Prof. Jan Fransoo, PhD

Professor for Operations Management and Logistics

Dean of Research

Jan C. Fransoo is Professor of Operations Management & Logistics at Kuehne Logistics University. He also serves as the University’s Dean of Research and Member of the Executive Board. He joined KLU in 2018 following a tenure of 22 years at Eindhoven University of Technology in the Netherlands, where he still holds an honorary visiting professorship in its School of Industrial Engineering. Fransoo holds a Master of Science (ir.) degree in Industrial Engineering and a Doctor of Philosophy (dr.) degree in Operations Management and Logistics, both from Eindhoven University of Technology.

Professor Fransoo’s research studies operations, logistics, and supply chain management decision making in the retail, chemical, food, pharmaceutical and transport industries. His current research focuses in particular on retail distribution and channel management in developing markets, on intermodal container transport, and on sustainability and social responsibility in supply chains. His recent books include Reaching 50 Million Nanostores: Retail Distribution in Emerging Megacities and Sustainable Supply Chains: A Research-Based Textbook on Operations and Strategy.

Fransoo has published over 130 academic journal articles and book chapters in journals such as Management Science, Manufacturing & Service Operations Management, Production and Operations Management, Operations Research, Transportation Science, and European Journal of Operational Research. He currently serves as Associate Editor of Production and Operations Management and Operations Research, and on the Editorial Board of seven other academic journals.

During his tenure at Eindhoven, Fransoo was Founding Program Director of the MSc program in Operations Management & Logistics, and subsequently served as Dean of the University’s Graduate School and Director of the 4TU Institute of Technological Design. Fransoo co-founded Dinalog (Dutch Institute for Advanced Logistics), a Netherlands center of excellence in the area of supply chain management, and served as the academic member in the Strategic Platform for Logistics, setting the national research and innovation agenda in logistics, mandated by the Dutch government. As part from his academic activities, he has conducted dozens of projects with industry, mainly through and with his PhD, PDEng and MSc students, and has consulted with the World Bank and various national governments in developed and developing countries. Fransoo held visiting appointments at various universities, including Clemson University, Stanford University, the University of California at Los Angeles, the Massachusetts Institute of Technology, and the University of Ljubljana (Slovenia). He is a regular visitor to Tsinghua University (China), Hong Kong University of Science and Technology (Hong Kong), and the Tec de Monterrey (Mexico).

More details, including a full publication list and his blogposts, can be found on https://www.janfransoo.com/.

 

Contact

Tel: +49 40 328707-223
Fax: +49 40 328707-109
jan.fransoo@the-klu.org

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Selected Publications

Copy reference link   DOI: 10.1016/j.ejor.2017.09.014

Abstract: In large cities in emerging economies, traditional retail is present in a very high density, with multiple independently owned small stores in each city block. Consequently, when faced with a stockout, consumers may not only substitute with a different product in the same store, but also switch to a neighboring store. Suppliers may take advantage of this behavior by strategically supplying these stores in a coherent manner. We study this problem using consumer choice models. We build two consumer choice models for this consumer behavior. First, we build a Nested Logit model for the consumer choice process, where the consumer chooses the store on the first level and selects the product on the second level. Then, we consider an Exogenous Substitution model. In both models, a consumer may substitute at either the store level or the product level. Furthermore, we estimate the parameters of the two models using Markov chain Monte Carlo algorithm in a Bayesian manner. We numerically find that the Nested Logit model outperforms the Exogenous Substitution model in estimating substitution probabilities. Further, the information on consumers’ purchase records helps improve the estimation accuracies of both the first-choice probabilities and the substitution probabilities when the beginning inventory level is low. Finally, we show that explicitly including such substitution behavior in the inventory optimization process can significantly increase the expected profit.

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Copy reference link   DOI: 10.1287/trsc.2013.0481

Abstract: The transport sector is the second largest carbon emissions contributor in Europe and its emissions continue to increase. Many producers are committing themselves to reducing transport emissions voluntarily, possibly in anticipation of increasing transport prices. In this paper we study a producer that has outsourced transport and has decided to cap its carbon emissions from outbound logistics for a group of customers. Setting an emission constraint for a group of customers allows for taking advantage of the portfolio effect. We focus on reducing emissions by switching transport modes within an existing network, since this has a large impact on emissions. In addition, the company sets the sales prices, which influence demand. The problem is solved by decomposing the multi-product problem into several single-product problems, which we then analyze separately. Using the single-product solutions we create an efficient frontier which reflects the trade-off between total carbon emissions and the total prot. It is observed that a diminishing rate of return applies in reducing emissions by switching transport modes. In a case study we apply our method to a producer of bulk liquids and find that emissions can be reduced by 10% at only a 0.7% increase in total logistics cost.

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Copy reference link   DOI: 10.1111/j.1937-5956.2011.01310.x

Abstract: With supply chains distributed across global markets, ocean container transport now is a critical element of any such supply chain. We identify key characteristics of ocean container transport from a supply chain perspective. We find that unlike continental (road) transport, service offerings tend to be consolidated in few service providers, and a strong focus exists on maximization of capital intensive resources. Based on the characteristics of ocean container transport as part of global supply chains, we list a number of relevant and challenging research areas and associated questions.

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Copy reference link   DOI: 10.1287/mnsc.1090.1141

Abstract: Retail store managers may not follow order advices generated by an automated inventory replenishment system if their incentives differ from the cost minimization objective of the system or if they perceive the system to be suboptimal. We study the ordering behavior of retail store managers in a supermarket chain to characterize such deviations in ordering behavior, investigate their potential drivers, and thereby devise a method to improve automated replenishment systems. Using orders, shipments, and point-of-sale data for 19,417 item–store combinations over five stores, we show that (i) store managers consistently modify automated order advices by advancing orders from peak to nonpeak days, and (ii) this behavior is explained significantly by product characteristics such as case pack size relative to average demand per item, net shelf space, product variety, demand uncertainty, and seasonality error. Our regression results suggest that store managers improve upon the automated replenishment system by incorporating two ignored factors: in-store handling costs and sales improvement potential through better in-stock. Based on these results, we construct a method to modify automated order advices by learning from the behavior of store managers. Motivated by the management coefficients theory, our method is efficient to implement and outperforms store managers by achieving a more balanced handling workload with similar average days of inventory.

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Copy reference link   DOI: 10.1016/j.jom.2005.09.008

Abstract: The complexity of planning tasks have increased over the past decade. There is relatively poor understanding what the implications are of increased task complexity in planning and scheduling operations. Previous work in the behavioral sciences have investigated the concept of cognitive load, addressing both task complexity and task workload or stress, and have concluded that decision makers tend to resort to routine action and reduce the variety in their actions with increasing complexity and workload. Alternatively, control theory suggests that a higher variety of actions is needed to deal with more complex problems. In this paper, we investigate the effects of task complexity in a chemical plant on the variety of actions deployed by the planners. The single work center resource structure and the availability of actual planning data from an MRP-application database allows us to both use field data and study a situation which is simple enough to measure the main effect. Our results suggest that increased task complexity without time pressure does indeed lead to increased action variety deployed by the planners. Keywords: Cognitive load; Task complexity; Field study; Chemical industry; Requisite variety

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Academic Positions

2018 - Current

Professor for Operations Management and Logistics, Kuehne Logistics University, Germany

2018 - Current

Dean of Research and Member of the Executive Board, Kuehne Logistics University, Germany

2018 - Current

Full Professor (Honorary/Visiting), Technische Universiteit Eindhoven, School of Industrial Engineering, Group of Operations Planning, Accounting, and Control

2003 – 2017

Full Professor, Technische Universiteit Eindhoven, School of Industrial Engineering (prior name: Department of Technology Management), Group of Operations Planning, Accounting, and Control, chair “Operations Planning and Control”. Member of the BETA Research School for Operations Management and Logistics

2014 – 2017

Dean, Graduate School, Technische Universiteit Eindhoven

2014

Director, Stan Ackermans Institute (SAI), Technische Universiteit Eindhoven

2005

Visiting Fellow, National University of Singapore and Singapore Management University

2014 – 2017 Director, 4TU-SAI, Federation of Technical Universities in the Netherlands (4TU)
2006 – 2013 Program Director, (2-year) MSc program in Operations Management & Logistics
2012 Interim chairman, unit (Capaciteitsgroep) Operations Planning, Accounting and Control
2011Visiting Professor, Massachusetts Institute of Technology, Center for Transportation and Logistics, Engineering Systems Division
2006 Interim Program Director, MSc program in Innovation Management
2003 – 2006 Program Director, Industrial Engineering Programs, Department of Technology Management, Technische Universiteit Eindhoven
2000 – 2003 Associate Professor, Technische Universiteit Eindhoven, Department of Technology Management, Subdepartment of Operations Planning and Control, chair “Production Control in Process Industries”
2003 Visiting Scholar, The John E. Anderson Graduate School of Management, University of California at Los Angeles (U.S.A.)
1996 – 1999 Assistant Professor, Technische Universiteit Eindhoven, Department of Technology Management, Subdepartment of Operations Planning and Control
1993 – 1996 Research Fellow, Royal Netherlands Academy of Sciences; as such employed at Technische Universiteit Eindhoven
1995 – 1996 Visiting Fulbright Scholar, Stanford University (U.S.A.), Department of Industrial Engineering and Engineering Management
1989 – 1993 Research Assistant (PhD Candidate), Technische Universiteit Eindhoven
1991 Visiting Researcher / Lecturer, Clemson University (U.S.A.), Department of Management
1989 - 1993 Doctorate (PhD) / Technische Universiteit Eindhoven
1984 - 1989 MSc in Industrial Engineering & Management Science / Technische Universiteit Eindhoven