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" Likelihood to Recommend (L2R) Prediction Using Quality of Experience (QoE) Measurements: A Longitudinal Study "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 1052643
Doc. No : TL51760
Main Entry : Azad-Armaki, Mohammad-Amin
Title & Author : Likelihood to Recommend (L2R) Prediction Using Quality of Experience (QoE) Measurements: A Longitudinal Study\ Azad-Armaki, Mohammad-AminChignell, Mark
College : University of Toronto (Canada)
Date : 2019
Degree : M.A.S.
student score : 2019
Note : 88 p.
Abstract : Models that predict satisfaction with a service over time need to consider the impact of emotions and remembered quality of experience in predicting overall attitudes towards a service. However, prior research on the subjective of quality of experience has typically focused on experiments conducted in a single session or over a short period of time. Thus, there is a gap between our understanding of instantaneous quality of experience and long-term judgments, such as overall satisfaction, and likelihood to recommend and likelihood to churn. The goal of the study reported here was to carry out a longitudinal study that would provide initial insights into how experiences of service quality over time are accumulated into memories that then drive longer term attitudes about the service. Our longitudinal study was carried out over a period of roughly 4 weeks with around 3 sessions per week.
Descriptor : Business education
: Industrial engineering
: Psychology
Added Entry : Chignell, Mark
Added Entry : University of Toronto (Canada)
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