Prof. dr. G. (Gui) Liberali
Gui Liberali is the full Professor of Digital Marketing at Rotterdam School of Management (RSM) of the Erasmus University. He holds a doctorate in marketing and a B.Sc. in computer science. His work has appeared on Marketing Science, Management Science, International Journal of Marketing Research, Sloan Management Review, and European Journal of Operational Research. His research interests include optimal learning, multi-armed bandits, digital experimentation, morphing theory and applications (e.g., website morphing, ad morphing), dynamic programming, machine learning, and product line optimization. Personal webpage: *www.guiliberali.org* For more details on professional experience, education, and latest news please visit my linkedin page at www.linkedin.com/in/gui-liberali/
Publications
Article (14)
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Academic (13)
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Liberali, G., Boersma, E., Lingsma, H., Brugts, J., Dippel, D., & Hauser, J. R. (2024). Adaptation of Bayesian Trials in the Presence of Interim Information. MIT Sloan Working Paper, 6639(21).
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Giesecke , K., Liberali, G., Nazerzadeh , H., Shanthikumar , J. G., & Teo, CP. (2022). Introduction to the Special Section on Data-Driven Prescriptive Analytics. Management Science, 68(3), 1591-1594. https://doi.org/10.1287/mnsc.2021.4296
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Liberali, G., & Ferecatu, A. (2022). Morphing for Consumer Dynamics: Bandits Meet Hidden Markov Models. Marketing Science, 41(4), 341-366. https://doi.org/10.1287/mksc.2021.1346
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Giesecke, K., Liberali, G., Nazerzadeh, H., Shanthikumar, G., & Teo, CP. (2018). Special Issue on Data-Driven Prescriptive Analytics. Management Science, 64(6), 2972-2972. https://doi.org/10.1287/mnsc.2018.3120
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Liberali, G., Muller, E., Rust, RT., & Stremersch, S. (2015). Introduction to the IJRM Special Issue on Marketing and Innovation. International Journal of Research in Marketing, 32(3), 235-237. https://doi.org/10.1016/j.ijresmar.2015.08.001
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Urban, G., Liberali, G., Bordley, R., Macdonald, E., & Hauser, J. (2014). Morphing Banner Advertising. Marketing Science, 33(1), 27-46. https://doi.org/10.1287/mksc.2013.0803
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Hauser, J., Liberali, G., & Urban, G. (2014). Website Morphing 2.0: Technical and Implementation Advances and a Field Experiment. Management Science, 60(6), 1594-1616. https://doi.org/10.1287/mnsc.2014.1961
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Liberali, G., Urban, G., & Hauser, J. (2012). Competitive Information, Trust, Brand Consideration and Sales: Two Field Experiments. International Journal of Research in Marketing, 30(2), 101-113. Article 1. https://doi.org/10.1016/j.ijresmar.2012.07.002
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Liberali, G., Gruca, T., & Nique, W. (2011). Effects of Sensitization and Habituation in Durable Goods Markets. European Journal of Operational Research, 212(2), 398-410. https://doi.org/10.1016/j.ejor.2011.01.038
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Liberali, G. (2011). Comments on Product Line Design Optimization. International Journal of Research in Marketing, 28(1), 28-29. https://doi.org/10.1016/j.ijresmar.2011.01.002
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Hauser, J., Urban, G., Liberali, G., & Braun, M. (2009). Website Morphing. Marketing Science, 28(2), 202-223. https://doi.org/10.1287/mksc.1080.0459
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Hauser, J., Urban, G., Liberali, G., & Braun, M. (2009). Rejoinder Response to Comments on "Website Morphing". Marketing Science, 28(2), 227-228. https://doi.org/10.1287/mksc.1080.0485
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Urban, G., Hauser, J., Liberali, G., Braun, M., & Sultan, F. (2009). Morphing the Web - Building Empathy, Trust, and Sales. MIT Sloan Management Review, 50(4), 53-61.
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Professional (1)
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Liberali, G. (2014). Morphing advertising to improve online campaign success. RSM Discovery - Management Knowledge, 20(4), 12-14. http://hdl.handle.net/1765/77381
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Chapter (1)
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Professional (1)
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Liberali, G. B., Hauser, J. R., & Urban, G. L. (2017). Morphing theory and applications. In International Series in Operations Research and Management Science (pp. 531-562). Springer New York. https://doi.org/10.1007/978-3-319-56941-3_18
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Comment/Letter to the editor (1)
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Popular (1)
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Urban, G. L., Hauser, J. R., Liberali, G., Braun, M., & Sultan, F. (2009). Morph the Web to build empathy, trust and sales. MIT Sloan Management Review, 50(4), 53-61.
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Inaugural speech (1)
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Popular (1)
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Liberali, G. (2018). Learning with a purpose: the balancing acts of machine learning and individuals in the digital society. Erasmus Research Institute of Management (ERIM). ERIM Inaugural Address Series Research in Management http://hdl.handle.net/1765/107428
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Additional activities (2)
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Management Science (Journal)
Editorial work (Academic)
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International Journal of Research in Marketing (Journal)
Editorial work (Academic)
PhD Tracks (7)
- Role: Member Doctoral Committee
- PhD Candidate: Agapi-Thaleia Fytraki
- Time frame: 2010 - 2018
- Role: Promotor
- PhD Candidate: Bob Jan Jouke Rombach
- Time frame: 2021 -
- Role: Member Doctoral Committee
- PhD Candidate: Zeynep Aydin
- Time frame: 2009 - 2021
- Role: Promotor
- PhD Candidate: Marina Lenkovskaya
- Time frame: 2021 -
- Role: Promotor
- PhD Candidate: Ting-Yi Lin
- Time frame: 2021 -
Course (1)
- Current Topics in Marketing Research (2023/2024)
PhD Vacancy (1)
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.
Events (43)
Address
Office: Mandeville Building T10-14
Burgemeester Oudlaan 50
3062 PA Rotterdam
Postbus 1738
3000 DR Rotterdam
Netherlands
