@article{KellnerLienlandUtz, author = {Kellner, Florian and Lienland, Bernhard and Utz, Sebastian}, title = {A multi-criteria decision-making approach for assembling optimal powertrain technology portfolios in low GHG emission environments}, series = {Journal of Industrial Ecology}, volume = {25}, journal = {Journal of Industrial Ecology}, number = {6}, publisher = {Wiley}, doi = {10.1111/jiec.13148}, pages = {1412 -- 1429}, abstract = {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.}, language = {en} } @article{Lienland, author = {Lienland, Bernhard}, title = {The Implementation of a Cash-Flow-Based Mathematical R\&D Project Selection Model}, series = {International Journal of Information Technology Project Management (IJITPM)}, volume = {7}, journal = {International Journal of Information Technology Project Management (IJITPM)}, number = {3}, publisher = {IGI Global}, doi = {10.4018/IJITPM.2016070102}, pages = {22}, abstract = {Customer project selection is a challenge for many industrial companies. An inappropriate project selection approach can lead to constraint violations, high fixed costs, and suboptimal portfolios. To overcome these problems a cash-flow-based linear optimization model was developed in partnership with a tier-1 automotive supplier. Implementation barriers had been verified through a case study conducted at two organizational hierarchies. Results suggest that an application at the operating levels is possible. At higher levels, though, product and firm complexity require major implementation efforts. This article serves theorists as well as practitioners in multiple regards. First, an overview of existing project selection methods and their application in practice is provided. Additionally, the supplier's current appraisal process is depicted. Second, operations research implementation barriers are identified and validated for the adoption of the proposed mathematical project selection approach. Third, a guideline including procedures to overcome experienced difficulties is presented.}, language = {en} } @unpublished{KellnerLienlandUtz, author = {Kellner, Florian and Lienland, Bernhard and Utz, Sebastian}, title = {An a Posteriori Multi-Objective Supplier Portfolio Selection Approach Under Risk and Sustainability Considerations}, series = {SSRN Electronic Journal}, journal = {SSRN Electronic Journal}, doi = {10.2139/ssrn.2901390}, pages = {39}, abstract = {This research presents a novel, state-of-the-art methodology for solving the multi-criteria supplier selection problem under risk and sustainability considerations. The approach combines multi-objective optimization with the analytic network process to meet the requirements for supplier portfolio configuration with sustainability considerations. To integrate the aspect 'risk' into the supplier selection problem, this research develops 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: to minimize the purchasing costs, to select the supplier portfolio with the highest logistics service, to minimize the supply risk, and to order 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 which analytically computes a set of efficient solutions and provides graphical decision support by 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 aspects of supplier portfolio configuration may be balanced to finally choose the composition that satisfies the purchasing company's strategy at 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.}, language = {en} } @article{FuchsBeckLienlandetal., author = {Fuchs, Christoph and Beck, Daniel and Lienland, Bernhard and Kellner, Florian}, title = {The role of IT in automotive supplier supply chains}, series = {Journal of Enterprise Information Management}, volume = {31}, journal = {Journal of Enterprise Information Management}, number = {1}, publisher = {emerald insight}, doi = {10.1108/JEIM-03-2017-0038}, pages = {64 -- 88}, abstract = {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.}, language = {en} } @article{LienlandBaumgartnerKnubben, author = {Lienland, Bernhard and Baumgartner, Alexander and Knubben, Evelyn}, title = {The undervaluation of corporate reputation as a supplier selection factor}, series = {Journal of Purchasing and Supply Management}, volume = {19}, journal = {Journal of Purchasing and Supply Management}, number = {2}, publisher = {Elsevier}, issn = {1478-4092}, doi = {10.1016/j.pursup.2013.04.001}, pages = {84 -- 97}, abstract = {Prior research studies on supplier selection factors assess vendor reputation as a low ranked criterion. Reputation in these articles, however, only refers to the position in the industry, without considering the role of the final customer. Our results from a survey with 565 individuals suggest that the end user as a stakeholder should be also considered when analyzing a vendor's prestige. We demonstrate that a supplier's standing has negative as well as positive reputational effects on the buyer. Depending on the relevance of the purchased good as well as the reputation of the supplier and the buyer, low/high-ranked ingredients significantly decrease/increase the final customer's perception of the buyer.}, language = {en} } @article{LienlandZeng, author = {Lienland, Bernhard and Zeng, Li}, title = {A Review and Comparison of Genetic Algorithms for the 0-1 Multidimensional Knapsack Problem}, series = {International Journal of Operations Research and Information Systems (IJORIS)}, volume = {6}, journal = {International Journal of Operations Research and Information Systems (IJORIS)}, number = {2}, publisher = {IGI Global}, issn = {1947-9328}, doi = {10.4018/ijoris.2015040102}, pages = {11}, abstract = {The 0-1 multidimensional knapsack problem (MKP) is a well-known combinatorial optimization problem with several real-life applications, for example, in project selection. Genetic algorithms (GA) are effective heuristics for solving the 0-1 MKP. Multiple individual GAs with specific characteristics have been proposed in literature. However, so far, these approaches have only been partially compared in multiple studies with unequal conditions. Therefore, to identify the "best" genetic algorithm, this article reviews and compares 11 existing GAs. The authors' tests provide detailed information on the GAs themselves as well as their performance. The authors validated fitness values and required computation times in varying problem types and environments. Results demonstrate the superiority of one GA.}, language = {en} } @incollection{KellnerLienlandUtz, author = {Kellner, Florian and Lienland, Bernhard and Utz, Sebastian}, title = {Optimal engine technology mix in a low carbon economy}, series = {2020 International Conference on Decision Aid Sciences and Application (DASA), 08-09 November 2020, Sakheer, Bahrain}, booktitle = {2020 International Conference on Decision Aid Sciences and Application (DASA), 08-09 November 2020, Sakheer, Bahrain}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-7281-9677-0}, doi = {10.1109/DASA51403.2020.9317094}, pages = {95 -- 98}, abstract = {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.}, language = {en} } @incollection{KellnerLienlandLukesch, author = {Kellner, Florian and Lienland, Bernhard and Lukesch, Maximilian}, title = {Produktionsfaktoren}, series = {Produktionswirtschaft : Planung, Steuerung und Industrie 4.0}, booktitle = {Produktionswirtschaft : Planung, Steuerung und Industrie 4.0}, publisher = {Springer Gabler}, address = {Berlin; Heidelberg}, isbn = {978-3-662-65802-4}, doi = {10.1007/978-3-662-65803-1_2}, pages = {31 -- 158}, abstract = {Kap. 2 bespricht die Produktionsfaktoren Mensch, Betriebsmittel und Material sowie den Faktor „Information" als Grundlage der betrieblichen Leitung. Der Abschnitt "Produktionsfaktor Mensch" beschreibt u. a. Maßnahmen zur Erh{\"o}hung der menschlichen Arbeitsleistung durch eine entsprechende Arbeits- und Lohngestaltung. Beim Produktionsfaktor Betriebsmittel werden Organisationstypen der Fertigung diskutiert und Detailprobleme vorgestellt, die sich durch die Wahl eines bestimmten Organisationstyps ergeben. Der Abschnitt Produktionsfaktor Material zeigt, welche Profitabilit{\"a}tswirkung durch eine Materialstandardisierung erreicht werden kann und wie sich Materialien klassifizieren lassen, um geeignete Dispositionsstrategien abzuleiten. Danach wird auf die von der betrieblichen Leitung genutzten Informationen und Informationssysteme eingegangen. Dabei wird zun{\"a}chst eine typische industrielle IT-Systemlandschaft mit Fokus auf Supply-Chain-Management-Systeme vorgestellt und abschließend die Informationstr{\"a}ger „St{\"u}ckliste" und „Arbeitsplan" besprochen.}, language = {de} } @article{KellnerLienlandUtz, author = {Kellner, Florian and Lienland, Bernhard and Utz, Sebastian}, title = {An a posteriori decision support methodology for solving the multi-criteria supplier selection problem}, series = {European Journal of Operational Research}, volume = {272}, journal = {European Journal of Operational Research}, number = {2}, publisher = {Springer}, doi = {10.1016/j.ejor.2018.06.044}, pages = {505 -- 522}, abstract = {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.}, language = {en} } @book{Lienland, author = {Lienland, Bernhard}, title = {Project Portfolio Selection in the Automotive Supplier Industry}, address = {Regensburg}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:355-epub-296849}, language = {en} } @book{KellnerLienlandLukesch, author = {Kellner, Florian and Lienland, Bernhard and Lukesch, Maximilian}, title = {Produktionswirtschaft : Planung, Steuerung und Industrie 4.0}, edition = {2., aktualisierte und erweiterte Auflage}, publisher = {Springer Gabler}, address = {Heidelberg}, doi = {10.1007/978-3-662-61446-4}, pages = {XXI, 399}, abstract = {Dieses Buch gibt einen umfassenden {\"U}berblick {\"u}ber wichtige Bereiche der Produktionswirtschaft. Der Schwerpunkt liegt auf dem operativen Produktionsmanagement. Es zeigt den Einsatz der Produktionsfaktoren Mensch, Betriebsmittel und Material, erkl{\"a}rt die Bedeutung von Informationen f{\"u}r die betriebliche F{\"u}hrung und bietet anhand zahlreicher Beispiele einen breiten Einblick in die Planung und Steuerung industrieller Produktion. Ausf{\"u}hrlich werden neben produktionswirtschaftlichen Grundlagen der Ablauf und Inhalt von Planungs- und Steuerungsprozessen erl{\"a}utert. Auch das aktuelle Thema Industrie 4.0 sowie cyber-physische Systeme werden dargestellt. In der 2. Auflage wurden umfangreiche {\"U}berarbeitungen hinsichtlich Sprache und Aufbau vorgenommen sowie anschauliche Beispielaufgaben, neue Unternehmensbeispiele und hilfreiche Hintergrunderkl{\"a}rungen erg{\"a}nzt.}, language = {de} } @book{KellnerLienlandLukesch, author = {Kellner, Florian and Lienland, Bernhard and Lukesch, Maximilian}, title = {Produktionswirtschaft : Planung, Steuerung und Industrie 4.0}, edition = {3., aktualisierte und erweiterte Auflage}, publisher = {Springer Gabler}, address = {Berlin}, isbn = {978-3-662-65802-4}, doi = {10.1007/978-3-662-65803-1}, pages = {XXI, 399}, abstract = {Dieses Buch bietet eine einsteigerfreundliche Einf{\"u}hrung in die f{\"u}r industrielle Betriebe maßgebliche Aufgabe der Produktionswirtschaft. Im Zentrum steht dabei das operative Produktionsmanagement. Hierzu geh{\"o}ren 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 {\"U}bungsaufgaben 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 pr{\"a}sentiert.}, language = {de} } @book{KellnerLienlandLukesch, author = {Kellner, Florian and Lienland, Bernhard and Lukesch, Maximilian}, title = {Produktionswirtschaft : Planung, Steuerung und Industrie 4.0}, publisher = {Springer}, address = {Berlin, Heidelberg}, isbn = {9783662543412}, doi = {10.1007/978-3-662-54341-2}, pages = {XVII, 331}, abstract = {Dieses Buch gibt einen umfassenden {\"U}berblick {\"u}ber wichtige Bereiche der Produktionswirtschaft. Der Schwerpunkt liegt auf dem operativen Produktionsmanagement. Es zeigt den Einsatz der Produktionsfaktoren Mensch, Betriebsmittel, Material und Information und bietet anhand zahlreicher Beispiele einen ausf{\"u}hrlichen Einblick in die Planung und Steuerung industrieller Produktion. Ausf{\"u}hrlich werden neben produktionswirtschaftlichen Grundlagen der Ablauf und Inhalt von Planungs- und Steuerungsprozessen erl{\"a}utert. Auch das aktuelle Thema Industrie 4.0 sowie cyber-physische Systeme werden dargestellt.}, language = {de} } @incollection{KellnerOttoLienland, author = {Kellner, Florian and Otto, Andreas and Lienland, Bernhard}, title = {Cost Assignment Paradox: Indirect Tooling Costs and Production Orders}, series = {Advances in Management Accounting}, volume = {23}, booktitle = {Advances in Management Accounting}, publisher = {Emerald}, doi = {10.1108/S1474-787120140000023007}, pages = {211 -- 251}, abstract = {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.}, language = {en} } @article{LienlandZengMayrocketal., author = {Lienland, Bernhard and Zeng, Li and Mayrock, Michael and Kellner, Florian}, title = {Operations Research im Controlling}, series = {Controlling : Zeitschrift f{\"u}r erfolgsorientierte Unternehmenssteuerung}, volume = {29}, journal = {Controlling : Zeitschrift f{\"u}r erfolgsorientierte Unternehmenssteuerung}, number = {2}, publisher = {C.H. Beck ; Vahlen}, doi = {10.15358/0935-0381-2017-2-55}, pages = {55 -- 57}, language = {de} } @article{KellnerGoerkLienland, author = {Kellner, Florian and Goerk, Anna Christina and Lienland, Bernhard}, title = {Mit CO2-Kennzahlen die {\"O}kobilanz verbessern}, series = {Controlling \& Management Review}, volume = {61}, journal = {Controlling \& Management Review}, number = {9}, publisher = {Springer}, doi = {10.1007/s12176-017-0118-z}, pages = {58 -- 64}, abstract = {CO-Emissionen sind ein wichtiger Indikator f{\"u}r die Beurteilung der {\"o}kologischen Nachhaltigkeit von Unternehmen. In der Praxis sind sie jedoch schwierig zu bestimmen. Insbesondere f{\"u}r Logistik-und Transportaktivit{\"a}ten, auf die ein Großteil der Emissionen entf{\"a}llt, sind zuverl{\"a}ssige Methoden zur Ermittlung und Reduktion des Schadstoffausstoßes erforderlich.}, language = {de} } @article{ZengKellnerLienland, author = {Zeng, Li and Kellner, Florian and Lienland, Bernhard}, title = {Rucksackprobleme in der Praxis - schnelle Entscheidungen schwer gemacht}, series = {HMD Praxis der Wirtschaftsinformatik}, volume = {53}, journal = {HMD Praxis der Wirtschaftsinformatik}, publisher = {Springer}, address = {Wiesbaden}, doi = {10.1365/s40702-016-0207-z}, pages = {310 -- 322}, abstract = {Unternehmen sind h{\"a}ufig mit Situationen konfrontiert, in denen schnell Entscheidungen bez{\"u}glich der Auswahl mehrerer Handlungsalternativen gefunden werden m{\"u}ssen. Mathematische Verfahren k{\"o}nnen hierbei unterst{\"u}tzen, z. B. f{\"u}r die Ermittlung einer ersten Diskussionsbasis. Verf{\"u}gbare Softwarel{\"o}sungen errechnen zwar h{\"a}ufig optimale Ergebnisse, zeigen jedoch Schw{\"a}chen bei der praktischen Anwendbarkeit. So ist eine Einarbeitung in komplexe Optimierungssoftware f{\"u}r die teilweise sporadisch auftretenden Probleme in der Regel f{\"u}r Unternehmen nicht m{\"o}glich, unter anderem auch unter Anbetracht der teilweise hohen Kosten der Standardsoftware und dem ben{\"o}tigten hohen Einarbeitungsaufwand. Gerade Problemstellungen in Fachbereichen, die nicht auf mathematische Probleml{\"o}sung spezialisiert sind, m{\"u}nden daher regelm{\"a}ßig in Ineffizienzen. Basierend auf den in der Literatur diskutierten L{\"o}sungsans{\"a}tzen wurde ein praxisorientierter Ansatz zur Entscheidungsunterst{\"u}tzung f{\"u}r Rucksackprobleme bzw. 0-1 Probleme mithilfe von Genetischen Algorithmen (GA) entwickelt und technisch in Microsoft Excel® umgesetzt. Ein Praxistest bei einem chinesischen Textilunternehmen belegt erh{\"o}hte Effektivit{\"a}t und Effizienz. Die Software kann kostenfrei nach MIT Lizenz unter http://www.solvega.de/ heruntergeladen werden.}, language = {de} } @article{LienlandKellner, author = {Lienland, Bernhard and Kellner, Florian}, title = {Projektauswahl mit der linearen Optimierung im Mittelstand}, series = {HMD Praxis der Wirtschaftsinformatik}, volume = {49}, journal = {HMD Praxis der Wirtschaftsinformatik}, publisher = {Springer}, doi = {10.1007/BF03340699}, pages = {52 -- 62}, abstract = {Die Projektauswahl stellt eine Herausforderung insbesondere f{\"u}r mittelst{\"a}ndische Industrieunternehmen dar. Abh{\"a}ngigkeiten verschiedener Alternativen und vorgegebene Investitionsbudgets f{\"u}hren bei Anwendung von in der Praxis standardm{\"a}ßig eingesetzten Verfahren regelm{\"a}ßig zu suboptimalen Projektkombinationen. In enger Abstimmung mit einem Automobilzulieferer wurde ein Ansatz zur Projektauswahl unter Ber{\"u}cksichtigung 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.}, language = {de} } @article{KanitzykSchillingKellneretal., author = {Kanitzyk, Justin and Schilling, Robert and Kellner, Florian and Lienland, Bernhard}, title = {Optimierung der Unternehmenssteuerung}, series = {CONTROLLER Magazin}, volume = {2025}, journal = {CONTROLLER Magazin}, number = {2}, publisher = {Haufe}, issn = {1616-0495}, pages = {84 -- 88}, abstract = {Die Unternehmenssteuerung wird in der Praxis nach wie vor von Finanzkennzahlen dominiert, obwohl diese nur einen spezifischen Ausschnitt der Vorg{\"a}nge einer Organisation widerspiegeln. F{\"u}r einen umfassenden Steuerungsansatz, der Zukunftsf{\"a}higkeit und Rationalit{\"a}t f{\"o}rdert, ist eine gezielte Beeinflussung von Performancetreibern notwendig. Diese Performancetreiber haben oftmals einen nicht-finanziellen Charakter. Eine verst{\"a}rkte Einbindung nicht-finanzieller Kennzahlen in die Unternehmenssteuerung ist erforderlich.}, language = {de} } @article{SchifferlStojanovicBlabKellneretal., author = {Schifferl, Ludwig and Stojanovic-Blab, Maja and Kellner, Florian and Lienland, Bernhard}, title = {Performance Measurement in Beratungsunternehmen}, series = {CONTROLLER Magazin}, journal = {CONTROLLER Magazin}, number = {1}, publisher = {Verlag f{\"u}r ControllingWissen AG}, pages = {20 -- 25}, abstract = {Der vorliegende Beitrag untersucht die Implementierung des Performance Measurements in der wissensintensiven Dienstleistungsbranche am Beispiel einer KMU-Unternehmensberatung. Dabei werden zentrale Herausforderungen sowie praxisorientierte Handlungsempfehlungen herausgearbeitet.}, language = {de} }