The faculty of the Department of Marketing Management connects through the many projects and initiatives of the ERIM research programme Marketing (MKT). Our work is dedicated to exploring new knowledge from complex advances in theory to efficient applications of scientific principles for practical application. The faculty publish research not only in top marketing journals but are important contributors in related fields like psychology, economics, and neuroscience.
Centres, Experts and Projects
The academics of the Department of Marketing Management are engaged in countless research projects in partnership with business, and with other international scholars.
These experts also head up, or work within, several significant Centres of Expertise:
Economics, psychology, and neuroscience are converging into a single discipline with the ultimate aim of providing a general theory of human behavior: Neuroeconomics. The work of the Erasmus Centre for Neuroeconomics is to understand the processes that connect sensation and action by revealing the neurobiological mechanisms that underlie decision-making.
The goal of eCode is to develop and disseminate machine learning and optimization methods, concepts, and tools that help firms improve the way they use the Internet to connect and interact with their consumers. This includes new ways to design and optimize digital experiments, new multi-armed bandits algorithms (such as website morphing), randomized controlled trials of marketing methods/tools, online field experiments, and behavioral analytics. We provide scientific support to the Erasmus Centre for Data Analytics.
The emergence of information and data technologies, together with the sophistication of tools in data analytics, have led to a radical shift in the way marketing operations are run. The focus of companies has been shifted away from product-centric approaches and mass marketing campaigns to customer-centric campaigns tailored to the needs and wants of each individual customer. Customer-centric campaigns target a well-chosen subset of customers, at a well-chosen time, and with a well-chosen incentive. At their core, they require strong data analytics tools in order to be able to predict each customer’s behavior and derive optimal marketing interventions. The Customer Analytics lab focuses on the development of predictive and prescriptive analytics to address these key challenges. Our team is involved in the design of new methodologies that can guide organizations in their customer-centric decision making.
New developments in machine learning have the potential to dramatically improve experimentation and clinical trials by making them more efficient, safe, and accessible. We develop and apply leading-edge clinical trial methods, such as multi-armed bandits and Bayesian adaptive designs, to help pharma companies and medical researchers with the statistical and methodological transition from RCTs to adaptive trials. Our researchers have robust statistical and methodological training that helps also other firms extract the most from their experiments and online investments, improving online and offline metrics and KPIs such as conversion and bouncing.
The Psychology of AI Lab explores the human side of AI and analytics. AI technology can create positive change only if companies truly recognize how AI solutions bring value to users, as well the impact of technology on its broader societal context. We help companies understand how to best design consumer AI experiences and address psychological barriers to adoption. The lab aims to be a world-leading center for behavioral science applications to AI, facilitate interactions between academia and industry, and disseminate and increase the impact of academic research.
The expert practice Virtual and Augmented Reality aims to bring together academic researchers from different disciplines (e.g., marketing, economics, operations and technology management, psychologists, and health care) and experts from practice (e.g., managers, business developers, psychologists) to jointly research the opportunities and challenges of these new technologies for a wide variety of contexts, such as business (real estate, entertainment, development and launch of new products), psychology (e.g., treatment of anxiety or eating-disorders, pain and stress reduction), medicine (before, during, and after surgeries), and education (e.g., virtual class rooms).
-
Celiktutan, B. (2025). Self-other differences in human-AI interactions and consumption. [Doctoral Thesis, Erasmus University Rotterdam]. Erasmus University Rotterdam (EUR).
-
Genevsky, A., & Boksem, M. (Accepted/In press). Applications in Consumer Neuroscience: Decoding and Neuroforecasting. In Neuroeconomics: Core Topics and Current Directions Springer Nature. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5001469
-
Krefeld-Schwalb, A., Hua, X., & Johnson, E. J. (2025). Measuring population heterogeneity requires heterogeneous populations. Proceedings of the National Academy of Sciences of the United States of America, 122(8), Article e2425536122. https://doi.org/10.1073/pnas.2425536122
-
GBD 2021 Upper Respiratory Infections and Otitis Media Collaborators (2025). Global, regional, and national burden of upper respiratory infections and otitis media, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021. The Lancet Infectious Diseases, 25(1), 36-51. https://doi.org/10.1016/S1473-3099(24)00430-4
-
Liberali, G., Boersma, E., Lingsma, H., Brugts, J., Dippel, D., Tijssen, J., & Hauser, J. (2025). Real-time adaptive randomization of clinical trials. Journal of Clinical Epidemiology, 178, Article 111612. https://doi.org/10.1016/j.jclinepi.2024.111612
-
Lenkovskaya, M., & Sweldens, S. (2025). How Numerical Cognition Explains Ambiguity Aversion. Journal of Consumer Research, 51(6), 1120-1143. https://doi.org/10.1093/jcr/ucae041
-
Kusterer, D. J., & Sliwka, D. (2025). Social Preferences and the Informativeness of Subjective Performance Evaluations. Management Science, 71(5), 4028-4048. https://doi.org/10.1287/mnsc.2022.02267
-
Hütter, M., & Sweldens, S. (2025). How People (Fail to) Control the Influence of Affective Stimuli on Attitudes. Journal of Personality and Social Psychology, 128(1), 38-60. https://doi.org/10.1037/pspa0000426
-
Genevsky, A., Tong, L., & Knutson, B. (2025). Neuroforecasting reveals generalizable components of choice. PNAS Nexus, 4(2), Article pgaf029. https://doi.org/10.1093/pnasnexus/pgaf029
-
Da Silva, A. A., Ferecatu, A., Vanhamme, J., Puntoni, S., & Souza e Silva, R. A. (2025). Enhancing B2B sustainability through customer training in product-service systems: A design science approach. Industrial Marketing Management, 125, 355-372. https://doi.org/10.1016/j.indmarman.2025.01.009
-
Cadario, R., Zimmermann, J., & Van den Bergh, B. (Accepted/In press). Beyond Opt-Out: How Presumed-Consent Language Shapes Persuasion. Journal of Marketing, Article 00222429251323885. https://doi.org/10.1177/00222429251323885
-
Cadario, R., Li, Y., & Klesse, A. K. (Accepted/In press). Bridging the Knowledge Gap: Mapping Carbon Emissions to Food Items Facilitates Choices of Plant-Based over Animal-Based Items. Appetite, 208, Article 107910. https://doi.org/10.1016/j.appet.2025.107910
-
Boegershausen, J., Cornil, Y., Yi, S., & Hardisty, D. J. (2025). On the persistent mischaracterization of Google and Facebook A/B tests: How to conduct and report online platform studies. International Journal of Research in Marketing. Advance online publication. https://doi.org/10.1016/j.ijresmar.2024.12.004
-
Acar, O. A., Klesse, A. K., Tuk, M., & Zhang, Y. (2025). Consumers Don’t Want AI to Seem Human. Harvard Business Review. https://hbr.org/2025/01/research-consumers-dont-want-ai-to-seem-human
-
Sweldens, S., Yue, T., Boegershausen, J., Laurelii, F., & Monnier, A., (2024). Renoon: Reinventing Shopping for Sustainable Fashion, 12 p. https://casecent.re/p/202128
-
van Rijn, L. (2024). Old habits die easily: Longitudinal studies on age-related consumer behavior changes. [Doctoral Thesis, Erasmus University Rotterdam]. Erasmus University Rotterdam (EUR).
-
van Everdingen, Y., & Martinovici, A. (2024). Buy refurbished! Join the race to mak the earth a better place. In Y. van Everdingen (Ed.), Insight into sustainable marketing and consumption: Topic of the year 2024 (7e editie ed., pp. 55-72). Data & Insights Network. https://datainsightsnetwork.nl/webshop/topic-2024/
-
Klesse, A. K., Zhang, Y., & Tuk, M. (2024). Algorithm Aversion. In Elgar Encyclopedia of Consumer Behavior (pp. 5-8). Edward Elgar Publishing. https://doi.org/10.4337/9781803926278.ch02
-
Zhang, Y., Tuk, M., & Klesse, A. K. (2024). Giving AI a Human Touch: Highlighting Human Input Increases the Perceived Helpfulness of Advice From AI Coaches. Journal of the Association for Consumer Research, 9(3), 344-356. https://doi.org/10.1086/730710
-
Wierenga, B., Szymanowski, M., & van Bruggen, G. H. (2024). DRIVERS OF MARKETING CAREER SUCCESS. Marketing Education Review, 34(1), 3-22. https://doi.org/10.1080/10528008.2023.2251950
-
Wang, Y., Jiang, Y., Liu, R., & Miao, M. (2024). A configurational analysis of the causes of the discontinuance behavior of augmented reality (AR) apps in e-commerce. Electronic Commerce Research and Applications, 63, Article 101355. https://doi.org/10.1016/j.elerap.2023.101355
-
Wang, Y., Zhu, J., Liu, R., & Jiang, Y. (2024). Enhancing recommendation acceptance: Resolving the personalization–privacy paradox in recommender systems: A privacy calculus perspective. International Journal of Information Management, 76, Article 102755. https://doi.org/10.1016/j.ijinfomgt.2024.102755
-
van Diepen, R., Boksem, M., & Smidts, A. (2024). Reliability of EEG metrics for assessing video advertisements. Journal of Advertising. Advance online publication. https://doi.org/10.1080/00913367.2024.2418109
-
Van den Bergh, B., Caprioli, S., & Fuchs, C. (2024). Why People Really Buy Upcycled Products. Harvard Business Review. https://hbr.org/2024/04/research-why-people-really-buy-upcycled-products
-
van Brussel, L., Boksem, M., Dietvorst, RC., & Smidts, A. (2024). Brain activity of professional investors signals future stock performance. Proceedings of the National Academy of Sciences of the United States of America, 121(16), e2307982121. Article e2307982121. https://doi.org/10.1073/pnas.2307982121
-
Ponte, G. R., Wieringa, J. E., Boot, T., & Verhoef, P. C. (2024). Where’s Waldo? A framework for quantifying the privacy-utility trade-off in marketing applications. International Journal of Research in Marketing, 41(3), 529-546. https://doi.org/10.1016/j.ijresmar.2024.05.003
-
Paolacci, G., & Andre, Q. (2024). Probabilistic Outcomes Are Valued Less in Expectation, Even Conditional on Their Realization. Management Science, 70(11), 7524-7536. https://doi.org/10.1287/mnsc.2021.02284
-
Molnar, A., & Paolacci, G. (2024). Competition increases the magnitude of dishonest reporting even when controlling for reward uncertainty. Scientific Reports, 14(1), Article 31980. https://doi.org/10.1038/s41598-024-83621-y
-
Mariadassou, S., Klesse, A. K., & Boegershausen, J. (2024). Averse to what: Consumer aversion to algorithmic labels, but not their outputs? Consumer aversion to algorithmic labels, but not their outputs? Current Opinion in Psychology, 58, Article 101839. https://doi.org/10.1016/j.copsyc.2024.101839
-
Loenneker, H. D., Buchanan, E. M., Martinovici, A., Primbs, M. A., Elsherif, M. M., Baker, B. J., Dudda, L. A., Đurđević, D. F., Mišić, K., Peetz, H. K., Röer, J. P., Schulze, L., Wagner, L., Wolska, J. K., Kührt, C., & Pronizius, E. (2024). We don't know what you did last summer. On the importance of transparent reporting of reaction time data pre-processing. Cortex, 172, 14-37. https://doi.org/10.1016/j.cortex.2023.11.012
-
Lembregts, C., & Cadario, R. (2024). Consumer-driven climate mitigation: Exploring barriers and solutions in studying higher mitigation potential behaviors. International Journal of Research in Marketing, 41(3), 513-528. https://doi.org/10.1016/j.ijresmar.2024.04.001
-
Lembregts, C., Schepers, J., & De Keyser, A. (2024). Is it as Bad as it Looks? Judgments of Quantitative Scores Depend on their Presentation Format. Journal of Marketing Research, 61(5), 937-954. https://doi.org/10.1177/00222437231193343
-
Krefeld-Schwalb, A., Sugerman, E. R., & Johnson, E. J. (2024). Exposing omitted moderators: Explaining why effect sizes differ in the social sciences. Proceedings of the National Academy of Sciences of the United States of America, 121(12), Article e2306281121. https://doi.org/10.1073/pnas.2306281121
-
Jaeger, B., Paolacci, G., & Boegershausen, J. (2024). Social Bias Blind Spots: Attractiveness Bias Is Seemingly Tolerated Because People Fail to Notice the Bias. Journal of Personality and Social Psychology.
-
Ho, J. Y., Eliashberg, J., Weinberg, C. B., & Wierenga, B. (2024). On enjoying watching movies in a theatre versus at home: a comparative analysis. Marketing Letters, 35(1), 29-44. https://doi.org/10.1007/s11002-023-09705-3
-
Guyt, J. Y., Datta, H., & Boegershausen, J. (2024). Unlocking the Potential of Web Data for Retailing Research. Journal of Retailing, 100(1), 130-147. https://doi.org/10.1016/j.jretai.2024.02.002
-
Gabel, S., Simester, D., & Timoshenko, A. (2024). How Retailers Became Ad Platforms. Harvard Business Review (digital). https://hbr.org/2024/06/how-retailers-became-ad-platforms
-
Gabel, S., Molitor, D., & Spann, M. (2024). The Effect of an Ad Ban on Retailer Sales: Insights from a Natural Experiment. Marketing Science, 43(4), 723-733. https://doi.org/10.1287/mksc.2023.0019
-
Ferecatu, A., De Bruyn, A., & Mukherjee, P. (2024). Silently killing your panelists one email at a time: The true cost of email solicitations. Journal of the Academy of Marketing Science, 52(4), 1216-1239. https://doi.org/10.1007/s11747-023-00992-w
-
du Plessis, C., D'Hooge, S., & Sweldens, S. (2024). The Science of Creating Brand Associations: A Continuous Trinity Model Linking Brand Associations to Learning Processes. Journal of Consumer Research, 51(1), 29-41. Article ucad046. https://doi.org/10.1093/jcr/ucad046
-
De Keyser, A., Lembregts, C., & Schepers, J. (2024). How Ratings Systems Shape User Behavior in the Gig Economy. Harvard Business Review (digital). https://hbr.org/2024/04/research-how-ratings-systems-shape-user-behavior-in-the-gig-economy
-
Chun, L., Lembregts, C., & Van den Bergh, B. (2024). Mind over minutes: The effect of task duration consideration on task delay. Journal of Consumer Psychology, 34(3), 502-509. https://doi.org/10.1002/jcpy.1390
-
Chan, H.-Y., Boksem, M., Venkratraman, V., Dietvorst, RC., Scholz, C., Vo, K., Falk, E. B., & Smidts, A. (2024). Neural signals of video advertisement liking: Insights into psychological processes and their temporal dynamics. Journal of Marketing Research, 61(5), 891-913. https://doi.org/10.1177/00222437231194319
-
Celiktutan, B., Klesse, A. K., & Tuk, M. A. (2024). Acceptability lies in the eye of the beholder: Self-other biases in GenAI collaborations. International Journal of Research in Marketing, 41(3), 496-512. https://doi.org/10.1016/j.ijresmar.2024.05.006
-
Celiktutan, B., Cadario, R., & Morewedge, C. K. (2024). People see more of their biases in algorithms. Proceedings of the National Academy of Sciences of the United States of America, 121(16), e2317602121. Article e2317602121. https://doi.org/10.1073/pnas.2317602121
-
Bolton, G. E., Ferecatu, A., & Kusterer, D. J. (2024). Rate This Transaction: Coordinating Mappings in Market Feedback Systems. Management Science, 70(1), 567-588. https://doi.org/10.1287/mnsc.2023.4694
-
Boksem, M., van Diepen, R., Eijlers, E., Boekel, W., & Smidts, A. (2024). Do EEG metrics derived from trailers predict the commercial success of movies? A systematic analysis of five independent datasets. Journal of Marketing Research. Advance online publication. https://doi.org/10.1177/00222437241309875
-
Aydin Gokgoz, Z., Ataman, M. B., & van Bruggen, G. H. (2024). If it ain't broke, should you still fix it? Effects of incorporating user feedback in product development on mobile application ratings. International Journal of Research in Marketing, 42(2), 467-486. Advance online publication. https://doi.org/10.1016/j.ijresmar.2024.10.004
-
Wierenga, B. (2024, Jan 8). Onderwijs in de volkstaal en weg was Franeker. https://www.nrc.nl/nieuws/2024/01/07/hoger-onderwijs-in-de-volkstaal-in-franeker-liep-dat-slecht-af-a4186198
The department of Marketing Management offers several degree programs:
Talented students interested in an academic career in Marketing can apply to join the PhD programme in Management at ERIM, a top research institute in Europe. Erasmus University has established a strong reputation for research excellence and PhD supervision in the field of marketing. It is consistently ranked in the top-3 of most productive universities outside of North America (counting publications in the top marketing journals). The department is especially noted for its research excellence. Whereas the faculty members are immensely diverse in their research interests and cultural background, they share the passion for rigorous, high-quality research that has important implications for theory and practice.
The ideal PhD candidate has a strong research background in one of the core disciplines (e.g., psychology, economics, business, statistics or mathematics) and the ambition to pursue an international career as a leading academic. Marketing PhD projects at RSM Erasmus University are generally in one of three areas: consumer behavior, quantitative modeling, or consumer neuroscience. The student will typically be supervised by a team of supervisors, which guarantees excellent support. The topic of the PhD will be defined by the student and the supervisory team and thus requires creativity, self-direction, and passion for scientific research. Importantly, at RSM the PhDs are open to establish research projects also with other faculty members both inside and outside RSM. To this end, our doctoral students are encouraged and funded to conduct extended research visits at the best North American universities. For instance, over the past five years our doctoral students have visited Stanford University, UCLA, University of Chicago, University of Pennsylvania, and University of British Columbia.
The doctoral programme at RSM Erasmus University offers unparalleled support in funding and research facilities. Notably the Erasmus Behavioral Lab is one of the best equipped behavioral laboratories in the world, featuring 28 sound-isolated cubicles, a large subject pool, and several state-of-the-art measurement devices (EEG, eye tracking, video monitoring etc.). Interested candidates are invited to visit the ERIM PhD in Management website for information about application procedures and criteria. They may also contact the coordinator of the PhD Programme in Marketing, Dr. Mirjam Tuk, for more information.
Many of the Marketing Management core faculty also teach in the MBA program. RSM offers a world class full-time MBA as well as several Executive MBA programs. RSM MBA programs focus on developing MBA students with advanced critical-thinking, problem solving, leadership, and communication skills necessary for directing the next generation of diverse and sustainable businesses.
With ever stronger impact of social media, big data, and globalization, now is a very exciting time to begin a career in marketing. Previous generations of marketers actively seek new generation of talent to help them face the challenges of the fast shifting landscape of marketing. Fresh graduates with personal experience and formal training incorporating these newly emerging domains can quickly rise in prominence and make a real impact in their organizations.
This well-established Msc Marketing Management programme has been proven to provide a solid education if you want to pursue a career in marketing-related function, and has a strong reputation for delivering high quality graduates. We make sure all students meet the key demands of the current job market: real-life problem solving skills, international perspective, and leadership, teamwork, and communication skills, while giving them the freedom to follow their passion by designing their own curriculum (i.e. choosing their own electives and thesis topic).
This programme is designed to provide students with the skills to apply data science to solve business challenges. Students have a deep theoretical and practical understanding of business analytics methods to solve data-based business problems. The training on analytics, applied statistics and applied machine learning in the program is driven and taught by domain-area experts, such as marketing statistical modelers, supply-chain modelers and finance modelers with background in both the domain area and in statistical methods.
The department of Marketing Management contributes to the curriculum of both the Bachelor of Science in International Business Administration (IBA) programme as well as the Bachelor of Science in Business Administration (Bedrijfskunde) programme.
Course topics include: Marketing Management and International Marketing Research.
