpretation of terms by MEA users in particular, a so-called "TextAnalyzer Pro" is to be developed, an innovative, intelligent module for processing and analysing texts with the help of Open AI technology. This module offers advantageous functions for identifying keywords in the text and then generates target-oriented process description features and fields (= individual criteria) in a practical table format for the MEA web system.

In this way, MEA users can be guided through the MEA process without scientific support. On the one hand, a web-based version allows a larger scope of criteria, on the other hand, this form of criteria selection shortens the processing time, which can then be used to expand the possible combinations of criteria in order to find the optimal innovation solution.