QoE Assessment of Enterprise Applications Based on Self-Motivated Ratings

In most companies, enterprise applications, such as office products or databases, are heavily used by employees during work hours. Impairments and performance issues not only slow down business processes, but might also increase the frustration of the workforce. While Quality of Experience (QoE) has been widely studied for personal multimedia applications, such as video streaming, its application to the business usage domain is still in its infancy. Due to several reasons, e.g., the high complexity of IT infrastructure, classical QoE studies can hardly be transferred to business applications. These studies are often independent from the context of usage and actively poll ratings from their participants. This work contrasts the commonly used “pull” method for collecting user ratings with a self-motivated “push” approach. This approach is inspired by complaint systems, in which users can directly report problems with a technical system as soon as they notice them. Therefore, performance assessments of a business application from employees of a cooperating company are collected with both rating systems during a time span of 1.5 years. Besides the analysis of the interaction of users with the “push” system, differences between the two methods are discussed. Further, QoE models for the monitored business application are derived based on the self-motivated “push” ratings.

[1]  Lea Skorin-Kapov,et al.  YouTube QoE Estimation from Encrypted Traffic: Comparison of Test Methodologies and Machine Learning Based Models , 2018, 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX).

[2]  Ronghua Liu,et al.  IPTV User’s Complaint Prediction based on the Gaussian Mixture Model for Imbalanced Dataset , 2017 .

[3]  Stanislav Lange,et al.  Identification of Delay Thresholds Representing the Perceived Quality of Enterprise Applications , 2018, 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX).

[4]  Lea Skorin-Kapov,et al.  QoE Analysis of the Setup of Different Internet Services for FIFO Server Systems , 2018, MMB.

[5]  W. Marsden I and J , 2012 .

[6]  Lea Skorin-Kapov,et al.  Survey of research on Quality of Experience modelling for web browsing , 2017 .

[7]  Jamie Woodcock,et al.  Doing Good Online: The Changing Relationships Between Motivations, Activity, and Retention Among Online Volunteers , 2018, Nonprofit and Voluntary Sector Quarterly.

[8]  Andreas Hotho,et al.  Text Categorization for Deriving the Application Quality in Enterprises Using Ticketing Systems , 2015, DaWaK.

[9]  Jianxin Chen,et al.  Unbiased Decision Tree Model for User's QoE in Imbalanced Dataset , 2016, 2016 International Conference on Cloud Computing Research and Innovations (ICCCRI).

[10]  Siegfried Olschner,et al.  Wie schnell ist "schnell" bei Business-Software? - Analyse zur Performance bei der Nutzung von Business-Software , 2015, Usability Professionals.

[11]  Khawaja A. Saeed,et al.  To Send or Not to Send: An Empirical Assessment of Error Reporting Behavior , 2008, IEEE Transactions on Engineering Management.

[12]  Peter Schelkens,et al.  Qualinet White Paper on Definitions of Quality of Experience , 2013 .

[13]  Selim Ickin,et al.  Factors influencing quality of experience of commonly used mobile applications , 2012, IEEE Communications Magazine.

[14]  Thomas Zinner,et al.  Designing a Survey Tool for Monitoring Enterprise QoE , 2017, Internet-QoE@SIGCOMM.

[15]  Ping Zhang,et al.  Predictors of customer perceived software quality , 2005, Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005..

[16]  Christian Timmerer,et al.  Challenges of QoE management for cloud applications , 2012, IEEE Communications Magazine.

[17]  Raimund Schatz,et al.  Quantifying the impact of network bandwidth fluctuations and outages on Web QoE , 2015, 2015 Seventh International Workshop on Quality of Multimedia Experience (QoMEX).

[18]  Ross Smith,et al.  Crowdsourcing and Gamification of Enterprise Meeting Software Quality , 2014, 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing.