TY - BOOK A1 - Gell, Sebastian T1 - Determinants of earnings forecast error, earnings forecast revision and earnings forecast accuracy N2 - ​Earnings forecasts are ubiquitous in today’s financial markets. They are essential indicators of future firm performance and a starting point for firm valuation. Extremely inaccurate and overoptimistic forecasts during the most recent financial crisis have raised serious doubts regarding the reliability of such forecasts. This thesis therefore investigates new determinants of forecast errors and accuracy. In addition, new determinants of forecast revisions are examined. More specifically, the thesis answers the following questions: 1) How do analyst incentives lead to forecast errors? 2) How do changes in analyst incentives lead to forecast revisions?, and 3) What factors drive differences in forecast accuracy? Y1 - 2012 SN - 978-3-8349-3936-4 SN - 978-3-8349-3937-1 U6 - http://dx.doi.org/10.1007/978-3-8349-3937-1 N1 - Titel in der Buchreihe: Quantitatives Controlling PB - Springer Gabler CY - Wiesbaden 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 - 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 - Drumm, Christian A1 - Emhardt, Selina N. A1 - Kok, Ellen M. A1 - Jarodzka, Halzka A1 - Brand-Gruwel, Saskia A1 - van Gog, Tamara T1 - How Experts Adapt Their Gaze Behavior When Modeling a Task to Novices JF - Cognitive science N2 - Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically. Y1 - 2020 U6 - http://dx.doi.org/10.1111/cogs.12893 SN - 1551-6709 VL - 44 IS - 9 PB - Wiley CY - Weinheim ER - TY - CHAP A1 - Eggert, Mathias A1 - Edelbauer, Thomas Rudolf T1 - Gamified Information Systems for Assisted Living Facilities - Relevant Design Guidelines, Affordances and Adoption Barriers T2 - 15th International Conference on Wirtschaftsinformatik, March 08-11, 2020 Potsdam, Germany Y1 - 2020 U6 - http://dx.doi.org/10.30844/wi_2020_f3-eggert SP - 1 EP - 16 ER - TY - JOUR A1 - Emhardt, Selina A1 - Jarodzka, Halszka A1 - Brand-Gruwel, Saskia A1 - Drumm, Christian A1 - Gog, Tamara van T1 - Introducing eye movement modeling examples for programming education and the role of teacher's didactic guidance JF - ETRA '20 Short Papers: ACM Symposium on Eye Tracking Research and Applications N2 - In this article, we introduce how eye-tracking technology might become a promising tool to teach programming skills, such as debugging with ‘Eye Movement Modeling Examples’ (EMME). EMME are tutorial videos that visualize an expert's (e.g., a programming teacher's) eye movements during task performance to guide students’ attention, e.g., as a moving dot or circle. We first introduce the general idea behind the EMME method and present studies that showed first promising results regarding the benefits of EMME to support programming education. However, we argue that the instructional design of EMME varies notably across them, as evidence-based guidelines on how to create effective EMME are often lacking. As an example, we present our ongoing research on the effects of different ways to instruct the EMME model prior to video creation. Finally, we highlight open questions for future investigations that could help improving the design of EMME for (programming) education. Y1 - 2020 U6 - http://dx.doi.org/10.1145/3379156.3391978 IS - Art. 52 SP - 1 EP - 4 PB - ACM CY - New York ER - TY - CHAP A1 - Eggert, Mathias A1 - Stanke, Max-Alexander T1 - Adoption of Integrated Voice Assistants in Health Care– Requirements and Design Guidelines T2 - 15th International Conference on Wirtschaftsinformatik, March 08-11, 2020 Potsdam, Germany Y1 - 2020 U6 - http://dx.doi.org/10.30844/wi_2020_k2-eggert SP - 1 EP - 16 ER - TY - JOUR A1 - Eggert, Mathias A1 - Alberts, Jens T1 - Frontiers of business intelligence and analytics 3.0: a taxonomy-based literature review and research agenda JF - Business Research N2 - Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper’s contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda. Y1 - 2020 U6 - http://dx.doi.org/10.1007/s40685-020-00108-y SN - 2198-2627 VL - 2020 IS - 13 SP - 685 EP - 739 PB - Springer CY - Heidelberg ER - 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 - Ernhardt, Selina A1 - Drumm, Christian A1 - van Gog, Tamara A1 - Brand-Gruwel, Saskia A1 - Jarodzka, Halszka T1 - Through the eyes of a programmer : a research project on how to foster programming education with eye-tracking technology T2 - Tagungsband zur 32. AKWI-Jahrestagung vom 15.09.2019 bis 18.09.2019 an der Fachhochschule für Angewandte Wissenschaften Aachen Y1 - 2019 SN - 978-3-944330-62-4 SP - 42 EP - 47 PB - Mana-Buch CY - Heide ER -