English

FEMtech research project funded by the Austrian Ministry for Transport, Innovation and Technology
October 2019 – September 2021

The project in short

The deployment of algorithmic pricing strategies online has been a standard for airline companies for a decade, and increasingly also enters e-commerce sites. Hereby, dynamic pricing is a common practice with regard to prices dependent on e.g. time or estimated demand. What remains an open question is to which extent different price claims are set depending on personal attributes of consumers. To analyse the prevalence and impact of online price discrimination, requires the focus on how different forms of discriminations intersect and concern a person.

The ongoing challenge is to discover and deliver scientific evidence for personalised pricing in the Austrian e-commerce sector and to analyse possible discriminatory practices in this domain. Companies act as a black-box and it remains unclear which techniques are used to constitute prices and which person-based parameters this concerns.

PRIMMING aims to find evidence by developing a framework, in which personas, their behaviour and scenarios are modelled. These are to be tested automatically in controlled measurements and the results are to be compared with a control group of real-time users. The objective is to empirically determine the forms and prevalence of dynamic pricing in Austria and to further inquire into discriminations occurring in this context such as related to gender.

A major result of the project will be a tool to monitor static, dynamic and personalised pricing. Based on AI and Machine Learning this shall not constitute a mere observation but allow for predictive analytics.

For more information please contact

Austrian Institute for Applied Telecommunication (ÖIAT):
Louise Horvath (project lead)
horvath at oiat at