Prof. Dr. Hanno Friedrich

Publications

Associate Professor of Freight Transportation - Modelling and Policy

Prof. Dr. Hanno Friedrich

Publications

Associate Professor of Freight Transportation - Modelling and Policy

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Journal Articles (Peer-Reviewed)

DOI: https://doi.org/10.1007/s12599-020-00653-0 

Abstract: Transparency in transport processes is becoming increasingly important for transport companies to improve internal processes and to be able to compete for customers. One important element to increase transparency is reliable, up-to-date and accurate arrival time prediction, commonly referred to as estimated time of arrival (ETA). ETAs are not easy to determine, especially for intermodal freight transports, in which freight is transported in an intermodal container, using multiple modes of transportation. This computational study describes the structure of an ETA prediction model for intermodal freight transport networks (IFTN), in which schedule-based and non-schedule-based transports are combined, based on machine learning (ML). For each leg of the intermodal freight transport, an individual ML prediction model is developed and trained using the corresponding historical transport data and external data. The research presented in this study shows that the ML approach produces reliable ETA predictions for intermodal freight transport. These predictions comprise processing times at logistics nodes such as inland terminals and transport times on road and rail. Consequently, the outcome of this research allows decision makers to proactively communicate disruption effects to actors along the intermodal transportation chain. These actors can then initiate measures to counteract potential critical delays at subsequent stages of transport. This approach leads to increased process efficiency for all actors in the realization of complex transport operations and thus has a positive effect on the resilience and profitability of IFTNs.

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DOI: https://doi.org/10.3390/ijerph17020444 

Abstract: Computational traceback methodologies are important tools for investigations of widespread foodborne disease outbreaks as they assist investigators to determine the causative outbreak location and food item. In modeling the entire food supply chain from farm to fork, however, these methodologies have paid little attention to consumer behavior and mobility, instead making the simplifying assumption that consumers shop in the area adjacent to their home location. This paper aims to fill this gap by introducing a gravity-based approach to model food-flows from supermarkets to consumers and demonstrating how models of consumer shopping behavior can be used to improve computational methodologies to infer the source of an outbreak of foodborne disease. To demonstrate our approach, we develop and calibrate a gravity model of German retail shopping behavior at the postal-code level. Modeling results show that on average about 70 percent of all groceries are sourced from non-home zip codes. The value of considering shopping behavior in computational approaches for inferring the source of an outbreak is illustrated through an application example to identify a retail brand source of an outbreak. We demonstrate a significant increase in the accuracy of a network-theoretic source estimator for the outbreak source when the gravity model is included in the food supply network compared with the baseline case when contaminated individuals are assumed to shop only in their home location. Our approach illustrates how gravity models can enrich computational inference models for identifying the source (retail brand, food item, location) of an outbreak of foodborne disease. More broadly, results show how gravity models can contribute to computational approaches to model consumer shopping interactions relating to retail food environments, nutrition, and public health.

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DOI: https://doi.org/10.1016/j.tre.2018.03.002 

Abstract: This paper presents a calibrated dynamic multi-scale multi-regional input–output (MSMRIO) model of the German food supply system based on real data. The model comprises 51 commodity groups from farm to fork differentiating three different temperature ranges as well as living animals. Spatially, it works on an aggregate level of 402 regions within Germany as well as its 50 most important trading nations. It determines the commodity flows and the additionally needed transport capacity in case of disruptions. Showing how changes in production, inventories, sourcing, and consumption affect commodity flows, the model uncovers vulnerabilities and makes risk evaluation possible.

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DOI: https://doi.org/10.1080/00207543.2019.1657248 

Abstract: Food is an important resource in disaster management, and food stock levels hold significance for disaster mitigation research and practice. The presence or absence of food stocks is a vulnerability indicator of a region. A large part of overall food stock, before a disaster strikes, is held by private companies (retailers, wholesalers and food producers). However, there is little-to-no information on the food stock levels of commercial companies, and no approach exists to derive such information. We develop an approximation model based on essential inventory management principles and available data sources to estimate aggregated food stock levels in supply networks. The model is applied in a case example that features dairy product stock levels in the German state of Saxonia. The resulting overall stock levels are normalised, and their usability is showcased in a simple vulnerability analysis. Disaster managers are provided with a model that can be used estimate otherwise unavailable data and facilitates investigations into the regional resilience of an area. The limitations of our study are based on the aggregated nature of the supply network structure and data usage (i.e. in the model, we do not consider any seasonality or trend effects).

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DOI: https://doi.org/10.1098/rsif.2018.0624 

Abstract: In today’s globally interconnected food system, outbreaks of foodborne disease can spread widely and cause considerable impact on public health. We study the problem of identifying the source of emerging large-scale outbreaks of foodborne disease; a crucial step in mitigating their proliferation. To solve the source identification problem, we formulate a probabilistic model of the contamination diffusion process as a random walk on a network and derive the maximum-likelihood estimator for the source location. By modelling the transmission process as a random walk, we are able to develop a novel, computationally tractable solution that accounts for all possible paths of travel through the network. This is in contrast to existing approaches to network source identification, which assume that the contamination travels along either the shortest or highest probability paths. We demonstrate the benefits of the multiple-paths approach through application to different network topologies, including stylized models of food supply network structure and real data from the 2011 Shiga toxin-producing Escherichia coli outbreak in Germany. We show significant improvements in accuracy and reliability compared with the relevant state-of-the-art approach to source identification. Beyond foodborne disease, these methods should find application in identifying the source of spread in network-based diffusion processes more generally, including in networks not well approximated by tree-like structure.

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DOI: https://doi.org/10.1016/j.ecolecon.2019.05.022 

Abstract: We compute degrees of food self-sufficiency for regions in North Germany with the city state of Hamburg at the centre, given different diets (the German average diet versus increasing substitution of legumes for meat) and production methods (conventional versus organic). Triangulating data of statistical databases, literature, and our own collection, we compute land footprints per capita and multiply by regional populations. Our findings indicate that there is great potential to feed the regional community surrounding Hamburg solely with regionally, organically grown foods, but this result depends on (1) composition of diets — specifically, the per capita meat consumption – and (2) agricultural area available in the defined region. On the basis of simplifying assumptions, the computation indicates an approximation of what is possible.

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DOI: https://doi.org/10.1016/j.tre.2017.08.009 

Abstract: The paper introduces a model to determine possible impacts of changes in supply chain structures on freight transport demand. Examples are centralisation or vertical (des)integration within supply chains. The model first generates a population of establishments and commodity flows in space which is then manipulated according to different scenarios. It uses methods from transport planning and optimisation as well as scenario technique. To demonstrate its applicability a centralisation in food supply chain structures in Germany is analysed. The results show that a more educated discussion is needed for such changes since the range of possible impacts is large.

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DOI: https://doi.org/10.1016/j.cstp.2015.08.003 

Abstract: Abstract This paper discusses the opportunities of sectoral freight transport demand models. The work is based on literature and insights from interdisciplinary research in the field of production, logistics and transport. First, current and future factors influencing freight transport are discussed. Next, a brief summary of the traditional transport modelling approach and recent extensions and adaptations of freight transport models is given. As interdisciplinary research has shown, the impact of the identified factors on the development of freight transport is strongly dependent on the sector under investigation. As a consequence, this paper proposes the application of a sectoral modelling approach. The automotive and food sectors in Germany are used as examples to further examine the opportunities of sectoral freight transport demand models.

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DOI: https://doi.org/10.14257/ijt.2014.2.1.03 

Abstract: Logistics optimization problems are often complex (NP - hard). Especially for large problem scopes in logistics and new agent-based freight transport models which have to solve these problems for many agents, simplifying modelling and solving procedures are necessary in order to reduce the level of complexity. Due to the variety of existing approaches and the specifics of each problem it is often difficult to find an appropriate method. This paper seeks to facilitate this process as it identifies ‘meta’ heuristics within literature, i.e. abstract courses of action that, when adapted, have proven successful in various problems. It presents a classification of general simplification principles that are useful for reducing the complexity of logistics problems, in order to facilitate understanding between academics and practice. The derivation of the related principles is based on the examination of five problems in logistics literature: facility location, distribution system, lot size, bin packing, and vehicle routing.

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DOI: https://doi.org/10.1007/s11116-012-9386-9 

Abstract: This article analyzes the concept of logistics networks in the context of behavioral freight transport modeling. Starting from the basic definition of networks, the different perceptions of networks in transportation science and logistics are worked out. The micro‐macro gap, as a main challenge in freight transport modeling, is explained by the existence of logistics networks on a meso level. A taxonomy of modeling methods dealing with logistics networks is defined, based on two characteristics: the changeability of networks within models (fixed, partially variable and variable networks) and the form of cost functions mapped (economies of scale, constant average cost, and diseconomies of scale). For each category, different possible modeling methods and their application in existing freight transport models are discussed. A special focus is placed on methodologies and models that map variable networks.

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Journal Articles (Professional)

Abstract: available for download: https://www.mckinsey.de/~/media/mckinsey/locations/europe%20and%20middle%20east/deutschland/news/presse/2018/2018-07-12/travel-and-logistics-data-drives-the-race-for-customers.ashx

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Abstract: Die Modellierung des Wirtschaftsverkehrs gewinnt aufgrund der aktuellen Anforderungen und Fragestellungen zunehmend an Bedeutung. Daher werden in der FGSV parallel zur Entwicklung entsprechender Regelwerke und Empfehlungen für den Personenverkehr auch der aktuelle Stand der Technik zur Modellierung des Wirtschaftsverkehrs beleuchtet sowie Empfehlungen und Hinweise zu seiner Modellierung entwickelt. Zunächst werden dazu die Fragestellungen analysiert. Im Anschluss daran werden die Unterschiede in der Modellierung des Wirtschaftsverkehrs zum Personenverkehr erläutert. Dabei werden der Modellaufbau, die verwendeten Modellierungsmethoden sowie eine Auswahl von Softwarewerkzeugen vorgestellt und analysiert. Nachdem die wesentlichen Datenquellen für Wirtschaftsverkehrsmodelle benannt wurden, werden abschließend einige Beispiele für Wirtschaftsverkehrsmodelle dargestellt. Due to increasing requirements the modelling of commercial traffic receives more and more attention. The German Road and Transportation Research Association (FGSV) compiled the state-of-practice of modelling transport and included, thus, specific recommendations for commercial transport. This article provides an overview of commercial transport modelling issues: First, the different purposes of modelling commercial transport are listed. In the next step the difference between private and commercial transport modelling is discussed. This section is subdivided into model architecture and modelling methods. An overview of software products is enclosed as well as a description of the relevant input data. The article closes with some examples for commercial transport models.

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Books

Abstract: Im SMECS-Projekt wurde durch Anwendung von KI-Verfahren des Maschinellen Lernens ein IT-System entwickelt, welches dynamisch die Ankunftszeit (ETA) von Containertransporten im intermodalen Vorlauf der maritimen Transportkette prognostiziert. Das System erkennt proaktiv Konflikte bei der Einhaltung des geplanten Transportverlaufes vom Warenversender bis zum Seehafen und befähigt die Anwender zu einer zielgerichteten und effizienten Durchführung geeigneter Störungsmaßnahmen durch die Vorgabe von akteursspezifischen Handlungsempfehlungen.

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Abstract: Die zuverlässige Versorgung mit Lebensmitteln ist ein Grundbedürfnis der Bevölkerung. Ein effizientes Risikomanagement zur Vermeidung von Versorgungsengpässen ist daher sowohl von staatlicher als auch privatwirtschaftlicher Seite erforderlich. Zu dieser übergeordneten Zielstellung, die Sicherheit der Lebensmittelversorgung für Bürgerinnen und Bürger zu erhöhen, liefert das Verbundprojekt einen Beitrag durch eine fokussierte Untersuchung hinsichtlich möglicher Versorgungsengpässe, um das Management derartiger Lagen zu verbessern. Konkret ergab sich für das Projekt SEAK daraus die Aufgabe, Möglichkeiten der Entscheidungsunterstützung zur Sicherstellung der Lebensmittelversorgung zu erforschen, um geeignete Instrumente für Unternehmen und Behörden zur Verfügung zu stellen.

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DOI: https://doi.org/10.5445/IR/1000020602 

Abstract: The study contributes to fill the gap between freight transportation analysis and logistic research. It describes the model SYNTRADE, a simulation model that reproduces logistic structures in the German food retailing sector. Logistic decisions and their interdependencies are simulated based on heuristics from the field of logistic optimization. The model provides the possibility to analyze changes in logistics and freight transport demand on a company, as well as on an overall sector level. http://digbib.ubka.uni-karlsruhe.de/volltexte/1000020602

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Abstract: Supervisors: Prof. Dr. Werner Rothengatter and Dr. Gernot Liedtke

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Conference Proceedings

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Conference Proceedings

DOI: https://doi.org/10.1007/978-3-030-13535-5_12 

Abstract: Intermodal logistics networks such as the maritime transport chain require a precise interaction of numerous actors. However, due to their complexity, the closely interlinked processes are highly susceptible to disruptions. Companies are constantly faced with the challenge of dealing effectively and efficiently with disruptions and resultant delays. At the same time, they are confronted with increasing logistical requirements related to higher quality and flexibility demands of customers (Straube et al. 2013). Supply chains are becoming increasingly vulnerable, due to the associated necessity to cope with increasing volatility while simultaneously reducing risk buffers in processes as a result of rising cost pressure. Combined with ongoing changes due to digitization, this situation contributes significantly to an increasing need for improved information transparency among companies and their customers.

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DOI: https://doi.org/10.1016/j.trpro.2020.08.219 

Abstract: Toll roads are believed to have a high ability to attract private investment since they are able to recover directly the costs of their operation and construction through toll charges. However, toll road development can only be attractive to investors and lenders if the long-term sustainability is achieved. This paper identifies and discusses various issues that government and project developers have to deal with from selected case studies. The seven selected toll road projects are priority sections of the National Trunk Highway System (NTHS) and located in strategic provinces in China. The issues examined are related to policy support, regional development, the fund-raising model, project development and the financial structure. This study reveals critical success factors to achieve sustainable toll road projects in the planning stage and to control and enhance the financial sustainability in the executing stage.

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DOI: https://doi.org/10.1016/j.trpro.2017.05.479 

Abstract: Integrating the decisions and the behavior of Logistics Service Providers (LSPs) into freight transport models is essential to be capable of accurately describing future developments in freight transport systems. Knowledge on the spatial distribution patterns of LSP locations, e.g. to represent network routing of shipments more accurately, is of paramount importance. Moreover, attributes characterizing the LSP locations are helpful to relate them to traffic generation. Therefore, the objective of this paper is to present intermediate results of an empirical study on LSP locations in Germany. Drawing on these findings, the freight generated by German less than truckload networks is estimated on an aggregate level. These findings shed some light on the spatial and structural patterns of the locations allocable to the German logistics sector and the freight transport it generates. These insights are highly relevant for freight transport and land use planning policies.

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DOI: https://doi.org/10.1016/j.trpro.2017.05.374 

Abstract: The objective of this study is to understand how and to what extend illegal parking should be legalized, giving the benefit for parking users, urban planning, and transport planning. From literature, the policies and theories based on the lessons from other countries have provided the basis that can be applied in investigating a new parking management paradigm. Empirical surveys are conducted to examine the parking conditions, parking user’s behavior and the consequence of illegal parking spaces in the core city center in Hanoi, Vietnam. Then, the requirements of para-parking (legalization of illegal parking spaces) are formulated including the change process that involves parking authorities, parking operators, and parking users. An in-depth analyze is undertaken to look at opportunities, risks and forms of para-parking and finally a proposal for a qualitative economic impact assessment of parking facility investment is given.

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Abstract: Due to strong interdependencies between production, logistics and traffic, a decision in one of these fields has impacts on the others. However, decision makers in and around today’s supply chains rarely consider effects of their decisions on other participants of the supply chain or the traffic system. Thus, a tool for decision support, which clearly illustrates the variety of impacts of a decision, is highly desirable. Accordingly, this paper presents a reference model in the context of production, logistics and traffic, called Interdisciplinary Decision Map (IDM). The IDM allows for describing and analyzing interdisciplinary impacts of decisions across the disciplines. Thus, it can serve as decision support tool for decision makers out of the considered domains. The IDM’s applicability is demonstrated by using it to analyze selected impacts of an heavy goods vehicles (HGV) toll’s introduction on production, logistics and traffic.

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Abstract: Wirtschaftsverkehrs- und City-Logistik-Modelle ermöglichen die Simulation des Verkehrsverhaltens sowie die Untersuchung und Bewertung von verschiedenen verkehrspolitischen Maßnahmen. Prominente Maßnahmen sind beispielsweise Einfahrverbote bestimmter Lkw-Typen, räumlich und zeitlich differenzierte Mautgebühren oder die Nutzung von Güterverkehrszentren. Diese Arbeit ist eingebettet in einen übergeordneten Ansatz zur mikroskopischen Modellierung des städtischen Distributionsverkehrs im Lebensmitteleinzelhandel. Neben der Verhaltensmodellierung der Entscheidungsträger sowie der physischen Simulation der Fahrzeugbewegungen liegt die große Herausforderung in der Gewinnung der Modelleingangsdaten zur Beschreibung des umfassenden Entscheidungsproblems in der Distributionslogistik. Die Ableitung dieser Daten sowie die Illustration am Beispiel eines Berlin-Szenarios ist Gegenstand des vorliegenden Aufsatzes.

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Abstract: This work aims to discuss modeling issues on solving the transport distribution problem in freight transport. The traditional distribution model – the Gravity Model – is introduced in detail with the focus on its forecasting capability of freight transport distribution. Through analyses on the base of observed and predicted data of freight transport in Germany, it is found that, compared to applying the Gravity Model, directly balancing the observed distribution from the last period using the Furness Method can generate more closer predictions to the official predictions in a planning project of the German Federal Ministry of Transport, Building and Urban Development. However, the re is a doubt about whether this Furness Method itself brings about an impact on the deterrence exponent. Based on the proposition that the Furness Method dilutes the deterrence effect of transport costs, a compensating procedure is developed in this work as a supplement to the traditional process, offering a new thinking to improve the prediction performance of distribution models.

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Abstract: Supplies of food and water are essential in disaster management, particularly in the very early chaotic phases when demand and available resources are highly uncertain, information systems are disrupted, and communication between communities, food suppliers, retail and emergency authorities is difficult. As many actors and organisations are involved in ever more complex food supply chains, cooperation and collaboration are vital for efficient and effective disaster management. To support decision-makers facing these problems, this paper introduces a scenario-based approach that integrates simulation of disruptions in food supply chains, and qualitative expert assessment to develop consistent scenarios that show the consequences of different strategies. To choose the best individual measures for all relevant actors and to compare it with the best overall strategy approaches from multi-criteria decision analysis are used.

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Abstract: Desicion-makers in and around today's supply chains are facing tough every day. However, when making decisions, they rarely consider what effects their desicions cause upon other participants of the supply chain or traffic management. This is mostly due to the lack of appropriate tools which help indicating the possible effects. Such tools are necessary to tackle the inherent complexity of the whole supply chain system. This paper describes how to construct and design such a tool for this interdisciplinary environment, called an Interdisciplinary Decision Map (IDM). The IDM is a powerful tool to visualise complex relationships, while at the same time retaining usability by showing relevant information only. We show how tu use a specific instance of an IDM to facilitate a better understanding to the underlying processes of other supply chain participants. The soundness of our approach is backed by findings from an interdisciplinary research project.

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Abstract: In this article, basic characteristics of HGV toll systems are described. Based on that, these systems' impacts on entrepreneurial processes and resulting changes in business choices are discussed. Furthermore, a case study on hauliers' reactions on the German HGV toll is presented. The results show that the haulage industry only has to deal with marginal impacts since costs are usually passed along to the customer, this is why operational changes do not seem necessary.

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Abstract: This paper estimates the shippers‟ reactions and their economic benefits from a multimodal transport network called LOGOTAKT. For this purpose, an econometric shipper model is being estimated in which the major factor influencing logistics decisions – the balance between warehouse and storage cost – is explicitly taken into account. The functional form is being deduced from the first order condition of Total Logistics Cost function minimization. Transport cost is expressed in form of a complex function depending on order size and the transport distance in order capture the effect of economies of scale in transportation. It is estimated based on empirical data of distribution obtained from two major German companies. Simulations show that the new multimodal transportation system has a significant impact on shipment size distributions changing them in favor of smaller shipments. This leads especially to significant reductions in warehouse costs. Finally, some implications of the analytical results on transport policy are provided: To achieve further modal shift from road to rail, public financial support and the regulatory framework must put railways into the position to consolidate shipments and to exhaust economies of scale.

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Abstract: In recent years a rising attention for logistics in politics and transport analysis can be ob-served. Therefore, freight transport models increasingly put more attention on logistics. How-ever, logistics is mostly modeled in a very simplified way and different parts of logistics are considered. Modelers have limited options to build more mature logistics models: A detailed representation of logistics requires the description of a heterogeneous economic landscape leading to very high data demand and it requires to model combinatorial logistic problems exceeding the processing capability available. Therefore a balance has to be found between mapping logistic behavior in a “reality-like” way and the need to keep the model as simple as possible. Based on conceptual frameworks on logistic choice levels and logistic structures the paper shortly reviews a selection of existing modeling approaches. This and a detailed discus-sion of two modeling experiences show future strategies in freight transport modeling to-wards finding this balance.

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DOI: https://link.springer.com/chapter/10.1007/978-3-030-36683-4_30 

Abstract: Computational traceback models are important tools for investigations of widespread food-borne disease outbreaks as they help to determine the causative outbreak location and food item. In an attempt to understand the entire food supply chain from farm to fork, however, these models have paid little attention to consumer behavior and mobility, instead making the simplifying assumption that consumers shop in their home location. This paper aims to fill this gap by modelling food-flows from supermarkets to consumers in a large-scale gravity model for Hesse, Germany. Modelling results show that on average, groceries are sourced from two to four postal zones with half of all goods originating from non-home postal zones. The results contribute to a better understanding of the last link in the food supply chain. In practice, this allows investigators to relate reported outbreak cases with sourcing zones and respective food-retailers. The inclusion of this information into existing models is expected to improve their performance.

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Book Chapters

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Book Chapters

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DOI: https://doi.org/10.1007/978-3-319-41097-5_3 

Abstract: Due to strong interdependencies between production, logistics and traffic, a decision in one of these fields has impacts on the others. However, decision-makers in and around today’s supply chains rarely consider effects of their decisions on other participants of the supply chain or the traffic system. Thus, a tool for decision support, which clearly illustrates the variety of impacts of a decision, is highly desirable. Accordingly, this chapter presents a reference model in the context of production, logistics and traffic, called Interdisciplinary Decision Map (IDM). The IDM allows for describing and analysing interdisciplinary impacts of decisions across the disciplines. Thus, it can serve as decision support tool for decision-makers out of the considered domains. The IDM’s applicability is demonstrated by using it to analyse selected impacts of an HGV toll’s introduction on production, logistics and traffic.

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DOI: https://doi.org/10.1007/978-3-319-41097-5_10 

Abstract: The freight transport system is a major determinant for the competitiveness of logistics and production activities. On the other hand, logistics and production shape freight transport demand. Therefore, freight transport demand models are needed that can capture the influence and requirements of ongoing trends in production and logistics. In this chapter, the German automotive industry is used as an example of how certain trends might influence the development of freight transport demand. Here, the impact of changes in the supply chain structure on freight transport demand is emphasised. Furthermore, data sources available on the sectoral level are discussed. Based on the insights into ongoing trends, available data and sectoral characteristics, a concept for a sectoral freight transport model for the German automotive industry is developed.

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DOI: https://doi.org/10.1007/978-3-319-21266-1_22 

Abstract: This work was created as part of the research project SEAK, which looks into possible causes and consequences of food shortfalls in Germany and is moreover also aimed at developing and evaluating possible mitigation strategies for these shortfalls. For the management of shortfalls in food supply it would be, as a first step, crucial to have information on existing inventories. Making for example decisions on the reallocation of food products into regions affected by disasters is only possible if knowledge about the (regional) availability of food quantities is present in the first place. This could be considered as a necessary transparency. However, in the German food sector, it is hard to get data about the inventories kept by companies like producers, logistic service providers (LSP’s), wholesalers or retailers. This is due to the fact that usually companies are not obliged to publish this information. Moreover, this information is also considered confidential in most companies, since it would give competitors insight into their business model and processes, which are oftentimes the basis for their success. Since information concerning food inventories is not publicly available, it has to be derived in another manner. This work is aimed at providing a scientific basis for the modelling of inventories along food supply chains. More specifically, it does so for the food commodity group of dairy products. We gathered information on all available food products, but limit this particular analysis to dairy products as a showcase of our approach. First, we introduce the data set used for the analysis and the methodology applied to it. In a next step, characteristics of typical German dairy supply chains are described using practical evidence as well as literature findings. The description follows the supply chain’s structure from start to finish, downstream. In the end, concluding remarks are made and possible further research ventures are suggested.

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DOI: https://doi.org/10.1007/978-3-319-21266-1_3 

Abstract: Due to the structural heterogeneity of freight transport and its long-term subordinate consideration, there have been low research activities in this field as well as low motivations to integrate this segment into transport demand models for decades. There is also no generally valid framework for freight transport modelling in comparison to passenger transport modelling. Without a common framework, it is difficult to exchange ideas between scientists and to enable an efficient communication and solid agreements between a client and a contractor of a transport modelling service. This contribution presents a typological order of characteristics of freight transport demand models which covers their internal structures and employed methods. In addition, a systematic overview of selected international freight transport demand models is given.

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DOI: doi:http://dx.doi.org/10.1016/B978-0-12-410400-6.00004-5 

Abstract: Distribution structures are important elements of the freight transportation system. Goods are routed via warehouses on their way from production to consumption. This chapter discusses drivers behind these structures, logistics decisions connected to distribution structures on the micro level, and possible modeling methodologies on the macro level. The authors show the connection between the micro and the macro level and highlight advantages of the different modeling approaches.

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