1,928 research outputs found
Ask questions, get sales : close the deak and create long-term relationships / Stephan Schiffman.
No full textIncludes index.v, 168 pages ;In Ask Questions, Get Sales, the author and sales guru Stephan Schiffman helps readers boost their careers to the gold-medal level by teaching them how to strengthen their questioning skills during the sales process. The premise is simple yet effective: In order to be successful, salespeople need to change their mindset from "need-orientated" to "do-orientated". The message of the book centers around six core "do" questions: What do you do? How do you do it? When and where do you do it? Why do you do it that way? Who do you do it with? How can we help you do it better? With this indispensable guide in their briefcase, salespeople will have information at the ready to score big sales over the short term and the long term
Discovering unusual study patterns using anomaly detection and XAI
No full textLearning Analytics (LA) has been leveraged as a tool to analyze and improve educational processes by informing its stakeholders. LA for student profiling focuses on discovering learning patterns and trends based on diverse features extracted from trace data.Prior studies have used classical clustering methods to group students and understand the study patterns of each cluster. However, variations within the clusters are still large making it difficult to draw concrete insights into the relation between study behaviors and learning outcomes. In this work, we leverage anomaly detection and eXplainable AI techniques to distinguish between normal and abnormal study patterns and to possibly discover unexpected patterns that are not apparent from clustering alone. We perform external validation to check the generalizability and compare the insights on study patterns from our method to be at par with insights gained from previous studies
Unemployment Benefits and Unemployment Rates of Low-Skilled and Elder Workers in West Germany: A Search Equilibrium Approach
No full textApproach Author & abstract Download 16 References 1 Citations Related works & more Corrections Author Listed: Launov, Andrey ([email protected]) (University of Kent) Wolff, Joachim ([email protected]) (Institute for Employment Research (IAB), Nuremberg) Klasen, Stephan ([email protected]) (University of Göttingen) Registered: Stephan Klasen Abstract In this paper we investigate whether the extension of the entitlement to unemployment benefits in the mid 80s can explain the increase in the unemployment rates of unskilled and elder workers in western Germany. To answer this question we estimate a version of the Burdett-Mortensen search equilibrium model and analyze how workers’ search behaviour responded to these reforms. We try both nonparametric and fully-parametric estimation methods and identify the cases in which the nonparametric approach cannot be applied. We find that the entitlement reforms are largely responsible for the increase of unemployment among unskilled workers
Unemployment Benefits and Unemployment Rates of Low-Skilled and Elder Workers in West Germany: A Search Equilibrium Approach
No full textApproach Author & abstract Download 16 References 1 Citations Related works & more Corrections Author Listed: Launov, Andrey ([email protected]) (University of Kent) Wolff, Joachim ([email protected]) (Institute for Employment Research (IAB), Nuremberg) Klasen, Stephan ([email protected]) (University of Göttingen) Registered: Stephan Klasen Abstract In this paper we investigate whether the extension of the entitlement to unemployment benefits in the mid 80s can explain the increase in the unemployment rates of unskilled and elder workers in western Germany. To answer this question we estimate a version of the Burdett-Mortensen search equilibrium model and analyze how workers’ search behaviour responded to these reforms. We try both nonparametric and fully-parametric estimation methods and identify the cases in which the nonparametric approach cannot be applied. We find that the entitlement reforms are largely responsible for the increase of unemployment among unskilled workers
Measuring Vulnerability to Poverty Using Long-Term Panel Data
No full textMeasuring Vulnerability to Poverty Using Long-Term Panel Data Author & abstract Download & other version 16 References 4 Citations Related works & more Corrections Author Listed: Katja Landau (Georg-August-University Göttingen) Stephan Klasen (Georg-August-University Göttingen) Walter Zucchini (Georg-August-University Göttingen) Registered: Stephan Klasen Abstract We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply di fferent regression models, based on household covariates and previous-year equivalence income, to classify a household as vulnerable or not. Predictive performance is assessed using the Receiver Operating Characteristics (ROC), which takes account of false positive as well as true positive rates. Estimates based on cross-sectional data are much less accurate than those based on panel data, but for Germany, the accuracy of vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and high mobility in and out of poverty
Measuring Vulnerability to Poverty Using Long-Term Panel Data
No full textMeasuring Vulnerability to Poverty Using Long-Term Panel Data Author & abstract Download & other version 16 References 4 Citations Related works & more Corrections Author Listed: Katja Landau (Georg-August-University Göttingen) Stephan Klasen (Georg-August-University Göttingen) Walter Zucchini (Georg-August-University Göttingen) Registered: Stephan Klasen Abstract We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply di fferent regression models, based on household covariates and previous-year equivalence income, to classify a household as vulnerable or not. Predictive performance is assessed using the Receiver Operating Characteristics (ROC), which takes account of false positive as well as true positive rates. Estimates based on cross-sectional data are much less accurate than those based on panel data, but for Germany, the accuracy of vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and high mobility in and out of poverty
Evaluation of in-store processes related to returnable packaging services offered in grocery stores - the store management perspective
No full textAuthor Stephan LehnerMasterarbeit Universität Linz 202
Evaluation of in-store processes related to returnable packaging services offered in grocery stores - the store management perspective
No full textAuthor Stephan LehnerMasterarbeit Universität Linz 202
Explainable learning analytics: assessing the stability of student success prediction models by means of explainable AI
No full textBeyond managing student dropout, higher education stakeholders need decision support to consistently influence the student learning process to keep students motivated, engaged, and successful. At the course level, the combination of predictive analytics and self-regulation theory can help instructors determine the best study advice and allow learners to better self-regulate and determine how they want to learn. The best performing techniques are often black-box models that favor performance over interpretability and are heavily influenced by course contexts. In this study, we argue that explainable AI has the potential not only to uncover the reasons behind model decisions, but also to reveal their stability across contexts, effectively bridging the gap between predictive and explanatory learning analytics (LA). In contributing to decision support systems research, this study (1) leverages traditional techniques, such as concept drift and performance drift, to investigate the stability of student success prediction models over time; (2) uses Shapley Additive explanations in a novel way to explore the stability of extracted feature importance rankings generated for these models; (3) generates new insights that emerge from stable features across cohorts, enabling teachers to determine study advice. We believe this study makes a strong contribution to education research at large and expands the field of LA by augmenting the interpretability and explainability of prediction algorithms and ensuring their applicability in changing contexts.</p
Dataset including the raw dataset and analyses used in the paper presented at the PACIS 2024 conference, titled: Measuring Internal Validity in Mixed Methods User Feedback Survey by Finding Inconsistencies with sentimentR and ChatGPT-4
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