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Dieses Buch zeigt konkret auf, was Geschäftsprozessmanagement ist und wie man es nutzen kann. Hierzu werden die zentralen Aspekte erklärt und praxistaugliche Tools anhand von Beispielen vorgestellt. Erleichtern Sie sich die tägliche Praxis der Analyse und Optimierung von Geschäftsprozessen! Der Inhalt Durchgängiges Fallbeispiel Überblick über praxisrelevante Modellierungsmethoden Modellierung von Prozesslandkarten, Swimlanes, BPMN- und eEPK-Diagrammen Analyse und Optimierung von Prozessen Prozesscontrolling mit Kennzahlen
Focus on what matters: improved feature selection techniques for personal thermal comfort modelling
(2022)
Occupants' personal thermal comfort (PTC) is indispensable for their well-being, physical and mental health, and work efficiency. Predicting PTC preferences in a smart home can be a prerequisite to adjusting the indoor temperature for providing a comfortable environment. In this research, we focus on identifying relevant features for predicting PTC preferences. We propose a machine learning-based predictive framework by employing supervised feature selection techniques. We apply two feature selection techniques to select the optimal sets of features to improve the thermal preference prediction performance. The experimental results on a public PTC dataset demonstrated the efficiency of the feature selection techniques that we have applied. In turn, our PTC prediction framework with feature selection techniques achieved state-of-the-art performance in terms of accuracy, Cohen's kappa, and area under the curve (AUC), outperforming conventional methods.
Konzept zum Umgang mit Prüfungsstress und Lernblockaden bei Studierenden in der Studieneingangsphase
(2021)
Improving insect conservation management through insect monitoring and stakeholder involvement
(2023)
In recent years, the decline of insect biodiversity and the imminent loss of provided ecosystem functions and services has received public attention and raised the demand for political action. The complex, multi-causal contributors to insect decline require a broad interdisciplinary and cross-sectoral approach that addresses ecological and social aspects to find sustainable solutions. The project Diversity of Insects in Nature protected Areas (DINA) assesses insect communities in 21 nature reserves in Germany, and considers interactions with plant diversity, pesticide exposure, spatial and climatic factors. The nature reserves border on agricultural land, to investigate impacts on insect diversity. Part of the project is to obtain scientific data from Malaise traps and their surroundings, while another part involves relevant stakeholders to identify opportunities and obstacles to insect diversity conservation. Our results indicate a positive association between insect richness and biomass. Insect richness was negatively related to the number of stationary pesticides (soil and vegetation), pesticides measured in ethanol, the amount of area in agricultural production, and precipitation. Our qualitative survey along with stakeholder interviews show that there is general support for insect conservation, while at the same time the stakeholders expressed the need for more information and data on insect biodiversity, as well as flexible policy options. We conclude that conservation management for insects in protected areas should consider a wider landscape. Local targets of conservation management will have to integrate different stakeholder perspectives. Scientifically informed stakeholder dialogues can mediate conflicts of interests, knowledge, and values to develop mutual conservation scenarios.
Trust your guts: fostering embodied knowledge and sustainable practices through voice interaction
(2023)
Despite various attempts to prevent food waste and motivate conscious food handling, household members find it difficult to correctly assess the edibility of food. With the rise of ambient voice assistants, we did a design case study to support households’ in situ decision-making process in collaboration with our voice agent prototype, Fischer Fritz. Therefore, we conducted 15 contextual inquiries to understand food practices at home. Furthermore, we interviewed six fish experts to inform the design of our voice agent on how to guide consumers and teach food literacy. Finally, we created a prototype and discussed with 15 consumers its impact and capability to convey embodied knowledge to the human that is engaged as sensor. Our design research goes beyond current Human-Food Interaction automation approaches by emphasizing the human-food relationship in technology design and demonstrating future complementary human-agent collaboration with the aim to increase humans’ competence to sense, think, and act.
Due to expected positive impacts on business, the application of artificial intelligence has been widely increased. The decision-making procedures of those models are often complex and not easily understandable to the company’s stakeholders, i.e. the people having to follow up on recommendations or try to understand automated decisions of a system. This opaqueness and black-box nature might hinder adoption, as users struggle to make sense and trust the predictions of AI models. Recent research on eXplainable Artificial Intelligence (XAI) focused mainly on explaining the models to AI experts with the purpose of debugging and improving the performance of the models. In this article, we explore how such systems could be made explainable to the stakeholders. For doing so, we propose a new convolutional neural network (CNN)-based explainable predictive model for product backorder prediction in inventory management. Backorders are orders that customers place for products that are currently not in stock. The company now takes the risk to produce or acquire the backordered products while in the meantime, customers can cancel their orders if that takes too long, leaving the company with unsold items in their inventory. Hence, for their strategic inventory management, companies need to make decisions based on assumptions. Our argument is that these tasks can be improved by offering explanations for AI recommendations. Hence, our research investigates how such explanations could be provided, employing Shapley additive explanations to explain the overall models’ priority in decision-making. Besides that, we introduce locally interpretable surrogate models that can explain any individual prediction of a model. The experimental results demonstrate effectiveness in predicting backorders in terms of standard evaluation metrics and outperform known related works with AUC 0.9489. Our approach demonstrates how current limitations of predictive technologies can be addressed in the business domain.
The implementation of the Sustainable Development Goals (SDGs) and the conservation and protection of nature are among the greatest challenges facing urban regions. There are few approaches so far that link the SDGs to natural diversity and related ecosystem services at the local level and track them in terms of increasing sustainable development at the local level. We want to close this gap by developing a set of indicators that capture ecosystem services in the sense of the SDGs and which are based on data that are freely available throughout Germany and Europe. Based on 10 SDGs and 35 SDG indicators, we are developing an ecosystem service and biodiversity-related indicator set for the evaluation of sustainable development in urban areas. We further show that it is possible to close many of the data gaps between SDGs and locally collected data mentioned in the literature and to translate the universal SDGs to the local level. Our example develops this set of indicators for the Bonn/Rhein-Sieg metropolitan area in North Rhine-Westphalia, Germany, which comprises both rural and densely populated settlements. This set of indicators can also help improve communication and plan sustainable development by increasing transparency in local sustainability, implementing a visible sustainability monitoring system, and strengthening the collaboration between local stakeholders.
Professor Dr. Dietmar Fink, Inhaber des Lehrstuhls für Unternehmensberatung an der Hochschule Bonn-Rhein-Sieg und Geschäftsführender Direktor der Wissenschaftlichen Gesellschaft für Management und Beratung (WGMB) in Bonn, über den Mehrwert von Consulting-Rankings und den Sinn von Beraterprojekten bei Versicherern
Eintreten und abschalten
(2022)