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Faculty
„Innovation für Society“
(2019)
Virtual reality (VR) is starting to realize some of its promise as a tool to improve training effectiveness. However, research on VR for training and development is limited. Existing theories and models relating to organizational training and learning are infrequently used in the VR literature. A greater understanding of why VR works in the training context would help training designers create effective programs that leverage this continuously developing technology. This paper provides a typology of VR technologies specifically relevant to HR and integrates HR training frameworks and theory into findings on VR training from these other literatures. We specifically focus on immersive VR technology and seek to better understand reasons for the effectiveness of VR technologies for both training and assessment. We review findings, integrate related streams of research, and offer guideposts for those contemplating VR implementation in four important areas: training reactions in a VR context, VR-specific learning outcomes, opportunities for assessment using VR, and the effect of VR on training transfer. We conclude the paper by identifying a VR-training agenda for HR researchers.
Process-Driven Applications flourish through the interaction between an executable BPMN process model, human tasks, and external software services. All these components operate on shared process data, so it is even more important to check the correct data flow. However, data flow is in most cases not explicitly defined but hidden in model elements, form declarations, and program code. This paper elaborates on data-flow anomalies acting as indicators for potential errors and how such anomalies can be uncovered despite implicit and hidden data-flow definitions. By considering an integrated view, it goes beyond other approaches which are restricted to separate data-flow analysis of either process model or source code. The main idea is to merge call graphs representing programmed services into a control-flow representation of the process model, to label the resulting graph with associated data operations, and to detect anomalies in that labeled graph using a dedicated data-flow analysis. The applicability of the solution is demonstrated by a prototype designed for the Camunda BPM platform.
A major requirement for Credit Scoring models is of course to provide a risk prediction that is as accurate as possible. In addition, regulators demand these models to be transparent and auditable. Thus, in Credit Scoring very simple Predictive Models such as Logistic Regression or Decision Trees are still widely used and the superior predictive power of modern Machine Learning algorithms cannot be fully leveraged. A lot of potential is therefore missed, leading to higher reserves or more credit defaults. This talk presents an overview of techniques that are able to make “black box” machine learning models transparent and demonstrate how they can be applied in Credit Scoring. We use the DALEX set of tools to compare a traditional scoring approach with state of the art Machine Learning models and asses both approaches in terms of interpretability and predictive power. Results show that a comparable degree of interpretability can be achieved while machine learning techniques keep their ability to improve predictive power.
Innovative business models for data-driven B2B platforms evolve rapidly based on the prospects of digital technology. In addition to the platform provider, service providers on the supply side of the digital platform - the so-called complementors - play an important role in the process of value creation. This paper highlights the complementors’ perspective on the different facets of complementor relationship management (CoRM) and answers the following research questions: From the perspective of a complementor, what are the main fields of CoRM for data-driven B2B platforms? What factors of influence comprise the reason complementors join a platform?
Focal companies are embedded in complex supply networks consisting of various suppliers, customers, competitors and complementors. The activities of these actors influence the com-petitive position of the focal companies. Some customers achieve preferred customer status and gain preferential treatment, others have to restrain to being standard customers getting less privileged services. Consequently, buying companies in such markets have to achieve transparency about the relationships of their suppliers towards their competitors and comple-mentors in order to map them and to analyse their impact. Current literature lacks a holistic approach to capture these relationships. In which sources can the focal companies find the desired information? Which kind of information do they really need? And in which situations is the need for transparency high and when is it low? The aim of this research is to examine these relationships using a World Café method with purchasers for data gathering followed by a Gioia method to structure the qualitative data. The result is a list of desired knowledge cov-ering business, supplier and collaboration details; a set of information sources clustered in pub-lished and unpublished sources as well as contingency factors regarding general conditions, changes and particular occasions that require a high supplier relationship knowledge. All an-swers have been rated by their importance during the World Café. The answers can help to operationalise the mapping of supplier relationships towards competitors and complementors in order to assess the own customer status compared to other customers.
Study programme development is one of the most challenging processes
at universities since all faculty is involved. And in our experience, the redesign of already existing programmes seems to be even more difficult: Whereas innovative forces want to pick up new trends (e.g. digitalisation or other new teaching concepts) more conservative forces emphasises on values and refer to existing experience. Both positions are important and contextually right. Thus, the presented format provides a gradual framework to bridge the gap between both sides in an interactive and creative process.
Both sides are invited to negotiate the best possible result by using an unusual approach for university discussions, the benefit analysis method known e.g. from economics. After the negotiating activity, it should be obvious that a change of perspective is also helpful, if not necessary, to create a new or updated study programme. The practiced approach helps as well to recognise which limits for study programme development remain when visionary ideas are measured against reality.