Doctoral Research in Marketing

Abstract

The marketing group at Rotterdam School of Management, Erasmus University seeks highly motivated PhD students looking to study topics in marketing, who aim to specialize either in the domain of quantitative marketing or consumer behavior. Our group is unique in the Netherlands with both scholars focusing on developing and applying state-of-the-art methodologies from the fields of statistics, economics, and machine learning, as well as scholars focusing on consumer behavior research that is deeply embedded in both theory and practice. Our faculty combines our methodological expertise with a deep understanding of the challenges businesses face. As part of a business school, we have strong ties with industry (profit and nonprofit) and government that allow our research to have direct societal impact. Strong applicants in the domain of quantitative marketing typically have backgrounds in computer science, statistics or econometrics. Strong applicants in the domain of consumer behavior typically have a background in psychology, business, statistics, or a related field. Strong applicants are typically looking to pursue careers as world-class academic researchers. Students define and execute their own projects in consultation with their advisers and thus need creativity, self-direction, and a passion for scientific research. We are looking for candidates that are equally interested in solid academic research and in addressing real-world problems.

Keywords

Machine Learning, Reinforcement Learning, Econometrics, Empirical IO, Behavioral Economics, Consumer behavior, Psychology, Judgement and decision making, Attitude formation and change, Preference formation and measurement, Marketplace morality, Technology

Topic

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, open-source software), and host regular seminars and visits to encourage knowledge exchange with other top schools in the world. Every year, we host a PhD day during which the students present their work and receive ample feedback. The group is diverse (in terms of research interests and cultural background), collaborative, and collegial.

Our PhD program seeks to train the next generation of marketing academics. We want our students to maximize their potential and become independent marketing scholars. We expect students to become experts in a specific domain of choice and define a research agenda around a topic of their choosing. As such, PhD positions in our group are open and students have the opportunity to collaborate with several faculty members when possible. The supervisory team will be formed considering the student’s research interests.

This vacancy targets two types of candidates: candidates interested in using or developing quantitative approaches to tackle real-world challenges based on advanced machine learning and other statistical methods and candidates interested in the field of consumer behavior. The application is not limited to a specific topic within this domain. Instead, the PhD candidate will define a research agenda around a topic of their choosing based on their own expertise, interests and fit with one or several of our faculty members. As such, PhD positions in our group are open. During their years of study, students define and execute their own projects. They do this in consultation with their advisers, but also work with other faculty, including those at other institutes.

Our quantitatively oriented faculty work on 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).

Our consumer behavior oriented faculty work on topics such as how advertising works psychologically (Steven Sweldens), judgment and decision making (Gabriele Paolacci), self-control, goal pursuit 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).

PhD students in our department receive excellent training. In addition to standard required course work, students working in the domain of quantitative marketing typically take courses in machine learning, (micro)economics, statistics, causal inference, econometrics, and seminars in quantitative marketing; students working in the domain of consumer behavior typically take courses in experimental design and statistics, and seminars in consumer behavior and psychology, both internally and externally. The exact portfolio of courses is chosen in consultation with the advisers.

Note: Applicants are asked to explicitly indicate in their application whether they want to work on quantitative marketing research or consumer behavior research. Those seeking to work at the intersection of consumer behavior and another discipline (quantitative marketing and/or neuroscience) should also indicate this preference in their application and discuss their motivation for interdisciplinary research.

Approach

The PhD student will work in close collaboration with the team of advisers and other faculty on tasks that include:

• Identifying novel research questions based on real-world phenomena.  
• Understanding the theoretical foundations and state-of-the-art models in marketing science, economics, psychology, and computer science literatures relevant to understanding the phenomena.
• Identifying the fundamental variables, trade-offs and relationships that are most important to studying the phenomena and formalizing them in a measurement model.
• Developing and coding the appropriate algorithms and methods that implement the novel concepts and models (Quantitative candidates).
• Gathering experimental or observational data to test hypotheses or highlight the strength and boundaries of the proposed methods.
• Identifying the critical assumptions needed to draw inferences from empirical results.
• Writing computer code to analyse experimental or secondary data according the best practices and tools in the relative sub-domain, including versioning (e.g., GitHub), pre-registration, data sharing and open science (e.g., Figshare).
• Presenting research findings at international conferences, in our PhD day and brownbag seminars.
• Writing up findings for publication in international journals.
• Attending classes and seminars (including those offered at other universities) to further develop thinking and research skills.
• Participating in and contributing to departmental research functions (PhD Day, research seminars, weekly research meetings).
• Teaching students (to a limited degree).

Through workshops, research seminars, applied and theoretical research with faculty, and seminars on key disciplines that provide the foundations of the marketing discipline (statistics, economics, psychology), the PhD student will gain the requisite experience for independent work.

Students have access to world-class research facilities:

• Erasmus Behavioral Lab provides facilities to conduct high-quality research, including a state-of-the-art virtual reality (VR) lab, sound-insulated cubicles, group labs, video labs, and facilities for eye tracking, EEG/ERP, facial coding, and hormone-administration studies.
• High-performance computing is available to researchers via SURFSara (a Dutch consortium for scientific computing).
• Excellent research funding

Required profile

We seek candidates with the following qualities:

• Intellectual curiosity, drive, eagerness to learn, and openness to criticism and other perspectives
• Strong motivation to pursue an international career as a leading scholar
• Strong commitment to methodological rigor and scientific integrity
• Strong passion for real-world problems faced by different types of organizations
• Excellent speaking and writing ability in fluent English, ideally with experience writing for a scientific audience
• Willingness and motivation to independently formulate research projects and carry them through to completion
• Excellent organizational skills
• Strong motivation to pursue an international career as a leading scholar
• Experience with conducting experimental research with human participants (consumer behavior profile)
• Masters’ degree (preferably a Research Master´s or MPhil degree) in one of the following fields: computer science, data science, operations research, economics, econometrics, psychology, statistics, management, or marketing. 
• The ideal candidate should also have some experience in programming (e.g., R, Python, Julia, Scala, Java, or C++) and in data analysis, management, preparation, and visualization, ideally as part of at least one end-to-end data science project.

Interdisciplinary focus:

One feature that sets our group apart from others is the tight collaboration between quantitative faculty (trained primarily in machine learning, operations research and economics; e.g., Jason Roos and Alina Ferecatu) and behavioral faculty (e.g., trained primarily in psychology or neuroscience; e.g., Dan Schley and Antonia Krefeld-Schwalb). Thus, we are also explicitly inviting applications of students who would like to work at the intersection of quantitative marketing and consumer behavior. In this fits your profile / interests, we encourage you  to explicitly mention it in your application (e.g., in the motivation letter and/or research statements).

Required by ERIM

All application documents required by ERIM can be found here.

If you have any questions about the formal admission requirements, please contact the ERIM doctoral office: phdadmissions@erim.eur.nl or Dr. Mirjam Tuk (tuk@rsm.nl).

Note: In November, we offer our PhD Virtual Open House Day. If you are interested in our PhD program and consider applying, we invite you to join us on November 28 from 4 pm to 5.30 pm CET OR on November 29 from 10 am to 11.30 am CET. In these info sessions we provide you with lots of information on our PhD program, department, and school. You will also get to know some of our faculty members and current PhD students, hear them talk about their research, and have the chance to ask questions.

Interested? Then please register here or use this QR code to register:

(Registration deadline: November 21).

Expected output

You will generate research that can be published in top-tier peer-reviewed journals in marketing, such as the Journal of Marketing Research, Journal of Consumer Research, Marketing Science, and Journal of Marketing. The research group at RSM has a strong record of publishing in these and other top journals in related fields, including Management, Psychology, Neuroscience, and Economics. The final results of the PhD project are published in a PhD dissertation, and most marketing PhD dissertations at RSM find their way into top journals. In addition, we strongly encourage our members to publish their codes on open-science platforms and create packages to generate more impact and adhere to the principle of Open Science.

Cooperation

To strengthen your international research network and complement your time at RSM, you may receive funding for a 3- to 6-month research visit. Past visits have included Stanford, Wharton, Chicago, Columbia, Harvard, Colorado, Cornell, and UCLA. We also strongly encourage collaboration with our business partners who are active in multiple domains (digital, retail, consumer goods, nonprofits, B2B, fintech, etc.).

Societal relevance

Students are encouraged to pursue topics that not only improve the practice of marketing, but also consumer or societal well-being, and thus align closely with the school’s mission to be a force for positive change in the world.

Scientific relevance

PhD research should be of the highest quality, carried out with scientific rigor and the utmost integrity. The department values openness and encourages students to embrace the principles and tools of open science (e.g., making code and data available to others and pre-registering experiments). The marketing group conducts research in our core field of marketing, as well as related disciplines such as management, psychology, judgment and decision-making, neuroscience, economics, and statistics. Our diversity and interdisciplinarity make the department a lively, creative, and intellectually stimulating place to conduct research.

Literature references & data sources

Please refer to the web pages for individual faculty members (https://www.rsm.nl/research/departments/marketing-management/faculty/) for more information about their current research interests. You may also refer to our RSM Discovery section (see here https://discovery.rsm.nl/researchers/). It offers a collection of articles and videos that our faculty (and those from other departments) have created about their research.

You may also look at the work done by several expert practices at ECDA:

• Trial Design and Experimentation: https://ecda.eur.nl/expert-practices/trial-design-experimentation/
• Virtual and Augmented Reality: https://ecda.eur.nl/expert-practices/virtual-augmented-reality/
• Customer Analytics: https://ecda.eur.nl/expert-practices/customer-analytics/
• Psychology of AI: https://ecda.eur.nl/expert-practices/psychology-of-ai/

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.