TY - JOUR A1 - Pietsch, Wolfram T1 - Augmenting voice of the customer analysis by analysis of belief JF - QFD-Forum Y1 - 2015 SN - 1431-6951 IS - 30 SP - 1 EP - 5 ER - TY - CHAP A1 - Schulte, Maximilian A1 - Eggert, Mathias T1 - Predicting hourly bitcoin prices based on long short-term memory neural networks T2 - Proceedings of the International Conference on Wirtschaftsinformatik (WI) 2021 N2 - Bitcoin is a cryptocurrency and is considered a high-risk asset class whose price changes are difficult to predict. Current research focusses on daily price movements with a limited number of predictors. The paper at hand aims at identifying measurable indicators for Bitcoin price movement s and the development of a suitable forecasting model for hourly changes. The paper provides three research contributions. First, a set of significant indicators for predicting the Bitcoin price is identified. Second, the results of a trained Long Short-term Memory (LSTM) neural network that predicts price changes on an hourly basis is presented and compared with other algorithms. Third, the results foster discussions of the applicability of neural nets for stock price predictions. In total, 47 input features for a period of over 10 months could be retrieved to train a neural net that predicts the Bitcoin price movements with an error rate of 3.52 %. Y1 - 2021 N1 - 16th International Conference on Wirtschaftsinformatik, March 2021, Essen, Germany ER - TY - JOUR A1 - Bernecker, Andreas A1 - Boyer, Pierre C. A1 - Gathmann, Christina T1 - The Role of Electoral Incentives for Policy Innovation: Evidence from the US Welfare Reform JF - American Economic Journal: Economic Policy Y1 - 2021 U6 - http://dx.doi.org/10.1257/pol.20190690 SN - 1945-774X VL - 13 IS - 2 SP - 26 EP - 57 PB - American Economic Association CY - Nashville, Tenn. ER - TY - CHAP A1 - Diekmann, Julian A1 - Eggert, Mathias T1 - Is a Progressive Web App an Alternative for Native App Development? T2 - 3. Wissenschaftsforum: Digitale Transformation (WiFo21) (Lecture Notes in Informatics ; P-319) N2 - The existence of several mobile operating systems, such as Android and iOS, is a challenge for developers because the individual platforms are not compatible with each other and require separate app developments. For this reason, cross-platform approaches have become popular but lack in cloning the native behavior of the different operating systems. Out of the plenty cross-platform approaches, the progressive web app (PWA) approach is perceived as promising but needs further investigation. Therefore, the paper at hand aims at investigating whether PWAs are a suitable alternative for native apps by developing a PWA clone of an existing app. Two surveys are conducted in which potential users test and evaluate the PWA prototype with regard to its usability. The survey results indicate that PWAs have great potential, but cannot be treated as a general alternative to native apps. For guiding developers when and how to use PWAs, four design guidelines for the development of PWA-based apps are derived based on the results. KW - Progressive Web App KW - PWA KW - Cross-platform KW - Evaluation KW - Mobile web Y1 - 2021 SN - 978-3-88579-713-5 SP - 35 EP - 48 PB - Gesellschaft für Informatik CY - Darmstadt ER - TY - CHAP A1 - Eggert, Mathias A1 - Kriska, Melina T1 - Gamification for software development processes – relevant affordances and design principles T2 - Proceedings of the 55th Hawaii International Conference on System Sciences N2 - A Gamified Information System (GIS) implements game concepts and elements, such as affordances and game design principles to motivate people. Based on the idea to develop a GIS to increase the motivation of software developers to perform software quality tasks, the research work at hand aims at investigating relevant requirements from that target group. Therefore, 14 interviews with software development experts are conducted and analyzed. According to the results, software developers prefer the affordances points, narrative storytelling in a multiplayer and a round-based setting. Furthermore, six design principles for the development of a GIS are derived. Y1 - 2022 SN - 978-0-9981331-5-7 U6 - http://dx.doi.org/10.24251/HICSS.2022.200 N1 - Hawaii International Conference on System Sciences (HICSS) 2022, 04.01.2022 – 07.01.2022 SP - 1614 EP - 1623 PB - HICSS Publishing CY - Honolulu ER - TY - JOUR A1 - Mueller, Tobias A1 - Segin, Alexander A1 - Weigand, Christoph A1 - Schmitt, Robert H. T1 - Feature selection for measurement models JF - International journal of quality & reliability management N2 - Purpose In the determination of the measurement uncertainty, the GUM procedure requires the building of a measurement model that establishes a functional relationship between the measurand and all influencing quantities. Since the effort of modelling as well as quantifying the measurement uncertainties depend on the number of influencing quantities considered, the aim of this study is to determine relevant influencing quantities and to remove irrelevant ones from the dataset. Design/methodology/approach In this work, it was investigated whether the effort of modelling for the determination of measurement uncertainty can be reduced by the use of feature selection (FS) methods. For this purpose, 9 different FS methods were tested on 16 artificial test datasets, whose properties (number of data points, number of features, complexity, features with low influence and redundant features) were varied via a design of experiments. Findings Based on a success metric, the stability, universality and complexity of the method, two FS methods could be identified that reliably identify relevant and irrelevant influencing quantities for a measurement model. Originality/value For the first time, FS methods were applied to datasets with properties of classical measurement processes. The simulation-based results serve as a basis for further research in the field of FS for measurement models. The identified algorithms will be applied to real measurement processes in the future. KW - Feature selection KW - Modelling KW - Measurement models KW - Measurement uncertainty Y1 - 2022 U6 - http://dx.doi.org/10.1108/IJQRM-07-2021-0245 SN - 0265-671X IS - Vol. ahead-of-print, No. ahead-of-print. PB - Emerald Group Publishing Limited CY - Bingley ER - TY - JOUR A1 - Bruksle, Ieva A1 - Chwallek, Constanze A1 - Krastina, Anzelika T1 - Strengthening sustainability in entrepreneurship education - implications for shifting entrepreneurial thinking towards sustainability at universities JF - ACTA PROSPERITATIS N2 - By developing innovative solutions to social and environmental problems, sustainable ventures carry greatpotential. Entrepreneurship which focuses especially on new venture creation can be developed through education anduniversities, in particular, are called upon to provide an impetus for social change. But social innovations are associatedwith certain hurdles, which are related to the multi-dimensionality, i.e. the tension between creating social,environmental and economic value and dealing with a multiplicity of stakeholders. The already complex field ofentrepreneurship education has to face these challenges. This paper, therefore, aims to identify starting points for theintegration of sustainability into entrepreneurship education. To pursue this goal experiences from three differentproject initiatives between the partner universities: Lapland University of Applied Sciences, FH Aachen University ofApplied Sciences and Turiba University are reflected and findings are systematically condensed into recommendationsfor education on sustainable entrepreneurship. KW - climate change KW - entrepreneurship education KW - Finland KW - Germany KW - Latvia Y1 - 2023 U6 - http://dx.doi.org/10.37804/1691-6077-2023-14-37-48 SN - 1691-6077 VL - 14 IS - 1 SP - 37 EP - 48 PB - Sciendo ER - TY - BOOK A1 - Drumm, Christian A1 - Scheuermann, Bernd A1 - Weidner, Stefan T1 - Introduction to SAP S/4HANA® : The official companion book based on model company Global Bike–for learning, teaching, and training N2 - This easy-to-understand introduction to SAP S/4HANA guides you through the central processes in sales, purchasing and procurement, finance, production, and warehouse management using the model company Global Bike. Familiarize yourself with the basics of business administration, the relevant organizational data, master data, and transactional data, as well as a selection of core business processes in SAP. Using practical examples and tutorials, you will soon become an SAP S/4HANA professional! Tutorials and exercises for beginners, advanced users, and experts make it easy for you to practice your new knowledge. The prerequisite for this book is access to an SAP S/4HANA client with Global Bike version 4.1. - Business fundamentals and processes in the SAP system - Sales, purchasing and procurement, production, finance, and warehouse management - Tutorials at different qualification levels, exercises, and recap of case studies - Includes extensive download material for students, lecturers, and professors Y1 - 2024 SN - 9783960122685 PB - Espresso Tutorials CY - Gleichen ER - TY - CHAP A1 - Kohl, Philipp A1 - Freyer, Nils A1 - Krämer, Yoka A1 - Werth, Henri A1 - Wolf, Steffen A1 - Kraft, Bodo A1 - Meinecke, Matthias A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - ALE: a simulation-based active learning evaluation framework for the parameter-driven comparison of query strategies for NLP T2 - Deep Learning Theory and Applications. DeLTA 2023. Communications in Computer and Information Science N2 - Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance. However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP. The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework. KW - Active learning KW - Query learning KW - Natural language processing KW - Deep learning KW - Reproducible research Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/978-3-031-39059-3 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 235 EP - 253 PB - Springer CY - Cham ER - TY - JOUR A1 - Kempt, Hendrik A1 - Freyer, Nils A1 - Nagel, Saskia K. T1 - Justice and the normative standards of explainability in healthcare JF - Philosophy & Technology N2 - Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability. KW - Clinical decision support systems KW - Justice KW - Medical AI KW - Explainability KW - Normative standards Y1 - 2022 U6 - http://dx.doi.org/10.1007/s13347-022-00598-0 VL - 35 IS - Article number: 100 SP - 1 EP - 19 PB - Springer Nature CY - Berlin ER -