PhD position in Supply Chain Management

Abstract

The aim of the ERIM Business Processes, Logistics, and Information Systems (LIS), Supply Chain Management (SCM) section doctoral program is to be at the forefront of developments in its domain. We are committed to making major contributions to management science by nurturing the next generation of supply chain scholars who can advance methodological and theoretical knowledge of supply chains.

Candidates will become active members of the large and diverse group of researchers at the SCM section. This group is one of the largest of its kind with more than 30 faculty members. It consistently ranks amongst the top-3 in Europe in terms of research output. Candidates are expected to contribute to the group's world-class research and teaching, and thereby to management science and management practice in logistics and supply chain management.

Keywords

Supply Chain Management

Topic

Below you will find a list of topics the SCM section currently works on. This is not a complete list and topics are not mutually exclusive. In your application we ask you to identify three topics that appeal to you most. We use this selection to establish an initial understanding of your interests. Your selection will not dictate what you will be working on if you join our group. For each topic a member of faculty is identified. Feel free to reach out to this person before you submit your application. Note that these are only meant as illustrations—in total the SCM section will fill a maximum of one PhD positions this year that can be on any of these topics.

Machine learning for stochastic last-mile deliveries

In recent years, stochasticity has received increasing attention in logistics optimization. In last-mile deliveries, in particular vehicle routing, solving stochastic problems efficiently has been of increasing importance due to the ever-growing size of the global supply chain. Most ways to model the stochasticity involve introducing nonlinear terms in the mathematical formulation. It is your goal to investigate how well machine learning methodology can be used to approximate these nonlinear terms and accelerate solving such problems, at the cost of some optimality guarantees. The trade-offs between speed and optimality could be investigated as well. Faculty to contact: Dr. Ymro Hoogendoorn.

Data-Driven Retail Operations

This project explores how data and advanced analytics can enhance retail operations, with particular focus on omnichannel retailing, the role of small-format stores, and evolving consumer behavior. Research directions may include optimizing assortment decisions, designing seamless cross-channel experiences, and understanding how consumers navigate hybrid online–offline journeys. The project aims to combine operations management perspectives with data-driven insights and behavioral modeling to inform strategic and operational decisions in modern retail contexts. Faculty to contact: Dr. Mert Cetin.

Inclusive Decision-Making in Operations

This project investigates how diversity-related factors influence decision-making in operational contexts, using behavioral lab experiments and discrete choice modeling. The aim is to understand how consumers, employees, or partners respond to signals and attributes related to gender, LGBTQ+ inclusion, or broader diversity cues when making service, product, or supply choices. For example, prior work has examined how inclusivity indicators affect service provider selection, and future studies could explore how representation, language, or identity cues shape preferences. Insights from this research can inform the design of more inclusive and effective operational strategies and systems. Faculty to contact: Mert Cetin.

Collaborative Value Creation in Circular Economy Ecosystems

The transition to a Circular Economy (CE) increasingly demands collaboration across entire value chains, where stakeholders jointly create value within interconnected ecosystems. While recent CE initiatives emphasize ecosystem-wide engagement, academic research still tends to focus on isolated products, firms, or industries. This narrow lens overlooks the intricate interdependencies among actors and provides limited empirical understanding of collaboration at the ecosystem level. This PhD project aims to address this gap by exploring how stakeholders co-create value in CE ecosystems, contributing to both theory and practice in sustainable business transformation. Faculty to contact: Dr. Koen Dittrich.

Designing Circular Business Models

The transition from linear to circular business models (CBMs) is essential for sustainability, yet designing and evaluating these models remains complex. This PhD research will investigate key design principles, success factors, and evaluation frameworks for CBMs across industries. It will explore how businesses integrate circular strategies—such as product-as-a-service, remanufacturing, and closed-loop supply chains—while balancing economic viability and environmental impact. Faculty to contact: Dr. Koen Dittrich.

Estimating true customer demand in competitive markets

Estimating true customer demand in competitive markets is challenging when key information—such as competitor sales, no-purchases, or capacity decisions—is unobservable, and when data is shaped by firms’ own pricing and assortment optimizations, creating endogeneity. Traditional discrete-choice and market share–based methods often fail under these constraints. Recent work has begun developing robust estimation frameworks that integrate structural modeling, machine learning, and competitive intelligence to infer demand using partial or aggregated signals. While early results are promising, important questions remain: Which partial data is sufficient? Can endogeneity be addressed without instruments? How can we reliably recover preferences when the observed data itself is optimized? Faculty to contact: Dr. Muge Tekin.

Flexibility in platform operations

Flexibility is a core concept in operations management, valued for its ability to mitigate demand uncertainty and enhance system performance. This project aims to investigate the value of flexibility and explore how it can be effectively leveraged across emerging online platforms. Applications will span a range of settings, including—but not limited to—retail, grocery delivery, service matching, and humanitarian fundraising. The objective is to model key trade-offs and develop practical, data-driven strategies that support real-time decision-making. Faculty to contact: Dr. Yeqing Zhou.

Approach

The research at ERIM-LIS is interdisciplinary and multi-methodological. Some examples of methods we apply in our research are mathematical modelling, optimization, statistical data analysis, surveys, case studies, and experiments.

Required profile

Required by ERIM

All application documents required by ERIM can be found here.

Expected output

Together with their supervisory team, we expect students to conduct research that is publishable in journals classified by ERIM as Primary Star (P*), or Primary (P).

Cooperation

We value being based in Rotterdam—a major logistics hub that is an important gateway to Europe. We intensely cooperate with organizations in our ecosystem. Examples of partner organizations are Albert Heijn, CoolBlue, DHL, DSM, Philips, Port of Rotterdam, Doctors without Borders, and Netherlands Railways. Our networks provide ample opportunities for cooperation.

PhD candidates are actively encouraged to undertake a research visit to one of the universities in our group’s network, such as MIT, INSEAD, University of Bologna, NYU Stern, University of Michigan, Northwestern University, and HEC Montreal.

Societal relevance

In line with RSM’s mission, we conduct research that contributes to positive change in our field of supply chain management.

Scientific relevance

As a group we have a solid track record of publishing our research in highly ranked management journals. In addition to undertaking research visits, we actively encourage participation in all major international conferences, and support PhD candidates in their travel to disseminate their research findings.

We commit to equipping candidates for the pursuit of a career at a renowned academic institute, and strongly encourage students who have the ambition to pursue an academic career to apply.

Employment conditions

ERIM offers fully-funded and salaried PhD positions, which means that accepted PhD candidates become employees (promovendi) of Erasmus University Rotterdam. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (CAO).

Erasmus University Rotterdam aspires to be an equitable and inclusive community. We nurture an open culture, where everyone is supported to fulfil their full potential. We see inclusivity of talent as the basis of our successes, and the diversity of perspectives and people as a highly valued outcome. EUR provides equal opportunities to all employees and applicants regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, functional impairment, citizenship, or any other aspect which makes them unique. We look forward to welcoming you to our community.

Contact information

For questions regarding the PhD application and selection procedure, please check the Admissions or send us an e-mail via phdadmissions@erim.eur.nl.