L. (Luuk) van Maasakkers MSc
PhD Track Marketing modelling for large-scale assortments
Consumers who shop (online) are often overloaded with information, choice options, web-sites, links to other web-pages, etc. Managers of (online) stores need to make many decisions: which products to sell, what prices to charge, which promotions to organize, which customers to target, etc. In principle a lot of data is available to optimize such decisions. However, both the dimension and level of detail of the data make it challenging to actually use the data. In this project you will work on the development and application of econometric marketing models that (i) can help guide practical decision making; (ii) are scalable (that is, can be estimated in a reasonable time frame); (iii) combine different data sources; and (iv) work at the individual product and/or customer level, such that customization of prices and promotions is feasible.
In this project we will seek active collaboration with Dutch or international (online) retailers. These contacts will help us target practically useful research questions and provide access to detailed data. In the ideal case we will be able to test the developed methodology in real life.
- Marketing, econometrics, machine learning, prediction, recommendation, online retailing, dynamic pricing
- Time frame
- 2019 -
van Maasakkers, L., Fok, D., & Donkers, B. (2023). Next-basket prediction in a high-dimensional setting using gated recurrent units. Expert Systems with Applications, 212, . https://doi.org/10.1016/j.eswa.2022.118795
Burgemeester Oudlaan 50
3062 PA Rotterdam
3000 DR Rotterdam