Dr. J.M.T. (Jason) Roos

Rotterdam School of Management (RSM)
Erasmus University Rotterdam
Member ERIM
Field: Marketing
Affiliated since 2012

My current research interests include

  • Internet and new media
  • Entertainment goods
  • Structural modeling
  • Bayesian econometrics


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  • Academic (5)
    • Daljord, Ø., Mela, C., Roos, J., Sprigg, J., & Yao, S. (2023). The Design and Targeting of Compliance Promotions. Marketing Science, 42(5), 866-891. https://doi.org/10.1287/mksc.2022.1420

    • Roos, J., Mela, CF., & Shachar, R. (2020). The Effect of Links and Excerpts on Internet News Consumption. Journal of Marketing Research, 57(3), 395-421. https://doi.org/10.1177/0022243720913029

    • Roos, J., & Shachar, R. (2014). When Kerry Met Sally: Politics and Perceptions in the Demand for Movies. Management Science, 60(7), 1617-1631. https://doi.org/10.1287/mnsc.2013.1834

    • Mela, CF., Roos, J., & Deng, Y. (2013). A Keyword History of Marketing Science. Marketing Science, 32(1), 8-18. https://doi.org/10.1287/mksc.1120.0764

    • Glickman, SW., Boulding, W., Roos, J., Staelin, R., Peterson, ED., & Schulman, K. (2009). Alternative pay-for-performance scoring methods: implications for quality improvement and patient outcomes. Medical Care, 47(10), 1062-1068. https://doi.org/10.1097/MLR.0b013e3181a7e54c

  • External (1)
    • Roos, J. (2012). Hyper-Media Search and Consumption. [Doctoral Thesis, Duke University]. Duke University.

  • Role: Daily Supervisor
  • Role: Member Doctoral Committee
  • PhD Candidate: Bruno Jacobs
  • Time frame: 2012 - 2017
  • Role: Daily Supervisor, Co-promotor
  • PhD Candidate: Martina Pocchiari
  • Time frame: 2017 - 2022
  • Role: Member Doctoral Committee
  • PhD Candidate: Thomas Frick
  • Time frame: 2013 - 2018
  • Role: Member Doctoral Committee
  • PhD Candidate: Wei Li
  • Time frame: 2009 - 2021
  • Role: Co-promotor
  • PhD Candidate: Marina Lenkovskaya
  • Time frame: 2021 -
  • Role: Co-promotor
  • PhD Candidate: Ting-Yi Lin
  • Time frame: 2021 -
  • Role: Member Doctoral Committee
  • PhD Candidate: Francesco Balocco
  • Time frame: 2016 - 2023
  • Current Topics in Marketing Research (2021/2022)

The Marketing group at Rotterdam School of Management, Erasmus University seeks a highly motivated PhD student with strong quantitative skills to study the problem of algorithmic biases in marketing.

As machines are trained to analyse complex problems, many tasks that previously required humans are now guided by Artificial Intelligence. Marketing is no exception in this domain. Increasingly, companies use algorithms to design targeted marketing campaigns. Causal Machine Learning is an emerging research field that can learn the causal effect of an intervention and how it varies within a population based on a large set of potential moderating variables. Its use in marketing has been rapidly growing over the last years (Lemmens and Gupta 2020; Esterzon, Lemmens, Van den Bergh 2023).

Unfortunately, algorithms can be discriminatory. The number of cases reporting biases in algorithms has exploded. Algorithms reproduce and amplify biases present in human decisions. They may even inadvertently create new discriminatory outcomes.

This PhD project ambitions to tackle this crucial managerial and societal challenge. The goal will be to better understand the problem of algorithmic biases in the context of targeting marketing campaigns and to develop a novel methodological framework to design effective and fair personalized policies. The project will include large-scale field experiments in collaboration with company partners.

Strong applicants typically have backgrounds in computer science, statistics or econometrics but should have an intrinsic interest for marketing problems. The PhD will be supervised by Prof. Dr. Aurélie Lemmens  and funded by a VICI NWO grant.

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  • Fellowship - ERIM early career talent programme (2012)


Visiting address

Office: Mandeville Building T10-19
Burgemeester Oudlaan 50
3062 PA Rotterdam

Postal address

Postbus 1738
3000 DR Rotterdam