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2018

Stakeholder influences and risks in sustainable supply chain management: a comparison of qualitative and quantitative studies

Rebs, T., Brandenburg, M., Seuring, S., & Stohler, M. (2018). Stakeholder influences and risks in sustainable supply chain management: a comparison of qualitative and quantitative studies, 11(2), 197–237,. http://doi.org/10.1007/s40685-017-0056-9

Abstract

Stakeholder influences on sustainable supply chain management (SSCM) are of increasing interest for researchers to take into account economic, environmental, and social risks. While extant literature on stakeholder influences or risks in SSCM concentrates on selected issues, a comprehensive review of both stakeholder and risk constructs is missing. Hence, this paper examines stakeholder influences and risks in SSCM, as addressed by conceptual frameworks, empirical studies, and formal models to shed light on the trends and gaps in qualitative and quantitative SSCM research. Based on a content analysis of systematically selected journal publications, the commonalities and differences between the research designs are identified. The findings suggest that the integration of economic risks prevails over the consideration of environmental and social risks. Qualitative studies frequently focus on customers or multiple stakeholders that trigger SSCM and relate to supply, demand, and particularly reputational risks. In contrast, quantitative models rather concentrate on formalizing governmental triggers and operational risks. Thus, mutual stimuli between conceptual, empirical, and model-based SSCM research and their implications for future research directions are derived.
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Brandenburg, Marcus
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2018

Journal Article

Tobias Rebs

Marcus Brandenburg

Stefan Seuring

Margarita Stohler
Supply network configuration—A benchmarking problem

Brandenburg, M. (2018). Supply network configuration—A benchmarking problem. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28, 033121. http://doi.org/10.1063/1.5012085
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2018

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Marcus Brandenburg
Applying Sustainable Supply Chain Management Frameworks to Two German Case Studies

Oelze, N., Brandenburg, M., Jansen, C., & Warasthe, R. (2018). Applying Sustainable Supply Chain Management Frameworks to Two German Case Studies. IFAC-PapersOnLine, 51, 293–296. http://doi.org/10.1016/j.ifacol.2018.11.304

Abstract

Sustainability has become a highly relevant factor for companies, economies and societies. As a consequence, the consideration of environmental and social factors is crucial to manage supply chains sustainably. The study at hand analyses and compares conceptual frameworks and empirical studies on sustainable supply chain management. The gained insights are transferred to case studies of two German firms.
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Brandenburg, Marcus
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2018

Journal Article

Nelly Oelze

Marcus Brandenburg

Christoph Jansen

Ronak Warasthe

Sustainability

Supply chain management

Conceptual framework

practices & policies

case study

Automotive industry

transportation sector
Design and Implementation of a Measurement and Management System for Operational and Supply Chain Performance

Brandenburg, M. (2018). Design and Implementation of a Measurement and Management System for Operational and Supply Chain Performance. IEEE Engineering Management Review, 46, 117–123. http://doi.org/10.1109/EMR.2018.2848968
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2018

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Marcus Brandenburg
Sustainable aggregate production planning in the chemical process industry - A benchmark problem and dataset

Brandenburg, M., & Hahn, G. J. (2018). Sustainable aggregate production planning in the chemical process industry - A benchmark problem and dataset. Data in Brief, 18, 961–967. http://doi.org/10.1016/j.dib.2018.03.064

Abstract

Process industries typically involve complex manufacturing operations and thus require adequate decision support for aggregate production planning (APP). The need for powerful and efficient approaches to solve complex APP problems persists. Problem-specific solution approaches are advantageous compared to standardized approaches that are designed to provide basic decision support for a broad range of planning problems but inadequate to optimize under consideration of specific settings. This in turn calls for methods to compare different approaches regarding their computational performance and solution quality. In this paper, we present a benchmarking problem for APP in the chemical process industry. The presented problem focuses on (i) sustainable operations planning involving multiple alternative production modes/routings with specific production-related carbon emission and the social dimension of varying operating rates and (ii) integrated campaign planning with production mix/volume on the operational level. The mutual trade-offs between economic, environmental and social factors can be considered as externalized factors (production-related carbon emission and overtime working hours) as well as internalized ones (resulting costs). We provide data for all problem parameters in addition to a detailed verbal problem statement. We refer to Hahn and Brandenburg [1] for a first numerical analysis based on and for future research perspectives arising from this benchmarking problem.
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Marcus Brandenburg

Gerd Hahn
A sustainable aggregate production planning model for the chemical process industry

Hahn, G. J., & Brandenburg, M. (2018). A sustainable aggregate production planning model for the chemical process industry. Computers & Operations Research, 94, 154–168. http://doi.org/10.1016/j.cor.2017.12.011

Abstract

Process industries typically involve complex manufacturing operations and thus require adequate decision support for aggregate production planning (APP). In this paper, we focus on two relevant features of APP in process industry operations: (i) sustainable operations planning involving multiple alternative production modes/routings with specific production-related carbon emission and the social dimension of varying operating rates, (ii) integrated campaign planning with the operational level in order to anticipate production mix/volume/routing decisions on campaign lead times and WIP inventories as well as the impact of variability originating from a stochastic manufacturing environment. We focus on the issue of multi-level chemical production processes and highlight the mutual trade-offs along the triple bottom line concerning economic, environmental and social factors. To this end, production-related carbon emission and overtime working hours are considered as externalized factors as well as internalized ones in terms of resulting costs. A hierarchical decision support tool is presented that combines a deterministic linear programming model and an aggregate stochastic queuing network model. The approach is exemplified at a case example from the chemical industry to illustrate managerial insights and methodological benefits of our approach.
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2018

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Gerd Hahn

Marcus Brandenburg

Sustainable production

Aggregate planning

Decision support system

Queuing networks

Chemical process industry

2017

A hybrid approach to configure eco-efficient supply chains under consideration of performance and risk aspects

Brandenburg, M. (2017). A hybrid approach to configure eco-efficient supply chains under consideration of performance and risk aspects. Omega, 70, 58–76. http://doi.org/10.1016/j.omega.2016.09.002

Abstract

Formal models that support multi-criteria decision making represent a strongly growing area in sustainable supply chain management research. However, uncertainties and risks are seldom considered in quantitative models for green supply chain (SC) design. The paper at hand suggests a hybrid approach to configure an eco-efficient SC for a new product under consideration of economic and environmental risks. Discrete-event simulation is applied to assess the financial, operational and environmental performance of different SC configuration options while the value-at-risk concept is adapted to evaluate related SC risks. The analytic hierarchy process is employed to solve the resulting multi-criteria decision problem of choosing the best option. The approach is illustrated at a case example of a fast moving consumer goods manufacturer.
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2017

Journal Article

Marcus Brandenburg

Supply chain management

Supply chain risks

Carbon emissions

Discrete-event simulation

Analytic hierarchy process

Fast moving consumer goods

2016

Supply chain efficiency, value creation and the economic crisis – An empirical assessment of the European automotive industry 2002–2010

Brandenburg, M. (2016). Supply chain efficiency, value creation and the economic crisis – An empirical assessment of the European automotive industry 2002–2010. International Journal of Production Economics, 171, 321–335. http://doi.org/10.1016/j.ijpe.2015.07.039

Abstract

This paper seeks to evaluate the development of supply chain (SC) efficiency and the resulting impacts on company value. In a secondary data analysis of the European automotive industry, the trends of cost efficiency and working capital performance in the years 2002–2010 and the resulting value impacts are assessed. It is detected that many companies failed to manage cost and working capital in a balanced and value-adding way, which resulted in considerable value losses. The economic crisis is identified as an amplifier, but not the major cause of these negative trends. Originality and value of the paper arise from the scarcity of financial analyses that focus on the car sector or that measure and compare several factors of SC efficiency or value creation.
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2016

Journal Article

Marcus Brandenburg

Supply chain performance

Company value

Economic crisis

Secondary data analysis
Supply Chain Controlling für soziale Aspekte in globalen Wertschöpfungsketten

Seuring, S., Yawar, S. A., & Brandenburg, M. (2016). Supply Chain Controlling für soziale Aspekte in globalen Wertschöpfungsketten. Controlling, 28(7), 397–402,. http://doi.org/10.15358/0935-0381-2016-7-397

Abstract

Fragen der sozialen Nachhaltigkeit verändern die Informationsbedarfe im Supply Chain Controlling. Unternehmen implementieren eine Kommunikations-, Compliance oder Lieferantenentwicklungsstrategie, um damit den Anforderungen interner und externer Stakeholder gerecht zu werden. Entsprechend ist das Controlling in Strategieumsetzung und Informationsflüssen auszugestalten. Supply chain controlling system can be described by: strategy implementation, target setting and performance measurement, rewards and incentives, information flows; additionally a stakeholder perspective is introduced. Three strategies for managing social issues in supply chains are introduced: communication, compliance and supplier development. These two approaches are combined to illustrate the measure taken in the supply chain from a controlling perspective.
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Fachbereich

Fachbereich 4: Wirtschaft
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2016

Journal Article

Stefan Seuring

Sadaat Yawar

Marcus Brandenburg

2015

Sustainable supply chain management: a modeling perspective

Brandenburg, M., & Rebs, T. (2015). Sustainable supply chain management: a modeling perspective, 229(1), 213–252,. http://doi.org/10.1007/s10479-015-1853-1

Abstract

Nowadays, the integration of sustainability into supply chain management (SCM) is a key issue for ensuring corporate competitiveness in face of dynamic ecological and social environments. This paper reviews 185 journal publications of the last 20 years that formalize issues related to sustainable supply chain management (SSCM) in quantitative models. In a content analysis, modeling and SCM characteristics as well as sustainability and SSCM constructs are elaborated. The models are assessed numerically by counting frequencies of occurrence and by clustering the paper sample according to selected characteristics. The findings indicate that SSCM models predominantly focus on deterministic approaches and the integration of environmental aspects of sustainability while neglecting stochastic modeling techniques and the consideration of social factors. By now, comprehensive modeling approaches are most often employed on intra-organizational levels whereas broader application areas are assessed by less complex models. The integration of pressures and incentives of external stakeholders or the formalization of sustainable supplier management and sustainability risks are identified as future research perspectives. Furthermore, the interrelationships between the triple bottom line dimensions are to be scrutinized in greater detail in order to avoid focused optimization of selected sustainability criteria. Seven modeling guidelines are derived from the reviewed literature to facilitate future model-based SSCM research.
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Marcus Brandenburg

Tobias Rebs

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