Prof. Dr. Hanno Friedrich

Associate Professor of Freight Transportation - Modelling and Policy

Prof. Dr. Hanno Friedrich

Associate Professor of Freight Transportation - Modelling and Policy

Hanno Friedrich is Associate Professor of Freight Transportation - Modelling and Policy. He studied Industrial Engineering at Karlsruhe Institute for Technology (KIT). After having finished his diploma in 2004, he worked for six years at McKinsey & Company, a strategic management consulting firm. Within this time, he did his Doctorate at the KIT under the supervision of Prof. Dr. Werner Rothengatter. After working for one year as a Postdoc at the KIT he received a call for a Junior Professorship in the area of commercial transport at the TU Darmstadt in 2011. Since September 2015 he is Assistant Professor at Kühne Logistics University (KLU) in Hamburg.

His research topics are freight transport demand modelling, transport economics, risk management in transport and logistics, and food logistics.

Up Close & Personal

“For me, diversity sets KLU apart.”
– Prof. Dr. Hanno Friedrich

Selected Publications

DOI: 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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Open reference in new window "An ETA Prediction Model for Intermodal Transport Networks Based on Machine Learning"

DOI: 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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Open reference in new window "Locating the source of large-scale outbreaks of foodborne disease"

DOI: 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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Open reference in new window "Can Regional Organic Agriculture Feed the Regional Community? A Case Study for Hamburg and North Germany"

DOI: 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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Open reference in new window "Modelling change in supply-chain-structures and its effect on freight transport demand"

DOI: 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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Open reference in new window "An inventory management approximation for estimating aggregated regional food stock levels"

Academic Positions

since 2020

Associate Professor of Freight Transportation - Modelling and Policy at Kühne Logistics University (KLU)

2015 - 2019

Assistant Professor of Freight Transportation - Modelling and Policy at Kühne Logistics University (KLU)

2011 - 2015

Junior Professor of Commercial Transport at TU Darmstadt

2010 - 2011

Postdoctoral Research and Teaching Assistant at the Karlsruhe Institute of Technology (KIT)

Professional Experience

2004 - 2010

Consultant at McKinsey & Company (on educational leave from 2006 to 2009)

Education

2006 - 2010

Dissertation in economics at the Karlsruhe Institute of Technology (KIT)
Thesis topic: “Simulation of Logistics in Food Retailing for Freight Transportation Analysis”, supervisor: Prof. Dr. Werner Rothengatter, co-examiner: Prof. Dr. Lori Tavasszy

2006

Visiting Scientist at the Institute for Transport (IVF) at the German Aerospace Center (DLR) in Berlin

2001 - 2003

International exchange programme (ERASMUS) in France at the “Ecole de Management Lyon” (EM Lyon)

1998 - 2003

Studies in industrial engineering at the University of Karlsruhe
Degree: Diplom-Wirtschaftsingenieur (Dipl.-Wi.-Ing.)

Committees

  • World Conference on Transport Research Society (WCTRS): Co-chair of SIG B5 Freight Transport Modeling.
  • European Transport Conference (ETC): Member of the Freight and Logistics committee.
  • Forschungsgesellschaft für Straßen- und Verkehrswesen (FGSV): member of AA 1.8 (Freight Transport) and AK 1.8.4 (Conceptualisation and application of transport demand models estimating commercial transport).

Research Projects

2019 - 2021Nutrisafe: Sicherheit in der Lebensmittelproduktion und Logistik durch die Distributed Ledger Technologie, Funding: BMBF (German ministry of research), Partner: Kühne Logistics University, Universität der Bundeswehr München, Universität Bremen (IGMR), OTARIS Interactive Services GmbH, SBCF & Cie., Diebold Nixdorf AG, Giesecke + Devrient Mobile Security GmbH, https://www.sifo.de/files/Projektumriss_NutriSafe.pdf
2018 - 2021Handlungsoptionen für eine ökologische Gestaltung der Langstreckenmobilität Modul B: Güterverkehr, Funding: UBA (Umweltbundesamt - Federal Agency for the Environment), Partner: DLR, TTS, Kantar TNS, Role: Advisory Board (wissenschaftlicher Begleitkreis)
2018 - 2020SMart Event ForeCast for Seaports (SMECS), Funding: BMVI (German ministry of transport), Partner: TU Berlin (Logistics Chair), Kühne Logistics University, DB Cargo, Dakosy Datenkommunikationssystem AG, Kühne + Nagel, Hamburg Süd, DB Netze, TFG Transfracht, Hamburger Hafen und Logistik AG (HHLA), Metrans, boxXpress.de, Verein Hamburger Spediteure, Lübecker Hafengesellschaft mbH.
2016Modelling Food Supply Systems to Identify Outbreak Origins (MFSSIOO), Funding: DFG, Bayer Foundation, BfR, MIT
2016 - 2018FALCON: Freight And Logistics in a Multimodal Context , Funding: Conference of European Directors of Roads (CEDR), Partner: HAN, VTI, DLR, TNO, IFSTTAR, BRRC, CUTS, MAN, Michelin, Role: Advisory Board
2013 - 2015SEAK: decision support for food supply shortfalls - quantitative modelling of the food supply in Germany, funding: BMBF, partner: TU Darmstadt, KIT, 4flow AG, www.seak-projekt.de
2015FCD: Utilisation of floating car data for freight transport modelling, funding: HOLM, partner: TU Wuppertal, TU Darmstadt.
2011 - 2014Dynamo PLV: dynamic and seamless integration of production, logistics and traffic, funding: State of Hesse (LOEWE-Project), partner: TU Darmstadt and EBS, role: head of commercial transport sub-project, dynamo-plv.de.
2010 - 2011RM-LOG: risk-management strategies in infrastructure and logistics networks from a business and macroeconomic perspective, funding: BMBF, partner: TU Berlin, KIT Karlsruhe, 4flow AG and Kühne & Nagel
2008 - 2010Logotakt: technologies and processes for robust and synchronised logistics networks, funding: BMWI, partner: KIT, LOCOM, PTV, Volkswagen, DB Schenker, Bosch

Consulting Projects

2019Luxembourg’s future role as an air cargo hub: a preliminary study (KLU consulting project, Germany/Luxemburg, 2 days).
2019Workshop on Logistics startups and opportunities for Lufthansa Technik Logistics services (Germany, 1 day).
2014Analysis and optimization of the distribution network of a German fresh food producer (Germany, 2 months).
2012Market-volume estimation for the transportation and storage of dangerous goods in Germany, (Germany, several days).
2009 - 2010Benefit assessment of an ERP implementation for a German food retailer (Germany, 6 months).
2005 - 2006Improvement of IT cost and performance for a European bank (Germany, 5 months).
2005IT organization and IT governance development for an international bank in a post-merger situation (USA and Switzerland, 6 months).
2005Concept development for a performance management system for a German institution in the public sector (Germany, 3 months).
2004IT strategy development and IT post-merger management for an international logistics company, in particular development of a harmonised process model in logistics for future IT support (USA and Germany, 8 months).
2004Improvement of IT costs and performance for a European retailer, especially in the area of cashpoint and logistics systems (Germany, 4 months).
2002Feasibility study for a shared service centre for an international electronics company (Germany, 3-month summer internship).

 

  • Co-chair of the 2nd Interdisciplinary Conference on Production, Logistics and Traffic (ICPLT), 21-22 July 2015, Dortmund, Germany.
  • Organizer of the Interdisciplinary Conference on Production, Logistics and Traffic (ICPLT), 19 - 21 March 2013, Darmstadt, Germany.
  • Co-chair of the session “Großbaustellen – Integrierte Optimierung von Bauverfahren, Logistik und Verkehr” (construction sites - integrated optimization of construction processes, logistics, and traffic) at the 2. Civil Engineering Congress at Darmstadt, 12 -13 March 2013, Darmstadt, Germany.