His research has primarily been focused on consumer decision making and visual attention in the retail environment. In the past years, Dr. Shams has developed methods and tools for monitoring consumer behavior and emotions in-situ using IOT technology and AI. His research has been awarded by the Gunnar Sundblad Research Foundation and published in several distinguished journals such as Journal of Business Research, Psychology & Marketing and Journal of Service Management.
The present project involves quantifying consumer behavior using sensor technology as a first step in creating deep learning algorithms that can interpret behavior in relation to factors in the service scape. This is a two-step process to first create the infrastructure to map behavior and then use the data from mapped behavior into machine learning algorithms that take action in manipulating the environment using smart technology. This will generate a platform for regulating customer experience depending on customer behavior using IOT in combination with AI.