This study provides deeper insight in the link between service quality and customer satisfaction. The traditional assumption of a linear relationship is challenged by exploring asymmetries and dynamics. The simultaneous influence of service quality and customer experience on satisfaction is examined by means of nonlinear structural equation modeling. Results show that functional-utilitarian qua...

In this paper, we present the Gaussian process regression as the predictive model for Quality-of-Service (QoS) attributes in Web service systems. The goal is to predict performance of the execution system expressed as QoS attributes given existing execution system, service repository, and inputs, e.g., streams of requests. In order to evaluate the performance of Gaussian process regression the ...

Customer clustering is used to understand customers’ preferences and behaviors by examining the differences and similarities between customers. Kohonen vector quantization clustering technology is used in this research and is compared with Kmeans clustering. The data set consists of customer records obtained from a mobile telecommunications service provider. The customers are clustered using va...

Web service discovery aims at finding available services that match a given service description. This involves mainly the matchmaking of the functional parameters of the services, whereas non-functional attributes can also be considered and aggregated in the matching score of a candidate service as additional criteria for ranking the results. In this paper, we address the problem of re-ranking ...

Quality web service discovery requires narrowing the search space from an overwhelming set of services down to the most relevant ones, while matching the consumer’s request. Today, the ranking of services only considers static attributes or snapshots of current attribute values, resulting in low-quality search results. To satisfy the user’s need for timely, well-chosen web services, we ought to...

The main goal of the study is development of the classification framework of smart service attributes as a first step in developing methodology of smart services implementation for Enterprise Information Portal (EIP) maintenance. First, we analyze available definitions of the “smart services” concept and concepts related to it: smart services are based on the idea of co-creation of value and re...

E-service evaluation is a complex problem in which many qualitative attributes must be considered. These kinds of attributes make the evaluation process hard and vague. Cost–benefit analyses applied to various areas are usually based on the data under certainty or risk. In case of uncertain, vague, and/or linguistic data, the fuzzy set theory can be used to handle the analysis. In this article,...

The web user is exposed to a vast amount of information services available from different sources. Online news are offered combined with additional relevant information, or service attributes such as a picture, a small text, user’s recommendation etc. We previously investigated the web user’s choice of online news focusing on the tradeoffs between reputation and other service attributes, which ...

The problem of composing services to deliver integrated business solutions has been widely studied in the last years. Besides addressing functional requirements, services compositions should also provide agreed service levels. Our goal is to support model-based analysis of service compositions, with a focus on the assessment of non-functional quality attributes, namely performance and reliabili...

. In order to improve the quality of service co-production, both academics and managers have pointed out the pivotal role of Front line Employees (FLEs) in improving the service experience. However, few studies have simultaneously examined the quality perceptions of each group. Do FLEs perceive service quality in the same way as their customers? If this is the case, service quality itself will ...