TY - JOUR A1 - Zeng, Li A1 - Kellner, Florian A1 - Lienland, Bernhard T1 - Rucksackprobleme in der Praxis - schnelle Entscheidungen schwer gemacht JF - HMD - Praxis der Wirtschaftsinformatik N2 - Unternehmen sind häufig mit Situationen konfrontiert, in denen schnell Entscheidungen bezüglich der Auswahl mehrerer Handlungsalternativen gefunden werden müssen. Mathematische Verfahren können hierbei unterstützen, z. B. für die Ermittlung einer ersten Diskussionsbasis. Verfügbare Softwarelösungen errechnen zwar häufig optimale Ergebnisse, zeigen jedoch Schwächen bei der praktischen Anwendbarkeit. So ist eine Einarbeitung in komplexe Optimierungssoftware für die teilweise sporadisch auftretenden Probleme in der Regel für Unternehmen nicht möglich, unter anderem auch unter Anbetracht der teilweise hohen Kosten der Standardsoftware und dem benötigten hohen Einarbeitungsaufwand. Gerade Problemstellungen in Fachbereichen, die nicht auf mathematische Problemlösung spezialisiert sind, münden daher regelmäßig in Ineffizienzen. Basierend auf den in der Literatur diskutierten Lösungsansätzen wurde ein praxisorientierter Ansatz zur Entscheidungsunterstützung für Rucksackprobleme bzw. 0–1 Probleme mithilfe von Genetischen Algorithmen (GA) entwickelt und technisch in Microsoft Excel® umgesetzt. Ein Praxistest bei einem chinesischen Textilunternehmen belegt erhöhte Effektivität und Effizienz. Die Software kann kostenfrei nach MIT Lizenz unter http://www.solvega.de/ heruntergeladen werden. Y1 - 2016 U6 - https://doi.org/10.1365/s40702-016-0207-z VL - 53 IS - 3 SP - 310 EP - 322 ER - TY - JOUR A1 - Kellner, Florian A1 - Otto, Andreas A1 - Lienland, Bernhard T1 - Cost Assignment Paradox: Indirect Tooling Costs and Production Orders JF - Advances in Management Accounting N2 - Purpose Tooling is a common component of an industrial product’s manufacture. Specific tooling is devised to serve the fabrication of a particular product, while generic tooling can be used in the manufacture of multiple products. In the latter case, companies are confronted with the problem of fairly allocating the indirect costs of the tooling. This article studies how to allocate costs of generic tooling to single production orders. Methodology Ten allocation methods (AMs) are described that are in principle suited to the distribution of generic tooling costs to production orders. Since the presented methods have for the most part been discussed in differing contexts, we apply them to a specified generic tooling problem for comparison. Evaluation of the various methods is based on 16 criteria. Reasoning is supported by a computational Monte Carlo simulation. Furthermore, we suggest using the Analytical Hierarchy Process (AHP) to elaborate one final proposition concerning the most preferable allocation scheme. Findings The article reports the single allocation rules’ performances for different allocation scenarios. The described characteristics refer to fairness, efficiency, and simplicity as well as to empty-core performance. Using AHP analysis allows for the aggregation of the rules’ criteria ratings. Thus, especially suitable allocation schemes for the problem at hand are identified. Practical implications An allocation is required for budgeting reasons and also for the definition of projects’ bottom-up sales prices. Selecting the “right” AM is important, as a suboptimal AM can result in unfair allocation vectors, which will act as incentives to stop using the common resource, potentially leading to higher total costs. Originality/value of the article Research on the comparison of AMs is typically performed for certain purposes, such as enterprise networks, horizontal cooperative purchasing scenarios, or municipal service units. This article will augment the research evaluating AMs by introducing a novel set of evaluation criteria and by providing an in-depth comparison of AMs suited for the allocation of generic tooling costs. KW - Tooling KW - Cost allocation KW - indirect cost KW - Overhead cost KW - Joint cost KW - Fairness criteria Y1 - 2014 U6 - https://doi.org/10.1108/S1474-787120140000023007 VL - 23 SP - 211 EP - 251 ER - TY - JOUR A1 - Lienland, Bernhard A1 - Kellner, Florian T1 - Projektauswahl mit der linearen Optimierung im Mittelstand JF - HMD - Praxis der Wirtschaftsinformatik N2 - Die Projektauswahl stellt eine Herausforderung insbesondere für mittelständische Industrieunternehmen dar. Abhängigkeiten verschiedener Alternativen und vorgegebene Investitionsbudgets führen bei Anwendung von in der Praxis standardmäßig eingesetzten Verfahren regelmäßig zu suboptimalen Projektkombinationen. In enger Abstimmung mit einem Automobilzulieferer wurde ein Ansatz zur Projektauswahl unter Berücksichtigung von Ressourcen und laufenden Projekten entwickelt sowie technisch umgesetzt. Implementierte Praxistests belegen Verbesserungen bei der Projektauswahl, aber auch bei der Budgeteinhaltung, der Fixkostenreduzierung sowie der Angebotspreisbestimmung. Y1 - 2012 U6 - https://doi.org/10.1007/BF03340699 VL - 49 IS - 3 SP - 52 EP - 62 ER - TY - JOUR A1 - Kellner, Florian A1 - Christina Goerk, Anna A1 - Lienland, Bernhard T1 - Mit CO₂-Kennzahlen die Ökobilanz verbessern JF - Controlling & Management Review Y1 - 2017 U6 - https://doi.org/10.1007/s12176-017-0118-z VL - 61 IS - 9 SP - 58 EP - 64 ER - TY - JOUR A1 - Lienland, Bernhard A1 - Zeng, Li A1 - Mayrock, Michael A1 - Kellner, Florian T1 - Operations Research im Controlling JF - Controlling: Zeitschrift für erfolgsorientierte Unternehmenssteuerung Y1 - 2017 U6 - https://doi.org/10.15358/0935-0381-2017-2 VL - 29 IS - 2 SP - 55 EP - 57 ER - TY - JOUR A1 - Kellner, Florian A1 - Lienland, Bernhard A1 - Utz, Sebastian T1 - A multi-criteria decision-making approach for assembling optimal powertrain technology portfolios in low GHG emission environments JF - Journal of Industrial Ecology N2 - Environmental regulations force car manufacturers to renew the powertrain technology portfolio offered to the customer to comply with greenhouse gas (GHG) emission targets. In turn, automotive companies face the task of identifying the “right” powertrain technology portfolio consisting of, for example, internal combustion engines and electric vehicles, because the selection of a particular powertrain technology portfolio affects different company targets simultaneously. What makes this decision even more challenging is that future market shares of the different technologies are uncertain. Our research presents a new decision-support approach for assembling optimal powertrain technology portfolios while making decision-makers aware of the trade-offs between the achievable profit, the achievable market share, the market share risk, and the GHG emissions generated by the selected vehicle fleet. The proposed approach combines “a posteriori” decision-making with multi-objective optimization. In an application case, we feed the outlooks of selected market studies into the proposed decision-support system. The result is a visualization and analysis of the current real-world decision-making problem faced by many automotive companies. Our findings indicate that for the proposed GHG restriction at work in 2030 in the European Union, no optimal powertrain technology portfolio with less than 35% of vehicles equipped with an electric motor exists. KW - automotive sector KW - decision-support system KW - industrial ecology KW - portfolio optimization KW - power-train technologies KW - technology selection Y1 - 2021 U6 - https://doi.org/10.1111/jiec.13148 VL - 25 IS - 6 SP - 1412 EP - 1429 ER - TY - CHAP A1 - Kellner, Florian A1 - Lienland, Bernhard A1 - Utz, Sebastian T1 - Optimal engine technology mix in a low carbon economy T2 - 2020 International Conference on Decision Aid Sciences and Application (DASA) N2 - Environmental regulations force automotive companies to modify the powertrain technology portfolio offered to the customer to comply with greenhouse gas (GHG) emission targets. Automotive companies, in turn, are faced with the decision of finding the right powertrain technology portfolio because the selection of a particular technology portfolio affects different company targets at the same time. What makes this decision even more interesting is the fact that future market shares of the different technologies are uncertain. With its numerous objectives, this challenge requires multi-criteria decision-making techniques to identify the optimal powertrain technology portfolio. The objective of this research is to present a new decision support approach for assembling optimal powertrain technology portfolios while making decision-makers aware of the trade-offs between the achievable market share, the market share risk, and the GHG emissions generated by the selected vehicle fleet. The proposed approach combines `a posteriori' decision-making, multi-objective optimization, and the Markowitz portfolio theory. In an application case, the outlooks of selected market studies are fed into the proposed decision support system. The result is a visualization and analysis of the current real-world decision-making problem faced by many automotive companies. Interesting findings of this research include that for the assumed GHG restrictions in place in 2030, there exists no optimal powertrain technology portfolio that is not composed of at least 20% of electric vehicles. Y1 - 2020 U6 - https://doi.org/10.1109/DASA51403.2020.9317094 SP - 95 EP - 98 ER - TY - BOOK A1 - Kellner, Florian A1 - Lienland, Bernhard A1 - Lukesch, Maximilian T1 - Produktionswirtschaft: Planung, Steuerung und Industrie 4.0 N2 - Dieses Buch bietet eine einsteigerfreundliche Einführung in die für industrielle Betriebe maßgebliche Aufgabe der Produktionswirtschaft. Im Zentrum steht dabei das operative Produktionsmanagement. Hierzu gehören die erfolgswirksame Bewirtschaftung der Produktionsfaktoren Mensch, Betriebsmittel und Material, der Einsatz von Information sowie die Planung und Steuerung der industriellen Produktion. Mithilfe zahlreicher Unternehmensbeispiele und Übungsaufgaben wird der Leser durch produktionswirtschaftliche Grundlagen sowie durch Ablauf und Inhalt zentraler Prozesse in der Industrie geleitet. Auch die aktuelle Diskussion um das Thema Industrie 4.0 und cyber-physische Produktionssysteme werden lesefreundlich und mit konkretem Anwendungsbezug präsentiert. Y1 - 2022 U6 - https://doi.org/10.1007/978-3-662-65803-1 PB - Springer Gabler CY - Berlin, Heidelberg ET - 3 ER - TY - JOUR A1 - Fuchs, Christoph A1 - Beck, Daniel A1 - Lienland, Bernhard A1 - Kellner, Florian T1 - The role of IT in automotive supplier supply chains JF - Journal of Enterprise Information Management N2 - Purpose The purpose of this paper is to explore the impact of information technology (IT) on supply chain performance in the automotive industry. Prior studies that analyzed the impact of IT on supply chain performance report results representing the situation of the “average industry.” This research focuses on the automotive industry because of its major importance in many national economies and due to the fact that automotive supply chains do not represent the supply chain of the average industry. Design/methodology/approach A research model is proposed to examine the relationships between IT capabilities, supply chain capabilities, and supplier performance. The model divides IT capabilities into functional and data capabilities, and supply chain capabilities into internal process excellence and information sharing. Data have been collected from 343 automotive first-tier suppliers. Structural equation modeling with partial least squares is used to analyze the data. Findings The results suggest that functional capabilities have the greatest impact on internal process excellence, which in turn enhances supplier performance. However, frequent and adequate information sharing also contributes significantly to supplier performance. Data capabilities enable supply chain capabilities through their positive impact on functional capabilities. Practical implications The findings will help managers to understand the effect of IT implementation on company performance and to decide whether to invest in the expansion of IT capacities. Originality/value This research reports the impact of IT on supply chain performance in one of the most important industries in many industrialized countries, and it provides a new perspective on evaluating the contribution of IT on firm performance. KW - Automotive industry; Information technology; Supply chain management Y1 - 2018 U6 - https://doi.org/10.1108/JEIM-03-2017-0038 VL - 31 IS - 1 SP - 64 EP - 88 ER - TY - JOUR A1 - Kellner, Florian A1 - Lienland, Bernhard A1 - Utz, Sebastian T1 - An a posteriori decision support methodology for solving the multi-criteria supplier selection problem JF - European Journal of Operational Research N2 - This research presents a novel, state-of-the-art methodology for solving a multi-criteria supplier selection problem considering risk and sustainability. It combines multi-objective optimization with the analytic network process to take into account sustainability requirements of a supplier portfolio configuration. To integrate ‘risk’ into the supplier selection problem, we develop a multi-objective optimization model based on the investment portfolio theory introduced by Markowitz. The proposed model is a non-standard portfolio selection problem with four objectives: (1) minimizing the purchasing costs, (2) selecting the supplier portfolio with the highest logistics service, (3) minimizing the supply risk, and (4) ordering as much as possible from those suppliers with outstanding sustainability performance. The optimization model, which has three linear and one quadratic objective function, is solved by an algorithm that analytically computes a set of efficient solutions and provides graphical decision support through a visualization of the complete and exactly-computed Pareto front (a posteriori approach). The possibility of computing all Pareto-optimal supplier portfolios is beneficial for decision makers as they can compare all optimal solutions at once, identify the trade-offs between the criteria, and study how the different objectives of supplier portfolio configuration may be balanced to finally choose the composition that satisfies the purchasing company's strategy best. The approach has been applied to a real-world supplier portfolio configuration case to demonstrate its applicability and to analyze how the consideration of sustainability requirements may affect the traditional supplier selection and purchasing goals in a real-life setting. KW - Supply chain management; Supplier selection; Sustainability; Logistics; Decision support systems Y1 - 2019 U6 - https://doi.org/10.1016/j.ejor.2018.06.044 VL - 272 IS - 2 SP - 505 EP - 522 ER -