The QoE alchemy: Turning quality into money. Experiences with a refined methodology for the evaluation of willingness-to-pay for service quality

Sackl, Andreas; Egger, Sebastian; Zwickl, Patrick; Reichl, Peter

doi:10.1109/qomex.2012.6263846

Cited by 25 publications

(32 citation statements)

References 6 publications

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“…In general, most Perceived Quality ratings were above 4, in fact only in 63 cases the Perceived Quality of a video was rated lower than 4. As mentioned earlier, only two bitrate levels were used in our previous study; 600kbps of bitrate is considered as a reasonable video quality level that users are willing to pay for [33], while 2000kbps of bitrate is considered as the entry level of HD quality. As a result, participants from our previous study thought that the quality of the videos was reasonable in most cases.…”

Section: Dataset Usedmentioning

confidence: 99%

Towards a comprehensive model for predicting the quality of individual visual experience

Zhu

Heynderickx

Hanjalic

et al. 2015

Human Vision and Electronic Imaging XX

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Recently, a lot of effort has been devoted to estimating the Quality of Visual Experience (QoVE) in order to optimize video delivery to the user. For many decades, existing objective metrics mainly focused on estimating the perceived quality of a video, i.e., the extent to which artifacts due to e.g. compression disrupt the appearance of the video. Other aspects of the visual experience, such as enjoyment of the video content, were, however, neglected. In addition, typically Mean Opinion Scores were targeted, deeming the prediction of individual quality preferences too hard of a problem. In this paper, we propose a paradigm shift, and evaluate the opportunity of predicting individual QoVE preferences, in terms of video enjoyment as well as perceived quality. To do so, we explore the potential of features of different nature to be predictive for a user's specific experience with a video. We consider thus not only features related to the perceptual characteristics of a video, but also to its affective content. Furthermore, we also integrate in our framework the information about the user and use context. The results show that effective feature combinations can be identified to estimate the QoVE from the perspective of both the enjoyment and perceived quality.

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Section: Dataset Usedmentioning

confidence: 99%

Towards a comprehensive model for predicting the quality of individual visual experience

Zhu

Heynderickx

Hanjalic

et al. 2015

Human Vision and Electronic Imaging XX

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“…In this section, we briefly revisit an empirical work of [4] (experiment 1) and complement it with the new experiment 2 in order to analyze user perceptions and behaviors regarding varying network video qualities. While experiment 1 investigates the end users' WTP with active user decisions, experiment 2 in complementation assesses video quality ratings without active user decisions.…”

Section: Empirical Workmentioning

confidence: 99%

“…For more details about the procedure and the setup, please see [4]. A short overview about the setup is given in Figure 1, which depicts how the user can interact with the video streaming system regarding the selection of video contents and the purchasing of quality levels.…”

Section: A Experiments 1 -With User Decisionsmentioning

confidence: 99%

“…In this paper, we focus on one particular direction of the mentioned link and investigate the impact of active user decisions on quality rating and purchases. Based on a series of recent user trials and complementing initial results reported in [4], as a main contribution we present evidence that users who decide to choose (and pay for) high quality multimedia services tend…”

Section: Introductionmentioning

confidence: 98%

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The role of cognitive dissonance for QoE evaluation of multimedia services

Sackl

Zwickl

Egger

et al. 2012

2012 IEEE Globecom Workshops

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In contrast to traditional QoS-based charging, charges for QoE (Quality of Experience) play a double role both as part of the evaluation context and as counterpart of the user's willingness-to-pay for service quality. To further investigate this link between pricing and QoE, we combine some unexpected results from empirical quality perception experiments with the socio-psychological theory of cognitive dissonance. With this approach, we are able to explain the influence of active user decisions on QoE. Moreover, economical implications, further research opportunities and practical advices for quality testing are presented.

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“…Another higher-level characteristic that is often related to the viewing or hearing behaviors when consuming multimedia services, it is guided by the attention mechanism. Attention is a cognitive process of selectively concentrating on certain external objects (e.g., visual or auditory) while paying less or no attention to others [50]. Objects might be salient not only because of their characteristics but also because surrounding objects are not.…”

Section: High-levelmentioning

confidence: 99%

Smart Client-Server Protocol and Architecture for Adaptive Multimedia Streaming

Abdullah¹

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In recent years, multimedia services consumption has increased and it is expected that this trend will continue in the near future, becoming the evaluation of Quality of Experience (QoE) as a very important issue for assessing the quality of providers' services. In this sense, the optimization of the QoE is progressively receiving much attention considering that current solutions are not based on the adaptation, feasibility, cost-effectiveness and reliability.The present dissertation is focused on the characterization, design, development and evaluation of different multimedia applications aimed to optimize the QoE.Therefore, this work investigates the influence that the networks infrastructure, the videos' characteristics and the users' terminals present on QoE of the current Internet multimedia services. The work is based on a comprehensive research of subjective and objective assessments in heterogeneous networks. Challenges and research questions related to the state of the art are discussed in this dissertation.In the first phase of this dissertation, we design a test methodology for assessing QoE of live video streaming and video on demand platforms to be transmitted over Wi-Fi and cellular networks. From this initial step, we will propound the related research issues and questions to solve along this dissertation. Our methodology considers the use of subjective and objective metrics to evaluate the QoE perceived by end-users. A set of laboratory experiments is conducted where our proposed methodology is applied. The obtained results are gathered and analyzed to extract the relations between Quality of Service (QoS) and QoE. From the results, we propose a QoSQoE mapping which allows predicting QoE.In the next phase of the research, we develop QoE-optimization algorithms based on network system management for Wi-Fi and cellular networks. The algorithms use the key parameters that were taken into account for QoE assessment. The goal of these algorithms is to provide a flexible management system for the networks in order to achieve the desirable tradeoff between QoE maximization and resource usage efficiency. IILastly, the system testbed is designed in order to evaluate the performance of generic multimedia services applications for the different environments under test. The system testbed is based on virtualization approach; it uses the shared resources of a physical hardware to virtualize all components. The virtualized testbed provides virtualized network functions for the different scenarios such as the Internet (Content Delivery NetworksCDNs) and wireless networks. Therefore, lightweight protocols and agile mechanisms are adopted in the system to provide enhanced service to endusers. The QoE results are reported to the service providers according to the parameters defined in the evaluation process. As a result, we have obtained a cost-effective system, which is considered as a feasible way for test evaluation. III ResumenEn los últimos años, el consumo de servicios multimedia ha aumentado y se pr...

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The QoE alchemy: Turning quality into money. Experiences with a refined methodology for the evaluation of willingness-to-pay for service quality

Cited by 25 publications

References 6 publications

Towards a comprehensive model for predicting the quality of individual visual experience

Towards a comprehensive model for predicting the quality of individual visual experience

The role of cognitive dissonance for QoE evaluation of multimedia services

Smart Client-Server Protocol and Architecture for Adaptive Multimedia Streaming

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