Role Of Experience Quality Research Articles

Bayesian K-means clustering based quality of experience aware multimedia video streaming

<span>Media streaming is an essential approach for delivering multimedia information from the source distributor to the end-user through the Internet. Along with the development of more number of users and the spread of mobile devices, the availability and diversity of multimedia applications has also increased. Multimedia users primarily prioritize quality of experience (QoE), as they seek to access multimedia content with high availability and enjoy smooth video streaming in the shortest possible time. The impact of video delivery plays a significant role in QoE, which is efficiently made by delivering the content through a specialized content delivery network architecture. In this research, a Bayesian K-means clustering algorithm is proposed for the identification of QoE in multimedia video streaming. In this multimedia video streaming, the Amazon Prime video dataset is utilized for determining the performance of the proposed model. The proposed method is developed from the ‘Patching Up’ the video quality problem (PatchVQ) model, the from patches to pictures (PaQ-2-PiQ) model is utilized for the spatial feature extraction, and 3D ResNet-18 is utilized for temporal feature extraction. The proposed Bayesian K-means achieved a QoE reward function of 5,237.42 and 5841.36 as well as a fairness reward function of 5,841.36 and 8,732.08 at the speed of 1,500 kB/s and 2,000 kB/s respectively.</span>

Client assessments of their audit experiences: the role of experience quality, similarity and client participation

PurposeThis study examines how three psychological factors (i.e. perceived experience quality, perceived similarity and client participation) that impact client evaluations of their recent audit experiences influence client satisfaction and trustworthiness, which, in turn, affect advocacy in an small- and medium-sized enterprise (SME) context. Furthermore, the study investigates whether the influence of the three psychological factors on client satisfaction and trustworthiness is contingent on client expertise.Design/methodology/approachThe sample consisted of 744 SME executives from the following four regions: central, northern, eastern and southern Thailand. Data were collected using a survey questionnaire. Confirmatory factor analysis was conducted to ensure the reliability and validity of the scale before structural equation modeling was applied to analyze the data.FindingsThe results showed significant positive effects of the three psychological factors (perceived experience quality, perceived similarity and client participation) on client satisfaction and perceived trustworthiness. The moderating role of client expertise on the relationships is also found. More specifically, client expertise positively moderated the connections between experience quality and satisfaction, experience quality and trustworthiness and client participation and trustworthiness. Conversely, client expertise negatively moderated the similarity–satisfaction and similarity–trustworthiness relationships.Originality/valueThis study contributes to the audit literature by examining the role of psychological factor that impacts client satisfaction and perceived trustworthiness in the SME context. Moreover, the moderating role of client expertise is examined for the first time, providing new insights into the boundary condition of the relationship.

When a RF beats a CNN and GRU, together—A comparison of deep learning and classical machine learning approaches for encrypted malware traffic classification

Internet traffic classification plays a crucial role in Quality of Experience (QoE), Quality of Services (QoS), intrusion detection, and traffic-trend analyses. While there is no theoretical guarantee that deep learning (DL)-based solutions perform better than classic machine learning (ML)-based ones, DL-based models have become the common default. This paper compares well-known DL-based and ML-based models and shows that in the case of malicious traffic classification, state-of-the-art DL-based solutions do not necessarily outperform the classical ML-based ones. We exemplify this finding using two well-known datasets for a varied set of tasks, such as: malware detection, malware family classification, detection of zero-day attacks, and classification of an iteratively growing dataset. Note that, it is not feasible to evaluate all possible models to make a concrete statement, thus the above finding is not a recommendation to avoid DL-based models, but rather an empirical finding that in some cases, there are more simplistic solutions, that may perform even better.

Investigating the role of experience quality in predicting destination image, perceived value, satisfaction, and behavioural intentions: a case of war tourism

ABSTRACT The present empirical study is aimed to investigate a theoretical model, which predicts the indirect and direct impacts of the quality of the tourists’ experience on behavioural intentions through perceived value, destination image, and tourists’ satisfaction in war tourism as a form of dark tourism. This research was conducted using data collected from 330 tourists visiting Khorramshahr War Museum and Holy Defense Museum Garden in Iran. The results of testing hypotheses using SPSS and SmartPLS software indicate that experience quality influenced behavioural intentions indirectly via destination image, perceived value, and tourists’ satisfaction. Tourists’ satisfaction was found as the strongest influencer of behavioural intentions in war tourism.

The effect of event experience quality on the satisfaction and behavioral intentions of motocross World Championship spectators

PurposeThe purpose of this study is to examine the theoretical relationship between experience quality (EXQ), satisfaction and the behavioral intentions (BI) of Motocross World Championship spectators.Design/methodology/approachThe research data were collected from spectators who participated in the World Motocross Championship race held in Afyon, Turkey in 2018. The structural equation model (SEM) was used to test the relationship among the research variables.FindingsThe results showed EXQ had significant and direct effects on satisfaction and BI. In addition to this, satisfaction had a partial mediating effect between EXQ and BI.Originality/valueTo date there has been no empirical study examining the consumer behaviors of motocross event spectators. Consequently, this research provides important contributions to the literature and informs event organizers about the role of EXQ in terms of understanding the behavior of motocross event spectators.

Modelling effects of S3D visual discomfort in human emotional state using data mining techniques

In recent years, the rapid development of diverse media has been evident in disparate fields such as consumer electronics, automotive infotainment and healthcare software. There is a need for innovative methods to assess user perceived Quality of Experience (QoE), as a proxy for consumer satisfaction with such systems and services. Users emotional state plays a key role in QoE; thus, it is necessary to consider it in user experience evaluation and the design process of stereoscopic 3D video content. In the present article we introduce the use of a specially designed model based on a feedforward Multilayer Perception Artificial Neural Network as an appropriate Machine Learning technique for the estimation of human emotional state while viewing various categories of stereoscopic 3D video content. The goal is to design an emotional state estimator based on direct psychophysiological measurements. The considered psychophysiological signals include heart rate (HR) calculated from an echocardiogram (ECG), electro-dermal activity (EDA), and brain activity (BA) in EEG signals. Participants watched a series of 3D video contents varying in terms of visual quality, while the mentioned psychophysiological signals were recorded, and self-reported subjectively experienced emotions using a Self-Assessment Manikin (SAM) questionnaire. The obtained results show that it is possible to construct such a highly precise estimator of emotional states.

Tourist loyalty in creative tourism: the role of experience quality, value, satisfaction, and motivation

ABSTRACTThis study examines tourist loyalty in creative tourism comprising of experience quality, perceived value, satisfaction, and motivation as its antecedents and assesses the mediation role of motivation in the development of tourist loyalty. The data was collected from four creative tourism attractions in Bandung, Indonesia. Self-administrated questionnaires were distributed to tourists after they experienced the attraction. In total, 369 useful questionnaires were collected with the hypotheses developed examined using Partial Least Square method. This study discloses that experience quality, perceived value, tourist satisfaction, and tourist motivation are key factors that determine tourist loyalty towards a creative attraction. Likewise, this study highlights that the influence of tourist loyalty determinants (on tourist loyalty), is partly mediated by tourist motivation. Lastly, this study discloses that among the loyalty determinants, experience quality has the biggest effect on tourist loyalty. These results offer a better understanding for both scholars and practitioners of creative attraction businesses on how to develop their clients’ loyalty.