PhD projects

in Marketing Management

The marketing group at Rotterdam School of Management (RSM) ranks among the best in the world. Our members publish their research in top journals in marketing as well as related fields. They deeply care about open science practices (e.g., data sharing and open-source software), and frequently host seminars to encourage knowledge exchange. The group is diverse (in terms of research interests and cultural background), collaborative, and collegial.

PhD Topics

Our faculty members can supervise PhD students on a broad range of topics, typically divided in three sub-domains: Quantitative Marketing, Consumer Behaviour, or Consumer Neuroscience. Several faculty members work as the intersection of two of these sub-disciplines (e.g., consumer behavior and quantitative marketing), which enables us to cater to students interested in more interdisciplinary research.

Quantitative Marketing:

The faculty in the quantitative group in our department work on a wide range of topics, such as design of multi-armed bandits and reinforcement learning models with applications to recommendation systems and clinical trials (Gui Liberali), virtual / augmented / mixed reality (Yvonne van Everdingen), digital platform markets (David Kusterer), privacy (Gilian Ponte), behavioral economics (Alina Ferecatu), causal inference (Jason Roos), marketing strategy (Gerrit van Bruggen), consumer eye tracking (Ana Martinovici), deep learning (Sebastian Gabel), consumer and firm networks (Xi Chen), customer analytics (Aurélie Lemmens), consumer learning (Maciej Szymanowski) and quantitative modelling approaches to predict the psychological processes involved in consumer judgments and decisions (Antonia Krefeld-Schwalb and Dan Schley).

Consumer Behavior:

Our faculty members in consumer behavior work on a wide range of topics, such as how advertising works psychologically (Steven Sweldens), judgment and decision making (Gabriele Paolacci), self-control and consumption (Mirjam Tuk), how technology augments behavior Shwetha Mariadassou and Anne-Kathrin Klesse), numerical processing (Dan Schley and Christophe Lembregts), biological influences on consumption and goal pursuit (Bram Van den Bergh), how to measure consumer preferences (Antonia Krefeld-Schwalb), pro-social behavior, social credit, and consumer advocacy (Alex Genevsky), marketplace morality (Johannes Boegershausen), and pro-societal consumer interventions (Romain Cadario).

Consumer Neuroscience:

Within the department, researchers at the Center for Neuroeconomics (Maarten van Boksem, Ale Smidts, and Alexander Genevsky) work on a wide range of topics in decision neuroscience such as understanding the neurological basis of emotions, social conformity, dishonesty, charitable giving, consumer judgments and predicting population-level outcomes from neural data.

Leveraging work experience 

Regardless of the specific topic that a PhD student likes to work on, the department sees a lot of value in supervising students who would like to leverage their work experience (e.g., from their current profession) to collect practically relevant data and/or conduct (field) experiments that can provide the empirical basis for their PhD project.

The PhD student’s task will be to:

  • identify novel research questions based on real-world phenomena and/or extant theory.
  • review existing literature and theories to build a coherent theoretical foundation for his/her own research.
  • identify the fundamental variables and relationships that are most important to studying the phenomena at hand and formalize them in a measurement model or set of experimental hypotheses.
  • gather experimental or observational data to test hypotheses or measure phenomena.
  • identify the critical assumptions needed to draw inferences from empirical results.
  • write computer code to analyze experimental or secondary data.
  • present research findings at international conferences.
  • write up findings for publication in international journals.
  • participate in and contribute to departmental research functions (PhD Day, research seminars, weekly research meetings)

Well-connected faculty members

Our faculty members possess excellent networks and have collaborators at top institutions worldwide. Further, several of our faculty members are leading expert practices at the Erasmus Centre for Data Analytics (ECDA). These expert practices fulfil the purpose to bring together academics from various disciplines and practitioners to exchange knowledge and collaborate on research questions surrounding specific topics. More information for each of these expert practices can be found here.   

More information on our faculty members can be found here.