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The assessment of greenhouse gas (GHG) emissions of supply chain activities is performed to create transparency across the supply chain and to identify emission-cutting opportunities. Literature provides several generic and case study approaches to estimate GHG emissions. But research often focuses on products. This paper sheds light on how the greenhouse performance of a fast-moving consumer goods (FMCG) distribution network depends on several (FMCG specific) variables to set up a “CO2 network footprint”. Within a quantitative computational study, the distribution network footprint of an existing FMCG manufacturer is analyzed. Three options being fundamentally able to reduce total GHG emissions are identified: number of distribution centers, performance of the engaged logistics service provider and shipment structure. First, transportation processes for the investigated FMCG manufacturer are analyzed to derive GHG emissions caused by different distribution shipments. Second, initial data are manipulated to simulate variable changes, that is, different logistics structures. Third, results are reported and analyzed to show up how different changes in logistics structures may reduce GHG, without technological propulsion or use of regenerative energy.
Distribution network design is about recommending long-term network structures in an environment where logistic variables like transportation costs or retailer order sizes dynamically change over time. The challenge for management is to recommend an optimal network configuration that will allow for longer term optimal results despite of environmental turbulences. This paper studies the robustness of cost-optimized FMCG (fast-moving consumer goods) distribution networks. It aims at observing the impact of changing variables/conditions on optimized logistic structures in terms of the optimal number and geographical locations of existing distribution centers. Five variables have been identified as relevant to the network structure. A case study approach is applied to study the robustness of an existing, typical, and optimized FMCG network. First, distribution network data of a German manufacturer of FMCG are recorded and analyzed. A quantitative model is set up to reflect the actual cost structure. Second, a cost optimal network configuration is determined as a benchmark for further analysis. Third, the variables investigated are altered to represent changes, both isolated (ceteris paribus) and in combination (scenario analysis). Each one of the variables investigated proves to be fundamentally able to suggest a change of the optimal network structure. However, the scenario analysis indicates that the expected changes will by and large compensate each other, leaving the network in near optimal condition over an extended period of time.
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.
In this paper, we propose a combined methodology for the selection of distribution centres (DCs) by integrating and balancing economic, environmental and social sustainability aspects. The analytic network process (ANP) permits to systematically evaluate possible DCs on the basis of a situation-specific decision structure. A systematic development of the decision networks, which is one of the core challenges using the ANP, is supported by the process analysis method which we extend for that purpose. The validity and soundness of the proposed framework are demonstrated by means of a case study. The case study results reveal that omitting aspects of sustainability can lead to unfortunate results.
There are growing concerns in the food industry about how supply chains can be managed in a more sustainable way. When distribution activities are outsourced to a logistics service provider (LSP), shippers need to evaluate the LSPs they may (potentially) engage in order to ensure that supply chain sustainability goals are met. In this paper, we present a methodology for LSP evaluation and focus on the ecological dimension of sustainability. We examine how the network carbon footprint of a real-world distribution system is affected by the LSP network that is chosen to forward goods from production facilities to customers. To do this, we analyze the shipment data of an existing Fast Moving Consumer Goods (FMCG) manufacturer. A quantitative distribution network model is set up to study the network carbon footprint of 125 scenarios. Real-world shipments are forwarded via five generic, idealized types of LSP networks. In total, 625 network carbon footprints, specified by three distribution logistics variables and the structure of the LSP network, have been calculated. The results show that LSP structures practicing a geographically decentralized consolidation of shipments are most efficient in reducing of greenhouse gas (GHG) emissions. Furthermore, the effects of changing the manufacturer's and the LSP's strategies for deciding on the tonnage to be forwarded via the LSP network or moved by direct transports are quantified. Finally, we estimate the GHG effect of improving the capacity utilization of the vehicles that move the products.
This research studies effects that the average increase in travel times due to road traffic congestion has on characteristics of an existing distribution network. It presents the most detailed estimate of ‘on-the-road’ effects on distribution network characteristics up to now, from the network modelling perspective and from the processed data point of view. A concrete network model allowing for the representation of all relevant transportation flows is presented. The processed traffic information relies on navigation service data. The use of such data allows the requirements that arise for the traffic analysis of a whole distribution network to be met. It is shown that this data source may considerably contribute in forthcoming research. The effects of traffic congestion are quantified to get insights into the extent to which regular traffic congestion affects distribution network characteristics and to understand the mitigating effect when the number of distribution centres is increased.
Purpose
The purpose of this paper is to propose a comprehensive methodology and a problem-specific model for the configuration of the optimal strategic supplier portfolio in terms of traditional, performance-related objectives and sustainability targets.
Design/methodology/approach
To bridge the research gap, i.e., to align strategic supplier portfolio selection with corporate sustainability targets, a hybrid model of the analytic network process (ANP) and goal programming (GP) is developed. To validate the model, a case example is presented and managerial feedback is collected.
Findings
By enabling the integration of sustainability targets into strategic supplier portfolio configuration, the hybrid ANP-GP model contributes to research in the area of sustainable supply chain management. Results indicate that simplifying the model by omitting one or more details may lead to unfortunate actions.
Research limitations/implications
The model has been applied using a case example in the automotive industry. To strengthen the findings, it should be examined under other terms as well.
Practical implications
Integrating economic, environmental, and social targets into strategic supplier portfolio configuration reduces supply risks and promotes the achievement of the sustainability goals of the purchasing company.
Social implications
Strategic supplier selection counts among the decisions that have an impact on the environment and society for several years. Configuring economically rational, environmentally friendly, and socially responsible supplier bases supports worldwide efforts towards sustainable development.
Originality/value
Although sustainable supplier selection has gained importance in recent years, this is the first time that a comprehensive model for the determination of the optimal strategic supplier portfolio in terms of performance-related objectives and sustainability targets has been proposed.
This research quantifies the impact that regular road traffic congestion has on the CO2 emissions of a real-world distribution network, and it studies the consequences when the number of distribution centers changes. For this purpose, this study makes use of a network model allowing for a detailed representation of all relevant transport operations, including production flows between factories and distribution centers, line haul shipments between distribution centers and customers, and round/delivery trips between transshipment points and retailer locations for the last mile. The processed trip and traffic information does not rely on standard traffic data collection approaches, such as interviews, in situ technologies, or floating car data, but the road traffic data are retrieved from an online navigation service, such as Bing Maps, Google Maps, Inrix, Here, and TomTom. This study proves that online navigation services may considerably contribute to future research projects analyzing CO2 sensitivities and greenhouse gas cutting opportunities in logistics networks.
Online-Navigationsdienste ermöglichen die Planung einer Reise von einem Start- zu einem Ziel-Ort. Die Berechnung von Reisedauer und Streckenlänge erfolgt auf Grundlage eines detaillierten Straßennetzes und unter Berücksichtigung Orts- und Zeit-typischer Verkehrsaufkommen. Dieser Beitrag zeigt, inwiefern Online-Navigationsdienste die Planung und Analyse logistischer Systeme unterstützen können. Er thematisiert insbesondere die Qualität der zur Verfügung gestellten Verkehrsinfrastrukturdaten und hebt die komparativen Vorteile des Einsatzes von Online-Navigationsdiensten im Vergleich zu ‚herkömmlichen‘ Verkehrsinformationsquellen hervor. Ein Anwendungsfall, bei dem die durch Transportaktivitäten verursachten CO2-Emissionen eines Güternahverkehrsnetzes untersucht werden, verdeutlicht die gewonnenen Erkenntnisse.
The European Norm EN 16258 was published in 2012 to provide a common methodology for the calculation and declaration of energy consumption and greenhouse gas emissions related to any transport operation. The objective was to offer a pragmatic and scientifically-acceptable approach that allows a wide group of users to prepare standardized, accurate, credible, comparable, and verifiable energy consumption and emission declarations. However, in its current form, EN 16258 contains gaps and ambiguities, and leaves room for interpretation, which makes comparisons of supply chains difficult. This research aims to overcome the shortcomings in the domain of allocating emissions from road freight transport operations to single shipments. Based on a discussion of emission drivers and the results of numerical experiments comparing the allocation vectors created by the EN 16258 allocation rules with those generated by the Shapley value, which is claimed to be the benchmark, ‘distance’ is identified as the single most useful unit for bridging the trade-off between accuracy and simplicity better than the other recommended allocation schemes. Thus, this paper claims that future versions of EN 16258 should only allow the allocation unit ‘distance.’ This will promote the accurateness, simplicity, consistency, transparency, and comparability of emission declarations.