TY - JOUR A1 - Goebel, Philipp A1 - Reuter, Carsten A1 - Pibernik, Richard A1 - Sichtmann, Christina T1 - The influence of ethical culture on supplier selection in the context of sustainable sourcing JF - International Journal of Production Economics KW - Beschaffung KW - Lieferantenwahl KW - Nachhaltigkeit Y1 - 2012 U6 - https://doi.org/10.1016/j.ijpe.2012.02.020 SN - 0925-5273 VL - 140 IS - 1 SP - 7 EP - 17 PB - Elsevier BV ER - TY - JOUR A1 - Wolpert, Stefan A1 - Reuter, Carsten T1 - Status Quo of City Logistics in Scientific Literature BT - Systematic Review JF - Transportation Research Record: Journal of the Transportation Research Board N2 - Roadway infrastructure is reaching maximum capacity in urban areas because of expanding urbanization, demographic changes, and continuously increasing freight volumes. An overview of the latest research on city logistics is needed to address these challenges, and a review of the scientific literature is presented. A specifically designed framework for systematic literature review was used to analyze 92 relevant articles from prominent electronic databases. A taxonomy of city logistics literature was created to aid academics and practitioners and to stimulate interest of other parties in this area. KW - Stadtentwicklung KW - Logistik Y1 - 2012 U6 - https://doi.org/10.3141/2269-13 SN - 0361-1981 VL - 2269 IS - 1 SP - 110 EP - 116 PB - SAGE Publications ER - TY - JOUR A1 - Reuter, Carsten A1 - Goebel, Philipp A1 - Foerstl, Kai T1 - The impact of stakeholder orientation on sustainability and cost prevalence in supplier selection decisions JF - Journal of Purchasing and Supply Management KW - Supply Chain Management KW - Nachhaltigkeit Y1 - 2012 U6 - https://doi.org/10.1016/j.pursup.2012.06.004 SN - 1478-4092 VL - 18 IS - 4 SP - 270 EP - 281 PB - Elsevier BV ER - TY - JOUR A1 - Goebel, Philipp A1 - Reuter, Carsten A1 - Pibernik, Richard A1 - Sichtmann, Christina A1 - Bals, Lydia T1 - Purchasing managers' willingness to pay for attributes that constitute sustainability JF - Journal of Operations Management N2 - Considering the increasing international division of labor, as well as stakeholders' growing awareness of sustainability, assuring that business practices are sustainable is a major challenge. Companies have to account for the fact that any misconduct at a supplier's premises may have spillover effects that reach the manufacturer or retailer. Therefore, purchasing managers have to assure that their suppliers are compliant with sustainability standards. This, however, may induce higher purchasing costs and, as a consequence, force a trade‐off between (short term) economic (i.e., purchasing cost reduction) and social/environmental sustainability criteria. How purchasing managers evaluate this trade‐off is particularly interesting because they often receive performance‐based salaries that incentivize the reduction of purchasing costs. Our paper sheds light on this trade‐off by examining how much purchasing managers are willing to pay to assure compliance along different sustainability dimensions when selecting new suppliers in a mature market setting, namely Germany. Additionally, we identify potential (individual, professional, and organization‐related) factors that may impact the purchasing managers' willingness to pay (WTP), and examine their effects. Among the most surprising findings, purchasing managers on average are willing to pay a price premium for manuals that demonstrate compliance with the United Nationals Global Compact (UNGC). Furthermore, the results show that this WTP is mostly influenced (negatively) by self‐enhancement (on the individual level) and/or obedience to authority (on the organizational level), but the effects of company, affiliation with the UNGC, gender, or years of experience have no influence. Moreover, the WTP is higher for the social than for the environmental dimension, and the marginal effect of accreditation on WTP depends on which combinations of dimensions are accredited. KW - Einkauf KW - Einkaufspolitik KW - Nachhaltigkeit Y1 - 2018 U6 - https://doi.org/10.1016/j.jom.2018.08.002 SN - 0272-6963 VL - 62 IS - 1 SP - 44 EP - 58 PB - Wiley ER - TY - CHAP A1 - Hubert, Andreas A1 - Guo, Chenxi A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Improving Fast 6D Pose Estimation with Adaptive Model Fusion T2 - 2025 5th International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) KW - Maschinelles Lernen KW - Deep Learning KW - Montagezelle Y1 - 2025 U6 - https://doi.org/https://doi.org/10.1109/MLISE66443.2025.11100239 SP - 58 EP - 63 PB - IEEE ER - TY - CHAP A1 - Serfling, Benjamin A1 - Reichert, Hannes A1 - Bayerlein, Lorenzo A1 - Doll, Konrad A1 - Radkhah-Lens, Kati T1 - LiDAR Based Semantic Perception for Forklifts in Outdoor Environments T2 - 2025 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) KW - Gabelstapler KW - Autonomes Fahrzeug Y1 - 2025 U6 - https://doi.org/https://doi.org/10.1109/SOLI66289.2025.11396313 SP - 40 EP - 45 PB - IEEE ER - TY - CHAP A1 - Hock, Isabell A1 - Haug, Jim A1 - Abke, Jörg T1 - DIDACTIC INTEGRATION OF SELF-STUDY AND FACE-TO-FACE TEACHING: EXPERIENCES WITH AN ADAPTIVE LEARNING SYSTEM IN ENGINEERING EDUCATION T2 - ICERI Proceedings N2 - This paper presents a study of student perspectives on the didactic integration of digital learning elements into face-to-face university lectures and seminars. The overarching context is the use of the adaptive learning system (ALS) HASKI (short for Hochschullehre: Adaptiv, selbstgesteuert, KI-gestützt, i.e. Higher Education: Adaptive, Self-Directed, AI-Supported), which was tested in computer science teaching within a blended learning approach, more specifically in flipped classroom scenarios. The joint project, consisting of three Bavarian universities, focuses on the exploratory integration of an AI-based ALS into higher education. The system was applied in a course for mechatronics students (2nd semester) and provided a variety of adaptive learning elements. HASKI generates individual learning paths with AI based on learning behavior and learning styles. It is designed to promote personalized, self-directed learning as support for blended learning scenarios. The method chosen for data collection is a qualitative content analysis based on exploratory interviews with a semi-structured set of questions. Four central analysis criteria were considered: acceptance and perception of the learning elements, integration into lectures and exercise sessions, didactic coherence, and suggestions for improvement. The results show that students prefer explanatory scripts, interactive tasks, and quiz elements that require a certain degree of reflection. In addition, the respondents are largely convinced of the integration into the seminar, as the HASKI system adequately guides them for what to prepare for. When it comes to embedding the system into lectures, especially in the form of question rotation in small groups, the feedback is ambivalent. Although the potential for in-depth learning was recognized, the low participation of fellow students was critically reflected upon. A particular difficulty mentioned was the lack of coordination between self-study and classroom attendance. While some participants saw this as a discrepancy of coherence, others viewed the adaptive system as a balancing factor. There was a desire for a clearer time structure and more in-depth materials that go beyond mere repetition. Overall, the findings provide initial indicators of successful aspects in the integration of adaptive systems into classroom teaching. The continuous development of a clear didactic division of roles between self-study and classroom phases is of central importance here. Further research with larger samples, if necessary, could provide more comprehensive insights. KW - E-Learning KW - Ingenieurstudium KW - Unterrichtsmethode Y1 - 2025 SN - 978-84-09-78706-7 U6 - https://doi.org/https://doi.org/10.21125/iceri.2025.1600 SN - 2340-1095 VL - 1 SP - 5825 EP - 5829 PB - IATED ER - TY - CHAP A1 - Schoppel, Paul A1 - Haug, Jim A1 - Manz, Julian A1 - Bigler, Dimitri A1 - Hock, Isabell A1 - Abke, Jörg A1 - Hagel, Georg T1 - METHODICAL APPROACH FOR ANALYZING LEARNING PATH FITNESS IN AN AI-BASED ADAPTIVE LEARNING SYSTEM T2 - EDULEARN Proceedings N2 - Learning paths are a cornerstone of many adaptive learning systems, particularly those focusing on adaptive navigational techniques. Evaluating and analyzing these paths is therefore crucial to ensure they effectively support both learners and instructors. For eLearning this process must be highly scalable despite minimal oversight and little to no control over learners’ behavior. Consequently, learning path evaluation should be automated, user-friendly, and precise. However, current research on this topic often emphasizes simulations, performance metrics, or mathematical models, without fully considering the broader, learner-centered aspects necessary for meaningful adaptation. The authors prior findings also indicate that approaches to assessing the suitability of learning paths must be optimized. To address these gaps, this paper presents a potential methodological approach for comprehensive learning path evaluation, aiming to enhance both the precision of adaptive learning systems and the overall learning experience. Three different algorithms, derived from learning style tendencies and a lecturer recommendation, were analyzed as an illustrative example, although the method itself is not constrained by the form or data basis of these algorithms. The adaptive learning system utilizes various measures to gauge the suitability of a learning path, all gathered through real-time learner feedback. These measures include the correlation between students’ preferred path and each algorithm, referred to as it’s fitness, the alignment between students’ actual adherence to a generated path and their own perception of their study behavior as well as their satisfaction with the path, and the connection between algorithm fitness and both actual performance and perceived performance. To collect data, students were asked to create their own preferred learning paths by digitally arranging the provided learning elements after receiving an introduction to the respective categories. Once they had completed a topic with a generated learning path, they rated their satisfaction with it and indicated whether they had followed its sequence. They also estimated whether their knowledge level had changed. Learning analytics were then employed to compare these self-reports with students’ actual study behavior. Performance was measured using a rating system, while Spearman’s Rho and Kendall’s Tau served as the main correlation metrics for data analysis. The results indicate that all three algorithms produce paths more closely aligned with students’ preferred learning paths than the lecturer recommendation, although no single algorithm demonstrated clear dominance. Student satisfaction showed some correlation with the fitness of the generated learning path. Additionally, student ratings appeared to have a slight positive correlation with learning path fitness, whereas self-perceived performance showed no discernible difference. Analysis of the link between actual student behavior and their feedback suggested that students were not reliable in judging whether or not they had followed a learning path. These findings are consistent with the authors earlier work suggesting the potential effectiveness of the learning path algorithms examined, thus supporting this new methodological approach to analyzing learning paths. The study also provided valuable insights for further development; however, its limited sample size remains a challenge for validation. KW - E-Learning KW - Unterrichtsmethode Y1 - 2025 SN - 978-84-09-74218-9 U6 - https://doi.org/https://doi.org/10.21125/edulearn.2025.2430 SN - 2340-1117 VL - 1 SP - 9438 EP - 9446 PB - IATED ER - TY - CHAP A1 - Fischer, David Vincent A1 - Haug, Jim A1 - Schoppel, Paul A1 - Abke, Jörg A1 - Becker, Matthias A1 - Hagel, Georg T1 - Evaluation of a Node-based Automatic Short Answer Tool “NodeGrade” T2 - Proceedings of the 6th European Conference on Software Engineering Education N2 - NodeGrade tries to provide a suitable solution for the problem of time-intensive short answer grading. This research focuses simultaneously on performance, functionality and user experience, which is underlined by a triangulated approach. The evaluation results show comparable performance of NodeGrade on public datasets, even outperforming GPT-4 on the SemEval 2013 Task 7. Matching of NodeGrade’s output with multiple human expert raters reveals some weaknesses regarding cases at the lower and upper boundary. In terms of user experience, the interviewed and observed students recognized both positive facets, like better learning support and helpful feedback, and negative sides, including technical limitations and lack of transparency. Overall, NodeGrade promises high potential for further practical use and testing in the field of software engineering education and automatic short answer grading. KW - Software Engineering KW - Hochschuldidaktik Y1 - 2025 U6 - https://doi.org/https://dl.acm.org/doi/10.1145/3723010.3723021 SP - 20 EP - 29 PB - ACM CY - New York, NY, USA ER - TY - CHAP A1 - Chaar, Mohamad Mofeed A1 - Raiyn, Jamal A1 - Weidl, Galia T1 - Predicting Depth Maps from Single RGB Images and Addressing Missing Information in Depth Estimation T2 - Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems N2 - Depth imaging is a crucial area in Autonomous Driving Systems (ADS), as it plays a key role in detecting and measuring objects in the vehicle’s surroundings. However, a significant challenge in this domain arises from missing information in Depth images, where certain points are not measurable due to gaps or inconsistencies in pixel data. Our research addresses two key tasks to overcome this challenge. First, we developed an algorithm using a multi-layered training approach to generate Depth images from a single RGB image. Second, we addressed the issue of missing information in Depth images by applying our algorithm to rectify these gaps, resulting in Depth images with complete and accurate data. We further tested our algorithm on the Cityscapes dataset and successfully resolved the missing information in its Depth images, demonstrating the effectiveness of our approach in real-world urban environments. KW - Autonomes Fahrzeug KW - Tiefenbild Y1 - 2025 U6 - https://doi.org/10.5220/0013365900003941 SP - 549 EP - 556 PB - SCITEPRESS - Science and Technology Publications ER -