Recruitment paused PhD positions in Supply Chain Management

Reference:
ERIM PhD RSM 2018 LIS_SCM

Abstract

The ERIM-LIS (Business Processes, Logistics, and Information Systems) research program consists of three main research themes: (i) Supply Chain Management; (ii) Business Information Management, and (iii) Innovation Management. The reader of this project description on Supply Chain Management is encouraged to visit the other project descriptions within the LIS-program as well. 


The aim of the ERIM-LIS research group is to be at the forefront of the developments in its domain and to make major contributions both to management science and to management practice. The research aims to contribute significantly to the leading role of the Netherlands as a gateway to Europe and as an innovative country. Much of the research is inspired by business challenges, and by the new opportunities of innovative information and communication systems, and technologies. 

The research in the ERIM-LIS program is inter-disciplinary, integrating both quantitative and empirical research methods. Around the main research themes several research centres have been built (e.g. Smart Port, Behavioural Operations, Closed Loop Supply Chains, Optimization in Public Transport, Procurement, and Future Energy Business), which are used to focus the research, to acquire external funding, and to disseminate the research findings.

Keywords

Logistics, Supply Chain Management, Transportation, Inventories, Port and Terminal Operations, Sustainability, Purchasing and Supply Management, Public Transport, Behavioral Operations Management.

Topic

Subtheme: Supply Chain Management

The research on Supply Chain Management focuses on the management of complete supply chains, rather than on individual parts of the supply chain. This theme covers topics such as collaboration and information exchange in supply chains and contracting. Also closed loop supply chains, involving both forward logistics and reverse logistics, are studied. The research methods are either empirical, or based on mathematical modelling.

Example projects are the following:
Environmental and social footprint validation by global supply chain visibility

Customers are progressively interested in the “environmental and social footprint” of products and services. Example footprints are the amount of emissions and the quality of labour conditions throughout the complete lifecycle of products and services. Supply chain visibility enables managers to make informed decisions in support of credible footprints. Also, footprint labels can be used to guide customer purchases. However, especially for complex supply chains and products and services, supply chain visibility and the validation of certificates and labels is difficult to achieve. This research aims to develop methods to study mechanisms for credible footprints in cases where firms need to comply with regulations, and in cases where firms participate in voluntary programs. The research may incorporate the use of enabling information technologies, such as reputation systems in digital social networks and block-chain distributed systems. Quantitative methods may prove useful to estimate the value of information created by informed decisions that improve environmental and social footprint.

For further information: prof. dr. Rob Zuidwijk: rzuidwijk@rsm.nl


Demand forecasting in humanitarian logistics

Humanitarian relief operations are known for their involvement in combatting the negative consequences of unforeseen natural disasters and human conflict. Information systems in these extreme circumstances are often insufficient to gather the required data to even begin assessing the performance of these logistics operations. However, a large portion of the activities of humanitarian relief organizations consists of long term commitments, for instance hospitals and field projects. Humanitarian organizations, like MSF, are increasingly aware of the importance of principled approaches to humanitarian logistics, and have massively invested in systems to record medical consumption under sometimes harsh field conditions. At the same time, important advancements can be observed in the domain of demand forecasting, a central activity in logistics. New techniques are being developed to handle the hierarchical nature of many supply chain activities, which tend to yield dramatic improvements in forecast accuracy at various organizational levels and related inventory management. The objective of this project is to explore the potential of these new techniques in the context of humanitarian logistics, thus contributing to the efficiency and effectiveness of humanitarian relief operations. 

Keywords: humanitarian logistics, hierarchical demand forecasting. Further information: dr Jan van Dalen (jdalen@rsm.nl), dr Erwin van der Laan (elaan@rsm.nl) 

•     Risk and security management in global supply chains

Globalization of supply chains provided firms with benefits such as achieving cost efficiency but at the same time it has exposed them to hazards such as violation of intellectual property rights, disruption vulnerabilities, infiltrations of adversaries into legitimate channels, counterfeiting, etc. In this research, we focus on mechanisms to mitigate risks arising from the globalization of supply chains. It has been advocated that risk management in global supply chains calls for an intense collaboration between public authorities and private companies. It is mainly because the information required to detect and manage risks lie at the private parties while the intelligence and resources are owned by public organizations such as customs. One central question arising is what the efficient mechanisms are to initiate and facilitate this collaboration.

 For further information:  dr. Morteza Pourakbar: mpourakbar@rsm.nl


Buyer-supplier relationship dynamics

Coordination in supply chains is essential to improve performance outcomes. Many questions however remain as to how this should be done. At what point in a new service or product development process should suppliers be involved? How much information should be shared? Is (and should) dependency between buyer and supplier always be symmetric? What are the implications of coordinating too little, or too much? How do the three main dimensions of buyer-supplier ties (structural, relational, and cognitive) interact? What developmental trajectory do relationships go through? These questions can be answered in different empirical settings, using different methodologies (case studies, complexity modelling, secondary data analysis, to name a few) The choice of setting and methodology for this project is up to the candidate.

For further information: dr. Merieke Stevens: mstevens@rsm.nl 

 


Subtheme: Terminal Optimization

The research on Terminal Optimization focuses on developing theories, and quantitative optimization models and tools to improve the design, operations, and planning and control of terminal processes. Such terminals include warehouses, port and railway terminals, and trans-shipment centres with the related material handling systems. Our research resulted into insight into the relations between layout, storage strategies, order batching, and picker routing methods. The developed design principles (layout, system selection) are currently used by several warehouse design companies.

An example project is the following:

Next generation robotic warehouses

New warehouses use more and more robotic technologies in storage, order picking, roll container stacking and internal transport. Such new robotic warehouses require sophisticated models to adequately describe, predict, and schedule picking, transporting, sorting, and buffering processes. Such models can be deterministic (e.g. scheduling based), or stochastic (using e.g. queuing networks) and have proved their value in supporting practical operations and decision making in, for example, warehouse layout, order scheduling, and product storage. In this project we aim to make a big leap forward in the development of models for such robotic systems. The proposal focusses on the study of stand-alone components, such as storage, retrieval, stacking and transport systems, as well as complete warehousing concepts, such as dynamic picking systems, or combinations of picking and sorting systems in interaction with manual processes. Ultimately we envision a hierarchical modelling approach: the results of the models will provide input to the optimization of the warehouse design. For further information: prof. dr. René B.M. de Koster: rkoster@rsm.nl.

Subtheme: Transportation Management

The aim of the research on Transportation Management is to improve the performance of passenger and cargo transportation systems, usually based on the application of simulation and mathematical optimization methods. The range of applications is wide. (1) Within the SmartPort program, research is carried out on international transportation networks, in particular multimodal land transport, and the role of information therein; (2) Urban distribution and last mile delivery transportation receive attention, including the use of crowd sourcing opportunities and shared economy principles; (3) Due to our close cooperation with Netherlands Railways (NS), much research focuses on optimization of public transportation. Specific topics of this subtheme include robustness and reliability of transportation systems, fleet composition, city distribution, the effective use of information, and revenue management.

For further information: Please contact dr. Niels Agatz (nagtaz@rsm.nl) for Urban distribution, dr. Marie Schmidt (schmidt2@rsm.nl) for Public transportation, prof. dr. Rob Zuidwijk (rzuidwijk@rsm.nl) for SmartPort.

Example projects in this subtheme are the following:


• Port performance and (big) data analytics

Sea ports are natural intersections of various logistics networks, involving road, rail as well as waterways. The often intense use of this infrastructure as well as environmental concerns have led to substantive efforts to enhance the efficiency of logistics operations and promote intermodal transport, where cargo transport is moved from land to water in order to reduce road haulage and make better use of inland waterways. Moreover, these efforts are motivated by competition between ports. Carriers and shippers often have a choice as to which port to use for transport, and investors have a choice as to where to invest their capital. The huge interests, the complexity of operations involved, and the variety of stakeholders, emphasize the need for informedness as a basis for coordination, logistics decision making, and continued improvement of port performance. The increasing availability of open data about, e.g. road usage (loop detectors, weigh-in-motion) and ship movements (AIS), provide unprecedented means for decision support, the assessment of environmental impact, insight into the dynamic interaction between trade and infrastructure use, and the performance of port services. The actual use of these data, for this purpose, is however limited. The objective of this project is to explore the use of open data about port-related logistics activities to gain insight into the environmental, logistics and service performance of ports. The outcomes of the project will contribute to the growing body of literature about port performance and the environmental impact of shipping, as well as to regulation by port authorities to combat operational inefficiencies, like congestion, and to enhance port services.

Keywords: port performance, (big) data analytics, AIS data.For further information: dr. Jan van Dalen (jdalen@rsm.nl), prof. dr. Rob Zuidwijk (rzuidwijk@rsm.nl)

Making drone delivery work 

The fast and cost-efficient delivery of goods ordered online is associated with many logistical challenges. The so called “last mile” is widely considered as the least-efficient and most difficult step of the e-fulfilment process. Therefore, companies are continuously looking for new ways to improve their last-mile operations. A technology-enabled opportunity that recently has received much attention is the use of autonomous drones to make deliveries. One of the key advantages of a delivery drone as compared to a regular delivery vehicle is that a drone is fast and can fly over congested roads without delay.  In order to reap the benefits of new autonomous technology for transportation and logistics, efficient planning tools are needed to integrate the use of regular delivery vehicles and autonomous drones. This research project aims to develop new models and solution methods to support and facilitate this integration. While there has been much research about the use of autonomous drones in automotive and aeronautic engineering, and many millions invested in tests and trails by logistics service providers and start-ups, the concept has not yet received much attention from the academic community in transportation and logistics planning. This suggests that the area is both practically relevant and academically innovative. 

For further information please contact dr. Niels Agatz (nagatz@rsm.nl) or dr. Marie Schmidt (schmidt2@rsm.nl)


Subtheme: Behavioural Operations

Our research in Behavioural Operations Management focuses on the impact of human factors on company performance, next to planning and control systems. We study the role of humans (managers, workers) in operational processes, in particular the effects of systems design, organizational climate and leadership on worker behaviour, well-being and performance, including innovation. We study leader behaviour, decision making, and implied worker behaviour in interaction with systems, in contexts relevant to society.

Example projects in this subtheme are the following:

• Team decision making and performance: A behavioural study of the Sales & Operations Planning process.

The Operations Management (OM) field witnesses a rapidly growing interest in behavioral research, but virtually all studies focus on individual decision-making. How teams make decisions is largely ignored – which is remarkable because operations and supply chain management decisions (sales & operations planning processes) are typically made in teams. Our research focuses on identification and analysis of cognitive and motivational biases that play out in sales & operations planning, including regulatory focus (a yet uncharted area in behavioral OM) and investigates the power of team reflexivity – the extent to which teams reflect on and modify their functioning – to mitigate such biases.

For further information: prof. dr. M. Schippers: mschippers@rsm.nl.

Online goal-setting intervention enhances student retention and academic performance.

The current project will use an online intervention that has shown to be been extremely successful in raising academic performance and retention rate of students. Especially clearly defined and articulated goals give students purpose and meaning. In the current project, we aim to advance our understanding of these effects by investigating (a) specific changes in student behavior as a result of participating in this program and (b) the testing and implementation of an advanced goal-setting app. 

For further information: prof. dr. M. Schippers: mschippers@rsm.nl.


Behavioral company performance.

It has been demonstrated in several environments that leadership and employee behavior have a direct impact on operations performance, beyond traditional OM concepts, like planning and control. We aim to study the impact of leadership in operational environments (in particular warehouses, restaurants, road transport), where managers and employees can make a difference in performance on safety, quality and productivity. The methods will include experimentation, and company surveys.

For further information: prof. dr. René B.M. de Koster: rkoster@rsm.nl. 


Cobotics: Human-robot performance in Industry 4.0.

In new production facilities and warehouses, resources (humans, machines) and objects (products, locations) are all connected and able to communicate. Such facilities are called ‘industry 4.0’ facilities. In such automated and robotic environments, humans still play a role, sometimes with help of robots; robots and humans must work together. We wish to study both in practice and in the (behavioral) lab, which type of persons (i.e. which behavioural traits) perform best under which circumstances and incentives, and how this can lead to company performance. Example projects that can be seen in practice include (1) order-picking robots with humans, (2) transport automated-guided vehicles (AGVs) cooperating with humans, or (3) pallet-stacking robots cooperating with humans.

For further information: prof. dr. René B.M. de Koster: rkoster@rsm.nl. 

Decision Support system in behavioral Inventory management.

Business Analytics is growing very fast enabling more sophisticated decision support tools using big data and machine learning. However, decisions are still mostly finally done by humans. Especially forecasting and inventory optimization tools develop more into “black boxes” and literature has shown that human decision makers show behavioral biases interacting with computerized agents, such as algorithm aversion. This research analyzes the biases human decision makers show in the interaction with inventory related decision support tools and optimizes the design of such tools to account for theses biases.

For further information: Dr. Michael Becker-Peth: m.beckerpeth@rsm.nl.

Supervisory Team

Jan Dul
Professor of Technology and Human Factors
  • Promotor
René de Koster
Professor of Logistics and Operations Management
  • Promotor
Erik van Raaij
Professor of Purchasing & Supply Management in Healthcare
  • Promotor
Michaéla Schippers
Endowed Professor in Behaviour and Performance Management
  • Promotor
Finn Wynstra
Professor of Purchasing and Supply Management
  • Promotor
Rob Zuidwijk
Endowed Professor of Ports in Global Networks
  • Promotor
Wilco van den Heuvel
Associate Professor of Opereations Research
  • External Member Supervisory Team