TY - JOUR A1 - Bernecker, Andreas T1 - Divided Government and the Adoption of Economic Reforms JF - CESifo DICE Report - Journal for Institutional Comparison Y1 - 2014 SN - 1612-0663 VL - 12 IS - 4 SP - 47 EP - 52 PB - Ifo Institute for Economic Research CY - München ER - TY - JOUR A1 - Görgens, Stefan A1 - Greubel, Steffen A1 - Moosdorf, Andreas T1 - How to mobilize 20,000 people: Perspectives on retail and consumer goods Y1 - 2013 SP - 52 EP - 58 ER - TY - JOUR A1 - Moosdorf, Andreas T1 - It’s not just the Talent, it’s the Knowledge Transfer Method JF - GC Ticker Y1 - 2009 IS - 1 SP - 16 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 - 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 - JOUR A1 - Klettke, Tanja A1 - Homburg, Carsten A1 - Gell, Sebastian T1 - How to measure analyst forecast effort JF - European Accounting Review N2 - We introduce a new way to measure the forecast effort that analysts devote to their earnings forecasts by measuring the analyst's general effort for all covered firms. While the commonly applied effort measure is based on analyst behaviour for one firm, our measure considers analyst behaviour for all covered firms. Our general effort measure captures additional information about analyst effort and thus can identify accurate forecasts. We emphasise the importance of investigating analyst behaviour in a larger context and argue that analysts who generally devote substantial forecast effort are also likely to devote substantial effort to a specific firm, even if this effort might not be captured by a firm-specific measure. Empirical results reveal that analysts who devote higher general forecast effort issue more accurate forecasts. Additional investigations show that analysts' career prospects improve with higher general forecast effort. Our measure improves on existing methods as it has higher explanatory power regarding differences in forecast accuracy than the commonly applied effort measure. Additionally, it can address research questions that cannot be examined with a firm-specific measure. It provides a simple but comprehensive way to identify accurate analysts. Y1 - 2015 U6 - http://dx.doi.org/10.1080/09638180.2014.909291 SN - 0963-8180 VL - 24 IS - 1 SP - 129 EP - 146 PB - Taylor & Francis CY - London ER - TY - JOUR A1 - Emhardt, Selina N. A1 - Jarodzka, Halszka A1 - Brand-Gruwel, Saskia A1 - Drumm, Christian A1 - Niehorster, Diederick C. A1 - van Gog, Tamara T1 - What is my teacher talking about? Effects of displaying the teacher’s gaze and mouse cursor cues in video lectures on students’ learning JF - Journal of Cognitive Psychology N2 - Eye movement modelling examples (EMME) are instructional videos that display a teacher’s eye movements as “gaze cursor” (e.g. a moving dot) superimposed on the learning task. This study investigated if previous findings on the beneficial effects of EMME would extend to online lecture videos and compared the effects of displaying the teacher’s gaze cursor with displaying the more traditional mouse cursor as a tool to guide learners’ attention. Novices (N = 124) studied a pre-recorded video lecture on how to model business processes in a 2 (mouse cursor absent/present) × 2 (gaze cursor absent/present) between-subjects design. Unexpectedly, we did not find significant effects of the presence of gaze or mouse cursors on mental effort and learning. However, participants who watched videos with the gaze cursor found it easier to follow the teacher. Overall, participants responded positively to the gaze cursor, especially when the mouse cursor was not displayed in the video. KW - Instructional design KW - eye movement modelling examples KW - video learning Y1 - 2022 U6 - http://dx.doi.org/10.1080/20445911.2022.2080831 SN - 2044-5911 SP - 1 EP - 19 PB - Routledge, Taylor & Francis Group CY - Abingdon 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 - 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 -