TY - CHAP A1 - Buchholz, Wolfgang A1 - Kappel, Antonia A1 - Schiele, Holger T1 - Cost versus Innovation Leaders: When do they need Supply Network Mapping? The impact of SNM on purchasing performance T2 - IPSERA Conference proceedings N2 - Buying firms lack transparency about the supplier relationships in their networks. The applica-tion of dedicated tools such as Supply Network Mapping (SNM) can help to visualize and analyze these relationships. However, the impact of such tools on the purchasing performance has not been explored yet. Moreover, companies with different competitive strategies might have different motivations to use these tools. Therefore, this paper tests the impact of supplier relationship information and SNM on the purchasing performance on a large sample of 624 purchasers. A multi-group analysis in structural equation modeling estimates the impact of a cost leadership versus a differentiation strategy on cost saving and innovation performance. We show that information quality and SNM indeed improve the purchasing performance. Moreover, cost leaders use SNM if they know their supplier relationships with sub-suppliers, while innovation leaders use it if they know their supplier relationships with other customers. Hence, our results prove the usefulness of the SNM tool and give recommendations for its use depending on a company’s competitive strategy. Y1 - 2019 SP - 1 EP - 19 ER - TY - CHAP A1 - Buchholz, Wolfgang A1 - Kappel, Antonia A1 - Schiele, Holger T1 - Knowing your suppliers: people or media as key sources of information? T2 - IPSERA Conference proceedings N2 - Most companies have realized the high importance of becoming the preferred customers of their suppliers to obtain preferential resource allocation. However, they cannot evaluate their own customer attractiveness properly. In order to make the assessment of the own customer status possible, this paper analyzes the impact of several information sources on the preferred customer status knowledge, supplier satisfaction knowledge and knowledge of alternative supplier relationships with other customers. Testing these hypotheses on a sample of 624 pur-chasers, we show that people provide more relevant information on the company’s strategic positioning than media. In particular, the suppliers, competitors and other actors are very im-portant information sources. Following our findings, purchasers should adopt their activities in order to better anticipate their suppliers’ intention and the customer treatment that they can expect from their suppliers. Y1 - 2019 SP - 1 EP - 21 ER - TY - CHAP A1 - Vallée, Franz A1 - Schulz, Colin A1 - Robert, Julia T1 - Getting rid of fixed delivery areas: the implications of dynamic vehicle routing on a German parcel delivery company T2 - Proceedings of the World Conference on Transport Research (WCTR) 2019 Y1 - 2019 CY - Mumbai ER - TY - CHAP A1 - Sormani, Eva A1 - Chak, Choiwai Maggie T1 - Bringing Society Back: A playbook to re-connect science and community, presentation at University-Industry Interaction Conference 2019 (18-20.06.2019) Y1 - 2019 ER - TY - CHAP A1 - Sormani, Eva A1 - Baaken, Marieke A1 - Baaken, Thomas A1 - Stroila, Iulia T1 - Nudging in the Context of Fostering Student Entrepreneurship as Part of the Third Mission of Higher Education Institutions T2 - High Tech Small Firm Conference 2019, (27-28.05.2019) Y1 - 2019 ER - TY - CHAP A1 - Chak, Choiwai Maggie T1 - Interactive dynamics in regional and local health community-academic partnerships: Impact of group climate on partner engagement and collaborative success T2 - Presentation at CMOB Research Carrousel "Changing Health Care through Medical Leadership and Engagement" (25.01.2019), Enschede, The Netherlands Y1 - 2019 ER - TY - CHAP A1 - Feldmann, Carsten A1 - Delke, Vincent A1 - Wasserman, Michael E. T1 - Strategically Aligning Additive Manufacturing Supply Chains for Sustainability and Effectiveness T2 - International Federation of Automatic Control (IFAC): Intelligent Manufacturing Systems (IMS 2019) Proceedings N2 - This paper builds on a previously developed framework that integrated additive manufacturing, life-cycle analysis, and value creation (Feldmann & Kirsch, 2019) by exploring conditions related to the life-cycle approach that would require alignment among suppliers, additive manufacturing firms, and customers. This extension creates a bridge to aid implementation of taking a sustainability approach to additive manufacturing. In order to develop this extension, we distinguish between direct/indirect customers and internal/external customers and then create a matrix of incentives and cognitive frames that we believe will help companies interested in large-scale AM improve both the speed and the effectiveness of AM adoption. We provide an organizing framework that managers can use to create a supply chain that is aligned around closed-loop principles that will help speed adoption and move closer to sustainable goals that exist for AM technologies. These include reduced raw material use, reduced scrap and material overage, and reduced rework, and lower transportation costs. The goal is to attain often-conflicting goals of lower long-term costs and decreased environmental footprint. Using our extension, we believe we can provide a useful framework to help managers implementing advanced manufacturing technologies to achieve lower costs and greater environmental sustainability by creating a common supply chain framework around customized, on-demand products. KW - supply chain KW - additive manufacturing Y1 - 2019 SN - 2405-8963 SP - 260 EP - 264 CY - Oshawa, Ontario, Canada ER - TY - CHAP A1 - Bücker, Michael A1 - Szepannek, Gero A1 - Biecek, Przemyslaw A1 - Gosiewska, Alicja A1 - Staniak, Mateusz ED - Crook, Jonathan T1 - Transparency of Machine Learning Models in Credit Scoring T2 - CRC Conference XVI Papers N2 - A major requirement for Credit Scoring models is of course to provide a risk prediction that is as accurate as possible. In addition, regulators demand these models to be transparent and auditable. Thus, in Credit Scoring very simple Predictive Models such as Logistic Regression or Decision Trees are still widely used and the superior predictive power of modern Machine Learning algorithms cannot be fully leveraged. A lot of potential is therefore missed, leading to higher reserves or more credit defaults. This talk presents an overview of techniques that are able to make “black box” machine learning models transparent and demonstrate how they can be applied in Credit Scoring. We use the DALEX set of tools to compare a traditional scoring approach with state of the art Machine Learning models and asses both approaches in terms of interpretability and predictive power. Results show that a comparable degree of interpretability can be achieved while machine learning techniques keep their ability to improve predictive power. Y1 - 2019 UR - https://crc.business-school.ed.ac.uk/wp-content/uploads/sites/55/2019/07/C13-Transparency-of-Machine-Learning-Models-in-Credit-Scoring-B%C3%BCcker.pdf SP - 1 EP - 1 PB - Credit Research Center, University of Edinburgh CY - Edinburgh ER - TY - CHAP A1 - Fernströning, Sebastian A1 - Feldmann, Carsten ED - Padoano, Elio ED - Villmer, Franz-Josef T1 - Perception of Additive Manufacturing by SME: Empirical Survey via World Cafés T2 - 9th International Conference on Production Engineering and Management (PEM) 2019, Proceedings Y1 - 2019 SN - 978-3-946856-04-7 SP - 267 EP - 280 CY - Triest, Lemgo ER - TY - CHAP A1 - Tackenberg, Sven A1 - Jungkind, Wilfried A1 - Feldmann, Carsten A1 - Appelfeller, Wieland ED - Padoano, Elio ED - Villmer, Franz-Josef T1 - Digital Transformation of Companies: Experience Gained in the Implementation of an IoT Check T2 - 9th International Conference on Production Engineering and Management (PEM) 2019, Proceedings Y1 - 2019 SN - 978-3-946856-04-7 SP - 281 EP - 290 CY - Triest, Lemgo ER -