Project Description
When data exist, we, as researchers, strive to find new ways of exploring and gathering new knowledge from it to make better decisions. From a business perspective, with Big Data and the fast growth of e-commerce, data-driven techniques became effective solutions for solving various issues in retailing.
In this context, the general scope of this Ph.D. project is data-driven decision support in digital retailing. The research topics undertake several highly nowadays demanded applications in retail. For example, product returns analysis and predictions and other applications aid in making decisions to make a difference in production, increase sales, and improve end-user loyalty, especially after the adverse effects caused by the Covid-19 in E-commerce. The scientific contributions will be researching improved or new algorithms and techniques applied in retailing. Such a project is not just an illustration of technical prowess but also demonstrates academic qualities and contributes to knowledge.
Links:
ORCID
Google Scholar
Thesis Project Team
Dirar Sweidan
PhD Student
Master of Science with a major in Computer Science and Engineering. Specialisation: Embedded and Intelligent Systems.
