Correlating QoE and technical parameters of an SAP system in an enterprise environment

The impact of waiting times on the Quality of Experience (QoE) in enterprise and working environments has not been in the focus of current research. This mostly stems from two factors: i) the high complexity of enterprise systems exacerbates the exact monitoring of relevant application response times on user granularity and ii) disturbances of the day-to-day business by user studies resulting in additional costs due nonproductive times. This paper approaches these challenges by combining non-intrusive application monitoring of response times and subjective user ratings on the perceived application performance. We evaluate the possibility of predicting the QoE based on the objective measurements using different machine learning approaches. The results imply a high correlation for specific users, but do not allow to derive a generic model.